Publications by authors named "Tanya M Teslovich"

58 Publications

The trans-ancestral genomic architecture of glycemic traits.

Nat Genet 2021 06 31;53(6):840-860. Epub 2021 May 31.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
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http://dx.doi.org/10.1038/s41588-021-00852-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610958PMC
June 2021

Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls.

Nature 2019 06 22;570(7759):71-76. Epub 2019 May 22.

Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, South Korea.

Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10) and candidate genes from knockout mice (P = 5.2 × 10). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.
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http://dx.doi.org/10.1038/s41586-019-1231-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6699738PMC
June 2019

Rare Protein-Truncating Variants in APOB, Lower Low-Density Lipoprotein Cholesterol, and Protection Against Coronary Heart Disease.

Circ Genom Precis Med 2019 05;12(5):e002376

Program in Medical and Population Genetics, Broad Institute, Cambridge, MA (A.V.K., M.C., S.K.).

Background Familial hypobetalipoproteinemia is a genetic disorder caused by rare protein-truncating variants (PTV) in the gene encoding APOB (apolipoprotein B), the major protein component of LDL (low-density lipoprotein) and triglyceride-rich lipoprotein particles. Whether heterozygous APOB deficiency is associated with decreased risk for coronary heart disease (CHD) is uncertain. We combined family-based and large scale gene-sequencing to characterize the association of rare PTVs in APOB with circulating LDL-C (LDL cholesterol), triglycerides, and risk for CHD. Methods We sequenced the APOB gene in 29 Japanese hypobetalipoproteinemia families, as well as 57 973 individuals derived from 12 CHD case-control studies-18 442 with early-onset CHD and 39 531 controls. We defined PTVs as variants that lead to a premature stop, disrupt canonical splice-sites, or lead to insertions/deletions that shift reading frame. We tested the association of rare APOB PTV carrier status with blood lipid levels and CHD. Results Among 29 familial hypobetalipoproteinemia families, 8 families harbored APOB PTVs. Carrying 1 APOB PTV was associated with 55 mg/dL lower LDL-C ( P=3×10) and 53% lower triglyceride level ( P=2×10). Among 12 case-control studies, an APOB PTV was present in 0.038% of CHD cases as compared to 0.092% of controls. APOB PTV carrier status was associated with a 43 mg/dL lower LDL-C ( P=2×10), a 30% decrease in triglycerides ( P=5×10), and a 72% lower risk for CHD (odds ratio, 0.28; 95% CI, 0.12-0.64; P=0.002). Conclusions Rare PTV mutations in APOB which are associated with lower LDL-C and reduced triglycerides also confer protection against CHD.
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http://dx.doi.org/10.1161/CIRCGEN.118.002376DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7044908PMC
May 2019

Genetics of blood lipids among ~300,000 multi-ethnic participants of the Million Veteran Program.

Nat Genet 2018 11 1;50(11):1514-1523. Epub 2018 Oct 1.

Initiative for Noncommunicable Diseases, Health Systems and Population Studies Division, International Centre for Diarrheal Disease Research, Dhaka, Bangladesh.

The Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of US military veterans. Here we genotyped 312,571 MVP participants using a custom biobank array and linked the genetic data to laboratory and clinical phenotypes extracted from electronic health records covering a median of 10.0 years of follow-up. Among 297,626 veterans with at least one blood lipid measurement, including 57,332 black and 24,743 Hispanic participants, we tested up to around 32 million variants for association with lipid levels and identified 118 novel genome-wide significant loci after meta-analysis with data from the Global Lipids Genetics Consortium (total n > 600,000). Through a focus on mutations predicted to result in a loss of gene function and a phenome-wide association study, we propose novel indications for pharmaceutical inhibitors targeting PCSK9 (abdominal aortic aneurysm), ANGPTL4 (type 2 diabetes) and PDE3B (triglycerides and coronary disease).
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http://dx.doi.org/10.1038/s41588-018-0222-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6521726PMC
November 2018

Biobank-driven genomic discovery yields new insight into atrial fibrillation biology.

Nat Genet 2018 09 30;50(9):1234-1239. Epub 2018 Jul 30.

Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.

