AU2017265006A1

AU2017265006A1 - Methods of analysis of polymorphisms and uses thereof

Info

Publication number: AU2017265006A1
Application number: AU2017265006A
Authority: AU
Inventors: Robert Peter Young
Original assignee: Synergenz Bioscience Ltd
Current assignee: Synergenz Bioscience Ltd
Priority date: 2005-05-20
Filing date: 2017-11-21
Publication date: 2018-01-18
Also published as: AU2015205934A1

Abstract

The present invention provides methods for the assessment of diseases that result from the combined or interactive effects of two or more genetic variants, and in particular for diagnosing risk of developing such diseases in subjects using an analysis of genetic polymorphisms. Methods for the derivation of a net score indicative of a subject's risk of developing a disease are provided. 80- M COPD (n=242) 70- ]Resistant (n= 197) 60- P=0.002 0 1 2+ Number of Protective Genes Figure 1 0-700 -4 -3 -2 -1 0 1 2 3 4 Net Genetic Burden (number of Protective-number of Susceptible Genes) Figure 2 Combined scores for protective and susceptibility polymorphisms in aero-pollutant exposed subjects a60 0 3+ 2+ 1+ 0 1- 2 Combined scores Figure 3 Combined score for protective (-1) and susceptible (+1) polymorphisms (n=15) 40 --- Series1 -J -2 -1 0 1 2 3 4+ Score Figure 4 Distribution of SNP score for lung cancer among smokers ru 60 -3 -2 -1 0 1 2 3 4 5 SNP score Figure 5

Description

The present invention provides methods for the assessment of diseases that result from the combined or interactive effects of two or more genetic variants, and in particular for diagnosing risk of developing such diseases in subjects using an analysis of genetic polymorphisms. Methods for the derivation of a net score indicative of a subject’s risk of developing a disease are provided.

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Number of Protective Genes

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Net Genetic Burden (number of Protective-number of Susceptible Genes)

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Combined scores for protective and susceptibility polymorphisms in aero-pollutant exposed subjects

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Combined score for protective (-1) and susceptible (+1) polymorphisms (n=15) ©

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Distribution of SNP score for lung cancer among smokers

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“METHODS OF ANALYSIS OF POLYMORPHISMS AND USES THEREOF”

FIELD OF THE INVENTION

The present invention is concerned with methods for the assessment of diseases that result from the combined or interactive effects of two or more genetic variants, and in particular for diagnosing risk of developing such diseases in subjects using an analysis of genetic polymorphisms.

BACKGROUND OF THE INVENTION

Diseases that result from the combined or interactive effects of two or more genetic variants, with or without environmental factors, are called complex diseases and include cancer, coronary artery disease, diabetes, stroke, and chronic obstructive pulmonary disease (COPD). Although combining non-genetic risk factors to determine a risk level of outcome has been in applied to coronary artery disease, (by combining individual factors such as blood pressure, gender, fasting cholesterol, and smoking status), there are no such methods in combining the effects of multiple genetic factors with non-genetic factors. There is a growing realization that the complex diseases, for which examples are given above, may result from the combined effects of common genetic variants or polymorphisms rather than mutations which are rare (believed to be present in less than 1% of the general population). Moreover, these relatively common polymorphisms may confer either susceptibility and/or protective effects on the development of these diseases. In addition, the likelihood that these polymorphisms are actually expressed (termed penetrance) as a disease or clinical manifestation requires a quantum of environmental exposure before such a genetic tendency can be clinically detected.

There is thus a need for a method for assessing a subject’s risk of developing a disease using genetic (and optionally non-genetic) risk factors.

It is an object of the present invention to go some way towards meeting this need and/or to provide the public with a useful choice.

SUMMARY OF THE INVENTION

The Applicant’s recent studies have identified a number of genetic variants or polymorphisms that confer susceptibility to protection from COPD, occupational COPD

2017265006 21 Nov 2017 (OCOPD), and lung cancer. The biological basis of just how these polymorphisms interact or combine to determine risk remains unclear.

The Applicants have now surprisingly found that an assessment approach which determines a subject’s net score following the balancing of the number of polymorphisms associated with protection from a disease against the number of polymorphisms associated with susceptibility to that disease present in the subject is indicative of that subject’s risk quotient. Furthermore, the applicants have determined that this approach is widely applicable, on a disease-by-disease basis.

It is broadly to this approach to risk assessment that the present invention is directed.

Accordingly, in a first aspect, the present invention provides a method of assessing a subject’s risk of developing a disease which comprises:

analysing a biological sample from said subject for the presence or absence of protective polymorphisms and for the presence or absence of susceptibility polymorphisms, wherein said protective and susceptibility polymorphisms are associated with said disease;

assigning a positive score for each protective polymorphism and a negative score for each susceptibility polymorphism or vice versa;

calculating a net score for said subject, said net score representing the balance between the combined value of the protective polymorphisms and the combined value of the susceptibility polymorphisms present in the subject sample;

wherein a net protective score is predictive of a reduced risk of developing said disease and a net susceptibility score is predictive of an increased risk of developingsaid disease.

The value assigned to each protective polymorphism may be the same or may be different.The value assigned to each susceptibility polymorphism may be the same or may be different, with either each protective polymorphism having a negative value and each susceptibility polymorphism having a positive value, or vice versa. When the disease is a lung disease, the protective polymorphisms analysed may be selected from one or more of the group consisting of:

+760GG or +760CG within the gene encoding superoxide dismutase 3 (SOD3); -1296TT within the promoter of the gene encoding tissue inhibitor of metalloproteinase 3 (TIMP3);

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CC (homozygous P allele) within codon 10 of the gene encoding transforming growth factor beta (TGFB);

2G2G within the promoter of the gene encoding metalloproteinase 1 (MMP1); or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms.

Linkage disequilibrium is a phenomenon in genetics whereby two or more mutations or polymorphisms are in such close genetic proximity that they are coinherited. This means that in genotyping, detection of one polymorphism as present infers the presence of the other. (Reich DE et al; Linkage disequilibrium in the human genome, Nature 2001, 411:199-204.).

Preferably, all polymorphisms of the group are analysed.

Preferably, the susceptibility polymorphisms analysed are selected from one or more of the group consisting of:

-82AA within the promoter of the gene encoding human macrophage elastase 15 (MMP12);

-1562CT or -1562TT within the promoter of the gene encoding metalloproteinase 9 (MMP9);

1237AG or 1237AA (Tt or tt allele genotypes) within the 3’ region of the gene encoding α 1-antitrypsin (alAT); or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms.

Preferably, all polymorphisms of the group are analysed.

In one embodiment each protective polymorphism is assigned a value of -1 and each susceptibility polymorphism is assigned a value of+1.

In another embodiment each protective polymorphism is assigned a value of + 1 and each susceptibility polymorphism is assigned a value of -1.

When the disease is COPD, the protective polymorphisms analysed may be selected from one or more of the group consisting of:

-765 CC or CG in the promoter of the gene encoding cyclooxygenase 2 (COX2); 30 Arg 130 Gin AA in the gene encoding Interleukin-13 (IL-13);

Asp 298 Glu TT in the gene encoding nitric oxide synthase 3 (NOS3);

Lys 420 Thr AA or AC in the gene encoding vitamin binding protein (VDBP);

Glu 416 Asp TT or TG in the gene encoding VDBP;

lie 105 Val AA in the gene encoding glutathione S-transferase (GSTPl);

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MS in the gene encoding α 1-antitrypsin (alAT);

the +489 GG geneotype in the gene encoding Tumour Necrosis factor a (TNFa);

the -308 GG geneotype in the gene encoding TNFa;

the C89Y AA or AG geneotype in the gene encodoing SMAD3;

the 161 GG genotype in the gene encodoing Mannose binding lectin 2 (MBL2);

the -1903 AA genotype in the gene encoding Chymase 1 (CMA1); the Arg 197 Gin AA genotype in the gene encoding N-Acetyl transferase 2 (NAT2);

the His 139 Arg GG genotype in the gene encoding Microsomal epoxide hydrolase (MEH);

the -366 AA or AG genotype in the gene encoding 5 Lipo-oxygenase (ALOX5); the HOM T2437C TT genotype in the gene encoding Heat Shock Protein 70 (HSP 70);

the exon 1 +49 CT or TT genotype in the gene encoding Elafin;

the Gin 27 Glu GG genotype in the gene encoding β2 Adrenergic receptor (ADBR);

the -1607 1G1G or 1G2G genotype in the promoter of the gene encoding Matrix Metalloproteinase 1 (MMP1);

or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms.Preferably, all polymorphisms of the group are analysed.

Arg 16 Gly GG in the gene encoding p2-adrenoreceptor (ADRB2);

105 AA in the gene encoding Interleukin-18 (IL-18);

-133 CC in the promoter of the gene encoding IL-18;

-675 5G5G in the promoter of the gene encoding plasminogen activator inhibitor 1 (PAI-1);

-1055 TT in the promoter of the gene encoding IL-13;

874 TT in the gene encoding interferon gamma (IFNy);

the +489 AA or AG genotype in the gene encoding TNFa;

the -308 AA or AG genotype in the gene encoding TNFa; the C89Y GG genotype in the gene encoding SMAD3;

the E469K GG genotype in the gene encoding Intracellular Adhesion molecule 1 (ICAM1);

2017265006 21 Nov 2017 the Gly 881 Arg GC or CC genotype in the gene encoding Caspase (NOD2);

the -511 GG genotype in the gene encoding 1L1B;

the Tyr 113 His TT genotype in the gene encoding MEH;

the -366 GG genotype in the gene encoding ALOX5;

the HOM T2437C CC or CT genotype in the gene encoding HSP 70;

the +13924 AA genotype in the gene encoding Chloride Channel Calciumactivated 1 (CLCA1);

the -159 CC genotype in the gene encoding Monocyte differentiation antigen CD-14 (CD-14);

or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms.

Preferably, all polymorphisms of the group are analysed .

In one embodiment each protective polymorphism is assigned a value of -1 and each susceptibility polymorphism is assigned a value of + 1.

In one embodiment each protective polymorphism is assigned a value of +1 and each susceptibility polymorphism is assigned a value of -1.

When the disease is OCOPD, the protective polymorphisms analysed may be selected from one or more of the group consisting of:

-765 CC or CG in the promoter of the gene encoding COX2;

-251 AA in the promoter of the gene encoding interleukin-8 (IL-8);

Lys 420 Thr AA in the gene encoding VDBP;

Glu 416 Asp TT or TG in the gene encoding VDBP;

exon 3 T/C RR in the gene encoding microsomal epoxide hydrolase (MEH);

Arg 312 Gin AG or GG in the gene encoding SOD3;

MS or SS in the gene encoding al AT;

Asp 299 Gly AG or GG in the gene encoding toll-like receptor 4 (TLR4);

Gin 27 Glu CC in the gene encoding ADRB2;

-518 AA in the gene encoding IL-11;

Asp 298 Glu TT in the gene encoding NOS3; or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms.

Preferably, all polymorphisms of the group are analysed.

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-765 GG in the promoter of the gene encoding COX2;

105 AA in the gene encoding IL-18;

-133 CC in the promoter of the gene encoding IL-18;

-675 5G5G in the promoter of the gene encoding PAI-1;

Lys 420 Thr CC in the gene encoding VDBP;

Glu 416 Asp GG in the gene encoding VDBP;

He 105 Val GG in the gene encoding GSTP1;

Arg 312 Gin AA in the gene encoding SOD3;

-1055 TT in the promoter of the gene encoding IL-13;

3’ 1237 Tt or tt in the gene encoding otlAT;

-1607 2G2G in the promoter of the gene encoding MMP1; or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms.

Preferably, all polymorphisms of the group are analysed.

When the disease is lung cancer, the protective polymorphisms analysed may be selected from one or more of the group consisting of:

the Asp 298 Glu TT genotype in the gene encoding NOS3; the Arg 312 Gin CG or GG genotype in the gene encoding SOD3; the Asn 357 Ser AG or GG genotype in the gene encoding MMP12; the 105 AC or CC genotype in the gene encoding IL-18;

the -133 CG or GG genotype in the gene encoding IL-18;

the -765 CC or CG genotype in the promoter of the gene encoding COX2; the -221 TT genotype in the gene encoding Mucin SAC (MUC5AC); the intron 1 C/T TT genotype in the gene encoding Arginase 1 (Argl); the Leu252Vai GG genotype in the gene encoding Insulin-like growth factor II receptor (IGF2R);

the -1082 GG genotype in the gene encoding Interleukin 10 (IL-10);

the -251 AA genotype in the gene encoding Interleukin 8 (IL-8);

the Arg 399 Gin AA genotype in the X-ray repair complementing defective in

Chinese hamster 1 (XRCC1) gene;

2017265006 21 Nov 2017 the A870G GG genotype in the gene encoding cyclin D (CCND1); the -751 GG genotype in the promoter of the xeroderma pigmentosum complementation group D (XPD) gene;

the He 462 Val AG or GG genotype in the gene encoding cytochrome P450 1A1 (CYP1A1);

the Ser 326 Cys GG genotype in the gene encoding 8-Oxoguanine DNA glycoiase (OGGI);

the Phe 257 Ser CC genotype in the gene encoding RE VI;

or one or more polymorphisms in linkage disequilibrium with any one or more of these polymorphisms.

Preferably, all polymorphisms of the group are analysed.

the -786 TT genotype in the promoter of the gene encoding NOS3;

the Ala 15 Thr GG genotype in the gene encoding anti-chymotrypsin (ACT);

the 105 AA genotype in the gene encoding IL-18; the -133 CC genotype in the promoter of the gene encoding IL-18; the 874 AA genotype in the gene encoding IFNy; the -765 GG genotype in the promoter of the gene encoding COX2;

the -447 CC or GC genotype in the gene encoding Connective tissue growth factor (CTGF); and the +161 AA or AG genotype in the gene encoding MBL2.

the -511 GG genotype in the gene encoding IL-1B;

the A-670G AA genotype in the gene encoding FAS (Apo-1/CD95);

the Arg 197 Gin GG genotype in the gene encoding N-acetyltransferase 2 (NAT2);

the Ile462 Val AA genotype in the gene encoding CYP1A1;

the 1019 G/C Pst I CC or CG genotype in the gene encoding cytochrome P450

2E1 (CYP2E1);

the C/T Rsa I TT or TC genotype in the gene encoding CYP2E1;

the GSTM null genotype in the gene encoding GSTM; the -1607 2G/2G genotype in the promoter of the gene encoding MMP1; the Gin 185 Glu CC genotype in the gene encoding Nibrin (NBS1); the Asp 148 Glu GG genotype in the gene encoding Apex nuclease (APE1);

2017265006 21 Nov 2017 or one or more polymorphisms in linkage disequilibrium with any one or more of these polymorphisms.

Preferably, all polymorphisms of the group are analysed.

In various embodiments the subject is or has been a smoker.

Preferably, the methods of the invention are performed in conjunction with an analysis of one or more risk factors, including one or more epidemiological risk factors, associated with the risk of developing a lung disease including COPD, emphysema, OCOPD, and lung cancer. Such epidemiological risk factors include but are not limited to smoking or exposure to tobacco smoke, age, sex, and familial history.

In another aspect, the invention provides a method of determining a subject’s risk of developing a disease, said method comprising obtaining the result of one or more analyses of a sample from said subject to determine the presence or absence of protective polymorphisms and the presence or absence of susceptibility polymorphisms, and wherein said protective and susceptibility polymorphisms are associated with said disease;

in a further aspect the present invention provides a method for assessing the risk of a subject developing a disease which comprises determining a net score for said subject in accordance with the methods of the invention described above, in combination with a score based on the presence or absence of one or more epidemiological risk factors,

2017265006 21 Nov 2017 wherein a net protective score is predictive of a reduced risk of developing said disease and a net susceptibility score is predictive of an increased predisposition and/or susceptibility to said disease.

In another aspect, the present invention provides a kit for assessing a subject’s 5 risk of developing a disease, said kit comprising a means of analysing a sample from said subject for the presence or absence of one or more protective polymorphisms and one or more susceptibility polymorphisms as described herein.

In yet a further aspect, the present invention provides a method of prophylactic or therapeutic intervention in relation to a subject having a net susceptibility score for a disease as determined by a method as defined above which includes the steps of communicating to said subject said net susceptibility score, and advising on changes to the subject’s lifestyle that could reduce the risk of developing said disease.

In still a further aspect, the present invention provides a method of treatment of a subject to decrease to the risk of developing a disease through alteration of the net score for said subject as determined by a method as defined above, wherein said method of treatment comprises reversing, genotypically or phenotypically, the presence and/or functional effect of one or more susceptibility polymorphisms associated with said disease; and/or replicating and/or mimicking, genotypically or phenotypically, the presence and/or functional effect of one or more protective polymorphisms associated with said disease.

BRIEF DESCRIPTION OF FIGURES

Figure 1: depicts a graph showing combined frequencies of the presence or absence of selected protective genotypes in the COPD subjects and in resistant smokers.

Figure 2: depicts a graph showing net scores for protective and susceptibility polymorphisms in COPD subjects.

Figure 3: depicts a graph showing net scores for protective and susceptibility polymorphisms in OCOPD subjects.

Figure 4: depicts a graph showing net scores for protective and susceptibility polymorphisms in subjects with lung cancer.

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Figure 5: depicts a graph showing net scores for protective and susceptibility polymorphisms in subjects with lung cancer.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention is directed to methods for the assessment of the genetic risk quotient of a particular subject with respect to a particular disease. The methods rely upon the recognition that for many (if not all) diseases there exist genetic polymorphisms which fall into two categories - namely those indicative of a reduced risk of developing a particular disease (which can be termed “protective polymorphisms” or “protective SNPs”) and those indicative of an increased risk of developing a particular disease (which can be termed “susceptibility polymorphisms” or “susceptibility SNPs”).

As used herein, the phrase “risk of developing [a] disease” means the likelihood that a subject to whom the risk applies will develop the disease, and includes predisposition to, and potential onset of the disease. Accordingly, the phrase increased risk of developing [a] disease” means that a subject having such an increased risk possesses an hereditary inclination or tendency to develop the disease. This does not mean that such a person will actually develop the disease at any time, merely that he or she has a greater likelihood of developing the disease compared to the general population of individuals that either does not possess a polymorphism associated with increased disease risk, or does possess a polymorphism associated with decreased disease risk. Subjects with an increased risk of developing the disease include those with a predisposition to the disease, for example in the case of COPD, a tendency or prediliction regardless of their lung function at the time of assessment, for example, a subject who is genetically inclined to COPD but who has normal lung function, those at potential risk, for example in the case of COPD, subjects with a tendency to mildly reduced lung function who are likely to go on to suffer COPD if they keep smoking, and subjects with potential onset of the disease, for example in the case of COPD, subjects who have a tendency to poor lung function on spirometry etc., consistent with COPD at the time of assessment.

Similarly, the phrase “decreased risk of developing [a] disease” means that a subject having such a decreased risk possesses an hereditary disinclination or reduced tendency to develop the disease. This does not mean that such a person will not develop the disease at any time, merely that he or she has a decreased likelihood of developing

2017265006 21 Nov 2017 the disease compared to the general population of individuals that either does possess one or more polymorphisms associated with increased disease risk, or does not possess a polymorphism associated with decreased disease risk.

It will be understood that in the context of the present invention the term 5 “polymorphisrri’means the occurrence together in the same population at a rate greater than that attributable to random mutation (usually greater than 1%) of two or more alternate forms (such as alleles or genetic markers) of a chromosomal locus that differ in nucleotide sequence or have variable numbers of repeated nucleotide units. See www.ornl.gov/sci/techresources/Human_Genome/publicat/97pr/09gloss.html#p.

Accordingly, the term “polymorphisms” is used herein contemplates genetic variations, including single nucleotide substitutions, insertions and deletions of nucleotides, repetitive sequences (such as microsatellites), and the total or partial absence of genes (eg. null mutations). As used herein, the term “polymorphisms” also includes genotypes and haplotypes. A genotype is the genetic composition at a specific locus or set of loci. A haplotype is a set of closely linked genetic markers present on one chromosome which are not easily separable by recombination, tend to be inherited together, and may be in linkage disequilibrium. A haplotype can be identified by patterns of polymorphisms such as SNPs. Similarly, the term “single nucleotide polymorphism” or “SNP” in the context of the present invention includes single base nucleotide subsitutions and short deletion and insertion polymorphisms.lt will further be understood that the term “disease” is used herein in its widest possible sense, and includes conditions which may be considered disorders and/or illnesses which have a genetic basis or to which the genetic makeup of the subject contributes.

Using case-control studies, the frequencies of several genetic variants (polymorphisms) of candidate genes have been compared in disease sufferers, for example, in chronic obstructive pulmonary disease (COPD) sufferers, in occupational chronic obstructive pulmonary disease (OCOPD) sufferers, and in lung cancer sufferers, and in control subjects not suffering from the relevant disease, for example smokers without lung cancer and with normal lung function. The majority of these candidate genes have confirmed (or likely) functional effects on gene expression or protein function.

In various specific embodiments, the frequencies of polymorphisms between blood donor controls, resistant subjects and those with COPD, the frequencies of polymorphisms between blood donor controls, resistant subjects and those with

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OCOPD, and the frequencies of polymorphisms between blood donor controls, resistant subjects and those with lung cancer, have been compared. This has resulted in both protective and susceptibility polymorphisms being identified for each disease.

The surprising finding by the Applicant relevant to this invention is that a combined analysis of protective and susceptibility polymorphisms discriminatoiy for a given disease yields a result that is indicative of that subject’s risk quotient for that disease. This approach is widely applicable, on a disease-by-disease basis.

The present invention identifies methods of assessing the risk of a subject developing a disease which comprises determining in said subject the presence or absence of protective and susceptibility polymorphisms associated with said disease. A net score for said subject is derived, said score representing the balance between the combined value of the protective polymorphisms present in said subject and the combined value of the susceptibility polymorphisms present in said subject. A net protective score is predictive of a reduced risk of developing said disease, and a net susceptibility score is predictive of an increased risk of developing said disease.

Within each category (protective polymorphisms, susceptibility polymorphisms, respectively) the polymorphisms can each be assigned the same value. For example, in the analyses presented in the Examples herein, each protective polymorphism associated with a given disease is assigned a value of +1, and each susceptibility polymorphism is assigned a value of-1. Alternatively, polymorphisms discriminatory for a disease within the same category can each be assigned a different value to reflect their discriminatory value for said disease. For example, a polymorphism highly discriminatory of risk of developing a disease may be assigned a high weighting, for example a polymorphism with a high Odd’s ratio can be considered highly discriminatoiy of disease, and can be assigned a high weighting.

2017265006 21 Nov 2017 calculating a net score for said subject, said net score representing the balance between the combined value of the protective polymorphisms and the combined value of the susceptibility polymorphisms present in the subject sample;

wherein a net protective score is predictive of a reduced risk of developing said 5 disease and a net susceptibility score is predictive of an increased risk of developingsaid disease.

The subject sample may have already been analysed for the presence or absence of one or more protective or susceptibility polymorphisms, and the method comprises the steps of assigning a positive score for each protective polymorphism and a negative score for each susceptibility polymorphism or vice versa;

In one embodiment described herein in Example 1, 17 susceptibility genetic polymorphisms and 19 protective genetic polymorphisms identified as discriminatory for COPD were analysed using methods of the invention. These analyses can be used to determine the risk quotient of any subject for COPD, and in particular to identify subjects at greater risk of developing lung cancer.

In another embodiment described herein in Example 2, 11 susceptibility genetic polymorphisms and 11 protective genetic polymorphisms identified as discriminatory for OCOPD are analysed using methods of the invention. These analyses can be used to determine the risk quotient of any subject for OCOPD, and in particular to identify subjects at greater risk of developing OCOPD.

In a further embodiment described herein in Example 3,19 susceptibility genetic polymorphisms and 17 protective genetic polymorphisms identified as discriminatory for lung cancer are analysed using methods of the invention. These analyses can be used to determine the risk quotient of any subject for lung cancer, and in particular to identify subjects at greater risk of developing lung cancer.

Susceptibility and protective polymorphisms can readily be identified for other diseases using approaches similar to those described in the Examples, as well as in PCT

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International Application No. PCT/NZ02/00106 (published as WO 02/099134 and incorporated by reference) via which four susceptibility and three protective polymorphisms discriminatory for lung disease were identified.

The one or more polymorphisms can be detected directly or by detection of one 5 or more polymorphisms which are in linkage disequilibrium with said one or more polymorphisms. As discussed above, linkage disequilibrium is a phenomenon in genetics whereby two or more mutations or polymorphisms are in such close genetic proximity that they are co-inherited. This means that in genotyping, detection of one polymorphism as present infers the presence of the other. (Reich DE et al; Linkage disequilibrium in the human genome, Nature 2001,411:199-204.)

Examples of polymorphisms reported to be in linkage disequilibrium are presented herein, and include the interleukin-18 -133 C/G and 105 A/C polymorphisms, and the Vitamin D binding protein Glu 416 Asp and Lys 420 Thr polymorphisms, as shown below.

Gene	SNPs	rs numbers	Alleles in LD	LD between alleles	Phenotype in COPD
Interleukin-18	1L18 -133 C/G	rs360721	C allele	Strong LD	CC susceptible
IL18 105 A/C	rs549908	A allele		AA susceptible
Vitamin D binding protein	VDBP Lys 420 Thr	rs4588	A allele	Strong LD	AA/AC protective
VDBP Glu 416 Asp	rs7041	T allele		TT/TG protective

It will be apparent that polymorphsisms in linkage disequilibrium with one or more other polymorphism associated with increased or decreased risk of developing COPD, emphysema, or both COPD and emphysema will also provide utility as biomarkers for risk of developing COPD, emphysema, or both COPD and emphysema. The data presented herein shows that the frequency for SNPs in linkage disequilibrium is very similar. Accordingly, these genetically linked SNPs can be utilized in combined polymorphism analyses to derive a level of risk comparable to that calculated from the original SNP.

It will therefore be apparent that one or more polymorphisms in linkage disequilibrium with the polymorphisms specified herein can be identified, for example, using public data bases. Examples of such polymorphisms reported to be in linkage disequilibrium with the polymorphisms specified herein are presented herein in Table

21.

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The methods of the invention are primarily reliant on genetic information such as that derived from methods suitable to the detection and identification of single nucleotide polymorphisms (SNPs) associated with the specific disease for which a risk assessment is desired. SNP is a single base change or point mutation resulting in genetic variation between individuals. SNPs occur in the human genome approximately once every 100 to 300 bases, and can occur in coding or non-coding regions. Due to the redundancy of the genetic code, a SNP in the coding region may or may not change the amino acid sequence of a protein product. A SNP in a non-coding region can, for example, alter gene expression by, for example, modifying control regions such as promoters, transcription factor binding sites, processing sites, ribosomal binding sites, and affect gene transcription, processing, and translation.

SNPs can facilitate large-scale association genetics studies, and there has recently been great interest in SNP discovery and detection. SNPs show great promise as markers for a number of phenotypic traits (including latent traits), such as for example, disease propensity and severity, wellness propensity, and drug responsiveness including, for example, susceptibility to adverse drug reactions. Knowledge of the association of a particular SNP with a phenotypic trait, coupled with the knowledge of whether an individual has said particular SNP, can enable the targeting of diagnostic, preventative and therapeutic applications to allow better disease management, to enhance understanding of disease states and to ultimately facilitate the discovery of more effective treatments, such as personalised treatment regimens.

Indeed, a number of databases have been constructed of known SNPs, and for some such SNPs, the biological effect associated with a SNP. For example, the NCBI SNP database “dbSNP” is incorporated into NCBI’s Entrez system and can be queried using the same approach as the other Entrez databases such as PubMed and GenBank. This database has records for over 1.5 million SNPs mapped onto the human genome sequence. Each dbSNP entry includes the sequence context of the polymorphism (i.e., the surrounding sequence), the occurrence frequency of the polymorphism (by population or individual), and the experimental method(s), protocols, and conditions used to assay the variation, and can include information associating a SNP with a particular phenotypic trait.

At least in part because of the potential impact on health and wellness, there has been and continues to be a great deal of effort to develop methods that reliably and rapidly identify SNPs. This is no trivial task, at least in part because of the complexity

2017265006 21 Nov 2017 of human genomic DNA, with a haploid genome of 3 x 10⁹ base pairs, and the associated sensitivity and discriminatory requirements.

Genotyping approaches to detect SNPs well-known in the art include DNA sequencing, methods that require allele specific hybridization of primers or probes, allele specific incorporation of nucleotides to primers bound close to or adjacent to the polymorphisms (often referred to as “single base extension”, or “minisequencing”), allele-specific ligation (joining) of oligonucleotides (ligation chain reaction or ligation padlock probes), allele-specific cleavage of oligonucleotides or PCR products by restriction enzymes (restriction fragment length polymorphisms analysis or RFLP) or chemical or other agents, resolution of allele-dependent differences in electrophoretic or chromatographic mobilities, by structure specific enzymes including invasive structure specific enzymes, or mass spectrometry. Analysis of amino acid variation is also possible where the SNP lies in a coding region and results in an amino acid change.

DNA sequencing allows the direct determination and identification of SNPs.

The benefits in specificity and accuracy are generally outweighed for screening purposes by the difficulties inherent in whole genome, or even targeted subgenome, sequencing.

Mini-sequencing involves allowing a primer to hybridize to the DNA sequence adjacent to the SNP site on the test sample under investigation. The primer is extended by one nucleotide using all four differentially tagged fluorescent dideoxynucleotides (A,C,G, or T), and a DNA polymerase. Only one of the four nucleotides (homozygous case) or two of the four nucleotides (heterozygous case) is incorporated. The base that is incorporated is complementary to the nucleotide at the SNP position.

A number of methods currently used for SNP detection involve site-specific and/or allele-specific hybridisation. These methods are largely reliant on the discriminatory binding of oligonucleotides to target sequences containing the SNP of interest. The techniques of Affymetrix (Santa Clara, Calif.) and Nanogen Inc. (San Diego, Calif.) are particularly well-known, and utilize the fact that DNA duplexes containing single base mismatches are much less stable than duplexes that are perfectly base-paired. The presence of a matched duplex is detected by fluorescence.

The majority of methods to detect or identify SNPs by site-specific hybridisation require target amplification by methods such as PCR to increase sensitivity and specificity (see, for example U.S. Pat. No. 5,679,524, PCT publication WO 98/59066, PCT publication WO 95/12607). US Application 20050059030 (incorporated herein in

2017265006 21 Nov 2017 its entirety) describes a method for detecting a single nucleotide polymorphism in total human DNA without prior amplification or complexity reduction to selectively enrich for the target sequence, and without the aid of any enzymatic reaction. The method utilises a single-step hybridization involving two hybridization events: hybridization of a first portion of the target sequence to a capture probe, and hybridization of a second portion of said target sequence to a detection probe. Both hybridization events happen in the same reaction, and the order in which hybridisation occurs is not critical.

