151
|
Vilne B, Schunkert H. Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach. Front Cardiovasc Med 2018; 5:89. [PMID: 30065929 PMCID: PMC6056735 DOI: 10.3389/fcvm.2018.00089] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2018] [Accepted: 06/22/2018] [Indexed: 12/26/2022] Open
Abstract
Coronary artery disease (CAD) and myocardial infarction (MI) remain among the leading causes of mortality worldwide, urgently demanding a better understanding of disease etiology, and more efficient therapeutic strategies. Genetic predisposition as well as the environment and lifestyle are thought to contribute to disease risk. It is likely that non-linear and complex interactions occur between these multiple factors, involving simultaneous pathological changes in diverse cell types, tissues, and organs, at multiple molecular levels. Recent technological advances have exponentially expanded the breadth of available -omics data, from genome, epigenome, transcriptome, proteome, metabolome to even the microbiome. Integration of multiple layers of information across several -omics domains, i.e., the so-called multi-omics approach, currently holds the promise as a path toward precision medicine. Indeed, a more meaningful interpretation of genotype-phenotype relationships and the development of successful therapeutics tailored to individual patients are urgently needed. In this review, we will summarize recent findings and applications of integrative multi-omics in elucidating the etiology of CAD/MI; with a special focus on established disease susceptibility loci sequentially identified in genome-wide association studies (GWAS) over the last 10 years. Moreover, in addition to the autosomal genome, we will also consider the genetic variation in our “second genome”—the mitochondrial genome. Finally, we will summarize the current challenges in the field and point to future research directions required in order to successfully and effectively apply these approaches for precision medicine.
Collapse
Affiliation(s)
- Baiba Vilne
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany.,Munich Heart Alliance, German Centre for Cardiovascular Research, Munich, Germany
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany.,Munich Heart Alliance, German Centre for Cardiovascular Research, Munich, Germany
| |
Collapse
|
152
|
Readhead B, Haure-Mirande JV, Funk CC, Richards MA, Shannon P, Haroutunian V, Sano M, Liang WS, Beckmann ND, Price ND, Reiman EM, Schadt EE, Ehrlich ME, Gandy S, Dudley JT. Multiscale Analysis of Independent Alzheimer's Cohorts Finds Disruption of Molecular, Genetic, and Clinical Networks by Human Herpesvirus. Neuron 2018; 99:64-82.e7. [PMID: 29937276 PMCID: PMC6551233 DOI: 10.1016/j.neuron.2018.05.023] [Citation(s) in RCA: 437] [Impact Index Per Article: 72.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Revised: 03/05/2018] [Accepted: 05/15/2018] [Indexed: 12/13/2022]
Abstract
Investigators have long suspected that pathogenic microbes might contribute to the onset and progression of Alzheimer's disease (AD) although definitive evidence has not been presented. Whether such findings represent a causal contribution, or reflect opportunistic passengers of neurodegeneration, is also difficult to resolve. We constructed multiscale networks of the late-onset AD-associated virome, integrating genomic, transcriptomic, proteomic, and histopathological data across four brain regions from human post-mortem tissue. We observed increased human herpesvirus 6A (HHV-6A) and human herpesvirus 7 (HHV-7) from subjects with AD compared with controls. These results were replicated in two additional, independent and geographically dispersed cohorts. We observed regulatory relationships linking viral abundance and modulators of APP metabolism, including induction of APBB2, APPBP2, BIN1, BACE1, CLU, PICALM, and PSEN1 by HHV-6A. This study elucidates networks linking molecular, clinical, and neuropathological features with viral activity and is consistent with viral activity constituting a general feature of AD.
Collapse
Affiliation(s)
- Ben Readhead
- Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Icahn Institute of Genomic Sciences and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; ASU-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe, AZ 85287-5001, USA
| | - Jean-Vianney Haure-Mirande
- Department of Neurology, Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Cory C Funk
- Institute for Systems Biology, Seattle, WA, 98109-5263, USA
| | | | - Paul Shannon
- Institute for Systems Biology, Seattle, WA, 98109-5263, USA
| | - Vahram Haroutunian
- Departments of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; James J. Peters VA Medical Center, 130 West Kingsbridge Road, New York, NY 10468, USA
| | - Mary Sano
- James J. Peters VA Medical Center, 130 West Kingsbridge Road, New York, NY 10468, USA; Department of Psychiatry, Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Winnie S Liang
- Arizona Alzheimer's Consortium, Phoenix, AZ 85014, USA; Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA
| | - Noam D Beckmann
- Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Icahn Institute of Genomic Sciences and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Nathan D Price
- Institute for Systems Biology, Seattle, WA, 98109-5263, USA
| | - Eric M Reiman
- Arizona Alzheimer's Consortium, Phoenix, AZ 85014, USA; Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA; Department of Psychiatry, University of Arizona, Phoenix, AZ 85721, USA; Banner Alzheimer's Institute, Phoenix, AZ 85006, USA
| | - Eric E Schadt
- Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Icahn Institute of Genomic Sciences and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Sema4, Stamford, CT 06902, USA
| | - Michelle E Ehrlich
- Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Icahn Institute of Genomic Sciences and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neurology, Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sam Gandy
- Department of Neurology, Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; James J. Peters VA Medical Center, 130 West Kingsbridge Road, New York, NY 10468, USA; Department of Psychiatry, Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for NFL Neurological Care, Department of Neurology, New York, NY 10029, USA
| | - Joel T Dudley
- Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Icahn Institute of Genomic Sciences and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; ASU-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe, AZ 85287-5001, USA.