To identify genetic variation underlying atrial fibrillation, the most common cardiac arrhythmia, we performed a genome-wide association study of >1,000,000 people, including 60,620 atrial fibrillation cases and 970,216 controls. We identified 142 independent risk variants at 111 loci and prioritized 151 functional candidate genes likely to be involved in atrial fibrillation. Many of the identified risk variants fall near genes where more deleterious mutations have been reported to cause serious heart defects in humans (GATA4, MYH6, NKX2-5, PITX2, TBX5), or near genes important for striated muscle function and integrity (for example, CFL2, MYH7, PKP2, RBM20, SGCG, SSPN). Pathway and functional enrichment analyses also suggested that many of the putative atrial fibrillation genes act via cardiac structural remodeling, potentially in the form of an 'atrial cardiomyopathy', either during fetal heart development or as a response to stress in the adult heart.
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http://dx.doi.org/10.1038/s41588-018-0171-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6530775PMC
September 2018

Genetic inactivation of ANGPTL4 improves glucose homeostasis and is associated with reduced risk of diabetes.

Nat Commun 2018 06 13;9(1):2252. Epub 2018 Jun 13.

Geisinger, Danville, 17822, PA, USA.

Angiopoietin-like 4 (ANGPTL4) is an endogenous inhibitor of lipoprotein lipase that modulates lipid levels, coronary atherosclerosis risk, and nutrient partitioning. We hypothesize that loss of ANGPTL4 function might improve glucose homeostasis and decrease risk of type 2 diabetes (T2D). We investigate protein-altering variants in ANGPTL4 among 58,124 participants in the DiscovEHR human genetics study, with follow-up studies in 82,766 T2D cases and 498,761 controls. Carriers of p.E40K, a variant that abolishes ANGPTL4 ability to inhibit lipoprotein lipase, have lower odds of T2D (odds ratio 0.89, 95% confidence interval 0.85-0.92, p = 6.3 × 10), lower fasting glucose, and greater insulin sensitivity. Predicted loss-of-function variants are associated with lower odds of T2D among 32,015 cases and 84,006 controls (odds ratio 0.71, 95% confidence interval 0.49-0.99, p = 0.041). Functional studies in Angptl4-deficient mice confirm improved insulin sensitivity and glucose homeostasis. In conclusion, genetic inactivation of ANGPTL4 is associated with improved glucose homeostasis and reduced risk of T2D.
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http://dx.doi.org/10.1038/s41467-018-04611-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5997992PMC
June 2018

Profiling and Leveraging Relatedness in a Precision Medicine Cohort of 92,455 Exomes.

Am J Hum Genet 2018 05;102(5):874-889

Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY 10591, USA. Electronic address:

Large-scale human genetics studies are ascertaining increasing proportions of populations as they continue growing in both number and scale. As a result, the amount of cryptic relatedness within these study cohorts is growing rapidly and has significant implications on downstream analyses. We demonstrate this growth empirically among the first 92,455 exomes from the DiscovEHR cohort and, via a custom simulation framework we developed called SimProgeny, show that these measures are in line with expectations given the underlying population and ascertainment approach. For example, within DiscovEHR we identified ∼66,000 close (first- and second-degree) relationships, involving 55.6% of study participants. Our simulation results project that >70% of the cohort will be involved in these close relationships, given that DiscovEHR scales to 250,000 recruited individuals. We reconstructed 12,574 pedigrees by using these relationships (including 2,192 nuclear families) and leveraged them for multiple applications. The pedigrees substantially improved the phasing accuracy of 20,947 rare, deleterious compound heterozygous mutations. Reconstructed nuclear families were critical for identifying 3,415 de novo mutations in ∼1,783 genes. Finally, we demonstrate the segregation of known and suspected disease-causing mutations, including a tandem duplication that occurs in LDLR and causes familial hypercholesterolemia, through reconstructed pedigrees. In summary, this work highlights the prevalence of cryptic relatedness expected among large healthcare population-genomic studies and demonstrates several analyses that are uniquely enabled by large amounts of cryptic relatedness.
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http://dx.doi.org/10.1016/j.ajhg.2018.03.012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5986700PMC
May 2018

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

Nat Genet 2018 04 9;50(4):559-571. Epub 2018 Apr 9.

