WO2013043041A2

WO2013043041A2 - Methods and compositions for diagnosing familial hypercholesterolemia

Info

Publication number: WO2013043041A2
Application number: PCT/MY2012/000253
Authority: WO
Inventors: Mathavan A CHANDRAN; Parmod G BAGALI; Livy ALEX; Jagdish Kaur CHAHIL; Say Hean LYE; Lian Wee LER
Original assignee: Infovalley® Group Of Companies
Priority date: 2011-09-21
Filing date: 2012-09-21
Publication date: 2013-03-28
Also published as: WO2013043041A3

Abstract

A method for diagnosing Familial Hypercholesterolemia (FH) and/or predisposition to FH in an individual of Asian descent, the method comprising detecting the presence of at least one single nucleotide polymorphism (SNP) in a sample of the individual.

Description

METHODS AND COMPOSITIONS FOR DIAGNOSING FAMILIAL

HYPERCHOLESTEROLEMIA

FIELD OF THE INVENTION

The present invention relates to method(s) and composition(s) for diagnosing Familial Hypercholesterolemia (FH) in a subject and in particular but not exclusively by using microarray.

BACKGROUND TO THE INVENTION FH (OMIM 143890) is an inherited disorder of lipoprotein metabolism, transmitted in an autosomal dominant manner. FH, the most common and most severe form of hypercholesterolemia, was the first genetic disease of lipid metabolism to be clinically and molecularly characterized. Clinically, FH is characterized by elevated levels of Low-density lipoprotein- Cholesterol (LDLC) and total cholesterol in the circulation, deposits of cholesterol in peripheral tissues, presence of tendon xanthomas and premature or accelerated atherosclerosis. Atherosclerosis may result in widespread clinical manifestations, including coronary heart disease (CHD), cerebrovascular disease (CVD) and peripheral vascular disease (PVD). Many subjects with hypercholesterolemia die each year as a result, and many have a reduced quality of life. Inevitably, this places very heavy demands on health service resources.

Because FH responds well to drug treatment, making an early diagnosis to reduce atherosclerosis risk is beneficial. Series of tests on FH family members is cost effective and merits further research. Heterozygous FH is the most frequent Mendelian disorder, being more frequent than other complex diseases. In most populations, the frequency of heterozygotes is not less than 1 in 500 and the frequency of the homozygote FH is 1 in a million.

The diagnosis of FH has traditionally been based on the detection of elevated total plasma cholesterol levels in subjects belonging to families with high frequencies of early-onset coronary artery disease (CAD) and/or primary hypercholesterolemia. Three sets of diagnostic criteria have been extensively used for the clinical diagnosis of FH: those of the Simon Broome Register Group (SBRG) in the United Kingdom (BMJ, 1991), the Make Early Diagnosis to Prevent Early Death (MEDPED) program in the United States (Williams, 1993), and the Dutch Lipid Clinic Network (DLCN) (Austin, 1993 and Betteridge, 2000). However, establishing an accurate diagnosis of FH is still difficult and as such, the disorder is severely under-diagnosed and under-treated in many countries.

Systematic screening for functional mutations in genes associated with FH is also one way of diagnosing FH. However, it is well known in the art that genetic variation exists among human individuals and in particular between ethnic groups. There are marked physical and physiological differences among human populations that presumably reflect long-term adaptation to unique ecological conditions, random genetic drift, and sex selection. In contemporary populations, these differences are evident both in morphological differences between ethnic groups and in differences in susceptibility and resistance to diseases. There are thus genetic markers that exist in one population and not in others and there are also genetic markers at loci at which different alleles are fixed in different populations. The FH risk associated with a specific genetic variant can be substantially different among different ethnic groups. Accordingly, the current method of systemic screening is not universal and accurate for all populations.

SUMMARY OF THE INVENTION

According to one aspect, the present invention relates to a method for diagnosing FH and/or predisposition to FH in an individual of Asian descent, the method comprising detecting the presence of at least one SNP in at least one gene associated with lipid metabolism in a sample of the individual. In particular, the gene may be LDLR gene, APOB gene, PCSK9 gene and/or the like. More in particular, the gene may be selected from the group consisting of Low-Density Lipoprotein Receptor gene (LDLR), Apolipoprotein B-100 gene (APOB), Proprotein Convertase Subtilisin/Kexin type 9 gene (PCSK9), ATP-binding cassette, sub-family B (MDR/TAP), member 1 (ABCB1), ATP-binding cassette, sub-family G (WHITE), member 5 (ABCG5), arachidonate 5-lipoxygenase-activating protein (ALOX5AP), apolipoprotein A-l (APOA1 ), apolipoprotein A-IV (APOA4), apolipoprotein B (including Ag(x) antigen) (APOB), apolipoprotein E (APOE), family with sequence similarity 5, member C (FAM5C), fibrinogen beta chain (FGB), G protein-coupled receptor kinase 5 (GRK5), insulin-like growth factor 1 receptor (IGF1 R), interleukin 6 (interferon, beta 2) (IL6), intragenic regions, intronic regions in taste receptor, type 2, member 50 (TAS2R50), integrin, beta 2 (complement component 3 receptor 3 and 4 subunit) (ITGB2), lipase, hepatic (LIPC), lipoprotein lipase (LPL), melanoma inhibitory activity family, member 3 (MIA3), and upstream transcription factor 1 (USF1 ). In particular, the SNP may be selected from the group of loci with nucleotide base change consisting of:

g.183884 T>A (reference sequence AY910577), g.12292096 A>T (reference sequence NT_024524.14), c.736C>T (reference sequence AF261279), c.237-55462 T>C (reference sequence NM_199051.1 ), c.122 A>T (reference sequence N _005308.2), g.22073404 C>T (reference sequence NT_008413.18), c.384-100 G>A (reference sequence NM_207005.1 ), c.^*187 C>T (reference sequence NM_207005.1), g.3534 G>A (reference sequence AY593992), g.1928 T>C (reference sequence AY593992),c.148 C>T (reference sequence NM_022436.2), c.101 G>T (reference sequence NM_000039), c.478 G>A (reference sequence NM_000039), c.664 G>A (reference sequence NM_000039), c.913 C>T (reference sequence NM_000482), g.32818 G>A (reference sequence AY324608), g.30761 G>A (reference sequence AY324608), g.16366 C>T (reference sequence AY324608), C.508 G>C (reference sequence AF261279), c.805 C>G (reference sequence AF261279), c.875 G>A (reference sequence AF261279), c.388 T>C (reference sequence NM_000041.2), g.1744 C>T (reference sequence AF388026), g.285748 G>A (reference sequence AY332722), g.3114 G>T (reference sequence AF372214), g.78787630 G>A (reference sequence NT_005612.16), g.9939206 T>C (reference sequence NT_010194.17), c-125-12532 G>A (reference sequence NM_006250.2), c.1323 T>G (reference sequence NM_001127491.1 ), g.26689 A>G (reference sequence AY324609), g.2673 C>G (reference sequence AY324609), c.89-18333 C>T (reference sequence NM_000236.2), c.596 C>G (reference sequence NM_000237), c.3632-105 A>C (reference sequence NMJ98551.2), g.5996 G>C (reference sequence AY829011 ), and g.13869 T>C (reference sequence AY829011 ) where "g" stands for genomic sequence and "c" stands for DNA coding sequence. Even more in particular, the SNP may be selected from the SNPs listed in Table 1.

According to other aspects, the present invention provides microarrays, chips, and/or kits comprising at least one probe capable of hybridizing to at least one SNP according to any aspect of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Bibliographic references mentioned in the present specification are for convenience listed in the form of a list of references and added at the end of the examples. The whole content of such bibliographic references is herein incorporated by reference.

Definitions For convenience, certain terms employed in the specification, examples and appended claims are collected here.

The term "Asian" used interchangeably with the term "of Asian descent" is herein defined to be a person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent. In particular, an individual of "Asian descent" includes a person of Chinese ancestry, Malay ancestry and/or Indian ancestry.

The term "comprising" is herein defined to be that where the various components, ingredients, or steps, can be conjointly employed in practicing the present invention. Accordingly, the term "comprising" encompasses the more restrictive terms "consisting essentially of" and "consisting of." With the term "consisting essentially of" it is understood that the method according to any aspect of the present invention "substantially" comprises the indicated SNP as "essential" element. Additional SNPs may be included. Accordingly, a method "consisting essentially of" a plurality of SNPs will be novel in view of a known polypeptide accidentally comprising one of the SNPs. With the term "consisting of" it is understood that the method, microarray and/or chip according to the invention corresponds to all of the SNPs. The term "label" or "label containing moiety" refers in a moiety capable of detection, such as a radioactive isotope or group containing same and nonisotopic labels, such as enzymes, biotin, avidin, streptavidin, digoxygenin, luminescent agents, dyes, haptens, and the like. Luminescent agents, depending upon the source of exciting energy, can be classified as radio luminescent, chemiluminescent, bio luminescent, and photo luminescent (including fluorescent and phosphorescent). A probe described herein can be bound, for example, chemically bound to label-containing moieties or can be suitable to be so bound. The probe can be directly or indirectly labelled.

The term "locus" is herein defined to be a specific location of a gene or DNA sequence on a chromosome. A variant of the DNA sequence at a given locus is called an allele. The ordered list of loci known for a particular genome is called a genetic map. Gene mapping is the process of determining the locus for a particular biological trait.

The term "polymorphism" is herein defined to be the occurrence of genetic variations that account for alternative DNA sequences and/or alleles among individuals in a population. The term "polymorphic site" is herein defined to be a genetic locus wherein one or more particular sequence variations occur. A polymorphic site can be one or more base pairs. For example, a "single nucleotide polymorphism (SNP)" is a polymorphism that occurs at a single nucleotide. As used herein, a "cluster" of SNPs refers to three or more SNPs that occur within 100 kilobases of each other in a particular polymorphic site, wherein all of the SNPs have a p-value e^"4 (i.e. < 1 x 10^"4).

