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Moix S, Sadler MC, Kutalik Z, Auwerx C. Breaking down causes, consequences, and mediating effects of telomere length variation on human health. Genome Biol 2024; 25:125. [PMID: 38760657 DOI: 10.1186/s13059-024-03269-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 05/07/2024] [Indexed: 05/19/2024] Open
Abstract
BACKGROUND Telomeres form repeated DNA sequences at the ends of chromosomes, which shorten with each cell division. Yet, factors modulating telomere attrition and the health consequences thereof are not fully understood. To address this, we leveraged data from 326,363 unrelated UK Biobank participants of European ancestry. RESULTS Using linear regression and bidirectional univariable and multivariable Mendelian randomization (MR), we elucidate the relationships between leukocyte telomere length (LTL) and 142 complex traits, including diseases, biomarkers, and lifestyle factors. We confirm that telomeres shorten with age and show a stronger decline in males than in females, with these factors contributing to the majority of the 5.4% of LTL variance explained by the phenome. MR reveals 23 traits modulating LTL. Smoking cessation and high educational attainment associate with longer LTL, while weekly alcohol intake, body mass index, urate levels, and female reproductive events, such as childbirth, associate with shorter LTL. We also identify 24 traits affected by LTL, with risk for cardiovascular, pulmonary, and some autoimmune diseases being increased by short LTL, while longer LTL increased risk for other autoimmune conditions and cancers. Through multivariable MR, we show that LTL may partially mediate the impact of educational attainment, body mass index, and female age at childbirth on proxied lifespan. CONCLUSIONS Our study sheds light on the modulators, consequences, and the mediatory role of telomeres, portraying an intricate relationship between LTL, diseases, lifestyle, and socio-economic factors.
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Affiliation(s)
- Samuel Moix
- Department of Computational Biology, UNIL, Lausanne, 1015, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
| | - Marie C Sadler
- Department of Computational Biology, UNIL, Lausanne, 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
- University Center for Primary Care and Public Health, Lausanne, 1015, Switzerland
| | - Zoltán Kutalik
- Department of Computational Biology, UNIL, Lausanne, 1015, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
- University Center for Primary Care and Public Health, Lausanne, 1015, Switzerland.
| | - Chiara Auwerx
- Department of Computational Biology, UNIL, Lausanne, 1015, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
- University Center for Primary Care and Public Health, Lausanne, 1015, Switzerland.
- Center for Integrative Genetics, UNIL, Lausanne, 1015, Switzerland.
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Sadler MC, Apostolov A, Cevallos C, Ribeiro DM, Altman RB, Kutalik Z. Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications. medRxiv 2024:2024.04.06.24305415. [PMID: 38633781 PMCID: PMC11023668 DOI: 10.1101/2024.04.06.24305415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Electronic health records (EHRs) coupled with large-scale biobanks offer great promises to unravel the genetic underpinnings of treatment efficacy. However, medication-induced biomarker trajectories stemming from such records remain poorly studied. Here, we extract clinical and medication prescription data from EHRs and conduct GWAS and rare variant burden tests in the UK Biobank (discovery) and the All of Us program (replication) on ten cardiometabolic drug response outcomes including lipid response to statins, HbA1c response to metformin and blood pressure response to antihypertensives (N = 740-26,669). Our findings at genome-wide significance level recover previously reported pharmacogenetic signals and also include novel associations for lipid response to statins (N = 26,669) near LDLR and ZNF800. Importantly, these associations are treatment-specific and not associated with biomarker progression in medication-naive individuals. Furthermore, we demonstrate that individuals with higher genetically determined low-density and total cholesterol baseline levels experience increased absolute, albeit lower relative biomarker reduction following statin treatment. In summary, we systematically investigated the common and rare pharmacogenetic contribution to cardiometabolic drug response phenotypes in over 50,000 UK Biobank and All of Us participants with EHR and identified clinically relevant genetic predictors for improved personalized treatment strategies.
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Affiliation(s)
- Marie C. Sadler
- University Center for Primary Care and Public Health, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Alexander Apostolov
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Caterina Cevallos
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Diogo M. Ribeiro
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Russ B. Altman
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
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3
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Dubath C, Porcu E, Delacrétaz A, Grosu C, Laaboub N, Piras M, von Gunten A, Conus P, Plessen KJ, Kutalik Z, Eap CB. DNA methylation may partly explain psychotropic drug-induced metabolic side effects: results from a prospective 1-month observational study. Clin Epigenetics 2024; 16:36. [PMID: 38419113 PMCID: PMC10903022 DOI: 10.1186/s13148-024-01648-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 02/19/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND Metabolic side effects of psychotropic medications are a major drawback to patients' successful treatment. Using an epigenome-wide approach, we aimed to investigate DNA methylation changes occurring secondary to psychotropic treatment and evaluate associations between 1-month metabolic changes and both baseline and 1-month changes in DNA methylation levels. Seventy-nine patients starting a weight gain inducing psychotropic treatment were selected from the PsyMetab study cohort. Epigenome-wide DNA methylation was measured at baseline and after 1 month of treatment, using the Illumina Methylation EPIC BeadChip. RESULTS A global methylation increase was noted after the first month of treatment, which was more pronounced (p < 2.2 × 10-16) in patients whose weight remained stable (< 2.5% weight increase). Epigenome-wide significant methylation changes (p < 9 × 10-8) were observed at 52 loci in the whole cohort. When restricting the analysis to patients who underwent important early weight gain (≥ 5% weight increase), one locus (cg12209987) showed a significant increase in methylation levels (p = 3.8 × 10-8), which was also associated with increased weight gain in the whole cohort (p = 0.004). Epigenome-wide association analyses failed to identify a significant link between metabolic changes and methylation data. Nevertheless, among the strongest associations, a potential causal effect of the baseline methylation level of cg11622362 on glycemia was revealed by a two-sample Mendelian randomization analysis (n = 3841 for instrument-exposure association; n = 314,916 for instrument-outcome association). CONCLUSION These findings provide new insights into the mechanisms of psychotropic drug-induced weight gain, revealing important epigenetic alterations upon treatment, some of which may play a mediatory role.
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Affiliation(s)
- Céline Dubath
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Hôpital de Cery, 1008, Prilly, Lausanne, Switzerland.
| | - Eleonora Porcu
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Aurélie Delacrétaz
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Hôpital de Cery, 1008, Prilly, Lausanne, Switzerland
| | - Claire Grosu
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Hôpital de Cery, 1008, Prilly, Lausanne, Switzerland
| | - Nermine Laaboub
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Hôpital de Cery, 1008, Prilly, Lausanne, Switzerland
| | - Marianna Piras
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Hôpital de Cery, 1008, Prilly, Lausanne, Switzerland
| | - Armin von Gunten
- Service of Old Age Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | - Philippe Conus
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | - Kerstin Jessica Plessen
- Service of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Chin Bin Eap
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Hôpital de Cery, 1008, Prilly, Lausanne, Switzerland.
- School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland.
- Center for Research and Innovation in Clinical Pharmaceutical Sciences, University of Lausanne, Lausanne, Switzerland.
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, University of Lausanne, Geneva, Switzerland.
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Darrous L, Hemani G, Davey Smith G, Kutalik Z. PheWAS-based clustering of Mendelian Randomisation instruments reveals distinct mechanism-specific causal effects between obesity and educational attainment. Nat Commun 2024; 15:1420. [PMID: 38360877 PMCID: PMC10869347 DOI: 10.1038/s41467-024-45655-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 01/31/2024] [Indexed: 02/17/2024] Open
Abstract
Mendelian Randomisation (MR) estimates causal effects between risk factors and complex outcomes using genetic instruments. Pleiotropy, heritable confounders, and heterogeneous causal effects violate MR assumptions and can lead to biases. To alleviate these, we propose an approach employing a Phenome-Wide association Clustering of the MR instruments (PWC-MR) and apply this method to revisit the surprisingly large apparent causal effect of body mass index (BMI) on educational attainment (EDU): [Formula: see text] = -0.19 [-0.22, -0.16]. First, we cluster 324 BMI-associated genetic instruments based on their association with 407 traits in the UK Biobank, which yields six distinct groups. Subsequent cluster-specific MR reveals heterogeneous causal effect estimates on EDU. A cluster enriched for socio-economic indicators yields the largest BMI-on-EDU causal effect estimate ([Formula: see text] = -0.49 [-0.56, -0.42]) whereas a cluster enriched for body-mass specific traits provides a more likely estimate ([Formula: see text] = -0.09 [-0.13, -0.05]). Follow-up analyses confirms these findings: within-sibling MR ([Formula: see text] = -0.05 [-0.09, -0.01]); MR for childhood BMI on EDU ([Formula: see text] = -0.03 [-0.06, -0.002]); step-wise multivariable MR ([Formula: see text] = -0.05 [-0.07, -0.02]) where socio-economic indicators are jointly modelled. Here we show how the in-depth examination of the BMI-EDU causal relationship demonstrates the utility of our PWC-MR approach in revealing distinct pleiotropic pathways and confounder mechanisms.
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Affiliation(s)
- Liza Darrous
- University Center for Primary Care and Public Health, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
| | - Gibran Hemani
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
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5
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Ying K, Liu H, Tarkhov AE, Sadler MC, Lu AT, Moqri M, Horvath S, Kutalik Z, Shen X, Gladyshev VN. Causality-enriched epigenetic age uncouples damage and adaptation. Nat Aging 2024; 4:231-246. [PMID: 38243142 PMCID: PMC11070280 DOI: 10.1038/s43587-023-00557-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 12/12/2023] [Indexed: 01/21/2024]
Abstract
Machine learning models based on DNA methylation data can predict biological age but often lack causal insights. By harnessing large-scale genetic data through epigenome-wide Mendelian randomization, we identified CpG sites potentially causal for aging-related traits. Neither the existing epigenetic clocks nor age-related differential DNA methylation are enriched in these sites. These CpGs include sites that contribute to aging and protect against it, yet their combined contribution negatively affects age-related traits. We established a new framework to introduce causal information into epigenetic clocks, resulting in DamAge and AdaptAge-clocks that track detrimental and adaptive methylation changes, respectively. DamAge correlates with adverse outcomes, including mortality, while AdaptAge is associated with beneficial adaptations. These causality-enriched clocks exhibit sensitivity to short-term interventions. Our findings provide a detailed landscape of CpG sites with putative causal links to lifespan and healthspan, facilitating the development of aging biomarkers, assessing interventions, and studying reversibility of age-associated changes.
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Affiliation(s)
- Kejun Ying
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- T. H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Hanna Liu
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Massachusetts College of Pharmacy and Health Sciences, Boston, MA, USA
- Department of Pharmacy, Massachusetts General Hospital, Boston, MA, USA
| | - Andrei E Tarkhov
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Marie C Sadler
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ake T Lu
- Altos Labs, San Diego, CA, USA
- Departments of Human Genetics and Biostatistics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Mahdi Moqri
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA
| | - Steve Horvath
- Altos Labs, San Diego, CA, USA
- Departments of Human Genetics and Biostatistics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Xia Shen
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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Auwerx C, Jõeloo M, Sadler MC, Tesio N, Ojavee S, Clark CJ, Mägi R, Reymond A, Kutalik Z. Rare copy-number variants as modulators of common disease susceptibility. Genome Med 2024; 16:5. [PMID: 38185688 PMCID: PMC10773105 DOI: 10.1186/s13073-023-01265-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 11/27/2023] [Indexed: 01/09/2024] Open
Abstract
BACKGROUND Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described. METHODS Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank. RESULTS We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs-and especially deletions-strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS. CONCLUSIONS Our results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.
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Affiliation(s)
- Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland.
| | - Maarja Jõeloo
- Institute of Molecular and Cell Biology, University of Tartu, 51010, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia
| | - Marie C Sadler
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland
| | - Nicolò Tesio
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
| | - Sven Ojavee
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
| | - Charlie J Clark
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland.
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7
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de La Harpe R, Schoeler T, Thorball CW, Thomas A, Kutalik Z, Vaucher J. Cannabis use and atherosclerotic cardiovascular disease: a Mendelian randomization study. BMC Cardiovasc Disord 2023; 23:611. [PMID: 38093188 PMCID: PMC10717446 DOI: 10.1186/s12872-023-03641-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 11/29/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Association between cannabis use and development of atherosclerotic cardiovascular disease (ASCVD) is inconsistent and challenging to interpret, given existing study limitations. METHODS Sixty five independent single-nucleotide polymorphisms (SNPs), obtained from a genome-wide association study on lifetime cannabis use, were employed as genetic instruments to estimate the effects of genetically indexed cannabis use on risk of coronary artery disease (CAD) and acute ischemic stroke (IS) using a two-sample Mendelian randomization (MR) approach. Summary statistics on CAD (CARDIoGRAMplusC4D; 60,801 cases and 123,504 controls) and IS (MEGASTROKE; 34,217 cases and 406,111 controls) were obtained separately. A comprehensive review of the observational literature on cannabis use and CAD or IS was also performed and contrasted with MR results. RESULTS There was no causal effect of cannabis use on the risk of CAD (odds ratio (OR) per ever-users vs. never-users 0.93; 95% confidence interval (CI), 0.83 to 1.03) or IS (OR 1.05; 95%CI, 0.93 to 1.19). Sensitivity analyses yielded similar results, and no heterogeneity and directional pleiotropy was observed. Our meta-analysis of observational studies showed no significant association between ever use of cannabis with risk of CAD (k = 6 studies; ORpooled = 1.23, 95%CI 0.78 to 1.69), nor with IS (k = 6 studies; ORpooled = 1.22, 95%CI 0.95 to 1.50). CONCLUSION Using a genetic approach approximating a clinical trial does not provide evidence consistent with a causal effect of genetic predisposition to cannabis use on CAD or IS development. Further studies are needed to replicate our findinds, an to investigate more precisely the risk of ASCVD in relation to the quantity, type, route of administration, or the age at exposure to cannabis.
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Affiliation(s)
- Roxane de La Harpe
- Department of Medicine, Division of Internal Medicine, University Hospital of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland.
| | - Tabea Schoeler
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Christian W Thorball
- Precision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital of Lausanne, Chemin des Roches 1a/1b, 1010, Lausanne, Switzerland
| | - Aurélien Thomas
- Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Centre universitaire de médecine et santé publique, Lausanne, Switzerland
| | - Julien Vaucher
- Department of Medicine, Division of Internal Medicine, University Hospital of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland
- HFR Freiburg Kantonspital, Lausanne, Switzerland
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8
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Hanssen R, Auwerx C, Jõeloo M, Sadler MC, Henning E, Keogh J, Bounds R, Smith M, Firth HV, Kutalik Z, Farooqi IS, Reymond A, Lawler K. Chromosomal deletions on 16p11.2 encompassing SH2B1 are associated with accelerated metabolic disease. Cell Rep Med 2023; 4:101155. [PMID: 37586323 PMCID: PMC10439272 DOI: 10.1016/j.xcrm.2023.101155] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 06/08/2023] [Accepted: 07/18/2023] [Indexed: 08/18/2023]
Abstract
New approaches are needed to treat people whose obesity and type 2 diabetes (T2D) are driven by specific mechanisms. We investigate a deletion on chromosome 16p11.2 (breakpoint 2-3 [BP2-3]) encompassing SH2B1, a mediator of leptin and insulin signaling. Phenome-wide association scans in the UK (N = 502,399) and Estonian (N = 208,360) biobanks show that deletion carriers have increased body mass index (BMI; p = 1.3 × 10-10) and increased rates of T2D. Compared with BMI-matched controls, deletion carriers have an earlier onset of T2D, with poorer glycemic control despite higher medication usage. Cystatin C, a biomarker of kidney function, is significantly elevated in deletion carriers, suggesting increased risk of renal impairment. In a Mendelian randomization study, decreased SH2B1 expression increases T2D risk (p = 8.1 × 10-6). We conclude that people with 16p11.2 BP2-3 deletions have early, complex obesity and T2D and may benefit from therapies that enhance leptin and insulin signaling.
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Affiliation(s)
- Ruth Hanssen
- University of Cambridge Metabolic Research Laboratories, Wellcome-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland; Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; University Center for Primary Care and Public Health, 1010 Lausanne, Switzerland
| | - Maarja Jõeloo
- Institute of Molecular and Cell Biology, University of Tartu, 51010 Tartu, Estonia; Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Marie C Sadler
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; University Center for Primary Care and Public Health, 1010 Lausanne, Switzerland
| | - Elana Henning
- University of Cambridge Metabolic Research Laboratories, Wellcome-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Julia Keogh
- University of Cambridge Metabolic Research Laboratories, Wellcome-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Rebecca Bounds
- University of Cambridge Metabolic Research Laboratories, Wellcome-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Miriam Smith
- University of Cambridge Metabolic Research Laboratories, Wellcome-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Helen V Firth
- Department of Clinical Genetics, Cambridge University Hospitals NHS Foundation Trust & Wellcome Sanger Institute, Cambridge, UK
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; University Center for Primary Care and Public Health, 1010 Lausanne, Switzerland
| | - I Sadaf Farooqi
- University of Cambridge Metabolic Research Laboratories, Wellcome-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK.
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland.
| | - Katherine Lawler
- University of Cambridge Metabolic Research Laboratories, Wellcome-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK.
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9
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Burgess S, Davey Smith G, Davies NM, Dudbridge F, Gill D, Glymour MM, Hartwig FP, Kutalik Z, Holmes MV, Minelli C, Morrison JV, Pan W, Relton CL, Theodoratou E. Guidelines for performing Mendelian randomization investigations: update for summer 2023. Wellcome Open Res 2023; 4:186. [PMID: 32760811 PMCID: PMC7384151 DOI: 10.12688/wellcomeopenres.15555.3] [Citation(s) in RCA: 81] [Impact Index Per Article: 81.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2023] [Indexed: 08/08/2023] Open
Abstract
This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into ten sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), extensions and additional analyses, data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 24 months.
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Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- BHF Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Neil M. Davies
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Division of Psychiatry, University College London, London, UK
- Department of Statistical Sciences, University College London, London, WC1E 6BT, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Fernando P. Hartwig
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland
| | - Michael V. Holmes
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Cosetta Minelli
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Jean V. Morrison
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Wei Pan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Caroline L. Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
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10
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Sadler MC, Auwerx C, Deelen P, Kutalik Z. Multi-layered genetic approaches to identify approved drug targets. Cell Genom 2023; 3:100341. [PMID: 37492104 PMCID: PMC10363916 DOI: 10.1016/j.xgen.2023.100341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/25/2023] [Accepted: 05/16/2023] [Indexed: 07/27/2023]
Abstract
Drugs targeting genes linked to disease via evidence from human genetics have increased odds of approval. Approaches to prioritize such genes include genome-wide association studies (GWASs), rare variant burden tests in exome sequencing studies (Exome), or integration of a GWAS with expression/protein quantitative trait loci (eQTL/pQTL-GWAS). Here, we compare gene-prioritization approaches on 30 clinically relevant traits and benchmark their ability to recover drug targets. Across traits, prioritized genes were enriched for drug targets with odds ratios (ORs) of 2.17, 2.04, 1.81, and 1.31 for the GWAS, eQTL-GWAS, Exome, and pQTL-GWAS methods, respectively. Adjusting for differences in testable genes and sample sizes, GWAS outperforms e/pQTL-GWAS, but not the Exome approach. Furthermore, performance increased through gene network diffusion, although the node degree, being the best predictor (OR = 8.7), revealed strong bias in literature-curated networks. In conclusion, we systematically assessed strategies to prioritize drug target genes, highlighting the promises and pitfalls of current approaches.
