Publications by authors named "Paul I W de Bakker"

208 Publications

Exome-chip association analysis of intracranial aneurysms.

Neurology 2020 02 15;94(5):e481-e488. Epub 2019 Nov 15.

From the Department of Neurology and Neurosurgery (F.N.G.v.H., G.J.E.R., Y.M.R.), Brain Center Rudolf Magnus, Department of Cardiology (J.v.S.), Department of Medical Genetics (P.I.W.d.B.), Centre for Molecular Medicine, and Department of Epidemiology (M.L.B., I.V., P.I.W.d.B.), Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, the Netherlands; Department of Medical and Molecular Genetics (D.L., T.F.), Indiana University School of Medicine, Indianapolis; and Department of Neurology and Rehabilitation Medicine (J.B., D.W.), University of Cincinnati School of Medicine, OH.

Objective: To investigate to what extent low-frequency genetic variants (with minor allele frequencies <5%) affect the risk of intracranial aneurysms (IAs).

Methods: One thousand fifty-six patients with IA and 2,097 population-based controls from the Netherlands were genotyped with the Illumina HumanExome BeadChip. After quality control (QC) of samples and single nucleotide variants (SNVs), we conducted a single variant analysis using the Fisher exact test. We also performed the variable threshold (VT) test and the sequence kernel association test (SKAT) at different minor allele count (MAC) thresholds of >5 and >0 to test the hypothesis that multiple variants within the same gene are associated with IA risk. Significant results were tested in a replication cohort of 425 patients with IA and 311 controls, and results of the 2 cohorts were combined in a meta-analysis.

Results: After QC, 995 patients with IA and 2,080 controls remained for further analysis. The single variant analysis comprising 46,534 SNVs did not identify significant loci at the genome-wide level. The gene-based tests showed a statistically significant association for fibulin 2 () (best = 1 × 10 for the VT test, MAC >5). Associations were not statistically significant in the independent but smaller replication cohort ( > 0.57) but became slightly stronger in a meta-analysis of the 2 cohorts (best = 4.8 × 10 for the SKAT, MAC ≥1).

Conclusion: Gene-based tests indicated an association for , a gene encoding an extracellular matrix protein implicated in vascular wall remodeling, but independent validation in larger cohorts is warranted. We did not identify any significant associations for single low-frequency genetic variants.
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http://dx.doi.org/10.1212/WNL.0000000000008665DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080288PMC
February 2020

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Nat Genet 2019 03 18;51(3):452-469. Epub 2019 Feb 18.

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

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.
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http://dx.doi.org/10.1038/s41588-018-0334-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6560635PMC
March 2019

Genome-wide association meta-analysis of 30,000 samples identifies seven novel loci for quantitative ECG traits.

Eur J Hum Genet 2019 06 24;27(6):952-962. Epub 2019 Jan 24.

Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital-The Capital Region, Copenhagen, Denmark.

Genome-wide association studies (GWAS) of quantitative electrocardiographic (ECG) traits in large consortia have identified more than 130 loci associated with QT interval, QRS duration, PR interval, and heart rate (RR interval). In the current study, we meta-analyzed genome-wide association results from 30,000 mostly Dutch samples on four ECG traits: PR interval, QRS duration, QT interval, and RR interval. SNP genotype data was imputed using the Genome of the Netherlands reference panel encompassing 19 million SNPs, including millions of rare SNPs (minor allele frequency < 5%). In addition to many known loci, we identified seven novel locus-trait associations: KCND3, NR3C1, and PLN for PR interval, KCNE1, SGIP1, and NFKB1 for QT interval, and ATP2A2 for QRS duration, of which six were successfully replicated. At these seven loci, we performed conditional analyses and annotated significant SNPs (in exons and regulatory regions), demonstrating involvement of cardiac-related pathways and regulation of nearby genes.
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http://dx.doi.org/10.1038/s41431-018-0295-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6777533PMC
June 2019

Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting.

Neurology 2019 Jan 16. Epub 2019 Jan 16.

Objective: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts.

Methods: We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI.

