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Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, Tanya M.,Musunuru, Kiran,Smith, Albert V.,Edmondson, Andrew C.,Stylianou, Ioannis M.,Koseki, Masahiro,Pirruccello, James P.,Ripatti, Samuli,Chasman, Daniel I.,Willer, Cristen J.,Johansen, C Nature Publishing Group, a division of Macmillan P 2010 Nature Vol.466 No.7307
Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P??<??5?????10<SUP>??8</SUP>), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes??GALNT2, PPP1R3B and TTC39B??with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.
The genetic architecture of type 2 diabetes
Fuchsberger, Christian,Flannick, Jason,Teslovich, Tanya M,Mahajan, Anubha,Agarwala, Vineeta,Gaulton, Kyle J,Ma, Clement,Fontanillas, Pierre,Moutsianas, Loukas,McCarthy, Davis J,Rivas, Manuel A,Perry, Macmillan Journals ltd., etc.] 2016 Nature Vol.536 No.7614
<P>The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes.</P>
Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees
Jun, Goo,Manning, Alisa,Almeida, Marcio,Zawistowski, Matthew,Wood, Andrew R.,Teslovich, Tanya M.,Fuchsberger, Christian,Feng, Shuang,Cingolani, Pablo,Gaulton, Kyle J.,Dyer, Thomas,Blackwell, Thomas W. National Academy of Sciences 2018 PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF Vol.115 No.2
<P>A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant c/s-expression quantitative trait loci that could not be detected in population studies, validating our approach. Flowever, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants.</P>