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
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http://dx.doi.org/10.1038/s41588-018-0084-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898373PMC
April 2018

A Protein-Truncating HSD17B13 Variant and Protection from Chronic Liver Disease.

N Engl J Med 2018 03;378(12):1096-1106

From the Regeneron Genetics Center (N.S.A.-H., A.H.L., C.S., S. McCarthy, C.O., J.S.P., S.B., N.G., S. Mukherjee, A.E.L., E.D.F., J.P., I.B.B., A.R.S., J.G.R., J.D.O., O.G., T.M.T., A.B., F.E.D.) and Regeneron Pharmaceuticals (X. Cheng, Y.X., P.S., Y.L., D.E., S.Y.K., B.Z., W.O., A.J.M., G.D.Y., J.G.), Tarrytown, NY; the University of Texas Southwestern Medical Center at Dallas, Dallas (J.K., S.S., H.H.H., J.C.C.); and Geisinger Health System, Danville (G.C.W., A.N.S., M.D.S., X. Chu, J.Z.L., U.L.M., D.J.C., C.D.S., T.M.), and Perelman School of Medicine, University of Pennsylvania, Philadelphia (M.D.F., A.S., S.M.D., D.J.R.) - both in Pennsylvania.

Background: Elucidation of the genetic factors underlying chronic liver disease may reveal new therapeutic targets.

Methods: We used exome sequence data and electronic health records from 46,544 participants in the DiscovEHR human genetics study to identify genetic variants associated with serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Variants that were replicated in three additional cohorts (12,527 persons) were evaluated for association with clinical diagnoses of chronic liver disease in DiscovEHR study participants and two independent cohorts (total of 37,173 persons) and with histopathological severity of liver disease in 2391 human liver samples.

Results: A splice variant (rs72613567:TA) in HSD17B13, encoding the hepatic lipid droplet protein hydroxysteroid 17-beta dehydrogenase 13, was associated with reduced levels of ALT (P=4.2×10) and AST (P=6.2×10). Among DiscovEHR study participants, this variant was associated with a reduced risk of alcoholic liver disease (by 42% [95% confidence interval {CI}, 20 to 58] among heterozygotes and by 53% [95% CI, 3 to 77] among homozygotes), nonalcoholic liver disease (by 17% [95% CI, 8 to 25] among heterozygotes and by 30% [95% CI, 13 to 43] among homozygotes), alcoholic cirrhosis (by 42% [95% CI, 14 to 61] among heterozygotes and by 73% [95% CI, 15 to 91] among homozygotes), and nonalcoholic cirrhosis (by 26% [95% CI, 7 to 40] among heterozygotes and by 49% [95% CI, 15 to 69] among homozygotes). Associations were confirmed in two independent cohorts. The rs72613567:TA variant was associated with a reduced risk of nonalcoholic steatohepatitis, but not steatosis, in human liver samples. The rs72613567:TA variant mitigated liver injury associated with the risk-increasing PNPLA3 p.I148M allele and resulted in an unstable and truncated protein with reduced enzymatic activity.

Conclusions: A loss-of-function variant in HSD17B13 was associated with a reduced risk of chronic liver disease and of progression from steatosis to steatohepatitis. (Funded by Regeneron Pharmaceuticals and others.).
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http://dx.doi.org/10.1056/NEJMoa1712191DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668033PMC
March 2018

Identification of seven novel loci associated with amino acid levels using single-variant and gene-based tests in 8545 Finnish men from the METSIM study.

Hum Mol Genet 2018 05;27(9):1664-1674

Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA.