| |
Collapse
|
153
|
CD90 Identifies Adventitial Mesenchymal Progenitor Cells in Adult Human Medium- and Large-Sized Arteries. Stem Cell Reports 2018; 11:242-257. [PMID: 30008326 PMCID: PMC6067150 DOI: 10.1016/j.stemcr.2018.06.001] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Revised: 06/01/2018] [Accepted: 06/03/2018] [Indexed: 12/15/2022] Open
Abstract
Mesenchymal stem cells (MSCs) reportedly exist in a vascular niche occupying the outer adventitial layer. However, these cells have not been well characterized in vivo in medium- and large-sized arteries in humans, and their potential pathological role is unknown. To address this, healthy and diseased arterial tissues were obtained as surplus surgical specimens and freshly processed. We identified that CD90 marks a rare adventitial population that co-expresses MSC markers including PDGFRα, CD44, CD73, and CD105. However, unlike CD90, these additional markers were widely expressed by other cells. Human adventitial CD90+ cells fulfilled standard MSC criteria, including plastic adherence, spindle morphology, passage ability, colony formation, and differentiation into adipocytes, osteoblasts, and chondrocytes. Phenotypic and transcriptomic profiling, as well as adoptive transfer experiments, revealed a potential role in vascular disease pathogenesis, with the transcriptomic disease signature of these cells being represented in an aortic regulatory gene network that is operative in atherosclerosis. We identify, in situ and in vivo, adventitial CD90+ MSCs in human arteries Human adventitial CD90+ cells fulfill all criteria for an MSC population Other markers, such as CD44 and PDGFRα, were non-specific for adventitial MSCs The CD90+ MSC transcriptomic signature suggests a major role in vascular disease
Collapse
|
154
|
Heinig M. Using Gene Expression to Annotate Cardiovascular GWAS Loci. Front Cardiovasc Med 2018; 5:59. [PMID: 29922679 PMCID: PMC5996083 DOI: 10.3389/fcvm.2018.00059] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Accepted: 05/15/2018] [Indexed: 01/27/2023] Open
Abstract
Genetic variants at hundreds of loci associated with cardiovascular phenotypes have been identified by genome wide association studies. Most of these variants are located in intronic or intergenic regions rendering the functional and mechanistic follow up difficult. These non-protein-coding regions harbor regulatory sequences. Thus the study of genetic variants associated with transcription—so called expression quantitative trait loci—has emerged as a promising approach to identify regulatory sequence variants. The genes and pathways they control constitute candidate causal drivers at cardiovascular risk loci. This review provides an overview of the expression quantitative trait loci resources available for cardiovascular genetics research and the most commonly used approaches for candidate gene identification.
Collapse
Affiliation(s)
- Matthias Heinig
- Institute of Computational Biology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany.,Department of Informatics, Technical University of Munich, Munich, Germany
| |
Collapse
|
155
|
Shu L, Blencowe M, Yang X. Translating GWAS Findings to Novel Therapeutic Targets for Coronary Artery Disease. Front Cardiovasc Med 2018; 5:56. [PMID: 29900175 PMCID: PMC5989327 DOI: 10.3389/fcvm.2018.00056] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 05/11/2018] [Indexed: 12/21/2022] Open
Abstract
The success of genome-wide association studies (GWAS) has significantly advanced our understanding of the etiology of coronary artery disease (CAD) and opens new opportunities to reinvigorate the stalling CAD drug development. However, there exists remarkable disconnection between the CAD GWAS findings and commercialized drugs. While this could implicate major untapped translational and therapeutic potentials in CAD GWAS, it also brings forward extensive technical challenges. In this review we summarize the motivation to leverage GWAS for drug discovery, outline the critical bottlenecks in the field, and highlight several promising strategies such as functional genomics and network-based approaches to enhance the translational value of CAD GWAS findings in driving novel therapeutics
Collapse
Affiliation(s)
- Le Shu
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, United States.,Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, United States
| | - Montgomery Blencowe
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, United States.,Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, United States.,Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, United States.,Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, Los Angeles, CA, United States.,Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, United States
| |
Collapse
|
156
|
Barbeira AN, Dickinson SP, Bonazzola R, Zheng J, Wheeler HE, Torres JM, Torstenson ES, Shah KP, Garcia T, Edwards TL, Stahl EA, Huckins LM, Nicolae DL, Cox NJ, Im HK. Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics. Nat Commun 2018; 9:1825. [PMID: 29739930 PMCID: PMC5940825 DOI: 10.1038/s41467-018-03621-1] [Citation(s) in RCA: 606] [Impact Index Per Article: 101.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 12/27/2017] [Indexed: 12/25/2022] Open
Abstract
Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.
