US20110182872A1

US20110182872A1 - Methods of analysis of polymorphisms and uses thereof

Info

Publication number: US20110182872A1
Application number: US13/049,612
Authority: US
Inventors: Robert Peter Young
Original assignee: Synergenz Bioscience Ltd
Current assignee: Synergenz Bioscience Ltd
Priority date: 2005-05-20
Filing date: 2011-03-16
Publication date: 2011-07-28
Also published as: US20130345287A1; WO2006123943A1; EP1888779A4; EP1888779A1; US7933722B2; AU2006248189A1; US20060275808A1

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.

Description

RELATED APPLICATIONS

This application claims priority to New Zealand Application Nos. 540249, filed May 20, 2005 and 541842, filed Aug. 15, 2005, both of which are incorporated by reference in their entireties.

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 can 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.

SUMMARY OF THE INVENTION

Recent studies have identified a number of genetic variants or polymorphisms that confer susceptibility to protection from COPD, occupational COPD (OCOPD), and lung cancer. The biological basis of just how these polymorphisms interact or combine to determine risk remains unclear.
Surprisingly, it has now been 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, it has presently been 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 includes:

- 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 developing said disease.

The value assigned to each protective polymorphism can be the same or can be different. The value assigned to each susceptibility polymorphism can be the same or can 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 can 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); CC (homozygous P allele) within codon 10 of the gene encoding transforming growth factor beta (TGFβ); 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 co-inherited. This means that in genotyping, detection of one polymorphism as present implies the presence of the other. (Reich, D. E. et al. Linkage disequilibrium in the human genome. Nature 411:199-204 (2001), herein incorporated by reference in its entirety).
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 (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 a1-antitrypsin (a1AT); 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 can 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 Gln 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; Ile 105 Val AA in the gene encoding glutathione S-transferase (GSTP1); MS in the gene encoding a 1-antitrypsin (a 1 AT); the +489 GG geneotype in the gene encoding Tissue 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 Gln 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 Gln 27 Glu GG genotype in the gene encoding 132 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.
Preferably, the susceptibility polymorphisms analysed are selected from one or more of the group consisting of: Arg 16 Gly GG in the gene encoding β2-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 (IFN?); 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); 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); 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 can 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 Gln AG or GG in the gene encoding SOD3; MS or SS in the gene encoding a1AT; Asp 299 Gly AG or GG in the gene encoding toll-like receptor 4 (TLR4); Gln 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.
Preferably, 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; Ile 105 Val GG in the gene encoding GSTP1; Arg 312 Gln 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 a 1AT; −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.
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 lung cancer, the protective polymorphisms analysed can 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 Gln 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 5AC (MUC5AC); the intron 1 C/T TT genotype in the gene encoding Arginase 1 (Arg1); the Leu252Val 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 Gln 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 Ile 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 glycolase (OGG1); the Phe 257 Ser CC genotype in the gene encoding REV1; or one or more polymorphisms in linkage disequilibrium with any one or more of these polymorphisms.
Preferably, all polymorphisms of the group are analysed.
Preferably, 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 IFN?; 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; −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 Gln 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 Gln 185 Glu CC genotype in the gene encoding Nibrin (NBS1); the Asp 148 Glu GG genotype in the gene encoding Apex nuclease (APE1); 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 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.
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;
- 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 developing said disease.

In a further aspect the present invention provides a method for assessing the risk of a subject developing a disease which includes

- 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,
- 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 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 includes 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

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

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

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

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

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

DESCRIPTION OF THE PREFERRED EMBODIMENTS

There is a need for a method for assessing a subject's risk of developing a disease using genetic (and optionally non-genetic) risk factors. In some embodiments, 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.
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 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 “polymorphism” 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 can 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 substitutions and short deletion and insertion polymorphisms. It will further be understood that the term “disease” is used herein in its widest possible sense, and includes conditions which can 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 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 relevant to this invention is that a combined analysis of protective and susceptibility polymorphisms discriminatory 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 includes 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 can be assigned a high weighting, for example a polymorphism with a high Odd's ratio can be considered highly discriminatory of disease, and can be assigned a high weighting.
Accordingly, in a first aspect, the present invention provides a method of assessing a subject's risk of developing a disease which includes:
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 developing said disease.
The subject sample can have already been analysed for the presence or absence of one or more protective or susceptibility polymorphisms, and the method includes the steps of

- 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 developing said disease.

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 International Application No. PCT/NZ02/00106 (published as WO 02/099134 and herein incorporated by reference in its entirety) 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 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 implies the presence of the other. (Reich D E 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.


				LD
		rs	Alleles	between	Phenotype
Gene	SNPs	numbers	in LD	alleles	in COPD

Interleukin-	IL18 −133	rs360721	C allele	Strong LD	CC
18	C/G				susceptible
	IL18 105	rs549908	A allele		AA
	A/C				susceptible
Vitamin D	VDBP	rs4588	A allele	Strong LD	AA/AC
binding	Lys 420				protective
protein	Thr
	VDBP	rs7041	T allele		TT/TG
	Glu 416				protective
	Asp

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.
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. In some embodiments, a 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 of human genomic DNA, with a haploid genome of 3×10⁹base 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 (Matsuzaki, H. et al. Genome Res. 14:414-425 (2004); Matsuzaki, H. et al. Nat. Methods 1:109-111 (2004); Sethi, A. A. et al. Clin. Chem. 50(2):443-446 (2004), each of the foregoing which is herein incorporated by reference in its entirety). 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, each of the foregoing which is herein incorporated by reference in its entirety). US Application 20050059030 (incorporated herein in 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 (herein incorporated by reference 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, herein incorporated by reference in its entirety). 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 (Ross, P. L. et al. Discrimination of single-nucleotide polymorphisms in human DNA using peptide nucleic acid probes detected by MALDI-TOF mass spectrometry. Anal. Chem. 69, 4197-4202 (1997), herein incorporated by reference in its entirety). 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 includes 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 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 (each of the foregoing which is herein incorporated by reference in its entirety).
U.S. Pat. No. 6,821,733 (herein incorporated by reference 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 ProteomIQ™ 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 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 glycosylation, 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 (Sloane, A. J. et al. High throughput peptide mass fingerprinting and protein macroarray analysis using chemical printing strategies. Mol Cell Proteomics 1(7):490-9 (2002), herein incorporated by reference in its entirety). 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 86:2766-2770 (1989), herein incorporated by reference in its entirety) 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 detectably 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 (Gasparini, P. et al. Scanning the first part of the neurofibromatosis type 1 gene by RNA-SSCP: identification of three novel mutations and of two new polymorphisms. Hum Genet. 97(4):492-5 (1996), herein incorporated by reference in its entirety), restriction endonuclease fingerprinting-SSCP (Liu, Q. et al. Restriction endonuclease fingerprinting (REF): a sensitive method for screening mutations in long, contiguous segments of DNA. Biotechniques 18(3):470-7 (1995), herein incorporated by reference in its entirety), dideoxy fingerprinting (a hybrid between dideoxy sequencing and SSCP) (Sarkar, G. et al. Dideoxy fingerprinting (ddF): a rapid and efficient screen for the presence of mutations. Genomics 13:441-443 (1992), herein incorporated by reference in its entirety), bi-directional dideoxy fingerprinting (in which the dideoxy termination reaction is performed simultaneously with two opposing primers) (Liu, Q. et al. Bi-directional dideoxy fingerprinting (Bi-ddF): a rapid method for quantitative detection of mutations in genomic regions of 300-600 bp. Hum Mol. Genet. 5(1):107-14 (1996), herein incorporated by reference in its entirety), and Fluorescent PCR-SSCP (in which PCR products are internally labelled with multiple fluorescent dyes, can be digested with restriction enzymes, followed by SSCP, and analysed on an automated DNA sequencer able to detect the fluorescent dyes) (Makino, R. et al. F-SSCP: fluorescence-based polymerase chain reaction-single-strand conformation polymorphism (PCR-SSCP) analysis. PCR Methods Appl. 2(1):10-13 (1992), herein incorporated by reference in its entirety).
Other methods which utilise the varying mobility of different nucleic acid structures include Denaturing Gradient Gel Electrophoresis (DGGE) (Cariello, N. F. et al. Resolution of a missense mutant in human genomic DNA by denaturing gradient gel electrophoresis and direct sequencing using in vitro DNA amplification: HPRT Munich. Am J Hum Genet. 42(5):726-34 (1988), herein incorporated by reference in its entirety), Temperature Gradient Gel Electrophoresis (TGGE) (Riesner, D. et al. Temperature-gradient gel electrophoresis for the detection of polymorphic DNA and for quantitative polymerase chain reaction. Electrophoresis. 13:632-6 (1992), herein incorporated by reference in its entirety), and Heteroduplex Analysis (HET) (Keen, J. et al. Rapid detection of single base mismatches as heteroduplexes on Hydrolink gels. Trends Genet. 7(1):5 (1991), herein, incorporated by reference in its entirety). 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 different rates, thereby enabling detection of mismatch nucleotides and thus SNPs (Giordano, M. et al. Identification by denaturing high-performance liquid chromatography of numerous polymorphisms in a candidate region for multiple sclerosis susceptibility. Genomics 56(3):247-53 (1999), herein incorporated by reference in its entirety).
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 (Moore, W. et al. Mutation detection in the breast cancer gene BRCA1 using the protein truncation test. Mol. Biotechnol. 14(2):89-97 (2000), herein incorporated by reference in its entirety). 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 binding protein to the heteroduplex protects the heteroduplex from exonuclease degradation.
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 (each of the foregoing which is herein incorporated by reference in its entirety).
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 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 can have a value of −2, whereas another more weakly protective polymorphism can 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 can 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 smoker, the methods of the invention can provide motivation to quit smoking. In this latter case, a ‘quit smoking’ program can be followed, which can include the use of anti-smoking medicaments (such as nicotine patches and the like) as well as anti-addiction 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 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 non-limiting 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 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 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 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, incorporated herein in its entirety by reference], all subjects were genotyped for the α1-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
Median (IQR)	N = 294	N = 217	Differences

% 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
FEV1 % 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 a1-antitrypsin Genotyping

Genomic DNA was extracted from whole blood samples [2, herein incorporated by reference in its entirety]. The Cyclo-oxygenase 2 −765 polymorphism was determined by minor modifications of a previously published method [3, herein incorporated by reference in its entirety]. The PCR reaction was carried out in a total volume of 25 ul and contained 20 ng genomic DNA, 500 pmol forward and reverse primers, 0.2 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.0 mM MgCl₂and 1 unit of polymerase (Life Technologies). Cycling times were incubations for 3 min at 95° C. followed by 33 cycles of 50 s at 94° C., 60 s at 66° C. and 60 s at 72° C. A final elongation of 10 min at 72° C. then followed. 4 ul of PCR products were visualised by ultraviolet trans-illumination of a 3% agarose gel stained with ethidium bromide. An aliquot of 3 ul of amplification product was digested for 1 hr with 4 units of AciI (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 123 bp ladder using ultraviolet transillumination after ethidium bromide staining. Using a PCR based method referenced above [1, herein incorporated by reference in its entirety], all COPD and resistant smoker subjects were genotyped for the α1-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 10× Buffer 15 mM MgCl₂1.25×, 25 mM MgCl₂1.625 mM, dNTP mix 25 mM 500 uM, primers 4 uM 100 nM, Taq polymerase (Qiagen hot start) 0.15 U/reaction, Genomic DNA 10 ng/ul. Cycling times were 95° C. for 15 mM, (5° C. for 15 s, 56° C. 30 s, 72° C. 30 s for 45 cycles with a prolonged extension time of 3 min to finish. Shrimp alkaline phosphotase (SAP) treatment was used (2 ul to 5 ul per PCR reaction) incubated at 35° C. for 30 min and extension reaction (add 2 ul to 7 ul after SAP treatment) with the following volumes per reaction of: water, 0.76 ul; hME 10× termination buffer, 0.2 ul; hME primer (10 uM), 1 ul; MassEXTEND enzyme, 0.04 ul.

Sequenom Conditions for the Polymorphisms Genotyping—1


SNP_ID	TERM	WELL	2nd-PCRP	1st-PCRP

Vitamin	ACT	W1	ACGTTGGATGGCTTGTTAACCAGCTTTGCC	ACGTTGGATGTTTTTCAGACTGGCAGAGCG [SEQ. ID. NO. 2]
DBP-420			[SEQ. ID. NO. 1]

Vitamin	ACT	W1	ACGTTGGATGTTTTTCAGACTGGCAGAGCG	ACGTTGGATGGCTTGTTAACCAGCTTTGCC [SEQ. ID. NO. 4]
DBP-416			[SEQ. ID. NO. 3]

IL13 C-	ACT	W2	ACGTTGGATGCATGTCGCCTTTTCCTGCTC	ACGTTGGATGCAACACCCAACAGGCAAATG [SEQ. ID. NO. 6]
1055T			[SEQ. ID. NO. 5]

GSTP1-	ACT	W2	ACGTTGGATGTGGTGGACATGGTGAATGAC	ACGTTGGATGTGGTGCAGATGCTCACATAG [SEQ. ID. NO. 8]
105			[SEQ. ID. NO. 7]

PAI1 G-	ACT	W2	ACGTTGGATGCACAGAGAGAGTCTGGACAC	ACGTTGGATGCTCTTGGTCTTTCCCTCATC [SEQ. ID. NO. 10]
675G			[SEQ. ID. NO. 9]

NOS3-	ACT	W3	ACGTTGGATGACAGCTCTGCATTCAGCACG	ACGTTGGATGAGTCAATCCCTTTGGTGCTC [SEQ. ID. NO. 12]
298			[SEQ. ID. NO. 11]

IL13-	ACT	W3	ACGTTGGATGGTTTTCCAGCTTGCATGTCC	ACGTTGGATGCAATAGTCAGGTCCTGTCTC [SEQ. ID. NO. 14]
Arg130Gln			[SEQ. ID. NO. 13]

ADRB2-	ACT	W3	ACGTTGGATGGAACGGCAGCGCCTTCTTG	ACGTTGGATGACTTGGCAATGGCTGTGATG [SEQ. ID. NO. 16]
Arg16Gly			[SEQ. ID. NO. 15]

IFNG-	CGT	W5	ACGTTGGATGCAGACATTCACAATTGATTT	ACGTTGGATGGATAGTTCCAAACATGTGCG [SEQ. ID. NO. 18]
A874T			[SEQ. ID. NO. 17]

IL18-C-	ACT	W6	ACGTTGGATGGGGTATTCATAAGCTGAAAC	ACGTTGGATGCCTTCAAGTTCAGTGGTCAG [SEQ. ID. NO. 20]
133G			[SEQ. ID. NO. 19]

IL18-	ACT	W8	ACGTTGGATGGGTCAATGAAGAGAACTTGG	ACGTTGGATGAATGTTTATTGTAGAAAACC [SEQ. ID. NO. 22]
A105C			[SEQ. ID. NO. 21]

Sequenom Conditions for the Polymorphisms Genotyping—2


SNP_ID	AMP_LEN	UP_CONF	MP_CONF	Tm(NN)	PcGC	PWARN	UEP_DIR

Vitamin DBP - 420	99	99.7	99.7	46.2	53.3	ML	R
Vitamin DBP - 416	99	99.7	99.7	45.5	33.3	M	F
IL13 C-1055T	112	97.5	80	48.2	60	L	R
GSTP1 - 105	107	99.4	80	49.9	52.9		F
PAI1 G-675G	109	97.9	80	59.3	66.7	g	F
NOS3 -298	186	98.1	65	61.2	63.2		F
IL13-Arg130Gln	171	99.3	65	55.1	47.6		F
ADRB2- Arg16Gly	187	88.2	65	65.1	58.3		F
IFNG - A874T	112	75.3	81.2	45.6	27.3		F
IL18- C-133G	112	93.5	74.3	41.8	46.7	L	F
IL18- A105C	121	67.2	74.3	48.9	40		R