Results: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, = 1.77 × 10; and LINC00539/ZDHHC20, = 5.82 × 10. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits ( value for BI, = 9.38 × 10; = 5.23 × 10 for hypertension), smoking ( = 4.4 × 10; = 1.2 × 10), diabetes ( = 1.7 × 10; = 2.8 × 10), previous cardiovascular disease ( = 1.0 × 10; = 2.3 × 10), stroke ( = 3.9 × 10; = 3.2 × 10), and MRI-defined white matter hyperintensity burden ( = 1.43 × 10; = 3.16 × 10), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI ( ≤ 0.0022), without indication of directional pleiotropy.

Conclusion: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.
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http://dx.doi.org/10.1212/WNL.0000000000006851DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6369905PMC
January 2019

Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes.

Neurol Genet 2018 Dec 3;4(6):e293. Epub 2018 Dec 3.

Department of Genetics (S.L.P., P.I.W.d. B.), University Medical Center Utrecht, Utrecht University, The Netherlands; P.I.W.d.B. is now with Computational Genomics, Vertex Pharmaceuticals, Boston, MA; Li Ka Shing Centre for Health Information and Discovery (S.L.P.), The Big Data Institute, University of Oxford, United Kingdom; Program in Medical and Population Genetics (S.L.P., L.-C.W., S.H.C., J.R., P.T.E., S.A.L., C.D.A.), Broad Institute, Cambridge, MA; Cardiovascular Research Center (L.-C.W., P.T.E., S.A.L.), Center for Genomic Medicine (J.R., C.D.A.), J.P. Kistler Stroke Research Center (J.R., C.D.A.), and Cardiac Arrhythmia Service (P.T.E., S.A.L.), Massachusetts General Hospital, Boston; Department of Medicine (P.F.M., B.D.M.), Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore; National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study (L.T., E.J.B.); Department of Biostatistics (L.T.) and Department of Epidemiology (E.J.B.), Boston University School of Public Health, MA; Geriatrics Research and Education Clinical Center (B.D.M.), Baltimore Veterans Administration Medical Center, MD; Cardiology Preventive Medicine Sections (E.J.B.), Evans Department of Medicine, Boston University School of Medicine; Department of Neurology (S.J.K.), University of Maryland School of Medicine; and Department of Neurology (S.J.K.), Veterans Affairs Medical Center, Baltimore, MD.

Objective: We sought to assess whether genetic risk factors for atrial fibrillation (AF) can explain cardioembolic stroke risk.

Methods: We evaluated genetic correlations between a previous genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.

Results: We observed a strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson r = 0.77 and 0.76, respectively, across SNPs with < 4.4 × 10 in the previous AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio [OR] per SD = 1.40, = 1.45 × 10), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per SD = 1.07, = 0.004), but no other primary stroke subtypes (all > 0.1).

Conclusions: Genetic risk of AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.
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http://dx.doi.org/10.1212/NXG.0000000000000293DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6283455PMC
December 2018

Genetic Susceptibility Loci for Cardiovascular Disease and Their Impact on Atherosclerotic Plaques.

Circ Genom Precis Med 2018 09;11(9):e002115

Laboratory of Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University Utrecht, The Netherlands (S.W.v.d.L., M.A.S., S.H., H.M.d.R., G.P.).

Background: Atherosclerosis is a chronic inflammatory disease in part caused by lipid uptake in the vascular wall, but the exact underlying mechanisms leading to acute myocardial infarction and stroke remain poorly understood. Large consortia identified genetic susceptibility loci that associate with large artery ischemic stroke and coronary artery disease. However, deciphering their underlying mechanisms are challenging. Histological studies identified destabilizing characteristics in human atherosclerotic plaques that associate with clinical outcome. To what extent established susceptibility loci for large artery ischemic stroke and coronary artery disease relate to plaque characteristics is thus far unknown but may point to novel mechanisms.

Methods: We studied the associations of 61 established cardiovascular risk loci with 7 histological plaque characteristics assessed in 1443 carotid plaque specimens from the Athero-Express Biobank Study. We also assessed if the genotyped cardiovascular risk loci impact the tissue-specific gene expression in 2 independent biobanks, Biobank of Karolinska Endarterectomy and Stockholm Atherosclerosis Gene Expression.

Results: A total of 21 established risk variants (out of 61) nominally associated to a plaque characteristic. One variant (rs12539895, risk allele A) at 7q22 associated to a reduction of intraplaque fat, P=5.09×10 after correction for multiple testing. We further characterized this 7q22 Locus and show tissue-specific effects of rs12539895 on HBP1 expression in plaques and COG5 expression in whole blood and provide data from public resources showing an association with decreased LDL (low-density lipoprotein) and increase HDL (high-density lipoprotein) in the blood.