Collapse
Affiliation(s)
- Alvaro N Barbeira
- Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Scott P Dickinson
- Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Rodrigo Bonazzola
- Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Jiamao Zheng
- Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Heather E Wheeler
- Department of Biology, Loyola University Chicago, Chicago, IL, 60660, USA.,Department of Computer Science, Loyola University Chicago, Chicago, IL, 60660, USA
| | - Jason M Torres
- Committee on Molecular Metabolism and Nutrition, The University of Chicago, Chicago, IL, 60637, USA
| | - Eric S Torstenson
- Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Kaanan P Shah
- Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Tzintzuni Garcia
- Center for Research Informatics, The University of Chicago, Chicago, IL, 60615, USA
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Eli A Stahl
- Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, NYC, NY, 10029, USA.,Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, NYC, NY, 10029, USA
| | - Laura M Huckins
- Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, NYC, NY, 10029, USA.,Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, NYC, NY, 10029, USA
| | | | - Dan L Nicolae
- Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Nancy J Cox
- Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Hae Kyung Im
- Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA.
| |
Collapse
|
157
|
Seldin MM, Koplev S, Rajbhandari P, Vergnes L, Rosenberg GM, Meng Y, Pan C, Phuong TMN, Gharakhanian R, Che N, Mäkinen S, Shih DM, Civelek M, Parks BW, Kim ED, Norheim F, Chella Krishnan K, Hasin-Brumshtein Y, Mehrabian M, Laakso M, Drevon CA, Koistinen HA, Tontonoz P, Reue K, Cantor RM, Björkegren JLM, Lusis AJ. A Strategy for Discovery of Endocrine Interactions with Application to Whole-Body Metabolism. Cell Metab 2018; 27:1138-1155.e6. [PMID: 29719227 PMCID: PMC5935137 DOI: 10.1016/j.cmet.2018.03.015] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Revised: 12/14/2017] [Accepted: 03/24/2018] [Indexed: 12/16/2022]
Abstract
Inter-tissue communication via secreted proteins has been established as a vital mechanism for proper physiologic homeostasis. Here, we report a bioinformatics framework using a mouse reference population, the Hybrid Mouse Diversity Panel (HMDP), which integrates global multi-tissue expression data and publicly available resources to identify and functionally annotate novel circuits of tissue-tissue communication. We validate this method by showing that we can identify known as well as novel endocrine factors responsible for communication between tissues. We further show the utility of this approach by identification and mechanistic characterization of two new endocrine factors. Adipose-derived Lipocalin-5 is shown to enhance skeletal muscle mitochondrial function, and liver-secreted Notum promotes browning of white adipose tissue, also known as "beiging." We demonstrate the general applicability of the method by providing in vivo evidence for three additional novel molecules mediating tissue-tissue interactions.
Collapse
Affiliation(s)
- Marcus M Seldin
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Simon Koplev
- Department of Genetics and Genomic Sciences, The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Prashant Rajbhandari
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Laurent Vergnes
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Gregory M Rosenberg
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Yonghong Meng
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Calvin Pan
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Thuy M N Phuong
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Raffi Gharakhanian
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Nam Che
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Selina Mäkinen
- Department of Medicine, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland; Minerva Foundation Institute for Medical Research, Biomedicum 2U, Helsinki, Finland
| | - Diana M Shih
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Mete Civelek
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - Brian W Parks
- Department of Nutritional Sciences, University of Wisconsin, Madison, WI, USA
| | - Eric D Kim
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Frode Norheim
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
| | | | | | - Margarete Mehrabian
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Christian A Drevon
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Heikki A Koistinen
- Department of Medicine, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland; Minerva Foundation Institute for Medical Research, Biomedicum 2U, Helsinki, Finland
| | - Peter Tontonoz
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Karen Reue
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Rita M Cantor
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Aldons J Lusis
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA; Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, CA, USA.