US Application 20050042608 (incorporated herein in its entirety) describes a modification of the method of electrochemical detection of nucleic acid hybridization of

Thorp et al. (U.S. Pat. No. 5,871,918). Briefly, capture probes are designed, each of which has a different SNP base and a sequence of probe bases on each side of the SNP base. The probe bases are complementary to the corresponding target sequence adjacent to the SNP site. Each capture probe is immobilized on a different electrode having a non-conductive outer layer on a conductive working surface of a substrate. The extent of hybridization between each capture probe and the nucleic acid target is detected by detecting the oxidation-reduction reaction at each electrode, utilizing a transition metal complex. These differences in the oxidation rates at the different electrodes are used to determine whether the selected nucleic acid target has a single nucleotide polymorphism at the selected SNP site.

The technique of Lynx Therapeutics (Hayward, Calif.) using MEGATYPE™ technology can genotype very large numbers of SNPs simultaneously from small or large pools of genomic material. This technology uses fluorescently labeled probes and compares the collected genomes of two populations, enabling detection and recovery of DNA fragments spanning SNPs that distinguish the two populations, without requiring prior SNP mapping or knowledge.

A number of other methods for detecting and identifying SNPs exist. These include the use of mass spectrometry, for example, to measure probes that hybridize to the SNP. This technique varies in how rapidly it can be performed, from a few samples per day to a high throughput of 40,000 SNPs per day, using mass code tags. A preferred example is the use of mass spectrometric determination of a nucleic acid sequence which comprises the polymorphisms of the invention, for example, which includes the promoter of the COX2 gene or a complementary sequence. Such mass spectrometric methods are known to those skilled in the art, and the genotyping methods of the invention are amenable to adaptation for the mass spectrometric detection of the

2017265006 21 Nov 2017 polymorphisms of the invention, for example, the COX2 promoter polymorphisms of the invention.

SNPs can also be determined by ligation-bit analysis. This analysis requires two primers that hybridize to a target with a one nucleotide gap between the primers. Each of the four nucleotides is added to a separate reaction mixture containing DNA polymerase, ligase, target DNA and the primers. The polymerase adds a nucleotide to the 3’end of the first primer that is complementary to the SNP, and the ligase then ligates the two adjacent primers together. Upon heating of the sample, if ligation has occurred, the now larger primer will remain hybridized and a signal, for example, fluorescence, can be detected. A further discussion of these methods can be found in U.S. Pat. Nos. 5,919,626; 5,945,283; 5,242,794; and 5,952,174.

US Patent 6,821,733 (incorporated herein in its entirety) describes methods to detect differences in the sequence of two nucleic acid molecules that includes the steps of: contacting two nucleic acids under conditions that allow the formation of a four-way complex and branch migration; contacting the four-way complex with a tracer molecule and a detection molecule under conditions in which the detection molecule is capable of binding the tracer molecule or the four-way complex; and determining binding of the tracer molecule to the detection molecule before and after exposure to the four-way complex. Competition of the four-way complex with the tracer molecule for binding to the detection molecule indicates a difference between the two nucleic acids.

Protein- and proteomics-based approaches are also suitable for polymorphism detection and analysis. Polymorphisms which result in or are associated with variation in expressed proteins can be detected directly by analysing said proteins. This typically requires separation of the various proteins within a sample, by, for example, gel electrophoresis or HPLC, and identification of said proteins or peptides derived therefrom, for example by NMR or protein sequencing such as chemical sequencing or more prevalently mass spectrometry. Proteomic methodologies are well known in the art, and have great potential for automation. For example, integrated systems, such as the ProteomlQ™ system from Proteome Systems, provide high throughput platforms for proteome analysis combining sample preparation, protein separation, image acquisition and analysis, protein processing, mass spectrometry and bioinformatics technologies.

The majority of proteomic methods of protein identification utilise mass spectrometry, including ion trap mass spectrometry, liquid chromatography (LC) and

2017265006 21 Nov 2017

LC/MSn mass spectrometry, gas chromatography (GC) mass spectroscopy, Fourier transform-ion cyclotron resonance-mass spectrometer (FT-MS), MALDI-TOF mass spectrometry, and ESI mass spectrometry, and their derivatives. Mass spectrometric methods are also useful in the determination of post-translational modification of proteins, such as phosphorylation or glycosyiation, and thus have utility in determining polymorphisms that result in or are associated with variation in post-translational modifications of proteins.

Associated technologies are also well known, and include, for example, protein processing devices such as the “Chemical Inkjet Printer” comprising piezoelectric printing technology that allows in situ enzymatic or chemical digestion of protein samples electroblotted from 2-D PAGE gels to membranes by jetting the enzyme or chemical directly onto the selected protein spots. After in-situ digestion and incubation of the proteins, the membrane can be placed directly into the mass spectrometer for peptide analysis.

A large number of methods reliant on the conformational variability of nucleic acids have been developed to detect SNPs.

For example, Single Strand Conformational Polymorphism (SSCP, Orita et al., PNAS 1989 86:2766-2770) is a method reliant on the ability of single-stranded nucleic acids to form secondary structure in solution under certain conditions. The secondary structure depends on the base composition and can be altered by a single nucleotide substitution, causing differences in electrophoretic mobility under nondenaturing conditions. The various polymorphs are typically detected by autoradiography when radioactively labelled, by silver staining of bands, by hybridisation with detectabiy labelled probe fragments or the use of fluorescent PCR primers which are subsequently detected, for example by an automated DNA sequencer.

Modifications of SSCP are well known in the art, and include the use of differing gel running conditions, such as for example differing temperature, or the addition of additives, and different gel matrices. Other variations on SSCP are well known to the skilled artisan, including,RNA-SSCP, restriction endonuclease fingerprinting-SSCP, dideoxy fingerprinting (a hybrid between dideoxy sequencing and SSCP), bi-directional dideoxy fingerprinting (in which the dideoxy termination reaction is performed simultaneously with two opposing primers), and Fluorescent PCR-SSCP (in which PCR products are internally labelled with multiple fluorescent dyes, may be

2017265006 21 Nov 2017 digested with restriction enzymes, followed by SSCP, and analysed on an automated DNA sequencer able to detect the fluorescent dyes).

Other methods which utilise the varying mobility of different nucleic acid structures include Denaturing Gradient Gel Electrophoresis (DGGE), Temperature

Gradient Gel Electrophoresis (TGGE), and Heterodupiex Analysis (HET). Here, variation in the dissociation of double stranded DNA (for example, due to base-pair mismatches) results in a change in electrophoretic mobility. These mobility shifts are used to detect nucleotide variations.

Denaturing High Pressure Liquid Chromatography (HPLC) is yet a further method utilised to detect SNPs, using HPLC methods well-known in the art as an alternative to the separation methods described above (such as gel electophoresis) to detect, for example, homoduplexes and heteroduplexes which elute from the HPLC column at d ifferent rates, thereby enabling detection of mismatch nucleotides and thu s SNPs.

Yet further methods to detect SNPs rely on the differing susceptibility of single stranded and double stranded nucleic acids to cleavage by various agents, including chemical cleavage agents and nucleolytic enzymes. For example, cleavage of mismatches within RNA:DNA heteroduplexes by RNase A, of heteroduplexes by, for example bacteriophage T4 endonuclease YII or T7 endonuclease I, of the 5’ end of the hairpin loops at the junction between single stranded and double stranded DNA by cleavase I, and the modification of mispaired nucleotides within heteroduplexes by chemical agents commonly used in Maxam-Gilbert sequencing chemistry, are all well known in the art.

Further examples include the Protein Translation Test (PTT), used to resolve stop codons generated by variations which lead to a premature termination of translation and to protein products of reduced size, and the use of mismatch binding proteins. Variations are detected by binding of, for example, the MutS protein, a component of Escherichia coli DNA mismatch repair system, or the human hMSH2 and GTBP proteins, to double stranded DNA heteroduplexes containing mismatched bases. DNA duplexes are then incubated with the mismatch binding protein, and variations are detected by mobility shift assay. For example, a simple assay is based on the fact that the binding of the mismatch bind ing protein to the heterodupiex protects the heterodupiex from exonuclease degradation.

2017265006 21 Nov 2017

Those skilled in the art will know that a particular SNP, particularly when it occurs in a regulatory region of a gene such as a promoter, can be associated with altered expression of a gene. Altered expression of a gene can also result when the SNP is located in the coding region of a protein-encoding gene, for example where the SNP is associated with codons of varying usage and thus with tRNAs of differing abundance. Such altered expression can be determined by methods well known in the art, and can thereby be employed to detect such SNPs. Similarly, where a SNP occurs in the coding region of a gene and results in a non-synonomous amino acid substitution, such substitution can result in a change in the function of the gene product. Similarly, in cases where the gene product is an RNA, such SNPs can result in a change of function in the RNA gene product. Any such change in function, for example as assessed in an activity or functionality assay, can be employed to detect such SNPs.

The above methods of detecting and identifying SNPs are amenable to use in the methods of the invention.

In practicing the present invention to assess the risk a particular subject faces with respect to a particular disease, that subject will be assessed to determine the presence or absence of polymorphisms (preferably SNPs) which are either associated with protection from the disease or susceptibility to the disease.

In order to detect and identify SNPs in accordance with the invention, a sample containing material to be tested is obtained from the subject. The sample can be any sample potentially containing the target SNPs (or target polypeptides, as the case may be) and obtained from any bodily fluid (blood, urine, saliva, etc) biopsies or other tissue preparations.

DNA or RNA can be isolated from the sample according to any of a number of methods well known in the art. For example, methods of purification of nucleic acids are described in Tijssen; Laboratory Techniques in Biochemistry and Molecular Biology: Hybridization with nucleic acid probes Part 1: Theory and Nucleic acid preparation, Elsevier, New York, N.Y. 1993, as well as in Maniatis, T., Fritsch, E. F. and Sambrook, J., Molecular Cloning Manual 1989.

Upon detection of the presence or absence of the polymorphisms tested for, the critical step is to determine a net susceptibility score for the subject. This score will represent the balance between the combined value of the protective polymorphisms present and the total value of the susceptibility polymorphisms present, with a net protective score (i.e., a greater weight of protective polymorphisms present than

2017265006 21 Nov 2017 susceptibility polymorphisms) being predictive of a reduced risk of developing the disease in question. The reverse is true where there is a net susceptibility score. To calculate where the balance lies, the individual polymorphisms are assigned a value. In the simplest embodiment, each polymorphisms within a category (i.e. protective or susceptibility) is assigned an equal value, with each protective polymorphism being -1 and each susceptibility polymorphism being +1 (or vice versa). It is however contemplated that the values assigned to individual polymorphisms within a category can differ, with some polymorphisms being assigned a value that reflects their predictive or discriminatory value. For example, one particularly strong protective polymorphism may have a value of -2, whereas another more weakly protective polymorphism may have a value of -0.75.

The net score, and the associated predictive outcome in terms of the risk of the subject developing a particular disease, can be represented in a number of ways. One example is as a graph as more particularly exemplified herein.

Another example is a simple numerical score (eg +2 to represent a subject with a net susceptibility score or -2 to represent a subject with a net protective score). In each case, the result is communicated to the subject with an explanation of what that result means to that subject. Preferably, advice on ways the subject may change their lifestyle so as to reduce the risk of developing the disease is also communicated to the subject.

It will be appreciated that the methods of the invention can be performed in conjunction with an analysis of other risk factors known to be associated with a disease, such as COPD, emphysema, OCOPD, or lung cancer. Such risk factors include epidemiological risk factors associated with an increased risk of developing the disease. Such risk factors include, but are not limited to smoking and/or exposure to tobacco smoke, age, sex and familial history. These risk factors can be used to augment an analysis of one or more polymorphisms as herein described when assessing a subject’s risk of developing a disease such as COPD, emphysema, OCOPD, or lung cancer.

The predictive methods of the invention allow a number of therapeutic interventions and/or treatment regimens to be assessed for suitability and implemented for a given subject, depending upon the disease and the overall risk quotient. The simplest of these can be the provision to a subject with a net susceptibility score of motivation to implement a lifestyle change, for example, in the case of OCOPD, to reduce exposure to aero-pollutants, for example, by an occupational change or by the use of safety equipment in the work place. Similarly where the subject is a current

2017265006 21 Nov 2017 smoker, the methods of the invention can provide motivation to quit smoking. In this latter ease, a ‘quit smoking’ program can be followed, which may include the use of anti-smoking medicaments (such as nicotine patches and the like) as well as antiaddiction medicaments.

Other therapeutic interventions can involve altering the balance between protective and susceptibility polymorphisms towards a protective state (such as by neutralizing or reversing a susceptibility polymorphism). The manner of therapeutic intervention or treatment will be predicated by the nature of the polymorphism(s) and the biological effect of said polymorphism(s). For example, where a susceptibility polymorphism is associated with a change in the expression of a gene, intervention or treatment is preferably directed to the restoration of normal expression of said gene, by, for example, administration of an agent capable of modulating the expression of said gene. Where a polymorphism, such as a SNP allele or genotype, is associated with decreased expression of a gene, therapy can involve administration of an agent capable of increasing the expression of said gene, and conversely, where a polymorphism is associated with increased expression of a gene, therapy can involve administration of an agent capable of decreasing the expression of said gene. Methods useful for the modulation of gene expression are well known in the art. For example, in situations were a polymorphism is associated with upregulated expression of a gene, therapy utilising, for example, RNAi or antisense methodologies can be implemented to decrease the abundance of mRNA and so decrease the expression of said gene. Alternatively, therapy can involve methods directed to, for example, modulating the activity of the product of said gene, thereby compensating for the abnormal expression of said gene.

Where a susceptibility polymorphism is associated with decreased gene product function or decreased levels of expression of a gene product, therapeutic intervention or treatment can involve augmenting or replacing of said function, or supplementing the amount of gene product within the subject for example, by administration of said gene product or a functional analogue thereof. For example, where a polymorphism is associated with decreased enzyme function, therapy can involve administration of active enzyme or an enzyme analogue to the subject. Similarly, where a polymorphism is associated with increased gene product function, therapeutic intervention or treatment can involve reduction of said function, for example, by administration of an inhibitor of said gene product or an agent capable of decreasing the level of said gene product in the

2017265006 21 Nov 2017 subject. For example, where a polymorphism is associated with increased enzyme function, therapy can involve administration of an enzyme inhibitor to the subject.

Likewise, when a protective polymorphism is associated with upregulation of a particular gene or expression of an enzyme or other protein, therapies can be directed to mimic such upregulation or expression in an individual lacking the resistive genotype, and/or delivery of such enzyme or other protein to such individual Further, when a protective polymorphism is associated with downregulation of a particular gene, or with diminished or eliminated expression of an enzyme or other protein, desirable therapies can be directed to mimicking such conditions in an individual that lacks the protective genotype.

EXAMPLES

The invention will now be described in more detail, with reference to nonlimiting examples.

EXAMPLE 1. CASE ASSOCIATION STUDY - COPD

METHODS

Subject recruitment

Subjects of European descent who had smoked a minimum of fifteen pack years and diagnosed by a physician with chronic obstructive pulmonary disease (COPD) were recruited. Subjects met the following criteria: were over 50 years old and had developed symptoms of breathlessness after 40 years of age, had a Forced expiratory volume in one second (FEV1) as a percentage of predicted <70% and a FEV1/FVC ratio (Forced expiratory volume in one second/Forced vital capacity) of < 79% (measured using American Thoracic Society criteria). Two hundred and ninety-four subjects were recruited, of these 58% were male, the mean FEV1/FVC (± 95%confidence limits) was

51% (49-53), mean FFV1 as a percentage of predicted was 43 (41-45). Mean age, cigarettes per day and pack year history was 65 yrs (64-66), 24 cigarettes/day (22-25) and 50 pack years (41-55) respectively. Two hundred and seventeen European subjects who had smoked a minimum of twenty pa ck years and who had never suffered breathlessness and had not been diagnosed with an obstructive lung disease in the past, in particular childhood asthma or chronic obstructive lung disease, were also studied. This control group was recruited through clubs for the elderly and consisted of 63% male, the mean FFV1/FVC ( 95%CI) was 82% (81-83), mean FFV1 as a percentage of

2017265006 21 Nov 2017 predicted was 96 (95-97). Mean age, cigarettes per day and pack year history was 59 yrs (57-61), 24 cigarettes/day (22-26) and 42 pack years (39-45) respectively. Using a PCR based method [1, incorporated herein in its entirety by reference], all subjects were genotyped for the α 1-antitrypsin mutations (S and Z alleles) and those with the ZZ allele were excluded. The COPD and resistant smoker cohorts were matched for subjects with the MZ genotype (5% in each cohort). 190 European blood donors (smoking status unknown) were recruited consecutively through local blood donor services. Sixty-three percent were men and their mean age was 50 years. On regression analysis, the age difference and pack years difference observed between COPD sufferers and resistant smokers was found not to determine FEV or COPD.

This study shows that polymorphisms found in greater frequency in COPD patients compared to controls (and/or resistant smokers) can reflect an increased susceptibility to the development of impaired lung function and COPD. Similarly, polymorphisms found in greater frequency in resistant smokers compared to susceptible smokers (COPD patients and/or controls) can reflect a protective role.

Summary of characteristics for the COPD, resistant smoker and healthy blood donors

Parameter	COPD	Resistant smokers	Differences
Median (1QR)	N-294	N=217
% male	58%	63%	ns
Age (yrs)	65 (64-66 )	59 (57-61)	P<0.05
Pack years	50 (46-53 )	42 (39-45)	P<0.05
Cigarettes/day	24 (22-25)	24(22-26)	ns
FEV1 (L)	1.6(0.7-2.5)	2.9(2.8-3.0)	P<0.05
FE Pl % predict	43 (41-45 )	96% (95-97)	P<0.05
FEV1/FVC	51 (49-53 )	82 (81-83)	P<0.05

Means and 95% confidence limits

Cyclo-oxygenase 2 (COX2) -765 G/C promoter polymorphism and o.l-antitrypsin genotyping

Genomic DNA was extracted from whole blood samples [2, incorporated herein in its entirety by reference]. The Cyclo-oxygenase 2 -765 polymorphism was

2017265006 21 Nov 2017 determined by minor modifications of a previously published method [3, incorporated herein in its entirety by reference]. The PCR reaction was carried out in a total volume of 25ul and contained 20 ng genomic DNA, SOOpmol forward and reverse primers, 0.2mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KC1, 1.0 mM MgCh and 1 unit of polymerase (Life Technologies). Cycling times were incubations for 3 min at 95°C followed by 33 cycles of 50s at 94°C, 60s at 66°C and 60s at 72°C. A final elongation of 10 min at 72°C then followed. 4ul of PCR products were visualised by ultraviolet transillumination of a 3% agarose gel stained with ethidium bromide. An aliquot, of 3ul of amplification product was digested for 1 hr with 4 units of Acil (Roche Diagnostics,

New Zealand) at 37°C. Digested products were separated on a 2.5% agarose gel run for 2.0 hours at 80 mV with TBE buffer. The products were visualised against a 123bp ladder using ultraviolet transillumination after ethidium bromide staining. Using a PCR based method referenced above [1], all COPD and resistant smoker subjects were genotyped for the al-antitrypsin S and Z alleles.

Other polymorphism genotyping

Genomic DNA was extracted from whole blood samples [2], Purified genomic

DNA was aliquoted (10 ng/ul concentration) into 96 well plates and genotyped on a Sequenom™ system (Sequenom™ Autoflex Mass Spectrometer and Samsung 24 pin nanodispenser) using the following sequences, amplification conditions and methods.

The following conditions were used for the PCR multiplex reaction: final concentrations were for lOxBuffer 15 mM MgCk 1.25x, 25mM MgCb 1.625mM, dNTP mix 25 mM 500uM, primers 4 uM lOOnM, Taq polymerase (Qiagen hot start) 0.15U/reaction, Genomic DNA 10 ng/ul. Cycling times were 95°C for 15 min, (5°C for 15 s, 56°C 30s, 72°C 30s for 45 cycles with a prolonged extension time of 3min to finish. Shrimp alkaline phosphotase (SAP) treatment was used (2ul to 5ul per PCR reaction) incubated at 35°C for 30 min and extension reaction (add 2ul to 7ul after SAP treatment) with the following volumes per reaction of: water, 0.76ul; hME lOx termination buffer, 0.2ul; hME primer (lOuM), lul; MassEXTEND enzyme, 0.04ul.

2017265006 21 Nov 2017

IL18- A105C	IL18- C- 133G	IFNG - A874T	ADRB2- Arg16Gly	IL13- Arg130Gln	NOS3- 298	PAI1 G- 675G	GSTP1 - 105	IL13 C- 1055T	Vitamin DBP-416	Vitamin DBP-420	\| SNP ID
ACT	> o -I	CGT	> o -I	> o -I	> a -I	> o -I	> o -I	> O -I	> o -I	> a -I	\| TERM
§ CO	£ 05	g cn	co	g co	g CO	g ΓΌ	g ro	g ro	g	g	\| WELL
ACGTTGGATGGGTCAATGAAGAGAACTTGG[SEQ.ID.N0.21]	ACGTTGGATGGGGTATTCATAAGCTGAAACfSEQ.ID.NO.19l	ACGTTGG ATGCAGACATTCACAATTG ATTT[SEQ. ID. N 0.17]	ACGTTGGATGGAACGGCAGCGCCTTCTTG[SEQ.ID.NO.15]	ACGTTGGATGGTTTTCCAGCTTGCATGTCCfSEQ.ID.NO.13]	ACGTTGG ATGACAGCTCTGCATTCAGCACGfS EQ. ID. N 0.11 ]	ACGTTGGATGCACAGAGAGAGTCTGGACAC[SEQ.ID.NO.9]	ACGTTGGATGTGGTGGACATGGTGAATGAC[SEQ.ID.N0.7]	ACGTTGGATGCATGTCGCCTTTTCCTGCTC[SEQ.ID.N0.5]	ACGTTGGATGTTTTTCAGACTGGCAGAGCGfSEQ. ID. NO. 3]	ACGTTGGATGGCTTGTTAACCAGCTTTGCCfSEQ.ID.NO.1]	\| 2nd-PCRP
ACGTTGGATG AATGTTTATTGTAGAAAAC C[S EQ. ID. NO .22]	ACGTTGGATGCCTTCAAGTTCAGTGGTCAGfSEQ.ID.NO.20]	ACGTTGGATGGATAGTTCCAAACATGTGCG[SEQ.ID.NO.18]	ACGTTGGATGACTTGGCAATGGCTGTGATG[SEQ.ID.NO.16]	ACGTTGGATGCAATAGTCAGGTCCTGTCTC[SEQ.ID.NO.14]	ACGTTGGATGAGTCAATCCCTTTGGTGCTC[SEQ.ID.NO.12]	ACGTTGGATGCTCTTGGTCTTTCCCTCATCfSEQ.ID.NO.10]	ACGTTGGATGTGGTGCAGATGCTCACATAG[SEQ.ID.N0.8]	ACGTTGGATGCAACACCCAACAGGCAAATG[SEQ.ID.N0.6]	ACGTTGGATGGCTTGTTAACCAGCTTTGCCfSEQ.ID.NO.4]	ACGTTGGATGTTTTTCAGACTGGCAGAGCG[SEQ.ID.N0.2]	\| 1st-PCRP \|

Sequenom conditions for the polymorphisms genotyping 2017265006 21 Nov 2017

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K	—k K	KJ	00 A		00 05	o CD	o	KJ	\| 66 \|	\| 66 \|	\| AMP LEN
I 67.2	I 93.5	I 75.3	I 88.2	\| 99.3	\| 98.1	\| 97.9	\| 99.4	I 97.5	I 99.7	I 99.7	\| UP CONF \|
I 74.3	I 74.3	I 81.2	I 65	I 65	I 65	I 80	I 80	I 80	\| 99.7	\| 99.7	\| MP CONF \|
\| 48.9	\| 41.8	\| 45.6	\| 65.1	I 55.1	\| 61.2	\| 59.3	\| 49.9	I 48.2	\| 45.5	I 46.2	\| Tm(NN)
o	I 46.7	\| 27.3	\| 58.3	I 47.6	\| 63.2	\| 66.7	\| 52.9	I 60	\| 33.3	\| 53.3	\| PcGC
	Γ					ΕΏ		r~	S	I ml	\| PWARN \|
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2017265006 21 Nov 2017

IL18- A105C	IL18- C- 133G	IFNG - A874T	ADRB2- Arg16Gly	IL13- Arg130Gln	NOS3- 298	PAI1 G- 675G	GSTP1 - 105	IL13 C- 1055T	Vitamin DBP-416	Vitamin DBP-420	\| SNP ID
TCAAGCTTGCCAAAGTAATCT[SEQ.ID.N0.54]	AGCTGAAACTTCTGGCfSEQ.ID.NO.52]	TCTTAC AAC AC AAAATC AAATCTfS EQ. ID. N 0.5 0]	AGCGCCTTCTTGCTGGCACCCAATAfSEQ.ID.NO.48]	AGAAACTTTTTCGCGAGGGACAfSEQ.ID.NO.46]	TGCTGCAGGCCCCAGATGAT[SEQ.ID.N0.44]	GAGTCTGGACACGTGGGGA[SEQ.ID.N0.42]	ACCTCCGCTGCAAATACA[SEQ.ID.NO.40]	TCCTGCTCTTCCCTCA[SEQ.ID.N0.38]	AAAAGCAAAATTGCCTGAT[SEQ.ID.N0.36]	AGCTTTGCCAGTTCCTfS EQ. ID. NO. 34]	\| EXT1 SEQ
O	0	>	0	0	0	0	0	O	0	O	\| EXT2 CALL \|
7040.6	5218.4	7225.8	8220.3	7416.8	6416.2	6247.1	5716.7	5023.3	6456.2	5136.4	m X —I ro 2 > ω ω
TCAAGCTTGCCAAAGTAATCGGA [SEQ.ID.NO.55]	AGCTGAAACTTCTGGGA fSEQ.ID.NO.53]	TCTTACAACACAAAATCAAATCAC [SEQ.ID.NO.51]	AGCGCCTTCTTGCTGGCACCCAATGGA fSEQ.ID.NO.49]	AGAAACTTTTTCGCGAGGGACGGT [SEQ.ID.NO.47]	TGCTGCAGGCCCCAGATGAGC [SEQ.ID.NO.45]	GAGTCTGGACACGTGGGGGA [SEQ.ID.NO.43]	ACCTCCGCTGCAAATACGT [SEQ.ID.NO.41]	TCCTGCTCTTCCCTCGT [SEQ.ID.NO.39]	AAAAGCAAAATTGCCTGAGGC [SEQ.ID.NO.37]	AGCTTTGCCAGTTCCGT [SEQ.ID.NO.35]	I EXT2 SEQ \|
6414.2	4921.2	6952.6	7593.9	6799.4	6143	5949.9	5428.5	4735.1	5853.9	4848.2	\| IstPAUSE \|

Sequenom conditions for the polymorphisms genotyping -4

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2017265006 21 Nov 2017

Sequenom conditions for the polymorphisms genotyping-8

-33 2017265006 21 Nov 2017 resistant smokers.