The term "probe" is herein defined to be an oligonucleotide. A probe can be single stranded at the time of hybridization to a target. Probes include but are not limited to primers, i.e., oligonucleotides that can be used to prime a reaction, for example at least in a PCR reaction.

The term "reference nucleotide sequence" used interchangeably with the term "reference sequence" is herein defined to be for a nucleotide sequence of a particular gene for example, in NCBI databases (www.ncbi.nlm.nih.gov). Alleles that differ from the reference are referred to as "variant" alleles. The polypeptide encoded by the reference nucleotide sequence is the "reference" polypeptide with a particular reference amino acid sequence, and polypeptides encoded by variant alleles are referred to as "variant" polypeptides with variant amino acid sequences. Nucleotide sequence variants can result in changes affecting properties of a polypeptide. These sequence differences, when compared to a reference nucleotide sequence, include insertions, deletions, conversions and substitutions: e.g. an insertion, a deletion or a conversion may result in a frame shift generating an altered polypeptide; a substitution of at least one nucleotide may result in a premature stop codon, amino acid change or abnormal mRNA splicing; the deletion of several nucleotides, resulting in a deletion of one or more amino acids encoded by the nucleotides; the insertion of several nucleotides, such as by unequal recombination or gene conversion, resulting in an interruption of the coding sequence of a reading frame; duplication of all or a part of a sequence; transposition; or a rearrangement of a nucleotide sequence. For example, AY324609 is a reference nucleotide sequence for LDLR that may be used. Other reference sequences may be used. For example, but not limiting, reference sequences AY910577 for ABCB1 , NM_022436.2 for ABCG5, NT_024524.14 for ALOX5AP, NM_000039 for APOA1 , NM_000482 for APOA4, AY324608 for APOB, AF261279 for APOE, NM_000041.2 for APOE, NM_199051.1 for FAM5C, AF388026 for FGB, NM_005308.2 for GRK5, AY332722 for IGF1 , AF372214 for IL6, NT _.008413.18 for Intergenic, NT_005612.16 for Intergenic, NT_0 0194.17 for Intergenic, NM_006250.2 for Intronic region of TAS2R50, NM_001127491.1 for ITGB2, NMJJ00236.2 for LIPC, NM_000237 for LPL, NMJ 98551.2 for MIA3, AY829011 for PCSK9, NM_207005.1 for USF1 , AY593992 for USF1 and the like may be used.

The term "sample" is herein defined to include but is not limited to be blood, sputum, saliva, mucosal scraping, tissue biopsy and the like.

A person skilled in the art will appreciate that the present invention may be practiced without undue experimentation according to the method given herein. The methods, techniques and chemicals are as described in the references given or from protocols in standard biotechnology and molecular biology text books.

FH can result from mutations in several genes associated with Lipid metabolism. In particular, FH can result from mutations in the Low-Density Lipoprotein Receptor gene (LDLR), the Apolipoprotein Β-10Ό gene (APOB), the Proprotein Convertase Subtilisin/Kexin type 9 gene (PCSK9) and the like. Most of these studies have been related to mutations of genes conducted in non-Asian populations. However, in South East Asia, only small-scale lipid studies have been done, and there is no Lipid Registry reported in this region. There is thus a need to provide a method of diagnosing FH in an Asian population. In particular, there is a need to determine polymorphisms in genes that contribute to the genetic predisposition for FH across the Asian population.

According to one aspect, there is provided at least one method for diagnosing FH and/or predisposition to FH in an individual of Asian descent. In particular, the method comprises detecting the presence of at least one SNP in the genes as described in a sample of the individual.

In particular, the SNP may be selected from g.183884 T>A (reference sequence AY910577), g.12292096 A>T (reference sequence NT_024524.14), c.736C>T (reference sequence AF261279), c.237-55462 T>C (reference sequence NM_199051.1), c.122 A>T (reference sequence NM_005308.2), g.22073404 C>T (reference sequence NT_008413.18), c.384-100 G>A (reference sequence NM_207005.1 ), c.^*187 C>T (reference sequence NM_207005.1 ), g.3534 G>A (reference sequence AY593992), g.1928 T>C (reference sequence AY593992),c.148 C>T (reference sequence NM_022436.2), C.101 G>T (reference sequence NM_000039), c.478 G>A (reference sequence NM_000039), c.664 G>A (reference sequence NMJ300039), c.913 C>T (reference sequence NM_000482), g.32818 G>A (reference sequence AY324608), g.30761 G>A (reference sequence AY324608), g.16366 C>T (reference sequence AY324608), c.508 G>C (reference sequence AF261279), c.805 C>G (reference sequence AF261279), c.875 G>A (reference sequence AF261279), c.388 T>C (reference sequence NM_000041.2), g.1744 C>T (reference sequence AF388026), g.285748 G>A (reference sequence AY332722), g.3114 G>T (reference sequence AF372214), g.78787630 G>A (reference sequence NT_005612.16), g.9939206 T>C (reference sequence NT_010194.17), c-125- 12532 G>A (reference sequence NM_006250.2), c.1323 T>C (reference sequence NM_001127491.1 ), g.26689 A>G (reference sequence AY324609), g.2673 C>G (reference sequence AY324609), c.89-18333 C>T (reference sequence NM_000236.2), c.596 C>G (reference sequence NM_000237), c.3632-105 A>C (reference sequence NM_198551.2), g.5996 G>C (reference sequence AY829011 ), g.13869 T>C (reference sequence AY829011) and the like. More in particular, the SNP may be selected from the SNPs listed in Table 1.

SNP Reference HGVS nomenclature rs number Sequence FH Risk SEQ ID

Sequence Allele No. g.183884T>A AY910577 NG_011513.1 :g.186947T>A rs2032582 TGAAAGATAAGAAAGAACTAGA A 1