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Affiliation(s)
- Marie C. Sadler
- University Center for Primary Care and Public Health, Route de Berne 113, 1010 Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Quartier Sorge, 1015 Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland
| | - Chiara Auwerx
- University Center for Primary Care and Public Health, Route de Berne 113, 1010 Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Quartier Sorge, 1015 Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Patrick Deelen
- Department of Genetics, University of Groningen, 9700 Groningen, the Netherlands
- Oncode Institute, 3521 Utrecht, the Netherlands
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, Route de Berne 113, 1010 Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Quartier Sorge, 1015 Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland
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11
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Zamariolli M, Auwerx C, Sadler MC, van der Graaf A, Lepik K, Schoeler T, Moysés-Oliveira M, Dantas AG, Melaragno MI, Kutalik Z. Response to Bassett et al. Am J Hum Genet 2023; 110:1219-1220. [PMID: 37419093 PMCID: PMC10357494 DOI: 10.1016/j.ajhg.2023.05.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/09/2023] Open
Affiliation(s)
- Malú Zamariolli
- Genetics Division, Universidade Federal de São Paulo, São Paulo, Brazil; Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Chiara Auwerx
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland; Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Marie C Sadler
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | | | - Kaido Lepik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Tabea Schoeler
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | | | - Anelisa G Dantas
- Genetics Division, Universidade Federal de São Paulo, São Paulo, Brazil
| | | | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.
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12
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Schoeler T, Speed D, Porcu E, Pirastu N, Pingault JB, Kutalik Z. Participation bias in the UK Biobank distorts genetic associations and downstream analyses. Nat Hum Behav 2023; 7:1216-1227. [PMID: 37106081 PMCID: PMC10365993 DOI: 10.1038/s41562-023-01579-9] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 03/07/2023] [Indexed: 04/29/2023]
Abstract
While volunteer-based studies such as the UK Biobank have become the cornerstone of genetic epidemiology, the participating individuals are rarely representative of their target population. To evaluate the impact of selective participation, here we derived UK Biobank participation probabilities on the basis of 14 variables harmonized across the UK Biobank and a representative sample. We then conducted weighted genome-wide association analyses on 19 traits. Comparing the output from weighted genome-wide association analyses (neffective = 94,643 to 102,215) with that from standard genome-wide association analyses (n = 263,464 to 283,749), we found that increasing representativeness led to changes in SNP effect sizes and identified novel SNP associations for 12 traits. While heritability estimates were less impacted by weighting (maximum change in h2, 5%), we found substantial discrepancies for genetic correlations (maximum change in rg, 0.31) and Mendelian randomization estimates (maximum change in βSTD, 0.15) for socio-behavioural traits. We urge the field to increase representativeness in biobank samples, especially when studying genetic correlates of behaviour, lifestyles and social outcomes.
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Affiliation(s)
- Tabea Schoeler
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
- Department of Clinical, Educational and Health Psychology, University College London, London, UK.
| | - Doug Speed
- Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Eleonora Porcu
- Precision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Nicola Pirastu
- Genomics Research Centre, Human Technopole, Milan, Italy
| | - Jean-Baptiste Pingault
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- University Center for Primary Care and Public Health, Lausanne, Switzerland.
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13
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Edelson JL, Schneider LD, Amar D, Brink-Kjaer A, Cederberg KL, Kutalik Z, Hagen EW, Peppard PE, Tempaku PF, Tufik S, Evans DS, Stone K, Tranah G, Cade B, Redline S, Haba-Rubio J, Heinzer R, Marques-Vidal P, Vollenweider P, Winkelmann J, Zou J, Mignot E. The genetic etiology of periodic limb movement in sleep. Sleep 2023; 46:zsac121. [PMID: 35670608 PMCID: PMC10091093 DOI: 10.1093/sleep/zsac121] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 12/12/2022] [Indexed: 11/14/2022] Open
Abstract
STUDY OBJECTIVES Periodic limb movement in sleep is a common sleep phenotype characterized by repetitive leg movements that occur during or before sleep. We conducted a genome-wide association study (GWAS) of periodic limb movements in sleep (PLMS) using a joint analysis (i.e., discovery, replication, and joint meta-analysis) of four cohorts (MrOS, the Wisconsin Sleep Cohort Study, HypnoLaus, and MESA), comprised of 6843 total subjects. METHODS The MrOS study and Wisconsin Sleep Cohort Study (N = 1745 cases) were used for discovery. Replication in the HypnoLaus and MESA cohorts (1002 cases) preceded joint meta-analysis. We also performed LD score regression, estimated heritability, and computed genetic correlations between potentially associated traits such as restless leg syndrome (RLS) and insomnia. The causality and direction of the relationships between PLMS and RLS was evaluated using Mendelian randomization. RESULTS We found 2 independent loci were significantly associated with PLMS: rs113851554 (p = 3.51 × 10-12, β = 0.486), an SNP located in a putative regulatory element of intron eight of MEIS1 (2p14); and rs9369062 (p = 3.06 × 10-22, β = 0.2093), a SNP located in the intron region of BTBD9 (6p12); both of which were also lead signals in RLS GWAS. PLMS is genetically correlated with insomnia, risk of stroke, and RLS, but not with iron deficiency. Pleiotropy adjusted Mendelian randomization analysis identified a causal effect of RLS on PLMS. CONCLUSIONS Because PLMS is more common than RLS, PLMS may have multiple causes and additional studies are needed to further validate these findings.
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Affiliation(s)
- Jacob L Edelson
- Department of Biomedical Data Sciences, Stanford University School of Medicine, Palo Alto, CA 94603, USA
| | - Logan D Schneider
- Stanford/VA Alzheimer’s Research Center, Palo Alto, CA 94603, USA
- Stanford Department of Psychiatry and Behavioral Medicine, Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Palo Alto, CA 94603, USA
| | - David Amar
- Stanford Department of Cardiovascular Medicine, Stanford University School of Medicine, Palo Alto, CA 94603, USA
| | - Andreas Brink-Kjaer
- Stanford Department of Psychiatry and Behavioral Medicine, Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Palo Alto, CA 94603, USA
| | - Katie L Cederberg
- Stanford Department of Psychiatry and Behavioral Medicine, Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Palo Alto, CA 94603, USA
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne 1010, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Erika W Hagen
- University of Wisconsin-Madison, School of Medicine and Public Health, Department of Population Health Sciences, Madison, WI 53726, USA
| | - Paul E Peppard
- University of Wisconsin-Madison, School of Medicine and Public Health, Department of Population Health Sciences, Madison, WI 53726, USA
| | | | - Sergio Tufik
- Department of Psychobiology, Universidade Federal de São Paulo, São Paulo 04021002, Brazil
| | - Daniel S Evans
- California Pacific Medical Center, Research Institute, San Francisco, CA 94107, USA
| | - Katie Stone
- California Pacific Medical Center, Research Institute, San Francisco, CA 94107, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA
| | - Greg Tranah
- California Pacific Medical Center, Research Institute, San Francisco, CA 94107, USA
| | - Brian Cade
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA 102115, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA 102115, USA
| | - Jose Haba-Rubio
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne 1011, Switzerland
| | - Raphael Heinzer
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne 1011, Switzerland
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne 1011, Switzerland
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne 1011, Switzerland
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Center Munich (HMGU) Technical University of Munich, 81675 Munich, Germany
- School of Medicine, Institute of Human Genetics Synergy, Cluster of Neuroscience Munich, 52246 Munich, Germany
| | - James Zou
- Department of Biomedical Data Sciences, Stanford University School of Medicine, Palo Alto, CA 94603, USA
| | - Emmanuel Mignot
- Stanford Department of Psychiatry and Behavioral Medicine, Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Palo Alto, CA 94603, USA
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14
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Mounier N, Kutalik Z. Bias correction for inverse variance weighting Mendelian randomization. Genet Epidemiol 2023; 47:314-331. [PMID: 37036286 DOI: 10.1002/gepi.22522] [Citation(s) in RCA: 41] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 03/02/2023] [Accepted: 03/14/2023] [Indexed: 04/11/2023]
Abstract
Inverse-variance weighted two-sample Mendelian randomization (IVW-MR) is the most widely used approach that utilizes genome-wide association studies (GWAS) summary statistics to infer the existence and the strength of the causal effect between an exposure and an outcome. Estimates from this approach can be subject to different biases due to the use of weak instruments and winner's curse, which can change as a function of the overlap between the exposure and outcome samples. We developed a method (MRlap) that simultaneously considers weak instrument bias and winner's curse while accounting for potential sample overlap. Assuming spike-and-slab genomic architecture and leveraging linkage disequilibrium score regression and other techniques, we could analytically derive, reliably estimate, and hence correct for the bias of IVW-MR using association summary statistics only. We tested our approach using simulated data for a wide range of realistic settings. In all the explored scenarios, our correction reduced the bias, in some situations by as much as 30-fold. In addition, our results are consistent with the fact that the strength of the biases will decrease as the sample size increases and we also showed that the overall bias is also dependent on the genetic architecture of the exposure, and traits with low heritability and/or high polygenicity are more strongly affected. Applying MRlap to obesity-related exposures revealed statistically significant differences between IVW-based and corrected effects, both for nonoverlapping and fully overlapping samples. Our method not only reduces bias in causal effect estimation but also enables the use of much larger GWAS sample sizes, by allowing for potentially overlapping samples.
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Affiliation(s)
- Ninon Mounier
- Department of Epidemiology and Health Systems, University Center for Primary Care and Public Health, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Zoltán Kutalik
- Department of Epidemiology and Health Systems, University Center for Primary Care and Public Health, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
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15
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Cheval B, Darrous L, Choi KW, Klimentidis YC, Raichlen DA, Alexander GE, Cullati S, Kutalik Z, Boisgontier MP. Genetic insights into the causal relationship between physical activity and cognitive functioning. Sci Rep 2023; 13:5310. [PMID: 37002254 PMCID: PMC10066390 DOI: 10.1038/s41598-023-32150-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/23/2023] [Indexed: 04/03/2023] Open
Abstract
Physical activity and cognitive functioning are strongly intertwined. However, the causal relationships underlying this association are still unclear. Physical activity can enhance brain functions, but healthy cognition may also promote engagement in physical activity. Here, we assessed the bidirectional relationships between physical activity and general cognitive functioning using Latent Heritable Confounder Mendelian Randomization (LHC-MR). Association data were drawn from two large-scale genome-wide association studies (UK Biobank and COGENT) on accelerometer-measured moderate, vigorous, and average physical activity (N = 91,084) and cognitive functioning (N = 257,841). After Bonferroni correction, we observed significant LHC-MR associations suggesting that increased fraction of both moderate (b = 0.32, CI95% = [0.17,0.47], P = 2.89e - 05) and vigorous physical activity (b = 0.22, CI95% = [0.06,0.37], P = 0.007) lead to increased cognitive functioning. In contrast, we found no evidence of a causal effect of average physical activity on cognitive functioning, and no evidence of a reverse causal effect (cognitive functioning on any physical activity measures). These findings provide new evidence supporting a beneficial role of moderate and vigorous physical activity (MVPA) on cognitive functioning.
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Affiliation(s)
- Boris Cheval
- Swiss Center for Affective Sciences, University of Geneva, Geneva, Switzerland.
- Laboratory for the Study of Emotion Elicitation and Expression (E3Lab), Department of Psychology, University of Geneva, Geneva, Switzerland.
| | - Liza Darrous
- University for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
| | - Karmel W Choi
- Department of Psychiatry, Massachusetts General Hospital, Massachusetts, Boston, MA, USA
| | - Yann C Klimentidis
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA
| | - David A Raichlen
- Human and Evolutionary Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
- Department of Anthropology, University of Southern California, Los Angeles, CA, USA
| | - Gene E Alexander
- Department of Psychology, University of Arizona, Tucson, AZ, USA
- Department of Psychiatry, University of Arizona, Tucson, AZ, USA
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
- Arizona Alzheimer's Consortium, Phoenix, AZ, USA
| | - Stéphane Cullati
- Population Health Laboratory, Department of Community Health, University of Fribourg, Fribourg, Switzerland
| | - Zoltán Kutalik
- University for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
| | - Matthieu P Boisgontier
- School of Rehabilitation Sciences, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada.
- Bruyère Research Institute, Ottawa, ON, Canada.
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16
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Auwerx C, Sadler MC, Woh T, Reymond A, Kutalik Z, Porcu E. Exploiting the mediating role of the metabolome to unravel transcript-to-phenotype associations. eLife 2023; 12:81097. [PMID: 36891970 PMCID: PMC9998083 DOI: 10.7554/elife.81097] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 01/17/2023] [Indexed: 02/17/2023] Open
Abstract
Despite the success of genome-wide association studies (GWASs) in identifying genetic variants associated with complex traits, understanding the mechanisms behind these statistical associations remains challenging. Several methods that integrate methylation, gene expression, and protein quantitative trait loci (QTLs) with GWAS data to determine their causal role in the path from genotype to phenotype have been proposed. Here, we developed and applied a multi-omics Mendelian randomization (MR) framework to study how metabolites mediate the effect of gene expression on complex traits. We identified 216 transcript-metabolite-trait causal triplets involving 26 medically relevant phenotypes. Among these associations, 58% were missed by classical transcriptome-wide MR, which only uses gene expression and GWAS data. This allowed the identification of biologically relevant pathways, such as between ANKH and calcium levels mediated by citrate levels and SLC6A12 and serum creatinine through modulation of the levels of the renal osmolyte betaine. We show that the signals missed by transcriptome-wide MR are found, thanks to the increase in power conferred by integrating multiple omics layer. Simulation analyses show that with larger molecular QTL studies and in case of mediated effects, our multi-omics MR framework outperforms classical MR approaches designed to detect causal relationships between single molecular traits and complex phenotypes.
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Affiliation(s)
- Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland.,University Center for Primary Care and Public Health, Lausanne, Switzerland.,Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Marie C Sadler
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.,University Center for Primary Care and Public Health, Lausanne, Switzerland.,Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Tristan Woh
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.,University Center for Primary Care and Public Health, Lausanne, Switzerland.,Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland.,University Center for Primary Care and Public Health, Lausanne, Switzerland
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17
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Zamariolli M, Auwerx C, Sadler MC, van der Graaf A, Lepik K, Schoeler T, Moysés-Oliveira M, Dantas AG, Melaragno MI, Kutalik Z. The impact of 22q11.2 copy-number variants on human traits in the general population. Am J Hum Genet 2023; 110:300-313. [PMID: 36706759 PMCID: PMC9943723 DOI: 10.1016/j.ajhg.2023.01.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 01/03/2023] [Indexed: 01/27/2023] Open
Abstract
While extensively studied in clinical cohorts, the phenotypic consequences of 22q11.2 copy-number variants (CNVs) in the general population remain understudied. To address this gap, we performed a phenome-wide association scan in 405,324 unrelated UK Biobank (UKBB) participants by using CNV calls from genotyping array. We mapped 236 Human Phenotype Ontology terms linked to any of the 90 genes encompassed by the region to 170 UKBB traits and assessed the association between these traits and the copy-number state of 504 genotyping array probes in the region. We found significant associations for eight continuous and nine binary traits associated under different models (duplication-only, deletion-only, U-shape, and mirror models). The causal effect of the expression level of 22q11.2 genes on associated traits was assessed through transcriptome-wide Mendelian randomization (TWMR), revealing that increased expression of ARVCF increased BMI. Similarly, increased DGCR6 expression causally reduced mean platelet volume, in line with the corresponding CNV effect. Furthermore, cross-trait multivariable Mendelian randomization (MVMR) suggested a predominant role of genuine (horizontal) pleiotropy in the CNV region. Our findings show that within the general population, 22q11.2 CNVs are associated with traits previously linked to genes in the region, and duplications and deletions act upon traits in different fashions. We also showed that gain or loss of distinct segments within 22q11.2 may impact a trait under different association models. Our results have provided new insights to help further the understanding of the complex 22q11.2 region.
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Affiliation(s)
- Malú Zamariolli
- Genetics Division, Universidade Federal de São Paulo, São Paulo, Brazil; Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Chiara Auwerx
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland; Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Marie C Sadler
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | | | - Kaido Lepik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Tabea Schoeler
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | | | - Anelisa G Dantas
- Genetics Division, Universidade Federal de São Paulo, São Paulo, Brazil
| | | | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.
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18
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Kentistou KA, Luan J, Wittemans LBL, Hambly C, Klaric L, Kutalik Z, Speakman JR, Wareham NJ, Kendall TJ, Langenberg C, Wilson JF, Joshi PK, Morton NM. Large scale phenotype imputation and in vivo functional validation implicate ADAMTS14 as an adiposity gene. Nat Commun 2023; 14:307. [PMID: 36658113 PMCID: PMC9852585 DOI: 10.1038/s41467-022-35563-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 12/09/2022] [Indexed: 01/20/2023] Open
Abstract
Obesity remains an unmet global health burden. Detrimental anatomical distribution of body fat is a major driver of obesity-mediated mortality risk and is demonstrably heritable. However, our understanding of the full genetic contribution to human adiposity is incomplete, as few studies measure adiposity directly. To address this, we impute whole-body imaging adiposity phenotypes in UK Biobank from the 4,366 directly measured participants onto the rest of the cohort, greatly increasing our discovery power. Using these imputed phenotypes in 392,535 participants yielded hundreds of genome-wide significant associations, six of which replicate in independent cohorts. The leading causal gene candidate, ADAMTS14, is further investigated in a mouse knockout model. Concordant with the human association data, the Adamts14-/- mice exhibit reduced adiposity and weight-gain under obesogenic conditions, alongside an improved metabolic rate and health. Thus, we show that phenotypic imputation at scale offers deeper biological insights into the genetics of human adiposity that could lead to therapeutic targets.
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Affiliation(s)
- Katherine A Kentistou
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, UK
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, UK
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Laura B L Wittemans
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Catherine Hambly
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, AB24 2TZ, UK
| | - Lucija Klaric
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Zoltán Kutalik
- Centre for Primary Care and Public Health, University of Lausanne, Lausanne, 1010, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - John R Speakman
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, AB24 2TZ, UK
- Centre for Energy Metabolism and Reproduction, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- Shenzhen Key Laboratory of Metabolic Health, CAS Centre of Excellence in Animal Evolution and Genetics, Kunming, China
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Timothy J Kendall
- Centre for Inflammation Research, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health (BIH) Charité University Medicine, Berlin, Germany
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Nicholas M Morton
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, UK.