RESULTS

Frequencies of individual polymorphisms are as follows:

Table 1. Polymorphism allele and genotype frequencies in the COPD patients and

Cyclo-oxygenase 2 -765 G/C
Frequency	Allele*	Genotype
	C	G	CC	CG	GG
Controls n=94 (%)	27 (14%)	161 (86%)	3 (3%)	21 (22%)	70 (75%)
COPD n=202 (%)	59(15%)	345 (85%)	6 (3%)	47 (23%)	149 (74%)
Resistant n=172 (%)	85² (25%)	259 (75%)	14¹ (8%)	57 (33%)	101 (59%)

Beta2-adrenoreceptor Arg 16 Gly
Frequency	Allele*		Genotype
	A	G	AA	AG	GG
Controls n=182 (%)	152 (42%)	212 (58%)	26 (14%)	100 (55%)	56 (31%)
COPD n=236 (%)	164 (34%)	308 (66%)	34 (14%)	96 (41%)	106³ (45%)
Resistant n=190 (%)	135 (36%)	245 (64%)	34(18%)	67 (35%)	89⁴ (47%)

Interleukin 18 105 A/C
Frequency	Allele*		Genotype
	C	A	CC	AC	AA
Controls n=184 (%)	118 (32%)	250 (68%)	22(12%)	74 (40%)	88 (48%)
COPD n=240 (%)	122 (25%)	3 77⁶ (75%)	21 (9%)	80 (33%)	139⁵·⁷ (58%)
Resistant n=196 (%)	113 (29%)	277 (71%)	16 (8%)	81 (41%)	99 (50%)

Interleukin 18 -133 C/G
Frequency	Allele*		Genotype
	G	C	GO	GC	CC
Contois n=187 /%)	120 (32%)	254 (68%)	23 (12%)	74 (40%)	90 (48%)
COPDn=238	123 (26%)	353’ (74%)	21 (9%)	81 (34%)	136^s (57%)
Resistant n=195 (%)	113 (29%)	277 (71%)	16 (8%)	81 (42%)	98 (50%)

Plasminogen activator inhibitor 1 -675 4G/5G
Frequency	Allele*		Genotype

-342017265006 21 Nov 2017

	5G	4G	5G5G	5G4G	4G4G
Controls n=186 (%)	158 (42%)	214 (58%)	31 (17%)	96 (52%)	59 (32%)
COPD n=237 (%)	219¹² (46%)	255 (54%)	54¹⁰'¹¹ (23%)	111 (47%)	72 (30%)
Resistant n=194 (%)	152 (39%)	236 (61%)	31 (16%)	90 (46%)	73¹⁰’¹¹ (38%)

Nitric oxide synthase 3 Frequency	Asp 298 Glu (T/G) Allele*		Genotype
	T	G	TT	TG	GG
Controls n=183 (%)	108 (30%)	258 (70%)	13 (7%)	82 (45%)	88 (48%)
COPD n=238 (%)	159 (42%)	317(58%)	25(10%)	109 (47%)	104 (43%)
Resistant n=194 (%)	136 (35%)	252 (65%)	28¹³(15%)	80 (41%)	86 (44%)

Vitamin D Binding Pro Frequency	tein Lys 420 Thr (A/C) Allele*		Genotype
	A	C	AA	AC	CC
Controls n=189 (%)	113 (30%)	265 (70%)	17 (9%)	79 (42%)	93 (49%)
COPD n=250 (%)	147 (29%)	353 (71%)	24 (10%)	99 (40%)	127 (50%)
Resistant n=195 (%)	140¹⁵ (36%)	250 (64%)	25¹⁴ (13%)	90¹⁴ (46%)	80 (41%)

Vitamin D Binding Pro Frequency	tein Glu 416 Asp (T/G) Allele*		Genotype
	T	G	TT	TG	GG
Controls n=188 (%)	162 (43%)	214 (57%)	35(19%)	92 (49%)	61 (32%)
COPD n=240 (%)	230 (48%)	250 (52%)	57 (24%)	116 (48%)	67 (28%)
Resistant n= 197 (%)	193¹⁷ (49%)	201 (51%)	43¹⁶ (22%)	107¹⁶ (54%)	47 (24%)

Glutathione S Transfer Frequency	ase Pl He 105 Val (A/G) Allele*		Genotype
	A	G	AA	AG	GG
Contois n=185 (%)	232 (63%)	138 (37%)	70 (38%)	92 (50%)	23 (12%)
COPD n=238 (%)	310 (65%)	166 (35%)	96 (40%)	118 (50%)	24 (10%)
Resistant n=194 (%)	269¹⁹ (69%)	119(31%)	91¹⁸ (47%)	87 (45%)	16(8%)

Interferon-gamma 874 Frequency	A/T Allele*		Genotype

-35 2017265006 21 Nov 2017

	A	T	AA	AT	TT
Controls n=186 (%)	183 (49%)	189(51%)	37 (20%)	109 (58%)	40 (22%)
COPD n=235 (%)	244 (52%)	226 (48%)	64²⁰ (27%)	116 (49%)	55 (24%)
Resistant n=193 (%)	208 (54%)	178 (46%)	51 (27%)	106 (55%)	36 (18%)

interleukin-13 Arg 130 Frequency	Gin (G/A) Allele*	Genotype
	A	G	AA	AG	GG
Controls n=184 (%)	67(18%)	301 (82%)	3 (2%)	61 (33%)	120 (65%)
COPD n=237 (%)	86(18%)	388 (82%)	8 (3%)	70 (30%)	159 (67%)
Resistant n=194 (%)	74(19%)	314(81%)	9²¹ (5%)	56 (28%)	129 (67%)

lnterleukin-13 -1055 Cl Frequency	T Allele*	Genotype
	T	C	TT	TC	CC
Controls n=182 (%)	65 (18%)	299 (82%)	5 (3%)	55 (30%)	122 (67%)
COPD n=234 (%)	94 (20%)	374 (80%)	8²² (4%)	78 (33%)	148 (63%)
Resistant n=192 (%)	72(19%)	312(81%)	2 (1%)	68 (35%)	122 (64%)

αΐ-antitrypsin S Frequency	Allele*	Genotype
	M	S	MM	MS	SS
COPD n=202 (%)	391 (97%)	13 (3%)	189 (94%)	13 (6%)	0 (0%)
Resistant n=189 (%)	350 (93%)	28 (7%)	162 (85%)	26²³ (14%)	I²³ (1%)

* number of chromosomes (2n)Genotype

1. Genotype. CC/CG vs GG for resistant vs COPD, Odds ratio (OR) =1.98, 95% confidence limits 1.3-3.1, χ² (Yates corrected)= 8,82, p=0.003, CC/CG = protective for COPD

2. Allele. C vs G for resistant vs COPD, Odds ratio (OR) =1.92, 95% confidence limits 1. 3-2.8, χ² (Yates corrected)= 11.56, p<0.001, C = protective for COPD

3. Genotype. GG vs AG/AA for COPD vs controls, Odds ratio (OR) =1.83, 95% confidence limits 1.2-2.8, χ2 (Yates corrected)= 8.1, p=0.004, GG = susceptible to COPD (depending on the presence of other snps)

4. Genotype. GG vs AG/AA for resistant vs controls. Odds ratio (OR) =1.98, 95% confidence limits 1.3-3.1,/2 (Yates corrected)=9.43, p=0.002

GG = resistance (depending on the presence of other snps)

2017265006 21 Nov 2017

-365. Genotype. AA vs AC/CC for COPD vs controls, Odds ratio (OR) =1.50, 95% confidence limits 1.0-2.3, χ2 (Yates uncorrected)= 4.26, p=0.04, AA = susceptible to COPD

6. Allele. A vs C for COPD vs control, Odds ratio (OR) =1.46, 95% confidence limits 1.1-2.0, χ2 (Yates corrected^

5.76, p=0.02

7. Genotype. AA vs AC/CC for COPD vs resistant, Odds ratio (OR) =1.35, 95% confidence limits 0.9-2.0, χ2 (Yates uncorrected)=2.39, p=0.12 (trend), AA = susceptible to COPD

8. Genotype. CC vs CG/GG for COPD vs controls. Odds ratio (OR) =1.44, 95% confidence limits 1.0-2.2, χ2 (Yates corrected)= 3.4. p=0.06, CC = susceptible to COPD

9. Allele. C vs G for COPD vs control, Odds ratio (OR) =1.36, 95% confidence limits 1.0-1.9, χ2 (Yates corrected)=

53.7, p=0.05, C = susceptible to COPD

10. Genotype. 5G5G vs rest for COPD vs resistant, Odds ratio (OR) =1.55, 95% confidence limits 0.9-2.6, χ2 (Yates uncorrected)= 3.12, p=0.08, 5G5G = susceptible to COPD

11. Genotype. 5G5G vs rest for COPD vs control, Odds ratio (OR) =1.48, 95% confidence limits 0.9-2.5, χ2 (Yates uncorrected)= 2.43, p=0.12, 5G5G = susceptible to COPD

12. Allele. 5G vs 4G for COPD vs resistant. Odds ratio (OR) =1.33, 95% confidence limits 1.0-1.8, χ2 (Yates corrected)=4.02, p=0.05, 5G = susceptible to COPD

13. Genotype. TT vs TG/GG for resistant vs controls, Odds ratio (OR) =2.2, 95% confidence limits 1.0-4.7, χ2 (Yates corrected)= 4.49, p=0.03, TT genotype = protective for COPD

14. Genotype. AA/AC vs CC for resistant vs COPD, Odds ratio (OR) =1.39, 95% confidence limits 0.9-2.1, χ2 (Yates uncorrected)= 2.59. p=0.10, AA/AC genotype = protective for COPD

15. Allele. A vs C for resistant vs COPD, Odds ratio (OR) =1.34, 95% confidence limits 1.0-1.8, χ2 (Yates corrected)=3.94, p=0.05, A allele = protective for COPD

16. Genotype. TT/TG vs GG for resistant vs controls. Odds ratio (OR) =1.53, 95% confidence limits 1.0-2.5, χ2 (Yates uncorrected)= 3.52. p=0.06, TT/TG genotype = protective for COPD

17. Allele. T vs G for resistant vs control. Odds ratio (OR) =1.27, 95% confidence limits 1.0-1.7, χ2 (Yates corrected)=2.69, p=0.1, T allele = protective for COPD

18. Genotype. AA vs AG/GG for resistant vs controls, Odds ratio (OR) =1.45, 95% confidence limits 0.9-2.2, /2 (Yates uncorrected)= 3.19, p=0.07, AA genotype = protective for COPD

19. Allele. A vs G lor resistant vs control, Odds ratio (OR) =1.34, 95% confidence limits 1.0-1.8, χ2 (Yates uncorrected)=3.71, p=0.05.

A allele = protective for COPD

2017265006 21 Nov 2017

-3720. Genotype. AA vs AT/TT for COPD vs controls, Odds ratio (OR) =1.51, 95% confidence limits 0.9-2.5, χ2 (Yates uncorrected)= 3.07, p=0.08, AA genotype = susceptible to COPD

21. Genotype. AA vs AG/GG for resistant vs controls. Odds ratio (OR) =2.94, 95% confidence limits 0.7-14.0, χ2 (Yates uncorrected)= 2.78, p=0.09, AA genotype = protective for COPD

22. Genotype. TT vs TC/CC for COPD vs resistant, Odds ratio (OR) =6.03. 95% confidence limits 1.1-42, χ2 (Yates corrected)= 4.9, p=0.03, TT= susceptible to COPD

23. Genotype. MS/SS vs MM for Resistant vs COPD, Odds ratio (OR) =2.42, 95% confidence limits 1.2-5.1, χ2 (Yates corrected)= 5.7, p=0.01, S= protective for COPD

Tumour Necrosis Factor a +489 G/A polymorphism allele and genotype frequency in the COPD patients and resistant smokers.

F requency	Allele*	Genotype
	A	G	AA	AG	GG
COPD n=242 (%)	54(11%)	430 (89%)	5 (2%)	44(18%)	193 (80%)
Resistant n=187 (%)	27 (7%)	347 (93%)	1 (1%)	25 (13%)	161 (86%)

* number of chromosomes (2n)

1. Genotype. AA/AG vs GG for COPD vs resistant, Odds ratio (OR) =-1.57, 95% confidence limits 0.92.7, χ² (Yales corrected)= 2.52, p=0.11,

AA/AG ^susceptible (GG=protective)

2. Allele. A vs G for COPD vs resistant, Odds ratio (OR) =1.61, 95% confidence limits 1. 0-2.7, χ²(Yates corrected)^ 3.38, p=0.07,

A =susceptible

Tumour Necrosis Factor a -308 G/A polymorphism allele and genotype frequency in the COPD patients and resistant smokers.

Frequency	Allele*	Genotype
	A	G	AA	AG	GG
COPD n=242 (%)	90 (19%)	394 (81%)	6 (2%)	78 (32%)	158 (65%)
Resistant n=190 (%)	58(15%)	322 (85%)	3 (2%)	52 (27%)	135 (71%)

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1. Genotype. GG vs AG/AA for COPD vs resistant, Odds ratio (OR) =0.77, 95% confidence limits 0.51.2, χ² (Yates uncorrected)= 1.62, p=0.20,

2017265006 21 Nov 2017

-38GG=protective (AA/AG ^susceptible) trend

2. Allele. A vs G for COPD vs resistant, Odds ratio (OR) =1.3, 95% confidence limits 0.9-1.9, χ²(Yates uncorrected)= 1.7, p=0.20,

A =susceptible trend

SMAD3 C89Y polymorphism allele and genotype frequency in the COPD patients and resistant smokers.

Frequency	Allele*	Genotype
	A	G	AA	AG	GG
COPD n=250 (%)	2(1%)	498 (99%)	0 (0%)	2 (1%)	248 (99%)
Resistant n=196 (%)	6 (2%)	386 (98%)	0 (0%)	6 (3%)	190 (97%)

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1. Genotype. AA/AG vs GG for COPD vs resistant, Odds ratio (OR) =0.26, 95% confidence limits 0.04-1.4, χ² (Yates uncorrected)= 3.19, p=0.07,

AA/AG =protective (GG susceptible)

Intracellular Adhesion molecule 1 (ICAM1) A/G E469K (rs5498) polymorphism allele and genotype frequency in COPD patients and resistant smokers.

Frequency	Allele*	Genotype
	A	G	AA	AG	GG
COPD n=242 (%)	259 (54%)	225 (46%)	73 (30%)	113 (47%)	56 (23%)
Resistant n=182 (%)	217(60%)	147 (40%)	64 (35%)	89 (49%)	29 (16%)

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1. Genotype. GG vs AG/GG for COPD vs resistant, Odds ratio (OR) =1.60, 95% confidence limits 0.92.7, χ² (Yates corrected)= 3.37, p=0.07,

GG =susceptibility

2. Allele. G vs A for COPD vs resistant, Odds ratio (OR) =1.3, 95% confidence limits 1.0-1.7, χ²(Yates corrected)= 2.90, p=0.09

Caspase (NOD2) Gly881Arg polymorphism allele and genotype frequencies in the COPD patients and resistant smokers.

Frequency	Allele*	Genotype
	G	C	GG	GC	CC

-392017265006 21 Nov 2017

COPD n=247	486 (98%)	8 (2%)	239 (97%)	8 (3%)	0 (0%)
Resistant n=195 (%)	388 (99.5%)	2 0.5%)	193 (99%)	2 (1%)	0 (0%)

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1. Genotype. CC/CG vs GG for COPD vs resistant, Odds ratio (OR) =3.2, 95% confidence limits 0.622, χ² (Yates uncorrected)= 2.41, p=0.11 (1-tailed),

GC/CC=suseeptibility (trend)

Mannose binding lectin 2(MBL2) +161 G/A polymorphism allele and genotype frequencies in the COPD patients and resistant smokers.

F requency	Allele*	Genotype
	A	G	AA	AG	GG
COPD n=218 (%)	110(25%)	326 (75%)	6 (3%)	98 (45%)	114(52%)
Resistant n=183 (%)	66(18%)	300 (82%)	6 (3%)	54 (30%)	123 (67%)

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1. Genotype. GG vs rest for COPD vs resistant, Odds ratio (OR) =0.53, 95% confidence limits 0.40.80, χ² (Yates uncorrected)= 8.55, p=0.003,

GG =protective

Chymase 1 (CMA1) -1903 G/A promoter polymorphism allele and genotype frequencies in the COPD patients and resistant smokers.

Frequency	Allele*	Genotype
	A	G	AA	AG	GG
COPD n=239 (%)	259 (54%)	219 (46%)	67 (28%)	125 (52%)	47 (20%)
Resistant n=181 (%)	209 (58%)	153 (42%)	63 (35%)	83 (46%)	35 (19%)

* number of chromosomes (2n)

1. Genotype. AA vs AG/GG for COPD vs resistant, Odds ratio (OR) =0.73, 95% confidence limits 0.51.1, χ² (Yates corrected)= 1.91, p=0.17.

AA genotype =protective trend

N-Acetyltransferase 2 Arg 197 Gin G/A polymorphism allele and genotype frequencies in COPD and resistant smokers.

Frequency	Allele*	Genotype
	A	G	AA	AG	GG

-402017265006 21 Nov 2017

COPD n=247 (%)	136 (28%)	358 (72%)	14 (6%)	108 (44%)	125 (50%)
Resistant n=196 (%)	125 (32%)	267 (68%)	21 (11%)	83 (42%)	92 (47%)

* number of chromosomes (2n)

1. Genotype. AA vs AG/GG for COPD vs resistant, Odds ratio (OR) =0.50, 95% confidence limits 0.2 1.0, χ² (Yates uncorrected)= 3.82, p=0.05,

AA genotype = protective

Interleukin IB (IL-lb) -511 A/G polymorphism allele and genotype frequencies in COPD and resistant smokers.

Frequency	Allele*	Genotype
	A	G	AA	AG	GG
COPD n=248 (%)	160 (32%)	336 (68%)	31 (13%)	98 (40%)	119 (48%)
Resistant n=195 (%)	142 (36%)	248 (64%)	27 (14%)	88 (45%)	80 (41%)

* number of chromosomes (2n)

1. Genotype. GG vs AA/AG for COPD vs resistant, Odds ratio (OR) =1.3, 95% confidence limits 0.92.0, χ² (Yates corrected)= 1.86, p=0.17,

GG genotype = susceptible trend

Microsomal epoxide hydrolase (MEH) Tyr 113 His T/C (exon 3) polymorphism allele and genotype frequency in COPD and resistant smokers.

Frequency	Allele*	Genotype
	C	T	CC	CT	TT
COPD n=249 (%)	137 (28%)	361 (72%)	18(7%)	101 (41%)	130 (52%)
Resistant n=194 (%)	130 (34%)	258 (66%)	19 (10%)	92 (47%)	83 (43%)

* number of chromosomes (2n)

1. Genotype. TT vs CT/CC for COPD vs resistant, Odds ratio (OR) =1.5, 95% confidence limits 1.02.2, χ² (Yates corrected)= 3.51, p=0.06,

TT genotype = susceptible

Microsomal epoxide hydrolase (MEH) His 139 Arg A/G (exon 4) polymorphism allele and genotype frequency in COPD and resistant smokers.

Frequency	Allele*	Genotype
	A	G	AA	AG	GG
COPD n=238 (%)	372 (78%)	104 (22%)	148 (62%)	76 (32%)	14 (6%)

-41 2017265006 21 Nov 2017

Resistant n=179 (%)

277 (77%)

81 (23%)

114(64%)

49 (27%)

16 (9%)

* number of chromosomes (2n)

1. Genotype. GG vs AA/AG for COPD vs resistant, Odds ratio (OR) =0.64, 95% confidence limits 0.31.4, χ² (Yates uncorrected)= 1.43, p=0.23,

GG genotype = protective (trend)

Lipo-oxygenase -366 G/A polymorphism allele and genotype frequencies in the COPD patients and resistant smokers.

Frequency	Allele*	Genotype
	A	G	AA	AG	GG
COPD n=247 (%)	21 (4%)	473 (96%)	1 (0.5%)	19 (7.5%)	227 (92%)
Resistant n=T92 (%)	25 (7%)	359 (93%)	0 (0%)	25 (13%)	167 (87%)

* number of chromosomes (2n)

1. Genotype. AA/AG vs GG for COPD vs resistant, Odds ratio (OR) =0.60, 95% confidence limits 0.3-1.1, χ² (Yates corrected)= 2.34, p=0.12,

AA/AG genotype = protective (GG susceptible) trend

Heat Shock Protein 70 (HSP 70) HOM T2437C polymorphism allele and genotype frequencies in the COPD patients and resistant smokers.

Frequency	Allele*	Genotype
	C	T	CC	CT	TT
COPD n=199 (%)	127 (32%)	271 (68%)	5 (3%)	117(59%)	77 (39%)
Resistant n=166 (%)	78 (23%)	254 (77%)	4 (2%)	70 (42%)	92 (56%)

* number of chromosomes (2n)

1. Genotype. CC/'CT vs TT for COPD vs resistant, Odds ratio (OR) =2.0, 95% confidence limits 1.33.1, χ² (Yates uncorrected)= 9.52, p=0.002,

CC/CT genotype = susceptible (TT=protective)

Chloride Channel Calcium-activated 1 (CLCA1) +13924 T/A polymorphism allele and genotype frequencies in the COPD patients and resistant smokers.

Frequency	Allele*	Genotype
	A	T	AA	AT	TT
COPD n=224 (%)	282 (63%)	166 (37%)	84 (38%)	114(51%)	26(12%)
Resistant n=158 (%)	178 (56%)	138 (44%)	42 (27%)	94 (59%)	22 (14%)

-422017265006 21 Nov 2017 * number of chromosomes (2n)

1. Genotype. AA vs AT/TT for COPD vs resistant. Odds ratio (OR) =1.7, 95% confidence limits 1.02.7, χ^{1 2} (Yates corrected)= 4.51, p=0.03,

AA=susceptible

Monocyte differentiation antigen CD-14 -159 promoter polymorphism allele and genotype frequencies in the COPD patients and resistant smokers.

Frequency	Allele*	Genotype
	C	T	CC	CT	TT
COPD n=240 (%)	268 (56%)	212 (44%)	77 (32%)	114(48%)	49 (20%)
Resistant n=180 (%)	182 (51%)	178 (49%)	46 (25%)	90 (50%)	44 (24%)

* number of chromosomes (2n)

1. Genotype.CC vs ( i l l for COPD vs Resistant, Odds ratio (OR) =1.4, 95% confidence limits 0.92.2, χ² (Yates uncorrected)= 2.12, p=0.15,

CC = susceptible (trend) £lafin +49 C/T polymorphism allele and genotype frequencies in the COPD patients, resistant smokers and controls.

Frequency	Allele*	Genotype
	C	T	CC	CT	TT
COPD n= 144 (%)	247 (86%)	41 (14%)	105 (73%)	37 (26%)	2 (1%)
Resistant n=75 (%)	121 (81%)	29(19%)	49 (65%)	23 (31%)	3 (4%)

* number of chromosomes (2n)

1. Genotype. CT/TT vs CC for COPD vs resistant, Odds ratio (OR) = 0.70, 95% confidence linrits= 0.4-1.3 , χ² (Yates uncorrected)= 1.36, p=0.24,

CT/TT genotype = protective (trend only)

2. Allele: T vs C for COPD vs resistant, Odds ratio (OR) = 0.69, 95% confidence limits= 0.4-1.2 , χ²(Yates uncorrected)= 1.91, p=0.17,

T genotype = protective (trend only)

Beta2-adrenoreceptor Gin 27 Glu polymorphism allele and genotype frequency in the COPD patients, resistant smokers and controls.

Frequency

Allele*

Genotype

-43 2017265006 21 Nov 2017

	C	G	CC	CG	GG
Controls n=185 (%)	204 (55%)	168 (45%)	57 (31%)	89 (48%)	39 (21%)
COPD n=238 (%)	268 (56%)	208 (44%)	67 (28%)	134 (56%)	37 (16%)
Resistant n=195 (%)	220 (56%)	170(44%)	64 (33%)	92 (47%)	39 (20%)

* number of chromosomes (2n)

1. Genotype. GG vs CG/CC for COPD vs resistant, Odds ratio (OR) = 0.74, 95% confidence limits = 0.4-1.2, χ² (Yates uncorrected)= 1.47 , p=0.23,

GG =protective (trend)

2. Genotype. GG vs CG/CC for COPD vs controls. Odds ratio (OR) = 0.69, 95% confidence limits = 0.4-1.2, χ² (Yates uncorrected)= 2.16 , p=0.14,

GG =protective (trend)

Maxtrix metalloproteinase 1 (MMP1) -1607 1G/2G polymorphism allele and genotype frequencies in COPD patients, resistant smokers and controls.

Frequency	Allele*	Genotype
	1G	2G	1G1G	1G2G	2G2G
Controls n=174 (%)	214 (61%)	134 (39%)	68 (39%)	78 (45%)	28 (16%)
COPD n=217 (%)	182 (42%)	252 (58%)	47 (22%)	88 (41%)	82 (38%)
Resistant n=187 (%)	186 (50%)	188 (50%)	46 (25%)	94 (50%)	47 (25%)

* number of chromosomes (2n)

1. Genotype. 1G1G vs rest for COPD vs controls, Odds ratio (OR) =0.43, 95% confidence limits 0.3-0.7, χ² (Yates uncorrected)= 13.3, p=0.0003

1G1G genotype =protective

2. Allele. 1G vs 2G for COPD vs controls, Odds ration (OR) =0.45, 95% confidence limits 0.3-0.6, χ2 (Yates corrected)= 28.8, pO.0001,

1G = protective

3. Genotype. 1G1G/1G2G vs rest for COPD vs resistant smokers, Odds ratio (OR) =0.55, 95% confidence limits 0.4-0.9, χ² (Yates uncorrected)= 6.83, p=0.009

1G1G/162G genotypes =protective

4. Allele. 1G vs 2G for COPD vs resistant smokers, Odds ratio (OR) =0.73, 95% confidence limits 0.6-1.0, χ2 (Yates corrected)= 4.61, p=0.03,

1G = protective

2017265006 21 Nov 2017

-445. Genotype. 2G2G vs 1G1 G/l G2G for COPD vs controls, Odds ratio (OR) =3.17, 95% confidence limits 1.9-5.3, χ2 (Yates uncorrected)= 21.4, p<0.0001 2G2G genotype =susceptible

6. Allele. 2G vs 1G for COPD vs controls, Odds ratio (OR) =2.2, 95% confidence limits 1.6-3.0, χ2 (Yates corrected)= 28.8, p<0.00001,

2G = susceptible

7. Genotype. 2G2G vs 1G1 G/lG2G for COPD vs resistant, Odds ratio (OR) = 1.81, 95% confidence limits 1.2-2.9, χ2 (Yates uncorrected)= 6.83, p=0.009

2G2G genotype =susceptible

8. Allele. 2G vs 1G for COPD vs resistant, Odds ratio (OR) =1.4, 95% confidence limits 1.0-1.8, χ2 (Yates corrected)= 4.61, p=0.0.03,

2G = susceptible

Table 2 below provides a summary of the protective and susceptibility polymorphisms determined for COPD.

Table 2. Summary of protective and susceptibility polymorphisms for COPD

Gene	Polymorphism	Role
Cyclo-oxygenase 2 (COX2)	COX2 -765 G/C	CC/'CG protective
P2-adrenoreceptor (ADBR)	ADBRArgl6Gly	GG susceptible
Interleukin -18 (IL 18)	IL18 -133 C7G	CC susceptible
Interleukin -18 (IL 18)	IL18 105 A/C	AA susceptible
Plasminogen activator inhibitor 1 (PAI-1)	PAI-I -675 4G/5G	5G5G susceptible
Nitric Oxide synthase 3 (NOS3)	NOS3 298 Asp/Glu	TT protective
Vitamin D Binding Protein (VDBP)	VDBP Lys 420 Thr	AA/AC protective
Vitamin D Binding Protein (VDBP)	VDBP Glu 416 Asp	TT/TG protective
Glutathione S Transferase (GSTP-1)	GSTP1 IlelOSVal	AA protective
Interferon γ (IFN-γ)	IFN-γ 874 A/T	AA susceptible
Interleukin-13 (IL 13)	IL13 Arg 130 Gin	AA protective
Interleukin-13 (IL 13)	1113 -1055C/T	TT susceptible
a 1-antitrypsin (al-AT)	al-AT S allele	MS protective
Tumour Necrosis Factor a TNFa	TNFa +489 G/A	ΛΆ/AG susceptible GG protective

-45 2017265006 21 Nov 2017

Tumour Necrosis Factor a TNFa	TNFa -308 G/A	GG protective AA/AG susceptible
SMAD3	SMAD3 C89Y AG	AA/AG protective GG susceptible
Intracellular adhesion molecule 1 (ICAM1)	ICAM1 E469K A/G	GG susceptible
Caspase (N0D2)	NOD2 Gly 881 Arg G/C	GC/'CC susceptible
Mannose binding lectin 2 (MBL2)	MBL2 161 G/A	GG protective
Chymase 1 (CMA1)	CMA1 -1903 G/A	AA protective
N- Acetyl transferase 2 (NAT2)	NAT2 Arg 197 Gin G/A	AA protective
Interleukin IB (ILIB)	(ILIB) -511 A/G	GG susceptible
Microsomal epoxide hydrolase (MEH)	MEH Tyr 113 His T/C	TT susceptible
Microsomal epoxide hydrolase (MEH)	MEH His 139 Arg G/A	GG protective
5 Lipo-oxygenase (ALOX5)	ALOX5 -366 G/A	AA/AG protective GG susceptible
Heat Shock Protein 70 (HSP 70)	HSP 70 HOMT2437C	CC C 1 susceptible TT protective
Chloride Channel Calcium-activated 1 (CLCA1)	CLCA1 +13924 T/A	AA susceptible
Monocyte differentiation antigen CD-14	CD-14-159 C/T	CC susceptible
Elafm	Elafm Exon 1 +49 C/T	CT/TT protective
B2-adrenergic receptor (ADBR)	ADBR Gin 27 Glu C/G	GG protective
Matrix metalloproteinase 1 (MMP1)	MMP1 -1607 1G/2G	1G1G/1G2G protective

The combined frequencies of the presence or absence of the selected protective genotypes COX2 (-765) CC/CG, β2 adreno-receptor AA, Interleukin-13 AA, Nitic Oxide Synthase 3 TT, and Vitamin D Binding Protein AA observed in the COPD subjects and in resistant smokers is presented below in Table 3.

Table 3. Combined frequencies of the presence or absence of selected protective genotypes in COPD subjects and in resistant smokers.

	Number of protective polymorphisms
Cohorts	0	1	>2	Total
COPD	136 (54%)	100 (40%)	16(7%)	252
Resistant smokers	79 (40%)	83 (42%)	34(17%)	196

-462017265006 21 Nov 2017

% of smokers with COPD

136/215 (63%)

100/183 (55%)

16/50 (32%)

Comparison	Odd’s ratio	95% CI	/2	P value
0 vs 1 vs 2+, Resist vs COPD	-	-	16.43	0.0003
2+ vs 0-1, Resist vs COPD	3.1	1.6-6.1	12.36	0.0004
1+ vs 0, Resist vs COPD	1.74	1.2-2.6	7.71	0.006

The combined frequencies of the presence or absence of the selected susceptibility genotypes Interleukin-18 105 AA, PAI-1 -675 5G5G, Interleukin-13 -1055 TT, and Interferon-γ -874 AA observed in the COPD subjects and in resistant smokers is presented below in Table 4.

Table 4. Combined frequencies of the presence or absence of selected susceptibility genotypes in the COPD subjects and in resistant smokers.

	Number of protective polymorphisms
Cohorts	0	1	>2	Total
COPD	66 (26%)	113 (45%)	73 (29%)	252
Resistant smokers	69 (35%)	92 (47%)	35 (18%)	196
% of smokers with COPD	66/135 (49%)	113/205 (55%)	73/108 (68%)

Comparison	Odd’s ratio	95% C.I	%2	P value
0 vs 1 vs 2+, COPD vs Resist	-	-	8.72	0.01
2+ vs 0-1, COPD vs Resist	1.9	1.2-3.0	6.84	0.009
1+ vs 0, COPD vs Resist	1.5	1.0-3.5	3.84	0.05

The combined frequencies of the presence or absence of the protective genotypes COX2 (-765) CC/CG, Interleukin-13 AA, Nitic Oxide Synthase 3 TT, Vitamin D Binding Protein AA/AC, GSTP1 AA, and al-antitypsin MS/SS, observed in the COPD subjects and in resistant smokers is presented below in Table 5 and in Figure 1.

2017265006 21 Nov 2017

-47Table 5. Combined frequencies of the presence or absence of selected protective genotypes in the COPD subjects and in resistant smokers.

	Number of protective polymorphisms
Cohorts	0	1	>2	Total
COPD	51 (19%)	64 (24%)	150 (57%)	265
Resistant smokers	16(8%)	56 (27%)	133 (65%)	205
% of smokers with COPD	51/76 (76%)	64/120 (53%)	150/283 (53%)

Comparison	Odd’s ratio	95% CI	Z2	P value
0 vs 1 vs 2+, Resist vs COPD	-	-	12.14	0.0005
1+ vs 0, Resist vs COPD	2.82	1.5-5.3	11.46	0.0004

Protective polymorphisms were assigned a score of +1 while susceptibility polymorphisms were assigned a score of -1. For each subject, a net score was then calculated according to the presence of susceptibility and protective genotypes. This produced a linear spread of values. When assessed as a range between -3 to +3, a linear relationship as depicted in Figure 2 was observed. This analysis indicates that for subjects with a net score of-2 or less, there was a 70% or greater risk of having COPD. In contrast, for subjects with a net score of 2+ or greater the risk was approximately 40% (see Figure 2).

In an analysis in which the value of a given polymorphism was weighted based on the Odd’s ratio for that polymorphism (generated by comparing its frequency between resistant and COPD subjects), a linear relationship was again observed. This analysis allowed for the distinction of smokers at high or low risk of having COPD.