| |
Collapse
|
158
|
Wirka RC, Pjanic M, Quertermous T. Advances in Transcriptomics: Investigating Cardiovascular Disease at Unprecedented Resolution. Circ Res 2018; 122:1200-1220. [PMID: 29700068 PMCID: PMC7274217 DOI: 10.1161/circresaha.117.310910] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Whole-genome transcriptional profiling has become a standard genomic approach to investigate biological processes. RNA sequencing (RNAseq) in particular has witnessed myriad applications in genetics and various biomedical fields. RNAseq involves a relatively simple experimental protocol of RNA extraction and cDNA library preparation and, because of decreasing next-generation sequencing cost and lower computational burden for data processing, has obtained a central role in the modern biology. The recent application of RNAseq methodology to single-cell transcriptional profiling has enabled the more precise characterization of cell lineage and cell state genetic profiles. The development of bioinformatic and statistical tools has provided for differential gene expression analysis, RNA isoform analysis, haplotype-specific analysis of gene expression (allele-specific expression), and analysis of expression quantitative trait loci. We give an overview of these and recent developments in RNAseq methodology with emphasis on quality control, read mapping, feature counting, differential gene expression, allele-specific expression and expression quantitative trait loci analysis, and fusion transcript detection. We describe utilization of RNAseq as a diagnostic tool in Mendelian diseases, complex phenotypes, and cancer and give an overview of long read RNAseq technology. Furthermore, we discuss in detail the recent revolution in single-cell transcriptomics that is reshaping modern biology.
Collapse
Affiliation(s)
| | | | - Thomas Quertermous
- Division of Cardiovascular Medicine, Stanford University, Stanford, CA 94305
| |
Collapse
|
159
|
Malik R, Chauhan G, Traylor M, Sargurupremraj M, Okada Y, Mishra A, Rutten-Jacobs L, Giese AK, van der Laan SW, Gretarsdottir S, Anderson CD, Chong M, Adams HHH, Ago T, Almgren P, Amouyel P, Ay H, Bartz TM, Benavente OR, Bevan S, Boncoraglio GB, Brown RD, Butterworth AS, Carrera C, Carty CL, Chasman DI, Chen WM, Cole JW, Correa A, Cotlarciuc I, Cruchaga C, Danesh J, de Bakker PIW, DeStefano AL, den Hoed M, Duan Q, Engelter ST, Falcone GJ, Gottesman RF, Grewal RP, Gudnason V, Gustafsson S, Haessler J, Harris TB, Hassan A, Havulinna AS, Heckbert SR, Holliday EG, Howard G, Hsu FC, Hyacinth HI, Ikram MA, ingelsson E, Irvin MR, Jian X, Jimenez-Conde J, Johnson JA, Jukema JW, Kanai M, Keene KL, Kissela BM, Kleindorfer DO, Kooperberg C, Kubo M, Lange LA, Langefeld CD, Langenberg C, Launer LJ, Lee JM, Lemmens R, Leys D, Lewis CM, Lin WY, Lindgren AG, Lorentzen E, Magnusson PK, Maguire J, Manichaikul A, McArdle PF, Meschia JF, Mitchell BD, Mosley TH, Nalls MA, Ninomiya T, O’Donnell MJ, Psaty BM, Pulit SL, Rannikmäe K, Reiner AP, Rexrode KM, Rice K, Rich SS, Ridker PM, Rost NS, Rothwell PM, Rotter JI, Rundek T, Sacco RL, Sakaue S, Sale MM, Salomaa V, Sapkota BR, Schmidt R, Schmidt CO, Schminke U, Sharma P, Slowik A, Sudlow CLM, Tanislav C, Tatlisumak T, Taylor KD, Thijs VNS, Thorleifsson G, Thorsteinsdottir U, Tiedt S, Trompet S, Tzourio C, van Duijn CM, Walters M, Wareham NJ, Wassertheil-Smoller S, Wilson JG, Wiggins KL, Yang Q, Yusuf S, Bis JC, Pastinen T, Ruusalepp A, Schadt EE, Koplev S, Björkegren JLM, Codoni V, Civelek M, Smith NL, Tregouet DA, Christophersen IE, Roselli C, Lubitz SA, Ellinor PT, Tai ES, Kooner JS, Kato N, He J, van der Harst P, Elliott P, Chambers JC, Takeuchi F, Johnson AD, Sanghera DK, Melander O, Jern C, Strbian D, Fernandez-Cadenas I, Longstreth WT, Rolfs A, Hata J, Woo D, Rosand J, Pare G, Hopewell JC, Saleheen D, Stefansson K, Worrall BB, Kittner SJ, Seshadri S, Fornage M, Markus HS, Howson JMM, Kamatani Y, Debette S, Dichgans M. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet 2018; 50:524-537. [PMID: 29531354 PMCID: PMC5968830 DOI: 10.1038/s41588-018-0058-3] [Citation(s) in RCA: 991] [Impact Index Per Article: 165.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Accepted: 01/08/2018] [Indexed: 02/02/2023]
Abstract
Stroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.
