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1. Predicting the presence of coronary plaques featuring high-risk characteristics using polygenic risk scores and targeted proteomics in patients with suspected coronary artery disease.

Author

Møller PL, Rohde PD, Dahl JN, Rasmussen LD, Nissen L, Schmidt SE, McGilligan V, Gudbjartsson DF, Stefansson K, Holm H, Bentzon JF, Bøttcher M, Winther S, and Nyegaard M

Subjects
Humans, Genetic Risk Score, Proteomics, Coronary Angiography methods, Risk Factors, Coronary Artery Disease diagnosis, Coronary Artery Disease genetics, Plaque, Atherosclerotic genetics, Plaque, Atherosclerotic complications
Abstract

Background: The presence of coronary plaques with high-risk characteristics is strongly associated with adverse cardiac events beyond the identification of coronary stenosis. Testing by coronary computed tomography angiography (CCTA) enables the identification of high-risk plaques (HRP). Referral for CCTA is presently based on pre-test probability estimates including clinical risk factors (CRFs); however, proteomics and/or genetic information could potentially improve patient selection for CCTA and, hence, identification of HRP. We aimed to (1) identify proteomic and genetic features associated with HRP presence and (2) investigate the effect of combining CRFs, proteomics, and genetics to predict HRP presence., Methods: Consecutive chest pain patients (n = 1462) undergoing CCTA to diagnose obstructive coronary artery disease (CAD) were included. Coronary plaques were assessed using a semi-automatic plaque analysis tool. Measurements of 368 circulating proteins were obtained with targeted Olink panels, and DNA genotyping was performed in all patients. Imputed genetic variants were used to compute a multi-trait multi-ancestry genome-wide polygenic score (GPS Mult ). HRP presence was defined as plaques with two or more high-risk characteristics (low attenuation, spotty calcification, positive remodeling, and napkin ring sign). Prediction of HRP presence was performed using the glmnet algorithm with repeated fivefold cross-validation, using CRFs, proteomics, and GPS Mult as input features., Results: HRPs were detected in 165 (11%) patients, and 15 input features were associated with HRP presence. Prediction of HRP presence based on CRFs yielded a mean area under the receiver operating curve (AUC) ± standard error of 73.2 ± 0.1, versus 69.0 ± 0.1 for proteomics and 60.1 ± 0.1 for GPS Mult . Combining CRFs with GPS Mult increased prediction accuracy (AUC 74.8 ± 0.1 (P = 0.004)), while the inclusion of proteomics provided no significant improvement to either the CRF (AUC 73.2 ± 0.1, P = 1.00) or the CRF + GPS Mult (AUC 74.6 ± 0.1, P = 1.00) models, respectively., Conclusions: In patients with suspected CAD, incorporating genetic data with either clinical or proteomic data improves the prediction of high-risk plaque presence., Trial Registration: https://clinicaltrials.gov/ct2/show/NCT02264717 (September 2014)., (© 2024. The Author(s).)

Published
2024
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2. Combining Polygenic and Proteomic Risk Scores With Clinical Risk Factors to Improve Performance for Diagnosing Absence of Coronary Artery Disease in Patients With de novo Chest Pain.

Author

Møller PL, Rohde PD, Dahl JN, Rasmussen LD, Schmidt SE, Nissen L, McGilligan V, Bentzon JF, Gudbjartsson DF, Stefansson K, Holm H, Winther S, Bøttcher M, and Nyegaard M

Subjects
Humans, Proteomics, Prospective Studies, Coronary Angiography methods, Risk Factors, Chest Pain diagnosis, Chest Pain genetics, Coronary Artery Disease diagnosis, Coronary Artery Disease genetics
Abstract

Background: Patients with de novo chest pain, referred for evaluation of possible coronary artery disease (CAD), frequently have an absence of CAD resulting in millions of tests not having any clinical impact. The objective of this study was to investigate whether polygenic risk scores and targeted proteomics improve the prediction of absence of CAD in patients with suspected CAD, when added to the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) minimal risk score (PMRS)., Methods: Genotyping and targeted plasma proteomics (N=368 proteins) were performed in 1440 patients with symptoms suspected to be caused by CAD undergoing coronary computed tomography angiography. Based on individual genotypes, a polygenic risk score for CAD (PRS CAD ) was calculated. The prediction was performed using combinations of PRS CAD , proteins, and PMRS as features in models using stability selection and machine learning., Results: Prediction of absence of CAD yielded an area under the curve of PRS CAD -model, 0.64±0.03; proteomic-model, 0.58±0.03; and PMRS model, 0.76±0.02. No significant correlation was found between the genetic and proteomic risk scores (Pearson correlation coefficient, -0.04; P =0.13). Optimal predictive ability was achieved by the full model (PRS CAD +protein+PMRS) yielding an area under the curve of 0.80±0.02 for absence of CAD, significantly better than the PMRS model alone ( P <0.001). For reclassification purpose, the full model enabled down-classification of 49% (324 of 661) of the 5% to 15% pretest probability patients and 18% (113 of 611) of >15% pretest probability patients., Conclusions: For patients with chest pain and low-intermediate CAD risk, incorporating targeted proteomics and polygenic risk scores into the risk assessment substantially improved the ability to predict the absence of CAD. Genetics and proteomics seem to add complementary information to the clinical risk factors and improve risk stratification in this large patient group., Registration: URL: https://www., Clinicaltrials: gov; Unique identifier: NCT02264717., Competing Interests: Disclosures Dr Bøttcher discloses advisory board participation for NOVO Nordisk, Astra-Zeneca, Pfizer, Boehringer Ingelheim, Bayer, Sanofi, Novartis, AMGEN, CLS-Behring, and Acarix. Dr Schmidt is a part-time consultant in Acarix and minor shareholder of Acarix. Drs Gudbjartsson, Stefansson, and Holm are employees of deCODE genetics/Amgen, Inc. The other authors report no conflicts.

Published
2023
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3. Complex effects of sequence variants on lipid levels and coronary artery disease.

Author

Snaebjarnarson AS, Helgadottir A, Arnadottir GA, Ivarsdottir EV, Thorleifsson G, Ferkingstad E, Einarsson G, Sveinbjornsson G, Thorgeirsson TE, Ulfarsson MO, Halldorsson BV, Olafsson I, Erikstrup C, Pedersen OB, Nyegaard M, Bruun MT, Ullum H, Brunak S, Iversen KK, Christensen AH, Olesen MS, Ghouse J, Banasik K, Knowlton KU, Arnar DO, Thorgeirsson G, Nadauld L, Ostrowski SR, Bundgaard H, Holm H, Sulem P, Stefansson K, and Gudbjartsson DF

Subjects
Animals, Humans, Epistasis, Genetic, Phenotype, Lipids blood, ABO Blood-Group System, Coronary Artery Disease blood, Coronary Artery Disease genetics
Abstract

Many sequence variants have additive effects on blood lipid levels and, through that, on the risk of coronary artery disease (CAD). We show that variants also have non-additive effects and interact to affect lipid levels as well as affecting variance and correlations. Variance and correlation effects are often signatures of epistasis or gene-environmental interactions. These complex effects can translate into CAD risk. For example, Trp154Ter in FUT2 protects against CAD among subjects with the A1 blood group, whereas it associates with greater risk of CAD in others. His48Arg in ADH1B interacts with alcohol consumption to affect lipid levels and CAD. The effect of variants in TM6SF2 on blood lipids is greatest among those who never eat oily fish but absent from those who often do. This work demonstrates that variants that affect variance of quantitative traits can allow for the discovery of epistasis and interactions of variants with the environment., Competing Interests: Declaration of interests The authors affiliated with deCODE genetics/Amgen, Inc. are employed by the company., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Published
2023
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4. Cholesterol not particle concentration mediates the atherogenic risk conferred by apolipoprotein B particles: a Mendelian randomization analysis.

Author

Helgadottir A, Thorleifsson G, Snaebjarnarson A, Stefansdottir L, Sveinbjornsson G, Tragante V, Björnsson E, Steinthorsdottir V, Gretarsdottir S, Helgason H, Saemundsdottir J, Olafsson I, Thune JJ, Raja AA, Ghouse J, Olesen MS, Christensen A, Jacobsen RL, Dowsett J, Bruun MT, Nielsen K, Knowlton K, Nadauld L, Benediktsson R, Erikstrup C, Pedersen OB, Banasik K, Brunak S, Bundgaard H, Ostrowski SR, Sulem P, Arnar DO, Thorgeirsson G, Thorsteinsdottir U, Gudbjartsson DF, Stefansson K, and Holm H

Subjects
Humans, Mendelian Randomization Analysis, Cholesterol, LDL, Risk Factors, Cholesterol, Apolipoproteins B genetics, Lipoproteins, Cholesterol, HDL, Apolipoprotein B-100 genetics, Coronary Artery Disease genetics, Atherosclerosis
Abstract

Background and Aims: The causal contribution of apolipoprotein B (apoB) particles to coronary artery disease (CAD) is established. We examined whether this atherogenic contribution is better reflected by non-high-density lipoprotein cholesterol (non-HDL-C) or apoB particle concentration., Method and Results: We performed Mendelian randomization (MR) analysis using 235 variants as genetic instruments; testing the relationship between their effects on the exposures, non-HDL-C and apoB, and on the outcome CAD using weighted regression. Variant effect estimates on the exposures came from the UK Biobank (N = 376 336) and on the outcome from a meta-analysis of five CAD datasets (187 451 cases and 793 315 controls). Subsequently, we carried out sensitivity and replication analyses.In univariate MR analysis, both exposures associated with CAD (βnon-HDL-C = 0.40, P = 2.8 × 10-48 and βapoB = 0.38, P = 1.3 × 10-44). Adding effects on non-HDL-C into a model that already included those on apoB significantly improved the genetically predicted CAD effects (P = 3.9 × 10-5), while adding apoB into the model including non-HDL-C did not (P = 0.69). Thirty-five per cent (82/235) of the variants used as genetic instruments had discordant effects on the exposures, associating with non-HDL-C/apoB ratio at P < 2.1 × 10-4 (0.05/235). Fifty-one variants associated at genome-wide significance., Conclusion: Many sequence variants have discordant effects on non-HDL-C and apoB. These variants allowed us to show that the causal mechanism underlying the relationship between apolipoprotein B particles and CAD is more associated with non-HDL-C than apoB particle concentration., Competing Interests: Conflict of interest: The following authors affiliated with deCODE genetics/Amgen, Inc., are employed by the company: A.H., G.Th., A.S., L.S., G.S., V.T., E.B., V.S., S.G., H.H., J.S., P.S., D.O.A., G.T., U.T., D.F.G., K.S, and H.H., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Published
2022
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5. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants.

Author

Aragam KG, Jiang T, Goel A, Kanoni S, Wolford BN, Atri DS, Weeks EM, Wang M, Hindy G, Zhou W, Grace C, Roselli C, Marston NA, Kamanu FK, Surakka I, Venegas LM, Sherliker P, Koyama S, Ishigaki K, Åsvold BO, Brown MR, Brumpton B, de Vries PS, Giannakopoulou O, Giardoglou P, Gudbjartsson DF, Güldener U, Haider SMI, Helgadottir A, Ibrahim M, Kastrati A, Kessler T, Kyriakou T, Konopka T, Li L, Ma L, Meitinger T, Mucha S, Munz M, Murgia F, Nielsen JB, Nöthen MM, Pang S, Reinberger T, Schnitzler G, Smedley D, Thorleifsson G, von Scheidt M, Ulirsch JC, Arnar DO, Burtt NP, Costanzo MC, Flannick J, Ito K, Jang DK, Kamatani Y, Khera AV, Komuro I, Kullo IJ, Lotta LA, Nelson CP, Roberts R, Thorgeirsson G, Thorsteinsdottir U, Webb TR, Baras A, Björkegren JLM, Boerwinkle E, Dedoussis G, Holm H, Hveem K, Melander O, Morrison AC, Orho-Melander M, Rallidis LS, Ruusalepp A, Sabatine MS, Stefansson K, Zalloua P, Ellinor PT, Farrall M, Danesh J, Ruff CT, Finucane HK, Hopewell JC, Clarke R, Gupta RM, Erdmann J, Samani NJ, Schunkert H, Watkins H, Willer CJ, Deloukas P, Kathiresan S, and Butterworth AS

Subjects
Humans, Genome-Wide Association Study, Coronary Artery Disease genetics
Abstract

The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD., (© 2022. The Author(s).)

Published
2022
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6. Genetic variability in the absorption of dietary sterols affects the risk of coronary artery disease.

