Article

Common single-nucleotide polymorphisms act in concert to affect plasma levels of high-density lipoprotein cholesterol.

Genetics Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
The American Journal of Human Genetics (Impact Factor: 11.2). 11/2007; 81(6):1298-303. DOI: 10.1086/522497
Source: PubMed

ABSTRACT The identification of DNA sequence variants underlying human complex phenotypes remains a significant challenge for several reasons: individual variants can have small phenotypic effects or low population frequencies, and multiple allelic variants may act in concert to affect a trait. We evaluated the combined effect of allelic variants in seven genes involved in high-density lipoprotein (HDL) metabolism, using forward stepwise regression. Analysis of all known common single-nucleotide polymorphisms (SNPs) in the seven candidate genes revealed four variants that were associated with incremental changes in HDL cholesterol levels in three independent samples. Conversely, analysis of 660 polymorphisms in eight genes that do not appear to be involved in HDL metabolism did not identify any associations with plasma HDL-cholesterol levels. These data indicate that several common SNPs act in concert to influence plasma levels of HDL cholesterol.

0 Bookmarks
 · 
84 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Despite the success of genome-wide association studies (GWASs) in detecting common variants (minor allele frequency ≥0.05) many suggested that rare variants also contribute to the genetic architecture of diseases. Recently, researchers demonstrated that rare variants can show a strong stratification which may not be corrected by using existing methods. In this paper, we focus on a case-parents study and consider methods for testing group-wise association between multiple rare (and common) variants in a gene region and a disease. All tests depend on the numbers of transmitted mutant alleles from parents to their diseased children across variants and hence they are robust to the effect of population stratification. We use extensive simulation studies to compare the performance of four competing tests: the largest single-variant transmission disequilibrium test (TDT), multivariable test, combined TDT, and a likelihood ratio test based on a random-effects model. We find that the likelihood ratio test is most powerful in a wide range of settings and there is no negative impact to its power performance when common variants are also included in the analysis. If deleterious and protective variants are simultaneously analyzed, the likelihood ratio test was generally insensitive to the effect directionality, unless the effects are extremely inconsistent in one direction.
    PLoS ONE 09/2013; 8(9):e74310. DOI:10.1371/journal.pone.0074310 · 3.53 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The heritability of high-density lipoprotein cholesterol (HDL-C) level is estimated at approximately 50%. Recent genome-wide association studies have identified genes involved in regulation of high-density lipoprotein cholesterol (HDL-C) levels. The precise genetic profile determining heritability of HDL-C however are far from complete and there is substantial room for further characterization of genetic profiles influencing blood lipid levels. Here we report an association study comparing the distribution of 139 SNPs from more than 30 genes between groups that represent extreme ends of HDL-C distribution. We genotyped 704 individuals that were selected from Genome Database of Latvian Population. 10 SNPs from CETP gene showed convincing association with low HDL-C levels (rs1800775, rs3764261, rs173539, rs9939224, rs711752, rs708272, rs7203984, rs7205804, rs11076175 and rs9929488) while 34 SNPs from 10 genes were nominally associated (p<0.05) with HDL-C levels. We have also identified haplotypes from CETP with distinct effects on determination of HDL-C levels. Our conclusion: So far the SNPs in CETP gene are identified as the most common genetic factor influencing HDL-C levels in the representative sample from Latvian population.
    PLoS ONE 05/2013; 8(5):e64191. DOI:10.1371/journal.pone.0064191 · 3.53 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Low high density lipoprotein cholesterol (HDL-C) is a known risk factor of coronary artery disease. Apolipoprotein A1 (APOA1) is the most abundant component of HDL-C. This study aimed at identifying sequence variations (rare and common) in the APOA1 gene and its association with serum HDL-C levels. This study was conducted from April 2012 to February 2013 on 79 Tehranians (participants of Tehran Lipid and Glucose Study) with extremely low HDL-C (within the 5th percentile) and 63 individuals with extremely high HDL-C (within the 95th percentile) levels. After DNA amplification by PCR, DNA sequencing of all three exons and 700 bps of promoter region of the APOA1 gene was performed. Sequence results were analyzed and interpreted using the appropriate software and variants were identified. After sequencing 42 common and rare variants were identified, 11 of which were known variants and the others had been unreported so far. Of the exonic variants, 11 were missense, 6 were synonymous and 1 was nonsense. There was a significant association between serum HDL-C and variant of rs2070665 as well as variants Chr.11:116707788, Chr.11:116708059, Chr.11:116708036, Chr.11:116707729, rs201148448, Chr.11:116707018, Chr.11:116707801, Chr.11:116708530, Chr.11:116708088, rs121912724 and Chr.11:116706966 (p < 0.001). Variants Chr.11:116707018, rs121912724 and 2070665 were independent predictors of the HDL-C level (p < 0.001). SNP Chr.11:116707018 was the strongest predictor of the HDL-C level (OR 7.527, p < 0.001). This study identified 42 variants in APOA1 gene, 31 of which were new variants. Three variants of rs2070665, rs121912724 and Chr.11:116707018 could predict the HDL-C level independently. Variant rs2070665 was protective against low-HDL-C levels while variants rs121912724 and Chr.11:116707018 were risk factors for that in our population.
    Lipids 10/2013; 48(12). DOI:10.1007/s11745-013-3847-6 · 2.56 Impact Factor

Full-text (2 Sources)

Download
14 Downloads
Available from
May 26, 2014