Gina M Peloso

University of Pennsylvania, Filadelfia, Pennsylvania, United States

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Publications (64)910.16 Total impact

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    ABSTRACT: Background Experiments in mice initially suggested a role for the protein angiopoietin-like 8 (ANGPTL8) in glucose homeostasis. However, subsequent experiments in model systems have challenged this proposed role. We sought to better understand the importance of ANGPTL8 in human glucose homeostasis by examining the association of a null mutation in ANGPTL8 with fasting glucose levels and risk for type 2 diabetes. Methods A naturally-occurring null mutation in human ANGPTL8 (rs145464906; c.361C > T; p.Q121X) is carried by ~1 in 1000 individuals of European ancestry and is associated with higher levels of plasma high-density lipoprotein cholesterol, suggesting that this mutation has functional significance. We examined the association of p.Q121X with fasting glucose levels and risk for type 2 diabetes in up to 95,558 individuals (14,824 type 2 diabetics and 80,734 controls). Results We found no significant association of p.Q121X with either fasting glucose or type 2 diabetes (p-value = 0.90 and 0.65, respectively). Given our sample sizes, we had >98 % power to detect at least a 0.23 mmol/L effect on plasma glucose and >95 % power to detect a 70 % increase in risk for type 2 diabetes. Conclusion Disruption of ANGPTL8 function in humans does not seem to have a large effect on measures of glucose tolerance.
    Full-text · Article · Dec 2016 · BMC Endocrine Disorders
  • Janina M Jeff · Gina M Peloso · Ron Do
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    ABSTRACT: Purpose of review: Rare variant association studies (RVAS) target the class of genetic variation with frequencies less than 1%. Recently, investigators have used exome sequencing in RVAS to identify rare alleles responsible for Mendelian diseases but have experienced greater difficulty discovering such alleles for complex diseases. In this review, we describe what we have learned about lipoprotein metabolism and coronary heart disease through the conduct of RVAS. Recent findings: Rare protein-altering genetic variation can provide important insights that are not as easily attainable from common variant association studies. First, RVAS can facilitate gene discovery by identifying novel rare protein-altering variants in specific genes that are associated with disease. Second, rare variant associations can provide supportive evidence for putative drug targets for novel therapies. Finally, rare variants can uncover new pathways and reveal new biologic mechanisms. Summary: The field of human genetics has already made tremendous progress in understanding lipoprotein metabolism and the causes of coronary heart disease in the context of rare variants. As next generation sequencing becomes more cost-effective, RVAS with larger sample sizes will be conducted. This will lead to more novel rare variant discoveries and the translation of genomic data into biological knowledge and clinical insights for cardiovascular disease.
    No preview · Article · Feb 2016 · Current opinion in lipidology
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    ABSTRACT: Individuals with exceptional longevity and their offspring have significantly larger high-density lipoprotein concentrations (HDL-C) particle sizes due to the increased homozygosity for the I405V variant in the cholesteryl ester transfer protein (CETP) gene. In this study, we investigate the association of CETP and HDL-C further to identify novel, independent CETP variants associated with HDL-C in humans.Methods:We performed a meta-analysis of HDL-C within the CETP region using 59,432 individuals imputed with 1000 Genomes data. We performed replication in an independent sample of 47,866 individuals and validation was done by Sanger sequencing.Results:The meta-analysis of HDL-C within the CETP region identified five independent variants, including an exonic variant and a common intronic insertion. We replicated these 5 variants significantly in an independent sample of 47,866 individuals. Sanger sequencing of the insertion within a single family confirmed segregation of this variant. The strongest reported association between HDL-C and CETP variants, was rs3764261; however, after conditioning on the five novel variants we identified the support for rs3764261 was highly reduced (βunadjusted=3.179 mg/dl (P value=5.25×10−509), βadjusted=0.859 mg/dl (P value=9.51×10−25)), and this finding suggests that these five novel variants may partly explain the association of CETP with HDL-C. Indeed, three of the five novel variants (rs34065661, rs5817082, rs7499892) are independent of rs3764261.Conclusions:The causal variants in CETP that account for the association with HDL-C remain unknown. We used studies imputed to the 1000 Genomes reference panel for fine mapping of the CETP region. We identified and validated five variants within this region that may partly account for the association of the known variant (rs3764261), as well as other sources of genetic contribution to HDL-C.
    Full-text · Article · Nov 2015