Author

Helgadottir A, Thorleifsson G, Alexandersson KF, Tragante V, Thorsteinsdottir M, Eiriksson FF, Gretarsdottir S, Björnsson E, Magnusson O, Sveinbjornsson G, Jonsdottir I, Steinthorsdottir V, Ferkingstad E, Jensson BÖ, Stefansson H, Olafsson I, Christensen AH, Torp-Pedersen C, Køber L, Pedersen OB, Erikstrup C, Sørensen E, Brunak S, Banasik K, Hansen TF, Nyegaard M, Eyjolfssson GI, Sigurdardottir O, Thorarinsson BL, Matthiasson SE, Steingrimsdottir T, Bjornsson ES, Danielsen R, Asselbergs FW, Arnar DO, Ullum H, Bundgaard H, Sulem P, Thorsteinsdottir U, Thorgeirsson G, Holm H, Gudbjartsson DF, and Stefansson K

Subjects
ATP Binding Cassette Transporter, Subfamily G, Member 5 genetics, Humans, Iceland, Sterols, Coronary Artery Disease epidemiology, Coronary Artery Disease genetics, Phytosterols
Abstract

Aims: To explore whether variability in dietary cholesterol and phytosterol absorption impacts the risk of coronary artery disease (CAD) using as instruments sequence variants in the ABCG5/8 genes, key regulators of intestinal absorption of dietary sterols., Methods and Results: We examined the effects of ABCG5/8 variants on non-high-density lipoprotein (non-HDL) cholesterol (N up to 610 532) and phytosterol levels (N = 3039) and the risk of CAD in Iceland, Denmark, and the UK Biobank (105 490 cases and 844 025 controls). We used genetic scores for non-HDL cholesterol to determine whether ABCG5/8 variants confer greater risk of CAD than predicted by their effect on non-HDL cholesterol. We identified nine rare ABCG5/8 coding variants with substantial impact on non-HDL cholesterol. Carriers have elevated phytosterol levels and are at increased risk of CAD. Consistent with impact on ABCG5/8 transporter function in hepatocytes, eight rare ABCG5/8 variants associate with gallstones. A genetic score of ABCG5/8 variants predicting 1 mmol/L increase in non-HDL cholesterol associates with two-fold increase in CAD risk [odds ratio (OR) = 2.01, 95% confidence interval (CI) 1.75-2.31, P = 9.8 × 10-23] compared with a 54% increase in CAD risk (OR = 1.54, 95% CI 1.49-1.59, P = 1.1 × 10-154) associated with a score of other non-HDL cholesterol variants predicting the same increase in non-HDL cholesterol (P for difference in effects = 2.4 × 10-4)., Conclusions: Genetic variation in cholesterol absorption affects levels of circulating non-HDL cholesterol and risk of CAD. Our results indicate that both dietary cholesterol and phytosterols contribute directly to atherogenesis., (© The Author(s) 2020. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Published
2020
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7. Genetic Risk of Coronary Artery Disease, Features of Atherosclerosis, and Coronary Plaque Burden.

Author

Christiansen MK, Nissen L, Winther S, Møller PL, Frost L, Johansen JK, Jensen HK, Guðbjartsson D, Holm H, Stefánsson K, Bøtker HE, Bøttcher M, and Nyegaard M

Subjects
Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease diagnostic imaging, Denmark, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Heart Disease Risk Factors, Humans, Male, Middle Aged, Multidetector Computed Tomography, Phenotype, Prognosis, Risk Assessment, Severity of Illness Index, Coronary Artery Disease genetics, Multifactorial Inheritance, Plaque, Atherosclerotic
Abstract

Background Polygenic risk scores (PRSs) based on risk variants from genome-wide association studies predict coronary artery disease (CAD) risk. However, it is unknown whether the PRS is associated with specific CAD characteristics. Methods and Results We consecutively included 1645 patients with suspected stable CAD undergoing coronary computed tomography angiography. A multilocus PRS was calculated as the weighted sum of CAD risk variants. Plaques were evaluated using an 18-segment model and characterized by stenosis severity and composition (soft [0%-19% calcified], mixed-soft [20%-49% calcified], mixed-calcified [50%-79% calcified], or calcified [≥80% calcified]). Coronary artery calcium score and segment stenosis score were used to characterize plaque burden. For each standard deviation increase in the PRS, coronary artery calcium score increased by 78% ( P =4.1e-26) and segment stenosis score increased by 16% ( P =2.4e-29) in the fully adjusted model. The PRS was associated with a higher prevalence of obstructive plaques (odds ratio [OR ] : 1.78, P =5.6e-16), calcified (OR: 1.69, P =6.5e-17), mixed-calcified (OR: 1.67, P =7.3e-9), mixed-soft (OR: 1.45, P =1.6e-6), and soft plaques (OR: 1.49, P =2.5e-6), and a higher prevalence of plaque in each coronary vessel (all P <1.0e-4). However, when analyzing data on a plaque level (3007 segments with plaque in 849 patients) the PRS was not associated with stenosis severity, plaque composition, or localization (all P >0.05). Conclusions Our results suggest that polygenic risk based on large genome-wide association studies increases CAD risk through an increased burden of coronary atherosclerosis rather than promoting specific plaque features. Clinical Trial Registration URL: https://www.clinicaltrials.gov. Unique identifier: NCT02264717.

Published
2020
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8. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure.

Author

Shah S, Henry A, Roselli C, Lin H, Sveinbjörnsson G, Fatemifar G, Hedman ÅK, Wilk JB, Morley MP, Chaffin MD, Helgadottir A, Verweij N, Dehghan A, Almgren P, Andersson C, Aragam KG, Ärnlöv J, Backman JD, Biggs ML, Bloom HL, Brandimarto J, Brown MR, Buckbinder L, Carey DJ, Chasman DI, Chen X, Chen X, Chung J, Chutkow W, Cook JP, Delgado GE, Denaxas S, Doney AS, Dörr M, Dudley SC, Dunn ME, Engström G, Esko T, Felix SB, Finan C, Ford I, Ghanbari M, Ghasemi S, Giedraitis V, Giulianini F, Gottdiener JS, Gross S, Guðbjartsson DF, Gutmann R, Haggerty CM, van der Harst P, Hyde CL, Ingelsson E, Jukema JW, Kavousi M, Khaw KT, Kleber ME, Køber L, Koekemoer A, Langenberg C, Lind L, Lindgren CM, London B, Lotta LA, Lovering RC, Luan J, Magnusson P, Mahajan A, Margulies KB, März W, Melander O, Mordi IR, Morgan T, Morris AD, Morris AP, Morrison AC, Nagle MW, Nelson CP, Niessner A, Niiranen T, O'Donoghue ML, Owens AT, Palmer CNA, Parry HM, Perola M, Portilla-Fernandez E, Psaty BM, Rice KM, Ridker PM, Romaine SPR, Rotter JI, Salo P, Salomaa V, van Setten J, Shalaby AA, Smelser DT, Smith NL, Stender S, Stott DJ, Svensson P, Tammesoo ML, Taylor KD, Teder-Laving M, Teumer A, Thorgeirsson G, Thorsteinsdottir U, Torp-Pedersen C, Trompet S, Tyl B, Uitterlinden AG, Veluchamy A, Völker U, Voors AA, Wang X, Wareham NJ, Waterworth D, Weeke PE, Weiss R, Wiggins KL, Xing H, Yerges-Armstrong LM, Yu B, Zannad F, Zhao JH, Hemingway H, Samani NJ, McMurray JJV, Yang J, Visscher PM, Newton-Cheh C, Malarstig A, Holm H, Lubitz SA, Sattar N, Holmes MV, Cappola TP, Asselbergs FW, Hingorani AD, Kuchenbaecker K, Ellinor PT, Lang CC, Stefansson K, Smith JG, Vasan RS, Swerdlow DI, and Lumbers RT

Subjects
Adaptor Proteins, Signal Transducing genetics, Apoptosis Regulatory Proteins genetics, Cardiomyopathies pathology, Carrier Proteins genetics, Case-Control Studies, Cyclin-Dependent Kinase Inhibitor p21 genetics, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Microfilament Proteins genetics, Muscle Proteins genetics, Risk Factors, Atrial Fibrillation genetics, Cardiomyopathies genetics, Coronary Artery Disease genetics, Heart Failure genetics, Heart Failure pathology, Ventricular Function, Left genetics
Abstract

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.

Published
2020
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9. Lipoprotein(a) Concentration and Risks of Cardiovascular Disease and Diabetes.

Author

Gudbjartsson DF, Thorgeirsson G, Sulem P, Helgadottir A, Gylfason A, Saemundsdottir J, Bjornsson E, Norddahl GL, Jonasdottir A, Jonasdottir A, Eggertsson HP, Gretarsdottir S, Thorleifsson G, Indridason OS, Palsson R, Jonasson F, Jonsdottir I, Eyjolfsson GI, Sigurdardottir O, Olafsson I, Danielsen R, Matthiasson SE, Kristmundsdottir S, Halldorsson BV, Hreidarsson AB, Valdimarsson EM, Gudnason T, Benediktsson R, Steinthorsdottir V, Thorsteinsdottir U, Holm H, and Stefansson K

Subjects
Case-Control Studies, Coronary Artery Disease genetics, Diabetes Mellitus, Type 2 genetics, Humans, Iceland, Kringles, Lipoprotein(a) genetics, Mendelian Randomization Analysis, Molecular Weight, Protein Isoforms blood, Risk Factors, Coronary Artery Disease blood, DNA Copy Number Variations, Diabetes Mellitus, Type 2 blood, Lipoprotein(a) blood
Abstract

Background: Lipoprotein(a) [Lp(a)] is a causal risk factor for cardiovascular diseases that has no established therapy. The attribute of Lp(a) that affects cardiovascular risk is not established. Low levels of Lp(a) have been associated with type 2 diabetes (T2D)., Objectives: This study investigated whether cardiovascular risk is conferred by Lp(a) molar concentration or apolipoprotein(a) [apo(a)] size, and whether the relationship between Lp(a) and T2D risk is causal., Methods: This was a case-control study of 143,087 Icelanders with genetic information, including 17,715 with coronary artery disease (CAD) and 8,734 with T2D. This study used measured and genetically imputed Lp(a) molar concentration, kringle IV type 2 (KIV-2) repeats (which determine apo(a) size), and a splice variant in LPA associated with small apo(a) but low Lp(a) molar concentration to disentangle the relationship between Lp(a) and cardiovascular risk. Loss-of-function homozygotes and other subjects genetically predicted to have low Lp(a) levels were evaluated to assess the relationship between Lp(a) and T2D., Results: Lp(a) molar concentration was associated dose-dependently with CAD risk, peripheral artery disease, aortic valve stenosis, heart failure, and lifespan. Lp(a) molar concentration fully explained the Lp(a) association with CAD, and there was no residual association with apo(a) size. Homozygous carriers of loss-of-function mutations had little or no Lp(a) and increased the risk of T2D., Conclusions: Molar concentration is the attribute of Lp(a) that affects risk of cardiovascular diseases. Low Lp(a) concentration (bottom 10%) increases T2D risk. Pharmacologic reduction of Lp(a) concentration in the 20% of individuals with the greatest concentration down to the population median is predicted to decrease CAD risk without increasing T2D risk., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2019
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10. Rare SCARB1 mutations associate with high-density lipoprotein cholesterol but not with coronary artery disease.

Author

Helgadottir A, Sulem P, Thorgeirsson G, Gretarsdottir S, Thorleifsson G, Jensson BÖ, Arnadottir GA, Olafsson I, Eyjolfsson GI, Sigurdardottir O, Thorsteinsdottir U, Gudbjartsson DF, Holm H, and Stefansson K

Subjects
Humans, Iceland, Liver metabolism, Mutation, Cholesterol, HDL metabolism, Coronary Artery Disease genetics, Scavenger Receptors, Class B genetics
Abstract

Aims: Scavenger receptor Class B Type 1 (SR-BI) is a major receptor for high-density lipoprotein (HDL) that promotes hepatic uptake of cholesterol from HDL. A rare mutation p.P376L, in the gene encoding SR-BI, SCARB1, was recently reported to associate with elevated HDL cholesterol (HDL-C) and increased risk of coronary artery disease (CAD), suggesting that increased HDL-C caused by SR-BI impairment might be an independent marker of cardiovascular risk. We tested the hypothesis that alleles in or close to SCARB1 that associate with elevated levels of HDL-C also associate with increased risk of CAD in the relatively homogeneous population of Iceland., Methods and Results: Using a large resource of whole-genome sequenced Icelanders, we identified thirteen SCARB1 coding mutations that we examined for association with HDL-C (n = 136 672). Three rare SCARB1 mutations, encoding p.G319V, p.V111M, and p.V32M (combined allelic frequency = 0.2%) associate with elevated levels of HDL-C (p.G319V: β = 11.1 mg/dL, P = 8.0 × 10-7; p.V111M: β = 8.3 mg/dL, P = 1.1 × 10-6; p.V32M: β = 10.2 mg/dL, P = 8.1 × 10-4). These mutations do not associate with CAD (36 886 cases/306 268 controls) (odds ratio = 0.90, 95% confidence interval 0.67-1.22, P = 0.49), despite effects on HDL-C comparable to that reported for p.P376L, both in terms of direction and magnitude. Furthermore, HDL-C raising alleles of three common SCARB1 non-coding variants, including one previously unreported (rs61941676-C: β = 1.25 mg/dL, P = 1.7 × 10-18), and of one low frequency coding variant (p.V135I) that independently associate with higher HDL-C, do not confer increased risk of CAD., Conclusion: Elevated HDL-C due to genetically compromised SR-BI function is not a marker of CAD risk.

Published
2018
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11. A rare splice donor mutation in the haptoglobin gene associates with blood lipid levels and coronary artery disease.