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19
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Sadler MC, Auwerx C, Lepik K, Porcu E, Kutalik Z. Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases. Nat Commun 2022; 13:7559. [PMID: 36477627 PMCID: PMC9729239 DOI: 10.1038/s41467-022-35196-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 11/22/2022] [Indexed: 12/12/2022] Open
Abstract
High-dimensional omics datasets provide valuable resources to determine the causal role of molecular traits in mediating the path from genotype to phenotype. Making use of molecular quantitative trait loci (QTL) and genome-wide association study (GWAS) summary statistics, we propose a multivariable Mendelian randomization (MVMR) framework to quantify the proportion of the impact of the DNA methylome (DNAm) on complex traits that is propagated through the assayed transcriptome. Evaluating 50 complex traits, we find that on average at least 28.3% (95% CI: [26.9%-29.8%]) of DNAm-to-trait effects are mediated through (typically multiple) transcripts in the cis-region. Several regulatory mechanisms are hypothesized, including methylation of the promoter probe cg10385390 (chr1:8'022'505) increasing the risk for inflammatory bowel disease by reducing PARK7 expression. The proposed integrative framework can be extended to other omics layers to identify causal molecular chains, providing a powerful tool to map and interpret GWAS signals.
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Affiliation(s)
- Marie C Sadler
- University Center for Primary Care and Public Health, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
| | - Chiara Auwerx
- University Center for Primary Care and Public Health, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Kaido Lepik
- University Center for Primary Care and Public Health, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Eleonora Porcu
- University Center for Primary Care and Public Health, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
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20
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Hofmeister RJ, Rubinacci S, Ribeiro DM, Buil A, Kutalik Z, Delaneau O. Parent-of-Origin inference for biobanks. Nat Commun 2022; 13:6668. [PMID: 36335127 PMCID: PMC9637181 DOI: 10.1038/s41467-022-34383-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 10/24/2022] [Indexed: 11/06/2022] Open
Abstract
Identical genetic variations can have different phenotypic effects depending on their parent of origin. Yet, studies focusing on parent-of-origin effects have been limited in terms of sample size due to the lack of parental genomes or known genealogies. We propose a probabilistic approach to infer the parent-of-origin of individual alleles that does not require parental genomes nor prior knowledge of genealogy. Our model uses Identity-By-Descent sharing with second- and third-degree relatives to assign alleles to parental groups and leverages chromosome X data in males to distinguish maternal from paternal groups. We combine this with robust haplotype inference and haploid imputation to infer the parent-of-origin for 26,393 UK Biobank individuals. We screen 99 phenotypes for parent-of-origin effects and replicate the discoveries of 6 GWAS studies, confirming signals on body mass index, type 2 diabetes, standing height and multiple blood biomarkers, including the known maternal effect at the MEG3/DLK1 locus on platelet phenotypes. We also report a novel maternal effect at the TERT gene on telomere length, thereby providing new insights on the heritability of this phenotype. All our summary statistics are publicly available to help the community to better characterize the molecular mechanisms leading to parent-of-origin effects and their implications for human health.
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Affiliation(s)
- Robin J Hofmeister
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Simone Rubinacci
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Diogo M Ribeiro
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Alfonso Buil
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Copenhagen, Denmark.,Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.,University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Olivier Delaneau
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland. .,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
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21
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Patxot M, Stojanov M, Ojavee SE, Gobert RP, Kutalik Z, Gavillet M, Baud D, Robinson MR. Haematological changes from conception to childbirth: An indicator of major pregnancy complications. Eur J Haematol 2022; 109:566-575. [PMID: 36059200 PMCID: PMC9825915 DOI: 10.1111/ejh.13844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 07/26/2022] [Accepted: 07/29/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND About 800 women die every day worldwide from pregnancy-related complications, including excessive blood loss, infections and high-blood pressure (World Health Organization, 2019). To improve screening for high-risk pregnancies, we set out to identify patterns of maternal hematological changes associated with future pregnancy complications. METHODS Using mixed effects models, we established changes in 14 complete blood count (CBC) parameters for 1710 healthy pregnancies and compared them to measurements from 98 pregnancy-induced hypertension, 106 gestational diabetes and 339 postpartum hemorrhage cases. RESULTS Results show interindividual variations, but good individual repeatability in CBC values during physiological pregnancies, allowing the identification of specific alterations in women with obstetric complications. For example, in women with uncomplicated pregnancies, haemoglobin count decreases of 0.12 g/L (95% CI -0.16, -0.09) significantly per gestation week (p value <.001). Interestingly, this decrease is three times more pronounced in women who will develop pregnancy-induced hypertension, with an additional decrease of 0.39 g/L (95% CI -0.51, -0.26). We also confirm that obstetric complications and white CBC predict the likelihood of giving birth earlier during pregnancy. CONCLUSION We provide a comprehensive description of the associations between haematological changes through pregnancy and three major obstetric complications to support strategies for prevention, early-diagnosis and maternal care.
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Affiliation(s)
- Marion Patxot
- Department of Computational BiologyUniversity of LausanneLausanneSwitzerland,Swiss Institute of BioinformaticsLausanneSwitzerland
| | - Miloš Stojanov
- Materno‐fetal and Obstetrics Research Unit, Department of Obstetrics and GynecologyCentre Hospitalier Universitaire VaudoisLausanneSwitzerland
| | - Sven Erik Ojavee
- Department of Computational BiologyUniversity of LausanneLausanneSwitzerland,Swiss Institute of BioinformaticsLausanneSwitzerland
| | | | - Zoltán Kutalik
- Department of Computational BiologyUniversity of LausanneLausanneSwitzerland,Swiss Institute of BioinformaticsLausanneSwitzerland,Statistical GeneticsUniversity Center for Primary Care and Public HealthLausanneSwitzerland
| | - Mathilde Gavillet
- Service and Central Laboratory of Haematology, Department of Oncology and Department of Laboratories and PathologyCentre Hospitalier Universitaire VaudoisLausanneSwitzerland
| | - David Baud
- Materno‐fetal and Obstetrics Research Unit, Department of Obstetrics and GynecologyCentre Hospitalier Universitaire VaudoisLausanneSwitzerland
| | - Matthew R. Robinson
- Medical GenomicsInstitute of Science and Technology AustriaKlosterneuburgAustria
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22
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Lepamets M, Auwerx C, Nõukas M, Claringbould A, Porcu E, Kals M, Jürgenson T, Morris AP, Võsa U, Bochud M, Stringhini S, Wijmenga C, Franke L, Peterson H, Vilo J, Lepik K, Mägi R, Kutalik Z. Omics-informed CNV calls reduce false-positive rates and improve power for CNV-trait associations. Human Genetics and Genomics Advances 2022; 3:100133. [PMID: 36035246 PMCID: PMC9399386 DOI: 10.1016/j.xhgg.2022.100133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 07/26/2022] [Indexed: 11/29/2022] Open
Abstract
Copy-number variations (CNV) are believed to play an important role in a wide range of complex traits, but discovering such associations remains challenging. While whole-genome sequencing (WGS) is the gold-standard approach for CNV detection, there are several orders of magnitude more samples with available genotyping microarray data. Such array data can be exploited for CNV detection using dedicated software (e.g., PennCNV); however, these calls suffer from elevated false-positive and -negative rates. In this study, we developed a CNV quality score that weights PennCNV calls (pCNVs) based on their likelihood of being true positive. First, we established a measure of pCNV reliability by leveraging evidence from multiple omics data (WGS, transcriptomics, and methylomics) obtained from the same samples. Next, we built a predictor of omics-confirmed pCNVs, termed omics-informed quality score (OQS), using only PennCNV software output parameters. Promisingly, OQS assigned to pCNVs detected in close family members was up to 35% higher than the OQS of pCNVs not carried by other relatives (p < 3.0 × 10−90), outperforming other scores. Finally, in an association study of four anthropometric traits in 89,516 Estonian Biobank samples, the use of OQS led to a relative increase in the trait variance explained by CNVs of up to 56% compared with published quality filtering methods or scores. Overall, we put forward a flexible framework to improve any CNV detection method leveraging multi-omics evidence, applied it to improve PennCNV calls, and demonstrated its utility by improving the statistical power for downstream association analyses.
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Affiliation(s)
- Maarja Lepamets
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia
- Corresponding author
| | - Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Center for Primary Care and Public Health (Unisanté), Department of Epidemiology and Health Systems, University of Lausanne, Lausanne 1010, Switzerland
| | - Margit Nõukas
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia
| | | | - Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Center for Primary Care and Public Health (Unisanté), Department of Epidemiology and Health Systems, University of Lausanne, Lausanne 1010, Switzerland
| | - Mart Kals
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki 00014, Finland
| | - Tuuli Jürgenson
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu 51009, Estonia
| | | | - Andrew Paul Morris
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester M13 9PL, UK
| | - Urmo Võsa
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Murielle Bochud
- Center for Primary Care and Public Health (Unisanté), Department of Epidemiology and Health Systems, University of Lausanne, Lausanne 1010, Switzerland
| | - Silvia Stringhini
- Unit of Population Epidemiology, Division of Primary Care, Geneva 1205, Switzerland
| | - Cisca Wijmenga
- University of Groningen, University Medical Center Groningen, Department of Genetics, 9713 AV Groningen, the Netherlands
| | - Lude Franke
- University of Groningen, University Medical Center Groningen, Department of Genetics, 9713 AV Groningen, the Netherlands
- Oncode Institute, 3521 AL Utrecht, the Netherlands
| | - Hedi Peterson
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | - Jaak Vilo
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | - Kaido Lepik
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Center for Primary Care and Public Health (Unisanté), Department of Epidemiology and Health Systems, University of Lausanne, Lausanne 1010, Switzerland
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Center for Primary Care and Public Health (Unisanté), Department of Epidemiology and Health Systems, University of Lausanne, Lausanne 1010, Switzerland
- Corresponding author
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23
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Sleiman MB, Roy S, Gao AW, Sadler MC, von Alvensleben GVG, Li H, Sen S, Harrison DE, Nelson JF, Strong R, Miller RA, Kutalik Z, Williams RW, Auwerx J. Sex- and age-dependent genetics of longevity in a heterogeneous mouse population. Science 2022; 377:eabo3191. [PMID: 36173858 PMCID: PMC9905652 DOI: 10.1126/science.abo3191] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
DNA variants that modulate life span provide insight into determinants of health, disease, and aging. Through analyses in the UM-HET3 mice of the Interventions Testing Program (ITP), we detected a sex-independent quantitative trait locus (QTL) on chromosome 12 and identified sex-specific QTLs, some of which we detected only in older mice. Similar relations between life history and longevity were uncovered in mice and humans, underscoring the importance of early access to nutrients and early growth. We identified common age- and sex-specific genetic effects on gene expression that we integrated with model organism and human data to create a hypothesis-building interactive resource of prioritized longevity and body weight genes. Finally, we validated Hipk1, Ddost, Hspg2, Fgd6, and Pdk1 as conserved longevity genes using Caenorhabditis elegans life-span experiments.
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Affiliation(s)
- Maroun Bou Sleiman
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Suheeta Roy
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN 38163, USA
| | - Arwen W. Gao
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Marie C. Sadler
- Institute of Primary Care and Public Health (Unisante), University of Lausanne, Lausanne 1011, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland
| | - Giacomo V. G. von Alvensleben
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Hao Li
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Saunak Sen
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | | | - James F. Nelson
- Barshop Center for Longevity Studies at the University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Randy Strong
- Barshop Center for Longevity Studies at the University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
- South Texas Veterans Healthcare System, San Antonio, TX 78229, USA
| | - Richard A. Miller
- Department of Pathology, University of Michigan Geriatrics Center, Ann Arbor, MI 48109-2200, USA
| | - Zoltán Kutalik
- Institute of Primary Care and Public Health (Unisante), University of Lausanne, Lausanne 1011, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland
| | - Robert W. Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN 38163, USA
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
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24
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Porcu E, Claringbould A, Weihs A, Lepik K, Richardson TG, Völker U, Santoni FA, Teumer A, Franke L, Reymond A, Kutalik Z. Limited evidence for blood eQTLs in human sexual dimorphism. Genome Med 2022; 14:89. [PMID: 35953856 PMCID: PMC9373355 DOI: 10.1186/s13073-022-01088-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 07/14/2022] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND The genetic underpinning of sexual dimorphism is very poorly understood. The prevalence of many diseases differs between men and women, which could be in part caused by sex-specific genetic effects. Nevertheless, only a few published genome-wide association studies (GWAS) were performed separately in each sex. The reported enrichment of expression quantitative trait loci (eQTLs) among GWAS-associated SNPs suggests a potential role of sex-specific eQTLs in the sex-specific genetic mechanism underlying complex traits. METHODS To explore this scenario, we combined sex-specific whole blood RNA-seq eQTL data from 3447 European individuals included in BIOS Consortium and GWAS data from UK Biobank. Next, to test the presence of sex-biased causal effect of gene expression on complex traits, we performed sex-specific transcriptome-wide Mendelian randomization (TWMR) analyses on the two most sexually dimorphic traits, waist-to-hip ratio (WHR) and testosterone levels. Finally, we performed power analysis to calculate the GWAS sample size needed to observe sex-specific trait associations driven by sex-biased eQTLs. RESULTS Among 9 million SNP-gene pairs showing sex-combined associations, we found 18 genes with significant sex-biased cis-eQTLs (FDR 5%). Our phenome-wide association study of the 18 top sex-biased eQTLs on >700 traits unraveled that these eQTLs do not systematically translate into detectable sex-biased trait-associations. In addition, we observed that sex-specific causal effects of gene expression on complex traits are not driven by sex-specific eQTLs. Power analyses using real eQTL- and causal-effect sizes showed that millions of samples would be necessary to observe sex-biased trait associations that are fully driven by sex-biased cis-eQTLs. Compensatory effects may further hamper their detection. CONCLUSIONS Our results suggest that sex-specific eQTLs in whole blood do not translate to detectable sex-specific trait associations of complex diseases, and vice versa that the observed sex-specific trait associations cannot be explained by sex-specific eQTLs.
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Affiliation(s)
- Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland. .,Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,University Center for Primary Care and Public Health, Lausanne, Switzerland.
| | - Annique Claringbould
- University Medical Centre Groningen, Groningen, the Netherlands.,Structural and Computational Biology Unit, European Molecular Biology Laboratories (EMBL), Heidelberg, Germany
| | - Antoine Weihs
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Kaido Lepik
- Institute of Computer Science, University of Tartu, Tartu, Estonia.,Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Tom G Richardson
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, OX3 7DQ, UK
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany.,DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Federico A Santoni
- Endocrine, Diabetes, and Metabolism Service, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland.,Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Alexander Teumer
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.,Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Lude Franke
- University Medical Centre Groningen, Groningen, the Netherlands
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,University Center for Primary Care and Public Health, Lausanne, Switzerland. .,Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
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25
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Collins RL, Glessner JT, Porcu E, Lepamets M, Brandon R, Lauricella C, Han L, Morley T, Niestroj LM, Ulirsch J, Everett S, Howrigan DP, Boone PM, Fu J, Karczewski KJ, Kellaris G, Lowther C, Lucente D, Mohajeri K, Nõukas M, Nuttle X, Samocha KE, Trinh M, Ullah F, Võsa U, Hurles ME, Aradhya S, Davis EE, Finucane H, Gusella JF, Janze A, Katsanis N, Matyakhina L, Neale BM, Sanders D, Warren S, Hodge JC, Lal D, Ruderfer DM, Meck J, Mägi R, Esko T, Reymond A, Kutalik Z, Hakonarson H, Sunyaev S, Brand H, Talkowski ME. A cross-disorder dosage sensitivity map of the human genome. Cell 2022; 185:3041-3055.e25. [PMID: 35917817 PMCID: PMC9742861 DOI: 10.1016/j.cell.2022.06.036] [Citation(s) in RCA: 99] [Impact Index Per Article: 49.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 03/17/2022] [Accepted: 06/20/2022] [Indexed: 02/06/2023]
Abstract
Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics.
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Affiliation(s)
- Ryan L Collins
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.
| | - Joseph T Glessner
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, Division of Human Genetics, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Maarja Lepamets
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia; Institute of Molecular and Cell Biology, University of Tartu, 51010 Tartu, Estonia
| | | | | | - Lide Han
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Theodore Morley
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | | | - Jacob Ulirsch
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Selin Everett
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Daniel P Howrigan
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Philip M Boone
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA
| | - Jack Fu
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Konrad J Karczewski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Georgios Kellaris
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Chelsea Lowther
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Diane Lucente
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Kiana Mohajeri
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Margit Nõukas
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia; Institute of Molecular and Cell Biology, University of Tartu, 51010 Tartu, Estonia
| | - Xander Nuttle
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Kaitlin E Samocha
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10, UK
| | - Mi Trinh
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10, UK
| | - Farid Ullah
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Urmo Võsa
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | | | | | - Matthew E Hurles
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10, UK
| | | | - Erica E Davis
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Hilary Finucane
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - James F Gusella
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | | | - Nicholas Katsanis
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | | | - Benjamin M Neale
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | | | - Jennelle C Hodge
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Dennis Lal
- Cologne Center for Genomics, University of Cologne, 51149 Cologne, Germany; Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Douglas M Ruderfer
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA; Center for Precision Medicine, Department of Biomedical Informatics, and Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | | | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; Center for Primary Care and Public Health, University of Lausanne, 1015 Lausanne, Switzerland; Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland
| | - Hakon Hakonarson
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, Division of Human Genetics, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Shamil Sunyaev
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Division of Genetics, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Pediatric Surgical Research Laboratories, Massachusetts General Hospital, Boston, MA 02114, USA.
| | - Michael E Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.
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Dubath C, Porcu E, Delacrétaz A, Grosu C, Laaboub N, Piras M, Von Gunten A, Conus P, Von Plessen K, Kutalik Z, Eap C. DNA methylation may mediate psychotropic drug-induced metabolic side effects: results from a 1-month observational study. Eur Psychiatry 2022. [PMCID: PMC9567522 DOI: 10.1192/j.eurpsy.2022.285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Introduction Metabolic side effects of psychotropic medications are a major drawback to patients’ effective treatment. Among the mechanisms underlying their development, DNA methylation may be involved. Objectives The aim of this study was to estimate DNA methylation changes occurring secondary to psychotropic treatment and evaluate associations between 1-month metabolic changes and baseline DNA methylation or 1-month DNA methylation changes, using an epigenome-wide approach. Methods Seventy-nine psychiatric patients recruited as part of PsyMetab study, who started a treatment with either an antipsychotic, a mood stabilizer or mirtazapine were selected. Epigenome-wide DNA methylation was measured using the Illumina Methylation EPIC BeadChip at baseline and after one month of treatment. Results A global methylation increase was observed after 1 month of treatment, which was more pronounced in patients whose weight remained stable (i.e., <2.5% weight increase). Epigenome-wide significant methylation changes were observed at 52 loci in the whole cohort and at one site, namely cg12209987, located in an intergenic region within an enhancer, specifically in patients who underwent important early weight gain (i.e., ≥5% weight increase) during the same period of treatment (p<5*10-8). Multivariable analysis confirmed an association between an increase in methylation at this locus and weight gain in the whole cohort (p=0.004). Epigenome-wide association analyses failed to identify any significant link between other metabolic changes (e.g. glucose or lipid levels) and methylation data. Conclusions These findings give new insight into the mechanisms of psychotropic drug-induced weight gain. With improved understanding of the metabolic side effects, the use of precision medicine with epigenetics may become possible Disclosure No significant relationships.