Sequenom Conditions for the Polymorphisms Genotyping—3


SNP_ID	UEP_MASS	UEP_SEQ	EXT1_CALL	EXT1_MASS

Vitamin DBP - 420	4518.9	AGCTTTGCCAGTTCC [SEQ. ID. NO. 23]	A	4807.1

Vitamin DBP - 416	5524.6	AAAAGCAAAATTGCCTGA [SEQ. ID. NO. 24]	T	5812.8

IL13 C-1055T	4405.9	TCCTGCTCTTCCCTC [SEQ. ID. NO. 25]	T	4703.1

GSTP1 - 105	5099.3	ACCTCCGCTGCAAATAC [SEQ. ID. NO. 26]	A	5396.5

PAI1 G-675G	5620.6	GAGTCTGGACACGTGGGG [SEQ. ID. NO. 27]	DEL	5917.9

NOS3 -298	5813.8	TGCTGCAGGCCCCAGATGA [SEQ. ID. NO. 28]	T	6102

IL13-Arg130Gln	6470.2	AGAAACTTTTTCGCGAGGGAC [SEQ. ID. NO. 29]	A	6767.4

ADRB2- Arg16Gly	7264.7	AGCGCCTTCTTGCTGGCACCCAAT [SEQ. ID. NO. 30]	A	7561.9

IFNG - A874T	6639.4	TCTTACAACACAAAATCAAATC [SEQ. ID. NO. 31]	T	6927.6

IL18- C-133G	4592	AGCTGAAACTTCTGG [SEQ. ID. NO. 32]	C	4865.2

IL18- A105C	6085	TCAAGCTTGCCAAAGTAATC [SEQ. ID. NO. 33]	A	6373.2

Sequenom Conditions for the Polymorphisms Genotyping—4


SNP_ID	EXT1_SEQ	EXT2_CALL	EXT2_MASS	EXT2_SEQ	1stPAUSE

Vitamin	AGCTTTGCCAGTTCCT [SEQ. ID. NO. 34]	C	5136.4	AGCTTTGCCAGTTCCGT	4848.2
DBP - 420				[SEQ. ID. NO. 35]

Vitamin	AAAAGCAAAATTGCCTGAT [SEQ. ID. NO. 36]	G	6456.2	AAAAGCAAAATTGCCTGAGGC	5853.9
DBP-416				[SEQ. ID. NO. 37]

IL13 C-	TCCTGCTCTTCCCTCA [SEQ. ID. NO. 38]	C	5023.3	TCCTGCTCTTCCCTCGT	4735.1
1055T				[SEQ. ID. NO. 39]

GSTP1-	ACCTCCGCTGCAAATACA [SEQ. ID. NO. 40]	G	5716.7	ACCTCCGCTGCAAATACGT	5428.5
105				[SEQ. ID. NO. 41]

PAI1 G-	GAGTCTGGACACGTGGGGA [SEQ. ID. NO. 42]	G	6247.1	GAGTCTGGACACGTGGGGGA	5949.9
675G				[SEQ. ID. NO. 43]

NOS3-	TGCTGCAGGCCCCAGATGAT [SEQ. ID. NO.	G	6416.2	TGCTGCAGGCCCCAGATGAGC	6143
298	44]			[SEQ. ID. NO. 45]

IL13-	AGAAACTTTTTCGCGAGGGACA	G	7416.8	AGAAACTTTTTCGCGAGGGACGGT	6799.4
Arg130Gln	[SEQ. ID. NO. 46]			[SEQ. ID. NO. 47]

ADRB2-	AGCGCCTTCTTGCTGGCACCCAATA	G	8220.3	AGCGCCTTCTTGCTGGCACCCAATGGA	7593.9
Arg16Gly	[SEQ. ID. NO. 48]			[SEQ. ID. NO. 49]

IFNG-	TCTTACAACACAAAATCAAATCT	A	7225.8	TCTTACAACACAAAATCAAATCAC	6952.6
A874T	[SEQ. ID. NO. 50]			[SEQ. ID. NO. 51]

IL18- C-	AGCTGAAACTTCTGGC [SEQ. ID. NO. 52]	G	5218.4	AGCTGAAACTTCTGGGA	4921.2
133G				[SEQ. ID. NO. 53]

IL18-	TCAAGCTTGCCAAAGTAATCT	C	7040.6	TCAAGCTTGCCAAAGTAATCGGA	6414.2
A105C	[SEQ. ID. NO. 54]			[SEQ. ID. NO. 55]

Sequenom Conditions for the Polymorphisms Genotyping—5


SNP_ID	2nd-PCRP	1st-PCRP

Lipoxygenase5-	ACGTTGGATGGAAGTCAGAGATGATGGCAG	ACGTTGGATGATGAATCCTGGACCCAAGAC
366G/A	[SEQ. ID. NO. 56]	[SEQ. ID. NO. 57]

TNFalpha+489G/A	ACGTTGGATGGAAAGATGTGCGCTGATAGG	ACGTTGGATGGCCACATCTCTTTCTGCATC
	[SEQ. ID. NO. 58]	[SEQ. ID. NO. 59]

SMAD3C89Y	ACGTTGGATGTTGCAGGTGTCCCATCGGAA [SEQ. ID. NO. 60]	ACGTTGGATGTAGCTCGTGGTGGCTGTGCA
		[SEQ. ID. NO. 61]

CaspaseGly881ArgG/C	ACGTTGGATGGTGATCACCCAAGGCTTCAG [SEQ. ID. NO. 62]	ACGTTGGATGGTCTGTTGACTCTTTTGGCC
		[SEQ. ID. NO. 63]

MBL2+161G/A	ACGTTGGATGGTAGCTCTCCAGGCATCAAC [SEQ. ID. NO. 64]	ACGTTGGATGGTACCTGGTTCCCCCTTTTC
		[SEQ. ID. NO. 65]

HSP70-HOM2437T/C	ACGTTGGATGTGATCTTGTTCACCTTGCCG [SEQ. ID. NO. 66]	ACGTTGGATGAGATCGAGGTGACGTTTGAC
		[SEQ. ID. NO. 67]

CD14-159C/T	ACGTTGGATGAGACACAGAACCCTAGATGC [SEQ. ID. NO. 68]	ACGTTGGATGGCAATGAAGGATGTTTCAGG
		[SEQ. ID. NO. 69]

Chymase1-1903G/A	ACGTTGGATGTAAGACAGCTCCACAGCATC [SEQ. ID. NO. 70]	ACGTTGGATGTTCCATTTCCTCACCCTCAG
		[SEQ. ID. NO. 71]

TNFalpha-308G/A	ACGTTGGATGGATTTGTGTGTAGGACCCTG [SEQ. ID. NO. 72]	ACGTTGGATGGGTCCCCAAAAGAAATGGAG
		[SEQ. ID. NO. 73]

CLCA1+13924T/A	ACGTTGGATGGGATTGGAGAACAAACTCAC [SEQ. ID. NO. 74]	ACGTTGGATGGGCAGCTGTTACACCAAAAG
		[SEQ. ID. NO. 75]

MEHTyr113HisT/C	ACGTTGGATGCTGGCGTTTTGCAAACATAC [SEQ. ID. NO. 76]	ACGTTGGATGTTGACTGGAAGAAGCAGGTG
		[SEQ. ID. NO. 77]

NAT2Arg197GlnG/A	ACGTTGGATGCCTGCCAAAGAAGAAACACC [SEQ. ID. NO. 78]	ACGTTGGATGACGTCTGCAGGTATGTATTC
		[SEQ. ID. NO. 79]

MEHHis139ArgG/A	ACGTTGGATGACTTCATCCACGTGAAGCCC [SEQ. ID. NO. 80]	ACGTTGGATGAAACTCGTAGAAAGAGCCGG
		[SEQ. ID. NO. 81]

IL-1B-511A/G	ACGTTGGATGATTTTCTCCTCAGAGGCTCC [SEQ. ID. NO. 82]	ACGTTGGATGTGTCTGTATTGAGGGTGTGG
		[SEQ. ID. NO. 83]

ADRB2Gln27GluC/G	ACGTTGGATGTTGCTGGCACCCAATGGAAG [SEQ. ID. NO. 84]	ACGTTGGATGATGAGAGACATGACGATGCC
		[SEQ. ID. NO. 85]

ICAM1E469KA/G	ACGTTGGATGACTCACAGAGCACATTCACG [SEQ. ID. NO. 86]	ACGTTGGATGTGTCACTCGAGATCTTGAGG
		[SEQ. ID. NO. 87]

Sequenom Conditions for the Polymorphisms Genotyping—6


SNP_ID	AMP_LEN	UP_CONF	MP_CONF	Tm(NN)	PcGC	UEP_DIR

Lipoxygenase5-366G/A	104	99.6	73.4	59	70.6	F
TNFalpha + 489G/A	96	99.6	73.4	45.5	38.9	F
SMAD3C89Y	107	87.3	71.7	45.7	47.1	F
CaspaseGly881ArgG/C	111	97.2	81	52.9	58.8	R
MBL2 + 161G/A	99	96.8	81	50.3	52.9	F
HSP70-HOM2437T/C	107	99.3	81	62.2	65	R
CD14-159C/T	92	98	76.7	53.3	50	F
Chymase1-1903G/A	105	99.6	76.7	53.6	39.1	R
TNFalpha-308G/A	100	99.7	81.6	59.9	70.6	R
CLCA1 + 13924T/A	101	98	98	45.3	36.8	R
MEHTyr113HisT/C	103	97.7	82.2	48.7	42.1	R
NAT2Arg197GlnG/A	115	97.4	70	48.5	36.4	F
MEHHis139ArgG/A	115	96.7	77.8	66	82.4	F
IL-1B-511A/G	111	99.2	83	46	47.1	R
ADRB2Gln27GluC/G	118	96.6	80	52.2	66.7	F
ICAM1E469KA/G	115	98.8	95.8	51.5	52.9	R

Sequenom Conditions for the Polymorphisms Genotyping—7


SNP_ID	UEP_MASS	UEP_SEQ	EXT1_CALL	EXT1_MASS

Lipoxygenase5-366G/A	5209.4	GTGCCTGTGCTGGGCTC [SEQ. ID. NO. 88]	A	5506.6

TNFalpha+489G/A	5638.7	GGATGGAGAGAAAAAAAC [SEQ. ID. NO. 89]	A	5935.9

SMAD3C89Y	5056.3	CCCTCATGTCATCTACT [SEQ. ID. NO. 90]	A	5353.5

CaspaseGly881ArgG/C	5097.3	GTCACCCACTCTGTTGC [SEQ. ID. NO. 91]	G	5370.5

MBL2+161G/A	5299.5	CAAAGATGGGCGTGATG [SEQ. ID. NO. 92]	A	5596.7

HSP70-HOM2437T/C	6026.9	CCTTGCCGGTGCTCTTGTCC [SEQ. ID. NO. 93]	T	6324.1

CD14-159C/T	6068	CAGAATCCTTCCTGTTACGG [SEQ. ID. NO. 94]	C	6341.1

Chymase1-1903G/A	6973.6	TCCACCAAGACTTAAGTTTTGCT [SEQ. ID. NO. 95]	G	7246.7

TNFalpha-308G/A	5156.4	GAGGCTGAACCCCGTCC [SEQ. ID. NO. 96]	G	5429.5

CLCA1+13924T/A	5759.8	CTTTTTCATAGAGTCCTGT [SEQ. ID. NO. 97]	A	6048

MEHTyr113HisT/C	5913.9	TTAGTCTTGAAGTGAGGGT [SEQ. ID. NO. 98]	T	6211.1

NAT2Arg197GlnG/A	6635.3	TACTTATTTACGCTTGAACCTC [SEQ. ID. NO. 99]	A	6932.5

MEHHis139ArgG/A	5117.3	CCAGCTGCCCGCAGGCC [SEQ. ID. NO. 100]	A	5414.5

IL-1B-511A/G	5203.4	AATTGACAGAGAGCTCC [SEQ. ID. NO. 101]	G	5476.6

ADRB2Gln27GluC/G	4547	CACGACGTCACGCAG [SEQ. ID. NO. 102]	C	4820.2

ICAM1E469KA/G	5090.3	CACATTCACGGTCACCT [SEQ. ID. NO. 103]	G	5363.5

Sequenom Conditions for the Polymorphisms Genotyping—8


		EXT2	EXT2			1^st
SNP_ID	EXT1_SEQ	CALL	MASS	EXT2_SEQ	PAUSE

Lipoxygenase5-	GTGCCTGTGCTGGGCTCA	G	5826.8	GTGCCTGTGCTGGGCTCGT [SEQ. ID. NO. 105]	5538.6
366G/A	[SEQ. ID. NO. 104]

TNFalpha+489G/A	GGATGGAGAGAAAAAAACA	G	6256.1	GGATGGAGAGAAAAAAACGT [SEQ. ID. NO. 107]	5967.9
	[SEQ. ID. NO. 106]

SMAD3C89Y	CCCTCATGTCATCTACTA	G	5658.7	CCCTCATGTCATCTACTGC [SEQ. ID. NO. 109]	5385.5
	[SEQ. ID. NO. 108]

CaspaseGly881ArgG/C	GTCACCCACTCTGTTGCC	C	5699.7	GTCACCCACTCTGTTGCGC [SEQ. ID. NO. 111]	5426.5
	[SEQ. ID. NO. 110]

MBL2+161G/A	CAAAGATGGGCGTGATGA	G	5901.9	CAAAGATGGGCGTGATGGC [SEQ. ID. NO. 113]	5628.7
	[SEQ. ID. NO. 112]

HSP70-HOM2437T/C	CCTTGCCGGTGCTCTTGTCCA	C	6644.3	CCTTGCCGGTGCTCTTGTCCGT	6356.1
	[SEQ. ID. NO. 114]			[SEQ. ID. NO. 115]

CD14-159C/T	CAGAATCCTTCCTGTTACGGC	T	6645.3	CAGAATCCTTCCTGTTACGGTC [SEQ. ID. NO. 117]	6372.2
	[SEQ. ID. NO. 116]

Chymase1-1903G/A	TCCACCAAGACTTAAGTTTTGCTC	A	7550.9	TCCACCAAGACTTAAGTTTTGCTTC	7277.8
	[SEQ. ID. NO. 118]			[SEQ. ID. NO. 119]

TNFalpha-308G/A	GAGGCTGAACCCCGTCCC	A	5733.7	GAGGCTGAACCCCGTCCTC [SEQ. ID. NO. 121]	5460.6
	[SEQ. ID. NO. 120]

CLCA1+13924T/A	CTTTTTCATAGAGTCCTGTT	T	6659.4	CTTTTTCATAGAGTCCTGTAAC [SEQ. ID. NO. 123]	6073
	[SEQ. ID. NO. 122]

MEHTyr113HisT/C	TTAGTCTTGAAGTGAGGGTA	C	6531.3	TTAGTCTTGAAGTGAGGGTGT [SEQ. ID. NO. 125]	6243.1
	[SEQ. ID. NO. 124]

NAT2Arg197GlnG/A	TACTTATTTACGCTTGAACCTCA	G	7261.8	TACTTATTTACGCTTGAACCTCGA	6964.5
	[SEQ. ID. NO. 126]			[SEQ. ID. NO. 127]

MEHHis139ArgG/A	CCAGCTGCCCGCAGGCCA	G	5734.7	CCAGCTGCCCGCAGGCCGT [SEQ. ID. NO. 129]	5446.5
	[SEQ. ID. NO. 128]

IL-1B-511A/G	AATTGACAGAGAGCTCCC	A	5820.8	AATTGACAGAGAGCTCCTG [SEQ. ID. NO. 131]	5507.6
	[SEQ. ID. NO. 130]

ADRB2Gln27GluC/G	CACGACGTCACGCAGC	G	5173.4	CACGACGTCACGCAGGA [SEQ. ID. NO. 133]	4876.2
	[SEQ. ID. NO. 132]

ICAM1E469KA/G	CACATTCACGGTCACCTC	A	5707.7	CACATTCACGGTCACCTTG [SEQ. ID. NO. 135]	5394.5
	[SEQ. ID. NO. 134]

Results
Frequencies of individual polymorphisms are as follows:

TABLE 1

Polymorphism allele and genotype frequencies in the COPD patients and resistant smokers.