Comprehensive metabolite profiling captures many highly heritable traits, including amino acid levels, which are potentially sensitive biomarkers for disease pathogenesis. To better understand the contribution of genetic variation to amino acid levels, we performed single variant and gene-based tests of association between nine serum amino acids (alanine, glutamine, glycine, histidine, isoleucine, leucine, phenylalanine, tyrosine, and valine) and 16.6 million genotyped and imputed variants in 8545 non-diabetic Finnish men from the METabolic Syndrome In Men (METSIM) study with replication in Northern Finland Birth Cohort (NFBC1966). We identified five novel loci associated with amino acid levels (P = < 5×10-8): LOC157273/PPP1R3B with glycine (rs9987289, P = 2.3×10-26); ZFHX3 (chr16:73326579, minor allele frequency (MAF) = 0.42%, P = 3.6×10-9), LIPC (rs10468017, P = 1.5×10-8), and WWOX (rs9937914, P = 3.8×10-8) with alanine; and TRIB1 with tyrosine (rs28601761, P = 8×10-9). Gene-based tests identified two novel genes harboring missense variants of MAF <1% that show aggregate association with amino acid levels: PYCR1 with glycine (Pgene = 1.5×10-6) and BCAT2 with valine (Pgene = 7.4×10-7); neither gene was implicated by single variant association tests. These findings are among the first applications of gene-based tests to identify new loci for amino acid levels. In addition to the seven novel gene associations, we identified five independent signals at established amino acid loci, including two rare variant signals at GLDC (rs138640017, MAF=0.95%, Pconditional = 5.8×10-40) with glycine levels and HAL (rs141635447, MAF = 0.46%, Pconditional = 9.4×10-11) with histidine levels. Examination of all single variant association results in our data revealed a strong inverse relationship between effect size and MAF (Ptrend<0.001). These novel signals provide further insight into the molecular mechanisms of amino acid metabolism and potentially, their perturbations in disease.
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http://dx.doi.org/10.1093/hmg/ddy067DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5905595PMC
May 2018

Genome-wide Study of Atrial Fibrillation Identifies Seven Risk Loci and Highlights Biological Pathways and Regulatory Elements Involved in Cardiac Development.

Am J Hum Genet 2018 01 28;102(1):103-115. Epub 2017 Dec 28.

Regeneron Genetics Center, Tarrytown, NY 10591, USA.

Atrial fibrillation (AF) is a common cardiac arrhythmia and a major risk factor for stroke, heart failure, and premature death. The pathogenesis of AF remains poorly understood, which contributes to the current lack of highly effective treatments. To understand the genetic variation and biology underlying AF, we undertook a genome-wide association study (GWAS) of 6,337 AF individuals and 61,607 AF-free individuals from Norway, including replication in an additional 30,679 AF individuals and 278,895 AF-free individuals. Through genotyping and dense imputation mapping from whole-genome sequencing, we tested almost nine million genetic variants across the genome and identified seven risk loci, including two novel loci. One novel locus (lead single-nucleotide variant [SNV] rs12614435; p = 6.76 × 10) comprised intronic and several highly correlated missense variants situated in the I-, A-, and M-bands of titin, which is the largest protein in humans and responsible for the passive elasticity of heart and skeletal muscle. The other novel locus (lead SNV rs56202902; p = 1.54 × 10) covered a large, gene-dense chromosome 1 region that has previously been linked to cardiac conduction. Pathway and functional enrichment analyses suggested that many AF-associated genetic variants act through a mechanism of impaired muscle cell differentiation and tissue formation during fetal heart development.
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http://dx.doi.org/10.1016/j.ajhg.2017.12.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777936PMC
January 2018

Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees.

Proc Natl Acad Sci U S A 2018 01 26;115(2):379-384. Epub 2017 Dec 26.

Department of Statistics, Seoul National University, Seoul 08826, Republic of Korea.

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 -expression quantitative trait loci that could not be detected in population studies, validating our approach. However, 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.
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http://dx.doi.org/10.1073/pnas.1705859115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777025PMC
January 2018

Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

Sci Data 2017 12 19;4:170179. Epub 2017 Dec 19.

Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
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http://dx.doi.org/10.1038/sdata.2017.179DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5735917PMC
December 2017

Common, low-frequency, and rare genetic variants associated with lipoprotein subclasses and triglyceride measures in Finnish men from the METSIM study.

PLoS Genet 2017 Oct 30;13(10):e1007079. Epub 2017 Oct 30.

Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.