Collapse
Affiliation(s)
- Rainer Malik
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Ganesh Chauhan
- Centre for Brain Research, Indian Institute of Science, Bangalore, India,INSERM U1219 Bordeaux Population Health Research Center, University of Bordeaux, France
| | - Matthew Traylor
- Stroke Research Group, Division of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Muralidharan Sargurupremraj
- INSERM U1219 Bordeaux Population Health Research Center, University of Bordeaux, France,Department of Neurology, Institute for Neurodegenerative Disease, Bordeaux University Hospital, Bordeaux, France
| | - Yukinori Okada
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan,Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, Australia
| | - Aniket Mishra
- INSERM U1219 Bordeaux Population Health Research Center, University of Bordeaux, France,Department of Neurology, Institute for Neurodegenerative Disease, Bordeaux University Hospital, Bordeaux, France
| | - Loes Rutten-Jacobs
- Stroke Research Group, Division of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Anne-Katrin Giese
- Department of Neurology, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, MA, USA
| | - Sander W. van der Laan
- Laboratory of Experimental Cardiology, Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | | | - Christopher D. Anderson
- Center for Genomic Medicine, MGH, Boston, MA, USA,J. Philip Kistler Stroke Research Center, Department of Neurology, MGH, Boston, MA, USA,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Michael Chong
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - Hieab H. H. Adams
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands,Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Tetsuro Ago
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Peter Almgren
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Philippe Amouyel
- INSERM, Institut Pasteur de Lille, LabEx DISTALZ-UMR1167, Risk Factors and Molecular Determinants of Aging-Related Diseases, Université Lille, Lille, France,Centre Hospitalier Universite Lille, Epidemiology and Public Health Department, Lille, France
| | - Hakan Ay
- J. Philip Kistler Stroke Research Center, Department of Neurology, MGH, Boston, MA, USA,AA Martinos Center for Biomedical Imaging, Department of Radiology, MGH, Harvard Medical School, Boston, MA, USA
| | - Traci M. Bartz
- Cardiovascular Health Research Unit, Departments of Biostatistics and Medicine, University of Washington, Seattle, WA, USA
| | - Oscar R. Benavente
- Division of Neurology, Faculty of Medicine, Brain Research Center, University of British Columbia, Vancouver, British Columbia, Canada
| | - Steve Bevan
- School of Life Science, University of Lincoln, Lincoln, UK
| | - Giorgio B. Boncoraglio
- Department of Cerebrovascular Diseases, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy
| | - Robert D. Brown
- Department of Neurology, Mayo Clinic Rochester, Rochester, MN, USA
| | - Adam S. Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK,National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
| | - Caty Carrera
- Neurovascular Research Laboratory, Vall d’Hebron Institut of Research, Neurology and Medicine Departments-Universitat Autònoma de Barcelona, Vall d’Hebrón Hospital, Barcelona, Spain,Stroke Pharmacogenomics and Genetics, Fundacio Docència i Recerca MutuaTerrassa, Terrassa, Spain
| | - Cara L. Carty
- Children’s Research Institute, Children’s National Medical Center, Washington, DC, USA,Center for Translational Science, George Washington University, Washington, DC, USA
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Wei-Min Chen
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - John W. Cole
- Department of Neurology, University of Maryland School of Medicine and Baltimore VAMC, Baltimore, MD, USA
| | - Adolfo Correa
- Departments of Medicine, Pediatrics and Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Ioana Cotlarciuc
- Institute of Cardiovascular Research, Royal Holloway University of London, London, UK, and Ashford and St Peters Hospital, Surrey, UK
| | - Carlos Cruchaga
- Department of Psychiatry, Hope Center Program on Protein Aggregation and Neurodegeneration (HPAN), Washington University School of Medicine, St. Louis, MO, USA,Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - John Danesh
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK,NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK,Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK,British Heart Foundation, Cambridge Centre of Excellence, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Paul I. W. de Bakker
- Department of Medical Genetics, University Medical Center Utrecht, Utrecht, the Netherlands,Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Anita L. DeStefano
- Boston University School of Public Health, Boston, MA, USA,Framingham Heart Study, Framingham, MA, USA
| | - Marcel den Hoed
- Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Qing Duan
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Stefan T. Engelter
- Department of Neurology and Stroke Center, Basel University Hospital, Basel, Switzerland,Neurorehabilitation Unit, University of Basel and University Center for Medicine of Aging and Rehabilitation Basel, Felix Platter Hospital, Basel, Switzerland
| | - Guido J. Falcone
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Rebecca F. Gottesman
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Raji P. Grewal
- Neuroscience Institute, SF Medical Center, Trenton, NJ, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association Research Institute, Kopavogur, Iceland,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Stefan Gustafsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Tamara B. Harris
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Ahamad Hassan
- Department of Neurology, Leeds General Infirmary, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Aki S. Havulinna
- National Institute for Health and Welfare, Helsinki, Finland,FIMM-Institute for Molecular Medicine Finland, Helsinki, Finland
| | - Susan R. Heckbert
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Elizabeth G. Holliday
- Public Health Stream, Hunter Medical Research Institute, New Lambton, New South Wales, Australia,Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, Australia
| | - George Howard
- School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Fang-Chi Hsu
