Gonçalo R Abecasis

Norwegian University of Science and Technology, Nidaros, Sør-Trøndelag, Norway

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Publications (307)4791.12 Total impact

  • Journal of Investigative Dermatology 12/2014; · 6.19 Impact Factor
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    ABSTRACT: Myocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance. When MI occurs early in life, genetic inheritance is a major component to risk. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families, whereas common variants at more than 45 loci have been associated with MI risk in the population. Here we evaluate how rare mutations contribute to early-onset MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (≤50 years in males and ≤60 years in females) along with MI-free controls. We identified two genes in which rare coding-sequence mutations were more frequent in MI cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare non-synonymous mutations were at 4.2-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). Approximately 2% of early MI cases harbour a rare, damaging mutation in LDLR; this estimate is similar to one made more than 40 years ago using an analysis of total cholesterol16. Among controls, about 1 in 217 carried an LDLR coding-sequence mutation and had plasma LDL cholesterol > 190 mg dl−1. At apolipoprotein A-V (APOA5), carriers of rare non-synonymous mutations were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol, whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding-sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase15, 17 and apolipoprotein C-III. Combined, these observations suggest that, as well as LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.
    Nature 12/2014; advance online publication. · 38.60 Impact Factor
  • Lam C Tsoi, James T Elder, Goncalo R Abecasis
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    ABSTRACT: Pathway analysis to reveal biological mechanisms for results from genetic association studies have great potential to better understand complex traits with major human disease impact. However, current approaches have not been optimized to maximize statistical power to identify enriched functions/pathways, especially when the genetic data derives from studies using platforms (e.g. Immunochip and Metabochip) customized to have pre-selected markers from previously identified top-rank loci. We present here a novel approach, called MEAGA (Minimum distance-based Enrichment Analysis for Genetic Association), with the potential to address both of these important concerns. MEAGA performs enrichment analysis using graphical algorithms to identify subgraphs among genes and measure their closeness in interaction database. It also incorporates a statistic summarizing the numbers and total distances of the subgraphs, depicting the overlap between observed genetic signals and defined function/pathway gene-sets. MEAGA uses sampling technique to approximate empirical and multiple testing-corrected p-values. We show in simulation studies that MEAGA is more powerful compared to count-based strategies in identifying disease-associated functions/pathways, and the increase in power is influenced by the shortest distances among associated genes in the interactome. We applied MEAGA to the results of a meta-analysis of psoriasis using Immunochip datasets, and showed that associated genes are significantly enriched in immune-related functions and closer with each other in the protein-protein interaction network. Availability and implementation: http://genome.sph.umich.edu/wiki/MEAGA. © The Author (2014). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
    Bioinformatics (Oxford, England). 12/2014;
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    ABSTRACT: The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD.
    Nature Genetics 12/2014; · 35.21 Impact Factor
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    ABSTRACT: Whole genome sequencing was completed on 1,325 individuals from 602 families, identifying 27 million autosomal variants. Genetic association tests were conducted for those individuals who had been assessed for one or more of 17 endophenotypes (N range = 802-1,185). No significant associations were found. These 27 million variants were then imputed into the full sample of individuals with psychophysiological data (N range = 3,088-4,469) and again tested for associations with the 17 endophenotypes. No association was significant. Using a gene-based variable threshold burden test of nonsynonymous variants, we obtained five significant associations. These findings are preliminary and call for additional analysis of this rich sample. We argue that larger samples, alternative study designs, and additional bioinformatics approaches will be necessary to discover associations between these endophenotypes and genomic variation.