Author

Bjornsson E, Helgason H, Halldorsson G, Helgadottir A, Gylfason A, Kehr B, Jonasdottir A, Jonasdottir A, Sigurdsson A, Oddsson A, Thorleifsson G, Magnusson OT, Gretarsdottir S, Zink F, Kristjansson RP, Asgeirsdottir M, Swinkels DW, Kiemeney LA, Eyjolfsson GI, Sigurdardottir O, Masson G, Olafsson I, Thorgeirsson G, Holm H, Thorsteinsdottir U, Gudbjartsson DF, Sulem P, and Stefansson K

Subjects
Adult, Alleles, Base Sequence, Coronary Artery Disease metabolism, DNA Copy Number Variations genetics, Female, Gene Frequency genetics, Genetic Association Studies methods, Genetic Variation, Haptoglobins metabolism, Humans, Iceland, Lipids blood, Lipids genetics, Lipoproteins genetics, Male, Mutation, Odds Ratio, RNA Splice Sites genetics, Risk Factors, Coronary Artery Disease genetics, Haptoglobins genetics
Abstract

Common sequence variants at the haptoglobin gene (HP) have been associated with blood lipid levels. Through whole-genome sequencing of 8,453 Icelanders, we discovered a splice donor founder mutation in HP (NM&#95;001126102.1:c.190 + 1G > C, minor allele frequency = 0.56%). This mutation occurs on the HP1 allele of the common copy number variant in HP and leads to a loss of function of HP1. It associates with lower levels of haptoglobin (P = 2.1 × 10-54), higher levels of non-high density lipoprotein cholesterol (β = 0.26 mmol/l, P = 2.6 × 10-9) and greater risk of coronary artery disease (odds ratio = 1.30, 95% confidence interval: 1.10-1.54, P = 0.0024). Through haplotype analysis and with RNA sequencing, we provide evidence of a causal relationship between one of the two haptoglobin isoforms, namely Hp1, and lower levels of non-HDL cholesterol. Furthermore, we show that the HP1 allele associates with various other quantitative biological traits., (© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Published
2017
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12. Variant ASGR1 Associated with a Reduced Risk of Coronary Artery Disease.

Author

Nioi P, Sigurdsson A, Thorleifsson G, Helgason H, Agustsdottir AB, Norddahl GL, Helgadottir A, Magnusdottir A, Jonasdottir A, Gretarsdottir S, Jonsdottir I, Steinthorsdottir V, Rafnar T, Swinkels DW, Galesloot TE, Grarup N, Jørgensen T, Vestergaard H, Hansen T, Lauritzen T, Linneberg A, Friedrich N, Krarup NT, Fenger M, Abildgaard U, Hansen PR, Galløe AM, Braund PS, Nelson CP, Hall AS, Williams MJ, van Rij AM, Jones GT, Patel RS, Levey AI, Hayek S, Shah SH, Reilly M, Eyjolfsson GI, Sigurdardottir O, Olafsson I, Kiemeney LA, Quyyumi AA, Rader DJ, Kraus WE, Samani NJ, Pedersen O, Thorgeirsson G, Masson G, Holm H, Gudbjartsson D, Sulem P, Thorsteinsdottir U, and Stefansson K

Subjects
Adult, Aged, Aged, 80 and over, Base Sequence, Female, Genetic Predisposition to Disease, Humans, Iceland, Kaplan-Meier Estimate, Male, Middle Aged, Molecular Sequence Data, Myocardial Infarction genetics, Risk, Sequence Analysis, DNA, White People genetics, Asialoglycoprotein Receptor genetics, Cholesterol blood, Coronary Artery Disease genetics, Haploinsufficiency
Abstract

Background: Several sequence variants are known to have effects on serum levels of non-high-density lipoprotein (HDL) cholesterol that alter the risk of coronary artery disease., Methods: We sequenced the genomes of 2636 Icelanders and found variants that we then imputed into the genomes of approximately 398,000 Icelanders. We tested for association between these imputed variants and non-HDL cholesterol levels in 119,146 samples. We then performed replication testing in two populations of European descent. We assessed the effects of an implicated loss-of-function variant on the risk of coronary artery disease in 42,524 case patients and 249,414 controls from five European ancestry populations. An augmented set of genomes was screened for additional loss-of-function variants in a target gene. We evaluated the effect of an implicated variant on protein stability., Results: We found a rare noncoding 12-base-pair (bp) deletion (del12) in intron 4 of ASGR1, which encodes a subunit of the asialoglycoprotein receptor, a lectin that plays a role in the homeostasis of circulating glycoproteins. The del12 mutation activates a cryptic splice site, leading to a frameshift mutation and a premature stop codon that renders a truncated protein prone to degradation. Heterozygous carriers of the mutation (1 in 120 persons in our study population) had a lower level of non-HDL cholesterol than noncarriers, a difference of 15.3 mg per deciliter (0.40 mmol per liter) (P=1.0×10(-16)), and a lower risk of coronary artery disease (by 34%; 95% confidence interval, 21 to 45; P=4.0×10(-6)). In a larger set of sequenced samples from Icelanders, we found another loss-of-function ASGR1 variant (p.W158X, carried by 1 in 1850 persons) that was also associated with lower levels of non-HDL cholesterol (P=1.8×10(-3))., Conclusions: ASGR1 haploinsufficiency was associated with reduced levels of non-HDL cholesterol and a reduced risk of coronary artery disease. (Funded by the National Institutes of Health and others.).

Published
2016
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13. Variants with large effects on blood lipids and the role of cholesterol and triglycerides in coronary disease.

Author

Helgadottir A, Gretarsdottir S, Thorleifsson G, Hjartarson E, Sigurdsson A, Magnusdottir A, Jonasdottir A, Kristjansson H, Sulem P, Oddsson A, Sveinbjornsson G, Steinthorsdottir V, Rafnar T, Masson G, Jonsdottir I, Olafsson I, Eyjolfsson GI, Sigurdardottir O, Daneshpour MS, Khalili D, Azizi F, Swinkels DW, Kiemeney L, Quyyumi AA, Levey AI, Patel RS, Hayek SS, Gudmundsdottir IJ, Thorgeirsson G, Thorsteinsdottir U, Gudbjartsson DF, Holm H, and Stefansson K

Subjects
Coronary Artery Disease blood, Coronary Artery Disease diagnosis, Humans, Cholesterol blood, Coronary Artery Disease genetics, Lipids blood, Triglycerides blood
Abstract

Sequence variants affecting blood lipids and coronary artery disease (CAD) may enhance understanding of the atherogenicity of lipid fractions. Using a large resource of whole-genome sequence data, we examined rare and low-frequency variants for association with non-HDL cholesterol, HDL cholesterol, LDL cholesterol, and triglycerides in up to 119,146 Icelanders. We discovered 13 variants with large effects (within ANGPTL3, APOB, ABCA1, NR1H3, APOA1, LIPC, CETP, LDLR, and APOC1) and replicated 14 variants. Five variants within PCSK9, APOA1, ANGPTL4, and LDLR associate with CAD (33,090 cases and 236,254 controls). We used genetic risk scores for the lipid fractions to examine their causal relationship with CAD. The non-HDL cholesterol genetic risk score associates most strongly with CAD (P = 2.7 × 10(-28)), and no other genetic risk score associates with CAD after accounting for non-HDL cholesterol. The genetic risk score for non-HDL cholesterol confers CAD risk beyond that of LDL cholesterol (P = 5.5 × 10(-8)), suggesting that targeting atherogenic remnant cholesterol may reduce cardiovascular risk.

Published
2016
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14. A Splice Region Variant in LDLR Lowers Non-high Density Lipoprotein Cholesterol and Protects against Coronary Artery Disease.

Author

Gretarsdottir S, Helgason H, Helgadottir A, Sigurdsson A, Thorleifsson G, Magnusdottir A, Oddsson A, Steinthorsdottir V, Rafnar T, de Graaf J, Daneshpour MS, Hedayati M, Azizi F, Grarup N, Jørgensen T, Vestergaard H, Hansen T, Eyjolfsson G, Sigurdardottir O, Olafsson I, Kiemeney LA, Pedersen O, Sulem P, Thorgeirsson G, Gudbjartsson DF, Holm H, Thorsteinsdottir U, and Stefansson K

Subjects
Humans, RNA, Messenger genetics, Cholesterol blood, Coronary Artery Disease prevention & control, RNA Splicing, Receptors, LDL genetics
Abstract

Through high coverage whole-genome sequencing and imputation of the identified variants into a large fraction of the Icelandic population, we found four independent signals in the low density lipoprotein receptor gene (LDLR) that associate with levels of non-high density lipoprotein cholesterol (non-HDL-C) and coronary artery disease (CAD). Two signals are novel with respect to association with non-HDL-C and are represented by non-coding low frequency variants (between 2-4% frequency), the splice region variant rs72658867-A in intron 14 and rs17248748-T in intron one. These two novel associations were replicated in three additional populations. Both variants lower non-HDL-C levels (rs72658867-A, non-HDL-C effect = -0.44 mmol/l, Padj = 1.1 × 10⁻⁸⁰ and rs17248748-T, non-HDL-C effect = -0.13 mmol/l, Padj = 1.3 × 10⁻¹²) and confer protection against CAD (rs72658867-A, OR = 0.76 and Padj = 2.7 × 10⁻⁸ and rs17248748-T, OR = 0.92 and Padj = 0.022). The LDLR splice region variant, rs72658867-A, located at position +5 in intron 14 (NM&#95;000527:c.2140+5G>A), causes retention of intron 14 during transcription and is expected to produce a truncated LDL receptor lacking domains essential for function of the receptor. About half of the transcripts generated from chromosomes carrying rs72658867-A are characterized by this retention of the intron. The same variant also increases LDLR mRNA expression, however, the wild type transcripts do not exceed levels in non-carriers. This demonstrates that sequence variants that disrupt the LDL receptor can lower non-HDL-C and protect against CAD.

Published
2015
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15. Discovery and refinement of loci associated with lipid levels.

Author

Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S, Ganna A, Chen J, Buchkovich ML, Mora S, Beckmann JS, Bragg-Gresham JL, Chang HY, Demirkan A, Den Hertog HM, Do R, Donnelly LA, Ehret GB, Esko T, Feitosa MF, Ferreira T, Fischer K, Fontanillas P, Fraser RM, Freitag DF, Gurdasani D, Heikkilä K, Hyppönen E, Isaacs A, Jackson AU, Johansson Å, Johnson T, Kaakinen M, Kettunen J, Kleber ME, Li X, Luan J, Lyytikäinen LP, Magnusson PKE, Mangino M, Mihailov E, Montasser ME, Müller-Nurasyid M, Nolte IM, O'Connell JR, Palmer CD, Perola M, Petersen AK, Sanna S, Saxena R, Service SK, Shah S, Shungin D, Sidore C, Song C, Strawbridge RJ, Surakka I, Tanaka T, Teslovich TM, Thorleifsson G, Van den Herik EG, Voight BF, Volcik KA, Waite LL, Wong A, Wu Y, Zhang W, Absher D, Asiki G, Barroso I, Been LF, Bolton JL, Bonnycastle LL, Brambilla P, Burnett MS, Cesana G, Dimitriou M, Doney ASF, Döring A, Elliott P, Epstein SE, Ingi Eyjolfsson G, Gigante B, Goodarzi MO, Grallert H, Gravito ML, Groves CJ, Hallmans G, Hartikainen AL, Hayward C, Hernandez D, Hicks AA, Holm H, Hung YJ, Illig T, Jones MR, Kaleebu P, Kastelein JJP, Khaw KT, Kim E, Klopp N, Komulainen P, Kumari M, Langenberg C, Lehtimäki T, Lin SY, Lindström J, Loos RJF, Mach F, McArdle WL, Meisinger C, Mitchell BD, Müller G, Nagaraja R, Narisu N, Nieminen TVM, Nsubuga RN, Olafsson I, Ong KK, Palotie A, Papamarkou T, Pomilla C, Pouta A, Rader DJ, Reilly MP, Ridker PM, Rivadeneira F, Rudan I, Ruokonen A, Samani N, Scharnagl H, Seeley J, Silander K, Stančáková A, Stirrups K, Swift AJ, Tiret L, Uitterlinden AG, van Pelt LJ, Vedantam S, Wainwright N, Wijmenga C, Wild SH, Willemsen G, Wilsgaard T, Wilson JF, Young EH, Zhao JH, Adair LS, Arveiler D, Assimes TL, Bandinelli S, Bennett F, Bochud M, Boehm BO, Boomsma DI, Borecki IB, Bornstein SR, Bovet P, Burnier M, Campbell H, Chakravarti A, Chambers JC, Chen YI, Collins FS, Cooper RS, Danesh J, Dedoussis G, de Faire U, Feranil AB, Ferrières J, Ferrucci L, Freimer NB, Gieger C, Groop LC, Gudnason V, Gyllensten U, Hamsten A, Harris TB, Hingorani A, Hirschhorn JN, Hofman A, Hovingh GK, Hsiung CA, Humphries SE, Hunt SC, Hveem K, Iribarren C, Järvelin MR, Jula A, Kähönen M, Kaprio J, Kesäniemi A, Kivimaki M, Kooner JS, Koudstaal PJ, Krauss RM, Kuh D, Kuusisto J, Kyvik KO, Laakso M, Lakka TA, Lind L, Lindgren CM, Martin NG, März W, McCarthy MI, McKenzie CA, Meneton P, Metspalu A, Moilanen L, Morris AD, Munroe PB, Njølstad I, Pedersen NL, Power C, Pramstaller PP, Price JF, Psaty BM, Quertermous T, Rauramaa R, Saleheen D, Salomaa V, Sanghera DK, Saramies J, Schwarz PEH, Sheu WH, Shuldiner AR, Siegbahn A, Spector TD, Stefansson K, Strachan DP, Tayo BO, Tremoli E, Tuomilehto J, Uusitupa M, van Duijn CM, Vollenweider P, Wallentin L, Wareham NJ, Whitfield JB, Wolffenbuttel BHR, Ordovas JM, Boerwinkle E, Palmer CNA, Thorsteinsdottir U, Chasman DI, Rotter JI, Franks PW, Ripatti S, Cupples LA, Sandhu MS, Rich SS, Boehnke M, Deloukas P, Kathiresan S, Mohlke KL, Ingelsson E, and Abecasis GR

Subjects
Asian People genetics, Black People genetics, Cholesterol, HDL blood, Cholesterol, HDL genetics, Cholesterol, LDL blood, Cholesterol, LDL genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Triglycerides blood, Triglycerides genetics, White People genetics, Coronary Artery Disease blood, Coronary Artery Disease genetics, Lipids blood, Lipids genetics
Abstract

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.