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Hyacinth I. Hyacinth
- Aflac Cancer and Blood Disorder Center, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Erik ingelsson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA,Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Marguerite R. Irvin
- Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Xueqiu Jian
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jordi Jimenez-Conde
- Neurovascular Research Group (NEUVAS), Neurology Department, Institut Hospital del Mar d’Investigació Mèdica, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Julie A. Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, College of Pharmacy, Gainesville, FL, USA,Division of Cardiovascular Medicine, College of Medicine, University of Florida, Gainesville, FL, USA
| | - J. Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Masahiro Kanai
- Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, Australia,Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA
| | - Keith L. Keene
- Department of Biology, East Carolina University, Greenville, NC, USA,Center for Health Disparities, East Carolina University, Greenville, NC, USA
| | - Brett M. Kissela
- University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | | | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Leslie A. Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Carl D. Langefeld
- Center for Public Health Genomics and Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Lenore J. Launer
- Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Jin-Moo Lee
- Department of Neurology, Radiology, and Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, USA
| | - Robin Lemmens
- Department of Neurosciences, Experimental Neurology, KU Leuven-University of Leuven, Leuven, Belgium,VIB Center for Brain & Disease Research, University Hospitals Leuven, Department of Neurology, Leuven, Belgium
| | - Didier Leys
- INSERM U 1171, CHU Lille, Universite Lille, Lille, France
| | - Cathryn M. Lewis
- Department of Medical and Molecular Genetics, King’s College London, London, UK,SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Wei-Yu Lin
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK,Northern Institute for Cancer Research, Newcastle University, Newcastle, UK
| | - Arne G. Lindgren
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden,Department of Neurology and Rehabilitation Medicine, Skåne University Hospital, Lund, Sweden
| | - Erik Lorentzen
- Bioinformatics Core Facility, University of Gothenburg, Gothenburg, Sweden
| | - Patrik K. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jane Maguire
- University of Technology Sydney, Faculty of Health, Ultimo, New South Wales, Australia
| | - Ani Manichaikul
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Patrick F. McArdle
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA,Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Thomas H. Mosley
- Division of Geriatrics, School of Medicine, University of Mississippi Medical Center, Jackson, MS, USA,Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Michael A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA,Data Tecnica International, Glen Echo, MD, USA
| | - Toshiharu Ninomiya
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Martin J. O’Donnell
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada,Clinical Research Facility, Department of Medicine, NUI Galway, Galway, Ireland
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA,Department of Epidemiology, University of Washington, Seattle, WA, USA,Department of Health Services, University of Washington, Seattle, WA, USA,Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Sara L. Pulit
- Department of Medical Genetics, University Medical Center Utrecht, Utrecht, the Netherlands,Brain Center Rudolf Magnus, Department of Neurology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Kristiina Rannikmäe
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Alexander P. Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA,Fred Hutchinson Cancer Research Center, University of Washington, Seattle, WA, USA
| | | | - Kenneth Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Natalia S. Rost
- Department of Neurology, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, MA, USA,J. Philip Kistler Stroke Research Center, Department of Neurology, MGH, Boston, MA, USA
| | - Peter M. Rothwell
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA,Division of Genomic Outcomes, Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Tatjana Rundek
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Ralph L. Sacco
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan,Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Michele M. Sale
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Bishwa R. Sapkota
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Carsten O. Schmidt
- Institute for Community Medicine, SHIP-KEF, University Medicine Greifswald, Greifswald, Germany
| | - Ulf Schminke
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Pankaj Sharma
- Institute of Cardiovascular Research, Royal Holloway University of London, London, UK, and Ashford and St Peters Hospital, Surrey, UK
| | - Agnieszka Slowik
- Department of Neurology, Jagiellonian University, Krakow, Poland
| | - Cathie L. M. Sudlow
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Turgut Tatlisumak
- Department of Clinical Neurosciences/Neurology, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden,Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Kent D. Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA,Division of Genomic Outcomes, Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Vincent N. S. Thijs
- Stroke Division, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Heidelberg, Victoria, Australia,Austin Health, Department of Neurology, Heidelberg, Victoria, Australia
| | | | | | - Steffen Tiedt
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Stella Trompet
- Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Christophe Tzourio
- INSERM U1219 Bordeaux Population Health Research Center, University of Bordeaux, France,INSERM, U1219 Bordeaux, France,Department of Public Health, Bordeaux University Hospital, Bordeaux, France
| | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands,Center for Medical Systems Biology, Leiden, the Netherlands
| | - Matthew Walters