Conclusions: Our study supports the view that cardiovascular susceptibility loci may exert their effect by influencing the atherosclerotic plaque characteristics.
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http://dx.doi.org/10.1161/CIRCGEN.118.002115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664607PMC
September 2018

A comprehensive evaluation of the genetic architecture of sudden cardiac arrest.

Eur Heart J 2018 11;39(44):3961-3969

Department of Statistics, University of Auckland, Private Bag 92014, Auckland, New Zealand.

Aims: Sudden cardiac arrest (SCA) accounts for 10% of adult mortality in Western populations. We aim to identify potential loci associated with SCA and to identify risk factors causally associated with SCA.

Methods And Results: We carried out a large genome-wide association study (GWAS) for SCA (n = 3939 cases, 25 989 non-cases) to examine common variation genome-wide and in candidate arrhythmia genes. We also exploited Mendelian randomization (MR) methods using cross-trait multi-variant genetic risk score associations (GRSA) to assess causal relationships of 18 risk factors with SCA. No variants were associated with SCA at genome-wide significance, nor were common variants in candidate arrhythmia genes associated with SCA at nominal significance. Using cross-trait GRSA, we established genetic correlation between SCA and (i) coronary artery disease (CAD) and traditional CAD risk factors (blood pressure, lipids, and diabetes), (ii) height and BMI, and (iii) electrical instability traits (QT and atrial fibrillation), suggesting aetiologic roles for these traits in SCA risk.

Conclusions: Our findings show that a comprehensive approach to the genetic architecture of SCA can shed light on the determinants of a complex life-threatening condition with multiple influencing factors in the general population. The results of this genetic analysis, both positive and negative findings, have implications for evaluating the genetic architecture of patients with a family history of SCA, and for efforts to prevent SCA in high-risk populations and the general community.
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http://dx.doi.org/10.1093/eurheartj/ehy474DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6247663PMC
November 2018

PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity.

Nat Commun 2018 07 25;9(1):2904. Epub 2018 Jul 25.

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA.

Electrocardiographic PR interval measures atrio-ventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. Our genome-wide association study of over 92,000 European-descent individuals identifies 44 PR interval loci (34 novel). Examination of these loci reveals known and previously not-yet-reported biological processes involved in cardiac atrial electrical activity. Genes in these loci are over-represented in cardiac disease processes including heart block and atrial fibrillation. Variants in over half of the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with missense variants. Six additional loci were identified either by meta-analysis of ~105,000 African and European-descent individuals and/or by pleiotropic analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation. These findings implicate developmental pathways, and identify transcription factors, ion-channel genes, and cell-junction/cell-signaling proteins in atrio-ventricular conduction, identifying potential targets for drug development.
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http://dx.doi.org/10.1038/s41467-018-04766-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6060178PMC
July 2018

Author Correction: A replication study of genetic risk loci for ischemic stroke in a Dutch population: a case-control study.

Sci Rep 2018 Apr 11;8(1):6057. Epub 2018 Apr 11.

Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.
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http://dx.doi.org/10.1038/s41598-018-22952-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5895799PMC
April 2018

Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes.

Nat Genet 2018 04 12;50(4):524-537. Epub 2018 Mar 12.

Institute of Cardiovascular Research, Royal Holloway University of London, London, UK, and Ashford and St Peters Hospital, Surrey, UK.

Stroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.
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http://dx.doi.org/10.1038/s41588-018-0058-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5968830PMC
April 2018

Genetic Association of Lipids and Lipid Drug Targets With Abdominal Aortic Aneurysm: A Meta-analysis.

JAMA Cardiol 2018 01;3(1):26-33

Department of Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, England.

Importance: Risk factors for abdominal aortic aneurysm (AAA) are largely unknown, which has hampered the development of nonsurgical treatments to alter the natural history of disease.

Objective: To investigate the association between lipid-associated single-nucleotide polymorphisms (SNPs) and AAA risk.