Published
2013
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16. Common variants associated with plasma triglycerides and risk for coronary artery disease.

Author

Do R, Willer CJ, Schmidt EM, Sengupta S, Gao C, Peloso GM, Gustafsson S, Kanoni S, Ganna A, Chen J, Buchkovich ML, Mora S, Beckmann JS, Bragg-Gresham JL, Chang HY, Demirkan A, Den Hertog HM, Donnelly LA, Ehret GB, Esko T, Feitosa MF, Ferreira T, Fischer K, Fontanillas P, Fraser RM, Freitag DF, Gurdasani D, Heikkilä K, Hyppönen E, Isaacs A, Jackson AU, Johansson A, Johnson T, Kaakinen M, Kettunen J, Kleber ME, Li X, Luan J, Lyytikäinen LP, Magnusson PK, Mangino M, Mihailov E, Montasser ME, Müller-Nurasyid M, Nolte IM, O'Connell JR, Palmer CD, Perola M, Petersen AK, Sanna S, Saxena R, Service SK, Shah S, Shungin D, Sidore C, Song C, Strawbridge RJ, Surakka I, Tanaka T, Teslovich TM, Thorleifsson G, Van den Herik EG, Voight BF, Volcik KA, Waite LL, Wong A, Wu Y, Zhang W, Absher D, Asiki G, Barroso I, Been LF, Bolton JL, Bonnycastle LL, Brambilla P, Burnett MS, Cesana G, Dimitriou M, Doney AS, Döring A, Elliott P, Epstein SE, Eyjolfsson GI, Gigante B, Goodarzi MO, Grallert H, Gravito ML, Groves CJ, Hallmans G, Hartikainen AL, Hayward C, Hernandez D, Hicks AA, Holm H, Hung YJ, Illig T, Jones MR, Kaleebu P, Kastelein JJ, Khaw KT, Kim E, Klopp N, Komulainen P, Kumari M, Langenberg C, Lehtimäki T, Lin SY, Lindström J, Loos RJ, Mach F, McArdle WL, Meisinger C, Mitchell BD, Müller G, Nagaraja R, Narisu N, Nieminen TV, Nsubuga RN, Olafsson I, Ong KK, Palotie A, Papamarkou T, Pomilla C, Pouta A, Rader DJ, Reilly MP, Ridker PM, Rivadeneira F, Rudan I, Ruokonen A, Samani N, Scharnagl H, Seeley J, Silander K, Stančáková A, Stirrups K, Swift AJ, Tiret L, Uitterlinden AG, van Pelt LJ, Vedantam S, Wainwright N, Wijmenga C, Wild SH, Willemsen G, Wilsgaard T, Wilson JF, Young EH, Zhao JH, Adair LS, Arveiler D, Assimes TL, Bandinelli S, Bennett F, Bochud M, Boehm BO, Boomsma DI, Borecki IB, Bornstein SR, Bovet P, Burnier M, Campbell H, Chakravarti A, Chambers JC, Chen YD, Collins FS, Cooper RS, Danesh J, Dedoussis G, de Faire U, Feranil AB, Ferrières J, Ferrucci L, Freimer NB, Gieger C, Groop LC, Gudnason V, Gyllensten U, Hamsten A, Harris TB, Hingorani A, Hirschhorn JN, Hofman A, Hovingh GK, Hsiung CA, Humphries SE, Hunt SC, Hveem K, Iribarren C, Järvelin MR, Jula A, Kähönen M, Kaprio J, Kesäniemi A, Kivimaki M, Kooner JS, Koudstaal PJ, Krauss RM, Kuh D, Kuusisto J, Kyvik KO, Laakso M, Lakka TA, Lind L, Lindgren CM, Martin NG, März W, McCarthy MI, McKenzie CA, Meneton P, Metspalu A, Moilanen L, Morris AD, Munroe PB, Njølstad I, Pedersen NL, Power C, Pramstaller PP, Price JF, Psaty BM, Quertermous T, Rauramaa R, Saleheen D, Salomaa V, Sanghera DK, Saramies J, Schwarz PE, Sheu WH, Shuldiner AR, Siegbahn A, Spector TD, Stefansson K, Strachan DP, Tayo BO, Tremoli E, Tuomilehto J, Uusitupa M, van Duijn CM, Vollenweider P, Wallentin L, Wareham NJ, Whitfield JB, Wolffenbuttel BH, Altshuler D, Ordovas JM, Boerwinkle E, Palmer CN, Thorsteinsdottir U, Chasman DI, Rotter JI, Franks PW, Ripatti S, Cupples LA, Sandhu MS, Rich SS, Boehnke M, Deloukas P, Mohlke KL, Ingelsson E, Abecasis GR, Daly MJ, Neale BM, and Kathiresan S

Subjects
Biological Transport, Cholesterol, HDL blood, Cholesterol, LDL blood, Coronary Artery Disease epidemiology, Coronary Artery Disease genetics, Humans, Polymorphism, Single Nucleotide, Risk Factors, Triglycerides metabolism, Cholesterol, HDL genetics, Cholesterol, LDL genetics, Coronary Artery Disease blood, Triglycerides blood, Triglycerides genetics
Abstract

Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

Published
2013
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17. Large-scale association analysis identifies new risk loci for coronary artery disease.

Author

Deloukas P, Kanoni S, Willenborg C, Farrall M, Assimes TL, Thompson JR, Ingelsson E, Saleheen D, Erdmann J, Goldstein BA, Stirrups K, König IR, Cazier JB, Johansson A, Hall AS, Lee JY, Willer CJ, Chambers JC, Esko T, Folkersen L, Goel A, Grundberg E, Havulinna AS, Ho WK, Hopewell JC, Eriksson N, Kleber ME, Kristiansson K, Lundmark P, Lyytikäinen LP, Rafelt S, Shungin D, Strawbridge RJ, Thorleifsson G, Tikkanen E, Van Zuydam N, Voight BF, Waite LL, Zhang W, Ziegler A, Absher D, Altshuler D, Balmforth AJ, Barroso I, Braund PS, Burgdorf C, Claudi-Boehm S, Cox D, Dimitriou M, Do R, Doney AS, El Mokhtari N, Eriksson P, Fischer K, Fontanillas P, Franco-Cereceda A, Gigante B, Groop L, Gustafsson S, Hager J, Hallmans G, Han BG, Hunt SE, Kang HM, Illig T, Kessler T, Knowles JW, Kolovou G, Kuusisto J, Langenberg C, Langford C, Leander K, Lokki ML, Lundmark A, McCarthy MI, Meisinger C, Melander O, Mihailov E, Maouche S, Morris AD, Müller-Nurasyid M, Nikus K, Peden JF, Rayner NW, Rasheed A, Rosinger S, Rubin D, Rumpf MP, Schäfer A, Sivananthan M, Song C, Stewart AF, Tan ST, Thorgeirsson G, van der Schoot CE, Wagner PJ, Wells GA, Wild PS, Yang TP, Amouyel P, Arveiler D, Basart H, Boehnke M, Boerwinkle E, Brambilla P, Cambien F, Cupples AL, de Faire U, Dehghan A, Diemert P, Epstein SE, Evans A, Ferrario MM, Ferrières J, Gauguier D, Go AS, Goodall AH, Gudnason V, Hazen SL, Holm H, Iribarren C, Jang Y, Kähönen M, Kee F, Kim HS, Klopp N, Koenig W, Kratzer W, Kuulasmaa K, Laakso M, Laaksonen R, Lee JY, Lind L, Ouwehand WH, Parish S, Park JE, Pedersen NL, Peters A, Quertermous T, Rader DJ, Salomaa V, Schadt E, Shah SH, Sinisalo J, Stark K, Stefansson K, Trégouët DA, Virtamo J, Wallentin L, Wareham N, Zimmermann ME, Nieminen MS, Hengstenberg C, Sandhu MS, Pastinen T, Syvänen AC, Hovingh GK, Dedoussis G, Franks PW, Lehtimäki T, Metspalu A, Zalloua PA, Siegbahn A, Schreiber S, Ripatti S, Blankenberg SS, Perola M, Clarke R, Boehm BO, O'Donnell C, Reilly MP, März W, Collins R, Kathiresan S, Hamsten A, Kooner JS, Thorsteinsdottir U, Danesh J, Palmer CN, Roberts R, Watkins H, Schunkert H, and Samani NJ

Subjects
Adult, Aged, Asian People, Cell Line, Female, Gene Regulatory Networks, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Risk Factors, White People genetics, Coronary Artery Disease genetics, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Quantitative Trait Loci
Abstract

Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r(2) < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways.

Published
2013
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18. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.

Author

Schunkert H, König IR, Kathiresan S, Reilly MP, Assimes TL, Holm H, Preuss M, Stewart AF, Barbalic M, Gieger C, Absher D, Aherrahrou Z, Allayee H, Altshuler D, Anand SS, Andersen K, Anderson JL, Ardissino D, Ball SG, Balmforth AJ, Barnes TA, Becker DM, Becker LC, Berger K, Bis JC, Boekholdt SM, Boerwinkle E, Braund PS, Brown MJ, Burnett MS, Buysschaert I, Carlquist JF, Chen L, Cichon S, Codd V, Davies RW, Dedoussis G, Dehghan A, Demissie S, Devaney JM, Diemert P, Do R, Doering A, Eifert S, Mokhtari NE, Ellis SG, Elosua R, Engert JC, Epstein SE, de Faire U, Fischer M, Folsom AR, Freyer J, Gigante B, Girelli D, Gretarsdottir S, Gudnason V, Gulcher JR, Halperin E, Hammond N, Hazen SL, Hofman A, Horne BD, Illig T, Iribarren C, Jones GT, Jukema JW, Kaiser MA, Kaplan LM, Kastelein JJ, Khaw KT, Knowles JW, Kolovou G, Kong A, Laaksonen R, Lambrechts D, Leander K, Lettre G, Li M, Lieb W, Loley C, Lotery AJ, Mannucci PM, Maouche S, Martinelli N, McKeown PP, Meisinger C, Meitinger T, Melander O, Merlini PA, Mooser V, Morgan T, Mühleisen TW, Muhlestein JB, Münzel T, Musunuru K, Nahrstaedt J, Nelson CP, Nöthen MM, Olivieri O, Patel RS, Patterson CC, Peters A, Peyvandi F, Qu L, Quyyumi AA, Rader DJ, Rallidis LS, Rice C, Rosendaal FR, Rubin D, Salomaa V, Sampietro ML, Sandhu MS, Schadt E, Schäfer A, Schillert A, Schreiber S, Schrezenmeir J, Schwartz SM, Siscovick DS, Sivananthan M, Sivapalaratnam S, Smith A, Smith TB, Snoep JD, Soranzo N, Spertus JA, Stark K, Stirrups K, Stoll M, Tang WH, Tennstedt S, Thorgeirsson G, Thorleifsson G, Tomaszewski M, Uitterlinden AG, van Rij AM, Voight BF, Wareham NJ, Wells GA, Wichmann HE, Wild PS, Willenborg C, Witteman JC, Wright BJ, Ye S, Zeller T, Ziegler A, Cambien F, Goodall AH, Cupples LA, Quertermous T, März W, Hengstenberg C, Blankenberg S, Ouwehand WH, Hall AS, Deloukas P, Thompson JR, Stefansson K, Roberts R, Thorsteinsdottir U, O'Donnell CJ, McPherson R, Erdmann J, and Samani NJ

Subjects
Adult, Aged, Alleles, Case-Control Studies, Coronary Artery Disease etiology, Female, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors, Coronary Artery Disease genetics
Abstract

We performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 individuals with CAD (cases) and 64,762 controls of European descent followed by genotyping of top association signals in 56,682 additional individuals. This analysis identified 13 loci newly associated with CAD at P < 5 × 10⁻⁸ and confirmed the association of 10 of 12 previously reported CAD loci. The 13 new loci showed risk allele frequencies ranging from 0.13 to 0.91 and were associated with a 6% to 17% increase in the risk of CAD per allele. Notably, only three of the new loci showed significant association with traditional CAD risk factors and the majority lie in gene regions not previously implicated in the pathogenesis of CAD. Finally, five of the new CAD risk loci appear to have pleiotropic effects, showing strong association with various other human diseases or traits.

Published
2011
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19. The chromosome 9p21 risk locus is associated with angiographic severity and progression of coronary artery disease.