Cyclo-oxygenase 2 −765 G/C

Allele*

Genotype

Frequency	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

Allele*

Genotype

Frequency	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

Allele*

Genotype

Frequency	C	A	CC	AC	AA

Controls n = 184 (%)	118 (32%)	250 (68%)	22 (12%)	74 (40%)	88 (48%)
COPD n = 240 (%)	122 (25%)	377⁶(75%)	21 (9%)	80 (33%)	139^{5, 7}(58%)
Resistant n = 196 (%)	113 (29%)	277 (71%)	16 (8%)	81 (41%)	99 (50%)

Interleukin 18 −133 C/G

Allele*

Genotype

Frequency	G	C	GG	GC	CC

Controls n = 187 (%)	120 (32%)	254 (68%)	23 (12%)	74 (40%)	90 (48%)
COPD n = 238	123 (26%)	353⁹(74%)	21 (9%)	81 (34%)	136⁸(57%)
Resistant n = 195 (%)	113 (29%)	277 (71%)	16 (8%)	81 (42%)	98 (50%)

Plasminogen activator inhibitor 1 −675 4G/5G

Allele*

Genotype

Frequency	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%)	54^10,11(23%)	111 (47%)	72 (30%)
Resistant n = 194 (%)	152 (39%)	236 (61%)	31 (16%)	90 (46%)	73^10,11(38%)

Nitric oxide synthase 3 Asp 298 Glu (T/G)

Allele*

Genotype

Frequency	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 Protein Lys 420 Thr (A/C)

Allele*

Genotype

Frequency	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 Protein Glu 416 Asp (T/G)

Allele*

Genotype

Frequency	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 Transferase P1 Ile 105 Val (A/G)

Allele*

Genotype

Frequency	A	G	AA	AG	GG

Controls 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 A/T

Allele*

Genotype

Frequency	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 Gln (G/A)

Allele*

Genotype

Frequency	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%)

Interleukin-13 −1055 C/T

Allele*

Genotype

Frequency	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%)

a1-antitrypsin S

Allele*

Genotype

Frequency	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%)	1²³(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, χ2 (Yates corrected)=9.43, p=0.002 GG=resistance (depending on the presence of other snps)
- 5. 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, χ2 (Yates uncorrected)=3.19, p=0.07, AA genotype=protective for COPD
- 19. Allele. A vs G for 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
- 20. 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

Tissue Necrosis Factor α +489 G/A Polymorphism Allele and Genotype Frequency in the COPD Patients and Resistant Smokers.


	1. Allele*	2. Genotype

Frequency	A	G	AA	AG	GG

COPD	54 (11%)	430 (89%)	5 (2%)	44 (18%)	193 (80%)
n = 242 (%)
Resistant	27 (7%)	347 (93%)	1 (1%)	25 (13%)	161 (86%)
n = 187 (%)

*number of chromosomes (2n)

- 1. Genotype. AA/AG vs GG for COPD vs resistant, Odds ratio (OR)=1.57, 95% confidence limits 0.9-2.7, χ²(Yates 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

Tissue Necrosis Factor α −308 G/A Polymorphism Allele and Genotype Frequency in the COPD Patients and Resistant Smokers.


	3. Allele*	4. Genotype

Frequency	A	G	AA	AG	GG

COPD	90 (19%)	394 (81%)	6 (2%)	78 (32%)	158 (65%)
n = 242 (%)
Resistant	58 (15%)	322 (85%)	3 (2%)	52 (27%)	135 (71%)
n = 190 (%)

*number of chromosomes (2n)

- 1. Genotype. GG vs AG/AA for COPD vs resistant, Odds ratio (OR)=0.77, 95% confidence limits 0.5-1.2, χ²(Yates uncorrected)=1.62, p=0.20,
  - GG=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.


	5. Allele*	6. Genotype

Frequency	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%)
(%)

*number of chromosomes (2n)

- 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.


	7. Allele*	8. Genotype

Frequency	A	G	AA	AG	GG

COPD	259 (54%)	225 (46%)	73 (30%)	113 (47%)	56 (23%)
n = 242 (%)
Resistant	217 (60%)	147 (40%)	64 (35%)	89 (49%)	29 (16%)
n = 182 (%)

*number of chromosomes (2n)

- 1. Genotype. GG vs AG/GG for COPD vs resistant, Odds ratio (OR)=1.60, 95% confidence limits 0.9-2.7, 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.


	9. Allele*	10. Genotype

Frequency	G	C	GG	GC	CC

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%)
(%)

*number of chromosomes (2n)

- 1. Genotype. CC/CG vs GG for COPD vs resistant, Odds ratio (OR)=3.2, 95% confidence limits 0.6-22, χ²(Yates uncorrected)=2.41, p=0.11 (1-tailed),
  - GC/CC=susceptibility (trend)

Mannose Binding Lectin 2(MBL2) +161 G/A Polymorphism Allele and Genotype Frequencies in the COPD Patients and Resistant Smokers.


	11. Allele*	12. Genotype

Frequency	A	G	AA	AG	GG

COPD n = 218	110 (25%)	326 (75%)	6 (3%)	98 (45%)	114 (52%)
(%)
Resistant	66 (18%)	300 (82%)	6 (3%)	54 (30%)	123 (67%)
n = 183 (%)

*number of chromosomes (2n)

- 1. Genotype. GG vs rest for COPD vs resistant, Odds ratio (OR)=0.53, 95% confidence limits 0.4-0.80, 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.


	13. Allele*	14. Genotype

Frequency	A	G	AA	AG	GG

COPD	259 (54%)	219 (46%)	67 (28%)	125 (52%)	47 (20%)
n = 239 (%)
Resistant	209 (58%)	153 (42%)	63 (35%)	83 (46%)	35 (19%)
n = 181 (%)

*number of chromosomes (2n)

- 1. Genotype. AA vs AG/GG for COPD vs resistant, Odds ratio (OR)=0.73, 95% confidence limits 0.5-1.1, χ²(Yates corrected)=1.91, p=0.17,
  - AA genotype=protective trend

N- Acetyltransferase 2 Arg 197 Gln G/A Polymorphism Allele and Genotype Frequencies in COPD and Resistant Smokers.


	15. Allele*	16. Genotype

Frequency	A	G	AA	AG	GG

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

*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 1B (IL-1B) −511 A/G Polymorphism Allele and Genotype Frequencies in COPD and Resistant Smokers.


	17. Allele*	18. Genotype

Frequency	A	G	AA	AG	GG

COPD	160 (32%)	336 (68%)	31 (13%)	98 (40%)	119 (48%)
n = 248 (%)
Resistant	142 (36%)	248 (64%)	27 (14%)	88 (45%)	80 (41%)
n = 195 (%)

*number of chromosomes (2n)

- 1. Genotype. GG vs AA/AG for COPD vs resistant, Odds ratio (OR)=1.3, 95% confidence limits 0.9-2.0, 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.


	19. Allele*	20. Genotype

Frequency	C	T	CC	CT	TT

COPD	137 (28%)	361 (72%)	18 (7%)	101 (41%)	130 (52%)
n = 249 (%)
Resistant	130 (34%)	258 (66%)	19 (10%)	92 (47%)	83 (43%)
n = 194 (%)

*number of chromosomes (2n)

- 1. Genotype. TT vs CT/CC for COPD vs resistant, Odds ratio (OR)=1.5, 95% confidence limits 1.0-2.2, 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.


	21. Allele*	22. Genotype

Frequency	A	G	AA	AG	GG

COPD n = 238	372 (78%)	104 (22%)	148 (62%)	76 (32%)	14 (6%)
(%)
Resistant	277 (77%)	81 (23%)	114 (64%)	49 (27%)	16 (9%)
n = 179 (%)

*number of chromosomes (2n)

- 1. Genotype. GG vs AA/AG for COPD vs resistant, Odds ratio (OR)=0.64, 95% confidence limits 0.3-1.4, 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.


	23. Allele*	24. Genotype

Frequency	A	G	AA	AG	GG

COPD n = 247	21 (4%)	473 (96%)	1 (0.5%)	19 (7.5%)	227 (92%)
(%)
Resistant	25 (7%)	359 (93%)	0 (0%)	25 (13%)	167 (87%)
n = 192 (%)

*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.


	25. Allele*	26. Genotype

Frequency	C	T	CC	CT	TT

COPD n = 199 (%)	127	271	5 (3%)	117 (59%)	77 (39%)
	(32%)	(68%)
Resistant n = 166	78	254	4 (2%)	70 (42%)	92 (56%)
(%)	(23%)	(77%)

*number of chromosomes (2n)

- 1. Genotype. CC/CT vs TT for COPD vs resistant, Odds ratio (OR)=2.0, 95% confidence limits 1.3-3.1, 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.


	27. Allele*	28. Genotype

Frequency	A	T	AA	AT	TT

COPD n = 224	282	166	84 (38%)	114 (51%)	26 (12%)
(%)	(63%)	(37%)
Resistant n = 158	178	138	42 (27%)	94 (59%)	22 (14%)
(%)	(56%)	(44%)

*number of chromosomes (2n)

- 1. Genotype. AA vs AT/TT for COPD vs resistant, Odds ratio (OR)=1.7, 95% confidence limits 1.0-2.7, χ²(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.


	29. Allele*	30. Genotype

Frequency	C	T	CC	CT	TT

COPD n = 240	268	212	77 (32%)	114 (48%)	49 (20%)
(%)	(56%)	(44%)
Resistant n = 180	182	178	46 (25%)	90 (50%)	44 (24%)
(%)	(51%)	(49%)

*number of chromosomes (2n)

- 1. Genotype CC vs CT/TT for COPD vs Resistant, Odds ratio (OR)=1.4, 95% confidence limits 0.9-2.2, χ₂(Yates uncorrected)=2.12, p=0.15,
  - CC=susceptible (trend)

Elafin +49 C/T Polymorphism Allele and Genotype Frequencies in the COPD Patients, Resistant Smokers and Controls.


	31. Allele*	32. Genotype

Frequency	C	T	CC	CT	TT

COPD n = 144 (%)	247	41	105 (73%)	37 (26%)	2 (1%)
	(86%)	(14%)
Resistant n = 75	121	29	49 (65%)	23 (31%)	3 (4%)
(%)	(81%)	(19%)

*number of chromosomes (2n)

- 1. Genotype. CT/TT vs CC for COPD vs resistant, Odds ratio (OR)=0.70, 95%
- confidence limits=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 Gln 27 Glu Polymorphism Allele and Genotype Frequency in the COPD Patients, Resistant Smokers and Controls.


	33. Allele*	34. Genotype

Frequency	C	G	CC	CG	GG

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

*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.


	35. Allele*	36. Genotype

Frequency	1G	2G	1G1G	1G2G	2G2G

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

*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, ?²(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, ?2 (Yates corrected)=28.8, p<0.0001,
- 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, ?²(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, ?2 (Yates corrected)=4.61, p=0.03,
- 1G=protective
5. Genotype. 2G2G vs 1G1G/1G2G for COPD vs controls, Odds ratio (OR)=3.17, 95% confidence limits 1.9-5.3, ?2 (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, ?2 (Yates corrected)=28.8, p<0.00001,
- 2G=susceptible
7. Genotype. 2G2G vs 1G1G/1G2G for COPD vs resistant, Odds ratio (OR)=1.81, 95% confidence limits 1.2-2.9, ?2 (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, ?2 (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
β2-adrenoreceptor (ADBR)	ADBR Arg16Gly	GG susceptible
Interleukin-18 (IL18)	IL18 −133 C/G	CC susceptible
Interleukin-18 (IL18)	IL18 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 (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 Ile105Val	AA protective
Interferon ? (IFN-?)	IFN-? 874 A/T	AA susceptible
Interleukin-13 (IL13)	IL13 Arg 130 Gln	AA protective
Interleukin-13 (IL13)	Il13 −1055C/T	TT susceptible
a1-antitrypsin (a1-AT)	a1-AT S allele	MS protective
Tissue Necrosis Factor α TNFa	TNFa +489 G/A	AA/AG
		susceptible
		GG protective
Tissue Necrosis Factor α TNFa	TNFa −308 G/A	GG protective
		AA/AG
		susceptible
SMAD3	SMAD3 C89Y AG	AA/AG protective
		GG susceptible
Intracellular adhesion molecule 1	ICAM1 E469K	GG susceptible
(ICAM1)	A/G
Caspase (NOD2)	NOD2 Gly 881Arg	GC/CC susceptible
	G/C
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 Gln	AA protective
	G/A
Interleukin 1B (IL1B)	(IL1B) −511 A/G	GG susceptible
Microsomal epoxide hydrolase (MEH)	MEH Tyr 113 His	TT susceptible
	T/C
Microsomal epoxide hydrolase (MEH)	MEH His 139 Arg	GG protective
	G/A
5 Lipo-oxygenase (ALOX5)	ALOX5 −366 G/A	AA/AG protective
		GG susceptible
Heat Shock Protein 70 (HSP 70)	HSP 70 HOM	CC/CT susceptible
	T2437C	TT protective
Chloride Channel Calcium-activated 1	CLCA1 +13924	AA susceptible
(CLCA1)	T/A
Monocyte differentiation antigen CD-14	CD-14 −159 C/T	CC susceptible
Elafin	Elafin Exon 1 +49	CT/TT protective
	C/T
B2-adrenergic receptor (ADBR)	ADBR Gln 27 Glu	GG protective
	C/G
Matrix metalloproteinase 1 (MMP1)	MMP1 −1607	1G1G/1G2G
	1G/2G	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
% of smokers with COPD	136/215	100/183	16/50
	(63%)	(55%)	(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-? −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	66/135	113/205	73/108
COPD	(49%)	(55%)	(68%)

Comparison	Odd's ratio	95% CI	?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 a1-antitypsin MS/SS, observed in the COPD subjects and in resistant smokers is presented below in Table 5 and in FIG. 1.

TABLE 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	64/120	150/283
	(76%)	(53%)	(53%)

Comparison	Odd's ratio	95% CI	?2	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 FIG. 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 FIG. 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.