- School of Medicine, Dentistry and Nursing at the University of Glasgow, Glasgow, UK
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Sylvia Wassertheil-Smoller
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, New York, NY, USA
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Kerri L. Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Qiong Yang
- Boston University School of Public Health, Boston, MA, USA
| | - Salim Yusuf
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - AFGen Consortium
- A list of members and affiliations appears in the Supplementary Note
| | | | | | - INVENT Consortium
- A list of members and affiliations appears in the Supplementary Note
| | - STARNET
- A list of members and affiliations appears in the Supplementary Note
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Tomi Pastinen
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Arno Ruusalepp
- Department of Pathophysiology, Institute of Biomedicine and Translation Medicine, University of Tartu, Tartu, Estonia,Department of Cardiac Surgery, Tartu University Hospital, Tartu, Estonia,Clinical Gene Networks AB, Stockholm, Sweden
| | - Eric E. Schadt
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Simon Koplev
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Johan L. M. Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai, New York, NY, USA,Department of Pathophysiology, Institute of Biomedicine and Translation Medicine, Biomeedikum, University of Tartu, Tartu, Estonia,Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden,Clinical Gene Networks AB, Stockholm, Sweden
| | - Veronica Codoni
- UPMC Univ. Paris 06, INSERM, UMR_S 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Sorbonne Universités, Paris, France,I CAN Institute for Cardiometabolism and Nutrition, Paris, France
| | - Mete Civelek
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA,Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - Nicholas L. Smith
- Department of Epidemiology, University of Washington, Seattle, WA, USA,Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA,Seattle Epidemiologic Research and Information Center, VA Office of Research and Development, Seattle, WA, USA
| | - David A. Tregouet
- UPMC Univ. Paris 06, INSERM, UMR_S 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Sorbonne Universités, Paris, France,I CAN Institute for Cardiometabolism and Nutrition, Paris, France
| | - Ingrid E. Christophersen
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA,Cardiovascular Research Center, MGH, Boston, MA, USA,Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Gjettum, Norway
| | - Carolina Roselli
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Steven A. Lubitz
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA,Cardiovascular Research Center, MGH, Boston, MA, USA
| | - Patrick T. Ellinor
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA,Cardiovascular Research Center, MGH, Boston, MA, USA
| | - E. Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jaspal S. Kooner
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Paul Elliott
- MRC-PHE Centre for Environment and Health, School of Public Health, Department of Epidemiology and Biostatistics and the NIHR Imperial Biomedical Research Centre, Imperial College London, London, UK
| | - John C. Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK,Department of Cardiology, Ealing Hospital NHS Trust, Southall, UK
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Andrew D. Johnson
- Framingham Heart Study, Framingham, MA, USA,National Heart, Lung and Blood Research Institute, Division of Intramural Research, Population Sciences Branch, Framingham, MA, USA
| | | | | | | | | | | | | | | | | | | | | | - Dharambir K. Sanghera
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA,Department of Pharmaceutical Sciences, College of Pharmacy, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA,Oklahoma Center for Neuroscience, Oklahoma City, OK, USA
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Christina Jern
- Department of Pathology and Genetics, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Daniel Strbian
- Department of Neurology, Helsinki University Hospital, Helsinki, Finland,Clinical Neurosciences, Neurology, University of Helsinki, Helsinki, Finland
| | - Israel Fernandez-Cadenas
- Neurovascular Research Laboratory, Vall d’Hebron Institut of Research, Neurology and Medicine Departments-Universitat Autònoma de Barcelona, Vall d’Hebrón Hospital, Barcelona, Spain,Stroke Pharmacogenomics and Genetics, Fundacio Docència i Recerca MutuaTerrassa, Terrassa, Spain
| | - W. T. Longstreth
- Department of Epidemiology, University of Washington, Seattle, WA, USA,Department of Neurology, University of Washington, Seattle, WA, USA
| | - Arndt Rolfs
- Albrecht Kossel Institute, University Clinic of Rostock, Rostock, Germany
| | - Jun Hata
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Daniel Woo
- University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Jonathan Rosand
- Center for Genomic Medicine, MGH, Boston, MA, USA,J. Philip Kistler Stroke Research Center, Department of Neurology, MGH, Boston, MA, USA,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Guillaume Pare
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - Jemma C. Hopewell
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Danish Saleheen
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kari Stefansson
- deCODE genetics/AMGEN Inc., Reykjavik, Iceland,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Bradford B. Worrall
- Departments of Neurology and Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Steven J. Kittner
- Department of Neurology, University of Maryland School of Medicine and Baltimore VAMC, Baltimore, MD, USA
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, MA, USA,Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, San Antonio, TX, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA,Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Hugh S. Markus
- Stroke Research Group, Division of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Joanna M. M. Howson
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan,Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Stephanie Debette
- Stroke Research Group, Division of Clinical Neurosciences, University of Cambridge, Cambridge, UK. .,Department of Neurology, Institute for Neurodegenerative Disease, Bordeaux University Hospital, Bordeaux, France.