Lipid and lipoprotein subclasses are associated with metabolic and cardiovascular diseases, yet the genetic contributions to variability in subclass traits are not fully understood. We conducted single-variant and gene-based association tests between 15.1M variants from genome-wide and exome array and imputed genotypes and 72 lipid and lipoprotein traits in 8,372 Finns. After accounting for 885 variants at 157 previously identified lipid loci, we identified five novel signals near established loci at HIF3A, ADAMTS3, PLTP, LCAT, and LIPG. Four of the signals were identified with a low-frequency (0.005
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http://dx.doi.org/10.1371/journal.pgen.1007079DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5679656PMC
October 2017

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans.

Diabetes 2017 11 31;66(11):2888-2902. Epub 2017 May 31.

MRC Epidemiology Unit, University of Cambridge, Cambridge, U.K.

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci ( < 5 × 10), including variants near the , , and genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.
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http://dx.doi.org/10.2337/db16-1253DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5652602PMC
November 2017

Genetic and Pharmacologic Inactivation of ANGPTL3 and Cardiovascular Disease.

N Engl J Med 2017 07 24;377(3):211-221. Epub 2017 May 24.

From Regeneron Genetics Center (F.E.D., C.O., C.S., O.G., S.M., C.V.V.H., S.B., L.H., A.L., J.P., N.S., A.J.M., J.D.O., J.G.R., A.R.S., I.B.B., T.M.T., G.D.Y., S.J.M., A. Baras) and Regeneron Pharmaceuticals (V.G., H.M.D., A.Z., W.S., N.S., A.J.M., S.H., A. Bouzelmat, R.Z., B.S., R.P., D.G., G.A.H., W.J.S., P.B., G.D.Y., S.J.M., J.G.) Tarrytown, NY; the Department of Medicine, Division of Translational Medicine and Human Genetics (R.L.D.), and Departments of Surgery (S.D.) and Genetics and Medicine (A.S., D.J.R.), Perelman School of Medicine, University of Pennsylvania, Philadelphia, and Geisinger Health System, Danville (J.B.L., M.F.M., M.D.R., H.L.K., D.H.L., D.J.C.) - both in Pennsylvania; the Division of Endocrinology and Metabolism, Department of Internal Medicine (W.H.H.S., I.-T.L.) and Cardiovascular Center (K.-W.L.), Taichung Veterans General Hospital, Institute of Medical Technology, National Chung-Hsing University (W.H.H.S.), School of Medicine, Chung Shan Medical University (I.-T.L.), and the Department of Medicine, China Medical University (K.-W.L.), Taichung, and School of Medicine, National Yang-Ming University (W.H.H.S., I.-T.L., K.-W.L.), and School of Medicine, National Defense Medical Center (W.H.H.S.), Taipei - all in Taiwan; Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA (X.G., J.I.R., Y.-D.I.C.); the Division of Cardiology, Department of Medicine, Molecular Physiology Institute, School of Medicine, Duke University, Durham, NC (W.E.K., S.H.S.); the Department of Clinical Biochemistry, Rigshospitalet (A.B.W., B.G.N., A.T.-H.), the Copenhagen General Population Study (B.G.N., A.T.-H.) and Department of Clinical Biochemistry (B.G.N.), Herlev and Gentofte Hospital, and the Copenhagen City Heart Study, Frederiksberg Hospital, Copenhagen University Hospital, and Faculty of Health and Medical Sciences, University of Copenhagen (B.G.N., A.T.-H.) - all in Copenhagen; and TNO Metabolic Health Research, Gaubius Laboratory, Leiden, the Netherlands (A.M.H., H.M.G.P.).

Background: Loss-of-function variants in the angiopoietin-like 3 gene (ANGPTL3) have been associated with decreased plasma levels of triglycerides, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol. It is not known whether such variants or therapeutic antagonism of ANGPTL3 are associated with a reduced risk of atherosclerotic cardiovascular disease.

Methods: We sequenced the exons of ANGPTL3 in 58,335 participants in the DiscovEHR human genetics study. We performed tests of association for loss-of-function variants in ANGPTL3 with lipid levels and with coronary artery disease in 13,102 case patients and 40,430 controls from the DiscovEHR study, with follow-up studies involving 23,317 case patients and 107,166 controls from four population studies. We also tested the effects of a human monoclonal antibody, evinacumab, against Angptl3 in dyslipidemic mice and against ANGPTL3 in healthy human volunteers with elevated levels of triglycerides or LDL cholesterol.