AGGT [A/G/T ] CTGGGAAGGTG

AG TCAAAC TAAATA

g.12292096A NT 024524. NT 024524.14:g.12292096 rs10507391 TGTCCAAGCCTCTCTTTGCAAT T 2 >T 14 A>T TCTA [A/T] TTAACCTCAATGT

TGCAACCATAGA

c736C>T AF261279 NM000041.2:c.736C>T rs121918395 AGGAGATGGGCAGCCGGACCCG c 3

CGAC [C/T ] GCCTGGACGAGGT

GAAGGAGCAGGT

.237- NM_199051 NM 199051.1 :c.237- rs1171381 AAACACTACTCAGTTTCCATCC T 4 55462T>C .1 55462T>C GTTT [C/T] TTTCTGGGAGTA

GGAGTGGGGTAC

.122A>T NM 005308 NM_005308.2:c.122A>T rs2230345 AATCCTGAAGTTCCCTCACATT A 5

.2 AGCC [A/T] GTGTGAAGACCTC

CGAAGGACCATA

g.22073404C NT 008413. NT 008413.18:g.22073404 rs1333040 AGACAGGAGGGTCAGAGGTAAG C 6 >T 18 C T AATG [C/T] TACCGCTGGGACA

GAGAGGAAGGTA

.384- NM 207005 NM 207005.1 :c.384- rs2073658 TGAGACACCACACCTAGCTACC A 7 100G>A .1 100G>A ATAA [A/G] TGGTCCTAATACC

TGCTAAATCTTG

.^*187C>T · NM 207005 NM_207005.1 :c.*187C>T rs3737787 CAGTGGTGTGAAACACACAATG T 8

.1 TGGA [ C/T] GTGCACTGACAGC

CTTGCCCACCCC

g.3534G>A AY593992 NG_011612.1 :g.7637G>A rs2516839 TTAGCACTCAGGCCTGTGAATC A 9

AGGA [A/G] TACAAAGACCTC

CAAAAAAGGACC

g.1928T>C AY593992 NG_011612.1 :g.6031T>C rs2516837 GACGCGGTCTTTCCGAGGCTTA C 10

TCCA [C/T] TGAAAATTTTCCT

TGGATAGGAAAG

c.148C>T NM 022436 NM_022436.2:c.148C>T rs6756629 TGTGATGTCCCACCAGGGCCTC T 11

.2 ACGC [A/C/G] GTGGCTTTAAA

GGAAACCCCAGGAA

c.101G>T NM 000039 rs28929476 TGAACCCCCCCAGAGCCCCTGG T 12

.1 NM_000039.1 :c.101G>T GATC [G/T] AGTGAAGGACCTG

GCCACTGTGTAC

0.478G>A NM 000039 rs121912718 AAGAGGGCGCGCGCCAGAAGCT A 13

.1 NM_000039.1 :c.478G>A GCAC [A/G] AGCTGCAAGAGAA

GCTGAGCCCACT

.664G>A NM_000039 NM 000039.1 :c.664G>A rs121912717 TGGCCGAGTACCACGCCAAGGC A 14 .1 CACC [A/G] AGCATCTGAGCAC

GCTCAGCGAGAA

C913C>T NM 000482 NM_000482.3:c.913C>T rs150264487 GTTTTCCCCGTAGGGCTCCACC T 15

.3 CGGC [A/G] TCGGAACTCCTCC

ACCTGCTGGTCC

g.32818G>A AY324608 NG_011793.1 :g.35861G>A rs13306187 CACAGACCATTTCAGCCTTCGG A 16

GCTC [A/G] TTACCACATGAAG

GCTGACTCTGTG

g.30761G>A AY324608 NG_011793.1 :g.33804G>A rs12720770 TAGTACCATTCACAACTATTTC A 17

CTAC [A/G] TATTTTCAGATGA

AGAGAAGATTGA

g.16366C>T AY324608 NG_011 93.1 :g.19 12C>T rs 13306194 TCCAGAAAGCTGCCATCCAGGC T 18

TCTG [C/T ] GGAAAATGGAGCC

TAAAGACAAGGT

.508G>C AF261279 NM_0000 1.2:c.508G>C N/A ATGATCCAGAAAGCTGCCArCC c 19

AGGCTCTG [ T /C ] GGAAAATGG

AGCCTAAAGACAAGGTAAAGT

C.805C>G AF261279 NM_000041.2:c.805C>G N/A CGCAAGCTGCGTAAGCGGCTCC G 20

TCCGCGAT [ C/GJ CCGATGACC

TGCAGAAGCGCCTGGCAGTGT

.875G>A AF261279 NM_000041.2:c.875G>A rs121918398 CGAGCCCCTGGTGGAAGACATG A 21

CAGC [A/G] CCAGTGGGCCGGG

CTGGTGGAGAAG

C.388T>C NM 000041 NM_000041.2:c.388T>C rs429358 GGCTGGGCGCGGACATGGAGGA C 22

.2 CGTG [C/T] GCGGCCGCCTGGT

GCAGTACCGCGG

g.1744C>T AF388026 NG_008833.1 :g.4884C>T rs1800787 TAATAGTTGTATGACAAGTAAA T 23

TAAG [C/T] TTTGCTGGGAAGA

TGTTGCTTAAAT

g.285748G>A AY332722 NG 009492.1 :g.290465G> rs2229765 GTGAACGAGGCCGCAAGCATGC A 24

A GTGA [A/G] AGGATTGAGTTTC

TCAACGAAGCTT

g.31 14G>T AF372214 NG_011640.1 :g.6484G>T rs2066992 CCTGGCTGTGGTTGAACAATGA G 25

AAAG [G/T] CCCTCTAGTGGTG

TTTGTTTTAGGG

g.78787630G NT 005612. NT 005612.16:g.78787630 rs2286983 ACATGGGCACATTATGGTACAG A 26 >A 16 G>A TTT [C/T ] CAACGATGTCCCC

CGTAGTCATTCC

g.9939206T> NT 010194. NT 010194.17:g.9939206T rs2624265 ATGAGCGCATTTTAAGAACCCC C 27 C 17 >C ATT A [ C / T ] AGAGAIAAGAGAA

CTTTTTGAGATA

C.-125- NM 006250 NM_176890.2:c.608G>A rs1376251 GGAGCTGCATCTTCTTGAGATG G 28 12532G>A .2 TTT [C/T ] C GAGAACAGAT

TAGCATCAGAAA

.1323T>C NM 001127 NM 001 127491.1:c.1323T> rs235326 TTCACGGACATAGTGACCGTGC T 29

491.1 C AGGT [C/T] CTTCCCCAGTGTG

AGTGCCGGTGCC

g.26689A>G AY324609 NG_009060.1 :g.29435A>G rs 1569372 CAGAGGGAATGGAGGGAGCAGG G 30

AAGG [ /G] GCTTCAGGAACTG

GTTAGTGGGCTG

g.2673C>G AY324609 NG_009060.1 :g.5419C>G rs 17242766 GGGGGCGCTGAGGGGAGCGCGA G 31

GGGT [C/G] GGGAGGAGTCTGA

GGGATTTAAGGG

.89- NM 000236 NM 000236.2x.89- rs8028759 GAAGGAAATAAACAAATGCAAG C 32

18333C>T .2 18333C>T GGTG [C/T] GTAGAAAGAGCAT

TAGATGGTAGGT

.596C>G NM 000237 NM_000237.2:c.596C>G rs118204072 GTATGCAGAAGCCCCGAGTCGT G 33

.2 CTTT [C/G] TCCTGATGATGCA

GATTTTGTAGAC

.3632- NM 198551 NM 198551.2 .3632- rs 17465637 AACCATAATAGTTATGCTGAGA A 34 105A>C .2 105A>C AGTT [A/C] TTTTTTGTCATAG

TGCAAGATAACA g.5996G>C AY829011 NG_009061.1 :g.8994G>C rs 10888896 GGCCTTTGGGCAGGGCCACCAG c 35

GAGC [C/G] ACCAGGCCCGTAG

AGAGCTGGGTGC

g.13869T>C AY829011 NG_009061.1 :g .16866T>C rs28362239 AGCAGCAACCTGCCTGAAGTCT c 36

TCCT [C/T] TGGCCTGGCTGAG

AGTTTCTGAGAC

Table 1. A list of SNPs that may be used to diagnose FH and/or predisposition to FH in an individual of Asian descent. The method comprises detecting the presence of at least one SNP in the genes as described in a sample of the individual. In the genetic context, a large array of mutations in LDLR gene (OMIM 606945), commonly caused by loss-of-function mutations, results in the lack of functional receptors for Low- density lipoprotein cholesterol (LDLC) on the liver cell surface, giving rise to increased plasma LDL levels. The plasma levels of LDLC in FH heterozygotes are lower and much more dependent on other genetic and environmental factors than are those in FH homozygotes. Irrespective of diet, medications, or lifestyle, the plasma levels of LDLC are consistently very high in FH homozygotes.

Mutations in APOB gene (OMIM 107730), the primary apolipoprotein essential for LDL formation, also reduces LDLC clearance. Mutations in PCSK9 (OMIM 607786) indirectly regulates the degradation of LDLR, and the loss-of-function mutations in PCSK9 results in low plasma LDL levels. It is thus advantageous to use these genes as genetic markers for the detection of FH in individuals.

In particular, the LDLR gene is located on chromosome 19p13.1— 13.3 which spans 45 kb and comprises of 18 exons and 17 introns encoding a mature protein of 839 amino acids. This gene is made up of six functional domains. The mature receptor can be divided into five regions: N-terminal ligand binding domain, epidermal growth factor (EGF) precursorlike domain, O-linked polysaccharide domain, membrane-spanning domain and the C- terminal cytoplasmic domain. LDLR is transported to the cell membrane via a clathrin- coated pit vesicle. On the membrane, the ligand-binding domain is exposed extracellularly to associate with and internalize LDL or very low density lipoprotein (VLDL), mediated by APOB or APOE, respectively. Once inside the cell, LDLR-ligand-containing vesicles are acidified by proton pumps, leading to uncoupling of the receptor-ligand complex. At this point, the LDLC or VLDL-chofesterol undergoes further processing to be readily available for the cell's requirements. Internalized receptor-ligand complex will be degraded in acidic compartment of lysosome, while LDLR will be recycled back to the cell surface to bind with other LDLC molecules. However, LDLR may get degraded together inside a lysosome depending on cellular homeostasis needs.

Mutations such as nucleotide substitutions, deletions and insertions, as well as rearrangements in the LDLR gene may cause FH. These mutations may thus be categorized as defects in synthesis, transport, binding, internalisation, recycling and the like according to their phenotypic effects on the LDLR protein. Detection of these mutations in LDLR may thus be useful in the detection of FH. To date, over 1100 variants have been identified in the LDLR gene as reported by British Heart Foundation (BHF). With the exception of a small number of founder populations where one or two mutations predominate, most geographically based surveys of FH subjects showed a large number of mutations segregating in a given population. Genetic differences among the various racial and ethnic groups usually show the differences in the distribution of polymorphic traits which occur at different frequencies in different populations between and within the racial groups. However, such differences may be prevalent outside of genetics as well. These varying distributions of polymorphisms in genes among the racial and ethnic groups, especially receptors and/or enzymes may affect an individual's predisposition to a disease and/or reaction to a drug against the disease. Similarly, different polymorphisms in LDLR exist in different racial and ethnic groups. Specific polymorphisms in LDLR in the Asian population may be used in the detection of FH and/or the predisposition to FH. In particular, these polymorphisms may be SNPs. More in particular, out of these hundreds of SNPs known in the art only 36 may be related to detection of FH and/or the predisposition to FH in the Asian population.

More in particular,. the SNP may be selected from the group consisting of:

g.183884 T>A (reference sequence AY910577), g.12292096 A>T (reference sequence NT_024524.14), c.736C>T (reference sequence AF261279), c.237-55462 T>C (reference sequence NMJ99051.1), c.122 A>T (reference sequence NM_005308.2), g.22073404 C>T (reference sequence NT_008413.18), c.384-100 G>A (reference sequence NM_207005.1 ), c.^*187 C>T (reference sequence NM_207005.1 ), g.3534 G>A (reference sequence AY593992), g.1928 T>C (reference sequence AY593992),c.148 C>T (reference sequence NM_022436.2), c.101 G>T (reference sequence NM_000039), c.478 G>A (reference sequence NM_000039), c.664 G>A (reference sequence NM_000039), c.913 C>T (reference sequence NM_000482), g.32818 G>A (reference sequence AY324608), g.30761 G>A (reference sequence AY324608), g.16366 C>T (reference sequence AY324608), C.508 G>C (reference sequence AF261279), c.805 C>G (reference sequence AF261279), c.875 G>A (reference sequence AF261279), c.388 T>C (reference sequence NM_000041.2), g.1744 C>T (reference sequence AF388026), g.285748 G>A (reference sequence AY332722), g.31 14 G>T (reference sequence AF372214), g.78787630 G>A (reference sequence NT_005612.16), g.9939206 T>C (reference sequence NT_010194.17), c-125-12532 G>A (reference sequence NM_ 006250.2), c.1323 T>C (reference sequence NM_001127491.1), g.26689 A>G (reference sequence AY324609), g.2673 C>G (reference sequence AY324609), c.89-18333 C>T (reference sequence NM_000236.2), c.596 C>G (reference sequence NM_000237), c.3632-105 A>C (reference sequence NM_198551.2), g.5996 G>C (reference sequence AY829011 ), and g.13869 T>C (reference sequence AY829011). Even more in particular, the SNPs may be selected from the SNPs listed in Table 1.