Author

Patel RS, Su S, Neeland IJ, Ahuja A, Veledar E, Zhao J, Helgadottir A, Holm H, Gulcher JR, Stefansson K, Waddy S, Vaccarino V, Zafari AM, and Quyyumi AA

Subjects
Adult, Aged, Aged, 80 and over, Coronary Angiography, Coronary Artery Disease diagnostic imaging, Disease Progression, Female, Genetic Markers genetics, Genetic Predisposition to Disease genetics, Genotype, Homozygote, Humans, Male, Middle Aged, Myocardial Infarction diagnostic imaging, Risk Factors, Young Adult, Chromosomes, Human, Pair 9 genetics, Coronary Artery Disease genetics, Myocardial Infarction genetics, Polymorphism, Single Nucleotide genetics
Abstract

Aims: we tested the hypothesis that the 9p21 risk locus promotes atherosclerosis by examining the association between rs10757278 and coronary artery disease (CAD) severity and progression determined by semi-quantitative angiographic scores., Methods and Results: the rs10757278 single nucleotide polymorphism (SNP) was genotyped as the marker for the 9p21 locus in 2334 Caucasian patients undergoing cardiac catheterization (mean age 63, male 67%). Angiographic CAD was assessed using two semi-quantitative scoring systems with one estimating severity (Gensini) and the other extent (Sullivan). A subset of 308 patients who underwent two or more coronary angiograms at least 6 months apart were examined for net change in Gensini and Sullivan scores over time to determine the rate of CAD progression by genotype and were further classified as 'progressors' or 'non-progressors' based on absolute change per year in angiographic severity score. We replicated the association between the rs10757278 SNP and myocardial infarction and binary (presence/absence) angiographic classifications of CAD. Furthermore, we observed a significant additive association with this SNP, and both severity and extent of CAD using angiographic scores, after adjustment for age, gender, body mass index, traditional cardiovascular risk factors, myocardial infarction, and statin use (Gensini P = 0.016, Sullivan P = 0.005). In addition, there was a significant linear association with CAD progression before and after adjustment for covariates (Gensini P = 0.023, Sullivan P = 0.003) with homozygotes for the risk variant having three-fold greater odds of CAD progression compared with the referent group., Conclusion: the 9p21 risk locus is associated with angiographically defined severity, extent, and progression of CAD, suggesting a role for this locus in influencing atherosclerosis and its progression.

Published
2010
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20. Design of the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) Study: A Genome-wide association meta-analysis involving more than 22 000 cases and 60 000 controls.

Author

Preuss M, König IR, Thompson JR, Erdmann J, Absher D, Assimes TL, Blankenberg S, Boerwinkle E, Chen L, Cupples LA, Hall AS, Halperin E, Hengstenberg C, Holm H, Laaksonen R, Li M, März W, McPherson R, Musunuru K, Nelson CP, Burnett MS, Epstein SE, O'Donnell CJ, Quertermous T, Rader DJ, Roberts R, Schillert A, Stefansson K, Stewart AF, Thorleifsson G, Voight BF, Wells GA, Ziegler A, Kathiresan S, Reilly MP, Samani NJ, and Schunkert H

Subjects
Adult, Aged, Algorithms, Female, Genotype, Humans, Male, Middle Aged, Myocardial Infarction genetics, Polymorphism, Single Nucleotide, Coronary Artery Disease genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Research Design
Abstract

Background: Recent genome-wide association studies (GWAS) of myocardial infarction (MI) and other forms of coronary artery disease (CAD) have led to the discovery of at least 13 genetic loci. In addition to the effect size, power to detect associations is largely driven by sample size. Therefore, to maximize the chance of finding novel susceptibility loci for CAD and MI, the Coronary ARtery DIsease Genome-wide Replication And Meta-analysis (CARDIoGRAM) consortium was formed., Methods and Results: CARDIoGRAM combines data from all published and several unpublished GWAS in individuals with European ancestry; includes >22 000 cases with CAD, MI, or both and >60 000 controls; and unifies samples from the Atherosclerotic Disease VAscular functioN and genetiC Epidemiology study, CADomics, Cohorts for Heart and Aging Research in Genomic Epidemiology, deCODE, the German Myocardial Infarction Family Studies I, II, and III, Ludwigshafen Risk and Cardiovascular Heath Study/AtheroRemo, MedStar, Myocardial Infarction Genetics Consortium, Ottawa Heart Genomics Study, PennCath, and the Wellcome Trust Case Control Consortium. Genotyping was carried out on Affymetrix or Illumina platforms followed by imputation of genotypes in most studies. On average, 2.2 million single nucleotide polymorphisms were generated per study. The results from each study are combined using meta-analysis. As proof of principle, we meta-analyzed risk variants at 9p21 and found that rs1333049 confers a 29% increase in risk for MI per copy (P=2×10⁻²⁰)., Conclusion: CARDIoGRAM is poised to contribute to our understanding of the role of common genetic variation on risk for CAD and MI.

Published
2010
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21. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants

Author

Aragam, Krishna G, Jiang, Tao, Goel, Anuj, Kanoni, Stavroula, Wolford, Brooke N, Atri, Deepak S, Weeks, Elle M, Wang, Minxian, Hindy, George, Zhou, Wei, Grace, Christopher, Roselli, Carolina, Marston, Nicholas A, Kamanu, Frederick K, Surakka, Ida, Venegas, Loreto Muñoz, Sherliker, Paul, Koyama, Satoshi, Ishigaki, Kazuyoshi, Åsvold, Bjørn O, Brown, Michael R, Brumpton, Ben, De Vries, Paul S, Giannakopoulou, Olga, Giardoglou, Panagiota, Gudbjartsson, Daniel F, Güldener, Ulrich, Haider, Syed M Ijlal, Helgadottir, Anna, Ibrahim, Maysson, Kastrati, Adnan, Kessler, Thorsten, Kyriakou, Theodosios, Konopka, Tomasz, Li, Ling, Ma, Lijiang, Meitinger, Thomas, Mucha, Sören, Munz, Matthias, Murgia, Federico, Nielsen, Jonas B, Nöthen, Markus M, Pang, Shichao, Reinberger, Tobias, Schnitzler, Gavin, Smedley, Damian, Thorleifsson, Gudmar, Von Scheidt, Moritz, Ulirsch, Jacob C, Danesh, John, Arnar, David O, Burtt, Noël P, Costanzo, Maria C, Flannick, Jason, Ito, Kaoru, Jang, Dong-Keun, Kamatani, Yoichiro, Khera, Amit V, Komuro, Issei, Kullo, Iftikhar J, Lotta, Luca A, Nelson, Christopher P, Roberts, Robert, Thorgeirsson, Gudmundur, Thorsteinsdottir, Unnur, Webb, Thomas R, Baras, Aris, Björkegren, Johan LM, Boerwinkle, Eric, Dedoussis, George, Holm, Hilma, Hveem, Kristian, Melander, Olle, Morrison, Alanna C, Orho-Melander, Marju, Rallidis, Loukianos S, Ruusalepp, Arno, Sabatine, Marc S, Stefansson, Kari, Zalloua, Pierre, Ellinor, Patrick T, Farrall, Martin, Ruff, Christian T, Finucane, Hilary K, Hopewell, Jemma C, Clarke, Robert, Gupta, Rajat M, Erdmann, Jeanette, Samani, Nilesh J, Schunkert, Heribert, Watkins, Hugh, Willer, Cristen J, Deloukas, Panos, Kathiresan, Sekar, Butterworth, Adam S, Aragam, Krishna G [0000-0003-3223-9131], Goel, Anuj [0000-0003-2307-4021], Kanoni, Stavroula [0000-0002-1691-9615], Wolford, Brooke N [0000-0003-3153-1552], Atri, Deepak S [0000-0001-8139-5419], Weeks, Elle M [0000-0002-4317-4444], Wang, Minxian [0000-0002-3753-508X], Zhou, Wei [0000-0001-7719-0859], Roselli, Carolina [0000-0001-5267-6756], Kamanu, Frederick K [0000-0001-7208-1047], Koyama, Satoshi [0000-0002-9286-0360], Ishigaki, Kazuyoshi [0000-0003-2881-0657], Åsvold, Bjørn O [0000-0003-3837-2101], Brumpton, Ben [0000-0002-3058-1059], Gudbjartsson, Daniel F [0000-0002-5222-9857], Güldener, Ulrich [0000-0001-5052-8610], Helgadottir, Anna [0000-0002-1806-2467], Kessler, Thorsten [0000-0003-3326-1621], Li, Ling [0000-0002-3280-9475], Mucha, Sören [0000-0002-1647-2526], Munz, Matthias [0000-0002-4728-3357], Murgia, Federico [0000-0002-3608-845X], Pang, Shichao [0000-0002-4111-2864], Smedley, Damian [0000-0002-5836-9850], Thorleifsson, Gudmar [0000-0003-4623-9087], von Scheidt, Moritz [0000-0001-7159-8271], Ulirsch, Jacob C [0000-0002-7947-0827], Costanzo, Maria C [0000-0001-9043-693X], Flannick, Jason [0000-0002-3618-795X], Ito, Kaoru [0000-0003-1843-773X], Khera, Amit V [0000-0001-6535-5839], Komuro, Issei [0000-0002-0714-7182], Kullo, Iftikhar J [0000-0002-6524-3471], Roberts, Robert [0000-0002-6792-4633], Webb, Thomas R [0000-0001-5998-8226], Baras, Aris [0000-0002-6830-3396], Björkegren, Johan LM [0000-0003-1945-7425], Holm, Hilma [0000-0002-9517-6636], Morrison, Alanna C [0000-0001-6381-4296], Orho-Melander, Marju [0000-0002-3578-2503], Stefansson, Kari [0000-0003-1676-864X], Farrall, Martin [0000-0003-4564-2165], Finucane, Hilary K [0000-0003-3864-9828], Clarke, Robert [0000-0002-9802-8241], Erdmann, Jeanette [0000-0002-4486-6231], Samani, Nilesh J [0000-0002-3286-8133], Schunkert, Heribert [0000-0001-6428-3001], Watkins, Hugh [0000-0002-5287-9016], Willer, Cristen J [0000-0001-5645-4966], Kathiresan, Sekar [0000-0002-3711-7101], Butterworth, Adam S [0000-0002-6915-9015], and Apollo - University of Cambridge Repository

Subjects
692/699/75/2, 631/208/205/2138, article, Humans, Coronary Artery Disease, Genome-Wide Association Study
Abstract

Funder: K.G.A. has received support from the American Heart Association Institute for Precision Cardiovascular Medicine (17IFUNP3384001), a KL2/Catalyst Medical Research Investigator Training (CMeRIT) award from the Harvard Catalyst (KL2 TR002542), and the NIH (1K08HL153937)., Funder: B.N.W is supported by the National Science Foundation Graduate Research Program (DGE 1256260)., Funder: I.S. is supported by a Precision Health Scholars Award from the University of Michigan Medical School., Funder: I.K., S.Ko., and K.It. are funded by the Japan Agency for Medical Research and Development, AMED, under Grant Numbers JP16ek0109070h0003, JP18kk0205008h0003, JP18kk0205001s0703, JP20km0405209, and JP20ek0109487. The BioBank Japan is supported by AMED under Grant Number JP20km0605001., Funder: J.L.M.B. acknowledges research support from NIH R01HL125863, American Heart Association (A14SFRN20840000), the Swedish Research Council (2018-02529) and Heart Lung Foundation (20170265) and the Foundation Leducq (PlaqueOmics: Novel Roles of Smooth Muscle and Other Matrix Producing Cells in Atherosclerotic Plaque Stability and Rupture, 18CVD02., Funder: P.S.dV was supported by American Heart Association grant number 18CDA34110116 and National Heart, Lung, and Blood Institute grant R01HL146860. The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I and HHSN268201700005I), R01HL087641, R01HL059367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research., Funder: O.G. has received funding from the British Heart Foundation (BHF) (FS/14/66/3129)., Funder: T.K. is supported by the Corona-Foundation (Junior Research Group Translational Cardiovascular Genomics) and the German Research Foundation (DFG) as part of the Sonderforschungsbereich SFB 1123 (B02)., Funder: D.S.A. has received support from a training grant from the NIH (T32HL007604)., Funder: N.P.B., M.C.C., J.F., and D.-K.J. have been funded by the National Institute of Diabetes and Digestive and Kidney Diseases (2UM1DK105554)., Funder: A.V.K. has been funded by 1K08HG010155 from the National Human Genome Research Institute., Funder: C.P.N. and T.R.W received funding from the British Heart Foundation (SP/16/4/32697)., Funder: The Trøndelag Health Study (The HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology), Trøndelag County Council, Central Norway Regional Health Authority, and the Norwegian Institute of Public Health. The K.G. Jebsen Center for Genetic Epidemiology is financed by Stiftelsen Kristian Gerhard Jebsen; Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology; and Central Norway Regional Health Authority. Whole genome sequencing for the HUNT study was funded by HL109946., Funder: O.M. was funded by the Swedish Heart- and Lung Foundation, the Swedish Research Council, the European Research Council ERC-AdG-2019-885003 and Lund University Infrastructure grant ”Malmö population-based cohorts” (STYR 2019/2046)., Funder: This work was supported by the European Commission (HEALTH-F2–2013-601456) and the TriPartite Immunometabolism Consortium [TrIC]- NovoNordisk Foundation (NNF15CC0018486), VIAgenomics (SP/19/2/344612), the British Heart Foundation, a Wellcome Trust core award (M.F., H.W., 203141/Z/16/Z) and support from the NIHR Oxford Biomedical Research Centre. M.F. and H.W. are members of the Oxford BHF Centre of Research Excellence (RE/13/1/30181). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health., Funder: J.D. is a British Heart Foundation Professor, European Research Council Senior Investigator, and National Institute for Health Research (NIHR) Senior Investigator., Funder: J.C.H. acknowledges personal funding from the British Heart Foundation (FS/14/55/30806) and is a member of the Oxford BHF Centre of Research Excellence (RE/13/1/30181)., Funder: R.C. has received funding from the British Heart Foundation and British Heart Foundation Centre of Research Excellence., Funder: This research was supported by BHF (SP/13/2/30111) and conducted using the UK Biobank Resource (application number 9922)., Funder: The GerMIFs gratefully acknowledge the support of the Bavarian State Ministry of Health and Care, furthermore founded this work within its framework of DigiMed Bayern (grant No: DMB-1805-0001), the German Federal Ministry of Education and Research (BMBF) within the framework of ERA-NET on Cardiovascular Disease (Druggable-MI-genes: 01KL1802), within the scheme of target validation (BlockCAD: 16GW0198K), within the framework of the e:Med research and funding concept (AbCD-Net: 01ZX1706C), the British Heart Foundation (BHF)/German Centre of Cardiovascular Research (DZHK)-collaboration (VIAgenomics) and the German Research Foundation (DFG) as part of the Sonderforschungsbereich SFB 1123 (B02) and the Sonderforschungsbereich SFB TRR 267 (B05)., Funder: C.J.W. is funded by NIH grant R35-HL135824., Funder: This work was supported by the British Heart Foundation (BHF) grant RG/14/5/30893 (P.D.) and forms part of the research themes contributing to the translational research portfolios of the Barts Biomedical Research Centre funded by the UK National Institute for Health Research (NIHR)., The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR–Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

