Display Settings:

Format

Send to:

Choose Destination
Am J Hypertens. 2006 Dec;19(12):1270-7.

Genome-wide linkage analysis of lipids in nondiabetic Chinese and Japanese from the SAPPHIRe family study.

Author information

  • 1Division of Biostatistics and Bioinformatics, National Health Research Institutes, Miaoli, Taiwan.

Abstract

BACKGROUND:

Lipid levels are recognized as major risk factors for coronary heart disease (CHD). Discovery of major loci underlying quantitative lipid traits could help to elucidate the genetics of CHD.

METHODS:

We performed a genome-wide search for quantitative trait loci linked to lipid phenotypes in 1538 Chinese subjects (509 families) and 625 Japanese subjects (204 families) not taking lipid-lowering medications from the Stanford-Asian Pacific Program in Hypertension and Insulin Resistance (SAPPHIRe) study. The multipoint variance-components method was used to test for linkage between marker loci and each trait by maximum likelihood methods adjusted for effects of age, age(2), gender, body mass index (BMI), smoking, alcohol drinking, physical activity, and field center.

RESULTS:

The highest logarithm of odds (LOD) score detected was 3.22 for logarithmically transformed HDL-cholesterol on chromosome 12 at 113 cM in Chinese subjects. This score overlaps the positive findings for HDL reported in Mexican Americans (chromosome 12 at 96 cM). Although no strong evidence for linkage was found in Japanese subjects, some modest peaks (LOD score >==1.5) were found in several regions that have been reported in other published genome scans. For example, the Japanese SAPPHIRe peak for HDL (chromosome 1 at 167 cM; LOD = 1.54) was very close to the quantitative trait loci (QTL) for HDL reported in the scan of white American HyperGEN (chromosome 1 at 159.9 cM).

CONCLUSIONS:

Genome-wide scan for genes influencing lipid phenotypes was conducted and we found significant linkage of HDL to a locus on chromosome 12 in Chinese subjects and no linkage signal exceeding 1.68 was found in the Japanese subjects.

PMID:
17161774
[PubMed - indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for HighWire
    Loading ...
    Write to the Help Desk