Design, Setting, And Participants: Genetic risk scores, composed of lipid trait-associated SNPs, were constructed and tested for their association with AAA using conventional (inverse-variance weighted) mendelian randomization (MR) and data from international AAA genome-wide association studies. Sensitivity analyses to account for potential genetic pleiotropy included MR-Egger and weighted median MR, and multivariable MR method was used to test the independent association of lipids with AAA risk. The association between AAA and SNPs in loci that can act as proxies for drug targets was also assessed. Data collection took place between January 9, 2015, and January 4, 2016. Data analysis was conducted between January 4, 2015, and December 31, 2016.

Exposures: Genetic elevation of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG).

Main Outcomes And Measures: The association between genetic risk scores of lipid-associated SNPs and AAA risk, as well as the association between SNPs in lipid drug targets (HMGCR, CETP, and PCSK9) and AAA risk.

Results: Up to 4914 cases and 48 002 controls were included in our analysis. A 1-SD genetic elevation of LDL-C was associated with increased AAA risk (odds ratio [OR], 1.66; 95% CI, 1.41-1.96; P = 1.1 × 10-9). For HDL-C, a 1-SD increase was associated with reduced AAA risk (OR, 0.67; 95% CI, 0.55-0.82; P = 8.3 × 10-5), whereas a 1-SD increase in triglycerides was associated with increased AAA risk (OR, 1.69; 95% CI, 1.38-2.07; P = 5.2 × 10-7). In multivariable MR analysis and both MR-Egger and weighted median MR methods, the association of each lipid fraction with AAA risk remained largely unchanged. The LDL-C-reducing allele of rs12916 in HMGCR was associated with AAA risk (OR, 0.93; 95% CI, 0.89-0.98; P = .009). The HDL-C-raising allele of rs3764261 in CETP was associated with lower AAA risk (OR, 0.89; 95% CI, 0.85-0.94; P = 3.7 × 10-7). Finally, the LDL-C-lowering allele of rs11206510 in PCSK9 was weakly associated with a lower AAA risk (OR, 0.94; 95% CI, 0.88-1.00; P = .04), but a second independent LDL-C-lowering variant in PCSK9 (rs2479409) was not associated with AAA risk (OR, 0.97; 95% CI, 0.92-1.02; P = .28).

Conclusions And Relevance: The MR analyses in this study lend support to the hypothesis that lipids play an important role in the etiology of AAA. Analyses of individual genetic variants used as proxies for drug targets support LDL-C lowering as a potential effective treatment strategy for preventing and managing AAA.
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http://dx.doi.org/10.1001/jamacardio.2017.4293DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5833524PMC
January 2018

Evaluating the Impact of Functional Genetic Variation on HIV-1 Control.

J Infect Dis 2017 11;216(9):1063-1069

Global Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Switzerland.

Background: Previous genetic association studies of human immunodeficiency virus-1 (HIV-1) progression have focused on common human genetic variation ascertained through genome-wide genotyping.

Methods: We sought to systematically assess the full spectrum of functional variation in protein coding gene regions on HIV-1 progression through exome sequencing of 1327 individuals. Genetic variants were tested individually and in aggregate across genes and gene sets for an influence on HIV-1 viral load.

Results: Multiple single variants within the major histocompatibility complex (MHC) region were observed to be strongly associated with HIV-1 outcome, consistent with the known impact of classical HLA alleles. However, no single variant or gene located outside of the MHC region was significantly associated with HIV progression. Set-based association testing focusing on genes identified as being essential for HIV replication in genome-wide small interfering RNA (siRNA) and clustered regularly interspaced short palindromic repeats (CRISPR) studies did not reveal any novel associations.

Conclusions: These results suggest that exonic variants with large effect sizes are unlikely to have a major contribution to host control of HIV infection.
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http://dx.doi.org/10.1093/infdis/jix470DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5853944PMC
November 2017

A replication study of genetic risk loci for ischemic stroke in a Dutch population: a case-control study.

Sci Rep 2017 09 22;7(1):12175. Epub 2017 Sep 22.

Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands.