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    ABSTRACT: Currently, next-generation sequencing studies aim to identify rare and low-frequency variation that may contribute to disease. For a given effect size, as the allele frequency decreases, the power to detect genes or variants of interest also decreases. Although many methods have been proposed for the analysis of such data, study design and analytic issues still persist in data interpretation. In this study we present sequencing data for ABCA1 that has known rare variants associated with high-density lipoprotein cholesterol (HDL-C). We contrast empirical findings from two study designs: a phenotypic extreme sample and a population-based random sample. We found differing strengths of association with HDL-C across the two study designs (P=0.0006 with n=701 phenotypic extremes vs P=0.03 with n=1600 randomly sampled individuals). To explore this apparent difference in evidence for association, we performed a simulation study focused on the impact of phenotypic selection on power. We demonstrate that the power gain for an extreme phenotypic selection study design is much greater in rare variant studies than for studies of common variants. Our study confirms that studying phenotypic extremes is critical in rare variant studies because it boosts power in two ways: the typical increases from extreme sampling and increasing the proportion of relevant functional variants ascertained and thereby tested for association. Furthermore, we show that when combining statistical evidence through meta-analysis from an extreme-selected sample and a second separate population-based random sample, power is lower when a traditional sample size weighting is used compared with weighting by the noncentrality parameter.European Journal of Human Genetics advance online publication, 9 September 2015; doi:10.1038/ejhg.2015.197.
    No preview · Article · Sep 2015 · European journal of human genetics: EJHG
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    ABSTRACT: The mechanisms underlying the association between diabetes and coronary artery disease (CAD) risk are unclear. We aimed to assess this association by studying genetic variants that have been shown to associate with type 2 diabetes (T2DM). If the association between diabetes and CAD is causal, we expected to observe an association of these variants with CAD as well. We studied all genetic variants currently known to be associated with T2DM at a genome-wide significant level (p < 5*10(-8)) in CARDIoGRAM, a genome-wide data-set of CAD including 22,233 CAD cases and 64,762 controls. Out of the 44 published T2DM SNPs 10 were significantly associated with CAD in CARDIoGRAM (OR>1, p < 0.05), more than expected by chance (p = 5.0*10(-5)). Considering all 44 SNPs, the average CAD risk observed per individual T2DM risk allele was 1.0076 (95% confidence interval (CI), 0.9973-1.0180). Such average risk increase was significantly lower than the increase expected based on i) the published effects of the SNPs on T2DM risk and ii) the effect of T2DM on CAD risk as observed in the Framingham Heart Study, which suggested a risk of 1.067 per allele (p = 7.2*10(-10) vs. the observed effect). Studying two risk scores based on risk alleles of the diabetes SNPs, one score using individual level data in 9856 subjects, and the second score on average effects of reported beta-coefficients from the entire CARDIoGRAM data-set, we again observed a significant - yet smaller than expected - association with CAD. Our data indicate that an association between type 2 diabetes related SNPs and CAD exists. However, the effects on CAD risk appear to be by far lower than what would be expected based on the effects of risk alleles on T2DM and the effect of T2DM on CAD in the epidemiological setting. Copyright © 2015. Published by Elsevier Ireland Ltd.
    No preview · Article · Jun 2015 · Atherosclerosis
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    Full-text · Dataset · May 2015
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    Full-text · Dataset · May 2015
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    ABSTRACT: Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value <6.61 × 10(-4)), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (βLDL-C=0.135, βTC=0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.
    Full-text · Article · Mar 2015 · Nature Communications
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    ABSTRACT: Author Summary Exome sequencing has proven powerful to identify protein-coding variation across the human genome, unravel the basis of monogenic diseases and discover rare alleles that confer risk for complex disease. Nevertheless, two key challenges limit its application to complex phenotypes: first, most alleles identified in a population are extremely rare; and second, most alleles are neutral on protein activities. Consequently, association tests that rely on enumerating rare alleles in cases and controls (termed rare variant association studies, RVAS) are typically underpowered, as the many neutral alleles dampen signals that arise from the few alleles that disrupt protein functions. Strategies to securely discriminate disruptive from neutral variants are immature, in particular for missense variants. Here we show that the statistical power of RVAS improves dramatically if variants are stratified according to their in vitro ascertained functions. We establish scalable technology to objectively profile the biological effects of exome-identified missense variants in the low-density lipoprotein receptor (LDLR) through systematic overexpression and complementation experiments in cells. We demonstrate that carriers of LDLR alleles, which our experiments identify as “disruptive-missense”, have higher plasma LDL-C, and that considering in vitro data may make it possible to reduce RVAS sample sizes by more than 2-fold.
    Full-text · Article · Feb 2015 · PLoS Genetics
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    ABSTRACT: Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
    Full-text · Article · Jan 2015 · Nature Communications