According to any aspect of the present invention, the method for diagnosing FH and/or predisposition to FH in an individual of Asian descent comprising, consisting of or consisting essentially of detecting the presence of at least one SNP in any one of the genes disclosed. More in particular, the method involves the detection of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, and 36 SNPs in any one of the genes according to any aspect of the present invention. More in particular, the method according to any aspect of the present invention may involve the detection of at least one SNP in at least one gene which may increase the risk of FH in an individual. The risk SNP may be selected from the group consisting of g.1 183884 T>A (reference sequence AY910577), g.12292096 A>T(reference sequence NT_024524.14), c.736C>T(reference sequence AF261279), c.237-55462 T>C(reference sequence NM_ 99051.1), c.122 A>T(reference sequence NM_005308.2), g.22073404 C>T(reference sequence NT_008413.18), c.384-100 G>A(reference sequence NM_207005.1 ), c.^*187 C>T(reference sequence NM_207005.1), g.3534 G>A(reference sequence AY593992), g.1928 T>C(reference sequence AY593992) and the like in a sample of the individual. In particular, the method may involve the detection of 1 , 2, 3, 4, 5, 6, 7, 8, 9, or 10 of the risk SNPs in any one of the genes according to any aspect of the present invention. Even more in particular, the risk SNP may be selected from the group consisting of the SNPs corresponding to SEQ ID NOs. 1 -10 in Table 1.

According to another aspect, there is provided at least one method for diagnosing FH and/or determining tolerance to FH in an individual of Asian descent, the method comprising detecting the presence of at least one SNP in at least one gene which may be protective against FH in an individual. The protective SNP may be selected from the group consisting of c.148 C>T (reference sequence NM_022436.2), c.101 G>T (reference sequence NM_000039), c.478 G>A (reference sequence NM_000039), c.664 G>A (reference sequence NM_000039), c.913 C>T (reference sequence NM_000482), g.32818 G>A (reference sequence AY324608), g.30761 G>A (reference sequence AY324608), g.16366 C>T (reference sequence AY324608), c.508 G>C (reference sequence AF261279), C.805 C>G (reference sequence AF261279), c.875 G>A (reference sequence AF261279), c.388 T>C (reference sequence NM_000041.2), g.1744 C>T (reference sequence AF388026), g.285748 G>A (reference sequence AY332722), g.31 14 G>T (reference sequence AF372214), g.78787630 G>A (reference sequence NT_005612.16), g.9939206 T>C (reference sequence NT_010194.17), c-125-12532 G>A (reference sequence NM_006250.2), c.1323 T>C (reference sequence NM_ 001127491.1), g.26689 A>G (reference sequence AY324609), g.2673 C>G (reference sequence AY324609), c.89- 18333 C>T (reference sequence NM_000236.2), c.596 C>G (reference sequence NM_000237), c.3632-105 A>C (reference sequence NMJ98551.2), g.5996 G>C (reference sequence AY829011), g.13869 T>C (reference sequence AY829011 ) and the like in a sample of the individual. In particular, the method may involve the detection of 1 , 2, 3, 4 5, 6, 7, 8, 9, 10, 1 1 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, or 26 of the protective SNPs in any one of the genes according to any aspect of the present invention.

More in particular, the protective SNP may be selected from the group consisting of SNPs corresponding to SEQ ID Nos. 11-36 in Table 1._The SNP may be determined by a microarray analysis. This is advantageous as it is efficient and more accurate than the methods known in the art.

The method according to any aspect of the present invention may further comprise a step of correlating results of the detection of SNPs with one or more clinicopathological data to implement a particular treatment plan for the individual. In particular, the clinicopathological data may be selected from the group consisting of the individual's age, lifestyle, previous personal and/or familial history of FH, previous personal and/or familial history of response to medications, any genetic or biochemical predisposition to FH and the like.

According to another aspect, there is provided a microarray and/or DNA chip comprising, consisting of or consisting essentially of at least one probe capable of hybridizing to at least one SNP of any one of the genes according to any aspect of the present invention in a sample nucleic acid of an individual of Asian descent, wherein the SNP may be in any genes locus selected from the group consisting of: g.183884 T>A (reference sequence AY910577), g.12292096 A>T (reference sequence NT_024524.14), c.736C>T (reference sequence AF261279), c.237-55462 T>C (reference sequence NM_199051.1), c.122 A>T (reference sequence NM_005308.2), g.22073404 C>T (reference sequence NT_008413.18), c.384-100 G>A (reference sequence NM_207005.1), a^* 187 C>T (reference sequence NM_207005.1), g.3534 G>A (reference sequence AY593992), g.1928 T>C (reference sequence AY593992),c.148 C>T (reference sequence NM_022436.2), a 101 G>T (reference sequence NM_000039), c.478 G>A (reference sequence NM_000039), c.664 G>A (reference sequence NM_000039), c.913 C>T (reference sequence NM_000482), g.32818 G>A (reference sequence AY324608), g.30761 G>A (reference sequence AY324608), g.16366 C>T (reference sequence AY324608), C.508 G>C (reference sequence AF261279), c.805 C>G (reference sequence AF261279), c.875 G>A (reference sequence AF261279), c.388 T>C (reference sequence NM_000041.2), g.1744 C>T (reference sequence AF388026), g.285748 G>A (reference sequence AY332722), g.3114 G>T (reference sequence AF372214), g.78787630 G>A (reference sequence NT_005612.16), g.9939206 T>C (reference sequence NT_010194.17), c.-125-12532 G>A (reference sequence NM_006250.2), c.1323 T>C (reference sequence N _001127491.1), g.26689 A>G (reference sequence AY324609), g.2673 C>G (reference sequence AY324609), c.89-18333 C>T (reference sequence NM_000236.2), c.596 C>G (reference sequence NM_000237), c.3632-105 A>C (reference sequence NM_198551.2), g.5996 G>C (reference sequence AY829011 ), g.13869 T>C (reference sequence AY829011) and the like. More in particular, the SNP may be any SNPs selected from Table 1.

The probe capable of hybridizing to at least one SNP of any one of the genes according to any aspect of the present invention in a sample nucleic acid of an individual of Asian descent may be designed using any one of SEQ ID Nos. 37-72 in Table 2.

SNP Reference HGVS nomenclature rs number Sequence used for designing SEQ ID

Sequence probes against SNP NO. g.183884T>A AY910577 NG_011513.1 :g.186947T>A rs2032582 GCACTGAAAGATAAGAAAGAACTAGAAG 37 GT [A/T] CTGGGAAGGTGAGTCAAACTA

AATATGATT

g.12292096A NT_024524.14 NT 024524.14:g.12292096 rs 10507391 TGTATGTCCAAGCCTCTCTTTGCAATTC 38 >T A>T TA [A/T] TTAACCTCAATGTTGCAACCA

TAGACCTAC

C736C>T AF261279 NM000041.2:c.736C>T rs121918395 ATGGAGGAGATGGGCAGCCGGACCCGCG 39

AC [T/C] GCCTGGACGAGGTGAAGGAGC AGGTGGCGG

.237- NM_199051 NM 199051.1 :c.237- rs1171381 TGGAAAACACTACTCAGTTTCCATCCGT 40 55462T>C 55462T>C TT [T/C] TTTTCTGGGAGTAGGAGTGGG

GTACATAGA

.122A>T N JJ05308.2 N _005308.2:c.122A>T rs2230345 AAGAAATCCTGAAGTTCCCTCACATTAG 41

CC [A/T] GTGTGAAGACCTCCGAAGGAC CATAGGTAA

g.22073404C NT_008413.18 NT 008413.18:g.22073404 rs1333040 AGAGAGACAGGAGGGTCAGAGGTAAGAA 42 >T C>T TG [T/C] TACCGCTGGGACAGAGAGGAA

GGTACAGAT

C.384- N _207005 NM 207005.1 :c.384- rs2073658 GGTGTGAGACACCACACCTAGCTACCAT 43 100G>A 100G>A AA [A/G] GGTCCTAATACCTGCTAAAT