We aimed to replicate reported associations of 10 SNPs at eight distinct loci with overall ischemic stroke (IS) and its subtypes in an independent cohort of Dutch IS patients. We included 1,375 IS patients enrolled in a prospective multicenter hospital-based cohort in the Netherlands, and 1,533 population-level controls of Dutch descent. We tested these SNPs for association with overall IS and its subtypes (large artery atherosclerosis, small vessel disease and cardioembolic stroke (CE), as classified by TOAST) using an additive multivariable logistic regression model, adjusting for age and sex. We obtained odds ratios (OR) with 95% confidence intervals (95% CI) for the risk allele of each SNP analyzed and exact p-values by permutation. We confirmed the association at 4q25 (PITX2) (OR 1.43; 95% CI, 1.13-1.81, p = 0.029) and 16q22 (ZFHX3) (OR 1.62; 95% CI, 1.26-2.07, p = 0.001) as risk loci for CE. Locus 16q22 was also associated with overall IS (OR 1.24; 95% CI, 1.08-1.42, p = 0.016). Other loci previously associated with IS and/or its subtypes were not confirmed. In conclusion, we validated two loci (4q25, 16q22) associated with CE. In addition, our study may suggest that the association of locus 16q22 may not be limited to CE, but also includes overall IS.
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http://dx.doi.org/10.1038/s41598-017-07404-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5610184PMC
September 2017

Genetic loci associated with heart rate variability and their effects on cardiac disease risk.

Nat Commun 2017 06 14;8:15805. Epub 2017 Jun 14.

Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina 27599, USA.

Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74
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http://dx.doi.org/10.1038/ncomms15805DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5474732PMC
June 2017

Negative selection in humans and fruit flies involves synergistic epistasis.

Science 2017 05;356(6337):539-542

Negative selection against deleterious alleles produced by mutation influences within-population variation as the most pervasive form of natural selection. However, it is not known whether deleterious alleles affect fitness independently, so that cumulative fitness loss depends exponentially on the number of deleterious alleles, or synergistically, so that each additional deleterious allele results in a larger decrease in relative fitness. Negative selection with synergistic epistasis should produce negative linkage disequilibrium between deleterious alleles and, therefore, an underdispersed distribution of the number of deleterious alleles in the genome. Indeed, we detected underdispersion of the number of rare loss-of-function alleles in eight independent data sets from human and fly populations. Thus, selection against rare protein-disrupting alleles is characterized by synergistic epistasis, which may explain how human and fly populations persist despite high genomic mutation rates.
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http://dx.doi.org/10.1126/science.aah5238DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6200135PMC
May 2017

Rare and low-frequency coding variants alter human adult height.

Nature 2017 02 1;542(7640):186-190. Epub 2017 Feb 1.

Netherlands Comprehensive Cancer Organisation, Utrecht, 3501 DB, The Netherlands.

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.
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http://dx.doi.org/10.1038/nature21039DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5302847PMC
February 2017

Genetic variation at 16q24.2 is associated with small vessel stroke.

Ann Neurol 2017 Mar;81(3):383-394

Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden.

Objective: Genome-wide association studies (GWAS) have been successful at identifying associations with stroke and stroke subtypes, but have not yet identified any associations solely with small vessel stroke (SVS). SVS comprises one quarter of all ischemic stroke and is a major manifestation of cerebral small vessel disease, the primary cause of vascular cognitive impairment. Studies across neurological traits have shown that younger-onset cases have an increased genetic burden. We leveraged this increased genetic burden by performing an age-at-onset informed GWAS meta-analysis, including a large younger-onset SVS population, to identify novel associations with stroke.

Methods: We used a three-stage age-at-onset informed GWAS to identify novel genetic variants associated with stroke. On identifying a novel locus associated with SVS, we assessed its influence on other small vessel disease phenotypes, as well as on messenger RNA (mRNA) expression of nearby genes, and on DNA methylation of nearby CpG sites in whole blood and in the fetal brain.

Results: We identified an association with SVS in 4,203 cases and 50,728 controls on chromosome 16q24.2 (odds ratio [OR; 95% confidence interval {CI}] = 1.16 [1.10-1.22]; p = 3.2 × 10 ). The lead single-nucleotide polymorphism (rs12445022) was also associated with cerebral white matter hyperintensities (OR [95% CI] = 1.10 [1.05-1.16]; p = 5.3 × 10 ; N = 3,670), but not intracerebral hemorrhage (OR [95% CI] = 0.97 [0.84-1.12]; p = 0.71; 1,545 cases, 1,481 controls). rs12445022 is associated with mRNA expression of ZCCHC14 in arterial tissues (p = 9.4 × 10 ) and DNA methylation at probe cg16596957 in whole blood (p = 5.3 × 10 ).