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    ABSTRACT: -Exome sequencing is a promising tool for gene mapping in Mendelian disorders. We utilized this technique in an attempt to identify novel genes underlying monogenic dyslipidemias. -We performed exome sequencing on 213 selected family members from 41 kindreds with suspected Mendelian inheritance of extreme levels of low-density lipoprotein (LDL) cholesterol (after candidate gene sequencing excluded known genetic causes for high LDL cholesterol families) or high-density lipoprotein (HDL) cholesterol. We used standard analytic approaches to identify candidate variants and also assigned a polygenic score to each individual in order to account for their burden of common genetic variants known to influence lipid levels. In nine families, we identified likely pathogenic variants in known lipid genes (ABCA1, APOB, APOE, LDLR, LIPA, and PCSK9); however, we were unable to identify obvious genetic etiologies in the remaining 32 families despite follow-up analyses. We identified three factors that limited novel gene discovery: (1) imperfect sequencing coverage across the exome hid potentially causal variants; (2) large numbers of shared rare alleles within families obfuscated causal variant identification; and (3) individuals from 15% of families carried a significant burden of common lipid-related alleles, suggesting complex inheritance can masquerade as monogenic disease. -We identified the genetic basis of disease in nine of 41 families; however, none of these represented novel gene discoveries. Our results highlight the promise and limitations of exome sequencing as a discovery technique in suspected monogenic dyslipidemias. Considering the confounders identified may inform the design of future exome sequencing studies.
    Full-text · Article · Jan 2015 · Circulation Cardiovascular Genetics
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    ABSTRACT: Myocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance. When MI occurs early in life, genetic inheritance is a major component to risk. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families, whereas common variants at more than 45 loci have been associated with MI risk in the population. Here we evaluate how rare mutations contribute to early-onset MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (≤50 years in males and ≤60 years in females) along with MI-free controls. We identified two genes in which rare coding-sequence mutations were more frequent in MI cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare non-synonymous mutations were at 4.2-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). Approximately 2% of early MI cases harbour a rare, damaging mutation in LDLR; this estimate is similar to one made more than 40 years ago using an analysis of total cholesterol16. Among controls, about 1 in 217 carried an LDLR coding-sequence mutation and had plasma LDL cholesterol > 190 mg dl−1. At apolipoprotein A-V (APOA5), carriers of rare non-synonymous mutations were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol, whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding-sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase15, 17 and apolipoprotein C-III. Combined, these observations suggest that, as well as LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.
    Full-text · Article · Dec 2014 · Nature
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    ABSTRACT: Background: Ezetimibe lowers plasma levels of low-density lipoprotein (LDL) cholesterol by inhibiting the activity of the Niemann-Pick C1-like 1 (NPC1L1) protein. However, whether such inhibition reduces the risk of coronary heart disease is not known. Human mutations that inactivate a gene encoding a drug target can mimic the action of an inhibitory drug and thus can be used to infer potential effects of that drug. Methods: We sequenced the exons of NPC1L1 in 7364 patients with coronary heart disease and in 14,728 controls without such disease who were of European, African, or South Asian ancestry. We identified carriers of inactivating mutations (nonsense, splice-site, or frameshift mutations). In addition, we genotyped a specific inactivating mutation (p.Arg406X) in 22,590 patients with coronary heart disease and in 68,412 controls. We tested the association between the presence of an inactivating mutation and both plasma lipid levels and the risk of coronary heart disease. Results: With sequencing, we identified 15 distinct NPC1L1 inactivating mutations; approximately 1 in every 650 persons was a heterozygous carrier for 1 of these mutations. Heterozygous carriers of NPC1L1 inactivating mutations had a mean LDL cholesterol level that was 12 mg per deciliter (0.31 mmol per liter) lower than that in noncarriers (P=0.04). Carrier status was associated with a relative reduction of 53% in the risk of coronary heart disease (odds ratio for carriers, 0.47; 95% confidence interval, 0.25 to 0.87; P=0.008). In total, only 11 of 29,954 patients with coronary heart disease had an inactivating mutation (carrier frequency, 0.04%) in contrast to 71 of 83,140 controls (carrier frequency, 0.09%). Conclusions: Naturally occurring mutations that disrupt NPC1L1 function were found to be associated with reduced plasma LDL cholesterol levels and a reduced risk of coronary heart disease. (Funded by the National Institutes of Health and others.).
    Full-text · Article · Nov 2014 · New England Journal of Medicine