CTTGTATAA

.'187C>T NM_207005.1 NM_207005.1 :c.*187C>T rs3737787 CCTGCAGTGGTGTGAAACACACAATGTG 44

GA [ T/C] GTGCACTGACAGCCTTGCCCA CCCCCACCA

g.3534G>A AY593992 NG_011612.1 :g.7637G>A rs2516839 GGACTTAGCACTCAGGCCTGTGAATCAG 45

G [ /G] ATACAAAGACCTCCAAAAAAG GACCAGTTC

g,1928T>C AY593992 NG_01 1612.1 :g.6031T>C rs2516837 CTCGGACGCGGTCTTTCCGAGGCTTATC 46

CA [ T/C] TGAAAATTTTCCTTGGATAGG AAAGGTTTG

.148C>T NM_022436.2 NM_022436.2:c.148C>T rs6756629 AAGATGTGATGTCCCACCAGGGCCTCAC 47

GC [A/G] GTGGCTTTAAAGGAAACCCCA GGAAGGCAA

.101G>T NM_000039.1 rs28929476 AAGATGAACCCCCCCAGAGCCCCTGGGA 48

NM_000039.1 :c.101G>T TC [ T/ G] AGTGAAGGACCTGGCCACTGT

GTACGTGGA

.478G>A NM_000039.1 CTCCAAGAGGGCGCGCGCCAGAAGCTGC 49

NM_000039.1 :c.478G>A AC [A/G] AGCTGCAAGAGAAGCTGAGCC

CACTGGGCG

C.664G>A NM_000039.1 rs121912717 AGACTGGCCGAGTACCACGCCAAGGCCA 50

NM_000039.1 :c.664G>A CC [A/G] GCATCTGAGCACGCTCAGCG

AGAAGGCCA

C913C>T N _000482.3 NM_000482.3:c.913C>T rs150264487 CACCTGGACCAGCAGGTGGAGGAGTTCC 51

GA [T/C] GCCGGGTGGAGCCCTACGC-GG AAAACTTCA

g.32818G>A AY324608 NG_01 1793.1.g.35861G>A rs 13306187 CCAGCACAGACCATTTCAGCCTTCGGGC 52

TC [A/G] TTACCACATGAAGGCTGACTC TGTGGTTGA

g.30761G>A AY324608 NG_011793.1 :g.33804G>A rs 12720770 GAACTAGTACCATTCACAACTATTTCCT 53

AC [A/G] TATTTTCAGATGAAGAGAAGA TTGAATTTG

g.16366C>T AY324608 NG_01 1793.1 :g.19412C>T rs 13306194 ATGATCCAGAAAGCTGCCATCCAGGCTC 54

TG [ T/C ] GGAAAATGGAGCCTAAAGACA AGGTAAAGT

.508G>C AF261279 NM_000041.2:c.508G>C N/A CGCAAGCTGCGTAAGCGGCTCCTCCGCG 55

AT f C/G] CCGATGACCTGCAGAAGCGCC TGGCAGTGT

.805C>G AF261279 NM_000041.2:c.805C>G N/A GCCAAGCTGGAGGAGCAGGCCCAGCAGA 56

TA [C/G] GCCTGCAGGCCGAGGCCTTCC AGGCCCGCC

C.875G>A AF261279 NM_000041.2:c.875G>A rs121918398 GGTTCGAGCCCCTGGTGGAAGACATGCA 57

GC [A/G] CCAGTGGGCCGGGCTGGTGGA GAAGGTGCA

.388T>C NM_000041.2 NM_ 000041.2:c.388T>C rs429358 GCCCGGCTGGGCGCGGACATGGAGGACG 58

TG [ T/C] GCGGCCGCCTGGTGCAGTACC GCGGCGAGG

g.1744C>T AF388026 NG_008833.1 :g.4884C>T rs1800787 AGAATAATAGTTGTATGAC AGTAAATA 59

AG [ T/C ] TTGCTGGGAAGATGTTGCTT AAATGATAA

g.285748G>A AY332722 NG 009492.1 :g.290465G> rs2229765 AACAGTGAACGAGGCCGCAAGCATGCGT 60

A GA [ A/G] AGGATTGAGTTTCTCAACGAA

GCTTCTGTG g.3114G>T AF372214 NG_01 1640.1 :g.6484G>T rs2066992 TTTCCTGGCTGTGGTTGAACAATGAAAA 61

G [T/G] CCCTCTAGTGGTGTTTGTTTTA GGGACACT

g.78787630G NT_005612.16 NT 005612.16:g.78787630 rs2286983 CCCCACATGGGCACATTATGGTACAGTT 62 >A G>A TT [ T/C ] CAACGATGTCCCCCGTAGTCA

TTCCTAGGG

g.9939206T> NT_0I0194.17 NT 010194.17:g.9939206T rs2624265 ATCTATGAGCGCATTTTAAGAACCCCAT 63 C >C TA [T/C ] AGAGATAAGAGAACTTTTTGA

GATAGCCGG

.-125- NM_006250.2 NM_176890.2:c.608G>A rs1376251 CCATGGAGCTGCATCTTCTTGAGATGTT 64 12532G>A TA [ T / C ] AC AGAGAACAGATT AGC ATCA

GAAAAGATA

.1323T>C NM 001127491. NM 001127491.1 :c.1323T> rs235326 GGGCTTCACGGACATAGTGACCGTGCAG 65

1 C GT (T/C ] CTTCCCCAGTGTGAGTGCCGG

TGCCGGGAC

g.26689A>G AY324609 NG_009060.1 :g.29435A>G rs1569372 GCTGCAGAGGGAATGGAGGGAGCAGGAA 66

GG [A/G] GCTTCAGGAACTGGTTAGTGG GCTGGGCAT

g.2673C>G AY324609 NG_009060.1 :g.5419C>G rs17242766 GGAGGGGGGCGCTGAGGGGAGCGCGAGG 67

GT [C/G] GGGAGGAGTCTGAGGGATTTA AGGGAAACG

.89- NMJJ00236.2 NM 000236.2x.89- rs8028759 GTCAGAAGGAAATAAACAAATGCAAGGG 68

18333C>T 18333C>T TG [ T/C] GTAGAAAGAGCATTAGATGGT

AGGTCCAGA

.596C>G NM_000237.2 NM_000237.2:c.596C>G rs 118204072 TTGAGTATGCAGAAGCCCCGAGTCGTCT 69

TT [C/G] TCCTGATGATGCAGATTTTGT AGACGTCTT

C.3632- NM_198551.2 NM 198551.2:0.3632- rs17465637 TTAAAACCATAATAGTTATGCTGAGAAG 70 105A C 105A>C TT [A/C] TTTTTGTCATAGTGCAAGAT

AACATGTCT

g.5996G>C AY82901 1 NG_009061.1 :g.8994G>C rs10888896 GGGTGGCCTTTGGGCAGGGCCACCAGGA 71

GC [C/G] ACCAGGCCCGTAGAGAGCTGG GTGCAGGTA

g.13869T>C AY82901 1 NG_009061.1 :g.16866T>C rs28362239 TGCTAGCAGCAACCTGCCTGAAGTCTTC 72

C [T/C ] TGGCCTGGCTGAGAGTTTCTG AGACCTGCG

Table 2. A list of sequences which may be used to design probes for detection of SNPs of any one of the genes according to any aspect of the present invention.

According to a further aspect, there is provided a kit for determining whether an individual has an increased risk for FH, the kit comprising:

(a) at least one oligonucleotide that can identify an. FH-associated SNP in in any one of the genes according to any aspect of the present invention wherein the SNP may be selected from the group consisting of: g.183884 T>A (reference sequence AY910577), g.12292096 A>T (reference sequence NT_024524.14), c.736C>T (reference sequence AF261279), c.237- 55462 T>C (reference sequence NM_199051.1 ), c.122 A>T (reference sequence NM_005308.2), g.22073404 C>T (reference sequence NT_ 008413.18), c.384-100 G>A (reference sequence NM_207005.1 ), c.^*187 C>T (reference sequence NM_207005.1 ), g.3534 G>A (reference sequence AY593992), g. 928 T>C (reference sequence AY593992),c.148 C>T (reference sequence NM_022436.2), c.101 G>T (reference sequence NM_000039), c.478 G>A (reference sequence NM_000039), c.664 G>A (reference sequence NM_000039), c.913 C>T (reference sequence NM_000482), g.32818 G>A (reference sequence AY324608), g.30761 G>A (reference sequence AY324608), g.16366 C>T (reference sequence AY324608), C.508 G>C (reference sequence AF261279), c.805 C>G (reference sequence AF261279), c.875 G>A (reference sequence AF261279), c.388 T>C (reference sequence NM_000041.2), g.1744 C>T (reference sequence AF388026), g.285748 G>A (reference sequence AY332722), g.3114 G>T (reference sequence AF372214), g.78787630 G>A (reference sequence NT_005612.16), g.9939206 T>C (reference sequence NT_010194.17), c-125-12532 G>A (reference sequence NM_006250.2), c.1323 T>C (reference sequence NM_001127491.1 ), g.26689 A>G (reference sequence AY324609), g.2673 C>G (reference sequence AY324609), c.89-18333 C>T (reference sequence NM_000236.2), c.596 C>G (reference sequence NM_000237), c.3632-105 A>C (reference sequence NM_198551.2), g.5996 G>C (reference sequence AY829011), g.13869 T>C (reference sequence AY829011) and the like; and

(b) instructions for use.

More in particular, the SNP may be selected from the SNPs listed in Table 1

Having now generally described the invention, the same will be more readily understood through reference to the following examples which are provided by way of illustration, and are not intended to be limiting of the present invention.

A person skilled in the art will appreciate that the present invention may be practised without undue experimentation according to the method given herein. The methods, techniques and chemicals are as described in the references given or from protocols in standard biotechnology and molecular biology text books.

EXAMPLES

Standard molecular biology techniques known in the art and not specifically described were generally followed as described in Sambrook and Russel, Molecular Cloning: A Laboratory Manual, Cold Springs Harbor Laboratory, New York (2001). EXAMPLE 1

Study population and data collection

The study included 150 clinically diagnosed FH and 150 control subjects recruited between January 2007 and September 2009 from the out-patient clinic at the University Malaya Medical Centre (UMMC) of Kuala Lumpur. A total of 164 (55%) females and 136 (45%) males, were recruited from a cross-sectional, genetically unrelated population of Malaysia representing the Malay (63%), Chinese (15%) and Indian (22%) ethnicity. The FH-DLCN (Austin, 1993 and Betteridge, 2000) was adopted as the diagnostic scoring method to determine whether the subjects were possible FH, probable FH or definite FH. DLCN was used based on the distinguishable clear-cut point lay-out that covers all possible clinical and molecular aspects.

Semi-structured questionnaires were used to collect the demography, clinical data and family history of participants.

All subjects undertook a screening protocol consisting of clinical history, physical examination and laboratory tests including fasting glucose (FG), fasting serum lipids (FSL), renal profile (RP), liver function tests (LFT) and thyroid function tests (TFT). Blood samples were analyzed for the above tests using standard techniques. This study complied with the declaration of Helsinki and the protocol was approved by the UMMC's ethics committee (Ref: 546.16: Detection of FH (LDLR AND APOB) mutations amongst Malaysian population) and written informed consent was obtained from all participants before their inclusion in the register.