Interpretation: 16q24.2 is associated with SVS. Associations of the locus with expression of ZCCHC14 and DNA methylation suggest the locus acts through changes to regulatory elements. Ann Neurol 2017;81:383-394.
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http://dx.doi.org/10.1002/ana.24840DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5366092PMC
March 2017

Resetting the bar: Statistical significance in whole-genome sequencing-based association studies of global populations.

Genet Epidemiol 2017 Feb 18;41(2):145-151. Epub 2016 Dec 18.

Department of Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands.

Genome-wide association studies (GWAS) of common disease have been hugely successful in implicating loci that modify disease risk. The bulk of these associations have proven robust and reproducible, in part due to community adoption of statistical criteria for claiming significant genotype-phenotype associations. As the cost of sequencing continues to drop, assembling large samples in global populations is becoming increasingly feasible. Sequencing studies interrogate not only common variants, as was true for genotyping-based GWAS, but variation across the full allele frequency spectrum, yielding many more (independent) statistical tests. We sought to empirically determine genome-wide significance thresholds for various analysis scenarios. Using whole-genome sequence data, we simulated sequencing-based disease studies of varying sample size and ancestry. We determined that future sequencing efforts in >2,000 samples of European, Asian, or admixed ancestry should set genome-wide significance at approximately P = 5 × 10 , and studies of African samples should apply a more stringent genome-wide significance threshold of P = 1 × 10 . Adoption of a revised multiple test correction will be crucial in avoiding irreproducible claims of association.
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http://dx.doi.org/10.1002/gepi.22032DOI Listing
February 2017

Meta-Analysis of Genome-Wide Association Studies for Abdominal Aortic Aneurysm Identifies Four New Disease-Specific Risk Loci.

Circ Res 2017 Jan 29;120(2):341-353. Epub 2016 Nov 29.

For the author affiliations, please see the Appendix.

Rationale: Abdominal aortic aneurysm (AAA) is a complex disease with both genetic and environmental risk factors. Together, 6 previously identified risk loci only explain a small proportion of the heritability of AAA.

Objective: To identify additional AAA risk loci using data from all available genome-wide association studies.

Methods And Results: Through a meta-analysis of 6 genome-wide association study data sets and a validation study totaling 10 204 cases and 107 766 controls, we identified 4 new AAA risk loci: 1q32.3 (SMYD2), 13q12.11 (LINC00540), 20q13.12 (near PCIF1/MMP9/ZNF335), and 21q22.2 (ERG). In various database searches, we observed no new associations between the lead AAA single nucleotide polymorphisms and coronary artery disease, blood pressure, lipids, or diabetes mellitus. Network analyses identified ERG, IL6R, and LDLR as modifiers of MMP9, with a direct interaction between ERG and MMP9.

Conclusions: The 4 new risk loci for AAA seem to be specific for AAA compared with other cardiovascular diseases and related traits suggesting that traditional cardiovascular risk factor management may only have limited value in preventing the progression of aneurysmal disease.
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http://dx.doi.org/10.1161/CIRCRESAHA.116.308765DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5253231PMC
January 2017

Extensive Association of Common Disease Variants with Regulatory Sequence.

PLoS One 2016 22;11(11):e0165893. Epub 2016 Nov 22.

Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, 3584 EA, The Netherlands.

Overlap between non-coding DNA regulatory sequences and common variant associations can help to identify specific cell and tissue types that are relevant for particular diseases. In a systematic manner, we analyzed variants from 94 genome-wide association studies (reporting at least 12 loci at p<5x10-8) by projecting them onto 466 epigenetic datasets (characterizing DNase I hypersensitive sites; DHSs) derived from various adult and fetal tissue samples and cell lines including many biological replicates. We were able to confirm many expected associations, such as the involvement of specific immune cell types in immune-related diseases and tissue types in diseases that affect specific organs, for example, inflammatory bowel disease and coronary artery disease. Other notable associations include adrenal glands in coronary artery disease, the immune system in Alzheimer's disease, and the kidney for bone marrow density. The association signals for some GWAS (for example, myopia or age at menarche) did not show a clear pattern with any of the cell or tissue types studied. In general, the identified variants from GWAS tend to be located outside coding regions. Altogether, we have performed an extensive characterization of GWAS signals in relation to cell and tissue-specific DHSs, demonstrating a key role for regulatory mechanisms in common diseases and complex traits.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0165893PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5119736PMC
June 2017

A high-quality human reference panel reveals the complexity and distribution of genomic structural variants.