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    ABSTRACT: Importance The association between sickle cell trait (SCT) and chronic kidney disease (CKD) is uncertain.Objective To describe the relationship between SCT and CKD and albuminuria in self-identified African Americans.Design, Setting, and Participants Using 5 large, prospective, US population-based studies (the Atherosclerosis Risk in Communities Study [ARIC, 1987-2013; n = 3402], Jackson Heart Study [JHS, 2000-2012; n = 2105], Coronary Artery Risk Development in Young Adults [CARDIA, 1985-2006; n = 848], Multi-Ethnic Study of Atherosclerosis [MESA, 2000-2012; n = 1620], and Women’s Health Initiative [WHI, 1993-2012; n = 8000]), we evaluated 15 975 self-identified African Americans (1248 participants with SCT [SCT carriers] and 14 727 participants without SCT [noncarriers]).Main Outcomes and Measures Primary outcomes were CKD (defined as an estimated glomerular filtration rate [eGFR] of <60 mL/min/1.73 m2 at baseline or follow-up), incident CKD, albuminuria (defined as a spot urine albumin:creatinine ratio of >30 mg/g or albumin excretion rate >30 mg/24 hours), and decline in eGFR (defined as a decrease of >3 mL/min/1.73 m2 per year). Effect sizes were calculated separately for each cohort and were subsequently meta-analyzed using a random-effects model.Results A total of 2233 individuals (239 of 1247 SCT carriers [19.2%] vs 1994 of 14 722 noncarriers [13.5%]) had CKD, 1298 (140 of 675 SCT carriers [20.7%] vs 1158 of 8481 noncarriers [13.7%]) experienced incident CKD, 1719 (150 of 665 SCT carriers [22.6%] vs 1569 of 8249 noncarriers [19.0%]) experienced decline in eGFR, and 1322 (154 of 485 SCT carriers [31.8%] vs 1168 of 5947 noncarriers [19.6%]) had albuminuria during the study period. Individuals with SCT had an increased risk of CKD (odds ratio [OR], 1.57 [95% CI, 1.34-1.84]; absolute risk difference [ARD], 7.6% [95% CI, 4.7%-10.8%]), incident CKD (OR, 1.79 [95% CI, 1.45-2.20]; ARD, 8.5% [95% CI, 5.1%-12.3%]), and decline in eGFR (OR, 1.32 [95% CI, 1.07-1.61]; ARD, 6.1% [95% CI, 1.4%-13.0%]) compared with noncarriers. Sickle cell trait was also associated with albuminuria (OR, 1.86 [95% CI, 1.49-2.31]; ARD, 12.6% [95% CI, 7.7%-17.7%]).Conclusions and Relevance Among African Americans in these cohorts, the presence of SCT was associated with an increased risk of CKD, decline in eGFR, and albuminuria, compared with noncarriers. These findings suggest that SCT may be associated with the higher risk of kidney disease in African Americans.
    Full-text · Article · Nov 2014 · JAMA The Journal of the American Medical Association
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    Full-text · Dataset · Nov 2014
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    ABSTRACT: Importance Plasma low-density lipoprotein cholesterol (LDL-C) has been associated with aortic stenosis in observational studies; however, randomized trials with cholesterol-lowering therapies in individuals with established valve disease have failed to demonstrate reduced disease progression.Objective To evaluate whether genetic data are consistent with an association between LDL-C, high-density lipoprotein cholesterol (HDL-C), or triglycerides (TG) and aortic valve disease.Design, Setting, and Participants Using a Mendelian randomization study design, we evaluated whether weighted genetic risk scores (GRSs), a measure of the genetic predisposition to elevations in plasma lipids, constructed using single-nucleotide polymorphisms identified in genome-wide association studies for plasma lipids, were associated with aortic valve disease. We included community-based cohorts participating in the CHARGE consortium (n = 6942), including the Framingham Heart Study (cohort inception to last follow-up: 1971-2013; n = 1295), Multi-Ethnic Study of Atherosclerosis (2000-2012; n = 2527), Age Gene/Environment Study–Reykjavik (2000-2012; n = 3120), and the Malmö Diet and Cancer Study (MDCS, 1991-2010; n = 28 461).Main Outcomes and Measures Aortic valve calcium quantified by computed tomography in CHARGE and incident aortic stenosis in the MDCS.Results The prevalence of aortic valve calcium across the 3 CHARGE cohorts was 32% (n = 2245). In the MDCS, over a median follow-up time of 16.1 years, aortic stenosis developed in 17 per 1000 participants (n = 473) and aortic valve replacement for aortic stenosis occurred in 7 per 1000 (n = 205). Plasma LDL-C, but not HDL-C or TG, was significantly associated with incident aortic stenosis (hazard ratio [HR] per mmol/L, 1.28; 95% CI, 1.04-1.57; P = .02; aortic stenosis incidence: 1.3% and 2.4% in lowest and highest LDL-C quartiles, respectively). The LDL-C GRS, but not HDL-C or TG GRS, was significantly associated with presence of aortic valve calcium in CHARGE (odds ratio [OR] per GRS increment, 1.38; 95% CI, 1.09-1.74; P = .007) and with incident aortic stenosis in MDCS (HR per GRS increment, 2.78; 95% CI, 1.22-6.37; P = .02; aortic stenosis incidence: 1.9% and 2.6% in lowest and highest GRS quartiles, respectively). In sensitivity analyses excluding variants weakly associated with HDL-C or TG, the LDL-C GRS remained associated with aortic valve calcium (P = .03) and aortic stenosis (P = .009). In instrumental variable analysis, LDL-C was associated with an increase in the risk of incident aortic stenosis (HR per mmol/L, 1.51; 95% CI, 1.07-2.14; P = .02).Conclusions and Relevance Genetic predisposition to elevated LDL-C was associated with presence of aortic valve calcium and incidence of aortic stenosis, providing evidence supportive of a causal association between LDL-C and aortic valve disease. Whether earlier intervention to reduce LDL-C could prevent aortic valve disease merits further investigation.
    Full-text · Article · Oct 2014 · JAMA The Journal of the American Medical Association

