title: Application of pooled genotyping to scan candidate regions for association with HDL cholesterol levels.
abstract: Association studies are used to identify genetic determinants of complex human traits of medical interest. With the large number of validated single nucleotide polymorphisms (SNPs) currently available, two limiting factors in association studies are genotyping capability and costs. Pooled DNA genotyping has been proposed as an efficient means of screening SNPs for allele frequency differences in case-control studies and for prioritising them for subsequent individual genotyping analysis. Here, we apply quantitative pooled genotyping followed by individual genotyping and replication to identify associations with human serum high-density lipoprotein (HDL) cholesterol levels. The DNA from individuals with low and high HDL cholesterol levels was pooled separately, each pool was amplified by polymerase chain reaction in triplicate and each amplified product was separately hybridised to a high-density oligonucleotide array. Allele frequency differences between case and control groups with low and high HDL cholesterol levels were estimated for 7,283 SNPs distributed across 71 candidate gene regions spanning a total of 17.1 megabases. A novel method was developed to take advantage of independently derived haplotype map information to improve the pooled estimates of allele frequency differences. A subset of SNPs with the largest estimated allele frequency differences between low and high HDL cholesterol groups was chosen for individual genotyping in the study population, as well as in a separate replication population. Four SNPs in a single haplotype block within the cholesteryl ester transfer protein (CETP) gene interval were significantly associated with HDL cholesterol levels in both populations. Our study is among the first to demonstrate the application of pooled genotyping followed by confirmation with individual genotyping to identify genetic determinants of a complex trait.
authors.affiliation: Perlegen Sciences, 2021 Stierlin Court, Mountain View, CA 94043, USA.
authors.forename: David A
authors.initials: DA
authors.lastname: Hinds
authors.forename: Albert B
authors.initials: AB
authors.lastname: Seymour
authors.forename: L Kathryn
authors.initials: LK
authors.lastname: Durham
authors.forename: Poulabi
authors.initials: P
authors.lastname: Banerjee
authors.forename: Dennis G
authors.initials: DG
authors.lastname: Ballinger
authors.forename: Patrice M
authors.initials: PM
authors.lastname: Milos
authors.forename: David R
authors.initials: DR
authors.lastname: Cox
authors.forename: John F
authors.initials: JF
authors.lastname: Thompson
authors.forename: Kelly A
authors.initials: KA
authors.lastname: Frazer
mesh_terms: D016022:Case-Control Studies; D008076:Cholesterol, HDL / Q000097:blood / Q000235:genetics*; D015331:Cohort Studies; D005260:Female; D005784:Gene Amplification; D005787:Gene Frequency; D005788:Gene Pool; D005838:Genotype; D006239:Haplotypes; D006801:Humans; D006937:Hypercholesterolemia / Q000235:genetics*; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D016133:Polymerase Chain Reaction; D020641:Polymorphism, Single Nucleotide
chemical_list: D008076:Cholesterol, HDL