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Pirastu N, McDonnell C, Grzeszkowiak EJ, Mounier N, Imamura F, Merino J, Day FR, Zheng J, Taba N, Concas MP, Repetto L, Kentistou KA, Robino A, Esko T, Joshi PK, Fischer K, Ong KK, Gaunt TR, Kutalik Z, Perry JRB, Wilson JF. Using genetic variation to disentangle the complex relationship between food intake and health outcomes. PLoS Genet 2022; 18:e1010162. [PMID: 35653391 PMCID: PMC9162356 DOI: 10.1371/journal.pgen.1010162] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 03/22/2022] [Indexed: 02/02/2023] Open
Abstract
Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes.
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Affiliation(s)
- Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Human Technopole, Milan, Italy
- * E-mail:
| | - Ciara McDonnell
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Centre for Cardiovascular Sciences, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Eryk J. Grzeszkowiak
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Ninon Mounier
- Centre for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Fumiaki Imamura
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Jordi Merino
- Diabetes Unit and Centre for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Felix R. Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Jie Zheng
- MRC Integrative Epidemiology Unit, Bristol Medical School, Bristol, United Kingdom
| | - Nele Taba
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, Trieste, Italy
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Maria Pina Concas
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, Trieste, Italy
| | - Linda Repetto
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Katherine A. Kentistou
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Centre for Cardiovascular Sciences, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Antonietta Robino
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, Trieste, Italy
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Peter K. Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Krista Fischer
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Ken K. Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Tom R. Gaunt
- MRC Integrative Epidemiology Unit, Bristol Medical School, Bristol, United Kingdom
| | - Zoltán Kutalik
- Centre for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - John R. B. Perry
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - James F. Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland, United Kingdom
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28
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Auwerx C, Lepamets M, Sadler MC, Patxot M, Stojanov M, Baud D, Mägi R, Porcu E, Reymond A, Kutalik Z, Metspalu A, Milani L, Mägi R, Nelis M. The individual and global impact of copy-number variants on complex human traits. Am J Hum Genet 2022; 109:647-668. [PMID: 35240056 PMCID: PMC9069145 DOI: 10.1016/j.ajhg.2022.02.010] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 02/09/2022] [Indexed: 12/25/2022] Open
Abstract
The impact of copy-number variations (CNVs) on complex human traits remains understudied. We called CNVs in 331,522 UK Biobank participants and performed genome-wide association studies (GWASs) between the copy number of CNV-proxy probes and 57 continuous traits, revealing 131 signals spanning 47 phenotypes. Our analysis recapitulated well-known associations (e.g., 1q21 and height), revealed the pleiotropy of recurrent CNVs (e.g., 26 and 16 traits for 16p11.2-BP4-BP5 and 22q11.21, respectively), and suggested gene functionalities (e.g., MARF1 in female reproduction). Forty-eight CNV signals (38%) overlapped with single-nucleotide polymorphism (SNP)-GWASs signals for the same trait. For instance, deletion of PDZK1, which encodes a urate transporter scaffold protein, decreased serum urate levels, while deletion of RHD, which encodes the Rhesus blood group D antigen, associated with hematological traits. Other signals overlapped Mendelian disorder regions, suggesting variable expressivity and broad impact of these loci, as illustrated by signals mapping to Rotor syndrome (SLCO1B1/3), renal cysts and diabetes syndrome (HNF1B), or Charcot-Marie-Tooth (PMP22) loci. Total CNV burden negatively impacted 35 traits, leading to increased adiposity, liver/kidney damage, and decreased intelligence and physical capacity. Thirty traits remained burden associated after correcting for CNV-GWAS signals, pointing to a polygenic CNV architecture. The burden negatively correlated with socio-economic indicators, parental lifespan, and age (survivorship proxy), suggesting a contribution to decreased longevity. Together, our results showcase how studying CNVs can expand biological insights, emphasizing the critical role of this mutational class in shaping human traits and arguing in favor of a continuum between Mendelian and complex diseases.
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Affiliation(s)
- Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland; Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland; Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; University Center for Primary Care and Public Health, Lausanne 1010, Switzerland
| | - Maarja Lepamets
- Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia; Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Marie C Sadler
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; University Center for Primary Care and Public Health, Lausanne 1010, Switzerland
| | - Marion Patxot
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland
| | - Miloš Stojanov
- Materno-fetal and Obstetrics Research Unit, Department Woman-Mother-Child, CHUV, Lausanne 1011, Switzerland
| | - David Baud
- Materno-fetal and Obstetrics Research Unit, Department Woman-Mother-Child, CHUV, Lausanne 1011, Switzerland
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
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- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland; Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; University Center for Primary Care and Public Health, Lausanne 1010, Switzerland
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland.
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland; Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; University Center for Primary Care and Public Health, Lausanne 1010, Switzerland.
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29
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Pain O, Hodgson K, Trubetskoy V, Ripke S, Marshe VS, Adams MJ, Byrne EM, Campos AI, Carrillo-Roa T, Cattaneo A, Als TD, Souery D, Dernovsek MZ, Fabbri C, Hayward C, Henigsberg N, Hauser J, Kennedy JL, Lenze EJ, Lewis G, Müller DJ, Martin NG, Mulsant BH, Mors O, Perroud N, Porteous DJ, Rentería ME, Reynolds CF, Rietschel M, Uher R, Wigmore EM, Maier W, Wray NR, Aitchison KJ, Arolt V, Baune BT, Biernacka JM, Bondolfi G, Domschke K, Kato M, Li QS, Liu YL, Serretti A, Tsai SJ, Turecki G, Weinshilboum R, McIntosh AM, Lewis CM, Kasper S, Zohar J, Souery D, Montgomery S, Albani D, Forloni G, Ferentinos P, Rujescu D, Mendlewicz J, Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, Adams MJ, Agerbo E, Air TM, Andlauer TF, Bacanu SA, Bækvad-Hansen M, Beekman AT, Bigdeli TB, Binder EB, Bryois J, Buttenschøn HN, Bybjerg-Grauholm J, Cai N, Castelao E, Christensen JH, Clarke TK, Coleman JR, Colodro-Conde L, Couvy-Duchesne B, Craddock N, Crawford GE, Davies G, Deary IJ, Degenhardt F, Derks EM, Direk N, Dolan CV, Dunn EC, Eley TC, Escott-Price V, Hassan Kiadeh FF, Finucane HK, Foo JC, Forstner AJ, Frank J, Gaspar HA, Gill M, Goes FS, Gordon SD, Grove J, Hall LS, Hansen CS, Hansen TF, Herms S, Hickie IB, Hoffmann P, Homuth G, Horn C, Hottenga JJ, Hougaard DM, Howard DM, Ising M, Jansen R, Jones I, Jones LA, Jorgenson E, Knowles JA, Kohane IS, Kraft J, Kretzschmar WW, Kutalik Z, Li Y, Lind PA, MacIntyre DJ, MacKinnon DF, Maier RM, Maier W, Marchini J, Mbarek H, McGrath P, McGuffin P, Medland SE, Mehta D, Middeldorp CM, Mihailov E, Milaneschi Y, Milani L, Mondimore FM, Montgomery GW, Mostafavi S, Mullins N, Nauck M, Ng B, Nivard MG, Nyholt DR, O’Reilly PF, Oskarsson H, Owen MJ, Painter JN, Pedersen CB, Pedersen MG, Peterson RE, Peyrot WJ, Pistis G, Posthuma D, Quiroz JA, Qvist P, Rice JP, Riley BP, Rivera M, Mirza SS, Schoevers R, Schulte EC, Shen L, Shi J, Shyn SI, Sigurdsson E, Sinnamon GC, Smit JH, Smith DJ, Stefansson H, Steinberg S, Streit F, Strohmaier J, Tansey KE, Teismann H, Teumer A, Thompson W, Thomson PA, Thorgeirsson TE, Traylor M, Treutlein J, Trubetskoy V, Uitterlinden AG, Umbricht D, Van der Auwera S, van Hemert AM, Viktorin A, Visscher PM, Wang Y, Webb BT, Weinsheimer SM, Wellmann J, Willemsen G, Witt SH, Wu Y, Xi HS, Yang J, Zhang F, Arolt V, Baune BT, Berger K, Boomsma DI, Cichon S, Dannlowski U, de Geus E, DePaulo JR, Domenici E, Domschke K, Esko T, Grabe HJ, Hamilton SP, Hayward C, Heath AC, Kendler KS, Kloiber S, Lewis G, Li QS, Lucae S, Madden PA, Magnusson PK, Martin NG, McIntosh AM, Metspalu A, Mors O, Mortensen PB, Müller-Myhsok B, Nordentoft M, Nöthen MM, O’Donovan MC, Paciga SA, Pedersen NL, Penninx BW, Perlis RH, Porteous DJ, Potash JB, Preisig M, Rietschel M, Schaefer C, Schulze TG, Smoller JW, Stefansson K, Tiemeier H, Uher R, Völzke H, Weissman MM, Werge T, Lewis CM, Levinson DF, Breen G, Børglum AD, Sullivan PF. Identifying the Common Genetic Basis of Antidepressant Response. Biol Psychiatry Glob Open Sci 2022; 2:115-126. [PMID: 35712048 PMCID: PMC9117153 DOI: 10.1016/j.bpsgos.2021.07.008] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/15/2021] [Accepted: 07/19/2021] [Indexed: 01/20/2023] Open
Abstract
Background Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods Genome-wide analysis of remission (n remit = 1852, n nonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism-based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism-based heritability was significantly different from zero for remission (h 2 = 0.132, SE = 0.056) but not for percentage improvement (h 2 = -0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.
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Auwerx C, Sadler MC, Reymond A, Kutalik Z. From Pharmacogenetics to Pharmaco-Omics:Milestones and Future Directions. Human Genetics and Genomics Advances 2022; 3:100100. [PMID: 35373152 PMCID: PMC8971318 DOI: 10.1016/j.xhgg.2022.100100] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. Since then, pharmacogenetics has grown into its own field, motivated by the translation of identified gene-drug interactions into therapeutic applications. Despite numerous challenges ahead, our understanding of the human pharmacogenetic landscape has greatly improved thanks to the integration of tools originating from disciplines as diverse as biochemistry, molecular biology, statistics, and computer sciences. In this review, we discuss past, present, and future developments of pharmacogenetics methodology, focusing on three milestones: how early research established the genetic basis of drug responses, how technological progress made it possible to assess the full extent of pharmacological variants, and how multi-dimensional omics datasets can improve the identification, functional validation, and mechanistic understanding of the interplay between genes and drugs. We outline novel strategies to repurpose and integrate molecular and clinical data originating from biobanks to gain insights analogous to those obtained from randomized controlled trials. Emphasizing the importance of increased diversity, we envision future directions for the field that should pave the way to the clinical implementation of pharmacogenetics.
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Darrous L, Mounier N, Kutalik Z. Simultaneous estimation of bi-directional causal effects and heritable confounding from GWAS summary statistics. Nat Commun 2021; 12:7274. [PMID: 34907193 PMCID: PMC8671515 DOI: 10.1038/s41467-021-26970-w] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 10/28/2021] [Indexed: 01/26/2023] Open
Abstract
Mendelian Randomisation (MR) is an increasingly popular approach that estimates the causal effect of risk factors on complex human traits. While it has seen several extensions that relax its basic assumptions, most suffer from two major limitations; their under-exploitation of genome-wide markers, and sensitivity to the presence of a heritable confounder of the exposure-outcome relationship. To overcome these limitations, we propose a Latent Heritable Confounder MR (LHC-MR) method applicable to association summary statistics, which estimates bi-directional causal effects, direct heritabilities, and confounder effects while accounting for sample overlap. We demonstrate that LHC-MR outperforms several existing MR methods in a wide range of simulation settings and apply it to summary statistics of 13 complex traits. Besides several concordant results with other MR methods, LHC-MR unravels new mechanisms (how disease diagnosis might lead to improved lifestyle) and reveals new causal effects (e.g. HDL cholesterol being protective against high systolic blood pressure), hidden from standard MR methods due to a heritable confounder of opposite effect direction.
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Affiliation(s)
- Liza Darrous
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ninon Mounier
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
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Ponte B, Sadler MC, Olinger E, Vollenweider P, Bochud M, Padmanabhan S, Hayward C, Kutalik Z, Devuyst O. Mendelian randomization to assess causality between uromodulin, blood pressure and chronic kidney disease. Kidney Int 2021; 100:1282-1291. [PMID: 34634361 DOI: 10.1016/j.kint.2021.08.032] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 08/02/2021] [Accepted: 08/26/2021] [Indexed: 11/24/2022]
Abstract
UMOD variants associated with higher levels of urinary uromodulin (uUMOD) increase the risk of chronic kidney disease (CKD) and hypertension. However, uUMOD levels also reflect functional kidney tubular mass in observational studies, questioning the causal link between uromodulin production and kidney damage. We used Mendelian randomization to clarify causality between uUMOD levels, kidney function and blood pressure in individuals of European descent. The link between uUMOD and estimated glomerular filtration rate (eGFR) was first investigated in a population-based cohort of 3851 individuals. In observational data, higher uUMOD associated with higher eGFR. Conversely, when using rs12917707 (an UMOD polymorphism) as an instrumental variable in one-sample Mendelian randomization, higher uUMOD strongly associated with eGFR decline. We next applied two-sample Mendelian randomization on four genome wide association study consortia to explore causal links between uUMOD and eGFR, CKD risk (567,460 individuals) and blood pressure (757,461 individuals). Higher uUMOD levels significantly associated with lower eGFR, higher odds for eGFR decline or CKD, and higher systolic or diastolic blood pressure. Each one standard deviation (SD) increase of uUMOD decreased log-transformed eGFR by -0.15 SD (95% confidence interval -0.17 to -0.13) and increased log-odds CKD by 0.13 SD (0.12 to 0.15). One SD increase of uUMOD increased systolic blood pressure by 0.06 SD (0.03 to 0.09) and diastolic blood pressure by 0.08 SD (0.05 to 0.12). The effect of uUMOD on blood pressure was mediated by eGFR, whereas the effect on eGFR was not mediated by blood pressure. Thus, our data support that genetically driven levels of uromodulin have a direct, causal and adverse effect on kidney function outcome in the general population, not mediated by blood pressure.
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Affiliation(s)
- Belen Ponte
- Nephrology and Hypertension Service, Department of Medicine, University Hospitals of Geneva (HUG), Geneva, Switzerland.
| | - Marie C Sadler
- Department of Epidemiology and Health Systems, University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland; Statistical Genetics Group, Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Eric Olinger
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology, University of Zurich, Zürich, Switzerland
| | - Peter Vollenweider
- Department of Internal Medicine, University Hospital of Lausanne (CHUV), Lausanne, Switzerland
| | - Murielle Bochud
- Department of Epidemiology and Health Systems, University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland
| | - Sandosh Padmanabhan
- Department of Health and Social Care, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, Scotland
| | - Caroline Hayward
- Biomedical Genomics Section, Medical Research Council (MRC) Human Genetics Unit, Institute of Genetics and Molecular Medicine (IGMM), University of Edinburgh, Edinburgh, Scotland
| | - Zoltán Kutalik
- Department of Epidemiology and Health Systems, University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland; Statistical Genetics Group, Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Olivier Devuyst
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology, University of Zurich, Zürich, Switzerland.
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Porcu E, Sadler MC, Lepik K, Auwerx C, Wood AR, Weihs A, Sleiman MSB, Ribeiro DM, Bandinelli S, Tanaka T, Nauck M, Völker U, Delaneau O, Metspalu A, Teumer A, Frayling T, Santoni FA, Reymond A, Kutalik Z. Differentially expressed genes reflect disease-induced rather than disease-causing changes in the transcriptome. Nat Commun 2021; 12:5647. [PMID: 34561431 PMCID: PMC8463674 DOI: 10.1038/s41467-021-25805-y] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 08/24/2021] [Indexed: 02/08/2023] Open
Abstract
Comparing transcript levels between healthy and diseased individuals allows the identification of differentially expressed genes, which may be causes, consequences or mere correlates of the disease under scrutiny. We propose a method to decompose the observational correlation between gene expression and phenotypes driven by confounders, forward- and reverse causal effects. The bi-directional causal effects between gene expression and complex traits are obtained by Mendelian Randomization integrating summary-level data from GWAS and whole-blood eQTLs. Applying this approach to complex traits reveals that forward effects have negligible contribution. For example, BMI- and triglycerides-gene expression correlation coefficients robustly correlate with trait-to-expression causal effects (rBMI = 0.11, PBMI = 2.0 × 10-51 and rTG = 0.13, PTG = 1.1 × 10-68), but not detectably with expression-to-trait effects. Our results demonstrate that studies comparing the transcriptome of diseased and healthy subjects are more prone to reveal disease-induced gene expression changes rather than disease causing ones.
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Affiliation(s)
- Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- University Center for Primary Care and Public Health, Lausanne, Switzerland.
| | - Marie C Sadler
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Kaido Lepik
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Andrew R Wood
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, Devon, UK
| | - Antoine Weihs
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Maroun S Bou Sleiman
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne, 1015, Switzerland
| | - Diogo M Ribeiro
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | | | - Toshiko Tanaka
- Clinical Res Branch, National Institute of Aging, Baltimore, MD, USA
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Uwe Völker
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Olivier Delaneau
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | | | - Alexander Teumer
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Timothy Frayling
- University of Exeter Medical School, University of Exeter, Exeter, Devon, UK
| | - Federico A Santoni
- Endocrine, Diabetes, and Metabolism Service, Lausanne University Hospital, Lausanne, Switzerland
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, Devon, UK
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
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Sulc J, Sonrel A, Mounier N, Auwerx C, Marouli E, Darrous L, Draganski B, Kilpeläinen TO, Joshi P, Loos RJF, Kutalik Z. Composite trait Mendelian randomization reveals distinct metabolic and lifestyle consequences of differences in body shape. Commun Biol 2021; 4:1064. [PMID: 34518635 PMCID: PMC8438050 DOI: 10.1038/s42003-021-02550-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 08/12/2021] [Indexed: 02/08/2023] Open
Abstract
Obesity is a major risk factor for a wide range of cardiometabolic diseases, however the impact of specific aspects of body morphology remains poorly understood. We combined the GWAS summary statistics of fourteen anthropometric traits from UK Biobank through principal component analysis to reveal four major independent axes: body size, adiposity, predisposition to abdominal fat deposition, and lean mass. Mendelian randomization analysis showed that although body size and adiposity both contribute to the consequences of BMI, many of their effects are distinct, such as body size increasing the risk of cardiac arrhythmia (b = 0.06, p = 4.2 ∗ 10-17) while adiposity instead increased that of ischemic heart disease (b = 0.079, p = 8.2 ∗ 10-21). The body mass-neutral component predisposing to abdominal fat deposition, likely reflecting a shift from subcutaneous to visceral fat, exhibited health effects that were weaker but specifically linked to lipotoxicity, such as ischemic heart disease (b = 0.067, p = 9.4 ∗ 10-14) and diabetes (b = 0.082, p = 5.9 ∗ 10-19). Combining their independent predicted effects significantly improved the prediction of obesity-related diseases (p < 10-10). The presented decomposition approach sheds light on the biological mechanisms underlying the heterogeneity of body morphology and its consequences on health and lifestyle.