    Psychophysiology 12/2014; 51(12):1309-20. · 3.29 Impact Factor
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    ABSTRACT: We mapped ∼85,000 rare nonsynonymous exonic single nucleotide polymorphisms (SNPs) to 17 psychophysiological endophenotypes in 4,905 individuals, including antisaccade eye movements, resting EEG, P300 amplitude, electrodermal activity, affect-modulated startle eye blink. Nonsynonymous SNPs are predicted to directly change or disrupt proteins encoded by genes and are expected to have significant biological consequences. Most such variants are rare, and new technologies can efficiently assay them on a large scale. We assayed 247,870 mostly rare SNPs on an Illumina exome array. Approximately 85,000 of the SNPs were polymorphic, rare (MAF < .05), and nonsynonymous. Single variant association tests identified a SNP in the PARD3 gene associated with theta resting EEG power. The sequence kernel association test, a gene-based test, identified a gene PNPLA7 associated with pleasant difference startle, the difference in startle magnitude between pleasant and neutral images. No other single nonsynonymous variant, or gene-based group of variants, was strongly associated with any endophenotype.
    Psychophysiology 12/2014; 51(12):1300-1308. · 3.29 Impact Factor
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    ABSTRACT: BACKGROUND: Ezetimibe lowers plasma levels of low-density lipoprotein (LDL) cholesterol by inhibiting the activity of the Niemann-Pick C1-like 1 (NPC1L1) protein. However, whether such inhibition reduces the risk of coronary heart disease is not known. Human mutations that inactivate a gene encoding a drug target can mimic the action of an inhibitory drug and thus can be used to infer potential effects of that drug. METHODS: We sequenced the exons of NPC1L1 in 7364 patients with coronary heart disease and in 14,728 controls without such disease who were of European, African, or South Asian ancestry. We identified carriers of inactivating mutations (nonsense, splice-site, or frameshift mutations). In addition, we genotyped a specific inactivating mutation (p.Arg406X) in 22,590 patients with coronary heart disease and in 68,412 controls. We tested the association between the presence of an inactivating mutation and both plasma lipid levels and the risk of coronary heart disease. RESULTS: With sequencing, we identified 15 distinct NPC1L1 inactivating mutations; approximately 1 in every 650 persons was a heterozygous carrier for 1 of these mutations. Heterozygous carriers of NPC1L1 inactivating mutations had a mean LDL cholesterol level that was 12 mg per deciliter (0.31 mmol per liter) lower than that in noncarriers (P=0.04). Carrier status was associated with a relative reduction of 53% in the risk of coronary heart disease (odds ratio for carriers, 0.47; 95% confidence interval, 0.25 to 0.87; P=0.008). In total, only 11 of 29,954 patients with coronary heart disease had an inactivating mutation (carrier frequency, 0.04%) in contrast to 71 of 83,140 controls (carrier frequency, 0.09%). CONCLUSIONS: Naturally occurring mutations that disrupt NPC1L1 function were found to be associated with reduced plasma LDL cholesterol levels and a reduced risk of coronary heart disease. (Funded by the National Institutes of Health and others.).
    New England Journal of Medicine 11/2014; 371(22):2072-82. · 54.42 Impact Factor
  • Ophthalmology 11/2014; · 5.56 Impact Factor
  • Christian Fuchsberger, Gonçalo R Abecasis, David A Hinds
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    ABSTRACT: Genotype imputation is a key step in the analysis of genome-wide association studies (GWAS). Upcoming very large reference panels, such as those from The 1000 Genomes Project and the Haplotype Consortium, will improve imputation quality of rare and less common variants, but will also increase the computational burden. Here, we demonstrate how the application of software engineering techniques can help to keep imputation broadly accessible. Overall, these improvements speed up imputation by an order of magnitude compared to our previous implementation. Availability: minimac2, including source code, documentation, and examples is available at http://genome.sph.umich.edu/wiki/Minimac2.