I. 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 (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 α1-antitrypsin 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	OCOPD	Exposed resistant
Mean (SD)	(N = 139)	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 1SD

Cyclooxygenase 2 (COX2) −765 G/C Promoter Polymorphism and a1-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 25 ul and contained 20 ng genomic DNA, 500 pmol forward and reverse primers, 0.2 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.0 mM MgCl₂and 1 unit of Taq polymerase (Life Technologies). Cycling times were incubations for 3 min at 95° C. followed by 33 cycles of 50 s at 94° C., 60 s at 66° C. and 60 s at 72° C. A final elongation of 10 min at 72° C. then followed. 4 ul of PCR products were visualised by ultraviolet trans-illumination of a 6% agarose gel stained with ethidium bromide. An aliquot of 3 ul of amplification product was digested for 1 hr with 4 units of AciI (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 123 bp ladder. Using a PCR based method discussed above [3], all smoking subjects were genotyped for the α1-antitrypsin M, S and Z alleles.

Genotyping of the Superoxide Dismutase 3 Arg 312 Gln 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, herein incorporated by reference in its entirety]. 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 25 μl and contained 80 ng genomic DNA, 10 pmol forward and reverse primers, 0.1 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.0 mM MgCl₂and 0.5 unit of Taq polymerase (Qiagen). Aliquots of amplification product were digested for 4 hrs with 5 U 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 1 Kb 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, herein incorporated by reference in its entirety]. 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 25 μl and contained 80 ng genomic DNA, 100 ng forward and reverse primers, 0.2 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.5 mM MgCl₂and 1.0 unit of Taq polymerase (Qiagen). Cycling conditions consisted of 94° C. 60 s, 56° C. 20 s, 72° C. 20 s for 38 cycles with an extended last extension of 3 min. Aliquots of amplification product were digested for 4 hrs with 5 U of the relevant restriction enzymes Eco RV (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 1 Kb 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 a1-Antitrypsin 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 [Sandford A J et al., [6], each of which is herein incorporated by reference in its entirety]. 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 25 μl and contained 80 ng genomic DNA, 100 ng forward and reverse primers, 0.2 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.5 mM MgCl₂and 1.0 unit of Taq polymerase (Qiagen). Forward and reverse prime sequences were 5′-CTACCAGGAATGGCCTTGTCC-3′ [SEQ.ID.NO.136] and 5′-CTCTCAGGTCTGGTGTCATCC-3′ [SEQ.ID.NO.137]. Cycling conditions consisted of 94 C 60 s, 56 C 20 s, 72 C 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 1 Kb 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]. 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 25 μl and contained 80 ng genomic DNA, 100 ng forward and reverse primers, 0.2 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.5 mM MgCl₂and 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. 30 s, 55° C. 30 s, 72° C. 30 s for 30 cycles with an extended last extension of 3 min. Aliquots of amplification product were digested for 4 hrs with 2 U of the restriction enzyme Nco 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 1 Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Genotyping of the −1607 1G2G 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 RFLP 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 25 μl and contained 80 ng genomic DNA, 100 ng forward and reverse primers, 200 mM dNTPs, 20 mM Tris-HCL (pH 8.4), 50 mM KCl, 1.5 mM MgCl₂and 1.0 unit of Taq polymerase (Qiagen). Forward and reverse prime sequences were 3′ TCGTGAGAATGTCTTCCCATT-3′ [SEQ.ID.NO.140] and 5′-TCTTGGATTGATTTGAGATAAGTGAAATC-3′ [SEQ.ID.NO.141]. Cycling conditions consisted of 94 C 60 s, 55 C 30 s, 72 C 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 1 Kb 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™ system (Sequenom™ 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 10× Buffer 15 mM MgCl2 1.25×, 25 mM MgCl2 1.625 mM, dNTP mix 25 mM 500 uM, primers 4 uM 100 nM, Taq polymerase (Quiagen hot start) 0.15 u/reaction, Genomic DNA 10 ng/ul. Cycling times were 95° C. for 15 min, (5° C. for 15 s, 56° C. 30 s, 72° C. 30 s for 45 cycles with a prolonged extension time of 3 min to finish. We used shrimp alkaline phosphotase (SAP) treatment (2 ul to 5 ul PCR reaction) incubated at 35° C. for 30 min and extension reaction (add 2 ul to 7 ul after SAP treatment) with the following volumes per reaction of water 0.76 ul, hME 10× termination buffer 0.2 ul, hME primer (10 uM) 1 ul, MassEXTEND enzyme 0.04 ul.

Sequenom Conditions for the Polymorphisms Genotyping—1


SNP_ID	TERM	WELL	2nd-PCRP	1st-PCRP

VDBP - 420	ACT	W1	ACGTTGGATGGCTTGTTAACCAGCTT	ACGTTGGATGTTTTTCAGACTGGCAG
			TGCC [SEQ. ID. NO. 142]	AGCG [SEQ. ID. NO. 143]

VDBP - 416	ACT	W1	ACGTTGGATGTTTTTCAGACTGGCAG	ACGTTGGATGGCTTGTTAACCAGCTTT
			AGCG [SEQ. ID. NO. 144]	GCC [SEQ. ID. NO. 145]

ADRB2-	ACT	W2	ACGTTGGATGTTGCTGGCACCCAATG	ACGTTGGATGATGAGAGACATGACGA
Gln27Glu			GAAG [SEQ. ID. NO. 146]	TGCC [SEQ. ID. NO. 147]

GSTP1 -105	ACT	W2	ACGTTGGATGTGGTGGACATGGTGAA	ACGTTGGATGTGGTGCAGATGCTCAC
			TGAC [SEQ. ID. NO. 148]	ATAG [SEQ. ID. NO. 149]

PAI1 G-675G	ACT	W2	ACGTTGGATGCACAGAGAGAGTCTGG	ACGTTGGATGCTCTTGGTCTTTCCCTC
			ACAC [SEQ. ID. NO. 150]	ATC
				[SEQ. ID. NO. 151]

IL-11 G518A	ACT	W3	ACGTTGGATGCCTCTGATCCTCTTTGC	ACGTTGGATGAAGAGGGAGTGGAAG
			TTC [SEQ. ID. NO. 152]	GGAAG [SEQ. ID. NO. 153]

NOS3 - 298	ACT	W3	ACGTTGGATGACAGCTCTGCATTCAG	ACGTTGGATGAGTCAATCCCTTTGGT
			CACG [SEQ. ID. NO. 154]	GCTC [SEQ. ID. NO. 155]

IL-8 A-251T	CGT	W5	ACGTTGGATGACTGAAGCTCCACAAT	ACGTTGGATGGCCACTCTAGTACTAT
			TTGG [SEQ. ID. NO. 156]	ATCTG [SEQ. ID. NO. 157]

IL-18 C-133G	ACT	W6	ACGTTGGATGGGGTATTCATAAGCTG	ACGTTGGATGCCTTCAAGTTCAGTGG
			AAAC [SEQ. ID. NO. 158]	TCAG [SEQ. ID. NO. 159]

IL-18 A105C	ACT	W8	ACGTTGGATGGGTCAATGAAGAGAA	ACGTTGGATGAATGTTTATTGTAGAA
			CTTGG [SEQ. ID. NO. 160]	AACC [SEQ. ID. NO. 161]

Sequenom Conditions for the Polymorphisms Genotyping—2


SNP_ID	AMP_LEN	UP_CONF	MP_CONF	Tm(NN)	PcGC	PWARN	UEP_DIR

VDBP - 420	99	99.7	99.7	46.2	53.3	ML	R
VDBP - 416	99	99.7	99.7	45.5	33.3	M	F
ADRB2-Gln27Glu	118	96.6	80	52.2	66.7	L	F
GSTP1 -105	107	99.4	80	49.9	52.9		F
PAI1 G-675G	109	97.9	80	59.3	66.7	g	F
IL-11 G518A	169	97.5	65	52.9	52.6	s	F
NOS3 - 298	186	98.1	65	61.2	63.2		F
IL-8 A-251T	119	92.6	81.2	45.9	28.6		R
IL-18 C-133G	112	93.5	74.3	41.8	46.7	L	F
IL-18 A105C	121	67.2	74.3	48.9	40		R

Sequenom Conditions for the Polymorphisms Genotyping—3


SNP_ID	UEP_MASS	UEP_SEQ	EXT1_CALL	EXT1_MASS

VDBP - 420	4518.9	AGCTTTGCCAGTTCC[SEQ. ID. NO. 162]	A	4807.1

VDBP - 416	5524.6	AAAAGCAAAATTGCCTGA[SEQ. ID. NO.	T	5812.8
		163]

ADRB2-	4547	CACGACGTCACGCAG[SEQ. ID. NO. 164]	C	4820.2
Gln27Glu

GSTP1 -105	5099.3	ACCTCCGCTGCAAATAC[SEQ. ID. NO. 165]	A	5396.5

PAI1 G-675G	5620.6	GAGTCTGGACACGTGGGG[SEQ. ID. NO.	DEL	5917.9
		166]

IL-11 G518A	5705.7	TCCATCTCTGTGGATCTCC[SEQ. ID. NO.	A	6002.9
		167]

NOS3 - 298	5813.8	TGCTGCAGGCCCCAGATGA[SEQ. ID. NO.	T	6102
		168]

IL-8 A-251T	6428.2	CACAATTTGGTGAATTATCAA[SEQ. ID.	A	6716.4
		NO. 169]

IL-18 C-133G	4592	AGCTGAAACTTCTGG[SEQ. ID. NO. 170]	C	4865.2

IL-18 A105C	6085	TCAAGCTTGCCAAAGTAATC[SEQ. ID.	A	6373.2
		NO. 171]

Sequenom Conditions for the Polymorphisms Genotyping—4


SNP_ID	EXT1_SEQ	EXT2_CALL	EXT2_MASS	EXT2_SEQ	1stPAUSE

VDBP - 420	AGCTTTGCCAGTTCCT	C	5136.4	AGCTTTGCCAGTTCCGT	4848.2
	[SEQ. ID. NO. 172]			[SEQ. ID. NO. 173]

VDBP - 416	AAAAGCAAAATTGCCTGA	G	6456.2	AAAAGCAAAATTGCCTGAG	5853.9
	T [SEQ. ID. NO. 174]			GC [SEQ. ID. NO. 175]

ADRB2-	CACGACGTCACGCAGC	G	5173.4	CACGACGTCACGCAGGA	4876.2
Gln27Glu	[SEQ. ID. NO. 176]			[SEQ. ID. NO. 177]

GSTP1 -105	ACCTCCGCTGCAAATACA	G	5716.7	ACCTCCGCTGCAAATACGT	5428.5
	[SEQ. ID. NO. 178]			[SEQ. ID. NO. 179]

PAI1 G-675G	GAGTCTGGACACGTGGGG	G	6247.1	GAGTCTGGACACGTGGGGG	5949.9
	A [SEQ. ID. NO. 180]			A [SEQ. ID. NO. 181]

IL-11 G518A	TCCATCTCTGTGGATCTCC	G	6323.1	TCCATCTCTGTGGATCTCC	6034.9
	A [SEQ. ID. NO. 182]			GT [SEQ. ID. NO. 183]

NOS3 - 298	TGCTGCAGGCCCCAGATG	G	6416.2	TGCTGCAGGCCCCAGATGA	6143
	AT [SEQ. ID. NO. 184]			GC [SEQ. ID. NO. 185]

IL-8 A-251T	CACAATTTGGTGAATTAT	T	7029.6	CACAATTTGGTGAATTATC	6741.4
	CAAT [SEQ. ID. NO. 186]			AAAT [SEQ. ID. NO. 187]

IL-18 C-133G	AGCTGAAACTTCTGGC	G	5218.4	AGCTGAAACTTCTGGGA	4921.2
	[SEQ. ID. NO. 188]			[SEQ. ID. NO. 189]

IL-18 A105C	TCAAGCTTGCCAAAGTAA	C	7040.6	TCAAGCTTGCCAAAGTAAT	6414.2
	TCT [SEQ. ID. NO. 190]			CGGA[SEQ. ID. NO. 191]

Results
Frequencies of individual polymorphisms are as follows:

TABLE 6

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

Cyclo-oxygenase 2 −765 G/C

Allele*

Genotype

Frequency	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%)	6¹(7%)	30¹(34%)	51 (59%)

Glutathione S Transferase P1 Ile 105 Val (A/G)

Allele*

Genotype

Frequency	A	G	AA	AG	GG

Controls n = 186 (%)	234 (63%)	138 (37%)	71 (38%)	92 (50%)	23 (12%)
OCOPD n = 123 (%)	159 (65%)	87 (36%)	52 (42%)	55 (45%)	16⁵(13%)
Resistant n = 98 (%)	136 (69%)	60 (31%)	44 (45%)	48 (49%)	6 (6%)

Interleukin 18 105 C/A

Allele*

Genotype

Frequency	C	A	CC	AC	AA

Controls n = 185 (%)	119 (32%)	251 (68%)	22 (12%)	75 (40%)	88 (48%)
OCOPD n = 122 (%)	62 (25%)	182 (75%)	12 (10%)	38 (31%)	72^6,7(59%)
Resistant n = 98 (%)	60 (31%)	136 (69%)	6 (6%)	48 (49%)	44 (45%)

Interleukin 18 −133 G/C

Allele*

Genotype

Frequency	G	C	GG	GC	CC

Controls n = 188 (%)	121 (32%)	255 (68%)	23 (12%)	75 (40%)	90 (48%)
OCOPD n = 122	62 (25%)	182 (75%)	12 (10%)	38 (31%)	72^8,9(59%)
Resistant n = 97 (%)	60 (31%)	134 (69%)	6 (6%)	48 (50%)	43 (44%)

Interleukin 8 −251 A/T

Allele*

Genotype

Frequency	A	T	AA	AT	TT

Controls n = 188 (%)	175 (47%)	201 (53%)	39 (21%)	97 (52%)	52 (28%)
OCOPD n = 116	101 (44%)	131 (56%)	21 (18%)	59 (51%)	36 (31%)
Resistant n = 93 (%)	94¹¹(50%)	92 (49%)	26¹⁰(28%)	42 (45%)	25 (27%)

Vitamin D Binding Protein Lys 420 Thr (A/C)

Allele*

Genotype

Frequency	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 Protein Glu 416 Asp (T/G)

Allele*

Genotype

Frequency	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 hydrolase R/r Exon 3 T/C

Allele*

Genotype

Frequency	r	R	rr	Rr	RR

Controls n = 184 (%)	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 3 Arg 312 Gln

Allele*

Genotype

Frequency	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%)

a1-antitrypsin S

Allele*

Genotype

Frequency	M	S	MM	MS	SS

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 Asp 299 Gly A/G

Allele*

Genotype

Frequency	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 Gln 27 Glu

Allele*

Genotype

Frequency	C	G	CC	CG	GG

Controls n = 186 (%)	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) −518 G/A

Allele*

Genotype

Frequency	A	G	AA	AG	GG

OCOPD n = 119 (%)	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/T

Allele*

Genotype

Frequency	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 inhibitor 1 −675 4G/5G

Allele*

Genotype

Frequency	5G	4G	5G5G	5G4G	4G4G

Controls n = 186 (%)	158 (42%)	214 (58%)	31 (17%)	96 (52%)	59 (32%)
OCOPD n = 122 (%)	115²⁸(47%)	129 (53%)	29²⁷(24%)	57 (47%)	36 (30%)
Resistant n = 98 (%)	76 (39%)	120 (61%)	14 (14%)	48 (49%)	36 (37%)

Nitric oxide synthase 3 Asp 298 Glu (T/G)