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Affiliation(s)
- Jonathan Sulc
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Anthony Sonrel
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Molecular Life Sciences, University of Zürich, Zürich, Switzerland
| | - Ninon Mounier
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Chiara Auwerx
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, London, UK
- Centre for Genomic Health, Life Sciences, London, UK
| | - Liza Darrous
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Neurology Department, Max-Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Peter Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK.
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35
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Porcu E, Sjaarda J, Lepik K, Carmeli C, Darrous L, Sulc J, Mounier N, Kutalik Z. Causal Inference Methods to Integrate Omics and Complex Traits. Cold Spring Harb Perspect Med 2021; 11:a040493. [PMID: 32816877 PMCID: PMC8091955 DOI: 10.1101/cshperspect.a040493] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Major biotechnological advances have facilitated a tremendous boost to the collection of (gen-/transcript-/prote-/methyl-/metabol-)omics data in very large sample sizes worldwide. Coordinated efforts have yielded a deluge of studies associating diseases with genetic markers (genome-wide association studies) or with molecular phenotypes. Whereas omics-disease associations have led to biologically meaningful and coherent mechanisms, the identified (non-germline) disease biomarkers may simply be correlates or consequences of the explored diseases. To move beyond this realm, Mendelian randomization provides a principled framework to integrate information on omics- and disease-associated genetic variants to pinpoint molecular traits causally driving disease development. In this review, we show the latest advances in this field, flag up key challenges for the future, and propose potential solutions.
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Affiliation(s)
- Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne 1010, Switzerland
| | - Jennifer Sjaarda
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne 1010, Switzerland
| | - Kaido Lepik
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne 1010, Switzerland
- Institute of Computer Science, University of Tartu, Tartu 50409, Estonia
| | - Cristian Carmeli
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne 1010, Switzerland
| | - Liza Darrous
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne 1010, Switzerland
| | - Jonathan Sulc
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne 1010, Switzerland
| | - Ninon Mounier
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne 1010, Switzerland
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne 1010, Switzerland
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX2 5AX, United Kingdom
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Porcu E, Gilardi F, Darrous L, Yengo L, Bararpour N, Gasser M, Marques-Vidal P, Froguel P, Waeber G, Thomas A, Kutalik Z. Triangulating evidence from longitudinal and Mendelian randomization studies of metabolomic biomarkers for type 2 diabetes. Sci Rep 2021; 11:6197. [PMID: 33737653 PMCID: PMC7973501 DOI: 10.1038/s41598-021-85684-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/03/2021] [Indexed: 02/08/2023] Open
Abstract
The number of people affected by Type 2 diabetes mellitus (T2DM) is close to half a billion and is on a sharp rise, representing a major and growing public health burden. Given its mild initial symptoms, T2DM is often diagnosed several years after its onset, leaving half of diabetic individuals undiagnosed. While several classical clinical and genetic biomarkers have been identified, improving early diagnosis by exploring other kinds of omics data remains crucial. In this study, we have combined longitudinal data from two population-based cohorts CoLaus and DESIR (comprising in total 493 incident cases vs. 1360 controls) to identify new or confirm previously implicated metabolomic biomarkers predicting T2DM incidence more than 5 years ahead of clinical diagnosis. Our longitudinal data have shown robust evidence for valine, leucine, carnitine and glutamic acid being predictive of future conversion to T2DM. We confirmed the causality of such association for leucine by 2-sample Mendelian randomisation (MR) based on independent data. Our MR approach further identified new metabolites potentially playing a causal role on T2D, including betaine, lysine and mannose. Interestingly, for valine and leucine a strong reverse causal effect was detected, indicating that the genetic predisposition to T2DM may trigger early changes of these metabolites, which appear well-before any clinical symptoms. In addition, our study revealed a reverse causal effect of metabolites such as glutamic acid and alanine. Collectively, these findings indicate that molecular traits linked to the genetic basis of T2DM may be particularly promising early biomarkers.
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Affiliation(s)
- Eleonora Porcu
- grid.9851.50000 0001 2165 4204Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland ,grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Federica Gilardi
- grid.150338.c0000 0001 0721 9812Unit of Forensic Toxicology and Chemistry, CURML, Lausanne University Hospital and Geneva University Hospitals, Geneva, Switzerland ,grid.9851.50000 0001 2165 4204Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Liza Darrous
- grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.9851.50000 0001 2165 4204Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Loic Yengo
- grid.1003.20000 0000 9320 7537Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Nasim Bararpour
- grid.150338.c0000 0001 0721 9812Unit of Forensic Toxicology and Chemistry, CURML, Lausanne University Hospital and Geneva University Hospitals, Geneva, Switzerland ,grid.9851.50000 0001 2165 4204Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Marie Gasser
- grid.150338.c0000 0001 0721 9812Unit of Forensic Toxicology and Chemistry, CURML, Lausanne University Hospital and Geneva University Hospitals, Geneva, Switzerland ,grid.9851.50000 0001 2165 4204Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Pedro Marques-Vidal
- grid.8515.90000 0001 0423 4662Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Philippe Froguel
- grid.410463.40000 0004 0471 8845Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Université de Lille, Institut Pasteur de Lille, Lille University Hospital, Lille, France ,grid.7445.20000 0001 2113 8111Department of Metabolism, Imperial College London, London, UK
| | - Gerard Waeber
- grid.8515.90000 0001 0423 4662Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Aurelien Thomas
- grid.150338.c0000 0001 0721 9812Unit of Forensic Toxicology and Chemistry, CURML, Lausanne University Hospital and Geneva University Hospitals, Geneva, Switzerland ,grid.9851.50000 0001 2165 4204Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.9851.50000 0001 2165 4204Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
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37
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Pistis G, Milaneschi Y, Vandeleur CL, Lasserre AM, Penninx BW, Lamers F, Boomsma DI, Hottenga JJ, Marques-Vidal P, Vollenweider P, Waeber G, Aubry JM, Preisig M, Kutalik Z. Obesity and atypical depression symptoms: findings from Mendelian randomization in two European cohorts. Transl Psychiatry 2021; 11:96. [PMID: 33542229 PMCID: PMC7862438 DOI: 10.1038/s41398-021-01236-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 01/12/2021] [Accepted: 01/15/2021] [Indexed: 02/08/2023] Open
Abstract
Studies considering the causal role of body mass index (BMI) for the predisposition of major depressive disorder (MDD) based on a Mendelian Randomization (MR) approach have shown contradictory results. These inconsistent findings may be attributable to the heterogeneity of MDD; in fact, several studies have documented associations between BMI and mainly the atypical subtype of MDD. Using a MR approach, we investigated the potential causal role of obesity in both the atypical subtype and its five specific symptoms assessed according to the Statistical Manual of Mental Disorders (DSM), in two large European cohorts, CoLaus|PsyCoLaus (n = 3350, 1461 cases and 1889 controls) and NESDA|NTR (n = 4139, 1182 cases and 2957 controls). We first tested general obesity measured by BMI and then the body fat distribution measured by waist-to-hip ratio (WHR). Results suggested that BMI is potentially causally related to the symptom increase in appetite, for which inverse variance weighted, simple median and weighted median MR regression estimated slopes were 0.68 (SE = 0.23, p = 0.004), 0.77 (SE = 0.37, p = 0.036), and 1.11 (SE = 0.39, p = 0.004). No causal effect of BMI or WHR was found on the risk of the atypical subtype or for any of the other atypical symptoms. Our findings show that higher obesity is likely causal for the specific symptom of increase in appetite in depressed participants and reiterate the need to study depression at the granular level of its symptoms to further elucidate potential causal relationships and gain additional insight into its biological underpinnings.
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Affiliation(s)
- Giorgio Pistis
- Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
| | - Yuri Milaneschi
- grid.420193.d0000 0004 0546 0540Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Vrije Universiteit Medical Center and GGZ inGeest, Amsterdam, The Netherlands
| | - Caroline L. Vandeleur
- grid.8515.90000 0001 0423 4662Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Aurélie M. Lasserre
- grid.8515.90000 0001 0423 4662Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Brenda W.J.H. Penninx
- grid.420193.d0000 0004 0546 0540Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Vrije Universiteit Medical Center and GGZ inGeest, Amsterdam, The Netherlands
| | - Femke Lamers
- grid.420193.d0000 0004 0546 0540Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Vrije Universiteit Medical Center and GGZ inGeest, Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- grid.12380.380000 0004 1754 9227Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- grid.12380.380000 0004 1754 9227Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Pedro Marques-Vidal
- grid.8515.90000 0001 0423 4662Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Peter Vollenweider
- grid.8515.90000 0001 0423 4662Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Gérard Waeber
- grid.8515.90000 0001 0423 4662Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jean-Michel Aubry
- grid.150338.c0000 0001 0721 9812Department of Psychiatry, University Hospital of Geneva, Geneva, Switzerland
| | - Martin Preisig
- grid.8515.90000 0001 0423 4662Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- grid.9851.50000 0001 2165 4204Institute of Primary Care and Public Health (Unisante), University of Lausanne, Lausanne, Switzerland ,grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, Lausanne, Switzerland
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38
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Vuilleumier N, Antiochos P, Marques Vidal P, Virzi J, Pagano S, Satta N, Hartley O, Brandt K, Burger F, Montecucco F, Kutalik Z, Waeber G, Mach F, Vollenweider P. Antibodies against the c-terminus of apoA-1 as predictors of death in the general population but not as therapeutic targets actionable through cognate peptides immunomodulation. Eur Heart J 2020. [DOI: 10.1093/ehjci/ehaa946.3661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Aims
Autoantibodies against apolipoprotein A-1 (anti-apoA-1 IgGs) have emerged as an independent biomarker for cardiovascular disease and mortality in humans, promote death in ApoE−/− mice, and seem to be preferentially oriented against the c-terminal part of apoA-1 (cterA1). Corresponding specific mimetic peptides were shown to reverse anti-apoA-1 IgG pro-inflammatory effects in vitro. We evaluated the association of IgG against c-terminus apoA-1 (anti-cterA1 IgGs) with all-cause mortality in the community and tested the ability of two cterA1 mimetic peptides to reverse the anti-apoA-1 IgG-induced inflammation in vitro and mortality in ApoE−/− mice.
Methods
Anti-cterA1 IgGs were measured on serum samples of 5220 consecutive participants included in the CoLaus study with median follow-up duration of 5.6 years. The primary study outcome was all-cause mortality. Two chemically engineered optimized cterA1 mimetic peptides were tested i) on HEK cells to modulate interleukin-8 (IL-8) and tumor necrosis-alpha (TNF-α) production, and ii) in apoE−/− mice exposed to 16 weeks of anti-apoA-1 IgG passive immunisation.
Results
Anti-cterA1 IgG independently predicted all-cause mortality, each standard deviation of anti-cterA1 IgG being associated with a 18% increase in mortality risk (Hazard Ratio:1.18, 95%confidence intervals:1.04–1.33; p=0.009). Both cterA1 mimetic peptides reduced the anti-apoA-1 IgG-induced inflammation in a dose-dependent manner in vitro, but did not rescue the anti-apoA-1 IgG-associated mortality in mice.
Conclusions
Anti-cterA1 IgG independently predict all-cause mortality in the general population. By failing to reverse the anti-apoA-1 IgG-induced mortality in mice, our data do not support the hypothesis that these autoantibodies could be actionable through cognate peptides immunomodulation.
Funding Acknowledgement
Type of funding source: Private grant(s) and/or Sponsorship. Main funding source(s): This work was supported by a grant from the Leenaards Foundation (grant number 3698 to N.V.) by the Swiss National Science Foundation (grant number 310030-163335 to N.V.) and by the De Reuter Foundation (grant number 315112 to N.V.).
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Affiliation(s)
| | - P Antiochos
- University Hospital Centre Vaudois (CHUV), Lausanne, Switzerland
| | - P Marques Vidal
- University Hospital Centre Vaudois (CHUV), Lausanne, Switzerland
| | - J Virzi
- Geneva University Hospitals, Geneva, Switzerland
| | - S Pagano
- Geneva University Hospitals, Geneva, Switzerland
| | - N Satta
- Geneva University Hospitals, Geneva, Switzerland
| | - O Hartley
- Geneva University Hospitals, Geneva, Switzerland
| | - K Brandt
- Geneva University Hospitals, Geneva, Switzerland
| | - F Burger
- Geneva University Hospitals, Geneva, Switzerland
| | | | - Z Kutalik
- University of Lausanne, Lausanne, Switzerland
| | - G Waeber
- University Hospital Centre Vaudois (CHUV), Lausanne, Switzerland
| | - F Mach
- Geneva University Hospitals, Geneva, Switzerland
| | - P Vollenweider
- University Hospital Centre Vaudois (CHUV), Lausanne, Switzerland
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39
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Kutalik Z. Commentary on: "The contribution of tissue-specific BMI-associated gene sets to cardiometabolic disease risk: a Mendelian randomization study". Int J Epidemiol 2020; 49:1257-1258. [PMID: 32386404 DOI: 10.1093/ije/dyaa062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/24/2020] [Indexed: 11/13/2022] Open
Affiliation(s)
- Zoltán Kutalik
- Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
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40
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Mounier N, Kutalik Z. bGWAS: an R package to perform Bayesian genome wide association studies. Bioinformatics 2020; 36:4374-4376. [PMID: 32470106 PMCID: PMC7520046 DOI: 10.1093/bioinformatics/btaa549] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Revised: 05/18/2020] [Accepted: 05/25/2020] [Indexed: 11/14/2022] Open
Abstract
SUMMARY Increasing sample size is not the only strategy to improve discovery in Genome Wide Association Studies (GWASs) and we propose here an approach that leverages published studies of related traits to improve inference. Our Bayesian GWAS method derives informative prior effects by leveraging GWASs of related risk factors and their causal effect estimates on the focal trait using multivariable Mendelian randomization. These prior effects are combined with the observed effects to yield Bayes Factors, posterior and direct effects. The approach not only increases power, but also has the potential to dissect direct and indirect biological mechanisms. AVAILABILITY AND IMPLEMENTATION bGWAS package is freely available under a GPL-2 License, and can be accessed, alongside with user guides and tutorials, from https://github.com/n-mounier/bGWAS. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Ninon Mounier
- Department of Training, Research and Innovation, University Center for Primary Care and Public Health, Lausanne 1010, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Zoltán Kutalik
- Department of Training, Research and Innovation, University Center for Primary Care and Public Health, Lausanne 1010, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
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41
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Burgess S, Davey Smith G, Davies NM, Dudbridge F, Gill D, Glymour MM, Hartwig FP, Kutalik Z, Holmes MV, Minelli C, Morrison JV, Pan W, Relton CL, Theodoratou E. Guidelines for performing Mendelian randomization investigations. Wellcome Open Res 2020; 4:186. [PMID: 32760811 PMCID: PMC7384151 DOI: 10.12688/wellcomeopenres.15555.2] [Citation(s) in RCA: 333] [Impact Index Per Article: 83.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2020] [Indexed: 01/01/2023] Open
Abstract
This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into nine sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 18 months.
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Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- BHF Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Neil M. Davies
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Division of Psychiatry, University College London, London, UK
- Department of Statistical Sciences, University College London, London, WC1E 6BT, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Fernando P. Hartwig
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland
| | - Michael V. Holmes
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Cosetta Minelli
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Jean V. Morrison
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Wei Pan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Caroline L. Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
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42
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de La Harpe R, Rüeger S, Kutalik Z, Ballabeni P, Suter M, Vionnet N, Laferrère B, Pralong F. Weight Loss Directly Influences Intermediate-Term Remission of Diabetes Mellitus After Bariatric Surgery: A Retrospective Case-Control Study. Obes Surg 2020; 30:1332-1338. [PMID: 31754925 PMCID: PMC10015445 DOI: 10.1007/s11695-019-04283-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
PURPOSE Roux en Y gastric bypass surgery (RYGB) is an effective therapy for patients with severe obesity. It induces both significant weight loss and rapid improvements of metabolic complications. This study was undertaken to better define the direct role of weight loss in the metabolic improvements. METHODS A retrospective, case-control study of a cohort of 649 patients with obesity who underwent RYGB, comparing higher and lower responders at 2 years after surgery (n = 100 pairs). Pairs of patients were matched for age, gender, and initial BMI. The rates of remission of diabetes, hypertension, dyslipidemia, and hyperuricemia were compared using a mixed effects logistic regression analysis. RESULTS Diabetes before surgery was present in 12/100 lower responders and 17/100 higher responders. Remission at 2 years was observed in 4/12 (33%) of lower responders, compared to 15/17 (88%) of higher responders. Thus, the odds of diabetes remission was significantly smaller in lower responders (OR = 0.067, 95% CI 0.01-0.447). A mixed model regression analysis of all the parameters for each patient showed that the odds of achieving remission of any comorbidity was significantly lower in lower responders (OR = 0.62, 95% CI = 0.39-0.97). CONCLUSION We could demonstrate that weight loss is a significant determinant of the remission of diabetes 2 years after RYGB. These data underline the importance of weight loss in the benefits of this procedure.
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Affiliation(s)
- R de La Harpe
- Service of Internal Medicine, Morges, Switzerland. .,Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland.
| | - S Rüeger
- School of Life Sciences, EPFL, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Z Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Center for Primary Care and Public Health (Unisanté), University of Lausanne (UNIL), Lausanne, Switzerland
| | - P Ballabeni
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Center for Primary Care and Public Health (Unisanté), University of Lausanne (UNIL), Lausanne, Switzerland.,Clinical Research Center (CRC), Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - M Suter
- Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland.,Department of Visceral Surgery, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Department of Surgery, Riviera-Chablais Hospital, Aigle-Monthey, Switzerland
| | - N Vionnet
- Service of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - B Laferrère
- New York Obesity Nutrition Research Center, Divison of Endocrinology, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, NY, United States
| | - F Pralong
- Center for Endocrinology, Diabetology and Obesity, La Tour Private Hospital, Meyrin, Switzerland
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43
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Glanville KP, Coleman JR, Hanscombe KB, Euesden J, Choi SW, Purves KL, Breen G, Air TM, Andlauer TF, Baune BT, Binder EB, Blackwood DH, Boomsma DI, Buttenschøn HN, Colodro-Conde L, Dannlowski U, Direk N, Dunn EC, Forstner AJ, de Geus EJ, Grabe HJ, Hamilton SP, Jones I, Jones LA, Knowles JA, Kutalik Z, Levinson DF, Lewis G, Lind PA, Lucae S, Magnusson PK, McGuffin P, McIntosh AM, Milaneschi Y, Mors O, Mostafavi S, Müller-Myhsok B, Pedersen NL, Penninx BW, Potash JB, Preisig M, Ripke S, Shi J, Shyn SI, Smoller JW, Streit F, Sullivan PF, Tiemeier H, Uher R, Van der Auwera S, Weissman MM, O'Reilly PF, Lewis CM. Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression. Biol Psychiatry 2020; 87:419-430. [PMID: 31570195 PMCID: PMC7001040 DOI: 10.1016/j.biopsych.2019.06.031] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 06/26/2019] [Accepted: 06/27/2019] [Indexed: 12/18/2022]
Abstract
BACKGROUND The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression. METHODS We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10-6) and a candidate threshold (1.6 × 10-4). RESULTS No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99). CONCLUSIONS We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.