Published
2022
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22. Cholesterol not particle concentration mediates the atherogenic risk conferred by apolipoprotein B particles:A Mendelian randomization analysis

Author

Helgadottir, Anna, Thorleifsson, Gudmar, Snaebjarnarson, Audunn, Stefansdottir, Lilja, Sveinbjornsson, Gardar, Tragante, Vinicius, Björnsson, Eyþór, Steinthorsdottir, Valgerdur, Gretarsdottir, Solveig, Helgason, Hannes, Saemundsdottir, Jona, Olafsson, Isleifur, Thune, Jens Jakob, Axelsson Raja, Anna, Ghouse, Jonas, Olesen, Morten Salling, Christensen, Alex, Jacobsen, Rikke Louise, Dowsett, Joseph, Bruun, Mie Topholm, Nielsen, Kaspar, Knowlton, Kirk, Nadauld, Lincoln, Benediktsson, Rafn, Erikstrup, Christian, Pedersen, Ole B., Banasik, Karina, Brunak, Søren, Bundgaard, Henning, Ostrowski, Sisse R., Sulem, Patrick, Arnar, David O., Thorgeirsson, Gudmundur, Thorsteinsdottir, Unnur, Gudbjartsson, Daniel F., Stefansson, Kari, Holm, Hilma, and Nyegaard, Mette

Subjects
Epidemiology, Apolipoproteins B/genetics, Coronary Artery Disease/genetics, Lipoproteins, Cholesterol, HDL, Non-HDL cholesterol, Coronary Artery Disease, Cholesterol, LDL, Mendelian Randomization Analysis, Atherosclerosis, Apolipoprotein, Cholesterol, Apolipoprotein B-100/genetics, Risk Factors, Apolipoprotein B-100, Mendelian randomization, Humans, Cardiology and Cardiovascular Medicine, Apolipoprotein B, Apolipoproteins B
Abstract

Background and aims:The causal contribution of apolipoprotein B (apoB) particles to coronary artery disease (CAD) is established. We examined whether this atherogenic contribution is better reflected by non-high-density lipoprotein cholesterol (non-HDL-C) or apoB particle concentration.Method and results:We performed Mendelian randomization (MR) analysis using 235 variants as genetic instruments; testing the relationship between their effects on the exposures, non-HDL-C and apoB, and on the outcome CAD using weighted regression. Variant effect estimates on the exposures came from the UK Biobank (N = 376 336) and on the outcome from a meta-analysis of five CAD datasets (187 451 cases and 793 315 controls). Subsequently, we carried out sensitivity and replication analyses.In univariate MR analysis, both exposures associated with CAD (βnon-HDL-C = 0.40, P = 2.8 × 10−48 and βapoB = 0.38, P = 1.3 × 10−44). Adding effects on non-HDL-C into a model that already included those on apoB significantly improved the genetically predicted CAD effects (P = 3.9 × 10−5), while adding apoB into the model including non-HDL-C did not (P = 0.69). Thirty-five per cent (82/235) of the variants used as genetic instruments had discordant effects on the exposures, associating with non-HDL-C/apoB ratio at P Conclusion:Many sequence variants have discordant effects on non-HDL-C and apoB. These variants allowed us to show that the causal mechanism underlying the relationship between apolipoprotein B particles and CAD is more associated with non-HDL-C than apoB particle concentration.