Allele*

Genotype

Frequency	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%)	15^29,30(15%)	41 (41%)	43 (43%)

a1-antitrypsin 3′ 1237 G/A (T/t)

Allele*

Genotype

Frequency	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 metalloproteinase 1 −1607 1G/2G

Allele*

Genotype

Frequency	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=1.1-4.8, χ²(Yates corrected)=4.76, P=1.03, 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=1.0-3.1, 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
- 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 AC/AA 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, χ²(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 0.8-8.4, 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 corrected)=4.9, p=0.03. TT=susceptible
- 27. 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. 50 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 corrected)=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
β2-adrenoreceptor (ADRB2)	ADRB2 Gln 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	PAI-1 −675 4G/5G	5G5G
inhibitor 1 (PAI-1)		susceptible
Nitric Oxide synthase 3 (NOS3)	NOS3 298 Asp/Glu	TT protective
Vitamin D Binding Protein	VDBR Lys 420 Thr	AA protective
(VDBR)		CC susceptible
Vitamin D Binding Protein	VDBP Glu 416 Asp	TT/TG protective
(VDBR)		GG susceptible
Glutathione S Transferase	GSTP1 Ile105Val	GG susceptible
(GSTP1)
Superoxide dismutase 3 (SOD3)	SOD3 Arg 312 Gln	AG/GG
		protective
		AA susceptible
a1-antitrypsin (a1AT)	a1AT 3′ 1237 G/A	Tt/tt susceptible
	(T/t)
a1-antitrypsin (a1AT)	a1AT S allele	MS protective
Toll-like receptor 4 (TLR4)	TLR4 Asp 299 Gly	AG/GG
	A/G	protective
Interleukin-8 (IL-8)	IL-8 −251 A/T	AA protective
Interleukin 11 (IL-11)	IL-11 −518 G/A	AA protective
Microsomal epoxide	MEH Exon 3 T/C	RR protective
hydrolase (MEH)	(r/R)
Interleukin 13 (IL-13)	IL-13 −1055 C/T	TT susceptible
Matrix Metalloproteinase 1	MMP1 −1607	2G2G susceptible
(MMP1)	1G/2G

The combined frequencies of the presence or absence of the selected protective genotypes COX2 −765 CC/CG, NOS3 298 TT, a 1AT 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	20 (19%)	31 (30%)	53 (51%)	104
smokers
% of	34/54 (63%)	51/82 (62%)	39/92 (42%)
smokers with
OCOPD

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.

TABLE 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	55 (54%)	37 (37%)	9 (9%)	101
smokers
% of	45/100 (45%)	55/92 (60%)	24/33 (73%)
smokers with
OCOPD

Comparison	Odd's ratio	95% CI	?2	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 −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 10. When assessed as a range between −2 to +3, a linear relationship as depicted in FIG. 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 FIG. 3). As a point of clarification, it is noted that FIG. 3 depicts the sum of the protective and susceptibility polymorphisms combined, rather than simply the sum of the protective polymorphisms in one graph and the sum of the susceptibility polymorphisms in another graph. Thus, the SNP score can be negative if there are only susceptibility polymorphisms, positive, if there are only protective polymorphisms, or either positive or negative, depending upon the relative numbers of protective to susceptibility polymorphisms.

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 = 124	8	28	33	39	11	5
Resistant n = 101	2	11	23	27	23	15
% OCOPD	80%	72%	59%	59%	32%	25%

II. 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 can 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 were genotyped for the α1-antitrypsin 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 can reflect an increased susceptibility to the development of lung cancer. Similarly, polymorphisms found in greater frequency in resistant smokers compared to lung cancer can reflect a protective role.
Summary of Characteristics.


Parameter	Lung Cancer	Resistant smokers
Median (IQR)	N = 109	N = 200	Differences

% 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, herein incorporated by reference in its entirety]. 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 μl and contained 80 ng genomic DNA, 100 ng forward and reverse primers, 200 mM dNTPs, 20 mM Tris-HCL (pH 8.4), 50 mM KCl, 2.5 mM MgCl2 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 94 C 60 s, 59 C 30 s, 72 C 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 transillumination following ethidium bromide staining and migration compared against a 1 Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Cyclooxygenase 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 (Papafili A, et al., 2002, incorporated in its entirety herein by reference)). The PCR reaction was carried out in a total volume of 25 ul and contained 20 ng genomic DNA, 500 pmol forward and reverse primers, 0.2 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.0 mM MgCl₂and 1 unit of polymerase (Life Technologies). Cycling times were incubations for 3 min at 95° C. followed by 33 cycles of 50 s at 94° C., 60 s at 66° C. and 60 s at 72° C. A final elongation of 10 min at 72° C. then followed. 4 ul of PCR products were visualised by ultraviolet trans-illumination of a 3% agarose gel stained with ethidium bromide. An aliquot of 3 ul of amplification product was digested for 1 hr with 4 units of AciI (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 123 bp ladder using ultraviolet transillumination after ethidium bromide staining.

Matrix Metalloproteinase 1 −1607 1G/2G 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 (Dunleavey, L. et al. Rapid genotype analysis of the matrix metalloproteinase-1 gene 1G/2G polymorphism that is associated with risk of cancer. Matrix Biol. 19(2):175-7 (2000), herein incorporated by reference in its entirety). 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 μl and contained 80 ng genomic DNA, 100 ng forward and reverse primers, 200 mM dNTPs, 20 mM Tris-HCL (pH 8.4), 50 mM KCl, 1.5 mM MgCl₂and 1.0 unit of Taq polymerase (Qiagen). Forward and reverse prime sequences were 3′ TCGTGAGAATGTCTTCCCATT-3′ [SEQ.ID.NO.195] and 5′-TCTTGGATTGATTTGAGATAAGTGAAATC-3′[SEQ.ID.NO.196]. Cycling conditions consisted of 94 C 60 s, 55 C 30 s, 72 C 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 1 Kb 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 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 10× Buffer 15 mM MgCl2 1.25×, 25 mM MgCl2 1.625 mM, dNTP mix 25 mM 500 uM, primers 4 uM 100 nM, Taq polymerase (Quiagen hot start) 0.15 U/reaction, Genomic DNA 10 ng/ul. Cycling times were 95° C. for 15 min, (5° C. for 15 s, 56° C. 30 s, 72° C. 30 s for 45 cycles with a prolonged extension time of 3 min to finish. We used shrimp alkaline phosphotase (SAP) treatment (2 ul to 5 ul per PCR reaction) incubated at 35° C. for 30 min and extension reaction (add 2 ul to 7 ul after SAP treatment) with the following volumes per reaction of: water, 0.76 ul; hME 10× termination buffer, 0.2 ul; hME primer (10 uM), 1 ul; MassEXTEND enzyme, 0.04 ul.

Sequenom Conditions for the Polymorphisms Genotyping—1


TERM	SNP_ID	2nd-PCRP	1st-PCRP

ACT	CYP2E1_1019G/CPst1	ACGTTGGATGAAACCAGAGGGAAGCAAAGG	ACGTTGGATGTCATTGGTTGTGCTGCACCT
		[SEQ. ID. NO. 197]	[SEQ. ID. NO. 198]

ACT	XPD-751 G/T	ACGTTGGATGCACCAGGAACCGTTTATGGC	ACGTTGGATGAGCAGCTAGAATCAGAGGAG
		[SEQ. ID. NO. 199]	[SEQ. ID. NO. 200]

ACT	IL-18 105 A/C	ACGTTGGATGGTCAATGAAGAGAACTTGGTC	ACGTTGGATGAATGTTTATTGTAGAAAACC
		[SEQ. ID. NO. 201]	[SEQ. ID. NO. 202]

ACT	IL-18-133 G/C	ACGTTGGATGGGGTATTCATAAGCTGAAAC	ACGTTGGATGCCTTCAAGTTCAGTGGTCAG
		[SEQ. ID. NO. 203]	[SEQ. ID. NO. 204]

ACT	CYP 1A1 Ile462Val	ACGTTGGATGGTGATTATCTTTGGCATGGG	ACGTTGGATGGGATAGCCAGGAAGAGAAAG
		[SEQ. ID. NO. 205]	[SEQ. ID. NO. 206]

ACT	MMP12 Asn 357 Ser A/G	ACGTTGGATGCCCTATTTCTTTGTCTTCAC	ACGTTGGATGCTTGGGATAATTTGGCTCTG
		[SEQ. ID. NO. 207]	[SEQ. ID. NO. 208]

ACT	OGG1 Ser 326 Cys G/C	ACGTTGGATGGGAACCCTTTCTGCGCTTTG	ACGTTGGATGCCTACAGGTGCTGTTCAGTG
		[SEQ. ID. NO. 209]	[SEQ. ID. NO. 210]

ACT	NAT2 Arg	197 Gln A/G	ACGTTGGATGCCTGCCAAAGAAGAAACACC	ACGTTGGATGACGTCTGCAGGTATGTATTC
		[SEQ. ID. NO. 211]	[SEQ. ID. NO. 212]

ACT	CYP2E1_C/T Rsa1	ACGTTGGATGGTTCTTAATTCATAGGTTGC	ACGTTGGATGCTTCATTTCTCATCATATTTTC
		[SEQ. ID. NO. 213]	[SEQ. ID. NO. 214]

ACG	CCND1 A870G	ACGTTGGATGTAGGTGTCTCCCCCTGTAAG	ACGTTGGATGTCCTCTCCAGAGTGATCAAG
		[SEQ. ID. NO. 215]	[SEQ. ID. NO. 216]

ACG	ILB1-511 A/G	ACGTTGGATGATTTTCTCCTCAGAGGCTCC	ACGTTGGATGTGTCTGTATTGAGGGTGTGG
		[SEQ. ID. NO. 217]	[SEQ. ID. NO. 218]

ACG	FAS_A-670G	ACGTTGGATGTTGTGGCTGCAACATGAGAG	ACGTTGGATGCTATGGCGCAACATCTGTAC
		[SEQ. ID. NO. 219]	[SEQ. ID. NO. 220]

ACG	NOS3-786 T/C	ACGTTGGATGACTGTAGTTTCCCTAGTCCC	ACGTTGGATGAGTCAGCAGAGAGACTAGGG
		[SEQ. ID. NO. 221]	[SEQ. ID. NO. 222]

ACT	ACT_Ala15Thr	ACGTTGGATGGAGTTGAGAATGGAGAGAATG	ACGTTGGATGTCAAGTGGGCTGTTAGGGTG
		[SEQ. ID. NO. 223]	[SEQ. ID. NO. 224]

ACT	SOD3 Arg 312 Gln	ACGTTGGATGTGCTGCGTGGTGGGCGTGTG	ACGTTGGATGGGCCTTGCACTCGCTCTCG
		[SEQ. ID. NO. 225]	[SEQ. ID. NO. 226]

ACT	NOS3 Asp 298 Glu	ACGTTGGATGAAACGGTCGCTTCGACGTGC	ACGTTGGATGACCTCAAGGACCAGCTCGG
		[SEQ. ID. NO. 227]	[SEQ. ID. NO. 228]

CGT	IL-8-251 A/T	ACGTTGGATGACTGAAGCTCCACAATTTGG	ACGTTGGATGGCCACTCTAGTACTATATCTG
		[SEQ. ID. NO. 229]	[SEQ. ID. NO. 230]

CGT	IFN gamma 874 A/T	ACGTTGGATGCAGACATTCACAATTGATTT	ACGTTGGATGGATAGTTCCAAACATGTGCG
		[SEQ. ID. NO. 231]	[SEQ. ID. NO. 232]

ACT	XRCC1 Arg 399 Gln G/A	ACGTTGGATGTAAGGAGTGGGTGCTGGACT	ACGTTGGATGAGGATAAGGAGCAGGGTTGG
		[SEQ. ID. NO. 233]	[SEQ. ID. NO. 234]

Sequenom Conditions for the Polymorphisms Genotyping—2


SNP_ID	AMP_LEN	UP_CONF	MP_CONF	Tm(NN)	PcGC	PWARN	UEP_DIR	UEP_MASS

CYP2E1_1019G/CPst 1	119	95.2	71.3	46.7	47.1	F	5256.4
XPD -751 G/T	113	97.6	71.3	49.8	47.4	F	5689.7
IL-18 105 A/C	120	65.6	71.3	49.8	36.4	R	6702.4
IL-18 -133 G/C	112	93.5	81.3	47.1	42.1	F	5811.8
CYP 1A1 Ile462Val	102	98.2	81.3	55.6	55	F	6222.1
MMP12 Asn 357 Ser A/G	95	92.6	81.3	48	30.4	F	7070.6
OGG1 Ser 326 Cys G/C	99	96.5	82.2	58.9	70.6	R	5227.4
NAT2 Arg 197 Gln A/G	115	97.4	70	48.5	36.4	F	6635.3
CYP2E1_C/T Rsa1	105	62.8	77.8	46.4	26.1	R	7018.6
CCND1 A870G	106	98.1	83	45.8	47.1	R	5034.3
ILB1 -511 A/G	111	99.2	83	46	47.1	R	5203.4
FAS_A-670G	103	99.2	83	54.4	50	R	6166
NOS3 -786 T/C	114	97.5	83	61.8	61.9	F	6358.1
ACT_Ala15Thr	118	93.4	68.2	45.2	47.1	F	5136.4
SOD3 Arg 312 Gln	119	63.2	68.2	55.5	57.9	F	5855.8
NOS3 Asp 298 Glu	113	82.2	68.2	65.4	66.7	F	6432.2
IL-8 -251 A/T	119	92.6	75.8	45.9	28.6	R	6428.2
IFN gamma 874 A/T	112	75.3	75.8	46.4	26.1	F	6943.6
XRCC1 Arg 399 Gln G/A	109	93.6	93.6	66.8	82.4	F	5099.3

Sequenom Conditions for the Polymorphisms Genotyping—3


		EXT1	EXT1		EXT2
SNP_ID	UEP_SEQ	CALL	MASS	EXT1_SEQ	CALL

CYP2E1_1019G/CPst1	TTCTTGGTTCAGGAGAG	C	5529.6	TTCTTGGTTCAGGAGAGC	G
	[SEQ. ID. NO. 235]			[SEQ. ID. NO. 236]

XPD-751 G/T	GCAATCTGCTCTATCCTCT	T	5977.9	GCAATCTGCTCTATCCTCTT	G
	[SEQ. ID. NO. 237]			[SEQ. ID. NO. 238]

IL-18 105 A/C	ATTCAAGCTTGCCAAAGTAATC	A	6990.6	ATTCAAGCTTGCCAAAGTAAT	C
	[SEQ. ID. NO. 239]			CT [SEQ. ID. NO. 240]

IL-18 -133 G/C	CATAAGCTGAAACTTCTGG	C	6085	CATAAGCTGAAACTTCTGGC	G
	[SEQ. ID. NO. 241]			[SEQ. ID. NO. 242]

CYP 1A1 Ile462Val	GGAAGTGTATCGGTGAGACC	A	6519.3	GGAAGTGTATCGGTGAGACC	G
	[SEQ. ID. NO. 243]			A [SEQ. ID. NO. 244]

MMP12 Asn 357 Ser	TGACAAATACTGGTTAATTAGCA	A	7367.8	TGACAAATACTGGTTAATTAG	G
A/G	[SEQ. ID. NO. 245]			CAA [SEQ. ID. NO. 246]