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Affiliation(s)
- Kylie P. Glanville
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom,Address correspondence to Kylie P. Glanville, M.Sc., Social, Genetic and Developmental Psychiatry Centre; Institute of Psychiatry, Psychology and Neuroscience; King’s College London, de Crespigny Park, London, United Kingdom.
| | - Jonathan R.I. Coleman
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom,National Institute for Health Research Biomedical Research Centre South London and Maudsley National Health Service Trust, King's College London, London, United Kingdom
| | - Ken B. Hanscombe
- Department of Medical and Molecular Genetics, King's College London, London, United Kingdom
| | - Jack Euesden
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Shing Wan Choi
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom,Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, New York, New York
| | - Kirstin L. Purves
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Gerome Breen
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom,National Institute for Health Research Biomedical Research Centre South London and Maudsley National Health Service Trust, King's College London, London, United Kingdom
| | - Tracy M. Air
- Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
| | - Till F.M. Andlauer
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Münster, Germany,Munich Cluster for Systems Neurology (SyNergy), Münster, Germany
| | - Bernhard T. Baune
- Department of Psychiatry, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia,Florey Institute for Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia,Department of Psychiatry, University of Münster, Münster, Germany
| | - Elisabeth B. Binder
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Emory University, Atlanta, Georgia,Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Münster, Germany
| | | | - Dorret I. Boomsma
- Department of Biological Psychology and EMGO+ Institute for Health and Care Research, Vrije Universiteit Medical Center, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Henriette N. Buttenschøn
- NIDO
- Danmark, Regional Hospital West Jutland, Herning, Denmark,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Denmark
| | - Lucía Colodro-Conde
- Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Nese Direk
- Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Psychiatry, Dokuz Eylul University School Of Medicine, Izmir, Turkey
| | - Erin C. Dunn
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts,Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts,Stanley Center for Psychiatric Research, Broad Institute, Cambridge, Massachusetts
| | - Andreas J. Forstner
- Institute of Human Genetics, School of Medicine and University Hospital Bonn, University of Bonn, Bonn, Germany,Centre for Human Genetics, University of Marburg, Marburg, Germany,Department of Psychiatry, University of Basel, Basel, Switzerland,Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Eco J.C. de Geus
- Department of Biological Psychology and EMGO+ Institute for Health and Care Research, Vrije Universiteit Medical Center, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands,Amsterdam Public Health Institute, Vrije Universiteit Medical Center, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Steven P. Hamilton
- Department of Psychiatry, Kaiser Permanente Northern California, San Francisco, California
| | - Ian Jones
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Lisa A. Jones
- Department of Psychological Medicine, University of Worcester, Worcester, United Kingdom
| | - James A. Knowles
- Psychiatry and the Behavioral Sciences, University of Southern California, Los Angeles, California
| | - Zoltán Kutalik
- Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne, Switzerland,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Douglas F. Levinson
- Psychiatry and Behavioral Sciences, Stanford University, Stanford, California
| | - Glyn Lewis
- Division of Psychiatry, University College London, London, United Kingdom
| | - Penelope A. Lind
- Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - Patrik K. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Peter McGuffin
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Andrew M. McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Universiteit Medical Center, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ole Mors
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Denmark,Psychosis Research Unit, Aarhus University Hospital, Risskov, Aarhus, Denmark
| | - Sara Mostafavi
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada,Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Bertram Müller-Myhsok
- University of Liverpool, Liverpool, United Kingdom,Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Münster, Germany,Munich Cluster for Systems Neurology (SyNergy), Münster, Germany
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Brenda W.J.H. Penninx
- Department of Psychiatry, Amsterdam Universiteit Medical Center, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Martin Preisig
- Department of Psychiatry, University Hospital of Lausanne, Prilly, Switzerland
| | - Stephan Ripke
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts,Department of Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts,Department of Psychiatry and Psychotherapy, Universitätsmedizin Berlin Campus Charité Mitte, Berlin, Germany
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Stanley I. Shyn
- Behavioral Health Services, Kaiser Permanente Washington, Seattle, Washington
| | - Jordan W. Smoller
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts,Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts,Stanley Center for Psychiatric Research, Broad Institute, Cambridge, Massachusetts
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Patrick F. Sullivan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina,Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Henning Tiemeier
- Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands,Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands,Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Sandra Van der Auwera
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Myrna M. Weissman
- Division of Epidemiology, New York State Psychiatric Institute, New York, New York,Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, New York
| | | | - Paul F. O'Reilly
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom,Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, New York, New York
| | - Cathryn M. Lewis
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom,Department of Medical and Molecular Genetics, King's College London, London, United Kingdom
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44
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Karsai G, Lone M, Kutalik Z, Brenna JT, Li H, Pan D, von Eckardstein A, Hornemann T. FADS3 is a Δ14Z sphingoid base desaturase that contributes to gender differences in the human plasma sphingolipidome. J Biol Chem 2020; 295:1889-1897. [PMID: 31862735 PMCID: PMC7029104 DOI: 10.1074/jbc.ac119.011883] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 12/16/2019] [Indexed: 12/18/2022] Open
Abstract
Sphingolipids (SLs) are structurally diverse lipids that are defined by the presence of a long-chain base (LCB) backbone. Typically, LCBs contain a single Δ4E double bond (DB) (mostly d18:1), whereas the dienic LCB sphingadienine (d18:2) contains a second DB at the Δ14Z position. The enzyme introducing the Δ14Z DB is unknown. We analyzed the LCB plasma profile in a gender-, age-, and BMI-matched subgroup of the CoLaus cohort (n = 658). Sphingadienine levels showed a significant association with gender, being on average ∼30% higher in females. A genome-wide association study (GWAS) revealed variants in the fatty acid desaturase 3 (FADS3) gene to be significantly associated with the plasma d18:2/d18:1 ratio (p = -log 7.9). Metabolic labeling assays, FADS3 overexpression and knockdown approaches, and plasma LCB profiling in FADS3-deficient mice confirmed that FADS3 is a bona fide LCB desaturase and required for the introduction of the Δ14Z double bond. Moreover, we showed that FADS3 is required for the conversion of the atypical cytotoxic 1-deoxysphinganine (1-deoxySA, m18:0) to 1-deoxysphingosine (1-deoxySO, m18:1). HEK293 cells overexpressing FADS3 were more resistant to m18:0 toxicity than WT cells. In summary, using a combination of metabolic profiling and GWAS, we identified FADS3 to be essential for forming Δ14Z DB containing LCBs, such as d18:2 and m18:1. Our results unravel FADS3 as a Δ14Z LCB desaturase, thereby disclosing the last missing enzyme of the SL de novo synthesis pathway.
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Affiliation(s)
- Gergely Karsai
- Institute for Clinical Chemistry, University Hospital and University Zurich, 8091 Zürich, Switzerland
| | - Museer Lone
- Institute for Clinical Chemistry, University Hospital and University Zurich, 8091 Zürich, Switzerland
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, University of Lausanne, 1010 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - J Thomas Brenna
- Dell Pediatric Research Institute, Departments of Chemistry, Pediatrics, and Nutrition, University of Texas, Austin, Texas 78723
| | - Hongde Li
- Department of Physiology, University of Texas Southwestern Medical Center, Dallas, Texas 75390
| | - Duojia Pan
- Department of Physiology, University of Texas Southwestern Medical Center, Dallas, Texas 75390
| | - Arnold von Eckardstein
- Institute for Clinical Chemistry, University Hospital and University Zurich, 8091 Zürich, Switzerland
| | - Thorsten Hornemann
- Institute for Clinical Chemistry, University Hospital and University Zurich, 8091 Zürich, Switzerland.
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45
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Abstract
PURPOSE OF REVIEW Our review provides a brief summary of the most recent advances towards the identification of the genetic basis of specific aspects of obesity and the quantification of their consequences on health. We also highlight the most promising avenues to be explored in the future. RECENT FINDINGS While obesity has been demonstrated to lead to adverse cardio-metabolic consequences, the determinants of inter-individual variability remain largely unknown. The elucidation of the molecular underpinnings of this relationship is hampered by the extremely heterogeneous nature of obesity as a human trait. Recent technological advances have facilitated a more in-depth characterization of body composition at large-scale. At the pace of current data acquisition and resolution, it is realistic to improve characterization of obesity and to advise individuals based on detailed body composition combined with tissue-specific molecular signatures. Individualized predictions of health implications would enable more personalized and effective public health interventions.
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Affiliation(s)
- Jonathan Sulc
- Institute for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Zoltán Kutalik
- Institute for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK.
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46
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Burgess S, Davey Smith G, Davies NM, Dudbridge F, Gill D, Glymour MM, Hartwig FP, Kutalik Z, Holmes MV, Minelli C, Morrison JV, Pan W, Relton CL, Theodoratou E. Guidelines for performing Mendelian randomization investigations. Wellcome Open Res 2019; 4:186. [PMID: 32760811 PMCID: PMC7384151 DOI: 10.12688/wellcomeopenres.15555.1] [Citation(s) in RCA: 442] [Impact Index Per Article: 88.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/18/2019] [Indexed: 12/20/2022] Open
Abstract
This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into nine sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust methods and one on other approaches), data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 18 months.
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Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- BHF Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Neil M. Davies
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Division of Psychiatry, University College London, London, UK
- Department of Statistical Sciences, University College London, London, WC1E 6BT, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Fernando P. Hartwig
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland
| | - Michael V. Holmes
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Cosetta Minelli
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Jean V. Morrison
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Wei Pan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Caroline L. Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
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47
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Carmeli C, Kutalik Z, Kelly-Irving M, Delpierre C, Bochud M, Kivimaki M, Vineis P, Chadeau-Hyam M, Dermitzakis E, Stringhini S. Early life socioeconomic position and adult systemic inflammation: the role of gene regulation. Eur J Public Health 2019. [DOI: 10.1093/eurpub/ckz185.228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Adverse socioeconomic conditions in childhood affect systemic low-grade inflammation in adulthood. Studies in animals and humans suggest that socioeconomic conditions get under the skin from early life thus contributing to shape pro-inflammatory phenotypes. Although the existence of socioeconomic differences in gene regulation of the immune function have been described previously, no study has so far assessed the extent to which these differences actually explain socioeconomic variations in inflammatory markers.
Methods
First, we ran 2-sample Mendelian Randomization (MR) methods to identify putative genes whose expression drives C-reactive protein (CRP) levels in blood. We used two databases with summary statistics of associations between single nucleotide polymorphisms and gene expression (eQTLGen, N = 31,486 individuals) and CRP (CHARGE, N = 148,164 individuals) in blood. We tested 10,701 genes and retained those with FDR<0.05. Second, we used individual-participant data from a Swiss population-based study (SKIPOGH, N = 723) to estimate the proportion of the effect of paternal occupational position (SEP) on low-grade inflammation in adulthood (CRP>3mg/L) mediated by the selected genes. We estimated odds ratios and mediated proportions through counterfactual-based mediation models.
Results
We identified 426 genes driving CRP levels (robust to unmeasured confounding thanks to MR). They jointly mediated the effect of low father’s occupation on inflammation in adulthood for a proportion up to about 70% [95% confidence intervals (CI) 11-90%] and with an odds ratio of 1.53 [95% CI 1.05-2.15] compared to individuals with high paternal SEP. Analysis of the effects of life-course SEP trajectories (upward, downward and stable low from paternal to adult SEP) on gene regulation revealed trajectory dependent effects.
Conclusions
We suggest that adverse childhood SEP affects systemic inflammation in adulthood through a long-lasting effect on gene regulation.
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Affiliation(s)
- C Carmeli
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Z Kutalik
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - M Kelly-Irving
- UMR1027 LEASP, Inserm & Université Toulouse III, University of Toulouse, France
| | - C Delpierre
- UMR1027 LEASP, Inserm & Université Toulouse III, University of Toulouse, France
| | - M Bochud
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - M Kivimaki
- Department of Epidemiology and Public Health, University College London, London, UK
| | - P Vineis
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - M Chadeau-Hyam
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - E Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland
| | - S Stringhini
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Unit of Population Epidemiology, Geneva University Hospitals, Geneva, Switzerland
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48
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Clark DW, Okada Y, Moore KHS, Mason D, Pirastu N, Gandin I, Mattsson H, Barnes CLK, Lin K, Zhao JH, Deelen P, Rohde R, Schurmann C, Guo X, Giulianini F, Zhang W, Medina-Gomez C, Karlsson R, Bao Y, Bartz TM, Baumbach C, Biino G, Bixley MJ, Brumat M, Chai JF, Corre T, Cousminer DL, Dekker AM, Eccles DA, van Eijk KR, Fuchsberger C, Gao H, Germain M, Gordon SD, de Haan HG, Harris SE, Hofer E, Huerta-Chagoya A, Igartua C, Jansen IE, Jia Y, Kacprowski T, Karlsson T, Kleber ME, Li SA, Li-Gao R, Mahajan A, Matsuda K, Meidtner K, Meng W, Montasser ME, van der Most PJ, Munz M, Nutile T, Palviainen T, Prasad G, Prasad RB, Priyanka TDS, Rizzi F, Salvi E, Sapkota BR, Shriner D, Skotte L, Smart MC, Smith AV, van der Spek A, Spracklen CN, Strawbridge RJ, Tajuddin SM, Trompet S, Turman C, Verweij N, Viberti C, Wang L, Warren HR, Wootton RE, Yanek LR, Yao J, Yousri NA, Zhao W, Adeyemo AA, Afaq S, Aguilar-Salinas CA, Akiyama M, Albert ML, Allison MA, Alver M, Aung T, Azizi F, Bentley AR, Boeing H, Boerwinkle E, Borja JB, de Borst GJ, Bottinger EP, Broer L, Campbell H, Chanock S, Chee ML, Chen G, Chen YDI, Chen Z, Chiu YF, Cocca M, Collins FS, Concas MP, Corley J, Cugliari G, van Dam RM, Damulina A, Daneshpour MS, Day FR, Delgado GE, Dhana K, Doney ASF, Dörr M, Doumatey AP, Dzimiri N, Ebenesersdóttir SS, Elliott J, Elliott P, Ewert R, Felix JF, Fischer K, Freedman BI, Girotto G, Goel A, Gögele M, Goodarzi MO, Graff M, Granot-Hershkovitz E, Grodstein F, Guarrera S, Gudbjartsson DF, Guity K, Gunnarsson B, Guo Y, Hagenaars SP, Haiman CA, Halevy A, Harris TB, Hedayati M, van Heel DA, Hirata M, Höfer I, Hsiung CA, Huang J, Hung YJ, Ikram MA, Jagadeesan A, Jousilahti P, Kamatani Y, Kanai M, Kerrison ND, Kessler T, Khaw KT, Khor CC, de Kleijn DPV, Koh WP, Kolcic I, Kraft P, Krämer BK, Kutalik Z, Kuusisto J, Langenberg C, Launer LJ, Lawlor DA, Lee IT, Lee WJ, Lerch MM, Li L, Liu J, Loh M, London SJ, Loomis S, Lu Y, Luan J, Mägi R, Manichaikul AW, Manunta P, Másson G, Matoba N, Mei XW, Meisinger C, Meitinger T, Mezzavilla M, Milani L, Millwood IY, Momozawa Y, Moore A, Morange PE, Moreno-Macías H, Mori TA, Morrison AC, Muka T, Murakami Y, Murray AD, de Mutsert R, Mychaleckyj JC, Nalls MA, Nauck M, Neville MJ, Nolte IM, Ong KK, Orozco L, Padmanabhan S, Pálsson G, Pankow JS, Pattaro C, Pattie A, Polasek O, Poulter N, Pramstaller PP, Quintana-Murci L, Räikkönen K, Ralhan S, Rao DC, van Rheenen W, Rich SS, Ridker PM, Rietveld CA, Robino A, van Rooij FJA, Ruggiero D, Saba Y, Sabanayagam C, Sabater-Lleal M, Sala CF, Salomaa V, Sandow K, Schmidt H, Scott LJ, Scott WR, Sedaghati-Khayat B, Sennblad B, van Setten J, Sever PJ, Sheu WHH, Shi Y, Shrestha S, Shukla SR, Sigurdsson JK, Sikka TT, Singh JR, Smith BH, Stančáková A, Stanton A, Starr JM, Stefansdottir L, Straker L, Sulem P, Sveinbjornsson G, Swertz MA, Taylor AM, Taylor KD, Terzikhan N, Tham YC, Thorleifsson G, Thorsteinsdottir U, Tillander A, Tracy RP, Tusié-Luna T, Tzoulaki I, Vaccargiu S, Vangipurapu J, Veldink JH, Vitart V, Völker U, Vuoksimaa E, Wakil SM, Waldenberger M, Wander GS, Wang YX, Wareham NJ, Wild S, Yajnik CS, Yuan JM, Zeng L, Zhang L, Zhou J, Amin N, Asselbergs FW, Bakker SJL, Becker DM, Lehne B, Bennett DA, van den Berg LH, Berndt SI, Bharadwaj D, Bielak LF, Bochud M, Boehnke M, Bouchard C, Bradfield JP, Brody JA, Campbell A, Carmi S, Caulfield MJ, Cesarini D, Chambers JC, Chandak GR, Cheng CY, Ciullo M, Cornelis M, Cusi D, Smith GD, Deary IJ, Dorajoo R, van Duijn CM, Ellinghaus D, Erdmann J, Eriksson JG, Evangelou E, Evans MK, Faul JD, Feenstra B, Feitosa M, Foisy S, Franke A, Friedlander Y, Gasparini P, Gieger C, Gonzalez C, Goyette P, Grant SFA, Griffiths LR, Groop L, Gudnason V, Gyllensten U, Hakonarson H, Hamsten A, van der Harst P, Heng CK, Hicks AA, Hochner H, Huikuri H, Hunt SC, Jaddoe VWV, De Jager PL, Johannesson M, Johansson Å, Jonas JB, Jukema JW, Junttila J, Kaprio J, Kardia SLR, Karpe F, Kumari M, Laakso M, van der Laan SW, Lahti J, Laudes M, Lea RA, Lieb W, Lumley T, Martin NG, März W, Matullo G, McCarthy MI, Medland SE, Merriman TR, Metspalu A, Meyer BF, Mohlke KL, Montgomery GW, Mook-Kanamori D, Munroe PB, North KE, Nyholt DR, O'connell JR, Ober C, Oldehinkel AJ, Palmas W, Palmer C, Pasterkamp GG, Patin E, Pennell CE, Perusse L, Peyser PA, Pirastu M, Polderman TJC, Porteous DJ, Posthuma D, Psaty BM, Rioux JD, Rivadeneira F, Rotimi C, Rotter JI, Rudan I, Den Ruijter HM, Sanghera DK, Sattar N, Schmidt R, Schulze MB, Schunkert H, Scott RA, Shuldiner AR, Sim X, Small N, Smith JA, Sotoodehnia N, Tai ES, Teumer A, Timpson NJ, Toniolo D, Tregouet DA, Tuomi T, Vollenweider P, Wang CA, Weir DR, Whitfield JB, Wijmenga C, Wong TY, Wright J, Yang J, Yu L, Zemel BS, Zonderman AB, Perola M, Magnusson PKE, Uitterlinden AG, Kooner JS, Chasman DI, Loos RJF, Franceschini N, Franke L, Haley CS, Hayward C, Walters RG, Perry JRB, Esko T, Helgason A, Stefansson K, Joshi PK, Kubo M, Wilson JF. Associations of autozygosity with a broad range of human phenotypes. Nat Commun 2019; 10:4957. [PMID: 31673082 PMCID: PMC6823371 DOI: 10.1038/s41467-019-12283-6] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Accepted: 08/30/2019] [Indexed: 11/20/2022] Open
Abstract
In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44-66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding.