Results: In the DiscovEHR study, participants with heterozygous loss-of-function variants in ANGPTL3 had significantly lower serum levels of triglycerides, HDL cholesterol, and LDL cholesterol than participants without these variants. Loss-of-function variants were found in 0.33% of case patients with coronary artery disease and in 0.45% of controls (adjusted odds ratio, 0.59; 95% confidence interval, 0.41 to 0.85; P=0.004). These results were confirmed in the follow-up studies. In dyslipidemic mice, inhibition of Angptl3 with evinacumab resulted in a greater decrease in atherosclerotic lesion area and necrotic content than a control antibody. In humans, evinacumab caused a dose-dependent placebo-adjusted reduction in fasting triglyceride levels of up to 76% and LDL cholesterol levels of up to 23%.

Conclusions: Genetic and therapeutic antagonism of ANGPTL3 in humans and of Angptl3 in mice was associated with decreased levels of all three major lipid fractions and decreased odds of atherosclerotic cardiovascular disease. (Funded by Regeneron Pharmaceuticals and others; ClinicalTrials.gov number, NCT01749878 .).
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http://dx.doi.org/10.1056/NEJMoa1612790DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5800308PMC
July 2017

Protein-Truncating Variants at the Cholesteryl Ester Transfer Protein Gene and Risk for Coronary Heart Disease.

Circ Res 2017 Jun 15;121(1):81-88. Epub 2017 May 15.

Rationale: Therapies that inhibit CETP (cholesteryl ester transfer protein) have failed to demonstrate a reduction in risk for coronary heart disease (CHD). Human DNA sequence variants that truncate the gene may provide insight into the efficacy of CETP inhibition.

Objective: To test whether protein-truncating variants (PTVs) at the gene were associated with plasma lipid levels and CHD.

Methods And Results: We sequenced the exons of the gene in 58 469 participants from 12 case-control studies (18 817 CHD cases, 39 652 CHD-free controls). We defined PTV as those that lead to a premature stop, disrupt canonical splice sites, or lead to insertions/deletions that shift frame. We also genotyped 1 Japanese-specific PTV in 27561 participants from 3 case-control studies (14 286 CHD cases, 13 275 CHD-free controls). We tested association of PTV carrier status with both plasma lipids and CHD. Among 58 469 participants with gene-sequencing data available, average age was 51.5 years and 43% were women; 1 in 975 participants carried a PTV at the gene. Compared with noncarriers, carriers of PTV at had higher high-density lipoprotein cholesterol (effect size, 22.6 mg/dL; 95% confidence interval, 18-27; <1.0×10), lower low-density lipoprotein cholesterol (-12.2 mg/dL; 95% confidence interval, -23 to -0.98; =0.033), and lower triglycerides (-6.3%; 95% confidence interval, -12 to -0.22; =0.043). PTV carrier status was associated with reduced risk for CHD (summary odds ratio, 0.70; 95% confidence interval, 0.54-0.90; =5.1×10).

Conclusions: Compared with noncarriers, carriers of PTV at displayed higher high-density lipoprotein cholesterol, lower low-density lipoprotein cholesterol, lower triglycerides, and lower risk for CHD.
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http://dx.doi.org/10.1161/CIRCRESAHA.117.311145DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5523940PMC
June 2017

A Low-Frequency Inactivating Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk.

Diabetes 2017 07 24;66(7):2019-2032. Epub 2017 Mar 24.

Diabetes and Endocrinology Unit, Department of Clinical Sciences Malmö, Lund University Diabetes Centre, Malmö, Sweden.

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of .
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http://dx.doi.org/10.2337/db16-1329DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5482074PMC
July 2017

Independent test assessment using the extreme value distribution theory.

BMC Proc 2016 18;10(Suppl 7):245-249. Epub 2016 Oct 18.

South Texas Diabetes and Obesity Institute, University of Texas at Brownsville, 2700 East Jackson Street, Brownsville, TX 78520 USA.