DNA isolation and normalization

Whole blood was collected from overnight fasting subjects in EDTA-anticoagulated tubes. Genomic DNA from all subjects was isolated from either whole blood or buccal cells using QIAamp DNA Mini Kit (QIAGEN) in 200 μΙ of total volume according to manufacturer's protocol. Qualitative and quantitative estimations were carried out on the DNA samples. All DNA samples were normalized to 50ng/ l. Selection of genes and SNPs

Following literature review, polymorphisms previously implicated in FH with the following attributes were selected: i) SNPs in the LDLR gene; and ii) SNPs that were known to have functional effects on in vitro assays or were non-synonymous or in regulatory regions. In LDLR, 75% of these SNPs were located in exons with 15% resulting in stop codons while 25% were in the non-coding region. Three publically available databases: BHF (www.ucl.ac.uk), dbSNP (ncbi.nlm.nih.gov/SNP/) and SNPedia (www.snpedia.com) were referred to for the design of the custom probes.

Microarray design, fabrication and quality controls

For the genotyping of polymorphic alleles, 1 ,536-custom probes (FH-Oligonucleotide Pool All) were synthesized by lllumina^®. The probes were selected based on their importance of reporting as well as significant odds ratios (OR). These probes were divided into four different series to ease reference during data analysis. The four series are provided below.

I) The IVFH-0001 series

There were a total of 829 mutation selected for this series. The mutations reported in the BHF's LDLR database were captured for the LDLR and PCSK9 gene while mutations in APOB were extracted from those reported in literatures. The mutations range from reduction of activity to gain of function to truncated proteins or just silent mutations. The basis of selecting these mutations were to compare if there were also such unique ones found in the Asian population especially in the three main ethnicities of Malaysia i.e., Malays, Chinese and Indians. Other reported mutations from another eight genes that involved in the lipoprotein pathway were also included in this series.

II) IVSFH-1000 series

SNPs in this series were selected entirely and randomly from the three known FH causing genes (LDLR, APOB and PCSK9) from the dbSNP database. These 545 SNPs may or may not have any effect on the function on these genes. The rational of selecting these SNPs was solely on the purpose of identifying the possibility that a portion or a region of any one of these genes may be truncated or deleted and then these SNPs will fail and the microarray scanner may not pick the signal. This series was selected as an in house micro- sequencing procedure and is also at times called the deletion-database. III) IVSFH-3000 series

A total of 144 SNPs which were reported to have significant odds ratio (OR) from SNPedia were selected for this series. The SNPs of this series were also reported to have association with cholesterol related diseases such as coronary vascular disease, myocardial infarction, ischemic heart disease and stroke as well as altered levels of cholesterol. SNPs in this series have been gathered from a wide range of genes.

Array Design Tool (ADT)

Probes of the SNPs were sent to lllumina's ADT for scoring, lllumina ranked SNPs are based on an in-built algorithm in the ADT page where SNPs scoring below 0.4 were given a designability rank of zero thus the probe was not designable by lllumina. A score between 0.4 to 0.6 gave a designability rank of 0.5 while a score above 0.6 was given a designability rank of 1 and both these ranks could be successfully designed as probes (Oligo Pool All, OPA) by lllumina. Probes were submitted to ADT in the Sequence List format.

A total of 1536 SNPs were successfully picked from an initial list containing approximately 1680 SNPs.

Genotyping

Genotyping was performed using the lllumina GGGT Microarray Assay, which was capable of multiplexing up to 1 ,536 SNPs in a single reaction. All assays were performed on 32- array Universal BeadChips according to the manufacturer's protocol and were carried out in compliance with MIAME guidelines (Brazma A., 2001 ).

GGGT assay

The lllumina GoldenGate Assay queried genomic DNA with three oligonucleotide probes for each locus and creates DNA fragments that could be amplified by standard PCR methods using universal primers. For each of the 1536 loci interrogated in each assay, the oligo mix contained 2 allele specific and one locus specific probe (i.e. 3 x 1536 oligos). The 3' ends of the two alternative allele specific probes were complementary to two universal primers, U1 and U2, with the 5' end complementary to the 3' end of the locus. Each probe sequence terminated at the SNP that is to be assayed with an allele specific base. The third probe, the locus specific probe, was complementary to the genomic DNA that started 5 to 20 bases 3' of the locus in question. As well as a locus specific sequence, this probe also contained a specific lllumicode sequence that was used to identify the locus (on the BeadArray) as well as the sequence for universal primer sequence U3. All 1536 probes was annealed to the genomic DNA at the same time, DNA polymerase was added to close the gap between the allele specific (including either U1 OR U2) and the locus specific (including U3) probes and the paired fragments were ligated together. The probe fragments were then separated from the genomic DNA and used to inoculate a PCR reaction. The primer mix for this PCR reaction comprised primers U1 and U2 labeled with Cy3 and Cy5 respectively and biotinylated primer U3.

Any specific GoldenGate assay required a particular pool of oligonucleotides corresponding to the allele and locus specific probes for the loci that will be interrogated. Any given oligo pool could interrogate up to 1536 different SNP loci. Multiple oligo pools could be run on sample sets to increase the number of loci queried. Oligo pools were shipped with their own information file designating which lllumicode was used to interrogate each locus as well as which allele was labeled with Cy3 and which with Cy5. icroarray scanning and quantification

Bead Array reader scanned the hybridized chip and determined the signal intensities for each dye at each bead location. Custom software, the Bead studio or the Genome Studio from lllumina used the information filed from the Bead Chip and the oligo pool to map the known location of each allele on the Chip back to the locus being interrogated by that code and to match the dye intensities to the specific alleles.

The dye intensities were examined by the software to determine the genotype of each sample for that locus. A locus predominantly returning a signal from Cy3 was AA, Cy5 was BB and an even ratio represents a heterozygous individual. Data was returned with the allele call for each locus as well as a something called a Gentrain score, a measure that represents the reliability of that genotyping call. Each locus was examined independently to make sure that the assigned genotypes were robust. Although, it was found that loci with high Gentrain scores usually require no manual intervention. Data analysis

All the raw intensity data from the custom GGGT microarray assays were fed to the lllumina GenomeStudioTM to decipher the true allele calls. Overall genotype call rate was 70 % and above with allelic data successfully generated for 84% of the SNP loci (1 ,292 out of 1 ,536). All genotyped SNPs were assessed for deviation from Hardy-Weinberg equilibrium using GenomeStudioTM. Subsequent statistical analyses were carried out using ST ATA version 10.0 (Stata Corp., Texas). JLIN software was used for linkage disequilibrium analysis. A level of p < 0.05 was accepted as statistically significant and 0.05 ≤ p < 0.10 was considered as marginally significant. For each SNP, the OR was calculated according to dominant and recessive models for the association between the genotypes and risk of FH. Chi-squared test was performed to test the statistical significance of the association (degree of freedom = 1). Woolf approximation was used to calculate standard error and 95% confidence interval of the OR. For statistically significant SNPs, multivariate logistic regression was performed to adjust for gender and age. Results

The characteristics of the study subjects were detailed in Table 3 above. The mean age was 41.7 ± 9.15 and 46.7 ± 11.14 years for controls and FH cases respectively. The diversity of Malaysia's population was also reflected in the ethnic composition of the study subjects. 81 1 potential FH-associated SNPs from LDLR gene were examined. Following microarray analysis, 448 SNPs with low call rate (<100 calls) and SNPs that were devoid of minor alleles were removed. By setting the predominant genotype of each of the remaining 363 SNPs as the reference, the OR for each variant genotype was calculated according to both recessive and dominant models as previously described (Suarez A., et al., 2007). In total, the association of 36 SNPs along the coding and non-coding regions of LDLR with FH were statistically significant (Table 3). The genotype frequencies of all of these SNPs did not deviate from Hardy-Weinberg equilibrium (P > 0.05), with exception for 2 SNPs all other showed a p of 0.5. Among them, 10 SNPs were associated with increased risk of FH (Table 4), while the remaining 26 SNPs conferred reduced risk of FH development (Tables 3)

The LDLR gene contains 18 exons. Exon 1 encodes a cell membrane localization signal peptide. Exons 2 to 6 encode the ligand binding domain. Exons 7 to 14 encode the EGF precursor-like domain. Exon 15 codes for the oligosaccharide-rich domain. Exon 16 and exon 17 code for the transmembrane domain. Exon 18 codes for the cytoplasmic domain. The 33 risk-associated or protective SNPs identified in this study were distributed throughout LDLR gene, in transcriptional promoter, coding (exonic), as well as noncoding (intronic) regions. The largest concentrations of SNPs were found in the coding regions of ligand binding domain (11 SNPs) and EGF precursor-like domain (15 SNPs).