EXAMPLE 2. CASE ASSOCIATION STUDY - OCOPD

METHODS

Subject recruitment

Subjects of European decent who had been exposed to chronic smoking (minimum 15 pack years) and aero-pollutants in the work place (noxious dusts or fumes) were identified from respiratory clinics. After spirometric testing those with occupational chronic obstructive pulmonary disease (OCOPD) with forced expiratory volume in one second

2017265006 21 Nov 2017

-48(FEV1) as a percentage of predicted <70% and a FEV1/FVC ratio (Forced expiratory volume in one second/Forced vital capacity) of < 79% (measured using American Thoracic Society criteria) were recruited. One hundred and thirty-nine subjects were recruited, of these 70% were male, the mean FEV1/FVC ( ± Standard Deviation) was 54% (SD 15), mean FEV1 as a percentage of predicted was 46 (SD 19). Mean age, cigarettes per day, and pack year history was 62 yrs (SD 9), 25 cigarettes/day (SD 16) and 53 pack years (SD 31), respectively. One hundred and twelve European subjects who had smoked a minimum of fifteen pack years and similarly been exposed in the work place to potentially noxious dusts or fumes were also studied. This control group was recruited through community studies of lung function and were 81% male; the mean FEV1/FVC ( SD) was 81% (SD 8), and mean FEV1 as a percentage of predicted was 96 (SD 10). Mean age, cigarettes per day and pack year history was 58 yrs (SD 11), 26 cigarettes/day (SD 14) and 45 pack years (SD 28), respectively. Using a PCR based method [1], all subjects were genotyped for the alantitrypsin mutations (M, S and Z alleles) and those with the ZZ allele were excluded. The OCOPD and resistant smoker cohorts were matched for subjects with the MZ genotype (6% in each cohort). They were also matched for age started smoking (mean 16 yr) and aged stopped smoking (mid fifties). 190 European blood donors (smoking and occupational exposure status unknown) were recruited consecutively through local blood donor services. Sixty-three percent were men and their mean age was 50 years. On regression analysis, the age difference and pack years difference observed between OCOPD sufferers and resistant smokers was found not to determine FEV or OCOPD.

Summary of characteristics for the OCOPD and exposed resistant smoker cohorts.

Parameter Mean (SD)	OCOPD (N=139)	Exposed resistant smokers (N=112)	Differences
% male	70%	81%	P<0.05
Age (yrs)	62(9)	58 (11)	ns
Pack years	53 (31)	45 (28)	P<0.05
Cigarettes/day	25 (16)	26 (14)	ns
FEV1 (L)	1.3 (0.7)	3.0 (0.7)	P<0.05
FEV1 %> predict	46 (19 )	96% (10)	P<0.05
FEV1/FVC	54 (15 )	81(8)	P<0.05

Means and 1 SD

2017265006 21 Nov 2017

-49Cyclooxygenase 2 (COX2) -765 G/Cpromoter polymorphism and al-antitrypsin genotyping

Genomic DNA was extracted from whole blood samples [2], The COX2 -765 polymorphism was determined by minor modifications of a previously published method [3], The PCR reaction was carried out in a total volume of 25ul and contained 20 ng genomic DNA, 500pmol forward and reverse primers, 0.2mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KC1, 1.0 mM MgCb and 1 unit of Taq polymerase (Life Technologies). Cycling times were incubations for 3 min at 95°C followed by 33 cycles of 50s at 94°C, 60s at 66°C and 60s at 72°C. A final elongation of 10 min at 72°C then followed. 4ul of PCR products were visualised by ultraviolet trans-illumination of a 6% agarose gel stained with ethidium bromide. An aliquot of 3ul of amplification product was digested for 1 hr with 4 units olAcil (Roche Diagnostics, New Zealand) at 37°C. Digested products were separated on a 2.5% agarose gel run for 2.0 hrs at 80 mV with TBE buffer and visualised using ultraviolet transillumination after ethidium bromide staining against a 123bp ladder. Using a PCR based method discussed above [3], all smoking subjects were genotyped for the alantitrypsin M, S and Z alleles.

Genotyping of the superoxide dismutase 3 Arg 312 Gin polymorphism

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [4, incorporated in its entirety herein by reference]. Genotyping was done using minor modifications of the above protocol optimised for laboratory conditions. The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25μΐ and contained 80ng genomic DNA, 10 pmol forward and reverse primers, O.lmM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KC1, 1.0 mM MgCh and 0.5 unit of Taq polymerase (Qiagen). Aliquots of amplification product were digested for 4 hrs with 5U of the relevant restriction enzymes (Roche Diagnostics, New Zealand) at designated temperatures and conditions. Digested products were separated on 8% polyacrylamide gels (49:1, Sigma). The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a

2017265006 21 Nov 2017

-501Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Genotyping of the Microsomal Epoxide Hydrolase Exon 3 TC polymorphism

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [5, incorporated in its entirety herein by reference]. Genotyping was done using minor modifications of the above protocol optimised for laboratory conditions. The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25μΐ and contained 80ng genomic DNA, 100 ng forward and reverse primers, 0.2mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KC1, 1.5 mM MgCh and 1.0 unit of Taq polymerase (Qiagen). Cycling conditions consisted of 94°C 60s, 56°C 20s, 72°C 20s for 38 cycles with an extended last extension of 3min. Aliquots of amplification product were digested for 4 hrs with 5U of the relevant restriction enzymes Eco RN (Roche Diagnostics, New Zealand) at designated temperature conditions. Digested products were separated on 8% polyacrylamide gels (49:1, Sigma). The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a 1Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Genotyping of the 3’ 1237 G/A (T/t) polymorphism of the al-antitrypsin gene

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-weil PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [Sandford AJ et al.,[6]]. Genotyping was done using minor modifications of the above protocol optimised for laboratory conditions The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25μΐ and contained 80ng genomic DNA, 100 ng forward and reverse primers, 0.2mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KC'l, 1.5 mM MgCh and 1.0 unit of Taq polymerase (Qiagen). Forward and reverse prime sequences were 5’-CTACCAGGAATGGCCTTGTCC-3’ [SEQ.ID.NO.136]

2017265006 21 Nov 2017

- 51 and 5’-CTCTCAGGTCTGGTGTCATCC-3’ [SEQ.ID.NO.137], Cycling conditions consisted of 94C 60 s, 56C 20s, 72C 20 s for 38 cycles with an extended last extension of 3 min. Aliquots of amplification product were digested for 4 hrs with 2 Units of the restriction enzymes Taq 1 (Roche Diagnostics, New Zealand) at designated temperature conditions. Digested products were separated on 3% agarose. The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a 1Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Genotyping of the Asp 299 Gly polymorphism of the toll-like receptor 4 gene

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [6, incorporated in its entirety herein by reference], Genotyping was done using minor modifications of the above protocol optimised for laboratory conditions The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25μ1 and contained 80ng genomic DNA, 100 ng forward and reverse primers, 0.2mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KC1, 1.5 mM MgCb and 1.0 unit of Taq polymerase (Qiagen). Forward and reverse prime sequences were 5’GATTAGCATACTTAGACTACTACCTCCATG-3’ [SEQ.ID.NO.138] and 5’GATCAACTTCTGAAAAAGCATTCCCAC-3’ [SEQ.ID.NO.139], Cycling conditions consisted of 94°C 30s, 55°C 30s, 72°C 30s for 30 cycles with an extended last extension of 3min. Aliquots of amplification product were digested for 4 hrs with 2U of the restriction enzyme Neo I (Roche Diagnostics, New Zealand) at designated temperature conditions. Digested products were separated on 3% agarose gel. The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a 1Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

2017265006 21 Nov 2017

-52Genotyping of the -16071G2G polymorphism of the matrix metalloproteinase 1 gene

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RF’LP assays details have been previously described [Dunleavey L, et al], Genotyping was done using minor modifications of the above protocol optimised for laboratory conditions The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25μΐ and contained 80ng genomic DNA, 100 ng forward and reverse primers, 200mM dNTPs, 20 mM Tris-HCL (pH 8.4), 50 mM KC1, 1.5 mM MgCk and 1.0 unit of Taq polymerase (Qiagen). Forward and reverse prime sequences were3’ TCGTGAGAATGTCTTCCCATT-3’ [SEQ.ID.NO.140] and 5’-TCTTGGATTGATTTGAGATAAGTGAAATC-3’ [SEQ.ID.NO.141], Cycling conditions consisted of 94C 60 s, 55C 30s, 72C 30 s for 35 cycles with an extended last extension of 3 min. Aliquots of amplification product were digested for 4 hrs with 6 Units of the restriction enzymes XmnI (Roche Diagnostics, New Zealand) at designated temperature conditions. Digested products were separated on 6% polyacrylamide gel. The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a 1Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Other polymorphism genotyping

Genomic DNA was extracted from whole blood samples [4], Purified genomic DNA was aliquoted (10 ng/ul concentration) into 96 well plates and genotyped on a Sequenom^IM system (Sequenomtm Autoflex Mass Spectrometer and Samsung 24 pin nanodispenser) using the sequences, amplification conditions and methods described below.

The following conditions were used for the PCR multiplex reaction: final concentrations were for lOxBuffer 15 mM MgC12 1.25x, 25mM MgC12 1.625mM, dNTP mix 25 mM 500uM, primers 4 uM lOOnM, Taq polymerase (Quiagen hot start) 0.15u/reaction, Genomic DNA 10 ng/ul. Cycling times were 95°C for 15min, (5°C for 15s, 56°C 30s, 72°C 30s for 45 cycles with a prolonged extension time of 3min to finish. We used shrimp alkaline phosphotase (SAP) treatment (2ul to Sul PCR reaction) incubated at

2017265006 21 Nov 2017

- 53 35°C for 30min and extension reaction (add 2ul to 7ul after SAP treatment) with the following volumes per reaction of water 0.76ul, hME lOx termination buffer 0.2ul, hME primer (lOuM) lul, MassEXTEND enzyme 0.04ul.

2017265006 21 Nov 2017

IL-18 A105C	IL-18 C-133G	IL-8 A-251T	NOS3 - 298	IL-11 G518A	PAI1 G-675G	GSTP1 -105	ADRB2-Gln27Glu	VDBP -416	VDBP - 420	¢/3 z 7 5
ACT	ACT	CGT	ACT	ACT	ACT	ACT	ACT	ACT	ACT	in π 2
W8	W6	3 ¢-/1	W3	W3	W2	W2	W2			n r n
ACGTTGGATGGGTCAATGAAGAGAACTTGG [SEQ.ID.NO. 160]	ACGTTGGATGGGGTATTCATAAGCTGAAAC [SEQ.ID.NO. 158]	ACGTTGGATGACTGAAG CTCCACAATTTGG [SEQ.ID.NO. 156]	ACGTTGGATGACAGCTCTGCATTCAGCACG [SEQ.ID.NO. 154]	ACGTTGGATGCCTCTGATCCTCTTTGCTTC [SEQ.ID.NO. 152]	ACGTTGGATGCACAGAGAGAGTCTGGACAC [SEQ.ID.NO. 150]	ACGTTGGATGTGGTGGACATGGTGAATGAC [SEQ.ID.NO. 148]	ACGTTGGATGTTGCTGGCACCCAATGGAAG [SEQ.ID.NO.146]	ACGTTGG ATGTTTTTCAG ACTGGCAGAG CG [SEQ.ID.NO.144]	ACGTTGGATGGCTTGTTAACCAGCT TTGCC [SEQ.ID.NO. 142]	bj B s. -c Π 5« n
ACGTTGGATGAATGTTTATTGTAGAAAACC [SEQ.ID.NO. 161]	ACGTTGGATGCCTTCAAGTTCAGTGGTCAG [SEQ.ID.NO. 159]	ACGTTGGATGGCCACTCTAGTACTATATCTG [SEQ.ID.NO. 157]	ACGTTGGATGAGTCAATCCCTTTGGTGCTC [SEQ.ID.NO. 155]	ACGTTGGATGAAGAGGGAGTGGAAGGGAAG [SEQ.ID.NO. 153]	ACG TTGG ATG CTCTTGGTCTTTCCCTCATC [SEQ.ID.NO. 151]	ACGTTGGATGTGGTGCAGATGCTCACATAG [SEQ.ID.NO. 149]	ACGTTGGATGATGAGAGACATGACGATGCC [SEQ.ID.NO. 147]	ACGTTGGATGGCTTGTTAACCAGCTTTGCC [SEQ.ID.NO. 145]	ACGTTGGATG TTTTTCAGACTGGCAGAGCG [SEQ.ID.NO. 143]	lst-PCRP

Sequenom conditions for the polymorphisms genotyping -1

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2017265006 21 Nov 2017

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IL-18 A105C	IL-18 C-133G	IL-8 A-251T	NOSS -298	IL-11 G518A	PAIl G-675G	GSTP1 -105	ADRB2-GIn27Glu	VDBP -416	VDBP - 420	CZ) 2 7 5
	ΙΌ	k©	186	Ok k©	109	107	OO	k© k©	k© k©	> 2 'r w 2
67.2	93.5	92.6	98.1	97.5	k© •o k©	99.4	96.6	k© k©	99.7	d 7 d o 2 *1
74.3	74.3	81.2	o CD	Ok <2l	00 o	OO o	00 o	99.7	99.7	2 0 1 d O 2 1
48.9	41.8	45.9	61.2	52.9	59.3	49.9	52.2	45.5	46.2	Tm(NN)
o	46.7	28.6	63.2	52.6	Ok Ok	52.9	66.7	33.3	53.3	PcGC
	r*			!Z2	00			s	ML	PWARN
73	*-Tj	73	Hd	h-rj	rtd		*Tj		73	UEP DIR

Sequenom conditions for the polymorphisms genotyping -2

2017265006 21 Nov 2017

IL-18 A105C	IL-18 C-133G	IL-8 A-251T	NOS3 - 298	IL-11 G518A	PAI1 G-675G	GSTP1 -105	ADRB2-Gln27Glu	VDBP -416	VDBP - 420	¢/3 z 7 5
TCAAGCTTGCCAAAGTAATCT [SEQ.ID.NO. 190]	AG CTGA AACTTCTGGC [SEQ.ID.NO. 188]	CACAATTTGGTGAATTATCAAT [SEQ.ID.NO. 186]	TGCTGCAGGCCCCAGATGAT [SEQ.ID.NO. 184]	TCCATCTCTGTGGATCTCCA [SEQ.ID.NO. 182]	GAGTCTGGACACGTGGGGA [SEQ.ID.NO. 180]	ACCTCCGCTGCAAATACA [SEQ.ID.NO. 178]	CACGACGTCACGCAGC [SEQ.ID.NO. 176]	AAAAGCAAAATTGCCTGAT [SEQ.ID.NO. 174]	AGCTTTGCCAGTTCCT [SEQ.ID.NO. 172]	x H 1 ¢/3 W O
n	O	H	a	c	C	C	C	O	n	w X H i^M o > r r
7040.6	5218.4	7029.6	6416.2	6323.1	6247.1	5716.7	5173.4	6456.2	5136.4	EXT2 MASS
TCAAGCTTGCCAAAGTAATCGGA [SEQ.ID.NO.191]	AGCTGAAACTTCTGGGA [SEQ.ID.NO. 189]	CACAATTTGGTGAATTATCAAAT [SEQ.ID.NO. 187]	TGCTGCAGGCCCCAGATGAGC [SEQ.ID.NO. 185]	TCCATCTCTGTGGATCTCCGT [SEQ.ID.NO. 183]	GAGTCTGGACACGTGGGGGA [SEQ.ID.NO.181]	ACCTCCGCTGCAAATACGT [SEQ.ID.NO. 179]	CACGACGTCACGCAGGA [SEQ.ID.NO. 177]	AAAAGCAAAATTGC'CTGAGGC [SEQ.ID.NO. 175]	AGCTTTGCCAGTTCCGT [SEQ.ID.NO. 173]	EXT2SEQ
6414.2	4921.2	6741.4	6143	6034.9	5949.9	5428.5	4876.2	5853.9	4848.2	IstPAUSE

Sequenom conditions for the polymorphisms genotyping -4

2017265006 21 Nov 2017

-57RESULTS

Frequencies of individual polymorphisms are as follows:

Table 6. Polymorphism allele and genotype frequency in the OCOPD patients, exposed resistant smokers and controls.

Cvclo-oxygenase 2 -765 F requency	G/C Allele*	Genotype
	C	G	CC	CG	GG
Controls n=95 (%)	27 (14%)	161 (86%)	3 (3%)	21 (22%)	70 (75%)
OCOPD n=82 (%)	22 (13%)	142⁴ (87%)	2 (2%)	18 (22%)	62³ (76%)
Resistant n=87 (%)	42² (24%)	132(76%)	6’ (7%)	30’ (34%)	51 (59%)

Glutathione S Transfer F requency	ase Pl He 105 Val (A/G) Allele*	Genotype
	A	G	AA	AG	GG
Controls n=l 86 (%)	234 (63%)	138 (37%)	71 (38%)	92 (50%)	23 (12%)
OCOPD n=123 (%)	159 (65%)	87 (36%)	52 (42%)	55 (45%)	16^s (13%)
Resistant n-98 (%)	136 (69%)	60(31%)	44 (45%)	48 (49%)	6 (6%)

Interleukin 18 105 C7A Frequency	Allele*	Genotype
	C	A	CC	AC	ΛΑ
Controls n=l 85 (%)	119(32%)	251 (68%)	22 (12%)	75 (40%)	88 (48%)
OCOPD n=122 (%)	62 (25%)	182 (75%)	12(10%)	38(31%)	72⁶·⁷ (59%)
Resistant n=98 (%)	60(31%)	136 (69%)	6 (6%)	48 (49%)	44 (45%)

Interleukin 18-133 G/C Frequency	Allele*	Genotype
	G	C	GG	GC	CC
Controls n=l 88 (%)	121 (32%)	255 (68%)	23 (12%)	75 (40%)	90 (48%)
OCOPD n= 122	62 (25%)	182 (75%)	12(10%)	38(31%)	72^s’⁰ (59%)
Resistant n=97 (%)	60(31%)	134 (69%)	6 (6%)	48 (50%)	43 (44%)

Interleukin 8 -251 A/T Frequency	Allele*	Genotype

-582017265006 21 Nov 2017

	A	T	AA	AT	TT
Controls n=l 88 (%)	175 (47%)	201 (53%)	39(21%)	97 (52%)	52 (28%)
OCOPD n=l 16	101 (44%)	131 (56%)	21 (18%)	59 (51%)	36 (31%)
Resistant n=93 (%)	94*¹ (50%)	92 (49%)	26¹⁽¹ (28%)	42 (45%)	25 (27%)

Vitamin D Binding Pro F requency	tein Lys 420 Thr (A/C) Allele*	Genotype
	A	C	AA	AC	CC
Controls n= 189 (%)	113 (30%)	265 (70%)	17(9%)	79 (42%)	93 (49%)
OCOPD n=122 (%)	62 (25%)	182 (75%)	5 (4%)	52 (43%)	65¹⁴ (53%)
Resistant n=99 (%)	73¹³ (37%)	125 (63%)	12¹² (12%)	49 (50%)	38 (38%)

Vitamin D Binding Pro Frequency	tein Glu 416 Asp (T/G) Allele*	Genotype
	T	G	TT	TG	GG
Controls n=189 (%)	163 (43%)	215 (57%)	35 (19%)	93 (49%)	61 (32%)
OCOPD n=122 (%)	109 (45%)	135 (55%)	25 (21%)	59 (48%)	38¹⁷ (31%)
Resistant n=99 (%)	103¹⁶ (52%)	95 (48%)	23¹⁵ (23%)	57¹⁵ (58%)	19(19%)

Microsomal epxoide hy F requency	drolase R/r Exon 3 T/C Allele*	Genotype
	1'	R	rr	Rr	RR
Controls n=l 84 (%)	228 (62%)	140 (38%)	77 (42%)	74 (40%)	33 (18%)
OCOPD n=98 (%)	144 (74%)	52 (26%)	55 (56%)	34 (35%)	9 (9%)
Resistant n=102 (%)	135 (66%)	69 (34%)	52(51%)	31 (30%)	19¹⁸ (19%)

Super oxide dismutase Frequency	3 Arg 312 Gin Allele*	Genotype
	A	G	AA	AG	GG
Controls n=190 (%)	371 (98%)	9 (2%)	183 (96%)	5 (3%)	2 (1%)
OCOPD n=100 (%)	199²⁰ (99%)	1 (1%)	99 (99%)	1 (1%)	0 (0%)
Resistant n=102 (%)	193 (95%)	11²⁰ (5%)	92 (90%)	9¹⁹ (9%)	1¹⁹(1%)

αΐ-antitrypsin S Frequency	Allele*	Genotype
	M	S	MM	MS	ss

-592017265006 21 Nov 2017

OCOPD n=88 (%)	171 (97%)	5 (3%)	83 (94%)	5 ¢6%)	0 (0%)
Resistant n=94 (%)	175 (93%)	13²² (7%)	81 (86%)	13²¹ (14%)	0 (0%)

Toll-like receptor 4 As] F requency	299 Gly A/G Allele*	Genotype
	A	G	AA	AG	GG
OCOPD n=60 (%)	117(98%)	1 (2%)	58 (98%)	1 (2%)	0 (0%)
Resistant n=34 (%)	65 (96%)	3 (4%)	31 (91%)	3²³ (9%)	0 (0%)

Beta2-adrenoreceptor < Frequency	Jin 27 Glu Allele*	Genotype
	C	G	CC	CG	GG
Controls n=l 86 (%)	204 (55%)	168 (45%)	57 (31%)	90 (48%)	39(21%)
OCOPD n=122 (%)	129 (53%)	115 (47%)	32 (26%)	65 (53%)	25 (21%)
Resistant n=99 (%)	117 (59%)	81 (41%)	38²⁴ (38%)	41 (41%)	20 (20%)

Interleukin 11 (IL-11) - Frequency	518 G/A Allele*	Genotype
	A	G	AA	AG	GG
OCOPD n=l 19(%)	110 (46%)	128 (54%)	22 (19%)	66 (55%)	31 (26%)
Resistant n=98 (%)	103 (53%)	93 (47%)	26²⁵ (27%)	51 (52%)	21 (21%)

Interleukin-13 -1055 C/ Frequency	T Allele*	Genotype
	T	C	TT	TC	CC
Controls n=182 (%)	65(18%)	299 (82%)	5 (3%)	55 (30%)	122 (67%)
OCOPD n=121 (%)	53 (22%)	189 (78%)	5²⁶ (4%)	43 (36%)	73 (60%)
Resistant n=97 (%)	31 (16%)	163 (84%)	1 (1%)	29 (30%)	67 (69%)

Plasminogen activator Frequency	inhibitor 1 -675 4G/5G Allele*	Genotype
	5G	4G	5G5G	5G4G	4G4G
Controls n=186 (%)	158 (42%)	214(58%)	31 (17%)	96 (52%)	59 (32%)
OCOPD n=122 (%)	115^2S (47%)	129(53%)	29²⁷ (24%)	57 (47%)	36 (30%)
Resistant n=98 (%)	76 (39%)	120 (61%)	14 (14%)	48 (49%)	36 (37%)

-602017265006 21 Nov 2017

Nitric oxide synthase 3 Frequency	Asp 298 Glu (T/G) Allele*	Genotype
	T	G	TT	TG	GG
Controls n= 183 (%)	108(30%)	258 (70%)	13 (7%)	82 (45%)	88 (48%)
OCOPD n=120 (%)	71 (30%)	169 (70%)	10(8%)	51 (43%)	59 (49%)
Resistant n=99 (%)	71 (36%)	127 (64%)	1529,30 _(15%)	41 (41%)	43 (43%)

al-antitrypsin 3’ 1237 F requency	G/A (T/t) Allele*	Genotype
	T	t	TT	Tt	tt
Controls n=178 (%)	345 (97%)	11 (3%)	167 (94%)	11 (6%)	0 (0%)
COPD n=61 (%)	109 (89%)	13 (11%)³²	50 (82%)	9(15%)³¹	2 (3%)³¹
Resistant n=35 (%)	67 (96%)	3 (4%)	32 (91%)	3 (9%)	0 (0%)

Matrix metalloproteina Frequency	se 1 -1607 1G/2G Allele*	Genotype
	1G	2G	1G1G	1G2G	2G2G
Controls n=174 (%)	214(61%)	134 (39%)	68 (39%)	78 (45%)	28 (16%)
COPD n=93 (%)	90 (48%)	96 (52%)³⁴	24 (26%)	42 (45%)	27 (29%)³³
Resistant n=94 (%)	99 (53%)	89 (47%)	25 (27%)	49 (52%)	20(21%)

* number of chromosomes (2n)

1. Genotype. CC/CG vs GG for resistant vs OCOPD, Odds ratio (OR) =2.2, 95% confidence limits=l.1-4.8, χ² (Yates corrected)= 4.76, P=Q.O3, CC/CG =protective

2. Allele. C vs G for resistant vs OCOPD, Odds ratio (OR) =2.1, 95% confidence limits 1.1- 3.8, χ² (Yates corrected)= 5.65, p=0.02. C =protective

3. Genotype. GG vs CG/CC for OCOPD vs resistant, Odds ratio (OR) =0.5, 95% confidence limits=0.2-0.9, χ² (Yates corrected)= 4.76, P=0.03. GG =susceptible

4. Allele. G vs C for OCOPD vs resistant, Odds ratio (OR) =0.5, 95% confidence limits 0.3- 0.9, χ² (Yates corrected)= 5.65, p=0.02. G =susceptible

5. Genotype. GG vs AG/AA for OCOPD vs resistant, Odds ratio (OR) = 2.3, 95% confidence limits= 0.8-6.9, χ² (Yates uncorrected)= 2.88, p=0.09. GG genotype = susceptible

6. Genotype. AA vs AC/CC for OCOPD vs resistant, Odds ratio (OR) =1.8, 95% confidence limits=l.0-3.1, χ² (Yates corrected)=3.8, p=0.05. AA =susceptibility

7. Genotype. AA vs AC/CC for OCOPD vs controls, Odds ratio (OR) =1.6, 95% confidence limits 1.0-2.6, χ² (Yates uncorrected)=3.86, p=0.05. AA = susceptibility

2017265006 21 Nov 2017

-61 8. Genotype. CC vs CG/GG for OCOPD vs controls, Odds ratio (OR) =1.6, 95% confidence limits=1.0-2.6, χ² (Yates uncorrected)=3.68, p=0.05. CC =susceptibility

9. Genotype. CC vs CG/GG for OCOPD vs resistant, Odds ratio (OR) =1.8, 95% confidence limits 1.0-3.2, χ² (Yates corrected)= 4.10, p=0.04. CC =susceptibility

10. Genotype. AA vs AT/TT for OCOPD vs resistant, Odds ratio (OR) =1.8, 95% confidence limits= 0.9-3.6, χ² (Yates uncorrected)=2.88, p=0.09. AA = protective

11. Allele. A vs T for OCOPD vs resistant, Odds ratio (OR) =1.3, 95% confidence limits= 0.9-2.0, χ² (Yates uncorrected)= 2.3, p=0.15. A = protective

12. Genotype. AA vs AC/CC for resistant vs OCOPD, Odds ratio (OR) =3.2, 95% confidence limits = 1.0-11.0, χ² (Yates corrected)= 3.89, p=0.05. AA genotype = protective

13. Allele. A vs C for resistant vs OCOPD, Odds ratio (OR) =1.7, 95% confidence limits 1.1-2.6, χ² (Yates corrected)=6.24, p=0.01. A allele = protective

14. Genotype. CC vs AC7AA for OCOPD vs resistant, Odds ratio (OR) =1.8, 95% confidence limits = 1.0-3.3, χ² (Yates corrected)= 4.29, p=0.04. CC genotype = susceptibility

15. Genotype. TT/TG vs GG for resistant vs OCOPD, Odds ratio (OR) =1.9, 95% confidence limits= 1.0-38, χ² (Yates uncorrected)= 4.08, p=0.04. TT/TG genotype = protective

16. Allele. T vs G for resistant vs OCOPD, Odds ratio (OR) =1.3, 95% confidence limits 0.9-2.0. χ² (Yates uncorrected)=2.36, p=0.12. A allele = protective

17. Genotype. GG vs TT/TG for OCOPD vs resistant, Odds ratio (OR) =0.5, 95% confidence limits= 0.3-1.0, χ² (Yates uncorrected)= 4.1, p=0.04. GG genotype = susceptible

18. Genotype. RR vs Rr/rr for resistant vs OCOPD, Odds ratio (OR) = 2.3, 95% confidence limits= 0.9-5.8 , χ² (Yates uncorrected)= 3.7, p=0.05, RR genotype = protective

19. Genotype. AG/GG vs AA for resistant vs OCOPD, Odds ratio (OR) = 10.8, 95% confidence limits= 1.4-229, χ² (Yates corrected)= 5.99 p=0.01. AG/GG genotype = protective, AA susceptible

20. Allele. G vs A for resistant vs OCOPD, Odds ratio (OR) =11.3, 95% confidence limits 1.5-237, χ (Yates corrected)=6.77, p=0.001. G allele = protective, A susceptible

21. Genotype. MS vs MM for Resistant vs OCOPD, Odds ratio (OR) =2.7, 95% confidence limits 0.8-9.0, χ² (Yates uncorrected)= 3.4, p=0.07. MS=protective

22. Allele: S vs M allele for resistant vs OCOPD, Odds ratio (OR) =2.5, 95% confidence limits 0.88.4, χ² (Yates uncorrected)= 3.24, p=0.07.