The new generation of whole genome sequencing platforms offers great possibilities and challenges for dissecting the genetic basis of complex traits. With a very high number of sequence variants, a naïve multiple hypothesis threshold correction hinders the identification of reliable associations by the overreduction of statistical power. In this report, we examine 2 alternative approaches to improve the statistical power of a whole genome association study to detect reliable genetic associations. The approaches were tested using the Genetic Analysis Workshop 19 (GAW19) whole genome sequencing data. The first tested method estimates the real number of effective independent tests actually being performed in whole genome association project by the use of an extreme value distribution and a set of phenotype simulations. Given the familiar nature of the GAW19 data and the finite number of pedigree founders in the sample, the number of correlations between genotypes is greater than in a set of unrelated samples. Using our procedure, we estimate that the effective number represents only 15 % of the total number of independent tests performed. However, even using this corrected significance threshold, no genome-wide significant association could be detected for systolic and diastolic blood pressure traits. The second approach implements a biological relevance-driven hypothesis tested by exploiting prior computational predictions on the effect of nonsynonymous genetic variants detected in a whole genome sequencing association study. This guided testing approach was able to identify 2 promising single-nucleotide polymorphisms (SNPs), 1 for each trait, targeting biologically relevant genes that could help shed light on the genesis of the human hypertension. The first gene, , associated with systolic blood pressure, interacts directly with genes involved in calcium-channel formation and the second gene, , encodes a microtubule-associated protein and had already been detected by previous genome-wide association study experiments conducted in an Asian population. Our results highlight the necessity of the development of alternative approached to improve the efficiency on the detection of reasonable candidate associations in whole genome sequencing studies.
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http://dx.doi.org/10.1186/s12919-016-0038-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133519PMC
October 2016

Omics-squared: human genomic, transcriptomic and phenotypic data for genetic analysis workshop 19.

BMC Proc 2016 18;10(Suppl 7):71-77. Epub 2016 Oct 18.

Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA.

Background: The Genetic Analysis Workshops (GAW) are a forum for development, testing, and comparison of statistical genetic methods and software. Each contribution to the workshop includes an application to a specified data set. Here we describe the data distributed for GAW19, which focused on analysis of human genomic and transcriptomic data.

Methods: GAW19 data were donated by the T2D-GENES Consortium and the San Antonio Family Heart Study and included whole genome and exome sequences for odd-numbered autosomes, measures of gene expression, systolic and diastolic blood pressures, and related covariates in two Mexican American samples. These two samples were a collection of 20 large families with whole genome sequence and transcriptomic data and a set of 1943 unrelated individuals with exome sequence. For each sample, simulated phenotypes were constructed based on the real sequence data. 'Functional' genes and variants for the simulations were chosen based on observed correlations between gene expression and blood pressure. The simulations focused primarily on additive genetic models but also included a genotype-by-medication interaction. A total of 245 genes were designated as 'functional' in the simulations with a few genes of large effect and most genes explaining < 1 % of the trait variation. An additional phenotype, Q1, was simulated to be correlated among related individuals, based on theoretical or empirical kinship matrices, but was not associated with any sequence variants. Two hundred replicates of the phenotypes were simulated. The GAW19 data are an expansion of the data used at GAW18, which included the family-based whole genome sequence, blood pressure, and simulated phenotypes, but not the gene expression data or the set of 1943 unrelated individuals with exome sequence.
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http://dx.doi.org/10.1186/s12919-016-0008-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133484PMC
October 2016

The genetic architecture of type 2 diabetes.

Nature 2016 08 11;536(7614):41-47. Epub 2016 Jul 11.

Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.

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 the heritability of this disease. Here, 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 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the 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 the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
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http://dx.doi.org/10.1038/nature18642DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5034897PMC
August 2016

Prosaposin is a regulator of progranulin levels and oligomerization.

Nat Commun 2016 06 30;7:11992. Epub 2016 Jun 30.

Division of Human Genetics, Cincinnati Children's Hospital Research Foundation, Cincinnati, Ohio 45229, USA.