Nat Commun 2016 10 6;7:12989. Epub 2016 Oct 6.

European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, Groningen 9713AD, The Netherlands.

Structural variation (SV) represents a major source of differences between individual human genomes and has been linked to disease phenotypes. However, the majority of studies provide neither a global view of the full spectrum of these variants nor integrate them into reference panels of genetic variation. Here, we analyse whole genome sequencing data of 769 individuals from 250 Dutch families, and provide a haplotype-resolved map of 1.9 million genome variants across 9 different variant classes, including novel forms of complex indels, and retrotransposition-mediated insertions of mobile elements and processed RNAs. A large proportion are previously under reported variants sized between 21 and 100 bp. We detect 4 megabases of novel sequence, encoding 11 new transcripts. Finally, we show 191 known, trait-associated SNPs to be in strong linkage disequilibrium with SVs and demonstrate that our panel facilitates accurate imputation of SVs in unrelated individuals.
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http://dx.doi.org/10.1038/ncomms12989DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5059695PMC
October 2016

52 Genetic Loci Influencing Myocardial Mass.

J Am Coll Cardiol 2016 09;68(13):1435-1448

Department of Medical Genetics, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands.

Background: Myocardial mass is a key determinant of cardiac muscle function and hypertrophy. Myocardial depolarization leading to cardiac muscle contraction is reflected by the amplitude and duration of the QRS complex on the electrocardiogram (ECG). Abnormal QRS amplitude or duration reflect changes in myocardial mass and conduction, and are associated with increased risk of heart failure and death.

Objectives: This meta-analysis sought to gain insights into the genetic determinants of myocardial mass.

Methods: We carried out a genome-wide association meta-analysis of 4 QRS traits in up to 73,518 individuals of European ancestry, followed by extensive biological and functional assessment.

Results: We identified 52 genomic loci, of which 32 are novel, that are reliably associated with 1 or more QRS phenotypes at p < 1 × 10(-8). These loci are enriched in regions of open chromatin, histone modifications, and transcription factor binding, suggesting that they represent regions of the genome that are actively transcribed in the human heart. Pathway analyses provided evidence that these loci play a role in cardiac hypertrophy. We further highlighted 67 candidate genes at the identified loci that are preferentially expressed in cardiac tissue and associated with cardiac abnormalities in Drosophila melanogaster and Mus musculus. We validated the regulatory function of a novel variant in the SCN5A/SCN10A locus in vitro and in vivo.

Conclusions: Taken together, our findings provide new insights into genes and biological pathways controlling myocardial mass and may help identify novel therapeutic targets.
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http://dx.doi.org/10.1016/j.jacc.2016.07.729DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5478167PMC
September 2016

Cystatin C and Cardiovascular Disease: A Mendelian Randomization Study.

J Am Coll Cardiol 2016 08;68(9):934-45

Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-University Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.

Background: Epidemiological studies show that high circulating cystatin C is associated with risk of cardiovascular disease (CVD), independent of creatinine-based renal function measurements. It is unclear whether this relationship is causal, arises from residual confounding, and/or is a consequence of reverse causation.

Objectives: The aim of this study was to use Mendelian randomization to investigate whether cystatin C is causally related to CVD in the general population.

Methods: We incorporated participant data from 16 prospective cohorts (n = 76,481) with 37,126 measures of cystatin C and added genetic data from 43 studies (n = 252,216) with 63,292 CVD events. We used the common variant rs911119 in CST3 as an instrumental variable to investigate the causal role of cystatin C in CVD, including coronary heart disease, ischemic stroke, and heart failure.