Infovalley Gene Chromosome Reference Region Allele Genomic ID sequence position

IVSFH- LDLR 19 AY324609 Intron 16 G>A 4231 1 1023

(NG_009060.1 )

IVSFH- LDLR 19 AY324609 Intron 17 G>A 43979 164

(NG_009060.1 )

IVSFH- LDLR 19 AY324609 Intron 17 G>A 44009

1 163

(NG_009060.1 )

IVSFH- LDLR 19 AY324609 Intron 17 A>G 44114 1278

(NG_009060.1 )

IVSFH- LDLR 19 AY324609 3' UTR G>A 44243 1048

(NG_009060.1 )

IVSFH- LDLR 19 AY324609 3' UTR G>A 44332 1238

(NG_009060.1 ) IVSFH- LDLR 19 AY324609 3' UTR C>G 44506

1210

(NG_009060.1)

Table 3: Diagnostic SNPs The presence of any one of these SNPs indicates the definite diagnosis of FH (Position: 42311 G>A, 43979 G>A, 44009 G>A, 44114 A>G, 44243 G>A, 44332 G>A, 44506 C>G Ref. Seq. : LDLR (AY324609))

Reference

INFOVALLEY ID Polymorphism Risk Genotypes Odds Ratio 95% CI R alue

Genotypes

IVPFH-2011 g.l83884T>A TT ΑΤ,ΑΑ 2.444 1.145-5.496 0.0127

IVSFH-3009 g.l2292096A>T AA ΤΤ,ΤΑ 2.223 1.234-4.017 0.0042

IVFH-0806 c.736C>T AA GG,AG 5.914 2.785-13.186 <0.0001

IVSFH-3122 c.237-55462T>C AG.GG AA 1.971 0.906-4.499 0.0657

IVSFH-3145 .122A>T π ΑΤ,ΑΑ 2.622 1.018-7.577 0.0298

IVSFH-3022 g.22073404C>T AA AG.GG 1.652 0.969-2.818 0.0496

IVSFH-3047 c.384-100G>A GG.AG AA 7.557 1.014-334.136 0.0262

IVSFH-3083 c.*187C>T GG AG.AA 1.815 0.995-3.348 0.0380

IV5FH-3144 g.3534G>A GG.AG AA 2.373 1.103-5.365 0.0168

IVSFH-3205 g.l928T>C AA.AG GG 2.134 0.989-4.839 0.0377

Table 4: List o f significant risk SN ³s on the LDLR gene

INFOVALLEY Polymorphism Reference Risk/Prote Odds Ratio 95% CI P value ID Genotypes ctive

Genotypes

IVSFH-3101 .148C>T GG AG,AA 0.325 0.053-1.474 0.0939

IVFH-0812 c.lOlGvT CC AC.AA 0.438 0.215-0.887 0.0123

IVFH-0819 .478G>A GG AG.AA 0.160 0 .038-0.516 0.0004

IVFH-0824 c.664G>A GG AG.AA 0.137 0.065-0.277 <0.0001

IVFH-0835 c.913C>T GG AG.AA 0.324 0.156-0.657 0.0006

IVSFH-1368 g.32818G>A GG AG.AA 0.139 0.0611-0.300 <0.0001

IV5FH-1379 g.30761G>A GG AG,AA 0.151 0.003-1.388 0.0495

IVSFH-1464 g.l6366C>T GG AG.AA 0.402 0.190-0.831 0.0072

IVFH-0804 c.508G>C GG CG.CC 0.304 .0481-1.481 0.0826

IVFH-0808 c.805C>G CC CG.GG 0.097 0.0424-0.209 <0.0001

IVFH-0809 c.875G>A GG AG.AA 0.101 0.002-0.816 0.0098

IVPFH-2016 c.388T>C AA AG.GG 0.473 0.264-0.847 0.0068

IV5FH-3036 g.l744C>T GG AG.AA 0.347 0.194-0.618 0.0001

IVSFH-3052 g.285748G>A GG AG.AA 0.569 0.333-0.972 0.0281

IVSFH-3044 g.3114G>T AA AC.CC 0.634 0.359-1.115 0.0921

IVSFH-3060 g.78787630G>A GG AG.AA 0.448 0.255-0.781 0.0025

IVSFH-3078 g.9939206T>C AA AG.GG 0.596 0.349-1.016 0.0432

IVSFH-3024 c.-125-12532G>A AA AG.GG 0.524 0.298-0.915 0.0155

IVSFH-3070 .1323T>C GG AG.AA 0.632 0.370-1.077 0.0726

IVSFH-1050 g.26689A>G AA,AG GG 0.538 0.237-1.200 0.0975

IVSFH-1077 g.2673C>G CC CG,GG 0.509 0.231-1.102 0.0611

IVSFH-3H7 .89-183330T AA AG.GG 0.480 0.276-0.831 0.0051

IVFH-0848 .5960G CC CG.GG 0.080 0.034-0.178 <0.0001

IVSFH-3160 c.3632-105A>C CC AC.AA 0.643 0.366-1.123 0.0989

IVSFH-1609 g.5996G>C GG CG.CC 0.477 0.231-0.971 0.0263

IVSFH-1671 g.l3869T>C AA AG,GG 0.170 0.003-1.764 0.0756

Table 5 List of significant protective SNPs on the LDLR gene

The risk associated with a specific genetic variant for the 10 risk-conferring SNPs, was also analyzed by stratification according to ethnicity. Among ethnic Malays, the variant genotypes of 4 SNPs (2288 C>G, 18211 T>C, 24417 T>C, and 24481 T>G) increased the risk of FH with statistical significance. Among ethnic Chinese, the variant genotypes of 3 SNPs (2288 C>G, 24481 T>G, and 33000 C>T) conferred increased risk of developing FH. However, none of the 10 SNPs was associated with the risk of FH among ethnic Indian with statistical significance. Similar ethnic stratification analysis was also conducted for the 26 protective SNPs of LDLR. SNPs were associated with decreased FH risk, with statistical significance, for ethnic Malays, Indians or Chinese respectively. Once again, the ethnic stratification analysis showed that none of the 28 protective SNPs conferred the opposite effect on FH predisposition in any of the three ethnicities.

REFERENCES 1. Austin MA, Hutter CM, Zimmern RL, Humphries SE. Genetic causes of monogenic heterozygous familial hypercholesterolemia: a HuGE prevalence review. Am J Epidemiol. 2004;160:407-20.

2. Betteridge J. Lipids and Vascular Disease. 2000.

3. Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al.

Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet. 2001 ;29:365-71.

4. Khoo KL, van Acker P, Defesche JC, Tan H, van de Kerkhof L, Heijnen-van Eijk SJ, et al. Low-density lipoprotein receptor gene mutations in a Southeast Asian population with familial hypercholesterolemia. Clin Genet. 2000;58:98-105.

5. Risk of fatal coronary heart disease in familial hypercholesterolemia. Scientific Steering Committee on behalf of the Simon Broome Register Group. BMJ. 1991 ;303:893-6.

6. Sambrook and Russel, Molecular Cloning: A Laboratory Manual, Cold Springs

Harbor Laboratory, New York (2001)

7. Suarez E, Sariol CA, Burguete A, McLachlan G. A tutorial in genetic epidemiology and some considerations in statistical modeling. P R Health Sci J. 2007;26:401-21. 8. Williams RR, Hunt SC, Schumacher MC, Hegele RA, Leppert MF, Ludwig EH, et al.

Diagnosing heterozygous familial hypercholesterolemia using new practical criteria validated by molecular genetics. Am J Cardiol. 1993;72:171-6.

Claims

A method for diagnosing Familial Hypercholesterolemia (FH) and/or predisposition to FH in an individual of Asian descent, the method comprising detecting the presence of at least one single nucleotide polymorphism (SNP) in at least one gene associated with lipid metabolism in a sample of the individual.

The method according to claim 1 , wherein the SNP is selected from the group consisting of: an A allele of single nucleotide polymorphism of rs2032582 represented by SEQ ID No. 1 ;

a T allele of single nucleotide polymorphism of rs10507391 represented by SEQ ID No. 2;

a C allele of single nucleotide polymorphism of rs121918395 represented by SEQ ID No. 3;

a T allele of single nucleotide polymorphism of rs1 171381 represented by SEQ ID No. 4;

an A allele of single nucleotide polymorphism of rs2230345 represented by SEQ ID No. 5;

a C allele of single nucleotide polymorphism of rs1333040 represented by SEQ ID No. 6;

an A allele of single nucleotide polymorphism of rs2073658 represented by SEQ ID No. 7;

a T allele of single nucleotide polymorphism of rs3737787 represented by SEQ ID No. 8;

an A allele of single nucleotide polymorphism of rs2516839 represented by SEQ ID No. 9;

a C allele of single nucleotide polymorphism of rs2516837 represented by SEQ ID No. 10;

a T allele of single nucleotide polymorphism of rs6756629 represented by SEQ ID No. 11 ;

a T allele of single nucleotide polymorphism of rs28929476 represented by SEQ ID No. 12;

an A allele of single nucleotide polymorphism of rs121912718 represented by SEQ ID No. 13;

an A allele of single nucleotide polymorphism of rs121912717 represented by SEQ ID No. 14; a T allele of single nucleotide polymorphism of rs150264487 represented by SEQ ID o. 15;

an A allele of single nucleotide polymorphism of rs13306187 represented by SEQ ID No. 16;

an A allele of single nucleotide polymorphism of rs12720770 represented by

SEQ ID No. 17;

a T allele of single nucleotide polymorphism of rs13306194 represented by SEQ ID No. 18;

a C allele of single nucleotide polymorphism SEQ ID No. 19;

a G allele of single nucleotide polymorphism SEQ ID No. 20;

an A allele of single nucleotide polymorphism of rs121918398 represented by SEQ ID No. 21 ;

a C allele of single nucleotide polymorphism of rs429358 represented by SEQ ID No. 22;

a T allele of single nucleotide polymorphism of rs1800787 represented by

SEQ ID No. 23;

an A allele of single nucleotide polymorphism of rs2229765 represented by SEQ ID No. 24;

a G allele of single nucleotide polymorphism of rs2066992 represented by SEQ ID No. 25;

an A allele of single nucleotide polymorphism of rs2286983 represented by SEQ ID No. 26;

a C allele of single nucleotide polymorphism of rs2624265 represented by SEQ ID No. 27;

a G allele of single nucleotide polymorphism of rs 376251 represented by

SEQ ID No. 28;

a T allele of single nucleotide polymorphism of rs235326 represented by SEQ ID No. 29;

a G allele of single nucleotide polymorphism of rs1569372 represented by SEQ ID No. 30;

a G allele of single nucleotide polymorphism of rs17242766 represented by SEQ ID No. 31.

a C allele of single nucleotide polymorphism of rs8028759 represented by SEQ ID No. 32;

a G allele of single nucleotide polymorphism of rs118204072 represented by SEQ ID No. 33; an A allele of single nucleotide polymorphism of rs17465637 represented by SEQ ID No. 34;

a C allele of single nucleotide polymorphism of rs10888896 represented by SEQ ID No. 35;

a C allele of single nucleotide polymorphism of rs28362239 represented by SEQ ID No. 36.

