Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans

By S. Kathiresan, O. Melander, C. Guiducci, Aarti Surti, N. Burtt, Mark J. Rieder, Gregory M. Cooper, C. Roos, B. Voight, Aki S. Havulinna and 16 more. Nature Genetics, 2008

1,459 citations recorded by the source corpus.

Blood concentrations of lipoproteins and lipids are heritable risk factors for cardiovascular disease. Using genome-wide association data from three studies (n = 8,816 that included 2,758 individuals from the Diabetes Genetics Initiative specific to the current paper as well as 1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables reported in a companion paper in this issue) and targeted replication association analyses in up to 18,554 independent participants, we show that common SNPs at 18 loci are reproducibly associated with concentrations of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and/or triglycerides. Six of these loci are new (P < 5 × 10−8 for each new locus). Of the six newly identified chromosomal regions, two were associated with LDL cholesterol (1p13 near CELSR2, PSRC1 and SORT1 and 19p13 near CILP2 and PBX4), one with HDL cholesterol (1q42 in GALNT2) and five with triglycerides (7q11 near TBL2 and MLXIPL, 8q24 near TRIB1, 1q42 in GALNT2, 19p13 near CILP2 and PBX4 and 1p31 near ANGPTL3). At 1p13, the LDL-associated SNP was also strongly correlated with CELSR2, PSRC1, and SORT1 transcript levels in human liver, and a proxy for this SNP was recently shown to affect risk for coronary artery disease. Understanding the molecular, cellular and clinical consequences of the newly identified loci may inform therapy and clinical care.

Subfields: Cardiology and Cardiovascular Medicine, Genetics, Surgery

View Paper: https://www.semanticscholar.org/paper/1ca64d1a17f1c865164257e02e28cd3a96da4095

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Citations in the corpus

Genome-Wide Association Analysis Identifies Variants Associated with Nonalcoholic Fatty Liver Disease That Have Distinct Effects on Metabolic Traits (2011, background): “[24]In addition, variants in or near GCKR, NCAN, and PPP1R3B have been previously associated with lipid levels, GCKR with glycemic traits and LYPLAL1 with abdominal obesity [16,25–29].”
HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials (2015, background): “20 Both were subsequently associated with LDL cholesterol at a genome-wide level of signiﬁ cance, 21 with strong associations in the largest genome-wide study of lipids so far (rs17238484 p=1·35 × 10 – ²¹; rs12916 p<1·00 × 10 – ³⁰).”
Progress and Promise of Genome-Wide Association Studies for Human Complex Trait Genetics (2011, background): “For other quantitative traits, including body mass index (Speliotes et al. 2010) and cholesterol (Kathiresan et al. 2008), GWASs of more than 240,000 and 22,000 individuals, respectively, have identified 32 and 18 loci that together explain only 2–4% and 5–6% of heritable variation.”
Progress and challenges in translating the biology of atherosclerosis (2011, background): “, as have several variants associated with lipoprotein disorder”
Identifying Relationships among Genomic Disease Regions: Predicting Genes at Pathogenic SNP Associations and Rare Deletions (2009, methodology): “We first applied GRAIL to a set of 19 validated SNPs associated with triglyceride, LDL, and/or HDL levels [5,6].”
Genotype Imputation (2009, methodology): “Genotype imputation was first used to combine GWAS for blood lipid levels (43, 111) and height (89) and soon thereafter to combine data across genome-wide scans for type 2 diabetes (116), body-mass index (62), and Crohn’s disease (6).”
Mapping the Genetic Architecture of Gene Expression in Human Liver (2008, background): “] and plasma low-density lipoprotein (LDL)-cholesterol levels [”
Newly identified loci that influence lipid concentrations and risk of coronary artery disease (2008, methodology): “, with data on 2,758 individuals from the Diabetes Genetics Initiativ”