Progranulin (GRN) loss-of-function mutations leading to progranulin protein (PGRN) haploinsufficiency are prevalent genetic causes of frontotemporal dementia. Reports also indicated PGRN-mediated neuroprotection in models of Alzheimer's and Parkinson's disease; thus, increasing PGRN levels is a promising therapeutic for multiple disorders. To uncover novel PGRN regulators, we linked whole-genome sequence data from 920 individuals with plasma PGRN levels and identified the prosaposin (PSAP) locus as a new locus significantly associated with plasma PGRN levels. Here we show that both PSAP reduction and overexpression lead to significantly elevated extracellular PGRN levels. Intriguingly, PSAP knockdown increases PGRN monomers, whereas PSAP overexpression increases PGRN oligomers, partly through a protein-protein interaction. PSAP-induced changes in PGRN levels and oligomerization replicate in human-derived fibroblasts obtained from a GRN mutation carrier, further supporting PSAP as a potential PGRN-related therapeutic target. Future studies should focus on addressing the relevance and cellular mechanism by which PGRN oligomeric species provide neuroprotection.
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http://dx.doi.org/10.1038/ncomms11992DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4931318PMC
June 2016

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

Nat Genet 2015 Dec 9;47(12):1415-25. Epub 2015 Nov 9.

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
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http://dx.doi.org/10.1038/ng.3437DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4666734PMC
December 2015

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

PLoS Genet 2015 Oct 1;11(10):e1005378. Epub 2015 Oct 1.

HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, United States of America.

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.
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http://dx.doi.org/10.1371/journal.pgen.1005378DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4591371PMC
October 2015

Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

PLoS Genet 2015 Jan 27;11(1):e1004876. Epub 2015 Jan 27.

Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America.

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.
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http://dx.doi.org/10.1371/journal.pgen.1004876DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4307976PMC
January 2015

Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

Nat Genet 2014 Mar 9;46(3):234-44. Epub 2014 Feb 9.

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.
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http://dx.doi.org/10.1038/ng.2897DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3969612PMC
March 2014

Re-sequencing expands our understanding of the phenotypic impact of variants at GWAS loci.

PLoS Genet 2014 Jan 30;10(1):e1004147. Epub 2014 Jan 30.

The Genome Institute at Washington University, St. Louis, Missouri, United States of America.

Genome-wide association studies (GWAS) have identified >500 common variants associated with quantitative metabolic traits, but in aggregate such variants explain at most 20-30% of the heritable component of population variation in these traits. To further investigate the impact of genotypic variation on metabolic traits, we conducted re-sequencing studies in >6,000 members of a Finnish population cohort (The Northern Finland Birth Cohort of 1966 [NFBC]) and a type 2 diabetes case-control sample (The Finland-United States Investigation of NIDDM Genetics [FUSION] study). By sequencing the coding sequence and 5' and 3' untranslated regions of 78 genes at 17 GWAS loci associated with one or more of six metabolic traits (serum levels of fasting HDL-C, LDL-C, total cholesterol, triglycerides, plasma glucose, and insulin), and conducting both single-variant and gene-level association tests, we obtained a more complete understanding of phenotype-genotype associations at eight of these loci. At all eight of these loci, the identification of new associations provides significant evidence for multiple genetic signals to one or more phenotypes, and at two loci, in the genes ABCA1 and CETP, we found significant gene-level evidence of association to non-synonymous variants with MAF<1%. Additionally, two potentially deleterious variants that demonstrated significant associations (rs138726309, a missense variant in G6PC2, and rs28933094, a missense variant in LIPC) were considerably more common in these Finnish samples than in European reference populations, supporting our prior hypothesis that deleterious variants could attain high frequencies in this isolated population, likely due to the effects of population bottlenecks. Our results highlight the value of large, well-phenotyped samples for rare-variant association analysis, and the challenge of evaluating the phenotypic impact of such variants.
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http://dx.doi.org/10.1371/journal.pgen.1004147DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907339PMC
January 2014

Discovery and refinement of loci associated with lipid levels.

Nat Genet 2013 Nov 6;45(11):1274-1283. Epub 2013 Oct 6.

Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA.

Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.
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http://dx.doi.org/10.1038/ng.2797DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3838666PMC
November 2013
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