23. Genotype AG vs AA in resistant vs OCOPD, Odd’s Ratio (OR)= 5.61, 95% confidence limits 0.5 146, χ² (Yates uncorrected)= 2.66, p=0.10. AG = protective

24. Genotype. CC vs CG/GG for resistant vs OOCOPD, Odds ratio (OR) = 1.75, 95% confidence limits = 1.0-3.2, χ² (Yates uncorrected)= 3.73, p=0.05. CC =protective

25. Genotype: AA vs AG/GG for resistant vs OCOPD, Odd’s Ratio (OR)=1.6, 95% confidence limits 0.8-32, χ² (Yates uncorrected)= 2.02, p=0.16. AA = protective

26. Genotype. TT vs TC/CC for OCOPD vs resistant, Odds ratio (OR) =6.03, 95% confidence limits 1.1-42, χ² (Yates correeted)= 4.9, p=0.03. TT=susceptible

2017265006 21 Nov 2017

-6227. Genotype. 5G5G vs rest for OCOPD vs resistant, Odds ratio (OR) =1.9, 95% confidence limits

0.9-4.0, χ² (Yates uncorrected)= 3.11, p=0.08. 5G5G = susceptible

28. Allele. 5G vs 4G for OCOPD vs resistant, Odds ratio (OR) =1.4, 95% confidence limits 0.9-2.1, χ² (Yates corrected)=3.1, p=0.08. 5G = susceptible

29. Genotype. TT vs TG/GG for resistant vs controls, Odds ratio (OR) =2.3, 95% confidence limits 1.0-5.5, χ² (Yates corrected)= 3.80, p=0.05. TT genotype =protective

30. Genotype. TT vs TG/GG for resistant vs OCOPD, Odds ratio (OR) =1.9, 95% confidence limits 0.8-5.0, χ² (Yates uncorrected)= 2.49, p=0.11. TT genotype =protective

31. Genotype: Tt/tt vs TT for COPD vs controls, Odd’s Ratio (OR) =3.34, 95% confidence limits 1.3 8.9, χ² (Yates corrected) = 6.28, p=0.01. Tt/tt = susceptible to OCOPD

32. Allele: t vs T for COPD vs controls, Odd’s Ratio (OR) 2.5. 95% confidence limits 1.0-6.3, χ² (Yates corrected)= 4.1, p=0.04. t = susceptible to OCOPD

33. Genotype. 2G2G vs 1G1G/1G2G for COPD vs controls, Odds ratio (OR) =2.1, 95% confidence limits 1.1-4.1, χ² (Yates eorrected)= 5.44, p=0.02. 2G2G genotype =susceptible for OCOPD

34. Allele. 2G vs 1G for COPD vs controls, Odds ratio (OR) =1.7, 95% confidence limits 1.2-2.5, χ² (Yates corrected)= 7.97, p=0.005. 2G = susceptible for OCOPD

Table 7 below provides a summary of the protective and susceptibility polymorphisms determined for OCOPD.

Table 7. Summary of protective and susceptibility polymorphisms for OCOPD

Gene	Polymorphism	Role
Cyclo-oxygenase (Cox) 2	Cox 2 -765 G/C	CC/CG protective GG susceptible
P2-adrenoreceptor (ADRB2)	ADRB2 Gin 27Glu	CC protective
Interleukin -18 (IL-18)	IL-18-133 C/G	CC susceptible
Interleukin -18 (IL-18)	IL-18 105 A/C	AA susceptible
Plasminogen activator inhibitor 1 (PAI-1)	PAI-1 -675 4G/5G	5G5G susceptible
Nitric Oxide synthase 3 (NOS3)	NOS3 298 Asp/Glu	TT protective
Vitamin D Binding Protein (VDBR)	VDBR Lys 420 Thr	AA protective CC susceptible
Vitamin D Binding Protein (VDBR)	VDBP Glu 416 Asp	TT/TG protective GG susceptible
Glutathione S Transferase (GSTP1)	GSTP1 IlelO5Val	GG susceptible
Superoxide dismutase 3 (SOD3)	SOD3 Arg 312 Gin	AG/GG protective

-63 2017265006 21 Nov 2017

		AA susceptible
a 1 -antitrypsin (alAT)	alAT 3’ 1237 G/A (T/t)	Tt/tt susceptible
a 1 -antitrypsin (a 1 AT)	alAT S allele	MS protective
Toll-like receptor 4 (TLR4)	TLR4 Asp 299 Gly A/G	AG/GG protective
Interleukin-8 (IL-8)	IL-8 -251 AT	AA protective
Interleukin 11 (IL-11)	IL-11 -518 G/A	AA protective
Microsomal epoxide hydrolase (MEH)	MEH Exon 3 T/C (r/R)	RR protective
Interleukin 13 (IL-13)	IL-13 -1055 C/T	TT susceptible
Matrix Metalloproteinase 1 (MMP1)	MMP1 -1607 1G/2G	2G2G susceptible

The combined frequencies of the presence or absence of the selected protective genotypes COX2 -765 CC/CG, NOS3 298 TT, alAT MS/SS, SOD3 AG/GG, MEH Exon 3 RR, and VDBP 420 AA observed in the OCOPD subjects and in resistant smokers is presented below in Table 8.

Table 8. Combined frequencies of the presence or absence of protective genotypes in OCOPD subjects and in resistant smokers.

	Number of protective polymorphisms
Cohorts	0	1	>2	Total
OCOPD	34 (27%)	51 (41%)	39 (32%)	124
Resistant smokers	20 (19%)	31 (30%)	53 (51%)	104
% of smokers with OCOPD	34/54 (63%)	51/82 (62%)	39/92 (42%)

Comparison	Odd’s ratio	95% CI	/2	P value
0 vs 1 vs 2+, Resist vs OCOPD	-	-	16.2	0.003
2+ vs 0-1, Resist vs OCOPD	2.3	1.3-4.0	8.15	0.004
0 vs 2+, OCOPD vs Resist	2.3	1.1-4.9	4.97	0.03

The combined frequencies of the presence or absence of the selected susceptibility genotypes MMP1 -1607 2G2G, GSTP1 105 GG, PAI-1 -675 5G5G, IL-13 -1055 TT, and VDBP 416 GG, observed in the OCOPD subjects and in resistant smokers is presented below in Table 9.

2017265006 21 Nov 2017

-64Table 9. Combined frequencies of the presence or absence of selected susceptibility genotypes in OCOPD subjects and in resistant smokers.

	Number of protective polymorphisms
Cohorts	0	1	>2	Total
OCOPD	45 (36%)	55 (44%)	24 (20%)	124
Resistant smokers	55 (54%)	37 (37%)	9 (9%)	101
% of smokers with OCOPD	45/100 (45%)	55/92 (60%)	24/33 (73%)

Comparison	Odd’s ratio	95% CI	χ2	P value
0 vs 1 vs 2+, OCOPD vs Resist	-	-	9.1	0.01
2+ vs 0-1, OCOPD vs Resist	2.5	1.0-6.0	4.05	0.04
0+ vs 1-2+, Resist vs OCOPD	2.1	1.2-3.7	6.72	0.01

Protective polymorphisms were assigned a score of +1 while susceptibility polymorphisms were assigned a score of-I. For each subject, a net score was then calculated according to the presence of susceptibility and protective genotypes. This produced a linear spread of values, as shown in Table 10. When assessed as a range between -2 to +3, a linear relationship as depicted in Figure 3 was observed. This analysis indicates that for subjects with a net score of -1 or less, there was an approximately 70% or greater risk of having OCOPD. In contrast, for subjects with a net score of 2+ or greater, the risk was approximately 25% (see Figure 3).

Table 10. Combined presence or absence of protective and susceptibility polymorphisms

	Score combining protective and susceptibility polymorphisms
	_2	-1	0	1	2	3
OCOPD n=T24	8	28	33	39	11	5
Resistant n=T01	2	11	23	27	23	15
% OCOPD	80%	72%	59%	59%	32%	25%

-65 2017265006 21 Nov 2017

EXAMPLE 3. CASE ASSOCIATION STUDY - LUNG CANCER

METHODS

Subject recruitment

Subjects of European decent who had smoked a minimum of fifteen pack years and diagnosed with lung cancer were recruited. Subjects met the following criteria: diagnosed with lung cancer based on radiological and histological grounds, including primary lung cancers with histological types of small cell lung cancer, squamous cell lung cancer, adenocarinoma of the lung, non-small cell cancer (where histological markers can not distinguish the subtype) and broncho-alveolar carcinoma. Subjects could be of any age and at any stage of treatment after the diagnosis had been confirmed. One hundred and nine subjects were recruited, of these 58% were male, the mean FEV1/FVC (± 95% confidence limits) was 51% (49-53), mean FEV1 as a percentage of predicted was 43 (41-45). Mean age, cigarettes per day and pack year history was 65 yrs (64-66), 24 cigarettes/day (22-25) and 50 pack years (41-55) respectively. Two hundred and seventeen European subjects who had smoked a minimum of twenty pack years and who had never suffered breathlessness and had not been diagnosed with an obstructive lung disease or lung cancer in the past were also studied. This control group was recruited through clubs for the elderly and consisted of 63% male, the mean FEV1/FVC ( 95%CI) was 82% (81-83), mean FEV1 as a percentage of predicted was 96 (95-97). Mean age, cigarettes per day and pack year history was 59 yrs (57-61), 24 cigarettes/day (22-26) and 42 pack years (39-45) respectively. Using a PCR based method [1], all subjects yvere genotyped for the otlantitrypsin mutations (S and Z alleles) and those with the ZZ allele were excluded. 190 European blood donors (smoking status unknown) were recruited consecutively through local blood donor services. Sixty-three percent were men and their mean age was 50 years. On regression analysis, the age difference and pack years difference observed between lung cancer sufferers and resistant smokers was found not to determine FEV or lung cancer.

This study shows that polymorphisms found in greater frequency in lung cancer patients compared to resistant smokers may reflect an increased susceptibility to the development of lung cancer. Similarly, polymorphisms found in greater frequency in resistant smokers compared to lung cancer may reflect a protective role.

2017265006 21 Nov 2017

-66Summary of characteristics.

Parameter	Lung Cancer	Resistant smokers	Differences
Median (IQR)	N-109	N-200
% male	52%>	64%	ns
Age (yrs)	68 (11)	60 (12)	P<0.05
Pack years	40 (31)	43 (25)	P<0.05
Cigarettes/day	18(11)	24(12)	ns
FEV1 (L)	1.7(0.6)	2.8 (0.7)	P<0.05
FEV1 % predict	67(22 )	96% (10)	P<0.05
FEV1/FVC	59 (14)	82 (8)	P<0.05

Means and 95% confidence limits

Glutathione S-transferase null polymorphisms genotyping

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [7, incorporated herein in its entirety by reference], Genotyping was done using minor modifications of the above protocol optimised for our own laboratory conditions The PCR reactions were amplified in MJ Research thermocyciers in a total volume of 25 μΐ and contained 80ng genomic DNA, 100 ng forward and reverse primers, 200mM dNTPs, 20 mM Tris-HCL (pH 8.4), 50 mM KC1, 2.5 mM MgC12 and 1.0 unit of Taq polymerase (Qiagen). Forward, internal (GSTM4) and reverse prime sequences were 5’ CTGCCCTACTTGATTGATGG-3’ [SEQ.ID.NO.192], 5’ ATCTTCTCCTCTTCTGTCTC -3’ [SEQ.ID.NO.193] and 5’TTCTGGATTGTAGCAGATCA -3’ [SEQ.ID.NO.194], Cycling conditions consisted of 94C 60 s, 59C 30s, 72C 30 s for 35 cycles with an extended last extension of 3 min. Digested products were separated on 3% agarose gel. The products were visualised by ultraviolet transiliumination following ethidium bromide staining and migration compared against a 1Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

2017265006 21 Nov 2017

-67Cyclooxygenase 2 polymorphisms genotyping

Genomic DNA was extracted from whole blood samples (Maniatis,T., Fritsch, E. F. and Sambrook, J., Molecular Cloning Manual. 1989). The Cyclo-oxygenase 2 -765 polymorphism was determined by minor modifications of a previously published method (Papafiii A, et al., 2002, incorporated in its entirety herein by reference)). The PCR reaction was carried out in a total volume of 25ul and contained 20 ng genomic DNA, 500pmol forward and reverse primers, 0.2mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KC1, 1.0 mM MgCh and 1 unit of polymerase (Life Technologies). Cycling times were incubations for 3 min at 95°C followed by 33 cycles of 50s at 94°C, 60s at 66°C and 60s at 72°C. A final elongation of 10 min at 72°C then followed. 4ul of PCR products were visualised by ultraviolet trans-illumination of a 3% agarose gel stained with ethidium bromide. An aliquot of 3ul of amplification product was digested for 1 hr with 4 units of Acil (Roche Diagnostics, New Zealand) at 37°C. Digested products were separated on a 2.5% agarose gel run for 2.0 hours at 80 mV with TBE buffer. The products were visualised against a 123bp ladder using ultraviolet transillumination after ethidium bromide staining.

Matrix metalloproteinase 1 -16071G/2Gpolymorphisms genotyping

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [Dunleavey L, et al], Genotyping was done using minor modifications of the above protocol optimised for our own laboratory conditions The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25 pi and contained 80ng genomic DNA, 100 ng forward and reverse primers, 200mM dNTPs, 20 mM Tris-HCL (pH 8.4), 50 mM KC1, 1.5 mM MgCh and 1.0 unit of Taq polymerase (Qiagen). Forward and reverse prime sequences were 3’ TCGTGAGAATGTCTTCCCATT-3’ [SLQ.ID.NO.195] and 5’TCTTGGATTGATTTGAGATAAGTGAAATC-3’ [SEQ.ID.NO.196], Cycling conditions consisted of 94C 60 s, 55C 30s, 72C 30 s for 35 cycles with an extended last extension of 3 min. Aliquots of amplification product were digested for 4 hrs with 6 Units of the restriction enzymes XmnI (Roche Diagnostics, New Zealand) at designated temperature conditions. Digested products were separated on 6% polyacrylamide gel. The products were visualised by ultraviolet transillumination following ethidium

2017265006 21 Nov 2017

-68 bromide staining and migration compared against a 1Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Polymorphism genotyping using the Sequenom Autoflex Mass Spectrometer

Genomic DNA was extracted from whole blood samples [2], Purified genomic DNA was aliquoted (10 ng/ul concentration) into 96 well plates and genotyped on a SequenomTM system (SequenomTM Autoflex Mass Spectrometer and Samsung 24 pin nanodispenser) using the following sequences, amplification conditions and methods. The following conditions were used for the PCR multiplex reaction: final concentrations were for lOxBuffer 15 mM MgC12 1.25x, 25mM MgC12 1.625mM, dNTP mix 25 mM 500uM, primers 4 uM lOOnM, Taq polymerase (Quiagen hot start) 0.15U/reaction, Genomic DNA 10 ng/ul. Cycling times were 95°C for 15 min, (5°C for 15 s, 56°C 30s, 72°C 30s for 45 cycles with a prolonged extension time of 3min to finish. We used shrimp alkaline phosphotase (SAP) treatment (2ul to 5ul per PCR reaction) incubated at 35°C for 30 min and extension reaction (add 2ul to 7ul after SAP treatment) with the following volumes per reaction of: water, 0.76ul; hME lOx termination buffer, 0.2ul; hME primer (lOuM), lul; MassEXTEND enzyme, 0.04ul.

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2017265006 21 Nov 2017

RESULTS

Frequencies of individual polymorphisms are as follows:

Table 11. Polymorphism allele and genotype frequencies in the Lung cancer patients, resistant smokers and controls.

Nitric oxide synthase 3 Asp 298 Glu (T/G)	Genotype
Frequency	Allele*
	T	G	TT	TG	GG
Controls n=183 (%)	108 (30%)	258 (70%)	13 (7%)	82 (45%)	88 (48%)
Lung Cancer n=107 (%)	71 (33%)	143 (67%)	9 (8%)	53 (50%)	45 (42%)
Resistant n=198 (%)	135 (34%)	261 (66%)	28¹·² (14%)	79 (40%)	91 (46%)

Nitric oxide synthase 3 Frequency	-786 T/C Allele*	Genotype
	C	T	CC	CT	TT
Controls n=183 (%)
Lung Cancer n=107 (%)	82 (38%)	132 (62%)	16 (15%)	50 (47%)	41³ (38%)
Resistant n=198 (%)	166 (42%)	228 (58%)	31 (16%)	104(53%)	62 (31%)

Super oxide dismutase Frequency	3 Arg 312 Gin C/G Allele*	Genotype
	C	G	CC	CG	GG
Controls n=190 (%)	371 (98%)	9 (2%)	183 (96%)	5 (3%)	2 (1%)
Lung Cancer n=104 (%)	208 (100%)	0 (0%)	104(100%)	0 (0%)	0 (0%)
Resistant n=l 82 (%)	390 (98%)	10(3%)	191 (95%)	8⁴ (4%)	I⁴ (1%)

XRCC1 Arg 399 Gin A Frequency	/G Allele*	Genotype
	A	G	AA	AG	GG
Controls n=190 (%)
Lung Cancer n=I03 (%)	68 (33%)	138 (67%)	4 (4%)	60 (58%)	39 (38%)
Resistant n= 193 (%)	132 (34%)	254 (66%)	18⁵ (9%)	96 (50%)	79 (41%)

Interleukin 8 -251 A/T

2017265006 21 Nov 2017

Frequency	Allele*	Genotype
	A	T	AA	AT	TT
Controls n=188 (%)	175 (47%)	201 (53%)	39(21%)	97 (52%)	52 (28%)
Lung Cancer n - 90	68 (38%)	112(62%)	6 (7%)	56 (52%)	28 (31%)
Resistant n=199 (%)	192⁷ (48%)	206 (52%)	45⁶ (23%)	102 (51%)	52 (26%)

Anti-chymotrypsin Ala Frequency	-15 Thr Allele*	Genotype
	A	G	AA	AG	GG
Lung Cancer 11= 108	99 (46%)	117⁹ (54%)	24 (22%)	51 (47%)	33⁸ (31%)
Resistant n=196 (%)	207 (53%)	185 (47%)	52 (27%)	103 (53%)	41 (21%)

Cyclin DI A 870 G Frequency	Allele*	Genotype
	A	G	AA	AG	GG
Lung Cancer n= 107	109 (51%)	105 (49%)	25¹¹ (23%)	59 (55%)	23 (21%)
Resistant n=199 (%)	188 (47%)	210(53%)	45 (23%)	98 (49%)	56¹⁰ (28%)

Interleukin IB -511 A/( Frequency	Allele*	Genotype
	A	G	AA	AG	GG
Lung Cancer n= 107	64 (30%)	150 (70%)	12(11%)	40 (37%)	55¹² (51%)
Resistant n=198 (%)	143 (36%)	253 (64%)	23 (12%)	97 (49%)	78 (39%)

FAS (Apo-l/CD 95) A - Frequency	670 G Allele*	Genotype
	A	G	AA	AG	GG
Lung Cancer n= 106	121¹⁴ (57%)	91 (43%)	32¹³ (30%)	57 (54%)	17 (16%)
Resistant n=198 (%)	202 (51%)	194 (49%)	45 (23%)	112 (57%)	41 (21%)

XPD 751 T/G Frequency	Allele*	Genotype
	G	T	GG	TG	TT
Lung Cancer n=108	72 (33%)	144 (66%)	11 (10%)	50 (46%)	47 (44%)
Resistant n= 197 (%)	147 (37%)	247 (63%)	31¹⁵ (16%)	85 (43%)	81 (41%)

2017265006 21 Nov 2017


Cytochrome P450 1A1 Frequency	lie 462 Val G/A Allele*	Genotype
	G	A	GG	AG	AA
Lung Cancer n=109	5 (2%)	213 (98%)	0 (0%)	5 (5%)	104¹⁶ (95%)
Resistant n=199 (%)	20 (5%)	378 (95%)	13¹⁶ (1%)	18¹⁶ (9%)	180² (90%)

MMP12 Asn 357 Ser Frequency	Allele*	Genotype
	G	A	GG	AG	AA
Lung Cancer n=109	8 (4%)	210(96%)	1 (1%)	6 ( 5%)	102 (94%)
Resistant n=199 (%)	21 (5%)	377 (95%)	0¹⁷ (0%)	21¹⁷ (11%)	178 (89%)

8-oxoguanine DNA glyt Frequency	:osylase Ser 326 Cys C/G Allele*	Genotype
	G	C	GG	CG	CC
Lung Cancer· n=109	40(18%)	178 (82%)	2 (2%)	36 (33%)	71 (65%)
Resistant n=199 (%)	100 (25%)	298 (75%)	14¹⁸ (7%)	72 (36%)	113 (57%)

N-Acetyltransferase 2 / Frequency	Vrg 197 Gin G/A Allele*	Genotype
	A	G	AA	AG	GG
Lung Cancer n=106	55 (26%)	157 (74%)	9 (8%)	37 (35%)	60¹⁹ (57%)
Resistant n=195 (%)	122 (31%)	268 (69%)	17 (9%)	88 (45%)	90 (46%)

Cytochrome P450 2E1 Frequency	1019 G/C Pstl Allele*	Genotype
	C	G	CC	CG	GG
Lung Cancer n=109	10 (5%)	208 (95%)	0 (0%)	10^2l! (9%)	99 (91%)
Resistant n= 197 (%)	li (3%)	383 (97%)	0 (0%)	11 (6%)	186 (94%)

Cytochrome P450 2E1 Frequency	C/T Rsa 1 Allele*	Genotype
	T	C	TT	TC	CC
Lung Cancer n=T08	11 (5%)	205 (95%)	0 (0%)	11²¹ (10%)	97 (90%)

2017265006 21 Nov 2017

Resistant n=198 (%)	11 (3%)	385 (97%)	0 (0%)	11 (6%)	187 (94%)

Interleukin 18 105 A/C Frequency	Allele*	Genotype
	C	A	CC	AC	AA
Lung Cancer n=107	50 (23%)	164 (77%)	8 (8%)	34 (33%)	65²² (61%)
Resistant n=200 (%)	116(29%)	284 (71%)	17²² (9%)	82²² (41%)	101 (50%)

Interleukin 18 -133 C/C Frequency	r Allele*	Genotype
	G	C	GG	CG	CC
Lung Cancer n=109	52 (24%)	166(76%)	8 (7%)	36 (33%)	65²³ (60%)
Resistant n=198 (%)	117(30%)	279 (70%)	17²³ (9%)	83” (42%)	98 (49%)

Glutathione S-Transfei Frequency	ase M null Allele*
	Null	Wild
Controls n=178	75 (42%)	103 (58%)
Lung Cancer n=107	67²⁴ (58%)	48 (42%)
Resistant n=182	100 (55%)	82 (45%)

Interferon-gamma 874 Frequency	A/T Allele*	Genotype
	A	T	AA	AT	TT
Controls n=I86 (%)	183 (49%)	189 (51%)	37 (20%)	109 (58%)	40 (22%)
Lung cancer n=106 (%)	116(55%)	96 (45%)	3425.26 (₃₂%)	48 (45%)	24 (23%)
Resistant n=196 (%)	209 (53%)	183 (47%)	50 (26%)	109 (56%)	37 (19%)

Cyclooxygenase -765 C Frequency	tG Allele*	Genotype
	C	G	CC	CG	GG
Controls n=95 (%)	27 (14%)	161 (86%)	3 (3%)	21 (22%)	70 (75%)
Lung Cancer n=109 (%)	34(16%)	184 (84%)³⁰	5 (5%²⁷)	24 (22%)²⁷	80 (73%)²⁹
Resistant n=I58(%)	75 (24%)^2S	241 (76%)	11 (7%)	53 (34%)	94 (59%)

2017265006 21 Nov 2017

Matrix metalloproteinase 1 -1607 1G/2G	Genotype
Frequency	Allele*
	1G	2G	1G1G	1G2G	2G2G
Controls n=174 (%)	214(61%)	134 (39%)	68 (39%)	78 (45%)	28 (16%)
Lung Cancer n=67 (%)	58 (43%)	76 (57%)³²	13 (19%)	32 (48%)	22 (33%)³¹
Resistant n=171 (%)	167 (49%)	175 (51%)	41 (24%)	85 (50%)	45 (26%)

* number of chromosomes (2n)

1. Genotype. TT vs TG/GG for resistant vs lung cancer. Odds ratio (OR) =1.8, 95% confidence limits 0.8

4.3, χ² (Yates uncorrected)= 2.14, p=0.14, TT genotype =protective

2. Genotype. TT vs TG/GG for resistant vs controls, Odds ratio (OR) =2.2, 95% confidence limits 1.04.6, χ² (Yates corrected)= 4.2, p=0.04, TT genotype =protective

3. Genotype. TT vs CC/CT for Lung cancer vs resistant, Odds ratio (OR) =1.4. 95% confidence limits

0.8-2.3, χ² (Yates uneorrected)= 1.45, p=0.23, TT genotype =susceptible

4. Genotype CG/GG vs CC for resistant vs lung cancer, Yates uncorrected=3.38, P=0.07 and Fisher’s

Two tailed test, P=0.03. CG/GG=protective

5. Genotype. AA vs AG/GG for resistant vs lung cancer, Odds ratio (OR) = 2.6, 95% confidence limits

0.8-9.2, χ² (Yates uncorrected)= 2.89, p=0.09. AA genotype = protective

6. Genotype. AA vs AT/TT for resistant vs lung cancer, Odds ratio (OR) =4.1, 95% confidence limits=l .6=11.2, χ² (Yates correeted)=9.8, p=0.002, AA= protective

7. Allele. A vs T for resistant smokers vs lung cancer, Odds ratio (OR) =1.5, 95% confidence limits 1.02.2, χ² (Yates corrected)= 5.07, p=0.02, A=protective

8. Genotype. GG vs .MV'AG for Lung cancer vs resistant, Odds ratio (OR) = 1.7, 95% confidence limits=

0.9-2.9, χ (Yates uneorrected)=3.51, p=0.06, GG =susceptible

9. Allele. G vs A for lung cancer vs resistant smokers. Odds ratio (OR) =1.3, 95% confidence limits 0.91.9, χ² (Yates uncorrected)= 2.71, p=0.10, G=susceptible

10. Genotype. GG vs AG/'AA for Resistant vs lung cancer. Odds ratio (OR) =1.4, 95% confidence limits=0.8-2.6, χ² (Yates uncorrected)=1.6, p=0.20, GG =protective

2017265006 21 Nov 2017

11. Genotype. AG/AA vs GG for Lung cancer vs resistant. Odds ratio (OR) =1.4, 95% confidence limits=0.8-2.6, χ² (Yates uneorrected)=1.6, p=0.20, AA =susceptibie

12. Genotype. GG vs AA/AG for Lung cancer vs resistant, Odds ratio (OR) = 1.6, 95% confidence limits= 1-2.7, χ² (Yates uncorrected)= 4.07, p=0.04, GG =susceptible

13. Genotype. AA vs AG/GG for Lung cancer vs resistant, Odds ratio (OR) =1.5, 95% confidence limits=0.8-2.6, χ² (Yates uncorrected)=2.03, p=0.15, AA =susceptible

14. Allele. A vs G for Lung cancer vs resistant. Odds ratio (OR) =1.3, 95% confidence limits 0.9-1.8, χ² (Yates uncorrected)= 2.04, p=0.15, Λ susceptible

15. Genotype. GG vs TG/TT for Resistant vs lung cancer, Odds ratio (OR) =1.7, 95% confidence limits=

0.8-3.7, χ² (Yates uncorreeted)= 1.81, p=0.18, GG =protective

16. Genotype. AG/GG vs AA for Resistant vs lung cancer, Odds ratio (OR) =2.2, 95% confidence limits= 0.7-6.9, χ² (Yates uncorrected)=2.41, p=0.12, GG/AG =protective, AA=suseeptible

17. Genotype. GG/AG vs AA for Resistant vs COPD, Odds ratio (OR) =1.7, 95% confidence limits= 0.74.6, χ² (Yates uncorrected)=l .45, p=0.23, GG/AG =protective

18. Genotype. GG vs CG/CC for Resistant vs lung cancer, Odds ratio (OR) =4.0, 95% confidence limits=0.9-26.3, χ² (Yates uncorrected)=3.87, p=0.05, GG =protective

19. Genotype. GG vs AG/AA for Lung cancer vs resistant, Odds ratio (OR) =1.5, 95% confidence iimits=0.9-2.5, χ² (Yates uncorrected)=3.0, p=0.08, GG =suseeptible

20. Genotype. CG vs GG for Lung cancer and resistant, Odds ratio (OR) =1.7, 95% confidence limits=0.7·

4.5, χ² (Yates uncorrected)=1.42, p=0.23, CG =susceptible

21. Genotype. TC vs CC for Lung cancer and resistant, Odds ratio (OR) =1.9, 95% confidence limits=0.85.0, χ² (Yates uncorrected)=2.24, p=0.13, TC =susceptible

22. Genotype. AA vs AC/CC for Lung cancer and resistant, Odds ratio (OR) =1.6, 95% confidence limits= 1.0-2.6, χ² (Yates uncorrected)=3.51, p=0.06, AA =susceptible, AC/CC protective

23. Genotype. CC vs CG/GG for Lung cancer and resistant, Odds ratio (OR) =1.5, 95% confidence limits=0.9-2.5, χ² (Yates uncorrected)=2.90, p=0.09. CC =susceptible, CG/GG protective

2017265006 21 Nov 2017

24. Genotype. Null vs wild for Lung cancer and controls, Odds ratio (OR) =1.92, 95% confidence limits=1.2-3.2, χ² (Yates corrected)=6.64, p=0.01, Null =susceptible

25. Genotype. AA vs A1 11 for lung cancer vs resistant. Odds ratio (OR) =1.4, 95% confidence limits

0.8-2.4, χ² (Yates uncorrected)= 1.48, p=0,22, AA genotype = susceptible

26. Genotype. AA vs Λ1 11 for lung cancer vs controls. Odds ratio (OR) =1.9, 95% confidence limits

1.1-3.4, χ² (Yates corrected)= 5.45, p=0.02, AA genotype = susceptible to lung cancer

27. Genotype. CC/CG vs GG for Lung cancer vs resistant, Odds ratio (OR) =0.53, 95% confidence iimits=0.3-0.9, χ² (Yates corrected)= 4.9, P=0.03 CC/CG =protective

28. Allele. C vs G for Lung cancer vs resistant, Odds ratio (OR) =0.59, 95% confidence limits 0.4- 0. 9, χ² (Yates corrected)= 4.8, p=0.03, C =protective

29. Genotype. GG vs CG/CC for Lung cancer vs resistant, Odds ratio (OR) =1.88, 95% confidence limits=l. 1-3.3, χ² (Yates corrected)= 4.9, P=0.03 GG =susceptibie (when compared against resistant smokers but not controls)

30. Allele. G vs C for Lung cancer vs resistant, Odds ratio (OR) =1.7, 95% confidence limits 1.1- 2.7, χ² (Yates corrected)= 4.8, p=0.03, G =susceptible (when compared against resistant smokers but not controls)

31. Genotype. 2G2G vs 1G1G/1G2G for Lung cancer vs controls, Odds ratio (OR) =2.55, 95% confidence limits 1.3-5.1, χ² (Yates corrected)= 7.3, p=0.007 2G2G genotype =susceptible

32. Allele. 2G vs 1G for Lung cancer vs controls, Odds ratio (OR) =2.1, 95% confidence limits 1.4-3.2, χ² (Yates corrected)= 12.3, p=0.0004, 2G = susceptible

Connective tissue growth factor (CTGF) -447 G/C polymorphism allele and genotype frequencies in the lung cancer and resistant smokers.