OGG1 Ser 326 Cys	GCTCCTGAGCATGGCGG	G	5500.6	GCTCCTGAGCATGGCGGC	C
G/C	[SEQ. ID. NO. 247]			[SEQ. ID. NO. 248]

NAT2 Arg 197 Gln	TACTTATTTACGCTTGAACCTC	A	6932.5	TACTTATTTACGCTTGAACCT	G
A/G	[SEQ. ID. NO. 249]			CA [SEQ. ID. NO. 250]

CYP2E1_C/T Rsa1	CTTAATTCATAGGTTGCAATTTT	T	7315.8	CTTAATTCATAGGTTGCAATT	C
	[SEQ. ID. NO. 251]			TTA [SEQ. ID. NO. 252]

CCND1 A870G	ACATCACCCTCACTTAC[SEQ. ID.	G	5307.5	ACATCACCCTCACTTACC	A
	NO. 253]			[SEQ. ID. NO. 254]

ILB1 -511 A/G	AATTGACAGAGAGCTCC	G	5476.6	AATTGACAGAGAGCTCCC	A
	[SEQ. ID. NO. 255]			[SEQ. ID. NO. 256]

FAS_A-670G	ATGAGAGGCTCACAGACGTT	G	6439.2	ATGAGAGGCTCACAGACGTT	A
	[SEQ. ID. NO. 257]			C [SEQ. ID. NO. 258]

NOS3-786 T/C	GGCATCAAGCTCTTCCCTGGC	C	6631.3	GGCATCAAGCTCTTCCCTGG	T
	[SEQ. ID. NO. 259]			CC [SEQ. ID. NO. 260]

ACT_Ala15Thr	GAATGTTACCTCTCCTG[SEQ. ID.	A	5433.6	GAATGTTACCTCTCCTGA	G
	NO. 261]			[SEQ. ID. NO. 262]

SOD3 Arg 312 Gln	GCACTCAGAGCGCAAGAAG	C	6129	GCACTCAGAGCGCAAGAAGC	G
	[SEQ. ID. NO. 263]			[SEQ. ID. NO. 264]

NOS3 Asp 298 Glu	GCTGCTGCAGGCCCCAGATGA	T	6720.4	GCTGCTGCAGGCCCCAGATG	G
	[SEQ. ID. NO. 265]			AT [SEQ. ID. NO. 266]

IL-8 -251 A/T	CACAATTTGGTGAATTATCAA	A	6716.4	CACAATTTGGTGAATTATCAA	T
	[SEQ. ID. NO. 267]			T [SEQ. ID. NO. 268]

IFN gamma 874 A/T	TTCTTACAACACAAAATCAAATC	T	7231.8	TTCTTACAACACAAAATCAAA	A
	[SEQ. ID. NO. 269]			TCT [SEQ. ID. NO. 270]

XRCC1 Arg 399 Gln	TCGGCGGCTGCCCTCCC	A	5396.5	TCGGCGGCTGCCCTCCCA	G
G/A	[SEQ. ID. NO. 271]			[SEQ. ID. NO. 272]

Sequenom Conditions for the Polymorphisms Genotyping—4


SNP_ID	EXT2_MASS	EXT2_SEQ	1stPAUSE

CYP2E1_1019G/CPst1	5873.8	TTCTTGGTTCAGGAGAGGT[SEQ. ID. NO. 273]	5585.6

XPD -751 G/T	6292.1	GCAATCTGCTCTATCCTCTGC[SEQ. ID. NO. 274]	6018.9

IL-18 105 A/C	7658	ATTCAAGCTTGCCAAAGTAATCGGA[SEQ. ID.	7031.6
		NO. 275]

IL-18 -133 G/C	6438.2	CATAAGCTGAAACTTCTGGGA[SEQ. ID. NO.	6141
		276]

CYP 1A1 Ile462Val	6839.5	GGAAGTGTATCGGTGAGACCGT[SEQ. ID. NO.	6551.3
		277]

MMP12 Asn 357 Ser A/G	7688	TGACAAATACTGGTTAATTAGCAGT[SEQ. ID.	7399.8
		NO. 278]

OGG1 Ser 326 Cys G/C	5853.8	GCTCCTGAGCATGGCGGGA[SEQ. ID. NO. 279]	5556.6

NAT2 Arg 197 Gln A/G	7261.8	TACTTATTTACGCTTGAACCTCGA[SEQ. ID.	6964.5
		NO. 280]

CYP2E1_C/T Rsa1	7636	CTTAATTCATAGGTTGCAATTTTGT[SEQ. ID.	7347.8
		NO. 281]

CCND1 A870G	5651.7	ACATCACCCTCACTTACTG[SEQ. ID. NO. 282]	5338.5

ILB1 -511 A/G	5820.8	AATTGACAGAGAGCTCCTG[SEQ. ID. NO. 283]	5507.6

FAS_A-670G	6743.4	ATGAGAGGCTCACAGACGTTTC[SEQ. ID. NO.	6470.2
		284]

NOS3-786 T/C	6975.5	GGCATCAAGCTCTTCCCTGGCTG[SEQ. ID.	6662.3
		NO. 285]

ACT_Ala15Thr	5738.7	GAATGTTACCTCTCCTGGC[SEQ. ID. NO. 286]	5465.6

SOD3 Arg 312 Gln	7116.6	GCACTCAGAGCGCAAGAAGGGGC[SEQ. ID.	6185
		NO. 287]

NOS3 Asp 298 Glu	7034.6	GCTGCTGCAGGCCCCAGATGAGC[SEQ. ID.	6761.4
		NO. 288]

IL-8 -251 A/T	7029.6	CACAATTTGGTGAATTATCAAAT[SEQ. ID. NO.	6741.4
		289]

IFN gamma 874 A/T	7530	TTCTTACAACACAAAATCAAATCAC[SEQ. ID.	7256.8
		NO. 290]

XRCC1 Arg 399 Gln G/A	6054.9	TCGGCGGCTGCCCTCCCGGA[SEQ. ID. NO.	5428.5
		291]

Sequenom Conditions for the Polymorphisms Genotyping—5


TERM	SNP_ID	2nd-PCRP	1st-PCRP

ACT	CTGF-447G/C	ACGTTGGATGAGGTAGCTGAAGAG	ACGTTGGATGGCCTATAGCCTCTAA
		GCAAAC [SEQ. ID. NO. 292]	AACGC [SEQ. ID. NO. 293]

ACT	NBS1 Gln185Glu	ACGTTGGATGCTTTCAATTTGTGGA	ACGTTGGATGTGTGCACTCATTTGT
	G/C	GGCTG [SEQ. ID. NO. 294]	GGACG [SEQ. ID. NO. 295]

ACT	MBL2 161 G/A	ACGTTGGATGGTAGCTCTCCAGGCA	ACGTTGGATGGTACCTGGTTCCCCC
		TCAAC [SEQ. ID. NO. 296]	TTTTC [SEQ. ID. NO. 297]

ACT	IGF2R Leu252Val	ACGTTGGATGACACCAGGCGTTTGA	ACGTTGGATGAAAAACGCCAACAGC
	C/G	TGTTG [SEQ. ID. NO. 298]	ATCGG [SEQ. ID. NO. 299]

ACT	MUC5AC -221 C/T	ACGTTGGATGAGGCGGAGATGGGT	ACGTTGGATGAGTCTAGGGTGGGG
		GTGTC [SEQ. ID. NO. 300]	TATGTG [SEQ. ID. NO. 301]

ACT	Arg1 intron1 C/T	ACGTTGGATGATGTGTGGATTCACA	ACGTTGGATGGGGTTGGCAACTCTA
		GCTCG [SEQ. ID. NO. 302]	AAAGG [SEQ. ID. NO. 303]

ACT	REV1 Phe257Ser	ACGTTGGATGCTCTGAAATCAGTGC	ACGTTGGATGATGGTCAACAGTGTT
	C/T	TGCTC [SEQ. ID. NO. 304]	GCCAG [SEQ. ID. NO. 305]

ACT	Apex1 Asp148Glu	ACGTTGGATGCACCTCTTGATTGCT	ACGTTGGATGACCCGGCCTTCCTGA
	G/T	TTCCC [SEQ. ID. NO. 306]	TCATG [SEQ. ID. NO. 307]

ACG	IL-10 -1082 A/G	ACGTTGGATGATTCCATGGAGGCTG	ACGTTGGATGGACAACACTACTAAG
		GATAG [SEQ. ID. NO. 308]	GCTTC [SEQ. ID. NO. 309]

Sequenom Conditions for the Polymorphisms Genotyping—6


SNP_ID	AMP_LEN	UP_CONF	MP_CONF	Tm(NN)	PcGC	PWARN	UEP_DIR	UEP_MASS

CTGF-447G/C	119	98.2	65	52	52.9		R	5090.3
NBS1 Gln185Glu G/C	118	97	65	51	52.9		R	5192.4
MBL2 161 G/A	99	96.8	65	50.3	52.9		F	5299.5
IGF2R Leu252Val C/G	114	98.5	67.8	68.6	82.4		F	5206.4
MUC5AC -221 C/T	119	81.8	67.8	56.9	64.7	g	R	5273.4
Arg1 intron1 C/T	102	99.6	67.8	53.3	52.6		R	5932.9
REV1 Phe257Ser C/T	105	99.6	67.8	57.5	55		R	6003.9
Apex1 Asp148Glu G/T	114	92.9	67.8	46.8	35		F	6113
IL-10 -1082 A/G	107	98	68.8	51.2	58.8		R	4977.2

Sequenom Conditions for the Polymorphisms Genotyping—7


SNP_ID	UEP_SEQ	EXT1_CALL	EXT1_MASS	EXT1_SEQ

CTGF-447G/C	AAAAGGTTTCTCCCCCC	G	5363.5	AAAAGGTTTCTCCCCCCC
	[SEQ. ID. NO. 310]			[SEQ. ID. NO. 311]

NBS1 Gln185Glu	AGGCTGCTTCTTGGACT	G	5465.6	AGGCTGCTTCTTGGACTC
G/C	[SEQ. ID. NO. 312]			[SEQ. ID. NO. 313]

MBL2 161 G/A	CAAAGATGGGCGTGATG	A	5596.7	CAAAGATGGGCGTGATGA
	[SEQ. ID. NO. 314]			[SEQ. ID. NO. 315]

IGF2R Leu252Val	GCCAGCCCCGGGACGGA	C	5479.6	GCCAGCCCCGGGACGGA
C/G	[SEQ. ID. NO. 316]			C [SEQ. ID. NO. 317]

MUC5AC -221	ATGGGTGTGTCTGCCGG	T	5570.6	ATGGGTGTGTCTGCCGGA
C/T	[SEQ. ID. NO. 318]			[SEQ. ID. NO. 319]

Arg1 intron1 C/T	GGCTGTAAGGAAATCTGGG	T	6230.1	GGCTGTAAGGAAATCTGG
	[SEQ. ID. NO. 320]			GA [SEQ. ID. NO. 321]

REV1 Phe257Ser	CCTTATCCTCCTCCTGGGAA	T	6301.1	CCTTATCCTCCTCCTGGG
C/T	[SEQ. ID. NO. 322]			AAA [SEQ. ID. NO. 323]

Apex1 Asp148Glu	TGTTTCATTTCTATAGGCGA	T	6401.2	TGTTTCATTTCTATAGGCG
G/T	[SEQ. ID. NO. 324]			AT [SEQ. ID. NO. 325]

IL-10 -1082 A/G	CCTATCCCTACTTCCCC	G	5250.4	CCTATCCCTACTTCCCCC
	[SEQ. ID. NO. 326]			[SEQ. ID. NO. 327]

Sequenom conditions for the polymorphisms Genotyping—8


SNP_ID	EXT2_CALL	EXT2_MASS	EXT2_SEQ	1stPAUSE

CTGF-447G/C	C	5716.7	AAAAGGTTTCTCCCCCCGA	5419.5
			[SEQ. ID. NO. 328]

NBS1 Gln185Glu	C	5818.8	AGGCTGCTTCTTGGACTGA	5521.6
G/C			[SEQ. ID. NO. 329]

MBL2 161 G/A	G	5901.9	CAAAGATGGGCGTGATGGC	5628.7
			[SEQ. ID. NO. 330]

IGF2R Leu252Val	G	5823.8	GCCAGCCCCGGGACGGAGT	5535.6
C/G			[SEQ. ID. NO. 331]

MUC5AC -221 C/T	C	5890.8	ATGGGTGTGTCTGCCGGGT	5602.6
			[SEQ. ID. NO. 332]

Arg1 intron1 C/T	C	6879.5	GGCTGTAAGGAAATCTGGGGGT	6262.1
			[SEQ. ID. NO. 333]

REV1 Phe257Ser	C	6630.3	CCTTATCCTCCTCCTGGGAAGA	6333.1
C/T			[SEQ. ID. NO. 334]

Apex1 Asp148Glu	G	7068.6	TGTTTCATTTCTATAGGCGAGGA	6442.2
G/T			[SEQ. ID. NO. 335]

IL-10 -1082 A/G	A	5858.8	CCTATCCCTACTTCCCCTTC	5281.4
			[SEQ. ID. NO. 336]

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)

Allele*

Genotype

Frequency	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%)	28^1.2	(14%)	79	(40%)	91	(46%)

Nitric oxide synthase 3 −786 T/C

Allele*

Genotype

Frequency	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 3 Arg 312 Gln C/G

Allele*

Genotype

Frequency	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 = 182 (%)	390	(98%)	10	(3%)	191	(95%)	8⁴	(4%)	1⁴	(1%)

XRCC1 Arg 399 Gln A/G

Allele*

Genotype

Frequency	A	G	AA	AG	GG

Controls n = 190 (%)
Lung Cancer n = 103 (%)	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

Allele*

Genotype

Frequency	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 −15 Thr

Allele*

Genotype

Frequency	A	G	AA	AG	GG

Lung Cancer n = 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 D1 A 870 G

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 1B −511 A/G

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-1/CD 95) A −670 G

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

Allele*

Genotype

Frequency	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%)

Cytochrome P450 1A1 Ile 462 Val G/A

Allele*

Genotype

Frequency	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

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 glycosylase Ser 326 Cys C/G

Allele*

Genotype

Frequency	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 Arg 197 Gln G/A

Allele*

Genotype

Frequency	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 1019 G/C Pst1

Allele*

Genotype

Frequency	C	G	CC	CG	GG

Lung Cancer n = 109	10	(5%)	208	(95%)	0	(0%)	10²⁰	(9%)	99	(91%)
Resistant n = 197 (%)	11	(3%)	383	(97%)	0	(0%)	11	(6%)	186	(94%)

Cytochrome P450 2E1 C/T Rsa I

Allele*

Genotype

Frequency	T	C	TT	TC	CC

Lung Cancer n = 108	11	(5%)	205	(95%)	0	(0%)	11²¹	(10%)	97	(90%)
Resistant n = 198 (%)	11	(3%)	385	(97%)	0	(0%)	11	(6%)	187	(94%)

Interleukin 18 105 A/C

Allele*

Genotype

Frequency	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/G

Allele*

Genotype

Frequency	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%)	83²³	(42%)	98	(49%)

Glutathione S-Transferase M null

Allele*

	Frequency	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 A/T

Allele*

Genotype

Frequency	A	T	AA	AT	TT

Controls n = 186 (%)	183	(49%)	189	(51%)	37	(20%)	109	(58%)	40	(22%)
Lung cancer n = 106 (%)	116	(55%)	96	(45%)	34^25,26	(32%)	48	(45%)	24	(23%)
Resistant n = 196 (%)	209	(53%)	183	(47%)	50	(26%)	109	(56%)	37	(19%)

Cyclooxygenase −765 C/G

Allele*

Genotype

Frequency	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 = 158 (%)	75	(24%)²⁸	241	(76%)	11	(7%)	53	(34%)	94	(59%)

Matrix metalloproteinase 1 −1607 1G/2G

Allele*

Genotype

Frequency	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 1.0-4.6, 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 uncorrected)=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=1.6=11.2, χ²(Yates corrected)=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 1.0-2.2, χ²(Yates corrected)=5.07, p=0.02, A=protective
- 8. Genotype. GG vs AA/AG for Lung cancer vs resistant, Odds ratio (OR)=1.7, 95% confidence limits=0.9-2.9, χ²(Yates uncorrected)=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 0.9-1.9, 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
- 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 uncorrected)=1.6, p=0.20, AA=susceptible
- 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, A=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 uncorrected)=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=susceptible
- 17. Genotype. GG/AG vs AA for Resistant vs COPD, Odds ratio (OR)=1.7, 95% confidence limits=0.7-4.6, χ²(Yates uncorrected)=1.45, 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 limits=0.9-2.5, χ²(Yates uncorrected)=3.0, p=0.08, GG=susceptible
- 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=0.8-5.0, 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
- 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 AT/TT 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 AT/TT 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 limits=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=1.1-3.3, χ²(Yates corrected)=4.9, P=0.03 GG=susceptible (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.