    Bioinformatics (Oxford, England). 10/2014;
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    ABSTRACT: The utility of genotype imputation in genome-wide association studies is increasing as progressively larger reference panels are improved and expanded through whole-genome sequencing. Developing general guidelines for optimally cost-effective imputation, however, requires evaluation of performance issues that include the relative utility of study-specific compared with general/multipopulation reference panels; genotyping with various array scaffolds; effects of different ethnic backgrounds; and assessment of ranges of allele frequencies. Here we compared the effectiveness of study-specific reference panels to the commonly used 1000 Genomes Project (1000G) reference panels in the isolated Sardinian population and in cohorts of European ancestry including samples from Minnesota (USA). We also examined different combinations of genome-wide and custom arrays for baseline genotypes. In Sardinians, the study-specific reference panel provided better coverage and genotype imputation accuracy than the 1000G panels and other large European panels. In fact, even gene-centered custom arrays (interrogating ~200 000 variants) provided highly informative content across the entire genome. Gain in accuracy was also observed for Minnesotans using the study-specific reference panel, although the increase was smaller than in Sardinians, especially for rare variants. Notably, a combined panel including both study-specific and 1000G reference panels improved imputation accuracy only in the Minnesota sample, and only at rare sites. Finally, we found that when imputation is performed with a study-specific reference panel, cutoffs different from the standard thresholds of MACH-Rsq and IMPUTE-INFO metrics should be used to efficiently filter badly imputed rare variants. This study thus provides general guidelines for researchers planning large-scale genetic studies.European Journal of Human Genetics advance online publication, 8 October 2014; doi:10.1038/ejhg.2014.216.
    European journal of human genetics: EJHG 10/2014; · 3.56 Impact Factor
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    ABSTRACT: Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated approximately 2,000, approximately 3,700 and approximately 9,500 SNPs explained approximately 21%, approximately 24% and approximately 29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
    Nature Genetics 10/2014; · 35.21 Impact Factor
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    ABSTRACT: Previous studies have identified 41 independent genome-wide significant psoriasis susceptibility loci. After our first psoriasis genome-wide association study, we designed a custom genotyping array to fine-map eight genome-wide significant susceptibility loci known at that time (IL23R, IL13, IL12B, TNIP1, MHC, TNFAIP3, IL23A and RNF114) enabling genotyping of 2269 single-nucleotide polymorphisms (SNPs) in the eight loci for 2699 psoriasis cases and 2107 unaffected controls of European ancestry. We imputed these data using the latest 1000 Genome reference haplotypes, which included both indels and SNPs, to increase the marker density of the eight loci to 49 239 genetic variants. Using stepwise conditional association analysis, we identified nine independent signals distributed across six of the eight loci. In the major histocompatibility complex (MHC) region, we detected three independent signals at rs114255771 (P=2.94 × 10(-74)), rs6924962 (P=3.21 × 10(-19)) and rs892666 (P=1.11 × 10(-10)). Near IL12B we detected two independent signals at rs62377586 (P=7.42 × 10(-16)) and rs918518 (P=3.22 × 10(-11)). Only one signal was observed in each of the TNIP1 (rs17728338; P=4.15 × 10(-13)), IL13 (rs1295685; P=1.65 × 10(-7)), IL23A (rs61937678; P=1.82 × 10(-7)) and TNFAIP3 (rs642627; P=5.90 × 10(-7)) regions. We also imputed variants for eight HLA genes and found that SNP rs114255771 yielded a more significant association than any HLA allele or amino-acid residue. Further analysis revealed that the HLA-C*06-B*57 haplotype tagged by this SNP had a significantly higher odds ratio than other HLA-C*06-bearing haplotypes. The results demonstrate allelic heterogeneity at IL12B and identify a high-risk MHC class I haplotype, consistent with the existence of multiple psoriasis effectors in the MHC.European Journal of Human Genetics advance online publication, 3 September 2014; doi:10.1038/ejhg.2014.172.