Frequency	Allele*	Genotype
	G	C	GG	GC	CC
Lung cancer n=109	201	17	92	17	0
(%)	(92%)	(8%)	(84%)	(16%)	(0%)
Resistant n=200	379	21	179	21	0
(%)	(95%)	(5%)	(90%)	(10%)	(0%)

2017265006 21 Nov 2017 * number of chromosomes (2n)

1. Genotype. GC/CC vs GG for lung cancer vs resistant, Odds ratio (OR) =1.6, 95% confidence limits 0.8-3.3, χ^{1 2} (Yates uncorrected)= 1.70, p=0.19,

GC/CC genotype = susceptibility (trend)

Mucin SAC (Muc5AC) -221 C/T polymorphism allele and genotype frequencies in the lung cancer and resistant smokers.

Frequency	Allele*	Genotype
	C	T	CC	CT	TT
Lung cancer n=109	177	41	73	31	5
(%)	(81%)	(19%)	(67%)	(28%)	(5%)
Resistant n=195	296	94 (24%)	119	58	18
(%)	(76%)		(61%)	(30%)	(9%)

* number of chromosomes (2n)

1. Genotype. TT vs CC/CT for lung cancer vs resistant, Odds ratio (OR) =0.47, 95% confidence limits 0.2-1.4, χ² (Yates uncorrected)= 2.16, p=0.14,

TT genotype = protective (trend)

Mannose binding lectin (MBL2) 161 G/A polymorphism allele and genotype frequencies in the lung cancer and resistant smokers.

Frequency	Allele*	Genotype
	G	A	GG	AG	AA
Lung cancer n=105	173	37	71	31	3
(%)	(82%)	(18%)	(67%)	(30%)	(3%)
Resistant n=197	338	56	147	44	6
(%)	(86%)	(14%)	(75%)	(22%)	(3%)

* number of chromosomes (2n)

1. Genotype. AG/AA vs GG for lung cancer vs resistant, Odds ratio (OR) =1.4, 95% confidence limits

0.8-2.4, χ² (Yates uncorreeted)= 1.67, p=0.20,

AG/AA genotype = susceptibility (trend)

2017265006 21 Nov 2017

Nibrin (NBS1) Glnl85Glu G/C polymorphism allele and genotype frequencies in the lung cancer and resistant smokers.

Frequency	Allele*	Genotype
	G	C	GG	GC	CC
Lung cancer n=109	150	68	54	42	13
(%)	(69%)	(31%)	(50%)	(39%)	(12%)
Resistant n=199	295	103	107	81	11
(%)	(74%)	(26%)	(54%)	(41%)	(6%)

* number of chromosomes (2n)

1. Genotype. CC vs CG/GG for lung cancer vs resistant, Odds ratio (OR) =2.3, 95% confidence limits 0.9-5.8, χ^{1 2} (Yates uncorrected)= 4.01, p=0.05,

CC genotype = susceptibility

Arginase 1 (Argl) intron 1 C/T polymorphism allele and genotype frequencies in the lung cancer and resistant smokers.

F requency	Allele*	Genotype
	C	T	CC	CT	TT
Lung cancer n=105	137	73	45	47	13
(%)	(65%)	(35%)	(43%)	(45%)	(12%)
Resistant n=180	203	157	65	73	42
(%)	(56%)	(44%)	(36%)	(41%)	(23%)

* number of chromosomes (2n)

1. Genotype. TT vs CC/CT for lung cancer vs resistant, Odds ratio (OR) =0.46, 95% confidence limits

0.2-0.95, χ² (Yates uncorrected)= 5.11, p=0.02,

TT genotype = protective

2. Allele. T vs C for lung cancer vs resistant, Odds ratio (OR) =0.69, 95% confidence limits 0.5-1.0, χ²(Yates corrected)= 3.96, p=0.05,

T allele = protective

REV1 Phe257Ser C/T polymorphism allele and genotype frequencies in the lung cancer and resistant smokers.

2017265006 21 Nov 2017

Frequency	Allele*	Genotype
	C	T	CC	CT	TT
Lung cancer n=109 (%)	129 (59%)	89(41%)	39 (36%)	51 (47%)	19 (17%)
Resistant n=192	242	142	83	76	33
(%)	(63%)	(37%)	(43%)	(40%)	(17%)

* number of chromosomes (2n)

1. Genotype. CC vs CT/TT for lung cancer vs resistant. Odds ratio (OR) =0.73, 95% confidence limits

0.4-1.2, χ² (Yates uncorrected)= 1.6, p=0.20,

CC genotype = protective (trend)

Insulin-like growth factor II receptor (IGF2R) Leu252Val C/G polymorphism allele and genotype frequencies in the lung cancer and resistant smokers.

Frequency	Allele*	Genotype
	C	G	CC	CG	GG
Lung cancer n=109	190	28	82	26	1
(%)	(87%)	(13%)	(75%)	(24%)	(1%)
Resistant n=198	342	54	150	42	6
(%)	(86%)	(14%)	(76%)	(21%)	(3%)

* number of chromosomes (2n)

1. Genotype. GG vs CC/CG for lung cancer vs resistant, Odds ratio (OR) =0.30, 95% confidence limits 0.01-2.5, χ² (Yates uncorrected)= 1.41, p=0.22 (1-tailed t-test),

GG genotype = protective (trend)

Apex nuclease (ΑΡΕΙ) Aspl48Gln T/G polymorphism allele and genotype frequencies in the lung cancer and resistant smokers.

Frequency	Allele*	Genotype
	T	G	TT	TG	GG
Lung cancer n=109	124	94	39	46	24
(%)	(57%)	(43%)	(36%)	(42%)	(22%)
Resistant n=192	229	155	69	91	32
(%)	(60%)	(40%)	(36%)	(47%)	(17%)

2017265006 21 Nov 2017 * number of chromosomes (2n)

1. Genotype. GG vs TT/TG for lung cancer vs resistant. Odds ratio (OR) =1.4, 95% confidence limits 0.8-2.7, χ² (Yates uncorrected)= 1.3, p=0.25,

GG genotype = susceptibility (trend)

Interleukin 10 (IL-10) -1082 A/G polymorphism allele and genotype frequencies in the lung cancer and resistant smokers.

Frequency	Allele*	Genotype
	G	C	GG	GC	CC
Lung cancer n=98	91	105	16	59	23
(%)	(46%)	(54%)	(16%)	(60%)	(24%)
Resistant n=196	174	218	40	94	62
(%)	(44%)	(56%)	(20%)	(48%)	(32%)

* number of chromosomes (2n)

1. Genotype. GG vs GC/CC for lung cancer vs resistant, Odds ratio (OR) =0.66, 95% confidence limits 0.4-1.2, χ² (Yates uncorrected)= 2.12, p=0.15,

GG genotype = protective (trend)

Table 12 below provides a summary of the protective and susceptibility polymorphisms determined for lung cancer.

Table 12. Summary of protective and susceptibility polymorphisms in Lung Cancer patients relative to resistant smokers (with normal lung function)

Gene	Polymorphism	Role
Nitric Oxide synthase 3 (NOS3)	NOS3 Asp 298 Glu	TT protective
Nitric Oxide synthase 3 (NOS 3)	NOS3 -786 T/C	TT susceptible
Superoxide dismutase 3 (SOD3)	SOD3 Arg 312 Gin	CG/GG protective
XRCC1	XRCC1 Arg 399 Gin G/A	AA protective
Interleukin-8 (IL-8)	IL-8 -251 A/T	AA protective
Anti-chymotrypsin (ACT)	ACT Ala 15 Thr	GG susceptible
Cyclin D (CCND1)	CCND1 A870G	GG protective

2017265006 21 Nov 2017

Interleukin IB (IL-IB)	IL-1B -511 AG	AA susceptible GG susceptible
FAS (Apo-1/CD95)	FAS A-670G	AA susceptible
XPD	XPD -751 G/T	GG protective
CYP1A1	CYP 1A1 He 462 Val AG	GG/AG protective
Matrix metalloproteinase 12 (MMP 12)	MMP12 Asn 357 Ser AG	A A susceptible GG/AG protective
8-Oxoguanine DNA glycolase (OGGI)	OGGI Ser 326 Cys G/C	GG protective
N-aeetyltransferase 2 (NAT2)	NAT2 Ag 197 Gin AG	GG susceptible
CYP2E1	CYP2E1 1019 G/C Pstl	CC/CG susceptible
CYP2E1	CYP2E1 C/T Rsa I	TT/TC susceptible
Interleukin -18 (IL-18)	IL-18 105 AC	AC/CC protective
Interleukin -18 (IL-18)	IL-18 -133 G/C	AA susceptible CG/GG protective
Glutathione S-transferase M	GSTM null	CC susceptible Null susceptible
Interferon gamma (IFNy)	ΙΕΝγ 874 A/T	AA susceptible
Cyclo-oxygenase 2 (COX2)	COX2 -765 G/C	CC/CG protective
Matrix metalloproteinase 1 (MMP1)	MMP -1607 1G/2G	GG susceptible 2G2G susceptible
Connective tissue growth factor (CTGF)	CTGF -447 G/C	GC/CC susceptible
Mucin 5AC (MUC5AC)	MUC5AC -221 C/T	TT protective
Mannose binding lectin 2 (MBL2)	MBL2 +161 G/A	AG/AA susceptible
Nibrin(NBSl)	NBS1 GInl85GluG/C	CC susceptible
Arginase 1 (Argl)	Argl intron 1 C/T	TT protective
REV1	REV1 Phe257Ser C/T	CC protective
Insulin-like growth factor II receptor	IGF2R Leu252Val C7G	GG protective
(IGF2R) Apex nuclease (Apex or APE 1))	Apex Aspl48Glu G/T	GG susceptible
Interleukin 10 (IL-10)	IL-10 -1082 AG	GG protective

The combined frequencies of the presence or absence of the selected protective genotypes CYP1A1 GG/AG, OGGI GG, CCND1 GG, NOS3 298 TT, IL-8 AA, and

2017265006 21 Nov 2017

XRCC1 AA observed in the subjects with lung cancer and in resistant smokers is presented below in Table 13.

Table 13. Combined frequencies of the presence or absence of selected protective genotypes in subjects with lung cancer and in resistant smokers.

	Number of protective polymorphisms
Cohorts	0	1	>2	Total
Lung Cancer	66 (61%)	37 (34%)	6 (6%)	109
Resistant smokers	71 (36%)	86 (43%)	42 (21%)	199
% of smokers with Lung cancer	66/137 (48%)	37/123 (30%)	6/42 (14%)

Comparison	Odd’s ratio	95% CI	χ2	P value
0 vs 1 vs 2+, Resist vs Lung cancer	-	-	22.3	<0.0001
2+ vs 0-1, Resist vs Lung cancer	4.6	1.8-12.5	11.87	0.0005
0 vs 2+, Lung cancer vs Resist	2.8	1.7-4.6	16.7	<0.0001

The combined frequencies of the presence or absence of the selected susceptibility genotypes CYP2E1 1019 CC/CG, FAS AA, IL-1B GG, and ACT 15 GG, observed in the subjects with lung cancer and in resistant smokers is presented below in Table 14.

Table 14. Combined frequencies of the presence or absence of selected susceptibility genotypes in subjects with lung cancer and in resistant smokers.

	Number of susceptibility polymorphisms
Cohorts	0	1	>2	Total
Lung Cancer	21 (19%)	52 (48%)	35 (33%)	108
Resistant smokers	71 (36%)	85 (43%)	42 (21%)	198
% of smokers with COPD	21/92 (23%)	52/137 (38%)	35/77 (45%)

2017265006 21 Nov 2017

Comparison	Odd’s ratio	95% CI	%2	P value
0 vs 1 vs 2+, Lung cancer vs Resist			10.2	0.006
2+ vs 0-1, Lung cancer vs Resist	1.8	1.0-3.1	4.1	0.04
0+ vs 1-2+, Resist vs COPD	2.3	1.3-4.2	8.2	0.004

The combined frequencies of the presence or absence of the selected protective genotypes CYP1A1 GG/AG, OGGI GG, CCND1 GG, NOS3 298 TT, SOD3 CG/GG, XPD GG, MMP12 GG/AG, and XRCC1 AA observed in the subjects with lung cancer and in resistant smokers is presented below in Table 15.

Table 15. Combined frequencies of the presence or absence of selected protective genotypes in subjects with lung cancer and in resistant smokers.

	Number of protective polymorphisms n=8
Cohorts	0	1	>2	Total
Lung Cancer	54 (50%)	50 (46%)	5 (4%)	109
Resistant smokers	67 (34%)	83 (42%)	50 (25%)	199
% of smokers with Lung cancer	54/121 (45%)	50/133 (38%)	5/55 (9%)

Comparison	Odd’s ratio	95% CI		P value
0 vs 1 vs 2+, Resist vs Lung cancer	-	-	21.5	<0.0001
2+ vs 0-1, Resist vs Lung cancer	6.9	2.5-20.5	18.7	<0.0001
0 vs 2 +, Lung cancer vs Resist	2.0	1.2-3.2	6.96	0.008

The combined frequencies of the presence or absence of the selected susceptibility genotypes CYP2E1 1019 CC/CG, FAS AA, IL-1B GG, ACT 15 GG, NAT2 GG, IL-18 105 AA, and IFNy AA, observed in the subjects with lung cancer and in resistant smokers is presented below in Table 16.

2017265006 21 Nov 2017

Table 16. Combined frequencies of the presence or absence of selected susceptibility genotypes in subjects with lung cancer and in resistant smokers.

	Number of susceptibility polymorphisms n=7
Cohorts	1	2	>3	Total
Lung Cancer	16(15%)	35 (32%)	58 (53%)	109
Resistant smokers	65 (33%)	66 (33%)	69 (34%)	200
% of smokers with COPD	16/81 (20%)	35/101 (35%)	58/127 (46%)

Comparison	Odd’s ratio	95% Cl	%2	P value
0 vs 1 vs 2+, Lung cancer vs Resist	-	-	14.6	0.0007
3+ vs 1-2, Lung cancer vs Resist	2.2	1.3-5.6	9.4	0.002
1 vs 2-3+, Resist vs COPD	2.8	1.5-5.4	10.7	0.001

The combined frequencies of the presence or absence of the selected protective genotypes CYP1A1 GG/AG, OGGI GG, CCND1 GG, NOS3 298 TT, IL-8 AA, XRCC1 AA, and Cox 2 -765 CC/CG, observed in the subjects with lung cancer and in resistant smokers is presented below in Table 17.

Table 17. Combined frequencies of the presence or absence of protective genotypes in the exposed smoking subjects (Lung cancer subjects and resistant smokers).

Number of protective genotypes

Cohorts	0	1	>2	Total
Lung Cancer	45 (40%)	50 (43%)	19(17%)	114
Resistant smokers	47 (23%)	79 (40%)	74 (37%)	200
% of smokers with Lung cancer	45/92 (49%)	50/129 (39%)	19/93 (20%)

Comparison	Odd’s ratio	95% CI	%2	P value
0 vs 1 vs 2+, Resist vs Lung cancer	-	-	16.8	0.0002
2+ vs 0-1, Resist vs Lung cancer	2.94	1.6-5.4	13.44	0.0002
0 vs 2+, Lung cancer vs Resist	2.12	1.3-3.6	8.2	0.004

2017265006 21 Nov 2017

The combined frequencies of the presence or absence of the selected susceptibility genotypes CYP2E1 1019 CC/CG, FAS AA. IL-B1 GG, ACT 15 GG, and MMP1 2G2G, observed in the subjects with lung cancer and in resistant smokers is presented below in Table 18.

Table 18. Combined frequencies of the presence or absence of susceptibility genotypes in the exposed smoking subjects (Lung cancer subjects and resistant smokers).

	Number of susceptibility genotypes
Cohorts	0-1	2-3	4-6	Total
Lung Cancer	13 (12%)	66 (61%)	30 (28%)	109
Resistant smokers	54 (27%)	113 (56%)	33 (17%)	200
% of smokers with COPD	13/67 (19%)	66/179 (37%)	30/63 (48%)

Comparison	Odd’s ratio	95% Cl	Z2	P value
0-1 vs 2-3 vs 4-6, Lung cancer vs Resist			11.8	0.003
4-6 vs rest, Lung cancer vs Resist	1.9	1.0-3.5	4.6	0.03
0-1 vs rest. Resist vs COPD	2.7	1.4-5.6	8.6	0.003

Protective polymorphisms were assigned a score of -1 while susceptibility polymorphisms were assigned a score of +1. For each subject, a net score was then calculated according to the presence of susceptibility and protective genotypes. This produced a linear spread of values, as shown in Table 14. When assessed as a range between -2 to +4, a linear relationship as depicted in Figure 4 was observed. This analysis indicates that for subjects with a net score of-2 or less, there was a minimal risk of having lung cancer. For subjects with a net score of -1, there was an approximately one in ten risk of having lung cancer. In contrast, for subjects with a net score of 4+ or greater, the risk was markedly increased to over 70% (see Table 19 and Figure 4).

2017265006 21 Nov 2017

Table 19. Combined presence or absence of protective and susceptibility polymorphisms

	Score combining p	rotective (-1) and susceptibility (+1) polymorphisms
	-2	-1	0	1	2	-> J	4+
Lung cancer	0	2	10	21	38	23	15
N=109(%)	(0%)	(2%)	(9%)	(19%)	(35%)	(21%)	(14%)
Resistant smokers	6	21	39	51	52	25	6
N=200(%)	(3%)	(11%)	(20%)	(26%)	(26%)	(13%)	(3%)
% Lung cancer	0%	9%	20%	29%	42%	48%	71%

A further combined analysis was performed using a greater number of polymorphisms. Again, this produced a linear spread of values, as shown in Table ?. When assessed as a range between -3 to +5, a linear relationship as depicted in Figure 5 was observed. This analysis indicates that for subjects with a net score of-2 or less, there was a minimal risk of having lung cancer. In contrast, for subjects with a net score of 5+ or greater, the risk was markedly increased to 80% (see Table 20 and Figure 5).

Table 20. Combined presence or absence of protective and susceptibility polymorphisms

	SNP score for Lung cancer according to the presence of protective)-1) and susceptibility (+1) genotypes for all smokers
Cohorts	<-3	-2	-1	0	1	2	3	4	5+
Lung cancer	0	1	o J	10	25	32	20	14	4
N=109	(0%)	(1%)	(3%)	(9%)	(23%)	(29%)	(18%)	(13%)	(4%)
Resistant smokers	3	12	16	34	58	48	21	7	1
N=200	(2%)	(6%)	(8%)	(17%)	29%)	(24%)	(11%)	(4%)	(0.5%)
% Lung cancer	0%	7%	16%	23%	30%	40%	49%	67%	80%

DISCUSSION

The methods of the invention allow the determination of risk of disease to be assessed. For example, a simple scoring system in which each polymorphism in a category

2017265006 21 Nov 2017 (i.e. protective or susceptibility) is assigned the same value allows the combined effects of all potentially relevant polymorphisms to be factored into the analysis. In other embodiments, the methods of the invention utilize a scoring system with adjustment (weighting) for the magnitude of the effect of each individual polymorphism, and again allow all polymorphisms to be simultaneously analyzed.

In other embodiments, analyses may utilise path anlaysis and/or Monte-Carlo analysis where the non-genetic and genetic factors can be analyzed.

Similar results were observed in comparing the presence or absence of susceptibility and resistant polymorphisms in smokers with OCOPD, and in smokers with lung cancer and resistant smokers.

The benefit of a net susceptibility score, having been determined for a subject is that it provides the opportunity for early prophylactic and/or therapeutic intervention. Such intervention may be as simple as communicating the net susceptibility score to the subject together with an explanation of the implications of that score. This alone may cause a lifestyle or occupational change, with the resultant beneficial effect for the subject.

Other, more direct approaches to prophylaxis or therapy can also be followed. These can include pharmaceutical or other medicaments being administered directed at favourably altering the net score of the subject together with other such approaches as discussed herein.

Table 21 below presents representative examples of polymorphisms in linkage disequilibrium with the polymorphisms specified herein. Examples of such polymorphisms can be located using public databases, such as that available at www.hapmap.org. Specified polymorphisms are indicated in the columns marked SNP NAME. Unique identifiers are indicated in the columns marked RS NUMBER.

Table 21. Polymorphisms reported to be in linkage disequilibrium (unless stated) with examples of specified polymorphism.

SNP NAME	RS NUMBER	SNP NAME	RS NUMBER	SNP NAME	RS NUMBER
	COX2 SNPs		rs6684912		rs5277
	rs7527769		rs2745559		rs2066823
	rs7550380		rs 12042763		rs4648263
	rs2206594		rs4648250		rs4987012
	rs6687495		rs4648251		rs20428

2017265006 21 Nov 2017

rs6681231		rs2223626	rs20429
rs 13376484		rs689462	rs4648264
rs12064238		rs4648253	rs4648265
rs10911911		rs689465	rs4648266
rs 12743673		rs12027712	rs4648267
rs10911910		rs689466	rs11567824
rs 12743516		rs2745558	rs4648268
rs10911909		rs3918304	rs4648269
rs1119066		rs20415	rs4648270
rs1119065		rs20416	rs12759220
rs1119064		rs4648254	rs20430
rs10798053		rs11567815	rs4648271
rs12409744	-765G>C	rs20417	rs 11567825
rs10911908		rs4648256	rs4648273
rs10911907		rs20419	rs16825748
rs7416022		rs2734779	rs4648274
rs2745561		rs20420	rs16825745
rs10911906		rs20422	rs20432
rs2734776		rs20423	rs20433
rs2734777		rs5270	rs3218622
rs12084433		rs20424	rs2066826
rs2734778		rs5271	rs5278
rs2745560		rs4648257	rs4648276
rs2223627		rs11567819	rs20434
rs2383517		rs 3134591	rs3218623
rs4295848		rs3134592	rs3218624
rs4428839		rs20426	rs5279
rs4609389		rs4648258	rs4648278
rs4428838		rs 11567820	rsl 3306034
rs12131210		rs2745557	rs2853803
rs2179555		rs 11567821	rs4648279
rs2143417		rs4648259	rs4648281
rs2143416		rs4648260	rs4648282
rs11583191		rs4648261	rs11567826
rs2383516		rs4648262	rs4648283
rs2383515		rs 11567822	rs4648284
rs10911905		rs 11567823	rs4648285
rs10911904		rs2066824	rs11567827
		rs20427	rs4648286

rs4648287	rs 1042719		rs5744244
rs5272	rs3729944		rs360722
rs4648288	rs3730182		rs5023207
rs5273	rs 1042720		rs5744246
rs5274	rs6879202		rs5744247
rs3218625	rs3777124	-133 C/G	rs360721
rs4648289	rs18Q3051		rs4988359
rs4648290	rs8192451		rs12721559

2017265006 21 Nov 2017

	rs1051896	rs4987255		rs5744248
	rs5275	rs3177007		rs5744249
	1ADRB SNPs	rs 1126871		rs5744250
	rs2082382	rs6885272		rs5744251
	rs2082394	rs6889528		rs100000356
	rs2082395	rs4521458		rs1834481
	rs9325119	rs 10463409		rs17215057
	rs9325120	rs7702861		rs5744253
	rs12189018	IL-18 SNPs		rs5744254
	rs11168066	rs 187238		rs5744255
	rs11959615	rs5744228		rs5744256
	rs11958940	rs360718		rs5744257
	rs4705270	rs360717		rs360720
	rs10079142	rs5744229		rs5744258
	rs9325121	rs 100000353		rs5744259
	rs11746634	rs5744231		rs5744260
	rs11168067	rs5744232		rs5744261
	rs9325122	rs7106524	105 A/C	rs549908
	rs11957351	rs 189667		PAI-1 SNPs
	rs 11948371	rs 12290658		rs6465787
	rs 11960649	rs12271175		rs7788533
	rs 1432622	rs 11606049		rs6975620
	rs1432623	rs360716		rs6956010
	rs11168068	rs360715		rs12534508
	rs17778257	rs360714		rs4729664
	rs2400706	rs2043055		rs2527316
	rs2895795	rs5744233		rs2854235
	rs2400707	rs795467		rs10228765
	rs2053044	rs 12270240		rs2854225
	rs17108803	rs 100000354		rs2854226
	rs 12654778	rs4937113		rs2227707
	rs11168070	rs 100000355		rs2227631
	rs 11959427	rs360723	-675 4G/5G	No rs
	rs 1042711	rs5744237		NOS3 SNPs
	rs1801704	rs5744238		rs2373962
Arg16Gly	rs1042713	rs5744239		rs2373961
	rs 1042714	rs7932965		rs6951150
	rs 1042717	rs11214103		rs13238512
	rs1800888	rs5744241		rs10247107
	rs1042718	rs5744242		rs10276930
	rs3729943	rs5744243		rs10277237

rs12703107		rs9282804	rs2282679
rs6946340	Asp298Glu	rs 1799983	rs2282680
rs6946091		VDBP SNPs	rs705117
rs6946415		rs222035	rs2070741
rs10952296		rs222036	rs2070742
rs13309715		rs 16846943	rs6821541

2017265006 21 Nov 2017

rs10952297		rs7668653	rs222048
rs7784943		rs 1491720	rs432031
rs11771443		rs 16845007	rs432035
rs2243310		rs 17830803	rs222049
rs1800783	Glu416Asp	rs7041	rs222050
rs3918155	Lys420Thr	rs4588	rs12510584
rs3918156		rs3737553	rs17467825
rs2566519		rs9016	GSTP1 SNPs
rs3918157		rs 1352846	rs656652
rs3918158		rs222039	rs625978
rs3918159		rs3775154	rs6591251
rs2566516		rs222040	rs12278098
rs3918225		rs843005	rs612020
rs3918160		rs222041	rs12284337
rs 1800779		rs7672977	rs12574108
rs2243311		rs705121	rs6591252
rs3918161		rs 11723621	rs597717
rs10952298		rs2298850	rs688489
rs2070744		rs705120	rs597297
rs3918226		rs2298851	rs6591253
rs3918162		rs844806	rs6591254
rs3918163		rs 1491709	rs7927381
rs3918164		rs705119	rs7940813
rs3918165		rs6845925	rs593055
rs1800781		rs 12640255	rs7927657
rs13310854		rs 12644050	rs614080
rs13310763		rs6845869	rs7941395
rs2853797		rs 12640179	rs7941648
rs13311166		rs222042	rs7945035
rs13310774		rs3187319	rs2370141
rs2853798		rs222043	rs2370142
rs 11974098		rs842999	rs7949394
rs3918166		rs222044	rs7949587
rs3730001		rs222045	rs6591255
rs3918167		rs 16846912	rs8191430
rs3918168		rs222046	rs6591256
rs3918169		rs705118	rs8191431
rs3918170		rs222047	rs8191432
rs3793342		rs13142062	rs7109914
rs3793341		rs843000	rs4147580
rs 1549758		rs3755967	rs8191436
rs 1007311		rs1491710	rs8191437
rs9282803		rs2282678	rs17593068

rs8191438	rs2069718	rs7145047
rs8191439	rs3087272	rs7141735
rs8191440	rs2069719	rs11558264
rs8191441	rs9282708	rs6647

2017265006 21 Nov 2017

	rs1079719		rs2069720		rs8350
	rs1871041		rs 1042274		rs2230075
	rs4147581		rs2069721		rs1049800
	rs8191444		rs2069734	S allele	rs17580
	rs8191445		rs2069722		rs2854258
	rs2370143		rs2234687		rs2753937
	rs8191446		rs7957366		rs2749547
	rs3891249		rs2069723		rs 1243162
	rs8191447		rs2069724		rs2753938
	rs12796085		rs2069725		rs2070709
	rs8191448		rs4394909		rs17090719
	rs762803		rs2069726		rs11846959
	rs8191449		rs2069727		rs1802962
lle105Val	rs947894		IL-13 SNPs		rs2749521
	rs4986948	-1055 C/T	rs 1800925		rs2753939
	rs675554		rs 11575055		rs1802959
	rs749174		rs2069755		rs1802961
	rs8191450		rs2069741		rs1050469
	rs743679		rs2069742	Z allele	no rs
	rs1799811		rs2069743		rs1050520
	rs11553890		rs2069756		rs12077
	rs4986949		rs3212142		rs12233
	rs8191451		rs2066960		rs13170
	rs 1871042		rs 1295687		rs1303
	rs11553892		rs3212145		rs1802960
	rs4891		rs2069744		rs 1243163
	rs6413486		rs2069745		rs2073333
	rs5031031		rs2069746		rs 1243164
	rs947895		rs2069747		_rS7144409
	IFN- SNPs		rs2069748		rs7142803
	rs2069707		rs 1295686		rs 1243165
	rs3814242	Arg 130Gln	rs20541		rs1051052
	rs2069709		rs2069749		rs 1243166
	rs2069710		rs 1295685		rs11628917
	rs2069711		rs848		rs11832
	rs2069712		rs2069750		rs9944155
874 A/T	rs2430561		rs847	1237 G/A	rs11568814
	rs2069713		a1-antitrypsin SNPs		rs877081
	rs 1861494		rs709932		rs877082
	rs2234685		rs 11558261		rs877083
	rs 1861493		rs20546		rs877084
	rs2069714		rs 11558263		rs875989
	rs2069715		F1028580		rs9944117
	rs2069716		rs7145770		rs1884546
	rs2069717		rs2239652		rs1884547

rs1885065 rs2735442 rs8046608

2017265006 21 Nov 2017

	rs 1884548	rs2569693	rs5743264
	rs 1243167	rs281439	rs5743266
	rs17751614	rs281440	rs2076752
	rs 1884549	rs2569694	rs5743267
	rs1243168	rs 11575073	rs8061316
	rs17090693	rs2569695	rs8061636
	rs 17824597	rs2075741	rs16948754
	TNFa SNPs	rs 11575074	rs7206340
	rs 1799964	rs2569696	rs2076753
	rs 1800630	rs2735439	rs2067085
	rs 1799724	rs2569697	rs16948755
+489 G/A	rs 1800610	rs2075742	rs2111235
	rs3093662	rs2569698	rs2111234
	rs3093664	rs 11669397	rs7190413
-308 G/A	rs1800629 (1)	rs901886	rs7206582
	SMAD3 SNPs	rs885742	rs8045009
C89Y	C89Y no rs (2)	rs2569699	rs6500328
	ICAM1	rs 1056538	rs7500036
	rs1799969	rs11549918	rs8057341
	rs5493	rs2569700	rs12918060
	rs5030381	rs2228615	rs7204911
	rs5494	rs2569701	rs7500826
	rs3093033	rs2569702	rs4785449
	rs5495	rs2735440	rs12922299
	rs1801714	rs2569703	rs 11649521
	rs13306429	rs10418913	rs13339578
	rs2071441	rs 1056536	rs17221417
	rs5496	rs2569704	rs13331327
	rs5497	rs 11673661	rs11642482
	rs 13306430	rs2569705	rs 11642646
E469K	rs5498	rs 10402760	rs17312836
	rs5030400	rs2569706	rs5743268
	rs2071440	rs2569707	rs5743269
	rs5499	rs2735441	rs5743270
	rs3093032	rs2436545	rs12925051
	rs1057981	rs2436546	rs12929565
	rs5500	rs2916060	rs13380733
	rs5501	rs2916059	rs 13380741
	rs5030383	rs2916058	rs 11647841
	rs281436	rs2569708	rs10451131
	rs923366	rs 12972990	rs2066842
	rs281437	rs735747	rs5743271
	rs3093030	rs885743	rs7498256
	rs5030384	NOD2 SNPs	rs5743272
	rs5030385	rs4785224	rs5743273
	rs3810159	rs5743261	rs2076754
	rs281438	rs5743262	rs2066843
	rs3093029	rs5743263	rs 1078327