The method according to claim 2, wherein at least 7 SNPs are selected from the group.

The method according to claim 1 , wherein the SNP is found in Low-Density Lipoprotein Receptor (LDLR) gene, Apolipoprotein B (APOB) gene and/or Proprotein Convertase Subtilisin/Kexin type 9 (PCSK9) gene.

A method for diagnosing Familial Hypercholesterolemia (FH) and/or predisposition to FH in an individual of Asian descent, the method comprising detecting the presence of at least one single nucleotide polymorphism (SNP) selected from the group consisting of: an A allele of single nucleotide polymorphism of rs2032582 represented by SEQ ID No. 1 ;

a T allele of single nucleotide polymorphism of rs10507391 represented by SEQ ID No.

2;

a C allele of single nucleotide polymorphism of rs121918395 represented by SEQ ID No.

3;

a T allele of single nucleotide polymorphism of rs1171381 represented by SEQ ID No.

4;

an A allele of single nucleotide polymorphism of rs2230345 represented by SEQ ID No.

5;

a C allele of single nucleotide polymorphism of rs2516837 represented by SEQ ID No. 10.

6. A method for diagnosing Familial Hypercholesterolemia (FH) and/or tolerance to FH in an individual of Asian descent, the method comprising detecting the presence of at least one single nucleotide polymorphism (SNP) selected from the group of consisting of: a T allele of single nucleotide polymorphism of rs6756629 represented by SEQ ID No. 11 ;

an A allele of single nucleotide polymorphism of rs121912717 represented by SEQ ID No. 14;

a T allele of single nucleotide polymorphism of rs150264487 represented by SEQ ID No. 15;

an A allele of single nucleotide polymorphism of rs12720770 represented by SEQ ID No. 17;

a C allele of single nucleotide polymorphism of SEQ ID No. 19;

a G allele of single nucleotide polymorphism of SEQ ID No. 20;

an A allele of single nucleotide polymorphism of rs121918398 represented by SEQ

ID No. 21 ;

a T allele of single nucleotide polymorphism of rs1800787 represented by SEQ ID No. 23;

a C allele of single nucleotide polymorphism of rs2624265 represented by SEQ ID No. 27; an G allele of single nucleotide polymorphism of rs1376251 represented by SEQ ID No. 28;

a G allele of single nucleotide polymorphism of rs1569372 represented by SEQ ID

No. 30;

a G allele of single nucleotide polymorphism of rs118204072 represented by SEQ ID No. 33;

an A allele of single nucleotide polymorphism of rs17465637 represented by SEQ ID No. 34;

a C allele of single nucleotide polymorphism of rs10888896 represented by SEQ ID

No. 35;

a C allele of single nucleotide polymorphism of rs28362239 represented by SEQ ID No. 36;

in a sample of the individual.

7. The method according to any one of the preceding claims, wherein the SNP is determined by a microarray analysis.

8. The method according to any one of the preceding claims, wherein the SNPs are detected by at least one probe designed using at least one sequence selected from the group consisting of SEQ ID Nos. 37-72.

9. The method according to any one of the preceding claims, wherein the sample is selected from the group consisting of blood, sputum, saliva, mucosal scraping and tissue biopsy.

10. The method according to any one of the preceding claims further comprising a step of correlating results of the detection of SNPs with one or more ciinicopathological data to implement a particular treatment plan for the individual.

1 1. The method of claim 9, wherein the ciinicopathological data is selected from the group consisting of the individual's age, lifestyle, previous personal and/or familial history of FH, previous personal and/or familial history of response to medications, and any genetic or biochemical predisposition to FH.

12. A method for diagnosing Familial Hypercholesterolemia (FH) and/or tolerance to FH in an individual of Asian descent, the method comprising detecting the presence of at least 7 single nucleotide polymorphism (SNP) selected from the group of consisting of

a T allele of single nucleotide polymorphism of rs28929476 represented by SEQ ID

No. 12;

an A allele of single nucleotide polymorphism of rs12720770 represented by SEQ

ID No. 17;

a C allele of single nucleotide polymorphism of SEQ ID No. 19;

a G allele of single nucleotide polymorphism of SEQ ID No. 20;

a T allele of single nucleotide polymorphism of rs1800787 represented by SEQ ID

No. 23;

an G allele of single nucleotide polymorphism of rs1376251 represented by SEQ ID

No. 28; a T allele of single nucleotide polymorphism of rs235326 represented by SEQ ID No. 29;

a G allele of single nucleotide polymorphism of rs1 18204072 represented by SEQ ID No. 33;

in a sample of the individual.

13. A microarray for determining FH risk comprising at least one probe capable of hybridizing to at least one SNP in a sample nucleic acid of an individual of Asian descent, wherein the SNP is found in at least one gene associated with lipid metabolism.

14. The microarray according to claim 13 wherein the probe is designed using at least one sequence selected from the group consisting of SEQ ID Nos. 37-72.

15. The microarray according to claim 13, wherein the SNP is found in LDLR gene, APOB gene and/or PCSK9 gene.

16. The microarray according to claim 13, wherein the SNP is selected from the group consisting of: an A allele of single nucleotide polymorphism of rs2032582 represented by SEQ ID No. 1 ;

a T allele of single nucleotide polymorphism of rs1171381 represented by SEQ ID No. 4; an A allele of single nucleotide polymorphism of rs2230345 represented by SEQ ID No. 5;

a C allele of single nucleotide polymorphism of rs 1333040 represented by SEQ ID No. 6;

an A allele of single nucleotide polymorphism of rs12 912717 represented by SEQ ID No. 14;

a T allele of single nucleotide polymorphism of rs 3306194 represented by SEQ ID No. 18;

a C allele of single nucleotide polymorphism SEQ ID No. 19;

a G allele of single nucleotide polymorphism SEQ ID No. 20;

a T allele of single nucleotide polymorphism of rs1800787 represented by SEQ ID No. 23; an A allele of single nucleotide polymorphism of rs2229765 represented by SEQ ID No. 24;

an A allele of single nucleotide polymorphism of rs2286983 represented by

SEQ ID No. 26;

a G allele of single nucleotide polymorphism of rs1376251 represented by SEQ ID No. 28;

a G allele of single nucleotide polymorphism of rs17242766 represented by

SEQ ID No. 31.

a G allele of single nucleotide polymorphism of rs1 8204072 represented by SEQ ID No. 33;

a C allele of single nucleotide polymorphism of rs28362239 represented by

SEQ ID No. 36.

17. A DNA chip comprising at least one probe capable of hybridizing to at least one SNP deposited on a solid support from a sample nucleic acid of an individual of Asian descent,, wherein the SNP is found in at least one gene associated with lipid metabolism.

18. The DNA chip according to claim 17, wherein the probe is designed using at least one sequence selected from the group consisting of SEQ ID Nos. 37-72.

19. The DNA chip according to either claim 17 or 18, wherein the SNP is found in LDLR gene, APOB gene and/or PCSK9 gene.

20. The DNA chip according to claim 17, wherein the SNP is selected from the group consisting of: an A allele of single nucleotide polymorphism of rs2032582 represented by SEQ ID No. 1 ;

a T allele of single nucleotide polymorphism of rs1171381 represented by SEQ ID No. 4;

an A allele of single nucleotide polymorphism of rs2230345 represented by

SEQ ID No. 5;

a C allele of single nucleotide polymorphism of rs2516837 represented by

SEQ ID No. 10;

a T allele of single nucleotide polymorphism of rs150264487 represented by

SEQ ID No. 15;

a T allele of single nucleotide polymorphism of rs13306194 represented by SEQ ID No. 18; a C allele of single nucleotide polymorphism SEQ ID No. 19;

a G allele of single nucleotide polymorphism SEQ ID No. 20;

a C allele of single nucleotide polymorphism of rs429358 represented by

SEQ ID No. 22;

a C allele of single nucleotide polymorphism of rs2624265 represented by

SEQ ID No. 27;

a C allele of single nucleotide polymorphism of rs8028759 represented by

SEQ ID No. 32;

21. A kit for determining whether an individual of Asian descent has an increased risk for FH, the kit comprising: at least one oligonucleotide that can identify an FH-associated SNP wherein the SNP is found in at least one gene associated with lipid metabolism.

22. The kit according to claim 16, wherein the SNP is found in LDLR gene, APOB gene and/or PCSK9 gene.

23. The kit chip according to claim 16, wherein the SNP is selected from the group of loci consisting of:

(a)

an A allele of single nucleotide polymorphism of rs2032582 represented by SEQ ID No. 1 ;

a T allele of single nucleotide polymorphism of rs10507391 represented by

SEQ ID No. 2;

a C allele of single nucleotide polymorphism of rs12 918395 represented by SEQ ID No. 3;

an A allele of single nucleotide polymorphism of rs2073658 represented by

SEQ ID No. 7;

a T allele of single nucleotide polymorphism of rs6756629 represented by SEQ ID No. 1 1 ;

a T allele of single nucleotide polymorphism of rs28929476 represented by

SEQ ID No. 12;

an A allele of single nucleotide polymorphism of rs12720770 represented by

SEQ ID No. 17;

a C allele of single nucleotide polymorphism SEQ ID No. 19;

a G allele of single nucleotide polymorphism SEQ ID No. 20;

a T allele of single nucleotide polymorphism of rs1800787 represented by

SEQ ID No. 23;

a G allele of single nucleotide polymorphism of rs1376251 represented by

SEQ ID No. 28;

a C allele of single nucleotide polymorphism of rs 10888896 represented by SEQ ID No. 35;

and

(b) instructions for use.

24. The kit according to claim 21 , wherein the oligonucleotide is a probe designed using at least one sequence selected from the group consisting of SEQ ID NOs. 37- 72.