    European journal of human genetics: EJHG 09/2014; · 3.56 Impact Factor
  • Seunggeung Lee, Gonçalo R Abecasis, Michael Boehnke, Xihong Lin
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    ABSTRACT: Despite the extensive discovery of trait- and disease-associated common variants, much of the genetic contribution to complex traits remains unexplained. Rare variants can explain additional disease risk or trait variability. An increasing number of studies are underway to identify trait- and disease-associated rare variants. In this review, we provide an overview of statistical issues in rare-variant association studies with a focus on study designs and statistical tests. We present the design and analysis pipeline of rare-variant studies and review cost-effective sequencing designs and genotyping platforms. We compare various gene- or region-based association tests, including burden tests, variance-component tests, and combined omnibus tests, in terms of their assumptions and performance. Also discussed are the related topics of meta-analysis, population-stratification adjustment, genotype imputation, follow-up studies, and heritability due to rare variants. We provide guidelines for analysis and discuss some of the challenges inherent in these studies and future research directions.
    The American Journal of Human Genetics 07/2014; 95(1):5-23. · 11.20 Impact Factor
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    ABSTRACT: Neurodegenerative diseases affecting the macula constitute a major cause of incurable vision loss and exhibit considerable clinical and genetic heterogeneity, from early-onset monogenic disease to multifactorial late-onset age-related macular degeneration (AMD). As part of our continued efforts to define genetic causes of macular degeneration, we performed whole exome sequencing in four individuals of a two-generation family with autosomal dominant maculopathy and identified a rare variant p.Glu1144Lys in Fibrillin 2 (FBN2), a glycoprotein of the elastin-rich extracellular matrix (ECM). Sanger sequencing validated the segregation of this variant in the complete pedigree, including two additional affected and one unaffected individual. Sequencing of 192 maculopathy patients revealed additional rare variants, predicted to disrupt FBN2 function. We then undertook additional studies to explore the relationship of FBN2 to macular disease. We show that FBN2 localizes to Bruch's membrane and its expression appears to be reduced in aging and AMD eyes, prompting us to examine its relationship with AMD. We detect suggestive association of a common FBN2 non-synonymous variant, rs154001 (p.Val965Ile) with AMD in 10,337 cases and 11,174 controls (OR=1.10; p-value=3.79×10(-5)). Thus, it appears that rare and common variants in a single gene - FBN2 - can contribute to Mendelian and complex forms of macular degeneration. Our studies provide genetic evidence for a key role of elastin microfibers and Bruch's membrane in maintaining blood-retina homeostasis and establish the importance of studying orphan diseases for understanding more common clinical phenotypes.
    Human Molecular Genetics 06/2014; · 7.69 Impact Factor
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    ABSTRACT: RAREMETAL is a computationally efficient tool for meta-analysis of rare variants genotyped using sequencing or arrays. RAREMETAL facilitates analyses of individual studies, accommodates a variety of input file formats, handles related and unrelated individuals, executes both single variant and burden tests, and performs conditional association analyses. Availability: http://genome.sph.umich.edu/wiki/RAREMETAL for executables, source code, documentation and tutorial.
    Bioinformatics (Oxford, England). 06/2014;
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    ABSTRACT: Genome sequencing of the 5,300-year-old mummy of the Tyrolean Iceman, found in 1991 on a glacier near the border of Italy and Austria, has yielded new insights into his origin and relationship to modern European populations. A key finding of that study was an apparent recent common ancestry with individuals from Sardinia, based largely on the Y chromosome haplogroup and common autosomal SNP variation. Here, we compiled and analyzed genomic datasets from both modern and ancient Europeans, including genome sequence data from over 400 Sardinians and two ancient Thracians from Bulgaria, to investigate this result in greater detail and determine its implications for the genetic structure of Neolithic Europe. Using whole-genome sequencing data, we confirm that the Iceman is, indeed, most closely related to Sardinians. Furthermore, we show that this relationship extends to other individuals from cultural contexts associated with the spread of agriculture during the Neolithic transition, in contrast to individuals from a hunter-gatherer context. We hypothesize that this genetic affinity of ancient samples from different parts of Europe with Sardinians represents a common genetic component that was geographically widespread across Europe during the Neolithic, likely related to migrations and population expansions associated with the spread of agriculture.