100

2017265006 21 Nov 2017

	rs5743274	rs 11645386		rs1031101
	rs1861759	rs7187857		rs10824795
	rs5743275	rs8061960		rs10824794
	rs5743276	rs5743294		rs920725
	rs2066844	rs2357791		rs7916582
	rs5743277	rs7359452		rs920724
	rs5743278	rs7203344		rs16933335
	rs6413461	rs5743295		rs11003125
	rs3813758	rs5743296		rs7100749
	rs5743279	rs3135499		rs11003124
	rs5743280	rs5743297		rs7084554
	rs5743281	rs5743298		rs7096206
	rs4785225	rs5743299		rs11003123
	rs 16948773	rs3135500		rs11575988
	rs9931711	rs5743300		rs11575989
	rs17313265	rs8056611		rs7095891
	rs11646168	rs2357792		rs4647963
	rs9925315	rs 12600253		rs8179079
	rs5743284	rs 12598306		rs5030737
	rs5743285	rs7205423	161 G/A	rs 1800450
	rs751271	rs718226		rs1800451
	rs748855	MBL2 SNPs		rs 12246310
	rs1861758	rs7899547		rs12255312
	rs13332952	rs 10824797		rs11003122
	rs7198979	rs11003131		rs1982267
	rs1861757	rs930506		rs1982266
	rs7203691	rs930505		rs4935047
	rs5743286	rs11003130		rs4935046
	rs5743287	rs2384044		rs10824793
	rs10521209	rs2384045		rs1838066
Gly881Arg	rs2066845	rs5027257		rs1838065
	rs5743289	rs2384046		rs930509
	rs8063130	rs 12263867		rs930508
	rs2076756	rs11003129		rs930507
	rs12920425	rs12221393		CMA1 SNPs
	rs12920040	rs2165811		rs1956920
	rs12920558	rs 12782244		rs1956921
	rs12919099	rs11003128	-1903 G/A	rs1800875
	rs12920721	rs 17664818		rs1800876
	rs2076755	rs7475766		rs3759635
	rs5743290	rs 10824796		rs1956922
	rs5743291	rs 16933417		rs1956923
	rs 11642651	rs2165810		NAT2 SNPs
	rs1861756	rs11003127		rs 11780272
	rs749910	rs3925313		rs2101857
	rs4990643	rs7094151		rs13363820
	rs 1077861	rs7071882		rs6984200
	rs5743292	rs 12264958		rs13277605
	rs9921146	rs11003126		rs9987109

101

2017265006 21 Nov 2017

	rs7820330		rs7596849	-366 G/A	rs9550373
	rs7460995		rs4848306		rs11542984
	rs2087852		rs3087257		rs4769055
	rs2101684		rs7556811		rs17074937
	rs7011792		rs7556903		rs9671065
	rs1390358		rs6743438		rs9579645
	rs923796		rs6743427		rs9579646
	rs4546703		rs6761336		rs4075131
	rs4634684		rs6761335		rs4075132
	rs2410556		rs6743338		rs9315043
	rs11996129		rs6761245		rs9315044
	rs4621844		rs6761237		rs4597169
	rs 11785247		rs6743330		rs9578037
	rs1115783		rs6743326		rs9578196
	rs1115784		rs6743322		rs4293222
	rs 1961456		rs6761220		rs10507391
	rs1112005		rs6761218		rs12429692
	rs11782802		rs5021469		rs4769871
	rs973874		rs6710598		rs4769872
	rs 1495744		rs 1143623		rs4769873
	rs7832071		rs 1143624		rs12430051
	rs1805158		rs2708920		rs9315045
	rs1801279		rs 1143625		rs9670278
	rs1041983		rs2853545		rs4503649
	rs1801280		rs2708921		rs9508832
	rs4986996		rs 1143626		rs9670460
	rs12720065		rs3087258		rs3885907
	rs4986997	C-511T	rs 16944		rs3922435
	rs1799929		rs3917346		rs9551957
Arg197Gln	rs1799930		rs4986962		rs12018461
	rs1208		rs 1143627		rs9551958
	rs1799931		MEH SNPs		rs 10467440
	rs2552	Tyr113His	rs 1051740 (2)		rs12017304
	rs4646247	His139Arg	rs2234922 (2)		rs9551959
	rs971473		ALOX5AP SNPs		rs11617473
	rs721398		rs4076128		rs11147438
	IL-1 B SNPs		rs9508830		rs10162089
	rs10169916		rs4073259		rs9551960
	rs13009179		rs4073260		rs9285075
	rs4849127		rs11616333		rs12431114
	rs4849126		rs4073261		rs4254165
	rs7558108		rs4075474		rs4360791
	rs13032029		rs4075473		rs17612031
	rs13013349		rs9670115		rs3803277
	rs12623093		rs9315042		rs3803278
	rs3087255		rs3809376		rs12429469
	rs3087256		rs 12877064		rs17612099

102

2017265006 21 Nov 2017

	rs6721954		rs9508831		rs9550576
	rs12621220		rs9670503		rs4356336

rs4584668	rs2075800	rs2734714
rs4238137	CLCA1 SNPs	rs6661730
rs17612127	rs2791519	rs2753377
rs4147063	rs2791518	rs2753378
rs4147064	rs5744302	rs2145412
rs4147062	rs1321697	rs2180762
rs9315046	rs2753338	rs 1005569
rs9506352	rs2791517	rs5744325
rs9670531	rs5744303	rs5744326
rs9671182	rs2734706	rs 1985554
rs9315047	rs2753345	rs1985555
rs17690694	rs2753347	rs 100000102
rs9652070	rs2753348	rs100000103
rs 17074966	rs2753349	rs1969719
rs4387455	rs5744304	rs2390102
rs4254166	rs5744305	rs5744329
rs4075692	rs 1358826	rs 1407142
rs 17690748	rs2753359	rs2753384
rs9671124	rs5744306	rs2753385
rs9671125	rs2734711	rs5744330
rs9741436	rs5744307	rs5744331
rs9578197	rs2734712	rs926064
rs4769056	rs2753361	rs926065
rs11147439	rs2753364	rs926066
rs12721459	rs 1555389	rs926067
rs4769874	rs2753365	rs2753386
HSP70 HOM SNPs	rs100000100	rs2180764
rs1043618	rs100000101	rs2734689
rs11576009	rs5744310	rs5744332
rs11557922	rs5744311	rs5744333
rs11576010	rs5744312	rs11161837
rs1008438	rs4656114	rs5744335
rs11576011	rs5744313	rs2038485
rs4713489	rs2753367	rs3765989
rs16867582	rs4656115	rs2734690
rs12526722	rs2734713	rs5744336
rs6933097	rs5744314	rs2734691
rs12213612	rs5744315	rs2734692
rs481825	rs5744316	rs5744337
rs7757853	rs5744317	rs5744338
rs7757496	rs5744318	rs2734694
rs9469057	rs926063	rs5744339
rs12182397	rs5744319	rs 100000104
rs16867580	rs5744320	rs2791515
rs2075799	rs5744321	rs4656116

103

2017265006 21 Nov 2017

	rs482145	rs5744322	rs5744342
	rs2227957	rs5744323	rs5744343
T2437C	rs2227956	rs5744324	rs2180761
	rs2227955	rs2791516	rs5744344

	rs5744345		rs5744443		rs6032038
	rs1358825		rs5744444		rs6032039
	rs2145410		rs3138074		rs2267863
	rs2734695		rs13166911		rs6124692
	rs5744346		rs2563310	+49 C/T	No rs
	rs5744347		rs2569193		rs17333103
	rs100000105		rs2569192		rs17333180
	rs5744349		rs5744446		rs1983649
	rs4655913		rs5744447		rs16989785
	rs1321696		rs5744448		rs 17424356
	rs5744352		rs3138076		rs6017500
	rs11583355		rs 12519656		rs6032040
	rs100000106		rs5744449		rs6017501
	rs1321695		rs2915863		rs2664581
+ 13924 T/A	rs1321694		rs3138078		rs 17424474
	rs2791514		rs6875483		rs17333381
	rs2734696		rs2569191		rs1053826
	rs5744354		rs5744451		rs2664533
	rs2791513		rs5744452		rs1053831
	rs2753332		rs 100000098		rs2664520
	rs2791512		rs17118968		rs2267864
	rs2791511		rs5744455		rs13038355
	rs2734697	-159 C/T	rs2569190		rs13043296
	CD14SNPs		rs2569189		rs13039213
	rs6877461		rs2563303		rs6104049
	rs3822356		rs3138079		rs13043503
	rs6877437		rs2228049		rs6104050
	rs12153256		rs 13763		rs17424578
	rs 11554680		rs11556179		rs 17424613
	rs12109040		rs4914		rs6017502
	rs12517200		Elafin SNPs		rs6094101
	rs5744430		rs2868237		rs6130778
	rs5744431		rs4632412		rs6130779
	rs100000092		rs7347427		rs6104051
	rs5744433		rs6032032		rs6104052
	rs100000093		rs 10854230		ADBR2 SNPs
	rs4912717		rs7347426		rs2082382
	rs100000094		rs8183548		rs2082394
	rs100000095		rs6104047		rs2082395
	rs100000096		rs6513967		rs9325119
	rs6864930		rs13038813		rs9325120
	rs100000097		rs8118673		rs12189018
	rs6864583		rs7346463		rs11168066

104

2017265006 21 Nov 2017

rs6864580	rs7362841	rs11959615
rs6889418	rs 13042694	rs11958940
rs6889416	rs 13038342	rs4705270
rs5744440	rs7363327	rs10079142
rs5744441	rs6073668	rs9325121
rs5744442	rs 13044826	rs11746634

	rs11168067		rs1800468		rs542603
	rs9325122		rs4987025		rs574939
	rs11957351		rs1800469		rs573764
	rs11948371		rs11466314		rs7102189
	rs 11960649		rs12977628		rs575727
	rs 1432622		rs12977601		rs552306
	rs 1432623		rs12985978		rs634607
	rs11168068		rs11466315		rs 12286876
	rs 17778257		rs11551223		rs 12285331
	rs2400706		rs11551226		rs519806
	rs2895795		rs11466316		rs 12283571
	rs2400707		rs13306706		rs2839969
	rs2053044		rs13306707		rs2000609
	rs17108803		rs13306708		rs7125865
	rs 12654778		rs9282871		rs570662
	rs11168070	LeulOPro	rs1982073		rs 11225427
	rs 11959427		rs 1800471		rs484915
	rs 1042711		rs 13447341		rs470307
	rs 1801704		rs11466318		rs2408490
	rs 1042713		rs12976890		rs 12279710
Gln27Glu	rs 1042714		rs12978333		rs685265
	rs 1042717		rs10420084		rs7107224
	rs 1800888		rs10418010		rs 1155764
	rs 1042718		rs12983775		rs534191
	SOD3 SNPs		rs 12462166		rs509332
Arg213Gly	rs 1799895 (2)		rs2241715		rs 12283759
	TGFB1 SNPs		rs9749548		rs2105581
	rs 1529717		rs7258445		rs470206
	rs 1046909		rs11466320		rs533621
	rs2241712		rs11466321	-1607 G/GG	rs 1799750
	rs2241713		rs8108052		rs470211
	rs2241714		rs6508976		rs470146
	rs 11673525		rs8108632		rs2075847
	rs2873369		rs11466324		rs473509
	rs11083617		rs2241716		rs498186
	rs11083616		rs2241717		GSTM1 polymorphism
	rs4803458		rs2288873	Null	Null allele No rs (2)
	rs11670143		rs12973435		MMP9 SNPs
	rs 1982072		rs2014015		rs 11696804
	rs11668109		rs1989457		rs6104416

105

2017265006 21 Nov 2017

rs13345981	rs 10406816	rs3933239
rs 11666933	rs8102918	rs3933240
rs11466310	rs4803455	rs6094237
rs11466311	MMP1 SNPs	rs11697325
rs2317130	rs529381	rs6130988
rs4803457	rs 1144396	rs6073983
rs3087453	rs504875	rs6130989
rs 1800820	rs526215	rs6130990
rs 1054797	rs12280880	rs10211842

	rs6073984	rs8125587		TIMP3 SNPs
	rs6073985	rs3918253		rs5754289
	rs8121146	rs2274755		rs5754290
	rs6032620	rs2664538		rs9606994
	rs 11698788	rs3918254		rs7285034
	rs6032621	rs6130993		rs13433582
	rs6065912	rs3918255		rs1962223
	rs6104417	rs2236416		rs8137129
	rs3848720	rs6130994		rs 1807471
	rs 13040272	rs3918256		rs7290885
	rs6104418	rs3918281		rs5749511
	rs3848721	rs3787268		rs 11703366
	rs3848722	rs3918257		rs4990774
	rs6104419	rs6017725	-1296 T/C	rs9619311
	rs4810482	rs6032623		rs2234921
	rs3761157	rs3918258		rs2234920
	rs3761158	rs2250889		rs16991235
	rs3761159	rs3918259		rs4638893
	rs8113877	rs3918260		rs12169569
	rs6065913	rs 13969		rs5998639
	rs6104420	rs6104427		rs7284166
	rs6104421	rs6104428		rs5749512
	rs3918240	rs2274756
	rs6104422	rs6017726
	rs3918278	rs3918261
	rs3918241	rs6032624
-1562 C/T	rs3918242	rs3918262
	rs3918243	rs3918263
	rs3918279	rs3918264
	rs3918280	rs6130995
	rs4578914	rs6130996
	rs6017724	rs3918265
	rs3918244	rs3918266
	rs3918245	rs3918267
	rs6130992	rs6073987
	rs3918247	rs6073988
	rs3918248	rs3918282
	rs3918249	rs 1802909

106

2017265006 21 Nov 2017

rs6104423		rs 13925
rs6104424		rs20544
rs6104425		rs 1056628
rs6104426		rs 1802908
rs3918250		rs2664517
rs 1805089		rs9509
rs3918251		rs3918268
rs 13040572		rs3918269
rs 13040580		rs3918270
rs3918252		MMP12SNPs
rs8125581	-82 A/G	rs2276109 (2)

(1 = no other SNPs reported to be in LD, 2=no other SNPS reported to be in LD)

INDUSTRIAL APPLICATION

The present invention is directed to methods for assessing a subject’s risk of developing a disease. The methods comprise the analysis of polymorphisms herein shown to be associated with increased or decreased risk of developing a disease, or the analysis of results obtained from such an analysis, and the determination of a net risk score. Methods of treating subjects at risk of developing a disease herein described are also provided.

Publications

1. Sandford AJ, et al., 1999. Z and S mutations of the α 1-antitrypsin gene and the risk of chronic obstructive pulmonary disease. Am J Respir Cell Mol Biol. 20; 287-291.

2. Maniatis,T., Fritsch, E. F. and Sambrook, J., Molecular Cloning Manual. 1989.

3. Papafili A, et al., 2002. Common promoter variant in cyclooxygenase-2 represses gene expression. Arterioscler Thromb Vase Biol. 20; 1631-1635.

4. Ukkola, 0., Erkkila, P. H., Savolainen, M. J. & Kesaniemi, Y. A. 2001. Lack of association between polymorphisms of catalase, copper zinc superoxide dismutase (SOD), extracellular SOD and endothelial nitric oxide synthase genes and macroangiopathy in patients with type 2 diabetes mellitus. J Int Med 249; 451-459.

5. Smith CAD & Harrison DJ, 1997. Association between polymorphism in gene for microsomal epoxide hydrolase and susceptibility to emphysema. Lancet. 350; 630633.

6. Lorenz E, et al., 2001. Determination of the TLR4 genotype using allele-specific PRC. Biotechniques. 31; 22-24.

2017265006 21 Nov 2017

107

7. Cantlay AM, Smith CA, Wallace WA, Yap PL, Lamb D, Harrison

DJ.Heterogeneous expression and polymorphic genotype of glutathione Stransferases in human lung. Thorax. 1994, 49(10):1010-4.

All patents, publications, scientific articles, and other documents and materials referenced or mentioned herein are indicative of the levels of skill of those skilled in the art to which the invention pertains, and each such referenced document and material is hereby incorporated by reference to the same extent as if it had been incorporated by reference in its entirety individually or set forth herein in its entirety. Applicants reserve the right to physically incorporate into this specification any and all materials and information from any such patents, publications, scientific articles, web sites, electronically available information, and other referenced materials or documents.

The specific methods and compositions described herein are representative of various embodiments or preferred embodiments and are exemplary only and not intended as limitations on the scope of the invention. Other objects, aspects, examples and embodiments will occur to those skilled in the art upon consideration of this specification, and are encompassed within the spirit of the invention as defined by the scope of the claims. It will be readily apparent to one skilled in the art that varying substitutions and modifications can be made to the invention disclosed herein without departing from the scope and spirit of the invention. The invention illustratively described herein suitably can be practiced in the absence of any element or elements, or limitation or limitations, which is not specifically disclosed herein as essential. Thus, for example, in each instance herein, in embodiments or examples of the present invention, any of the terms “comprising”, “consisting essentially of”, and “consisting of” may be replaced with either of the other two terms in the specification, thus indicating additional examples, having different scope, of various alternative embodiments of the invention. Also, the terms “comprising”, “including”, containing”, etc. are to be read expansively and without limitation. The methods and processes illustratively described herein suitably may be practiced in differing orders of steps, and that they are not necessarily restricted to the orders of steps indicated herein or in the claims. It is also that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural reference unless the context clearly

2017265006 21 Nov 2017

108 dictates otherwise. Thus, for example, a reference to “a host cell” includes a plurality (for example, a culture or population) of such host cells, and so forth. Under no circumstances may the patent be interpreted to be limited to the specific examples or embodiments or methods specifically disclosed herein. Under no circumstances may the patent be interpreted to be limited by any statement made by any Examiner or any other official or employee of the Patent and Trademark Office unless such statement is specifically and without qualification or reservation expressly adopted in a responsive writing by Applicants.

The terms and expressions that have been employed are used as terms of description and not of limitation, and there is no intent in the use of such terms and expressions to exclude any equivalent of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention as claimed. Thus, it will be understood that although the present invention has been specifically disclosed by preferred embodiments and optional features, modification and variation of the concepts herein disclosed may be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this invention as defined by the appended indicative claims.

The invention has been described broadly and generically herein. Each of the narrower species and subgeneric groupings falling within the generic disclosure also form part of the invention. This includes the generic description of the invention with a proviso or negative limitation removing any subject matter from the genus, regardless of whether or not the excised material is specifically recited herein.

Other embodiments are within the following indicative claims. In addition, where features or aspects of the invention are described in terms of Markush groups, those skilled in the art will recognize that the invention is also thereby described in terms of any individual member or subgroup of members of the Markush group.

109

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Claims

1. A method of assessing a subject’s risk of developing a disease which comprises:

wherein a net protective score is predictive of a reduced risk of developing said disease and a net susceptibility score is predictive of an increased risk of developing said disease.

2. A method according to claim 1 wherein the value assigned to each protective polymorphism is the same.

3. A method according to claim 1 or claim 2 wherein the value assigned to each susceptibility polymorphism is the same.

4. A method according to any one of claims 1 to 3 wherein each protective polymorphism has a negative value and each susceptibility polymorphism having a positive value.

5. A method according to any one of claims 1 to 3 wherein each protective polymorphism has a positive value and each susceptibility polymorphism has a negative value.

6. A method according to any one of claims 1 to 5 wherein when the disease is a lung disease, the protective polymorphisms analysed may be selected from one or more of the group consisting of:

+760GG or +760CG within the gene encoding superoxide dismutase 3 (SOD3); -1296TT within the promoter of the gene encoding tissue inhibitor of metalloproteinase 3 (T1MP3 );

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110

7. A method according to claim 6 wherein all polymorphisms of the group are analysed.

8. A method according to any one of claims 1 to 7 wherein when the disease is a lung disease, the susceptibility polymorphisms analysed are selected from one or more of the group consisting of:

-82AA within the promoter of the gene encoding human macrophage elastase (MMP12);

1237AG or 1237AA (Tt or tt allele genotypes) within the 3’ region of the gene encoding al-antitrypsin (alAT); or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms.

9. A method according to claim 8 wherein all polymorphisms of the group are analysed.

10. A method according to any one of claims 1 to 5 wherein when the disease is COPD, the protective polymorphisms analysed may be selected from one or more of the group consisting of:

-765 CC or CG in the promoter of the gene encoding cyclooxygenase 2 (COX2);

Arg 130 Gin AA in the gene encoding Interleukin-13 (IL-13);

Asp 298 Glu TT in the gene encoding nitric oxide synthase 3 (NOS3);

Lys 420 Thr AA or AC in the gene encoding vitamin binding protein (VDBP);

Glu 416 Asp TT or TG in the gene encoding VDBP;

lie 105 Val AA in the gene encoding glutathione S-transferase (GSTP1);

MS in the gene encoding α 1-antitrypsin (alAT);

the +489 GG geneotype in the gene encoding Tumour Necrosis factor a (TNFa);

the -308 GG geneotype in the gene encoding TNFa;

the C89Y AA or AG geneotype in the gene encodoing SMAD3;

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111 the 161 GG genotype in the gene encodoing Mannose binding lectin 2 (MBL2);

the -1903 AA genotype in the gene encoding Chymase 1 (CMA1);

the Arg 197 Gin AA genotype in the gene encoding N-Acetyl transferase 2 (NAT2);

the exon 1 +49 CT or TT genotype in the gene encoding Elafin; the Gin 27 Glu GG genotype in the gene encoding β2 Adrenergic receptor (ADBR); the -1607 1G1G or 1G2G genotype in the promoter of the gene encoding Matrix Metalloproteinase 1 (MMP1);

11. A method according to claim 10 wherein all polymorphisms of the group are analysed.

12. A method according to any one of claims 1 to 5, 10 or 11 wherein when the disease is COPD, the susceptibility polymorphisms analysed are selected from one or more of the group consisting of:

Arg 16 Gly GG in the gene encoding p2-adrenoreceptor (ADRB2);

105 AA in the gene encoding Interleukin-18 (IL-18);

-133 CC in the promoter of the gene encoding IL-18;

-1055 TT in the promoter of the gene encoding IL-13;

874 TT in the gene encoding interferon gamma (IFNy); the +489 AA or AG genotype in the gene encoding TNFa; the -308 AA or AG genotype in the gene encoding TNFa; the C89Y GG genotype in the gene encoding SMAD3;

2017265006 21 Nov 2017

112 the Gly 881 Arg GC or CC genotype in the gene encoding Caspase (NOD2);

the -511 GG genotype in the gene encoding IL1B;

the Tyr 113 His TT genotype in the gene encoding MEH;

the -366 GG genotype in the gene encoding ALOX5;

the HOM T2437C CC or CT genotype in the gene encoding HSP 70;

the +13924 AA genotype in the gene encoding Chloride Channel Calcium-activated

1 (CLCA1);

13. A method according to claim 12 wherein all polymorphisms of the group are analysed.

14. A method according to any one of claims 1 to 5 wherein when the disease is OCOPD, the protective polymorphisms analysed may be selected from one or more of the group consisting of:

-765 CC or CG in the promoter of the gene encoding COX2;

-251 AA in the promoter of the gene encoding interleukin-8 (IL-8);

Lys 420 Thr AA in the gene encoding VDBP;

Glu 416 Asp TT or TG in the gene encoding VDBP;

exon 3 T/C RR in the gene encoding microsomal epoxide hydrolase (MEH);

Arg 312 Gin AG or GG in the gene encoding SOD3;

MS or SS in the gene encoding alAT;

Asp 299 Gly AG or GG in the gene encoding toll-like receptor 4 (TLR4);

Gin 27 Glu CC in the gene encoding ADRB2;

-518 AA in the gene encoding IL-11;

15. A method according to claim 14 wherein all polymorphisms of the group are analysed.

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113

16. A method according to any one of claims 1 to 5, 14, or 15 wherein when the disease is OCOPD, the susceptibility polymorphisms analysed are selected from one or more of the group consisting of:

-765 GG in the promoter of the gene encoding COX2;

105 AA in the gene encoding IL-18;

-133 CC in the promoter of the gene encoding IL-18;

-675 5G5G in the promoter of the gene encoding PAI-1;

Lys 420 Thr CC in the gene encoding VDBP;

Glu 416 Asp GG in the gene encoding VDBP; lie 105 Val GG in the gene encoding GSTP1;

Arg 312 Gin AA in the gene encoding SOD3;

-1055 TT in the promoter of the gene encoding IL-13;

3’ 1237 Tt or tt in the gene encoding alAT;

17. A method according to claim 16 wherein all polymorphisms of the group are analysed.

18. A method according to any one of claims 1 to 5 wherein when the disease is lung cancer, the protective polymorphisms analysed may be selected from one or more of the group consisting of:

the Asp 298 Glu TT genotype in the gene encoding NOS3;

the Arg 312 Gin CG or GG genotype in the gene encoding SOD3;

the Asn 357 Ser AG or GG genotype in the gene encoding MMP12;

the 105 AC or CC genotype in the gene encoding IL-18;

the -133 CG or GG genotype in the gene encoding IL-18;

the -765 CC or CG genotype in the promoter of the gene encoding COX2;

the -221 TT genotype in the gene encoding Mucin SAC (MUC5AC);

the intron 1 C/T TT genotype in the gene encoding Arginase 1 (Argl);

the Leu252Val GG genotype in the gene encoding Insulin-like growth factor II receptor (1GF2R);

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114 the -1082 GG genotype in the gene encoding Interleukin 10 (IL-10);

the -251 AA genotype in the gene encoding Interleukin 8 (IL-8);

the Arg 399 Gin AA genotype in the X-ray repair complementing defective in

Chinese hamster 1 (XRCC1) gene ;

the A870G GG genotype in the gene encoding cyclin D (CCND1); the -751 GG genotype in the promoter of the xeroderma pigmentosum complementation group D (XPD) gene ;

the lie 462 Val AG or GG genotype in the gene encoding cytochrome P450 1 Al (CYP1A1);

the Phe 257 Ser CC genotype in the gene encoding REV1;

19. A method according to claim 18 wherein all polymorphisms of the group are analysed.

20. A method according to any one of claims 1 to 5, 18 or 19 wherein when the disease is lung cancer, the susceptibility polymorphisms analysed are selected from one or more of the group consisting of:

the -786 TT genotype in the promoter of the gene encoding NOS3;

the Ala 15 Thr GG genotype in the gene encoding anti-chymotrypsin (ACT);

the 105 AA genotype in the gene encoding IL-18;

the -133 CC genotype in the promoter of the gene encoding IL-18;

the 874 AA genotype in the gene encoding IFNy;

the -765 GG genotype in the promoter of the gene encoding COX2;

the -511 GG genotype in the gene encoding IL-1B;

the A-670G AA genotype in the gene encoding FAS (Apo-1/CD95);

the Arg 197 Gin GG genotype in the gene encoding N-acetyltransferase 2 (NAT2);

2017265006 21 Nov 2017

115 the Ile462 Val AA genotype in the gene encoding CYP1A1;

the 1019 G/C Pst I CC or CG genotype in the gene encoding cytochrome P450 2E1 (CYP2E1);

the C/T Rsa I TT or TC genotype in the gene encoding CYP2E1;

the GSTM null genotype in the gene encoding GSTM;

the -1607 2G/2G genotype in the promoter of the gene encoding MMP1;

the Gin 185 Glu CC genotype in the gene encoding Nibrin (NBS1);

the Asp 148 Glu GG genotype in the gene encoding Apex nuclease (APE1);

21. A method according to claim 18 wherein all polymorphisms of the group are analysed.

22. A method according to any one of claims 1 to 21 wherein each protective polymorphism is assigned a value of -1 and each susceptibility polymorphism is assigned a value of+1.

23. A method according to any one of claims 1 to 21 wherein each protective polymorphism is assigned a value of +1 and each susceptibility polymorphism is assigned a value of -1.

24. A method according to any one of claims 1 to 23 wherein the subject is or has been a smoker.

25. A method according to any one of claims 1 to 24 wherein the method comprises an analysis of one or more risk factors, including one or more epidemiological risk factors, associated with the risk of developing said disease.

26. A method of determining a subject’s risk of developing a disease, said method comprising:

obtaining the result of one or more analyses of a sample from said subject to determine the presence or absence of protective polymorphisms and the presence or absence of susceptibility polymorphisms, and wherein said protective and susceptibility polymorphisms are associated with said disease;

2017265006 21 Nov 2017

116 calculating a net score for said subject, said net score representing the balance between the combined value of the protective polymorphisms and the combined value of the susceptibility polymorphisms present in the subject sample;

27. A method of prophylactic or therapeutic intervention in relation to a subject having a net susceptibility score for a disease as determined by a method according to any one of claims 1 to 26, wherein said method includes the steps of communicating to said subject said net susceptibility score, and advising on changes to the subject’s lifestyle that could reduce the risk of developing said disease.

28. A method of treatment of a subject to decrease to the risk of developing a disease through alteration of the net score for said subject as determined by a method as defined above, wherein said method of treatment comprises:

reversing, genotypically or phenotypically, the presence and/or functional effect of one or more susceptibility polymorphisms associated with said disease; and/or replicating and/or mimicking, genotypically or phenotypically, the presence and/or functional effect of one or more protective polymorphisms associated with said disease.

29. A kit for assessing a subject’s risk of developing a disease, said kit comprising a means of analysing a sample from said subject for the presence or absence of one or more protective polymorphisms and one or more susceptibility polymorphisms in accordance with a method of any one of claims 1 to 28.