	37. Allele*	38. Genotype

Frequency	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%)

*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, χ²(Yates uncorrected)=1.70, p=0.19, GC/CC genotype=susceptibility (trend)

Mucin 5AC (Muc5AC)-221 C/T Polymorphism Allele and Genotype Frequencies in the Lung Cancer and Resistant Smokers.


	39. Allele*	40. Genotype

Frequency	C	T	CC	CT	TT

Lung cancer n = 109	177	41	73	31	5
(%)	(81%)	(19%)	(67%)	(28%)	(5%)
Resistant n = 195	296	94	119	58	18
(%)	(76%)	(24%)	(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.


	41. Allele*	42. Genotype

Frequency	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 uncorrected)=1.67, p=0.20, AG/AA genotype=susceptibility (trend)

Nibrin (NBS1) Gln185Glu G/C Polymorphism Allele and Genotype Frequencies in the Lung Cancer and Resistant Smokers.


	43. Allele*	44. Genotype

Frequency	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, χ²(Yates uncorrected)=4.01, p=0.05, CC genotype=susceptibility

Arginase 1 (Arg1) Intron 1 C/T Polymorphism Allele and Genotype Frequencies in the Lung Cancer and Resistant Smokers.


	45. Allele*	46. Genotype

Frequency	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.


	47. Allele*	48. Genotype

Frequency	C	T	CC	CT	TT

Lung cancer n = 109	129	89	39	51	19
(%)	(59%)	(41%)	(36%)	(47%)	(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.


	49. Allele*	50. Genotype

Frequency	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 (APE1) Asp148Glu T/G Polymorphism Allele and Genotype Frequencies in the Lung Cancer and Resistant Smokers.


	51. Allele*	52. Genotype

Frequency	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%)

*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.


	53. Allele*	54. Genotype

Frequency	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 (NOS3)	NOS3 −786 T/C	TT susceptible
Superoxide dismutase 3 (SOD3)	SOD3 Arg 312 Gln	CG/GG protective
XRCC1	XRCC1 Arg 399 Gln 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
		AA susceptible
Interleukin 1B (IL-1B)	IL-1B −511 A/G	GG susceptible
FAS (Apo-1/CD95)	FAS A-670G	AA susceptible
XPD	XPD −751 G/T	GG protective
CYP 1A1	CYP 1A1 Ile 462 Val	GG/AG protective
	A/G	AA susceptible
Matrix metalloproteinase 12	MMP12 Asn 357 Ser	GG/AG protective
(MMP12)	A/G
8-Oxoguanine DNA glycolase	OGG1 Ser 326 Cys G/C	GG protective
(OGG1)
N-acetyltransferase 2 (NAT2)	NAT2 Arg 197 Gln A/G	GG susceptible
CYP2E1	CYP2E1 1019 G/C Pst I	CC/CG
		susceptible
CYP2E1	CYP2E1 C/T Rsa I	TT/TC
		susceptible
Interleukin-18 (IL-18)	IL-18 105 A/C	AC/CC protective
		AA susceptible
Interleukin-18 (IL-18)	IL-18 −133 G/C	CG/GG protective
		CC susceptible
Glutathione S-transferase M	GSTM null	Null susceptible
Interferon gamma (IFN?)	IFN? 874 A/T	AA susceptible
Cyclo-oxygenase 2 (COX2)	COX2 −765 G/C	CC/CG protective
		GG susceptible
Matrix metalloproteinase 1 (MMP1)	MMP −1607 1G/2G	2G2G susceptible
Connective tissue growth factor	CTGF −447 G/C	GC/CC
(CTGF)		susceptible
Mucin 5AC (MUC5AC)	MUC5AC −221 C/T	TT protective
Mannose binding lectin 2 (MBL2)	MBL2 +161 G/A	AG/AA
		susceptible
Nibrin (NBS1)	NBS1 Gln185Glu G/C	CC susceptible
Arginase 1 (Arg1)	Arg1 intron 1 C/T	TT protective
REV1	REV1 Phe257Ser C/T	CC protective
Insulin-like growth factor II receptor	IGF2R Leu252Val C/G	GG protective
(IGF2R)
Apex nuclease (Apex or APE1))	Apex Asp148Glu G/T	GG susceptible
Interleukin 10 (IL-10)	IL-10 −1082 A/G	GG protective

The combined frequencies of the presence or absence of the selected protective genotypes CYP1A1 GG/AG, OGG1 GG, CCND1 GG, NOS3 298 TT, IL-8 AA, and 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	66/137	37/123	6/42
cancer	(48%)	(30%)	(14%)

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, Resist vs Lung	—	—	22.3	<0.0001
cancer
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	21/92	52/137	35/77
COPD	(23%)	(38%)	(45%)

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+,	—	—	10.2	0.006
Lung cancer vs Resist
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, OGG1 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	54/121	50/133	5/55
cancer	(45%)	(38%)	(9%)

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, Resist vs Lung	—	—	21.5	<0.0001
cancer
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 IFN? AA, observed in the subjects with lung cancer and in resistant smokers is presented below in Table 16.

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	16/81	35/101	58/127
COPD	(20%)	(35%)	(46%)

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, Lung cancer	—	—	14.6	0.0007
vs Resist
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, OGG1 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	45/92	50/129	19/93
cancer	(49%)	(39%)	(20%)

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, Resist vs Lung	—	—	16.8	0.0002
cancer
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

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	13/67	66/179	30/63
COPD	(19%)	(37%)	(48%)

Comparison	Odd's ratio	95% CI	?2	P value

0-1 vs 2-3 vs 4-6,	—	—	11.8	0.003
Lung cancer vs Resist
4-6 vs rest, Lung cancer vs	1.9	1.0-3.5	4.6	0.03
Resist
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 FIG. 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 FIG. 4). It is noted that for FIG. 4, unlike the data presented in FIG. 3, the protective polymorphisms are assigned a negative value while the susceptibility polymorphisms are assigned a positive value. The precise value or sign given to each one is not critical, as long as it is consistent between the types of polymorphisms.