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    ABSTRACT: Genome sequencing of the 5,300-year-old mummy of the Tyrolean Iceman, found in 1991 on a glacier near the border of Italy and Austria, has yielded new insights into his origin and relationship to modern European populations. A key finding of that study was an apparent recent common ancestry with individuals from Sardinia, based largely on the Y chromosome haplogroup and common autosomal SNP variation. Here, we compiled and analyzed genomic datasets from both modern and ancient Europeans, including genome sequence data from over 400 Sardinians and two ancient Thracians from Bulgaria, to investigate this result in greater detail and determine its implications for the genetic structure of Neolithic Europe. Using whole-genome sequencing data, we confirm that the Iceman is, indeed, most closely related to Sardinians. Furthermore, we show that this relationship extends to other individuals from cultural contexts associated with the spread of agriculture during the Neolithic transition, in contrast to individuals from a hunter-gatherer context. We hypothesize that this genetic affinity of ancient samples from different parts of Europe with Sardinians represents a common genetic component that was geographically widespread across Europe during the Neolithic, likely related to migrations and population expansions associated with the spread of agriculture.
    PLoS Genetics 05/2014; 10(5):e1004353. · 8.52 Impact Factor
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    ABSTRACT: The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development.
    Nature 04/2014; 508(7497):469-76. · 38.60 Impact Factor
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    ABSTRACT: Genetic and genomic studies have enhanced our understanding of complex neurodegenerative diseases that exert a devastating impact on individuals and society. One such disease, age-related macular degeneration (AMD), is a major cause of progressive and debilitating visual impairment. Since the pioneering discovery in 2005 of complement factor H (CFH) as a major AMD susceptibility gene, extensive investigations have confirmed 19 additional genetic risk loci, and more are anticipated. In addition to common variants identified by now-conventional genome-wide association studies, targeted genomic sequencing and exome-chip analyses are uncovering rare variant alleles of high impact. Here, we provide a critical review of the ongoing genetic studies and of common and rare risk variants at a total of 20 susceptibility loci, which together explain 40-60% of the disease heritability but provide limited power for diagnostic testing of disease risk. Identification of these susceptibility loci has begun to untangle the complex biological pathways underlying AMD pathophysiology, pointing to new testable paradigms for treatment. Expected final online publication date for the Annual Review of Genomics and Human Genetics Volume 15 is September 01, 2014. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.
    Annual review of genomics and human genetics 04/2014; · 11.57 Impact Factor
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    ABSTRACT: Genome-wide association studies have identified variants, primarily common, that are associated with coronary artery disease or myocardial infarction (MI), but have not tested the majority of the low frequency and rare variation in the genome. We explored the hypothesis that previously untested low frequency (1-5% minor allele frequency) and rare (<1% minor allele frequency) coding variants are associated with MI. We genotyped 2,906 MI cases and 6,738 non-MI controls from Norway using the Illumina HumanExome Beadchip, allowing for direct genotyping of 85,972 polymorphic coding variants as well as 48 known GWAS SNPs. We followed-up 37 coding variants in an additional 2,350 MI cases and 2,318 controls from Norway. We evaluated exome array coverage in a subset of these samples using whole exome sequencing (N=151). The exome array provided successful genotyping for an estimated 72.5% of Norwegian loss-of-function or missense variants with frequency >1% and 66.2% of variants <1% frequency observed more than once. Despite 80% power in the two-stage study (N=14,312) to detect association with low frequency variants with high effect sizes (odds ratio [OR] >1.86 and >1.36 for 1% and 5% frequency, respectively), we did not identify any novel genes or single variants that reached significance. This suggests that low frequency coding variants with large effect sizes (OR >2) may not exist for MI. Larger sample sizes may identify coding variants with more moderate effects.