1/3

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2+

Figure 1

Number of Protective Genes

I-1-1-1-1-1-1-1-1

-4-3-2-10 1 2 3 4

Net Genetic Burden (number of Protective-number of Susceptible Genes)

Figure 2

2/3

2017265006 21 Nov 2017

Figure 4

3/3

2017265006 21 Nov 2017

Distribution of SNP score for lung cancer among smokers

Figure 5

2017265006 21 Nov 2017

542814.st25.txt SEQUENCE LISTING

<110> Synergenz Bioscience Limited Young, Robert <120> Methods of Analysis of Polymorphisms and Uses Thereof <130> 542814 <150> NZ 540249 <151> 2005-05-20 <150> NZ 541842 <151> 2005-08-15 <160> 336 <170> Patentln version 3.2 <210> 1 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 1 acgttggatg gcttgttaac cagctttgcc <210> 2 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 2 acgttggatg tttttcagac tggcagagcg <210> 3 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 3 acgttggatg tttttcagac tggcagagcg <210> 4 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 4

acgttggatg gcttgttaac cagctttgcc 30 <210> 5

Page 1

542814.st25.txt

2017265006 21 Nov 2017 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 5 acgttggatg catgtcgcct tttcctgctc <210> 6 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 6 acgttggatg caacacccaa caggcaaatg <210> 7 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 7 acgttggatg tggtggacat ggtgaatgac <210> 8 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 8 acgttggatg tggtgcagat gctcacatag <210> 9 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 9 acgttggatg cacagagaga gtctggacac <210> 10 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 10

Page 2

542814.st25.txt

2017265006 21 Nov 2017 acgttggatg ctcttggtct ttccctcatc 30 <210> 11 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 11 acgttggatg acagctctgc attcagcacg 30 <210> 12 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 12 acgttggatg agtcaatccc tttggtgctc 30 <210> 13 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 13 acgttggatg gttttccagc ttgcatgtcc 30 <210> 14 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 14 acgttggatg caatagtcag gtcctgtctc 30 <210> 15 <211> 29 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 15 acgttggatg gaacggcagc gccttcttg 29 <210> 16 <211> 30 <212> DNA <213> Artificial

Page 3

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2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 16 acgttggatg acttggcaat ggctgtgatg <210> 17 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 17 acgttggatg cagacattca caattgattt <210> 18 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 18 acgttggatg gatagttcca aacatgtgcg <210> 19 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 19 acgttggatg gggtattcat aagctgaaac <210> 20 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 20 acgttggatg ccttcaagtt cagtggtcag <210> 21 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 21 acgttggatg ggtcaatgaa gagaacttgg <210> 22

Page 4

542814.st25.txt

2017265006 21 Nov 2017 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 22 acgttggatg aatgtttatt gtagaaaacc 30 <210> 23 <211> 15 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 23 agctttgcca gttcc 15 <210> 24 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 24 aaaagcaaaa ttgcctga 18 <210> 25 <211> 15 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 25 tcctgctctt ccctc 15 <210> 26 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 26 acctccgctg caaatac 17

<210> 27 <211> 18 <212> DNA <213> Artificial <220> <223> Synthetic <400> 27

Page 5

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2017265006 21 Nov 2017 gagtctggac acgtgggg 18 <210> 28 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 28 tgctgcaggc cccagatga 19 <210> 29 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 29 agaaactttt tcgcgaggga c 21 <210> 30 <211> 24 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 30 agcgccttct tgctggcacc caat 24 <210> 31 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 31 tcttacaaca caaaatcaaa tc 22 <210> 32 <211> 15 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 32 agctgaaact tctgg 15 <210> 33 <211> 20 <212> DNA <213> Artificial

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2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 33 tcaagcttgc caaagtaatc 20 <210> 34 <211> 16 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 34 agctttgcca gttcct 16 <210> 35 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 35 agctttgcca gttccgt 17 <210> 36 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 36 aaaagcaaaa ttgcctgat 19 <210> 37 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 37 aaaagcaaaa ttgcctgagg c 21 <210> 38 <211> 16 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 38 tcctgctctt ccctca 16 <210> 39

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2017265006 21 Nov 2017

<211> 17 <212> DNA <213> Artificial <220> <223> Syntheti c <400> 39 tcctgctctt ccctcgt <210> 40 <211> 18 <212> DNA <213> Artificial <220> <223> Synthetic <400> 40 acctccgctg caaataca <210> 41 <211> 19 <212> DNA <213> Artificial <220> <223> Synthetic <400> 41 acctccgctg caaatacgt <210> 42 <211> 19 <212> DNA <213> Artificial <220> <223> Synthetic <400> 42 gagtctggac acgtgggga <210> 43 <211> 20 <212> DNA <213> Artificial <220> <223> Synthetic <400> 43 gagtctggac acgtggggga <210> 44 <211> 20 <212> DNA <213> Artificial <220> <223> Synthetic <400> 44

Page 8

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2017265006 21 Nov 2017 tgctgcaggc cccagatgat <210> 45 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 45 tgctgcaggc cccagatgag c 21 <210> 46 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 46 agaaactttt tcgcgaggga ca 22 <210> 47 <211> 24 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 47 agaaactttt tcgcgaggga cggt 24 <210> 48 <211> 25 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 48 agcgccttct tgctggcacc caata 25 <210> 49 <211> 27 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 49 agcgccttct tgctggcacc caatgga 27 <210> 50 <211> 23 <212> DNA <213> Artificial

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2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 50 tcttacaaca caaaatcaaa tct 23 <210> 51 <211> 24 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 51 tcttacaaca caaaatcaaa tcac 24 <210> 52 <211> 16 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 52 agctgaaact tctggc 16 <210> 53 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 53 agctgaaact tctggga 17 <210> 54 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 54 tcaagcttgc caaagtaatc t 21 <210> 55 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 55 tcaagcttgc caaagtaatc gga 23 <210> 56

Page 10

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2017265006 21 Nov 2017 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 56 acgttggatg gaagtcagag atgatggcag <210> 57 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 57 acgttggatg atgaatcctg gacccaagac <210> 58 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 58 acgttggatg gaaagatgtg cgctgatagg <210> 59 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 59 acgttggatg gccacatctc tttctgcatc <210> 60 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 60 acgttggatg ttgcaggtgt cccatcggaa <210> 61 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 61

Page 11

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2017265006 21 Nov 2017 acgttggatg tagctcgtgg tggctgtgca <210> 62 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 62 acgttggatg gtgatcaccc aaggcttcag <210> 63 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 63 acgttggatg gtctgttgac tcttttggcc <210> 64 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 64 acgttggatg gtagctctcc aggcatcaac <210> 65 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 65 acgttggatg gtacctggtt cccccttttc <210> 66 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 66 acgttggatg tgatcttgtt caccttgccg <210> 67 <211> 30 <212> DNA <213> Artificial

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2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 67 acgttggatg agatcgaggt gacgtttgac <210> 68 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 68 acgttggatg agacacagaa ccctagatgc <210> 69 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 69 acgttggatg gcaatgaagg atgtttcagg <210> 70 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 70 acgttggatg taagacagct ccacagcatc <210> 71 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 71 acgttggatg ttccatttcc tcaccctcag <210> 72 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 72 acgttggatg gatttgtgtg taggaccctg <210> 73

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2017265006 21 Nov 2017

<211> 30 <212> DNA <213> Artificial <220> <223> Syntheti c <400> 73 acgttggatg ggtccccaaa agaaatggag <210> 74 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 74 acgttggatg ggattggaga acaaactcac <210> 75 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 75 acgttggatg ggcagctgtt acaccaaaag <210> 76 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 76 acgttggatg ctggcgtttt gcaaacatac <210> 77 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 77 acgttggatg ttgactggaa gaagcaggtg <210> 78 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 78

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2017265006 21 Nov 2017

acgttggatg cctgccaaag aagaaacacc <210> 79 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 79 acgttggatg acgtctgcag gtatgtattc <210> 80 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 80 acgttggatg acttcatcca cgtgaagccc <210> 81 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 81 acgttggatg aaactcgtag aaagagccgg <210> 82 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 82 acgttggatg attttctcct cagaggctcc <210> 83 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 83 acgttggatg tgtctgtatt gagggtgtgg <210> 84 <211> 30 <212> DNA <213> Artificial

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2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 84 acgttggatg ttgctggcac ccaatggaag 30 <210> 85 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 85 acgttggatg atgagagaca tgacgatgcc 30 <210> 86 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 86 acgttggatg actcacagag cacattcacg 30 <210> 87 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 87 acgttggatg tgtcactcga gatcttgagg 30 <210> 88 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 88 gtgcctgtgc tgggctc 17 <210> 89 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 89 ggatggagag aaaaaaac 18 <210> 90

Page 16

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2017265006 21 Nov 2017

<211> 17 <212> DNA <213> Artificial <220> <223> Syntheti c <400> 90 ccctcatgtc atctact <210> 91 <211> 17 <212> DNA <213> Artificial <220> <223> Synthetic <400> 91 gtcacccact ctgttgc <210> 92 <211> 17 <212> DNA <213> Artificial <220> <223> Synthetic <400> 92 caaagatggg cgtgatg <210> 93 <211> 20 <212> DNA <213> Artificial <220> <223> Synthetic <400> 93 ccttgccggt gctcttgtcc <210> 94 <211> 20 <212> DNA <213> Artificial <220> <223> Synthetic <400> 94 cagaatcctt cctgttacgg <210> 95 <211> 23 <212> DNA <213> Artificial <220> <223> Synthetic <400> 95

Page 17

542814.st25.txt

2017265006 21 Nov 2017 tccaccaaga cttaagtttt get <210> 96 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 96 gaggctgaac cccgtcc 17 <210> 97 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 97 ctttttcata gagtcctgt 19 <210> 98 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 98 ttagtcttga agtgagggt 19 <210> 99 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 99 taettattta cgcttgaacc tc 22 <210> 100 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 100 ccagctgccc gcaggcc 17 <210> 101 <211> 17 <212> DNA <213> Artificial

Page 18

542814.st25.txt

2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 101 aattgacaga gagctcc 17 <210> 102 <211> 15 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 102 cacgacgtca cgcag 15 <210> 103 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 103 cacattcacg gtcacct 17 <210> 104 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 104 gtgcctgtgc tgggctca 18 <210> 105 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 105 gtgcctgtgc tgggctcgt 19 <210> 106 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 106 ggatggagag aaaaaaaca 19 <210> 107

Page 19

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2017265006 21 Nov 2017

<211> 20 <212> DNA <213> Artificial <220> <223> Syntheti c <400> 107 ggatggagag aaaaaaacgt <210> 108 <211> 18 <212> DNA <213> Artificial <220> <223> Synthetic <400> 108 ccctcatgtc atctacta <210> 109 <211> 19 <212> DNA <213> Artificial <220> <223> Synthetic <400> 109 ccctcatgtc atctactgc <210> 110 <211> 18 <212> DNA <213> Artificial <220> <223> Synthetic <400> 110 gtcacccact ctgttgcc <210> 111 <211> 19 <212> DNA <213> Artificial <220> <223> Synthetic <400> 111 gtcacccact ctgttgcgc <210> 112 <211> 18 <212> DNA <213> Artificial <220> <223> Synthetic <400> 112

Page 20

542814.st25.txt

2017265006 21 Nov 2017 caaagatggg cgtgatga <210> 113 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 113 caaagatggg cgtgatggc 19 <210> 114 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 114 ccttgccggt gctcttgtcc a 21 <210> 115 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 115 ccttgccggt gctcttgtcc gt 22 <210> 116 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 116 cagaatcctt cctgttacgg c 21 <210> 117 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 117 cagaatcctt cctgttacgg tc 22 <210> 118 <211> 24 <212> DNA <213> Artificial

Page 21

542814.st25.txt

2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 118 tccaccaaga cttaagtttt gctc 24 <210> 119 <211> 25 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 119 tccaccaaga cttaagtttt gcttc 25 <210> 120 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 120 gaggctgaac cccgtccc 18 <210> 121 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 121 gaggctgaac cccgtcctc 19 <210> 122 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 122 ctttttcata gagtcctgtt 20 <210> 123 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 123 ctttttcata gagtcctgta ac 22 <210> 124

Page 22

542814.st25.txt

2017265006 21 Nov 2017 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 124 ttagtcttga agtgagggta 20 <210> 125 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 125 ttagtcttga agtgagggtg t 21 <210> 126 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 126 tacttattta cgcttgaacc tea 23 <210> 127 <211> 24 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 127 tacttattta cgcttgaacc tega 24 <210> 128 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 128 ccagctgccc gcaggcca 18 <210> 129 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 129

Page 23

542814.st25.txt

2017265006 21 Nov 2017 ccagctgccc gcaggccgt 19 <210> 130 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 130 aattgacaga gagctccc 18 <210> 131 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 131 aattgacaga gagctcctg 19 <210> 132 <211> 16 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 132 cacgacgtca cgcagc 16 <210> 133 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 133 cacgacgtca cgcagga 17 <210> 134 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 134 cacattcacg gtcacctc 18 <210> 135 <211> 19 <212> DNA <213> Artificial

Page 24

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2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 135 cacattcacg gtcaccttg 19 <210> 136 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 136 ctaccaggaa tggccttgtc c 21 <210> 137 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 137 ctctcaggtc tggtgtcatc c 21 <210> 138 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 138 gattagcata cttagactac tacctccatg 30 <210> 139 <211> 27 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 139 gatcaacttc tgaaaaagca ttcccac 27 <210> 140 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 140 tcgtgagaat gtcttcccat t 21 <210> 141

Page 25

542814.st25.txt

2017265006 21 Nov 2017

<211> 29 <212> DNA <213> Artificial <220> <223> Syntheti c <400> 141 tcttggattg atttgagata agtgaaatc <210> 142 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 142 acgttggatg gcttgttaac cagctttgcc <210> 143 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 143 acgttggatg tttttcagac tggcagagcg <210> 144 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 144 acgttggatg tttttcagac tggcagagcg <210> 145 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 145 acgttggatg gcttgttaac cagctttgcc <210> 146 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 146

Page 26

542814.st25.txt

2017265006 21 Nov 2017 acgttggatg ttgctggcac ccaatggaag <210> 147 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 147 acgttggatg atgagagaca tgacgatgcc <210> 148 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 148 acgttggatg tggtggacat ggtgaatgac <210> 149 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 149 acgttggatg tggtgcagat gctcacatag <210> 150 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 150 acgttggatg cacagagaga gtctggacac <210> 151 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 151 acgttggatg ctcttggtct ttccctcatc <210> 152 <211> 30 <212> DNA <213> Artificial

Page 27

542814.st25.txt

2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 152 acgttggatg cctctgatcc tctttgcttc 30 <210> 153 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 153 acgttggatg aagagggagt ggaagggaag 30 <210> 154 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 154 acgttggatg acagctctgc attcagcacg 30 <210> 155 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 155 acgttggatg agtcaatccc tttggtgctc 30 <210> 156 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 156 acgttggatg actgaagctc cacaatttgg 30 <210> 157 <211> 31 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 157 acgttggatg gccactctag tactatatct g 31 <210> 158

Page 28

542814.st25.txt

2017265006 21 Nov 2017 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 158 acgttggatg gggtattcat aagctgaaac <210> 159 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 159 acgttggatg ccttcaagtt cagtggtcag <210> 160 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 160 acgttggatg ggtcaatgaa gagaacttgg <210> 161 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 161 acgttggatg aatgtttatt gtagaaaacc <210> 162 <211> 15 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 162 agctttgcca gttcc <210> 163 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 163

Page 29

542814.st25.txt

2017265006 21 Nov 2017 aaaagcaaaa ttgcctga 18 <210> 164 <211> 15 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 164 cacgacgtca cgcag 15 <210> 165 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 165 acctccgctg caaatac 17 <210> 166 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 166 gagtctggac acgtgggg 18 <210> 167 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 167 tccatctctg tggatctcc 19 <210> 168 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 168 tgctgcaggc cccagatga 19 <210> 169 <211> 21 <212> DNA <213> Artificial

Page 30

542814.st25.txt

2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 169 cacaatttgg tgaattatca a 21 <210> 170 <211> 15 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 170 agctgaaact tctgg 15 <210> 171 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 171 tcaagcttgc caaagtaatc 20 <210> 172 <211> 16 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 172 agctttgcca gttcct 16 <210> 173 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 173 agctttgcca gttccgt 17 <210> 174 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 174 aaaagcaaaa ttgcctgat 19 <210> 175

Page 31

542814.st25.txt

2017265006 21 Nov 2017 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 175 aaaagcaaaa ttgcctgagg c 21 <210> 176 <211> 16 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 176 cacgacgtca cgcagc 16 <210> 177 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 177 cacgacgtca cgcagga 17 <210> 178 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 178 acctccgctg caaataca 18 <210> 179 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 179 acctccgctg caaatacgt 19 <210> 180 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 180

Page 32

542814.st25.txt

2017265006 21 Nov 2017 gagtctggac acgtgggga 19 <210> 181 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 181 gagtctggac acgtggggga 20 <210> 182 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 182 tccatctctg tggatctcca 20 <210> 183 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 183 tccatctctg tggatctccg t 21 <210> 184 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 184 tgctgcaggc cccagatgat 20 <210> 185 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 185 tgctgcaggc cccagatgag c 21 <210> 186 <211> 22 <212> DNA <213> Artificial

Page 33

542814.st25.txt

2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 186 cacaatttgg tgaattatca at 22 <210> 187 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 187 cacaatttgg tgaattatca aat 23 <210> 188 <211> 16 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 188 agctgaaact tctggc 16 <210> 189 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 189 agctgaaact tctggga 17 <210> 190 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 190 tcaagcttgc caaagtaatc t 21 <210> 191 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 191 tcaagcttgc caaagtaatc gga 23 <210> 192

Page 34

542814.st25.txt

2017265006 21 Nov 2017 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 192 ctgccctact tgattgatgg 20 <210> 193 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 193 atcttctcct cttctgtctc 20 <210> 194 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 194 ttctggattg tagcagatca 20 <210> 195 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 195 tcgtgagaat gtcttcccat t 21 <210> 196 <211> 29 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 196 tcttggattg atttgagata agtgaaatc 29

<210> 197 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 197

Page 35

542814.st25.txt

2017265006 21 Nov 2017 acgttggatg aaaccagagg gaagcaaagg 30 <210> 198 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 198 acgttggatg tcattggttg tgctgcacct 30 <210> 199 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 199 acgttggatg caccaggaac cgtttatggc 30 <210> 200 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 200 acgttggatg agcagctaga atcagaggag 30 <210> 201 <211> 31 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 201 acgttggatg gtcaatgaag agaacttggt c 31 <210> 202 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 202 acgttggatg aatgtttatt gtagaaaacc 30 <210> 203 <211> 30 <212> DNA <213> Artificial

Page 36

542814.st25.txt

2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 203 acgttggatg gggtattcat aagctgaaac <210> 204 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 204 acgttggatg ccttcaagtt cagtggtcag <210> 205 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 205 acgttggatg gtgattatct ttggcatggg <210> 206 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 206 acgttggatg ggatagccag gaagagaaag <210> 207 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 207 acgttggatg ccctatttct ttgtcttcac <210> 208 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 208 acgttggatg cttgggataa tttggctctg <210> 209

Page 37

542814.st25.txt

2017265006 21 Nov 2017 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 209 acgttggatg ggaacccttt ctgcgctttg <210> 210 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 210 acgttggatg cctacaggtg ctgttcagtg <210> 211 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 211 acgttggatg cctgccaaag aagaaacacc <210> 212 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 212 acgttggatg acgtctgcag gtatgtattc <210> 213 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 213 acgttggatg gttcttaatt cataggttgc <210> 214 <211> 32 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 214

Page 38

542814.st25.txt

2017265006 21 Nov 2017

acgttggatg cttcatttct catcatattt <210> 215 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 215 acgttggatg taggtgtctc cccctgtaag <210> 216 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 216 acgttggatg tcctctccag agtgatcaag <210> 217 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 217 acgttggatg attttctcct cagaggctcc <210> 218 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 218 acgttggatg tgtctgtatt gagggtgtgg <210> 219 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 219 acgttggatg ttgtggctgc aacatgagag <210> 220 <211> 30 <212> DNA <213> Artificial

Page 39

542814.st25.txt

2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 220 acgttggatg ctatggcgca acatctgtac 30 <210> 221 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 221 acgttggatg actgtagttt ccctagtccc 30 <210> 222 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 222 acgttggatg agtcagcaga gagactaggg 30 <210> 223 <211> 31 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 223 acgttggatg gagttgagaa tggagagaat g 31 <210> 224 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 224 acgttggatg tcaagtgggc tgttagggtg 30 <210> 225 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 225 acgttggatg tgctgcgtgg tgggcgtgtg 30 <210> 226

Page 40

542814.st25.txt

2017265006 21 Nov 2017 <211> 29 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 226 acgttggatg ggccttgcac tcgctctcg 29 <210> 227 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 227 acgttggatg aaacggtcgc ttcgacgtgc 30 <210> 228 <211> 29 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 228 acgttggatg acctcaagga ccagctcgg 29 <210> 229 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 229 acgttggatg actgaagctc cacaatttgg 30 <210> 230 <211> 31 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 230 acgttggatg gccactctag tactatatct g 31 <210> 231 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 231

Page 41

542814.st25.txt

2017265006 21 Nov 2017 acgttggatg cagacattca caattgattt 30 <210> 232 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 232 acgttggatg gatagttcca aacatgtgcg 30 <210> 233 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 233 acgttggatg taaggagtgg gtgctggact 30 <210> 234 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 234 acgttggatg aggataagga gcagggttgg 30 <210> 235 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 235 ttcttggttc aggagag 17 <210> 236 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 236 ttcttggttc aggagagc 18 <210> 237 <211> 19 <212> DNA <213> Artificial

Page 42

542814.st25.txt

2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 237 gcaatctgct ctatcctct 19 <210> 238 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 238 gcaatctgct ctatcctctt 20 <210> 239 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 239 attcaagctt gccaaagtaa tc 22 <210> 240 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 240 attcaagctt gccaaagtaa tct 23 <210> 241 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 241 cataagctga aacttctgg 19 <210> 242 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 242 cataagctga aacttctggc 20 <210> 243

Page 43

542814.st25.txt

2017265006 21 Nov 2017 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 243 ggaagtgtat cggtgagacc 20 <210> 244 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 244 ggaagtgtat cggtgagacc a 21 <210> 245 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 245 tgacaaatac tggttaatta gca 23 <210> 246 <211> 24 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 246 tgacaaatac tggttaatta gcaa 24 <210> 247 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 247 gctcctgagc atggcgg 17 <210> 248 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 248

Page 44

542814.st25.txt

2017265006 21 Nov 2017 gctcctgagc atggcggc <210> 249 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 249 tacttattta cgcttgaacc tc 22 <210> 250 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 250 tacttattta cgcttgaacc tea 23 <210> 251 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 251 cttaattcat aggttgcaat ttt 23 <210> 252 <211> 24 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 252 cttaattcat aggttgcaat ttta 24 <210> 253 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 253 acatcaccct cacttac 17 <210> 254 <211> 18 <212> DNA <213> Artificial

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2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 254 acatcaccct cacttacc 18 <210> 255 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 255 aattgacaga gagctcc 17 <210> 256 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 256 aattgacaga gagctccc 18 <210> 257 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 257 atgagaggct cacagacgtt 20 <210> 258 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 258 atgagaggct cacagacgtt c 21 <210> 259 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 259 ggcatcaagc tcttccctgg c 21 <210> 260

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542814.st25.txt

2017265006 21 Nov 2017 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 260 ggcatcaagc tcttccctgg cc 22 <210> 261 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 261 gaatgttacc tctcctg 17 <210> 262 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 262 gaatgttacc tctcctga 18 <210> 263 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 263 gcactcagag cgcaagaag 19 <210> 264 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 264 gcactcagag cgcaagaagc 20 <210> 265 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 265

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542814.st25.txt

2017265006 21 Nov 2017 gctgctgcag gccccagatg a 21 <210> 266 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 266 gctgctgcag gccccagatg at 22 <210> 267 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 267 cacaatttgg tgaattatca a 21 <210> 268 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 268 cacaatttgg tgaattatca at 22 <210> 269 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 269 ttcttacaac acaaaatcaa ate 23 <210> 270 <211> 24 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 270 ttcttacaac acaaaatcaa atet 24 <210> 271 <211> 17 <212> DNA <213> Artificial

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2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 271 tcggcggctg ccctccc 17 <210> 272 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 272 tcggcggctg ccctccca 18 <210> 273 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 273 ttcttggttc aggagaggt 19 <210> 274 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 274 gcaatctgct ctatcctctg c 21 <210> 275 <211> 25 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 275 attcaagctt gccaaagtaa tcgga 25 <210> 276 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 276 cataagctga aacttctggg a 21 <210> 277

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542814.st25.txt

2017265006 21 Nov 2017

<211> <212> <213> 22 DNA Artificial <220> <223> Syntheti c <400> 277 ggaagtgtat cggtgagacc gt <210> 278 <211> 25 <212> DNA <213> Artificial <220> <223> Synthetic <400> 278 tgacaaatac tggttaatta gcagt <210> 279 <211> 19 <212> DNA <213> Artificial <220> <223> Synthetic <400> 279 gctcctgagc atggcggga <210> 280 <211> 24 <212> DNA <213> Artificial <220> <223> Synthetic <400> 280 tacttattta cgcttgaacc tcga <210> 281 <211> 25 <212> DNA <213> Artificial <220> <223> Synthetic <400> 281 cttaattcat aggttgcaat tttgt <210> 282 <211> 19 <212> DNA <213> Artificial <220> <223> Synthetic <400> 282

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542814.st25.txt

2017265006 21 Nov 2017 acatcaccct cacttactg 19 <210> 283 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 283 aattgacaga gagctcctg 19 <210> 284 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 284 atgagaggct cacagacgtt tc 22 <210> 285 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 285 ggcatcaagc tcttccctgg ctg 23 <210> 286 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 286 gaatgttacc tctcctggc 19 <210> 287 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 287 gcactcagag cgcaagaagg ggc 23 <210> 288 <211> 23 <212> DNA <213> Artificial

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542814.st25.txt

2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 288 gctgctgcag gccccagatg age 23 <210> 289 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 289 cacaatttgg tgaattatca aat 23 <210> 290 <211> 25 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 290 ttcttacaac acaaaatcaa atcac 25 <210> 291 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 291 teggeggetg ccctcccgga 20 <210> 292 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 292 acgttggatg aggtagctga agaggcaaac 30 <210> 293 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 293 acgttggatg gcctatagcc tetaaaaege 30 <210> 294

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542814.st25.txt

2017265006 21 Nov 2017

<211> 30 <212> DNA <213> Artificial <220> <223> Syntheti c <400> 294 acgttggatg ctttcaattt gtggaggctg <210> 295 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 295 acgttggatg tgtgcactca tttgtggacg <210> 296 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 296 acgttggatg gtagctctcc aggcatcaac <210> 297 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 297 acgttggatg gtacctggtt cccccttttc <210> 298 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 298 acgttggatg acaccaggcg tttgatgttg <210> 299 <211> 30 <212> DNA <213> Artificial <220> <223> Synthetic <400> 299

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542814.st25.txt

2017265006 21 Nov 2017 acgttggatg aaaaacgcca acagcatcgg 30 <210> 300 <211> 29 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 300 acgttggatg aggcggagat gggtgtgtc 29 <210> 301 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 301 acgttggatg agtctagggt ggggtatgtg 30 <210> 302 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 302 acgttggatg atgtgtggat tcacagctcg 30 <210> 303 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 303 acgttggatg gggttggcaa ctctaaaagg 30 <210> 304 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 304 acgttggatg ctctgaaatc agtgctgctc 30 <210> 305 <211> 30 <212> DNA <213> Artificial

Page 54

542814.st25.txt

2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 305 acgttggatg atggtcaaca gtgttgccag 30 <210> 306 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 306 acgttggatg cacctcttga ttgctttccc 30 <210> 307 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 307 acgttggatg acccggcctt cctgatcatg 30 <210> 308 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 308 acgttggatg attccatgga ggctggatag 30 <210> 309 <211> 30 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 309 acgttggatg gacaacacta ctaaggcttc 30 <210> 310 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 310 aaaaggtttc tcccccc 17 <210> 311

Page 55

542814.st25.txt

2017265006 21 Nov 2017

<211> 18 <212> DNA <213> Artificial <220> <223> Syntheti c <400> 311 aaaaggtttc tccccccc <210> 312 <211> 17 <212> DNA <213> Artificial <220> <223> Synthetic <400> 312 aggctgcttc ttggact <210> 313 <211> 18 <212> DNA <213> Artificial <220> <223> Synthetic <400> 313 aggctgcttc ttggactc <210> 314 <211> 17 <212> DNA <213> Artificial <220> <223> Synthetic <400> 314 caaagatggg cgtgatg <210> 315 <211> 18 <212> DNA <213> Artificial <220> <223> Synthetic <400> 315 caaagatggg cgtgatga <210> 316 <211> 17 <212> DNA <213> Artificial <220> <223> Synthetic <400> 316

Page 56

542814.st25.txt

2017265006 21 Nov 2017 gccagccccg ggacgga 17 <210> 317 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 317 gccagccccg ggacggac 18 <210> 318 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 318 atgggtgtgt ctgccgg 17 <210> 319 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 319 atgggtgtgt ctgccgga 18 <210> 320 <211> 19 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 320 ggctgtaagg aaatctggg 19 <210> 321 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 321 ggctgtaagg aaatctggga 20 <210> 322 <211> 20 <212> DNA <213> Artificial

Page 57

542814.st25.txt

2017265006 21 Nov 2017 <220>

<223> Synthetic <400> 322 ccttatcctc ctcctgggaa 20 <210> 323 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 323 ccttatcctc ctcctgggaa a 21 <210> 324 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 324 tgtttcattt ctataggcga 20 <210> 325 <211> 21 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 325 tgtttcattt ctataggcga t 21 <210> 326 <211> 17 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 326 cctatcccta cttcccc 17 <210> 327 <211> 18 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 327 cctatcccta cttccccc 18 <210> 328

Page 58

542814.st25.txt

2017265006 21 Nov 2017

<211> 19 <212> DNA <213> Artificial <220> <223> Syntheti c <400> 328 aaaaggtttc tccccccga <210> 329 <211> 19 <212> DNA <213> Artificial <220> <223> Synthetic <400> 329 aggctgcttc ttggactga <210> 330 <211> 19 <212> DNA <213> Artificial <220> <223> Synthetic <400> 330 caaagatggg cgtgatggc <210> 331 <211> 19 <212> DNA <213> Artificial <220> <223> Synthetic <400> 331 gccagccccg ggacggagt <210> 332 <211> 19 <212> DNA <213> Artificial <220> <223> Synthetic <400> 332 atgggtgtgt ctgccgggt <210> 333 <211> 22 <212> DNA <213> Artificial <220> <223> Synthetic <400> 333

Page 59

542814.st25.txt

2017265006 21 Nov 2017 ggctgtaagg aaatctgggg gt 22 <210> 334 <211> 22 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 334 ccttatcctc ctcctgggaa ga 22 <210> 335 <211> 23 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 335 tgtttcattt ctataggcga gga 23 <210> 336 <211> 20 <212> DNA <213> Artificial <220>

<223> Synthetic <400> 336 cctatcccta cttccccttc 20

Page 60