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Affiliation(s)
- David W Clark
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, Scotland
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Osaka, 565-0871, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Osaka, 565-0871, Japan
| | | | - Dan Mason
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Trust, Bradford, BD96RJ, UK
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, Scotland
| | - Ilaria Gandin
- Research Unit, Area Science Park, Trieste, 34149, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Hannele Mattsson
- Unit of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Catriona L K Barnes
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, Scotland
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Jing Hua Zhao
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Cardiovascular Epidemiology Unit, Department of Public health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Patrick Deelen
- Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands, Groningen, Groningen, 9700 RB, The Netherlands
| | - Rebecca Rohde
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Ichan School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Xiuqing Guo
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, 90502, USA
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, Middlesex, Middlesex, UB1 3HW, UK
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
- The Generation R Study Group, Erasmus University Medical Center, Rotterdam, 3015 CN, The Netherlands
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177, Sweden
| | - Yanchun Bao
- Institute for Social and Economic Research, University of Essex, Colchester, CO4 3SQ, UK
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Biostatistics and Medicine, University of Washington, Seattle, WA, 98101, USA
| | - Clemens Baumbach
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Ginevra Biino
- Institute of Molecular Genetics, National Research Council of Italy, Pavia, 27100, Italy
| | - Matthew J Bixley
- Department of Biochemistry, University of Otago, Dunedin, 9054, New Zealand
| | - Marco Brumat
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore, 117549, Singapore
| | - Tanguy Corre
- Department of Computational Biology, University of Lausanne, Lausanne, 1011, Switzerland
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - Diana L Cousminer
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Annelot M Dekker
- Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht University, Utrecht, 3584 CX, The Netherlands
| | - David A Eccles
- Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
- Malaghan Institute of Medical Research, Wellington, 6242, New Zealand
| | - Kristel R van Eijk
- Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht University, Utrecht, 3584 CX, The Netherlands
| | - Christian Fuchsberger
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, 39100, Italy
| | - He Gao
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
| | - Marine Germain
- INSERM UMR_S 1166, Sorbonne Universités, Paris, 75013, France
- ICAN Institute for Cardiometabolism and Nutrition, Paris, 75013, France
| | - Scott D Gordon
- QIMR Berghofer Institute of Medical Research, Brisbane, Australia
| | - Hugoline G de Haan
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, 2333 ZA, The Netherlands
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Genomic & Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, 8036, Austria
- Institute of Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, 8036, Austria
| | - Alicia Huerta-Chagoya
- CONACyT, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico, 03940, México
| | - Catherine Igartua
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Iris E Jansen
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
- Alzheimer Center Department of Neurology, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, 1081HV, The Netherlands
| | - Yucheng Jia
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, 90502, USA
| | - Tim Kacprowski
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, 17475, Germany
- Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising-Weihenstephan, 85354, Germany
| | - Torgny Karlsson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 75108, Uppsala, Sweden
| | - Marcus E Kleber
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany
| | - Shengchao Alfred Li
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick National Lab for Cancer Research, Frederick, MD, USA
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, 2333 ZA, The Netherlands
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, The University of Tokyo, Tokyo, 108-8639, Japan
| | - Karina Meidtner
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Weihua Meng
- Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, UK
| | - May E Montasser
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Matthias Munz
- Institute for Cardiogenetics, University of Lübeck, Lübeck, 23562, Germany
- DZHK (German Research Centre for Cardiovascular Research), partner site Hamburg/Lübeck/Kiel, Lübeck, 23562, Germany
- University Heart Center Luebeck, Lübeck, 23562, Germany
- Charité - University Medicine Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute for Dental and Craniofacial Sciences, Department of Periodontology and Synoptic Dentistry, Berlin, Germany
| | - Teresa Nutile
- Institute of Genetics and Biophysics A. Buzzati-Traverso - CNR, Naples, 80131, Italy
| | - Teemu Palviainen
- Finnish Institute for Molecular Medicine, University of Helsinki, Helsinki, Finland
| | - Gauri Prasad
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110020, India
| | - Rashmi B Prasad
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Lund University, Skåne University Hospital, Malmö, 20502, Sweden
| | - Tallapragada Divya Sri Priyanka
- Genomic Research on Complex diseases (GRC Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, 500007, India
| | - Federica Rizzi
- ePhood Scientific Unit, ePhood SRL, Bresso (Milano), 20091, Italy
- Department of Health Sciences, University of Milano, Milano, 20139, Italy
| | - Erika Salvi
- Department of Health Sciences, University of Milano, Milano, 20139, Italy
- Neuroalgology Unit, IRCCS Foundation Carlo Besta Neurological Institute, Milano, 20133, Italy
| | - Bishwa R Sapkota
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, 20892-5635, USA
| | - Line Skotte
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, DK-2300, Denmark
| | - Melissa C Smart
- Institute for Social and Economic Research, University of Essex, Colchester, CO4 3SQ, UK
| | - Albert Vernon Smith
- Icelandic Heart Association, Kopavogur, 201, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Ashley van der Spek
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | | | - Rona J Strawbridge
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, G12 8RZ, UK
- Cardiovascular Medicine Unit, Department of Medicine Solna, Centre for Molecular Medicine, Karolinska Institutet, Stockholm, 171 76, Sweden
| | - Salman M Tajuddin
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore City, Maryland, 21224, USA
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, 2300RC, the Netherlands
| | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Niek Verweij
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Ther Netherlands, Groningen, 9713 GZ, the Netherlands
| | - Clara Viberti
- Italian Institute for Genomic Medicine (IIGM) and Dept. Medical Sciences, University of Turin, Italy, Turin, 10126, Italy
| | - Lihua Wang
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, Saint Louis, MO, 63110-1093, USA
| | - Helen R Warren
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Robyn E Wootton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, BS8 2BN, UK
- School of Psychological Science, University of Bristol, Bristol, BS8 1TU, UK
| | - Lisa R Yanek
- Department of Medicine, GeneSTAR Research Program, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Jie Yao
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, 90502, USA
| | - Noha A Yousri
- Department of Genetic Medicine, Weill Cornell Medicine Qatar, Doha, Qatar
- Computer and Systems Engineering, Alexandria University, Alexandria, Egypt
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, 20892-5635, USA
| | - Saima Afaq
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
| | - Carlos Alberto Aguilar-Salinas
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico, 14080, México
- Unidad de Investigacion de Enfermades Metabolicas, Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, N.L., 64710, México
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Fukuoka, 812-8582, Japan
| | - Matthew L Albert
- Immunobiology of Dendritic Cells, Institut Pasteur, Paris, 75015, France
- Inserm U1223, Paris, 75015, France
- Centre for Translational Research, Institut Pasteur, Paris, 75015, France
- Department of Cancer Immunology, Genentech Inc, San Francisco, California, 94080, USA
| | - Matthew A Allison
- Division of Preventive Medicine, Department of Family Medicine and Public Health, UC San Diego School of Medicine, La Jolla, California, 92093, USA
| | - Maris Alver
- Estonian Genome Center, University of Tartu, University of Tartu, Tartu, 51010, Estonia
| | - Tin Aung
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, 169856, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore, 169857, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore, 119228, SG, Singapore
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, 19839-63113, Iran
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, 20892-5635, USA
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Eric Boerwinkle
- Health Science Center at Houston, UTHealth School of Public Health, University of Texas, Houston, TX, 77030, USA
| | - Judith B Borja
- USC-Office of Population Studies Foundation, Inc., Department of Nutrition and Dietetics, Talamban, University of San Carlos, Cebu City, 6000, Cebu, Philippines
| | - Gert J de Borst
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Center Utrecht, University of Utrecht, Utrecht, Utrecht, 3584 CX, Netherlands
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Ichan School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Digital Health Center, Hasso Plattner Institute, Universität Potsdam, Potsdam, 14482, Germany
| | - Linda Broer
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, Scotland
| | - Stephen Chanock
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Miao-Li Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, 169856, Singapore
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, 20892-5635, USA
| | - Yii-Der I Chen
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, 90502, USA
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Yen-Feng Chiu
- Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan, Taiwan
| | - Massimiliano Cocca
- Institute for Maternal and Child Health - IRCCS Burlo Garofolo, Trieste, 34137, Italy
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, 20892, USA
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS Burlo Garofolo, Trieste, 34137, Italy
| | - Janie Corley
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Giovanni Cugliari
- Italian Institute for Genomic Medicine (IIGM) and Dept. Medical Sciences, University of Turin, Italy, Turin, 10126, Italy
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore, 117549, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, SG, Singapore
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, 02115, USA
| | - Anna Damulina
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, 8036, Austria
| | - Maryam S Daneshpour
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, 19839-63113, Iran
| | - Felix R Day
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Graciela E Delgado
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany
| | - Klodian Dhana
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, 02115, USA
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - Alexander S F Doney
- MEMO Research, Molecular and Clinical Medicine, University of Dundee, Dundee, DD19SY, UK
| | - Marcus Dörr
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, 17475, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, 17475, Germany
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, 20892-5635, USA
| | - Nduna Dzimiri
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, KSA, 12713, Saudi Arabia
| | - S Sunna Ebenesersdóttir
- deCODE genetics/Amgen Inc., Reykjavik 101, Iceland
- Department of Anthropology, University of Iceland, Reykjavik, 101, Iceland
| | - Joshua Elliott
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
- National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare NHS Trust and Imperial College London, London, UK
- UK Dementia Research Institute (UK DRI) at Imperial College London, London, UK
- Health Data Research UK - London, London, England
| | - Ralf Ewert
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Janine F Felix
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
- The Generation R Study Group, Erasmus University Medical Center, Rotterdam, 3015 CN, The Netherlands
- Department of Pediatrics, Erasmus University Medical Center, Rotterdam, 3015CN, The Netherlands
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, University of Tartu, Tartu, 51010, Estonia
| | - Barry I Freedman
- Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, 27101, US
| | - Giorgia Girotto
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
- Medical Genetics, Institute for Maternal and Child Health - IRCCS Burlo Garofolo, Trieste, Italy
| | - Anuj Goel
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DU, UK
| | - Martin Gögele
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, 39100, Italy
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, 90048, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27514, USA
| | | | - Francine Grodstein
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Simonetta Guarrera
- Italian Institute for Genomic Medicine (IIGM) and Dept. Medical Sciences, University of Turin, Italy, Turin, 10126, Italy
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik 101, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Kamran Guity
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, 19839-63113, Iran
| | | | - Yu Guo
- Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Saskia P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, 90089, USA
| | - Avner Halevy
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore City, Maryland, 21224, USA
| | - Mehdi Hedayati
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, 19839-63113, Iran
| | - David A van Heel
- Blizard Institute, Queen Mary University of London, London, E1 2AT, UK
| | - Makoto Hirata
- Laboratory of Genome Technology, Institute of Medical Science, The University of Tokyo, Tokyo, 108-8639, Japan
| | - Imo Höfer
- Laboratory of Clinical Chemistry and Hematology, Division Laboratories and Pharmacy, University Medical Center Utrecht, University of Utrecht, Utrecht, Utrecht, 3584 CX, Netherlands
| | - Chao Agnes Hsiung
- Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan, Taiwan
| | - Jinyan Huang
- Shanghai Institute of Hematology, State Key Laboratory Of Medical Genomics, Rui-jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 200025, China
| | - Yi-Jen Hung
- Division of Endocrine and Metabolism, Tri-Service General Hospital Songshan branch, Taipei, Taiwan, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan, Taiwan
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - Anuradha Jagadeesan
- deCODE genetics/Amgen Inc., Reykjavik 101, Iceland
- Department of Anthropology, University of Iceland, Reykjavik, 101, Iceland
| | - Pekka Jousilahti
- Unit of Public Health Promotion, National Institute for Health and Welfare, Helsinki, Finland
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8507, Japan
| | - Masahiro Kanai
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Osaka, 565-0871, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Nicola D Kerrison
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Thorsten Kessler
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, 80636, Germany
| | - Kay-Tee Khaw
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB2 0SR, UK
| | - Chiea Chuen Khor
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, 169856, Singapore
- Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore, 138672, Singapore
| | - Dominique P V de Kleijn
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Center Utrecht, University of Utrecht, Utrecht, Utrecht, 3584 CX, Netherlands
| | - Woon-Puay Koh
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore, 117549, Singapore
- Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore, 169857
| | - Ivana Kolcic
- Centre for Global Health, Faculty of Medicine, University of Split, Split, Croatia
| | - Peter Kraft
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, 02115, USA
| | - Bernhard K Krämer
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany
| | - Zoltán Kutalik
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Kuopio University Hospital, Kuopio, Finland
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore City, Maryland, 21224, USA
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, BS8 2BN, UK
- Bristol NIHR Biomedical Research Centre, Bristol, BS8 2BN, UK
- Population Health Science, Bristol Medical School, Bristol, BS8 2BY, UK
| | - I-Te Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan, Taipei, 112, Taiwan
- School of Medicine, Chung Shan Medical University, Taichung, Taiwan, Taichung City, 402, Taiwan
| | - Wen-Jane Lee
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan, Taiwan
| | - Markus M Lerch
- Department of Internal Medicine A, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Liming Li
- Department of Epidemiology and Biostatistics, Peking University Health Science Centre, Peking University, Beijing, 100191, China
| | - Jianjun Liu
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, SG, Singapore
- Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore, 138672, Singapore
| | - Marie Loh
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research, Singapore (A*STAR), Singapore, 138648, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore, 117596, Singapore
| | - Stephanie J London
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, Durham, NC, 27709, USA
| | - Stephanie Loomis
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Ichan School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, University of Tartu, Tartu, 51010, Estonia
| | - Ani W Manichaikul
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, 22908, USA
| | - Paolo Manunta
- Genomics of Renal Diseases and Hypertension Unit, IRCCS San Raffaele Scientific Institute, Università Vita Salute San Raffaele, Milano, 20132, Italy
| | - Gísli Másson
- deCODE genetics/Amgen Inc., Reykjavik 101, Iceland
| | - Nana Matoba
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
| | - Xue W Mei
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Christa Meisinger
- Helmholtz Zentrum München, Independent Research Group Clinical Epidemiology, Neuherberg, 85764, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum Muenchen, Neuherberg, 85764, Germany
- Institute of Human Genetics, Technical University of Munich, Munich, 81675, Germany
- DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, 80802, Germany
| | - Massimo Mezzavilla
- Medical Genetics, Institute for Maternal and Child Health - IRCCS Burlo Garofolo, Trieste, Italy
| | - Lili Milani
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, 51010, Estonia
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
| | - Amy Moore
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Pierre-Emmanuel Morange
- Laboratory of Haematology, La Timone Hospital, Marseille, France
- INSERM UMR_S 1263, Center for CardioVascular and Nutrition research (C2VN), Aix-Marseille University, Marseille, France
| | | | - Trevor A Mori
- Medical School, The University of Western Australia, Perth, Western Australia/Australia, 6009, Australia
| | - Alanna C Morrison
- The University of Texas Health Science Center at Houston, School of Public Health, Department of Epidemiology, Human Genetics and Environmental Sciences, Houston, Texas, 77030, USA
| | - Taulant Muka
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
- Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland
| | - Yoshinori Murakami
- Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, Tokyo, 108-8639, Japan
| | - Alison D Murray
- The Institute of Medical Sciences, Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, AB25 2ZD, UK
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, 2333 ZA, The Netherlands
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, 22908, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, Bethesda, MD, 20892, USA
- Data Tecnica International LLC, Glen Echo, MD, 20812, USA
| | - Matthias Nauck
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, 17475, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Matt J Neville
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Headington, Oxford, OX3 7LJ, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Ken K Ong
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Department of Paediatrics, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Mexico, 14610, México
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | | | - James S Pankow
- Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 55454, USA
| | - Cristian Pattaro
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, 39100, Italy
| | - Alison Pattie
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Ozren Polasek
- Centre for Global Health, Faculty of Medicine, University of Split, Split, Croatia
- Gen-info Ltd, Zagreb, Croatia, Zagreb, Select a Province, 10000, Croatia
| | - Neil Poulter
- International Centre for Circulatory Health, Imperial College London, London, W2 1PG, UK
- Imperial Clinical Trials Unit, Imperial College London, London, London, W12 7TA, UK
| | - Peter P Pramstaller
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, 39100, Italy
| | - Lluis Quintana-Murci
- Human Evolutionary Genetics Unit, Institut Pasteur, Paris, 75015, France
- Centre National de la Recherche Scientifique (CNRS) UMR2000, Paris, 75015, France
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, 75015, France
| | - Katri Räikkönen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, University of Helsinki, Helsinki, 00014, Finland
| | - Sarju Ralhan
- Hero Heart Institute and Dyanand Medical College and Hospital, Ludhiana, Punjab, India
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Wouter van Rheenen
- Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht University, Utrecht, 3584 CX, The Netherlands
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, 22908, USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Cornelius A Rietveld
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, 3062 PA, The Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus University Rotterdam, Rotterdam, 3062 PA, The Netherlands
| | - Antonietta Robino
- Institute for Maternal and Child Health - IRCCS Burlo Garofolo, Trieste, 34137, Italy
| | - Frank J A van Rooij
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics A. Buzzati-Traverso - CNR, Naples, 80131, Italy
- IRCCS Neuromed, Pozzilli (IS), 86077, Italy
| | - Yasaman Saba
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Division of Molecular Biology and Biochemistry, Medical University of Graz, 8010, Graz, Austria
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, 169856, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore, 169857, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore, 119228, SG, Singapore
| | - Maria Sabater-Lleal
- Cardiovascular Medicine Unit, Department of Medicine Solna, Centre for Molecular Medicine, Karolinska Institutet, Stockholm, 171 76, Sweden
- Unit of Genomics of Complex Diseases, Institut de Recerca Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain
| | | | - Veikko Salomaa
- Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, FI-00271, Finland
| | - Kevin Sandow
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, 90502, USA
| | - Helena Schmidt
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Division of Molecular Biology and Biochemistry, Medical University of Graz, 8010, Graz, Austria
| | - Laura J Scott
- Department of Biostatistics, and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, 48109, USA
| | - William R Scott
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
| | - Bahareh Sedaghati-Khayat
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, 19839-63113, Iran
| | - Bengt Sennblad
- Cardiovascular Medicine Unit, Department of Medicine Solna, Centre for Molecular Medicine, Karolinska Institutet, Stockholm, 171 76, Sweden
- Dept of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, SE-752 37, Uppsala, Sweden
| | - Jessica van Setten
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, Utrecht, 3485 CX, Netherlands
| | - Peter J Sever
- International Centre for Circulatory Health, Imperial College London, London, W2 1PG, UK
| | - Wayne H-H Sheu
- School of Medicine, National Defense Medical Center, Taipei, Taiwan, Taiwan
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan, Taiwan
- Institute of Medical Technology, National Chung-Hsing University, Taichung, Taiwan, Taiwan
| | - Yuan Shi
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, 169856, Singapore
| | - Smeeta Shrestha
- Genomic Research on Complex diseases (GRC Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, 500007, India
- School of Basic and Applied Sciences, Dayananda Sagar University, Bangalore, Karnataka, 560078, India
| | - Sharvari Rahul Shukla
- Diabetes Unit, KEM Hospital and Research Centre, Pune, Maharashtra, 411101, India
- Symbiosis Statistical Institute, Symbiosis International University, Pune, Maharashtra, 411007, India