  • No preview · Article · Oct 2014 · The Canadian journal of cardiology
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    ABSTRACT: Background: Plasma lipid levels as well as coronary artery disease (CAD) have been shown to be highly heritable with estimates ranging from 40% to 60%. However, top variants detected by large-scale genome-wide association studies explain only a fraction of the total variance in plasma lipid phenotypes and CAD. Methods and results: We performed a conditional and joint association analysis using summary-level statistics from 2 large genome-wide association meta-analyses: the Global Lipids Genetics Consortium (GLGC) study, and the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) study. There were 100 184 individuals from 46 GLGC studies for plasma lipids, and 22 233 cases and 64 762 controls from 14 studies for CAD. We detected several loci where multiple independent single-nucleotide polymorphisms were associated with lipid traits within a locus (12 out of 33 loci for high-density lipoprotein cholesterol, 10 of 35 loci for low-density lipoprotein cholesterol, 13 of 44 loci for total cholesterol, and 8 of 28 loci for triglycerides), reaching genome-wide significance (P<5×10(-8)), nearly doubling the heritability explained by genome-wide association studies (from 3.6 to 7.6% for high-density lipoprotein cholesterol, from 5.0 to 8.8% for low-density lipoprotein cholesterol, from 5.5 to 8.8% for total cholesterol, and from 5.7 to 8.5% for triglycerides). Multiple single-nucleotide polymorphisms were also associated with CAD (3 of 15 loci; an increase from 9.6% to 11.4% of heritability explained). Conclusions: These results demonstrate that a portion of the missing heritability for lipid traits and CAD can be explained by multiple variants at each locus.
    Preview · Article · Aug 2014 · Circulation Cardiovascular Genetics

  • No preview · Article · Aug 2014 · Atherosclerosis
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    ABSTRACT: Background: Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype. Methods: We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons. Results: An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G→A and IVS3+1G→T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P=4×10(-6)). Conclusions: Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.).
    No preview · Article · Jul 2014 · New England Journal of Medicine

Publication Stats

5k Citations
910.16 Total Impact Points

Institutions

  • 2015
    • University of Pennsylvania
      Filadelfia, Pennsylvania, United States
  • 2012-2015
    • Massachusetts General Hospital
      • • Center for Human Genetic Research
      • • Cardiovascular Research Center
      Boston, Massachusetts, United States
    • National Heart, Lung, and Blood Institute
      베서스다, Maryland, United States
    • McGill University
      • Department of Epidemiology, Biostatistics and Occupational Health
      Montréal, Quebec, Canada
  • 2013-2014
    • Broad Institute of MIT and Harvard
      • Program in Medical and Population Genetics
      Cambridge, Massachusetts, United States
  • 2012-2014
    • Harvard University
      Cambridge, Massachusetts, United States
  • 2007-2013
    • Boston University
      • Department of Biostatistics
      Boston, Massachusetts, United States
  • 2009
    • University of Massachusetts Boston
      Boston, Massachusetts, United States