Published
2022

23. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

Author

Shah, Sonia, Henry, Albert, Roselli, Carolina, Lin, Honghuang, Sveinbjornsson, Gardar, Fatemifar, Ghazaleh, Hedman, Asa K, Wilk, Jemma B, Morley, Michael P, Chaffin, Mark D, Helgadottir, Anna, Verweij, Niek, Dehghan, Abbas, Almgren, Peter, Andersson, Charlotte, Aragam, Krishna G, Arnlov, Johan, Backman, Joshua D, Biggs, Mary L, Bloom, Heather L, Brandimarto, Jeffrey, Brown, Michael R, Buckbinder, Leonard, Carey, David J, Chasman, Daniel I, Chen, Xing, Chen, Xu, Chung, Jonathan, Chutkow, William, Cook, James P, Delgado, Graciela E, Denaxas, Spiros, Doney, Alexander S, Doerr, Marcus, Dudley, Samuel C, Dunn, Michael E, Engstrom, Gunnar, Esko, Tonu, Felix, Stephan B, Finan, Chris, Ford, Ian, Ghanbari, Mohsen, Ghasemi, Sahar, Giedraitis, Vilmantas, Giulianini, Franco, Gottdiener, John S, Gross, Stefan, Gudbjartsson, Daniel F, Gutmann, Rebecca, Haggerty, Christopher M, van der Harst, Pim, Hyde, Craig L, Ingelsson, Erik, Jukema, J Wouter, Kavousi, Maryam, Khaw, Kay-Tee, Kleber, Marcus E, Kober, Lars, Koekemoer, Andrea, Langenberg, Claudia, Lind, Lars, Lindgren, Cecilia M, London, Barry, Lotta, Luca A, Lovering, Ruth C, Luan, Jian'an, Magnusson, Patrik, Mahajan, Anubha, Margulies, Kenneth B, Maerz, Winfried, Melander, Olle, Mordi, Ify R, Morgan, Thomas, Morris, Andrew D, Morris, Andrew P, Morrison, Alanna C, Nagle, Michael W, Nelson, Christopher P, Niessner, Alexander, Niiranen, Teemu, O'Donoghue, Michelle L, Owens, Anjali T, Palmer, Colin NA, Parry, Helen M, Perola, Markus, Portilla-Fernandez, Eliana, Psaty, Bruce M, Rice, Kenneth M, Ridker, Paul M, Romaine, Simon PR, Rotter, Jerome I, Salo, Perttu, Salomaa, Veikko, van Setten, Jessica, Shalaby, Alaa A, Smelser, Diane T, Smith, Nicholas L, Stender, Steen, Stott, David J, Svensson, Per, Tammesoo, Mari-Liis, Taylor, Kent D, Teder-Laving, Maris, Teumer, Alexander, Thorgeirsson, Gudmundur, Thorsteinsdottir, Unnur, Torp-Pedersen, Christian, Trompet, Stella, Tyl, Benoit, Uitterlinden, Andre G, Veluchamy, Abirami, Voelker, Uwe, Voors, Adriaan A, Wang, Xiaosong, Wareham, Nicholas J, Waterworth, Dawn, Weeke, Peter E, Weiss, Raul, Wiggins, Kerri L, Xing, Heming, Yerges-Armstrong, Laura M, Yu, Bing, Zannad, Faiez, Zhao, Jing Hua, Hemingway, Harry, Samani, Nilesh J, McMurray, John JV, Yang, Jian, Visscher, Peter M, Newton-Cheh, Christopher, Malarstig, Anders, Holm, Hilma, Lubitz, Steven A, Sattar, Naveed, Holmes, Michael V, Cappola, Thomas P, Asselbergs, Folkert W, Hingorani, Aroon D, Kuchenbaecker, Karoline, Ellinor, Patrick T, Lang, Chim C, Stefansson, Kari, Smith, J Gustav, Vasan, Ramachandran S, Swerdlow, Daniel I, Lumbers, R Thomas, Abecasis, Goncalo, Backman, Joshua, Bai, Xiaodong, Balasubramanian, Suganthi, Banerjee, Nilanjana, Baras, Aris, Barnard, Leland, Beechert, Christina, Blumenfeld, Andrew, Cantor, Michael, Chai, Yating, Coppola, Giovanni, Damask, Amy, Dewey, Frederick, Economides, Aris, Eom, Gisu, Forsythe, Caitlin, Fuller, Erin D, Gu, Zhenhua, Gurski, Lauren, Guzzardo, Paloma M, Habegger, Lukas, Hahn, Young, Hawes, Alicia, van Hout, Cristopher, Jones, Marcus B, Khalid, Shareef, Lattari, Michael, Li, Alexander, Lin, Nan, Liu, Daren, Lopez, Alexander, Manoochehri, Kia, Marchini, Jonathan, Marcketta, Anthony, Maxwell, Evan K, McCarthy, Shane, Mitnaul, Lyndon J, O'Dushlaine, Colm, Overton, John D, Padilla, Maria Sotiropoulos, Paulding, Charles, Penn, John, Pradhan, Manasi, Reid, Jeffrey G, Schleicher, Thomas D, Schurmann, Claudia, Shuldiner, Alan, Staples, Jeffrey C, Sun, Dylan, Toledo, Karina, Ulloa, Ricardo H, Widom, Louis, Wolf, Sarah E, Yadav, Ashish, Ye, Bin, Ctr, Regeneron Genetics, Shah, Sonia [0000-0001-5860-4526], Henry, Albert [0000-0001-7422-2288], Roselli, Carolina [0000-0001-5267-6756], Lin, Honghuang [0000-0003-3043-3942], Chaffin, Mark D. [0000-0002-1234-5562], Helgadottir, Anna [0000-0002-1806-2467], Verweij, Niek [0000-0002-4303-7685], Almgren, Peter [0000-0002-0473-0241], Chen, Xu [0000-0002-7299-3238], Ghanbari, Mohsen [0000-0002-9476-7143], Giedraitis, Vilmantas [0000-0003-3423-2021], Gross, Stefan [0000-0003-4121-7161], Guðbjartsson, Daníel F. [0000-0002-5222-9857], Hyde, Craig L. [0000-0002-6939-287X], Ingelsson, Erik [0000-0003-2256-6972], Jukema, J. Wouter [0000-0002-3246-8359], Kleber, Marcus E. [0000-0003-0663-7275], Koekemoer, Andrea [0000-0001-8222-3547], Langenberg, Claudia [0000-0002-5017-7344], Lindgren, Cecilia M. [0000-0002-4903-9374], Lovering, Ruth C. [0000-0002-9791-0064], Luan, Jian’an [0000-0003-3137-6337], Magnusson, Patrik [0000-0002-7315-7899], Mahajan, Anubha [0000-0001-5585-3420], Mordi, Ify R. [0000-0002-2686-729X], Morris, Andrew D. [0000-0002-1766-0473], Nagle, Michael W. [0000-0002-4677-7582], Nelson, Christopher P. [0000-0001-8025-2897], Palmer, Colin N. A. [0000-0002-6415-6560], Rice, Kenneth M. [0000-0002-3071-7278], Rotter, Jerome I. [0000-0001-7191-1723], Salomaa, Veikko [0000-0001-7563-5324], van Setten, Jessica [0000-0002-4934-7510], Svensson, Per [0000-0003-0372-6272], Taylor, Kent D. [0000-0002-2756-4370], Teder-Laving, Maris [0000-0002-5872-1850], Teumer, Alexander [0000-0002-8309-094X], Tyl, Benoit [0000-0001-5297-8412], Uitterlinden, Andre G. [0000-0002-7276-3387], Völker, Uwe [0000-0002-5689-3448], Wiggins, Kerri L. [0000-0003-2749-1279], Hemingway, Harry [0000-0003-2279-0624], Yang, Jian [0000-0003-2001-2474], Visscher, Peter M. [0000-0002-2143-8760], Lubitz, Steven A. [0000-0002-9599-4866], Sattar, Naveed [0000-0002-1604-2593], Cappola, Thomas P. [0000-0002-9630-7204], Asselbergs, Folkert W. [0000-0002-1692-8669], Kuchenbaecker, Karoline [0000-0001-9726-603X], Ellinor, Patrick T. [0000-0002-2067-0533], Vasan, Ramachandran S. [0000-0001-7357-5970], Lumbers, R. Thomas [0000-0002-9077-4741], Apollo - University of Cambridge Repository, Chaffin, Mark D [0000-0002-1234-5562], Guðbjartsson, Daníel F [0000-0002-5222-9857], Hyde, Craig L [0000-0002-6939-287X], Jukema, J Wouter [0000-0002-3246-8359], Kleber, Marcus E [0000-0003-0663-7275], Lindgren, Cecilia M [0000-0002-4903-9374], Lovering, Ruth C [0000-0002-9791-0064], Luan, Jian'an [0000-0003-3137-6337], Mordi, Ify R [0000-0002-2686-729X], Morris, Andrew D [0000-0002-1766-0473], Nagle, Michael W [0000-0002-4677-7582], Nelson, Christopher P [0000-0001-8025-2897], Palmer, Colin NA [0000-0002-6415-6560], Rice, Kenneth M [0000-0002-3071-7278], Rotter, Jerome I [0000-0001-7191-1723], Taylor, Kent D [0000-0002-2756-4370], Uitterlinden, Andre G [0000-0002-7276-3387], Wiggins, Kerri L [0000-0003-2749-1279], Visscher, Peter M [0000-0002-2143-8760], Lubitz, Steven A [0000-0002-9599-4866], Cappola, Thomas P [0000-0002-9630-7204], Asselbergs, Folkert W [0000-0002-1692-8669], Ellinor, Patrick T [0000-0002-2067-0533], Vasan, Ramachandran S [0000-0001-7357-5970], Lumbers, R Thomas [0000-0002-9077-4741], Palmer, Colin N A [0000-0002-6415-6560], Cardiovascular Centre (CVC), University of Queensland [Brisbane], University College of London [London] (UCL), Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], University Medical Center Groningen [Groningen] (UMCG), Boston University School of Medicine (BUSM), Boston University [Boston] (BU), Framingham Heart Study, National Heart, Lung, and Blood Institute [Bethesda] (NHLBI)-Boston University [Boston] (BU), deCODE genetics [Reykjavik], Karolinska Institutet [Stockholm], Pfizer, University of Pennsylvania [Philadelphia], University of Groningen [Groningen], Imperial College London, Lund University [Lund], Herlev and Gentofte Hospital, Massachusetts General Hospital [Boston], Department of Neurobiology, Care Sciences and Society [Stockholm, Sweden] (Division of Family Medicine), Dalarna University, Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, Department of Biostatistics, University of Washington [Seattle], Emory University School of Medicine, Emory University [Atlanta, GA], The University of Texas Medical School at Houston, Department of Molecular and Functional Genomics, Geisinger, Danville, PA, Brigham and Women's Hospital [Boston], Harvard Medical School [Boston] (HMS), Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY, Novartis Institutes for BioMedical Research (NIBR), University of Liverpool, Universität Heidelberg [Heidelberg], Medizinische Fakultät Mannheim, The Alan Turing Institute, Ninewells Hospital and Medical School [Dundee], Universität Greifswald - University of Greifswald, German Center for Cardiovascular Research (DZHK), Berlin Institute of Health (BIH), University of Minnesota System, Regeneron Pharmaceuticals [Tarrytown], Department of Clinical Sciences, Cardiovascular Epidemiology, Skane University Hospital [Lund], Institute of Genomics [Tartu, Estonia], University of Tartu, Robertson Centre for Biostatistics, University of Glasgow, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Uppsala University, Brigham & Women’s Hospital [Boston] (BWH), University of Maryland School of Medicine, University of Maryland System, School of Science and Engineering (Reykjavik University), Carver College of Medicine, University of Iowa, Geisinger Health System [Danville, PA, USA], Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, Stanford School of Medicine [Stanford], Stanford Medicine, Stanford University-Stanford University, Stanford Cardiovascular Institute, Uppsala Universitet [Uppsala], Leiden University Medical Center (LUMC), Einthoven Laboratory for Experimental Vascular Medicine (ELEVM - LEIDEN), Department of Public Health and Primary Care, University of Cambridge [UK] (CAM), Rigshospitalet [Copenhagen], Copenhagen University Hospital, Glenfield Hospital, University Hospitals Leicester, MRC Epidemiology Unit, University of Cambridge [UK] (CAM)-Institute of Metabolic Science, Big Data Institute, University of Oxford [Oxford], University of Iowa [Iowa City], The Wellcome Trust Centre for Human Genetics [Oxford], Synlab Academy, Synlab Holding Deutschland GmbH, Mannheim, Medical University Graz, Skane University Hospital [Malmo], Vanderbilt University School of Medicine [Nashville], University of Edinburgh, Université médicale de Vienne, Autriche, National Institute for Health and Welfare [Helsinki], University of Turku, Birmingham Women's and Children's NHS Foundation Trust, Kaiser Permanente, Harbor UCLA Medical Center [Torrance, Ca.], Los Angeles Biomedical Research Institute (LA BioMed), University Medical Center [Utrecht], University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Seattle Epidemiologic Research and Information Center [Seattle], Institute of Cardiovascular and Medical Sciences [Glasgow], University of Glasgow, Department of Cardiology, Södersjukhuset, Stockholm, Estonian Genome and Medicine, Landspitali National University Hospital of Iceland, University of Iceland [Reykjavik], Aalborg University [Denmark] (AAU), Institut de Recherches SERVIER (IRS), Interfaculty Institute for Genetics and Functional Genomics, Ernst-Moritz-Arndt-Universität Greifswald, GlaxoSmithKline, Glaxo Smith Kline, Northeastern Ohio Medical University (NEOMED), Centre d'investigation clinique plurithématique Pierre Drouin [Nancy] (CIC-P), Centre d'investigation clinique [Nancy] (CIC), Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM), Défaillance Cardiovasculaire Aiguë et Chronique (DCAC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Cardiovascular and Renal Clinical Trialists [Vandoeuvre-les-Nancy] (INI-CRCT), Institut Lorrain du Coeur et des Vaisseaux Louis Mathieu [Nancy], French-Clinical Research Infrastructure Network - F-CRIN [Paris] (Cardiovascular & Renal Clinical Trialists - CRCT ), MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, British Heart Foundation Glasgow Cardiovascular Research Centre (BHF GCRC), University of Glasgow-NHS Greater Glasgow and Clyde, Department of Cardiovascular Sciences [Leicester], University of Leicester, Queensland Brain Institute, Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, University of Dundee, National Heart and Lung Institute [London] (NHLI), Imperial College London-Royal Brompton and Harefield NHS Foundation Trust, Atherosclerosis Risk in Communities Study (ARIC)The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts N01-HC-55015, N01-HC- 55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC55021, N01-HC-55022, R01HL087641, R01HL59367, R01HL086694 and RC2 HL102419, National Human Genome Research Institute contract U01HG004402, and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. A systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT- CHF)This project was funded by a grant from the European Commission (FP7‐242209‐ BIOSTAT‐CHF, EudraCT 2010–020808–29). Cardiovascular Health Study (CHS) This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, HHSN268200960009C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, and NHLBI grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, and U01HL130114 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through R01AG023629 from the National Institute on Aging (NIA). A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. deCODE Heart Failure Study (deCODE) We at deCODE thank the women and men of Iceland that have participated in our studies and our colleagues that contributed to data collection and processing. DiscovEHR We acknowledge and thank all participants in Geisinger’s MyCode Community Health Initiative for their support and permission to use their health and genomic information in the DiscovEHR collaboration. This work was supported by the Regeneron Genetics Center and Geisinger. Estonian Genome Center at the University of Tartu (EGCUT) This study was supported by Estonian Research Council Grant IUT20-60, EU, H2020 grant 692145, European Union through the European Regional Development Fund (Project No. 2014-2020.4.01.15-0012) GENTRANSMED. Eplerenone Post-Acute Myocardial Infarction Heart Failure Efficacy and Survival Study (EPHESUS) The EPHESUS was supported by Pfizer, Inc. The European Prospective Investigation of Cancer, Norfolk study (EPIC-Norfolk) The EPIC-Norfolk Study is supported by programme grants from the Medical Research Council UK (G1000143) and Cancer Research UK (C864/A14136) and with additional support from the European Union, Stroke Association, British Heart Foundation, Research into Ageing, Department of Health, The Wellcome Trust and the Food Standards Agency. NJW and CL also acknowledge support from the Medical Research Council, UK (MC_UU_12015/1, MC_PC_13048). We thank all EPIC participants and staff for their contribution to the study, and thank staff from the Technical, Field Epidemiology and Data Functional Group Teams of the Medical Research Council Epidemiology Unit in Cambridge, UK, for carrying out sample preparation, DNA provision and quality control, genotyping and data handling work. Framingham Heart Study (FHS) This work was conducted using data and resources from the Framingham Heart Study (FHS) of the National Heart Lung and Blood Institute and Boston University School of Medicine. The study was supported by the National Heart, Lung and Blood Institute’s Framingham Heart Study (Contract No. N01-HC-25195 and HHSN268201500001I) and its contract with Affymetrix, Inc for genotyping services (Contract No.N02-HL-6-4278). The work was also supported by R01 HL093328, R01 HL105993, and R01 HL71039 (PI: Ramachandran). FINRISK V.S. has been supported by the Finnish Foundation for Cardiovascular Research. Genetics of Diabetes Audit and Research Tayside Scotland GoDARTS) The Wellcome Trust United Kingdom Type 2 Diabetes Case Control Collection (supporting GoDARTS) was funded by the Wellcome Trust (072960/Z/03/Z, 084726/Z/08/Z, 084727/Z/08/Z, 085475/Z/08/Z, 085475/B/08/Z) and as part of the EU IMI-SUMMIT programme. We acknowledge the support of the Health Informatics Centre, University of Dundee, for managing and supplying the anonymized data and NHS Tayside, the original data owner. The Genetic Risk Assessment of Defibrillator Events (GRADE) NIH-NHLBI R01 HL77398 (Genetic Modulators of Sudden Death). S.L. is supported by NIH grant 1R01HL139731 and American Heart Association 18SFRN34250007. The LUdwigshafen RIsk and Cardiovascular Health (LURIC) study We extend our appreciation to the participants of the LURIC study, without their collaboration, this article would not have been written. We thank the LURIC study team who were either temporarily or permanently involved in patient recruitment as well as sample and data handling, in addition to the laboratory staff at the Ludwigshafen General Hospital and the Universities of Freiburg and Ulm, Germany. LURIC has received funding from the 7th Framework Program (RiskyCAD, grant agreement number 305739 and Atheroremo, grant agreement number 201668) of the European Union. Malmö Diet and Cancer Study (MDCS) J. Gustav Smith was supported by grants from the Swedish Heart-Lung Foundation (2016- 0134 and 2016-0315), the Swedish Research Council (2017-02554), the European Research Council (ERC-STG-2015-679242), the Crafoord Foundation, Skåne University Hospital, the Scania county, governmental funding of clinical research within the Swedish National Health Service, a generous donation from the Knut and Alice Wallenberg foundation to the Wallenberg Center for Molecular Medicine in Lund, and funding from the Swedish Research Council (Linnaeus grant Dnr 349-2006-237, Strategic Research Area Exodiab Dnr 2009-1039) and Swedish Foundation for Strategic Research (Dnr IRC15- 0067) to the Lund University Diabetes Center. The Malmo Diet and Cancer Study was made possible by grants from the Swedish Cancer Society, the Swedish Medical Research Council, the Swedish Dairy Association, and the Malmo city council. Penn Heart Failure Study (PHFS) The study was supported by NIH grants (NIH R01L088577 and NIH R01H105993). Prevention of REnal and Vascular ENd-stage Disease (PREVEND) The Prevention of Renal and Vascular Endstage Disease Study (PREVEND) genetics is supported by the Dutch Kidney Foundation (Grant E033), the EU project grant GENECURE (FP-6 LSHM CT 2006 037697), the National Institutes of Health (grant LM010098), the Netherlands organisation for health research and development (NWO VENI grant 916.761.70), and the Dutch Inter University Cardiology Institute Netherlands (ICIN). Niek Verweij was supported by NWO VENI grant 016.186.125. PROspective Study of Pravastatin in the Elderly at Risk for vascular disease (PROSPER)The PROSPER study was supported by an investigator-initiated grant obtained from Bristol- Myers Squibb. Support for genotyping was provided by the seventh framework program of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). J.W.J. is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Study of Health in Pomerania (SHIP) SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network ‘Greifswald Approach to Individualized Medicine (GANI_MED)’ funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg- West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. Stabilization of Plaque using Darapladib-Thrombolysis in Myocardial Infarction 52 (SOLID)SOLID-TIMI 52 was funded by GlaxoSmithKline. TwinGene (TwinGene) TwinGene received funding from the Swedish Research Council (M-2005-1112), GenomEUtwin (EU/QLRT-2001-01254, QLG2-CT-2002-01254), NIH DK U01-066134, The Swedish Foundation for Strategic Research (SSF) and the Heart and Lung foundation no. 20070481. TwinGene is part of the Swedish Twin Registry which is managed by Karolinska Institutet and receives funding through the Swedish Research Council (2017–00641). UK Biobank (UKBiobank) This research has been conducted using the UK Biobank Resource under Application Number 15422. This work was supported in part by grants to R.T.L. from the EU/EFPIA Innovative Medicines Initiative 2 Joint Undertaking BigData@Heart grant no. 116074, MRC Proximity to Discovery Award Scheme, the American Heart Association Institute for Precision Mecidine, Pfizer Ltd, the University College London British Heart Foundation Research Accelerator (AA/18/6/34223), and was supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. A. H. is supported by the British Heart Foundation Cardiovascular Biomedicine PhD studentship. R.T.L is supported by a UK Research and Innovation Rutherford Fellowship and was previously supported by a National Institutes of Health Research Clinical Lectureship. Uppsala Longitudinal Study of Adult Men (ULSAM) J.Ä. is supported by the Swedish Research Council and the Swedish Heart Lung foundation. C.M.L is supported by the Li Ka Shing Foundation, WT-SSI/John Fell funds and by the NIHR Biomedical Research Centre, Oxford, by Widenlife and NIH (5P50HD028138- 27). Women’s Genome Health Study (WGHS) The WGHS is supported by the National Heart, Lung, and Blood Institute (HL043851 and HL080467, HL099355) and the National Cancer Institute (CA047988 and UM1CA182913), with collaborative scientific support and funding for genotyping provided by Amgen., Epidemiology, Internal Medicine, Læknadeild (HÍ), Faculty of Medicine (UI), Verkfræði- og náttúruvísindasvið (HÍ), School of Engineering and Natural Sciences (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, and University of Iceland