| | | | - Timo Tonis Sikka
- Estonian Genome Center, University of Tartu, University of Tartu, Tartu, 51010, Estonia
| | | | - Blair H Smith
- Division of Population Health Sciences, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK
| | - Alena Stančáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Alice Stanton
- RCSI Molecular & Cellular Therapeutics (MCT), Royal College of Surgeons in Ireland, RCSI Education & Research Centre, Beaumont Hospital, Dublin 9, Ireland
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, EH8 9JZ, Scotland
| | | | - Leon Straker
- School of Physiotherapy and Exercise Science, Faculty of Health Sciences, Curtin University, Perth, Western Australia/Australia, 6102, Australia
| | | | | | - Morris A Swertz
- Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands, Groningen, Groningen, 9700 RB, The Netherlands
| | - Adele M Taylor
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Kent D Taylor
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, 90502, USA
| | - Natalie Terzikhan
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, 9000, Belgium
| | - Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, 169856, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore, 169857, Singapore
| | | | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik 101, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Annika Tillander
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177, Sweden
| | - Russell P Tracy
- Department of Pathology, University of Vermont, Colchester, VT, 05446, USA
| | - Teresa Tusié-Luna
- Departamento de Medicina Genómica y Toxicología Ambiental, Instituto de Investigaciones Biomédicas, UNAM, Mexico, 04510, México
- Unidad De Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico, 14080, México
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, 45110, Greece
| | - Simona Vaccargiu
- Institute of Genetic and Biomedical Research - Support Unity, National Research Council of Italy, Rome, Italy
| | - Jagadish Vangipurapu
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Jan H Veldink
- Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht University, Utrecht, 3584 CX, The Netherlands
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, Scotland
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, 17475, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, 17475, Germany
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, FI-00014, Finland
| | - Salma M Wakil
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, KSA, 12713, Saudi Arabia
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Gurpreet S Wander
- Department of Cardiology, Hero DMC Heart Institute, Dayanand Medical College & Hospital, Ludhiana, Punjab, 141001, India
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Science Key Lab, Beijing, China, 100005, China
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Sarah Wild
- Centre for Population Health Sciences, Usher Institute of Population Health and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, Scotland
| | | | - Jian-Min Yuan
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Lingyao Zeng
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, 80636, Germany
| | - Liang Zhang
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, 169856, Singapore
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, 20892-5635, USA
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, Utrecht, 3584 CX, Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, WC1E 6DD, UK
- Durrer Center for Cardiovascular Research, Netherlands Heart Institute, Utrecht, Netherlands
- Farr Institute of Health Informatics Research and Institute of Health Informatics, University College London, London, UK
| | - Stephan J L Bakker
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, 9713GZ, The Netherlands
| | - Diane M Becker
- Department of Medicine, GeneSTAR Research Program, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Leonard H van den Berg
- Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht University, Utrecht, 3584 CX, The Netherlands
| | - Sonja I Berndt
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Dwaipayan Bharadwaj
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Murielle Bochud
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Mike Boehnke
- Department of Biostatistics, and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, 48109, USA
| | - Claude Bouchard
- Pennington Biomedical Research Center, Baton Rouge, Louisiane, 70808, USA
| | - Jonathan P Bradfield
- Center for Applied Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Quantinuum Research LLC, San Diego, CA, 92101, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA
| | - Archie Campbell
- Centre for Genomic & Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Shai Carmi
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Mark J Caulfield
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - David Cesarini
- Center for Experimental Social Science, Department of Economics, New York University, New York, New York, 10012, USA
- Research Institute for Industrial Economics (IFN), Stockholm, 102 15, Sweden
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, Middlesex, Middlesex, UB1 3HW, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
- Imperial College Healthcare NHS Trust, London, London, W12 0HS, UK
| | - Giriraj Ratan Chandak
- Genomic Research on Complex diseases (GRC Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, 500007, India
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, 169856, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore, 169857, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore, 119228, SG, Singapore
| | - Marina Ciullo
- Institute of Genetics and Biophysics A. Buzzati-Traverso - CNR, Naples, 80131, Italy
- IRCCS Neuromed, Pozzilli (IS), 86077, Italy
| | - Marilyn Cornelis
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Daniele Cusi
- Department of Health Sciences, University of Milano, Milano, 20139, Italy
- Institute of Biomedical Technologies Milano, National Research Council of Italy (CNR), Segrate (Milano), 20090, Italy
- Bio4Dreams Scientific Unit, Bio4Dreams SRL, Bio4Dreams - business nursery for life sciences, Milano, 20121, Italy
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, BS8 2BN, UK
- Population Health Science, Bristol Medical School, Bristol, BS8 2BY, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Rajkumar Dorajoo
- Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore, 138672, Singapore
| | - Cornelia M van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, 24105, Kiel, Germany
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Lübeck, 23562, Germany
| | - Johan G Eriksson
- Department of General Practice and Primary health Care, University of Helsinki, Tukholmankatu 8 B, Helsinki, 00014, Finland
- National Institute for Health and Welfare, Helsinki, Finland
- Unit of General Practice, Helsinki University Central Hospital, Helsinki, Finland
- Folkhälsan Research Centre, Helsinki, Finland
- Vasa Central Hospital, Vaasa, Finland
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, 45110, Greece
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore City, Maryland, 21224, USA
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48014, USA
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, DK-2300, Denmark
| | - Mary Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, Saint Louis, MO, 63110-1093, USA
| | | | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, 24105, Kiel, Germany
| | - Yechiel Friedlander
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Paolo Gasparini
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
- Medical Genetics, Institute for Maternal and Child Health - IRCCS Burlo Garofolo, Trieste, Italy
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Clicerio Gonzalez
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Cuernavaca, 01120, México
| | | | - Struan F A Grant
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Center for Applied Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Lyn R Griffiths
- Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
| | - Leif Groop
- Finnish Institute for Molecular Medicine, University of Helsinki, Helsinki, Finland
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Lund University, Skåne University Hospital, Malmö, 20502, Sweden
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, 201, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 75108, Uppsala, Sweden
| | - Hakon Hakonarson
- Center for Applied Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Anders Hamsten
- Cardiovascular Medicine Unit, Department of Medicine Solna, Centre for Molecular Medicine, Stockholm, 171 76, Sweden
| | - Pim van der Harst
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Ther Netherlands, Groningen, 9713 GZ, the Netherlands
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Khoo Teck Puat - National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Andrew A Hicks
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, 39100, Italy
| | - Hagit Hochner
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Heikki Huikuri
- Research Unit of Internal Medicine, Medical Research Center Oulu, University of Oulu and Oulu University Hospital, Oulu, 90014, Finland
| | - Steven C Hunt
- Department of Genetic Medicine, Weill Cornell Medicine Qatar, Doha, Qatar
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, 84108, USA
| | - Vincent W V Jaddoe
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
- The Generation R Study Group, Erasmus University Medical Center, Rotterdam, 3015 CN, The Netherlands
- Department of Pediatrics, Erasmus University Medical Center, Rotterdam, 3015CN, The Netherlands
| | - Philip L De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 650 West 168th street, PH19-311, Newyork, NY, 10032, USA
- Cell Circuits Program, Broad Institute, Cambridge, MA, 02142, USA
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm, SE-113 83, Sweden
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 75108, Uppsala, Sweden
| | - Jost B Jonas
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Science Key Lab, Beijing, China, 100005, China
- Department of Ophthalmology, Medical Faculty Mannheim of the Ruprecht-Karls-University of Heidelberg, Mannheim, 698167, Germany
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
| | - Juhani Junttila
- Research Unit of Internal Medicine, Medical Research Center Oulu, University of Oulu and Oulu University Hospital, Oulu, 90014, Finland
| | - Jaakko Kaprio
- Finnish Institute for Molecular Medicine, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, FI-00014, Finland
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Headington, Oxford, OX3 7LJ, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Meena Kumari
- Institute for Social and Economic Research, University of Essex, Colchester, CO4 3SQ, UK
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Kuopio University Hospital, Kuopio, Finland
| | - Sander W van der Laan
- Laboratory of Clinical Chemistry and Hematology, Division Laboratories and Pharmacy, University Medical Center Utrecht, University of Utrecht, Utrecht, 3584 CX, Netherlands
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, University of Helsinki, Helsinki, 00014, Finland
- Helsinki Collegium for Advanced Studies, University of Helsinki, University of Helsinki, Helsinki, 00014, Finland
| | - Matthias Laudes
- University Hospital Schleswig-Holstein (UKSH), Campus Kiel, Kiel, 24105, Germany
| | - Rodney A Lea
- Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
| | - Wolfgang Lieb
- Institute of Epidemiology and PopGen Biobank, University of Kiel, Kiel, Schleswig Holstein, 24105, Germany
| | - Thomas Lumley
- Department of Statistics, University of Auckland, Auckland, New Zealand
| | | | - Winfried März
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
- Synlab Academy, Synlab Holding Deutschland GmbH, Mannheim, Germany
| | - Giuseppe Matullo
- Italian Institute for Genomic Medicine (IIGM) and Dept. Medical Sciences, University of Turin, Italy, Turin, 10126, Italy
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Headington, Oxford, OX3 7LJ, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Sarah E Medland
- QIMR Berghofer Institute of Medical Research, Brisbane, Australia
| | - Tony R Merriman
- Department of Biochemistry, University of Otago, Dunedin, 9054, New Zealand
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, University of Tartu, Tartu, 51010, Estonia
| | - Brian F Meyer
- Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh, 11211, Saudi Arabia
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Grant W Montgomery
- QIMR Berghofer Institute of Medical Research, Brisbane, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Dennis Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, 2333 ZA, The Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, 2333 ZA, The Netherlands
| | - Patricia B Munroe
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Dale R Nyholt
- QIMR Berghofer Institute of Medical Research, Brisbane, Australia
- School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD, 4059, Australia
| | - Jeffery R O'connell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
| | - Carole Ober
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Albertine J Oldehinkel
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Walter Palmas
- Department of Medicine, Columbia University Medical Center, New York, New York, USA
| | - Colin Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, The School of Medicine, University of Dundee, Dundee, DD1 9SY, UK
| | - Gerard G Pasterkamp
- Laboratory of Clinical Chemistry and Hematology, Division Laboratories and Pharmacy, University Medical Center Utrecht, University of Utrecht, Utrecht, Utrecht, 3584 CX, Netherlands
| | - Etienne Patin
- Human Evolutionary Genetics Unit, Institut Pasteur, Paris, 75015, France
- Centre National de la Recherche Scientifique (CNRS) UMR2000, Paris, 75015, France
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, 75015, France
| | - Craig E Pennell
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, New South Wales, Australia
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia/Australia, 6009, Australia
| | - Louis Perusse
- Department of kinesiology, Laval University, Quebec, QC, G1V 0A6, Canada
- Institute of Nutrition and Functional Foods, Laval University, Quebec, QC, G1V 0A6, Canada
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Mario Pirastu
- Institute of Genetic and Biomedical Research - Support Unity, National Research Council of Italy, Sassari, 07100, Italy
| | - Tinca J C Polderman
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Genomic & Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
- Department of Clinical Genetics, Amsterdam Neuroscience, VU Medical Centre, Amsterdam, 1081HV, The Netherlands
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Epidemiology, Medicine and Health Services, University of Washington, Seattle, WA, 98101, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, 98101, USA
| | - John D Rioux
- Montreal Heart Institute, Montreal, QC, Canada
- Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, Quebec, H3T 1J4, Canada
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
- The Generation R Study Group, Erasmus University Medical Center, Rotterdam, 3015 CN, The Netherlands
| | - Charles Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, 20892-5635, USA
| | - Jerome I Rotter
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, 90502, USA
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, Scotland
| | - Hester M Den Ruijter
- Laboratory of Experimental Cardiology, Division Heart & Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, Utrecht, 3584 CX, Netherlands
| | - Dharambir K Sanghera
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
- Oklahoma Center for Neuroscience, Oklahoma City, OK, 73104, USA
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Reinhold Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, 8036, Austria
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute of Nutritional Sciences, University of Potsdam, Nuthetal, Germany
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, 80636, Germany
- Deutsches Zentrum für Herz- und Kreislauferkrankungen (DZHK), Munich Heart Alliance, Munich, 80636, Germany
| | - Robert A Scott
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Alan R Shuldiner
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Inc, Tarrytown, NY, 10591-6607, USA
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore, 117549, Singapore
| | - Neil Small
- Faculty of Health Studies, University of Bradford, Bradford, West Yorkshire, BD7 1DP, UK
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48014, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, 98101, USA
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore, 117549, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, SG, Singapore
- Duke-NUS Medical School, National University of Singapore, Singapore, Singapore, 169857, SG, Singapore
| | - Alexander Teumer
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, 17475, Germany
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, BS8 2BN, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2PR, UK
- Avon Longitudinal Study of Parents and Children (ALSPAC), University of Bristol, Bristol, BS8 2PR, UK
| | | | | | - Tiinamaija Tuomi
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Endocrinology, Abdominal Centre, University of Helsinki, Helsinki University Hospital, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- Research Program of Diabetes and Endocrinology, University of Helsinki, Helsinki, Finland
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, 1011, Switzerland
| | - Carol A Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, New South Wales, Australia
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia/Australia, 6009, Australia
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48014, USA
| | - John B Whitfield
- QIMR Berghofer Institute of Medical Research, Brisbane, Australia
| | - Cisca Wijmenga
- Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands, Groningen, Groningen, 9700 RB, The Netherlands
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, 169856, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore, 169857, Singapore
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Trust, Bradford, BD96RJ, UK
| | - Jingyun Yang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Babette S Zemel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Division of Gastroenterology, Hepatology and Nutrition, Children's Hospital of Philadelphia, Philadelphia, PA, 19146, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore City, Maryland, 21224, USA
| | - Markus Perola
- Unit of Genomics and Biomarkers, National Institute for Health and Welfare, Helsinki, 00271, Finland
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177, Sweden
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
- The Generation R Study Group, Erasmus University Medical Center, Rotterdam, 3015 CN, The Netherlands
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, Middlesex, Middlesex, UB1 3HW, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
- Imperial College Healthcare NHS Trust, London, London, W12 0HS, UK
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Ichan School of Medicine at Mount Sinai, New York, NY, 10029, USA
- The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Lude Franke
- Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands, Groningen, Groningen, 9700 RB, The Netherlands
| | - Chris S Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, Scotland
- Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, Scotland
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, Scotland
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - John R B Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Tōnu Esko
- Estonian Genome Center, University of Tartu, University of Tartu, Tartu, 51010, Estonia
- Program in Medical and Population Genetics, Broad Institute, Broad Institute, Cambridge, MASSACHUSETTS, 02142, USA
| | - Agnar Helgason
- deCODE genetics/Amgen Inc., Reykjavik 101, Iceland
- Department of Anthropology, University of Iceland, Reykjavik, 101, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik 101, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, Scotland
| | - Michiaki Kubo
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, Scotland.
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, Scotland.
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49
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Abstract
In order to design efficient interventions aimed to improve public health, policy makers need to be provided with reliable information of the health burden of different risk factors. For this purpose, we are interested in the proportion of cases that could be prevented had some harmful exposure been eliminated from the population, i.e. the attributable fraction. The attributable fraction is a causal measure; thus, to estimate the attributable fraction from observational data, we have to make appropriate adjustment for confounding. However, some confounders may be unobserved, or even unknown to the investigator. A possible solution to this problem is to use instrumental variable analysis. In this work, we present how the attributable fraction can be estimated with instrumental variable methods based on the two-stage estimator or the G-estimator. One situation when the problem of unmeasuredconfounding may be particularly severe is when assessing the effect of low educational qualifications on coronary heart disease. By using Mendelian randomization, a special case of instrumental variable analysis, it has been claimed that low educational qualifications is a causal risk factor for coronary heart disease. We use Mendelian randomization to estimate the causal risk ratio and causal odds ratio of low educational qualifications as a risk factor for coronary heart disease with data from the UK Biobank. We compare the two-stage and G-estimator as well as the attributable fraction based on the two estimators. The plausibility of drawing causal conclusion in this analysis is thoroughly discussed and alternative genetic instrumental variables are tested.
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Affiliation(s)
- Elisabeth Dahlqwist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Arvid Sjölander
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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50
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Choobdar S, Ahsen ME, Crawford J, Tomasoni M, Fang T, Lamparter D, Lin J, Hescott B, Hu X, Mercer J, Natoli T, Narayan R, Subramanian A, Zhang JD, Stolovitzky G, Kutalik Z, Lage K, Slonim DK, Saez-Rodriguez J, Cowen LJ, Bergmann S, Marbach D. Assessment of network module identification across complex diseases. Nat Methods 2019; 16:843-852. [PMID: 31471613 PMCID: PMC6719725 DOI: 10.1038/s41592-019-0509-5] [Citation(s) in RCA: 140] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 07/10/2019] [Indexed: 12/11/2022]
Abstract
Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different types of network remains poorly understood. We launched the 'Disease Module Identification DREAM Challenge', an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets. This community challenge establishes biologically interpretable benchmarks, tools and guidelines for molecular network analysis to study human disease biology.
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Affiliation(s)
- Sarvenaz Choobdar
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Mehmet E Ahsen
- Icahn Institute for Genomics and Multiscale Biology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jake Crawford
- Department of Computer Science, Tufts University, Medford, MA, USA
| | - Mattia Tomasoni
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Tao Fang
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - David Lamparter
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Verge Genomics, San Francisco, CA, USA
| | - Junyuan Lin
- Department of Mathematics, Tufts University, Medford, MA, USA
| | - Benjamin Hescott
- College of Computer and Information Science, Northeastern University, Boston, MA, USA
| | - Xiaozhe Hu
- Department of Mathematics, Tufts University, Medford, MA, USA
| | - Johnathan Mercer
- Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Stanley Center at the Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ted Natoli
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Rajiv Narayan
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Jitao D Zhang
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Gustavo Stolovitzky
- Icahn Institute for Genomics and Multiscale Biology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Institute of Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Kasper Lage
- Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Stanley Center at the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Biological Psychiatry, Mental Health Center Sct. Hans, University of Copenhagen, Roskilde, Denmark
| | - Donna K Slonim
- Department of Computer Science, Tufts University, Medford, MA, USA
- Department of Immunology, Tufts University School of Medicine, Boston, MA, USA
| | - Julio Saez-Rodriguez
- Institute for Computational Biomedicine, Faculty of Medicine, Heidelberg University, Bioquant, Heidelberg, Germany
- RWTH Aachen University, Faculty of Medicine, Joint Research Center for Computational Biomedicine, Aachen, Germany
| | - Lenore J Cowen
- Department of Computer Science, Tufts University, Medford, MA, USA
- Department of Mathematics, Tufts University, Medford, MA, USA
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa.
| | - Daniel Marbach
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland.
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