    Human Molecular Genetics 04/2014; · 7.69 Impact Factor

Publication Stats

47k Citations
4,791.12 Total Impact Points


  • 2014
    • Norwegian University of Science and Technology
      • Department of Public Health and General Practice
      Nidaros, Sør-Trøndelag, Norway
  • 2002–2014
    • University of Michigan
      • • Department of Biostatistics
      • • Department of Dermatology
      • • School of Public Health
      • • Department of Ophthalmology and Visual Sciences
      • • Center for Statistical Genetics
      Ann Arbor, Michigan, United States
    • King's College London
      • Institute of Psychiatry
      London, ENG, United Kingdom
  • 2013
    • Columbia University
      • Department of Psychiatry
      New York City, New York, United States
    • University of California, Berkeley
      Berkeley, California, United States
    • Universität Regensburg
      Ratisbon, Bavaria, Germany
    • Harvard Medical School
      Boston, Massachusetts, United States
    • Università degli Studi di Sassari
      • Dipartimento di Scienze della Natura e del Territorio
      Sassari, Sardinia, Italy
  • 2012–2013
    • Vanderbilt University
      • Center for Human Genetics Research (CHGR)
      Nashville, Michigan, United States
    • University of Pennsylvania
      • Department of Pharmacology
      Philadelphia, PA, United States
    • University of Chicago
      • Department of Human Genetics
      Chicago, IL, United States
    • McGill University
      • Department of Epidemiology, Biostatistics and Occupational Health
      Montréal, Quebec, Canada
    • Massachusetts General Hospital
      • Cardiovascular Research Center
      Boston, MA, United States
    • Childrens Hospital of Pittsburgh
      Pittsburgh, Pennsylvania, United States
  • 2005–2013
    • Concordia University–Ann Arbor
      Ann Arbor, Michigan, United States
    • Cold Spring Harbor Laboratory
      Cold Spring Harbor, New York, United States
  • 2010–2012
    • Christian-Albrechts-Universität zu Kiel
      • Institute of Clinical Molecular Biology
      Kiel, Schleswig-Holstein, Germany
    • University of Exeter
      • Peninsula College of Medicine and Dentistry
      Exeter, ENG, United Kingdom
    • Calvin College
      • Department of Mathematics and Statistics
      Grand Rapids, MI, United States
    • University Hospital Regensburg
      Ratisbon, Bavaria, Germany
  • 2009–2012
    • National Institute on Aging
      • Laboratory of Genetics (LG)
      Baltimore, MD, United States
    • National Institutes of Health
      • Laboratory of Neurobiology-Neurodegeneration and Repair
      Bethesda, MD, United States
    • MedStar Health Research Institute
      Maryland, United States
    • National Eye Institute
      Maryland, United States
  • 2008–2012
    • Broad Institute of MIT and Harvard
      • Program in Medical and Population Genetics
      Cambridge, Massachusetts, United States
    • Boston Children's Hospital
      Boston, Massachusetts, United States
    • Lund University
      • Department of Clinical Sciences
      Lund, Skane, Sweden
  • 2006–2012
    • National Research Council
      • Institute of Neurogenetics and Neuropharmacology IRGB
      Roma, Latium, Italy
    • University of Colorado
      • Department of Medicine
      Denver, CO, United States
  • 2000–2012
    • University of Oxford
      • Wellcome Trust Centre for Human Genetics
      Oxford, ENG, United Kingdom
  • 2011
    • Wellcome Trust Sanger Institute
      Cambridge, England, United Kingdom
  • 2008–2011
    • University of North Carolina at Chapel Hill
      • • Department of Genetics
      • • Department of Biostatistics
      Chapel Hill, NC, United States
  • 2007–2010
    • Imperial College London
      • Department of Epidemiology and Biostatistics
      London, ENG, United Kingdom
  • 2003
    • The Rockefeller University
      New York City, New York, United States
  • 2001
    • The University of the West Indies at Mona
      Kingston, Kingston, Jamaica