TABLE 19

Combined presence or absence of protective and susceptibility polymorphisms

Score combining protective (−1) and susceptibility (+1) polymorphisms

	−2	−1	0	1	2	3	4+

Lung cancer	0 (0%)	2 (2%)	10 (9%)	21 (19%)	38 (35%)	23 (21%)	15 (14%)
N = 109 (%)
Resistant smokers	6 (3%)	21 (11%)	39 (20%)	51 (26%)	52 (26%)	25 (13%)	6 (3%)
N = 200 (%)
% 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 (Table 20). When assessed as a range between −3 to +5, a linear relationship as depicted in FIG. 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 FIG. 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 (0%)	1 (1%)	3 (3%)	10 (9%)	25 (23%)	32 (29%)	20 (18%)	14 (13%)	4 (4%)
N = 109
Resistant smokers	3 (2%)	12 (6%)	16 (8%)	34 (17%)	58 29%)	48 (24%)	21 (11%)	7 (4%)	1 (0.5%)
N = 200
% 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 (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 can utilise path analysis 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 can be as simple as communicating the net susceptibility score to the subject together with an explanation of the implications of that score. This alone can 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 online at world wide web dot hapmap dot 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		rs12042763		rs4648263
	rs2206594		rs4648250		rs4987012
	rs6687495		rs4648251		rs20428
	rs6681231		rs2223626		rs20429
	rs13376484		rs689462		rs4648264
	rs12064238		rs4648253		rs4648265
	rs10911911		rs689465		rs4648266
	rs12743673		rs12027712		rs4648267
	rs10911910		rs689466		rs11567824
	rs12743516		rs2745558		rs4648268
	rs10911909		rs3918304		rs4648269
	rs1119066		rs20415		rs4648270
	rs1119065		rs20416		rs12759220
	rs1119064		rs4648254		rs20430
	rs10798053		rs11567815		rs4648271
	rs12409744	−765G > C	rs20417		rs11567825
	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		rs3134591		rs3218623
	rs4295848		rs3134592		rs3218624
	rs4428839		rs20426		rs5279
	rs4609389		rs4648258		rs4648278
	rs4428838		rs11567820		rs13306034
	rs12131210		rs2745557		rs2853803
	rs2179555		rs11567821		rs4648279
	rs2143417		rs4648259		rs4648281
	rs2143416		rs4648260		rs4648282
	rs11583191		rs4648261		rs11567826
	rs2383516		rs4648262		rs4648283
	rs2383515		rs11567822		rs4648284
	rs10911905		rs11567823		rs4648285
	rs10911904		rs2066824		rs11567827
			rs20427		rs4648286
	rs4648287		rs1042719		rs5744244
	rs5272		rs3729944		rs360722
	rs4648288		rs3730182		rs5023207
	rs5273		rs1042720		rs5744246
	rs5274		rs6879202		rs5744247
	rs3218625		rs3777124	−133 C/G	rs360721
	rs4648289		rs1803051		rs4988359
	rs4648290		rs8192451		rs12721559
	rs1051896		rs4987255		rs5744248
	rs5275		rs3177007		rs5744249
	1ADRB SNPs		rs1126871		rs5744250
	rs2082382		rs6885272		rs5744251
	rs2082394		rs6889528		rs100000356
	rs2082395		rs4521458		rs1834481
	rs9325119		rs10463409		rs17215057
	rs9325120		rs7702861		rs5744253
	rs12189018		IL-18 SNPs		rs5744254
	rs11168066		rs187238		rs5744255
	rs11959615		rs5744228		rs5744256
	rs11958940		rs360718		rs5744257
	rs4705270		rs360717		rs360720
	rs10079142		rs5744229		rs5744258
	rs9325121		rs100000353		rs5744259
	rs11746634		rs5744231		rs5744260
	rs11168067		rs5744232		rs5744261
	rs9325122		rs7106524	105 A/C	rs549908
	rs11957351		rs189667		PAI-1 SNPs
	rs11948371		rs12290658		rs6465787
	rs11960649		rs12271175		rs7788533
	rs1432622		rs11606049		rs6975620
	rs1432623		rs360716		rs6956010
	rs11168068		rs360715		rs12534508
	rs17778257		rs360714		rs4729664
	rs2400706		rs2043055		rs2527316
	rs2895795		rs5744233		rs2854235
	rs2400707		rs795467		rs10228765
	rs2053044		rs12270240		rs2854225
	rs17108803		rs100000354		rs2854226
	rs12654778		rs4937113		rs2227707
	rs11168070		rs100000355		rs2227631
	rs11959427		rs360723	−675 4G/5G	No rs
	rs1042711		rs5744237		NOS3 SNPs
	rs1801704		rs5744238		rs2373962
Arg16Gly	rs1042713		rs5744239		rs2373961
	rs1042714		rs7932965		rs6951150
	rs1042717		rs11214103		rs13238512
	rs1800888		rs5744241		rs10247107
	rs1042718		rs5744242		rs10276930
	rs3729943		rs5744243		rs10277237
	rs12703107		rs9282804		rs2282679
	rs6946340	Asp298Glu	rs1799983		rs2282680
	rs6946091		VDBP SNPs		rs705117
	rs6946415		rs222035		rs2070741
	rs10952296		rs222036		rs2070742
	rs13309715		rs16846943		rs6821541
	rs10952297		rs7668653		rs222048
	rs7784943		rs1491720		rs432031
	rs11771443		rs16845007		rs432035
	rs2243310		rs17830803		rs222049
	rs1800783	Glu416Asp	rs7041		rs222050
	rs3918155	Lys420Thr	rs4588		rs12510584
	rs3918156		rs3737553		rs17467825
	rs2566519		rs9016		GSTP1 SNPs
	rs3918157		rs1352846		rs656652
	rs3918158		rs222039		rs625978
	rs3918159		rs3775154		rs6591251
	rs2566516		rs222040		rs12278098
	rs3918225		rs843005		rs612020
	rs3918160		rs222041		rs12284337
	rs1800779		rs7672977		rs12574108
	rs2243311		rs705121		rs6591252
	rs3918161		rs11723621		rs597717
	rs10952298		rs2298850		rs688489
	rs2070744		rs705120		rs597297
	rs3918226		rs2298851		rs6591253
	rs3918162		rs844806		rs6591254
	rs3918163		rs1491709		rs7927381
	rs3918164		rs705119		rs7940813
	rs3918165		rs6845925		rs593055
	rs1800781		rs12640255		rs7927657
	rs13310854		rs12644050		rs614080
	rs13310763		rs6845869		rs7941395
	rs2853797		rs12640179		rs7941648
	rs13311166		rs222042		rs7945035
	rs13310774		rs3187319		rs2370141
	rs2853798		rs222043		rs2370142
	rs11974098		rs842999		rs7949394
	rs3918166		rs222044		rs7949587
	rs3730001		rs222045		rs6591255
	rs3918167		rs16846912		rs8191430
	rs3918168		rs222046		rs6591256
	rs3918169		rs705118		rs8191431
	rs3918170		rs222047		rs8191432
	rs3793342		rs13142062		rs7109914
	rs3793341		rs843000		rs4147580
	rs1549758		rs3755967		rs8191436
	rs1007311		rs1491710		rs8191437
	rs9282803		rs2282678		rs17593068
	rs8191438		rs2069718		rs7145047
	rs8191439		rs3087272		rs7141735
	rs8191440		rs2069719		rs11558264
	rs8191441		rs9282708		rs6647
	rs1079719		rs2069720		rs8350
	rs1871041		rs1042274		rs2230075
	rs4147581		rs2069721		rs1049800
	rs8191444		rs2069734	S allele	rs17580
	rs8191445		rs2069722		rs2854258
	rs2370143		rs2234687		rs2753937
	rs8191446		rs7957366		rs2749547
	rs3891249		rs2069723		rs1243162
	rs8191447		rs2069724		rs2753938
	rs12796085		rs2069725		rs2070709
	rs8191448		rs4394909		rs17090719
	rs762803		rs2069726		rs11846959
	rs8191449		rs2069727		rs1802962
Ile105Val	rs947894		IL-13 SNPs		rs2749521
	rs4986948	−1055 C/T	rs1800925		rs2753939
	rs675554		rs11575055		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
	rs1871042		rs1295687		rs1303
	rs11553892		rs3212145		rs1802960
	rs4891		rs2069744		rs1243163
	rs6413486		rs2069745		rs2073333
	rs5031031		rs2069746		rs1243164
	rs947895		rs2069747		rs7144409
	IFN-SNPs		rs2069748		rs7142803
	rs2069707		rs1295686		rs1243165
	rs3814242	Arg130Gln	rs20541		rs1051052
	rs2069709		rs2069749		rs1243166
	rs2069710		rs1295685		rs11628917
	rs2069711		rs848		rs11832
	rs2069712		rs2069750		rs9944155
874 A/T	rs2430561		rs847	1237 G/A	rs11568814
	rs2069713		a1-antitrypsin		rs877081
			SNPs
	rs1861494		rs709932		rs877082
	rs2234685		rs11558261		rs877083
	rs1861493		rs20546		rs877084
	rs2069714		rs11558263		rs875989
	rs2069715		F1028580		rs9944117
	rs2069716		rs7145770		rs1884546
	rs2069717		rs2239652		rs1884547
	rs1885065		rs2735442		rs8046608
	rs1884548		rs2569693		rs5743264
	rs1243167		rs281439		rs5743266
	rs17751614		rs281440		rs2076752
	rs1884549		rs2569694		rs5743267
	rs1243168		rs11575073		rs8061316
	rs17090693		rs2569695		rs8061636
	rs17824597		rs2075741		rs16948754
	TNFa SNPs		rs11575074		rs7206340
	rs1799964		rs2569696		rs2076753
	rs1800630		rs2735439		rs2067085
	rs1799724		rs2569697		rs16948755
+489 G/A	rs1800610		rs2075742		rs2111235
	rs3093662		rs2569698		rs2111234
	rs3093664		rs11669397		rs7190413
−308 G/A	rs1800629 (1)		rs901886		rs7206582
	SMAD3 SNPs		rs885742		rs8045009
C89Y	C89Y no rs (2)		rs2569699		rs6500328
	ICAM1		rs1056538		rs7500036
	rs1799969		rs11549918		rs8057341
	rs5493		rs2569700		rs12918060
	rs5030381		rs2228615		rs7204911
	rs5494		rs2569701		rs7500826
	rs3093033		rs2569702		rs4785449
	rs5495		rs2735440		rs12922299
	rs1801714		rs2569703		rs11649521
	rs13306429		rs10418913		rs13339578
	rs2071441		rs1056536		rs17221417
	rs5496		rs2569704		rs13331327
	rs5497		rs11673661		rs11642482
	rs13306430		rs2569705		rs11642646
E469K	rs5498		rs10402760		rs17312836
	rs5030400		rs2569706		rs5743268
	rs2071440		rs2569707		rs5743269
	rs5499		rs2735441		rs5743270
	rs3093032		rs2436545		rs12925051
	rs1057981		rs2436546		rs12929565
	rs5500		rs2916060		rs13380733
	rs5501		rs2916059		rs13380741
	rs5030383		rs2916058		rs11647841
	rs281436		rs2569708		rs10451131
	rs923366		rs12972990		rs2066842
	rs281437		rs735747		rs5743271
	rs3093030		rs885743		rs7498256
	rs5030384		NOD2 SNPs		rs5743272
	rs5030385		rs4785224		rs5743273
	rs3810159		rs5743261		rs2076754
	rs281438		rs5743262		rs2066843
	rs3093029		rs5743263		rs1078327
	rs5743274		rs11645386		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
	rs16948773		rs3135500		rs11575988
	rs9931711		rs5743300		rs11575989
	rs17313265		rs8056611		rs7095891
	rs11646168		rs2357792		rs4647963
	rs9925315		rs12600253		rs8179079
	rs5743284		rs12598306		rs5030737
	rs5743285		rs7205423	161 G/A	rs1800450
	rs751271		rs718226		rs1800451
	rs748855		MBL2 SNPs		rs12246310
	rs1861758		rs7899547		rs12255312
	rs13332952		rs10824797		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		rs12263867		rs930508
	rs2076756		rs11003129		rs930507
	rs12920425		rs12221393		CMA1 SNPs
	rs12920040		rs2165811		rs1956920
	rs12920558		rs12782244		rs1956921
	rs12919099		rs11003128	−1903 G/A	rs1800875
	rs12920721		rs17664818		rs1800876
	rs2076755		rs7475766		rs3759635
	rs5743290		rs10824796		rs1956922
	rs5743291		rs16933417		rs1956923
	rs11642651		rs2165810		NAT2 SNPs
	rs1861756		rs11003127		rs11780272
	rs749910		rs3925313		rs2101857
	rs4990643		rs7094151		rs13363820
	rs1077861		rs7071882		rs6984200
	rs5743292		rs12264958		rs13277605
	rs9921146		rs11003126		rs9987109
	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
	rs11785247		rs6743330		rs9578037
	rs1115783		rs6743326		rs9578196
	rs1115784		rs6743322		rs4293222
	rs1961456		rs6761220		rs10507391
	rs1112005		rs6761218		rs12429692
	rs11782802		rs5021469		rs4769871
	rs973874		rs6710598		rs4769872
	rs1495744		rs1143623		rs4769873
	rs7832071		rs1143624		rs12430051
	rs1805158		rs2708920		rs9315045
	rs1801279		rs1143625		rs9670278
	rs1041983		rs2853545		rs4503649
	rs1801280		rs2708921		rs9508832
	rs4986996		rs1143626		rs9670460
	rs12720065		rs3087258		rs3885907
	rs4986997	C-511T	rs16944		rs3922435
	rs1799929		rs3917346		rs9551957
Arg197Gln	rs1799930		rs4986962		rs12018461
	rs1208		rs1143627		rs9551958
	rs1799931		MEH SNPs		rs10467440
	rs2552	Tyr113His	rs1051740 (2)		rs12017304
	rs4646247	His139Arg	rs2234922 (2)		rs9551959
	rs971473		ALOX5AP SNPs		rs11617473
	rs721398		rs4076128		rs11147438
	IL-1B 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		rs12877064		rs17612099
	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		rs1005569
	rs9506352		rs2791517		rs5744325
	rs9670531		rs5744303		rs5744326
	rs9671182		rs2734706		rs1985554
	rs9315047		rs2753345		rs1985555
	rs17690694		rs2753347		rs100000102
	rs9652070		rs2753348		rs100000103
	rs17074966		rs2753349		rs1969719
	rs4387455		rs5744304		rs2390102
	rs4254166		rs5744305		rs5744329
	rs4075692		rs1358826		rs1407142
	rs17690748		rs2753359		rs2753384
	rs9671124		rs5744306		rs2753385
	rs9671125		rs2734711		rs5744330
	rs9741436		rs5744307		rs5744331
	rs9578197		rs2734712		rs926064
	rs4769056		rs2753361		rs926065
	rs11147439		rs2753364		rs926066
	rs12721459		rs1555389		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		rs100000104
	rs16867580		rs5744320		rs2791515
	rs2075799		rs5744321		rs4656116
	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		rs17424356
	rs5744352		rs3138076		rs6017500
	rs11583355		rs12519656		rs6032040
	rs100000106		rs5744449		rs6017501
	rs1321695		rs2915863		rs2664581
+13924 T/A	rs1321694		rs3138078		rs17424474
	rs2791514		rs6875483		rs17333381
	rs2734696		rs2569191		rs1053826
	rs5744354		rs5744451		rs2664533
	rs2791513		rs5744452		rs1053831
	rs2753332		rs100000098		rs2664520
	rs2791512		rs17118968		rs2267864
	rs2791511		rs5744455		rs13038355
	rs2734697	−159 C/T	rs2569190		rs13043296
	CD14 SNPs		rs2569189		rs13039213
	rs6877461		rs2563303		rs6104049
	rs3822356		rs3138079		rs13043503
	rs6877437		rs2228049		rs6104050
	rs12153256		rs13763		rs17424578
	rs11554680		rs11556179		rs17424613
	rs12109040		rs4914		rs6017502
	rs12517200		Elafin SNPs		rs6094101
	rs5744430		rs2868237		rs6130778
	rs5744431		rs4632412		rs6130779
	rs100000092		rs7347427		rs6104051
	rs5744433		rs6032032		rs6104052
	rs100000093		rs10854230		ADBR2 SNPs
	rs4912717		rs7347426		rs2082382
	rs100000094		rs8183548		rs2082394
	rs100000095		rs6104047		rs2082395
	rs100000096		rs6513967		rs9325119
	rs6864930		rs13038813		rs9325120
	rs100000097		rs8118673		rs12189018
	rs6864583		rs7346463		rs11168066
	rs6864580		rs7362841		rs11959615
	rs6889418		rs13042694		rs11958940
	rs6889416		rs13038342		rs4705270
	rs5744440		rs7363327		rs10079142
	rs5744441		rs6073668		rs9325121
	rs5744442		rs13044826		rs11746634
	rs11168067		rs1800468		rs542603
	rs9325122		rs4987025		rs574939
	rs11957351		rs1800469		rs573764
	rs11948371		rs11466314		rs7102189
	rs11960649		rs12977628		rs575727
	rs1432622		rs12977601		rs552306
	rs1432623		rs12985978		rs634607
	rs11168068		rs11466315		rs12286876
	rs17778257		rs11551223		rs12285331
	rs2400706		rs11551226		rs519806
	rs2895795		rs11466316		rs12283571
	rs2400707		rs13306706		rs2839969
	rs2053044		rs13306707		rs2000609
	rs17108803		rs13306708		rs7125865
	rs12654778		rs9282871		rs570662
	rs11168070	Leu10Pro	rs1982073		rs11225427
	rs11959427		rs1800471		rs484915
	rs1042711		rs13447341		rs470307
	rs1801704		rs11466318		rs2408490
	rs1042713		rs12976890		rs12279710
Gln27Glu	rs1042714		rs12978333		rs685265
	rs1042717		rs10420084		rs7107224
	rs1800888		rs10418010		rs1155764
	rs1042718		rs12983775		rs534191
	SOD3 SNPs		rs12462166		rs509332
Arg213Gly	rs1799895 (2)		rs2241715		rs12283759
	TGFB1 SNPs		rs9749548		rs2105581
	rs1529717		rs7258445		rs470206
	rs1046909		rs11466320		rs533621
	rs2241712		rs11466321	−1607 G/GG	rs1799750
	rs2241713		rs8108052		rs470211
	rs2241714		rs6508976		rs470146
	rs11673525		rs8108632		rs2075847
	rs2873369		rs11466324		rs473509
	rs11083617		rs2241716		rs498186
	rs11083616		rs2241717		GSTM1
					polymorphism
	rs4803458		rs2288873	Null	Null allele No rs (2)
	rs11670143		rs12973435		MMP9 SNPs
	rs1982072		rs2014015		rs11696804
	rs11668109		rs1989457		rs6104416
	rs13345981		rs10406816		rs3933239
	rs11666933		rs8102918		rs3933240
	rs11466310		rs4803455		rs6094237
	rs11466311		MMP1 SNPs		rs11697325
	rs2317130		rs529381		rs6130988
	rs4803457		rs1144396		rs6073983
	rs3087453		rs504875		rs6130989
	rs1800820		rs526215		rs6130990
	rs1054797		rs12280880		rs10211842
	rs6073984		rs8125587		TIMP3 SNPs
	rs6073985		rs3918253		rs5754289
	rs8121146		rs2274755		rs5754290
	rs6032620		rs2664538		rs9606994
	rs11698788		rs3918254		rs7285034
	rs6032621		rs6130993		rs13433582
	rs6065912		rs3918255		rs1962223
	rs6104417		rs2236416		rs8137129
	rs3848720		rs6130994		rs1807471
	rs13040272		rs3918256		rs7290885
	rs6104418		rs3918281		rs5749511
	rs3848721		rs3787268		rs11703366
	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		rs13969		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		rs1802909
	rs6104423		rs13925
	rs6104424		rs20544
	rs6104425		rs1056628
	rs6104426		rs1802908
	rs3918250		rs2664517
	rs1805089		rs9509
	rs3918251		rs3918268
	rs13040572		rs3918269
	rs13040580		rs3918270
	rs3918252		MMP12 SNPs
	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 include 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. Additional information regarding the above material, or subparts thereof, can be found in U.S. patent application Ser. No. 10/479,525, filed Jun. 16, 2004; and PCT Application No. PCT/NZ02/00106, filed Jun. 5, 2002, which further designates New Zealand Application No. 512169, filed Jun. 5, 2001; New Zealand Application No. 513016, filed Jul. 17, 2001, and New Zealand Application No. 514275, filed Sep. 18, 2001, all of which are incorporated by reference in their entireties. Additional information can also be found in PCT application Nos. ______ and ______, filed May 10, 2006, entitled “Methods and Compositions for Assessment of Pulmonary Function and Disorders” and “Methods of Analysis of Polymorphisms and Uses Thereof” respectively, having Agent Reference Nos. 542813JBM and 542814JBM respectively, both of which are incorporated in their entireties by reference. PCT Application Agent Reference No. 542813JBM claims priority to: NZ application No. 539934, filed May 10, 2005; NZ application No. 541935, filed Aug. 19, 2005; and JP application No. 2005-360523, filed Dec. 14, 2005, all of which are incorporated by reference in their entireties. PCT Application Agent Reference No. 542814JBM claims priority to: NZ application No. 540249, filed May 20, 2005; and NZ application No. 541842, filed Aug. 15, 2005, all of which are incorporated in their entireties by reference. Additional information can also be found in U.S. Pat. No. ______, filed concurrently with the instant application, entitled “Methods and Compositions for Assessment of Pulmonary Function and Disorders”, attorney docket No; SGENZ.013AUS, incorporated by reference in its entirety.

PUBLICATIONS

1. Sandford A J, et al., 1999. Z and S mutations of the α1-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 Vasc Biol. 20; 1631-1635.
4. Ukkola, O., Erkkilä, P. H., Savolainen, M. J. & Kesäniemi, 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 C A D & Harrison D J, 1997. Association between polymorphism in gene for microsomal epoxide hydrolase and susceptibility to emphysema. Lancet. 350; 630-633.
6. Lorenz E, et al., 2001. Determination of the TLR4 genotype using allele-specific PRC. Biotechniques. 31; 22-24.
7. Cantlay A M, Smith C A, Wallace W A, Yap P L, Lamb D, Harrison D J. Heterogeneous expression and polymorphic genotype of glutathione S-transferases 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. Any and all materials and information from any such patents, publications, scientific articles, web sites, electronically available information, and other referenced materials or documents can be physically incorporated into this specification.
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” can 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 can 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 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 the Applicant.
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 can 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.

Claims

1. 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 a protective polymorphism and for the presence or absence of a susceptibility polymorphism, wherein said protective polymorphism and said susceptibility polymorphism 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 polymorphism and the combined value of the susceptibility polymorphism 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 developing said disease.

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

3.-25. (canceled)

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 a presence or absence of a protective polymorphism and a presence or absence of a susceptibility polymorphism, and 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; and

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

27. (canceled)

28. A method of treatment of a subject to decrease a 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

3) a) reversing, genotypically or phenotypically, the presence, functional effect, or presence and functional effect of one or more susceptibility polymorphisms associated with said disease and

b) replicating, mimicking, or replicating and mimicking, genotypically or phenotypically, the presence, functional effect, or presence and functional effect of one or more protective polymorphisms associated with said disease.

29. (canceled)