Results: Cystatin C concentrations were associated with CVD risk after adjusting for age, sex, and traditional risk factors (relative risk: 1.82 per doubling of cystatin C; 95% confidence interval [CI]: 1.56 to 2.13; p = 2.12 × 10(-14)). The minor allele of rs911119 was associated with decreased serum cystatin C (6.13% per allele; 95% CI: 5.75 to 6.50; p = 5.95 × 10(-211)), explaining 2.8% of the observed variation in cystatin C. Mendelian randomization analysis did not provide evidence for a causal role of cystatin C, with a causal relative risk for CVD of 1.00 per doubling cystatin C (95% CI: 0.82 to 1.22; p = 0.994), which was statistically different from the observational estimate (p = 1.6 × 10(-5)). A causal effect of cystatin C was not detected for any individual component of CVD.

Conclusions: Mendelian randomization analyses did not support a causal role of cystatin C in the etiology of CVD. As such, therapeutics targeted at lowering circulating cystatin C are unlikely to be effective in preventing CVD.
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http://dx.doi.org/10.1016/j.jacc.2016.05.092DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451109PMC
August 2016

A reference panel of 64,976 haplotypes for genotype imputation.

Nat Genet 2016 10 22;48(10):1279-83. Epub 2016 Aug 22.

IRGB, CNR, Sardinia, Italy.

We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.
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http://dx.doi.org/10.1038/ng.3643DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5388176PMC
October 2016

Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis.

Nat Genet 2016 09 25;48(9):1043-8. Epub 2016 Jul 25.

Department of Molecular Genetics, Institute of Pathology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.

To elucidate the genetic architecture of amyotrophic lateral sclerosis (ALS) and find associated loci, we assembled a custom imputation reference panel from whole-genome-sequenced patients with ALS and matched controls (n = 1,861). Through imputation and mixed-model association analysis in 12,577 cases and 23,475 controls, combined with 2,579 cases and 2,767 controls in an independent replication cohort, we fine-mapped a new risk locus on chromosome 21 and identified C21orf2 as a gene associated with ALS risk. In addition, we identified MOBP and SCFD1 as new associated risk loci. We established evidence of ALS being a complex genetic trait with a polygenic architecture. Furthermore, we estimated the SNP-based heritability at 8.5%, with a distinct and important role for low-frequency variants (frequency 1-10%). This study motivates the interrogation of larger samples with full genome coverage to identify rare causal variants that underpin ALS risk.
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http://dx.doi.org/10.1038/ng.3622DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5556360PMC
September 2016

Shared Genetic Risk Factors of Intracranial, Abdominal, and Thoracic Aneurysms.

J Am Heart Assoc 2016 07 14;5(7). Epub 2016 Jul 14.

Surgery Department, University of Otago, Dunedin, New Zealand.

Background: Intracranial aneurysms (IAs), abdominal aortic aneurysms (AAAs), and thoracic aortic aneurysms (TAAs) all have a familial predisposition. Given that aneurysm types are known to co-occur, we hypothesized that there may be shared genetic risk factors for IAs, AAAs, and TAAs.

Methods And Results: We performed a mega-analysis of 1000 Genomes Project-imputed genome-wide association study (GWAS) data of 4 previously published aneurysm cohorts: 2 IA cohorts (in total 1516 cases, 4305 controls), 1 AAA cohort (818 cases, 3004 controls), and 1 TAA cohort (760 cases, 2212 controls), and observed associations of 4 known IA, AAA, and/or TAA risk loci (9p21, 18q11, 15q21, and 2q33) with consistent effect directions in all 4 cohorts. We calculated polygenic scores based on IA-, AAA-, and TAA-associated SNPs and tested these scores for association to case-control status in the other aneurysm cohorts; this revealed no shared polygenic effects. Similarly, linkage disequilibrium-score regression analyses did not show significant correlations between any pair of aneurysm subtypes. Last, we evaluated the evidence for 14 previously published aneurysm risk single-nucleotide polymorphisms through collaboration in extended aneurysm cohorts, with a total of 6548 cases and 16 843 controls (IA) and 4391 cases and 37 904 controls (AAA), and found nominally significant associations for IA risk locus 18q11 near RBBP8 to AAA (odds ratio [OR]=1.11; P=4.1×10(-5)) and for TAA risk locus 15q21 near FBN1 to AAA (OR=1.07; P=1.1×10(-3)).

Conclusions: Although there was no evidence for polygenic overlap between IAs, AAAs, and TAAs, we found nominally significant effects of two established risk loci for IAs and TAAs in AAAs. These two loci will require further replication.
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http://dx.doi.org/10.1161/JAHA.115.002603DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5015357PMC
July 2016
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