Subjects
0301 basic medicine, Dánartíðni, Epidemiology, LOCI, 45/43, General Physics and Astronomy, Muscle Proteins, Genome-wide association study, Disease, Coronary Artery Disease, 030204 cardiovascular system & hematology, Bioinformatics, Genome-wide association studies, DISEASE, Ventricular Function, Left, Coronary artery disease, 0302 clinical medicine, Risk Factors, Atrial Fibrillation, IMPUTATION, Medicine, Blóðrásarsjúkdómar, 692/308/174, lcsh:Science, 2. Zero hunger, RISK, Multidisciplinary, Microfilament Proteins, article, Atrial fibrillation, Mendelian Randomization Analysis, CATALOG, 3. Good health, OBESITY, Erfðarannsóknir, Cardiomyopathies, Medical Genetics, Cyclin-Dependent Kinase Inhibitor p21, Science, 631/208/205/2138, Heart failure, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, 631/443/592/2727, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, RESOURCE, Humans, Mortality, METAANALYSIS, Genetic association, Medicinsk genetik, Adaptor Proteins, Signal Transducing, Heart Failure, HYPERTENSION, business.industry, Case-control study, Klinisk medicin, 692/699/75/230, General Chemistry, Cardiovascular genetics, medicine.disease, R1, 030104 developmental biology, Case-Control Studies, lcsh:Q, Morbidity, Clinical Medicine, business, Apoptosis Regulatory Proteins, Carrier Proteins, Genome-Wide Association Study
Abstract

Publisher's version (útgefin grein), Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies., We acknowledge the contribution from the EchoGen Consortium.

Published
2020

24. Discovery and refinement of loci associated with lipid levels

Author

Willer, Cristen J, Schmidt, Ellen M, Sengupta, Sebanti, Peloso, Gina M, Gustafsson, Stefan, Kanoni, Stavroula, Ganna, Andrea, Chen, Jin, Buchkovich, Martin L, Mora, Samia, Beckmann, Jacques S, Bragg-Gresham, Jennifer L, Chang, Hsing-Yi, Demirkan, Ayşe, Den Hertog, Heleen M, Do, Ron, Donnelly, Louise A, Ehret, Georg B, Esko, Tõnu, Feitosa, Mary F, Ferreira, Teresa, Fischer, Krista, Fontanillas, Pierre, Fraser, Ross M, Freitag, Daniel F, Gurdasani, Deepti, Heikkilä, Kauko, Hyppönen, Elina, Isaacs, Aaron, Jackson, Anne U, Johansson, Åsa, Johnson, Toby, Kaakinen, Marika, Kettunen, Johannes, Kleber, Marcus E, Li, Xiaohui, Luan, Jian'an, Lyytikäinen, Leo-Pekka, Magnusson, Patrik KE, Mangino, Massimo, Mihailov, Evelin, Montasser, May E, Müller-Nurasyid, Martina, Nolte, Ilja M, O'Connell, Jeffrey R, Palmer, Cameron D, Perola, Markus, Petersen, Ann-Kristin, Sanna, Serena, Saxena, Richa, Service, Susan K, Shah, Sonia, Shungin, Dmitry, Sidore, Carlo, Song, Ci, Strawbridge, Rona J, Surakka, Ida, Tanaka, Toshiko, Teslovich, Tanya M, Thorleifsson, Gudmar, Van den Herik, Evita G, Voight, Benjamin F, Volcik, Kelly A, Waite, Lindsay L, Wong, Andrew, Wu, Ying, Zhang, Weihua, Absher, Devin, Asiki, Gershim, Barroso, Inês, Been, Latonya F, Bolton, Jennifer L, Bonnycastle, Lori L, Brambilla, Paolo, Burnett, Mary S, Cesana, Giancarlo, Dimitriou, Maria, Doney, Alex SF, Döring, Angela, Elliott, Paul, Epstein, Stephen E, Ingi Eyjolfsson, Gudmundur, Gigante, Bruna, Goodarzi, Mark O, Grallert, Harald, Gravito, Martha L, Groves, Christopher J, Hallmans, Göran, Hartikainen, Anna-Liisa, Hayward, Caroline, Hernandez, Dena, Hicks, Andrew A, Holm, Hilma, Hung, Yi-Jen, Illig, Thomas, Jones, Michelle R, Kaleebu, Pontiano, Kastelein, John JP, Khaw, Kay-Tee, and Kim, Eric

Subjects
Asian Continental Ancestry Group, Genotype, HDL, European Continental Ancestry Group, Black People, Coronary Artery Disease, Cardiovascular, Medical and Health Sciences, White People, LDL, Asian People, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Aetiology, Heart Disease - Coronary Heart Disease, Metabolic and endocrine, Triglycerides, African Continental Ancestry Group, Nutrition, Human Genome, Global Lipids Genetics Consortium, Biological Sciences, Atherosclerosis, Lipids, Heart Disease, Cholesterol, lipids (amino acids, peptides, and proteins), Genome-Wide Association Study, Developmental Biology
Abstract

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.

Published
2013

25. Common variants associated with plasma triglycerides and risk for coronary artery disease

Author

Do, Ron, Willer, Cristen J, Schmidt, Ellen M, Sengupta, Sebanti, Gao, Chi, Peloso, Gina M, Gustafsson, Stefan, Kanoni, Stavroula, Ganna, Andrea, Chen, Jin, Buchkovich, Martin L, Mora, Samia, Beckmann, Jacques S, Bragg-Gresham, Jennifer L, Chang, Hsing-Yi, Demirkan, Ayşe, Den Hertog, Heleen M, Donnelly, Louise A, Ehret, Georg B, Esko, Tõnu, Feitosa, Mary F, Ferreira, Teresa, Fischer, Krista, Fontanillas, Pierre, Fraser, Ross M, Freitag, Daniel F, Gurdasani, Deepti, Heikkilä, Kauko, Hyppönen, Elina, Isaacs, Aaron, Jackson, Anne U, Johansson, Asa, Johnson, Toby, Kaakinen, Marika, Kettunen, Johannes, Kleber, Marcus E, Li, Xiaohui, Luan, Jian'an, Lyytikäinen, Leo-Pekka, Magnusson, Patrik KE, Mangino, Massimo, Mihailov, Evelin, Montasser, May E, Müller-Nurasyid, Martina, Nolte, Ilja M, O'Connell, Jeffrey R, Palmer, Cameron D, Perola, Markus, Petersen, Ann-Kristin, Sanna, Serena, Saxena, Richa, Service, Susan K, Shah, Sonia, Shungin, Dmitry, Sidore, Carlo, Song, Ci, Strawbridge, Rona J, Surakka, Ida, Tanaka, Toshiko, Teslovich, Tanya M, Thorleifsson, Gudmar, Van den Herik, Evita G, Voight, Benjamin F, Volcik, Kelly A, Waite, Lindsay L, Wong, Andrew, Wu, Ying, Zhang, Weihua, Absher, Devin, Asiki, Gershim, Barroso, Inês, Been, Latonya F, Bolton, Jennifer L, Bonnycastle, Lori L, Brambilla, Paolo, Burnett, Mary S, Cesana, Giancarlo, Dimitriou, Maria, Doney, Alex SF, Döring, Angela, Elliott, Paul, Epstein, Stephen E, Eyjolfsson, Gudmundur Ingi, Gigante, Bruna, Goodarzi, Mark O, Grallert, Harald, Gravito, Martha L, Groves, Christopher J, Hallmans, Göran, Hartikainen, Anna-Liisa, Hayward, Caroline, Hernandez, Dena, Hicks, Andrew A, Holm, Hilma, Hung, Yi-Jen, Illig, Thomas, Jones, Michelle R, Kaleebu, Pontiano, Kastelein, John JP, and Khaw, Kay-Tee

Subjects
HDL, Prevention, Biological Transport, Single Nucleotide, Coronary Artery Disease, Biological Sciences, Cardiovascular, Atherosclerosis, Medical and Health Sciences, LDL, Heart Disease, Cholesterol, Risk Factors, 2.1 Biological and endogenous factors, Humans, lipids (amino acids, peptides, and proteins), Aetiology, Polymorphism, Heart Disease - Coronary Heart Disease, Triglycerides, Developmental Biology
Abstract

Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

Published
2013

26. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

Author

Shah, Sonia, Henry, Albert, Roselli, Carolina, Lin, Honghuang, Sveinbjörnsson, Garðar, Fatemifar, Ghazaleh, Hedman, Åsa K, Wilk, Jemma B, Morley, Michael P, Chaffin, Mark D, Helgadottir, Anna, Verweij, Niek, Dehghan, Abbas, Almgren, Peter, Andersson, Charlotte, Aragam, Krishna G, Ärnlöv, Johan, Backman, Joshua D, Biggs, Mary L, Bloom, Heather L, Brandimarto, Jeffrey, Brown, Michael R, Buckbinder, Leonard, Carey, David J, Chasman, Daniel I, Chen, Xing, Chen, Xu, Chung, Jonathan, Chutkow, William, Cook, James P, Delgado, Graciela E, Denaxas, Spiros, Doney, Alexander S, Dörr, Marcus, Dudley, Samuel C, Dunn, Michael E, Engström, Gunnar, Esko, Tõnu, Felix, Stephan B, Finan, Chris, Ford, Ian, Ghanbari, Mohsen, Ghasemi, Sahar, Giedraitis, Vilmantas, Giulianini, Franco, Gottdiener, John S, Gross, Stefan, Guðbjartsson, Daníel F, Gutmann, Rebecca, Haggerty, Christopher M, Van Der Harst, Pim, Hyde, Craig L, Ingelsson, Erik, Jukema, J Wouter, Kavousi, Maryam, Khaw, Kay-Tee, Kleber, Marcus E, Køber, Lars, Koekemoer, Andrea, Langenberg, Claudia, Lind, Lars, Lindgren, Cecilia M, London, Barry, Lotta, Luca A, Lovering, Ruth C, Luan, Jian'an, Magnusson, Patrik, Mahajan, Anubha, Margulies, Kenneth B, März, Winfried, Melander, Olle, Mordi, Ify R, Morgan, Thomas, Morris, Andrew D, Morris, Andrew P, Morrison, Alanna C, Nagle, Michael W, Nelson, Christopher P, Niessner, Alexander, Niiranen, Teemu, O'Donoghue, Michelle L, Owens, Anjali T, Palmer, Colin NA, Parry, Helen M, Perola, Markus, Portilla-Fernandez, Eliana, Psaty, Bruce M, Regeneron Genetics Center, Rice, Kenneth M, Ridker, Paul M, Romaine, Simon PR, Rotter, Jerome I, Salo, Perttu, Salomaa, Veikko, Van Setten, Jessica, Shalaby, Alaa A, Smelser, Diane T, Smith, Nicholas L, Stender, Steen, Stott, David J, Svensson, Per, Tammesoo, Mari-Liis, Taylor, Kent D, Teder-Laving, Maris, Teumer, Alexander, Thorgeirsson, Guðmundur, Thorsteinsdottir, Unnur, Torp-Pedersen, Christian, Trompet, Stella, Tyl, Benoit, Uitterlinden, Andre G, Veluchamy, Abirami, Völker, Uwe, Voors, Adriaan A, Wang, Xiaosong, Wareham, Nicholas J, Waterworth, Dawn, Weeke, Peter E, Weiss, Raul, Wiggins, Kerri L, Xing, Heming, Yerges-Armstrong, Laura M, Yu, Bing, Zannad, Faiez, Zhao, Jing Hua, Hemingway, Harry, Samani, Nilesh J, McMurray, John JV, Yang, Jian, Visscher, Peter M, Newton-Cheh, Christopher, Malarstig, Anders, Holm, Hilma, Lubitz, Steven A, Sattar, Naveed, Holmes, Michael V, Cappola, Thomas P, Asselbergs, Folkert W, Hingorani, Aroon D, Kuchenbaecker, Karoline, Ellinor, Patrick T, Lang, Chim C, Stefansson, Kari, Smith, J Gustav, Vasan, Ramachandran S, Swerdlow, Daniel I, and Lumbers, R Thomas

Subjects
2. Zero hunger, Cyclin-Dependent Kinase Inhibitor p21, Heart Failure, Microfilament Proteins, Muscle Proteins, Coronary Artery Disease, Mendelian Randomization Analysis, Ventricular Function, Left, 3. Good health, Risk Factors, Case-Control Studies, Atrial Fibrillation, Humans, Apoptosis Regulatory Proteins, Cardiomyopathies, Carrier Proteins, Adaptor Proteins, Signal Transducing, Genome-Wide Association Study
Abstract

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.

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