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany. .,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany. .,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.
| |
Collapse
|
160
|
Kozawa S, Ueda R, Urayama K, Sagawa F, Endo S, Shiizaki K, Kurosu H, Maria de Almeida G, Hasan SM, Nakazato K, Ozaki S, Yamashita Y, Kuro-O M, Sato TN. The Body-wide Transcriptome Landscape of Disease Models. iScience 2018; 2:238-268. [PMID: 30428375 PMCID: PMC6135982 DOI: 10.1016/j.isci.2018.03.014] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 03/09/2018] [Accepted: 03/14/2018] [Indexed: 12/14/2022] Open
Abstract
Virtually all diseases affect multiple organs. However, our knowledge of the body-wide effects remains limited. Here, we report the body-wide transcriptome landscape across 13–23 organs of mouse models of myocardial infarction, diabetes, kidney diseases, cancer, and pre-mature aging. Using such datasets, we find (1) differential gene expression in diverse organs across all models; (2) skin as a disease-sensor organ represented by disease-specific activities of putative gene-expression network; (3) a bone-skin cross talk mediated by a bone-derived hormone, FGF23, in response to dysregulated phosphate homeostasis, a known risk-factor for kidney diseases; (4) candidates for the signature activities of many more putative inter-organ cross talk for diseases; and (5) a cross-species map illustrating organ-to-organ and model-to-disease relationships between human and mouse. These findings demonstrate the usefulness and the potential of such body-wide datasets encompassing mouse models of diverse disease types as a resource in biological and medical sciences. Furthermore, the findings described herein could be exploited for designing disease diagnosis and treatment. Body-wide multi-organ transcriptome datasets encompassing diverse disease models Skin is a disease-sensor organ, and FGF23 mediates a bone-skin cross talk in diseases Diverse putative inter-organ cross talk selectively associates with diseases A cross-species map illustrating the mouse-human relationships
Collapse
Affiliation(s)
- Satoshi Kozawa
- The Thomas N. Sato BioMEC-X Laboratories, Advanced Telecommunications Research Institute International (ATR), 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan; ERATO Sato Live Bio-Forecasting Project, Japan Science and Technology Agency (JST), Kyoto 619-0288, Japan
| | - Ryosuke Ueda
- The Thomas N. Sato BioMEC-X Laboratories, Advanced Telecommunications Research Institute International (ATR), 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan; ERATO Sato Live Bio-Forecasting Project, Japan Science and Technology Agency (JST), Kyoto 619-0288, Japan
| | - Kyoji Urayama
- The Thomas N. Sato BioMEC-X Laboratories, Advanced Telecommunications Research Institute International (ATR), 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan; ERATO Sato Live Bio-Forecasting Project, Japan Science and Technology Agency (JST), Kyoto 619-0288, Japan
| | - Fumihiko Sagawa
- The Thomas N. Sato BioMEC-X Laboratories, Advanced Telecommunications Research Institute International (ATR), 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan; ERATO Sato Live Bio-Forecasting Project, Japan Science and Technology Agency (JST), Kyoto 619-0288, Japan; Karydo TherapeutiX, Inc., Tokyo 102-0082, Japan
| | - Satsuki Endo
- The Thomas N. Sato BioMEC-X Laboratories, Advanced Telecommunications Research Institute International (ATR), 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan; ERATO Sato Live Bio-Forecasting Project, Japan Science and Technology Agency (JST), Kyoto 619-0288, Japan; Karydo TherapeutiX, Inc., Tokyo 102-0082, Japan
| | - Kazuhiro Shiizaki
- Division of Anti-aging Medicine, Center for Molecular Medicine, Jichi Medical University, Tochigi 329-0498, Japan
| | - Hiroshi Kurosu
- Division of Anti-aging Medicine, Center for Molecular Medicine, Jichi Medical University, Tochigi 329-0498, Japan
| | | | | | | | - Shinji Ozaki
- Department of Breast Surgery, Kure Medical Center and Chugoku Cancer Center, Hiroshima 737-0023, Japan
| | - Yoshinori Yamashita
- Institute for Clinical Research and Department of Chest Surgery, Kure Medical Center and Chugoku Cancer Center, Hiroshima 737-0023, Japan
| | - Makoto Kuro-O
- Division of Anti-aging Medicine, Center for Molecular Medicine, Jichi Medical University, Tochigi 329-0498, Japan; AMED-CREST, Japan Agency for Medical Research and Development, Tokyo 100-0004, Japan
| | - Thomas N Sato
- The Thomas N. Sato BioMEC-X Laboratories, Advanced Telecommunications Research Institute International (ATR), 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan; ERATO Sato Live Bio-Forecasting Project, Japan Science and Technology Agency (JST), Kyoto 619-0288, Japan; Karydo TherapeutiX, Inc., Tokyo 102-0082, Japan; Department of Biomedical Engineering, Cornell University, Ithaca, NY 14853, USA; Centenary Institute, Newtown, NSW 2042, Australia.
| |
Collapse
|
161
|
Wobst J, Schunkert H, Kessler T. Genetic alterations in the NO-cGMP pathway and cardiovascular risk. Nitric Oxide 2018; 76:105-112. [PMID: 29601927 DOI: 10.1016/j.niox.2018.03.019] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2017] [Revised: 03/18/2018] [Accepted: 03/26/2018] [Indexed: 12/18/2022]
Abstract
In the past ten years, several chromosomal loci have been identified by genome-wide association studies to influence the risk of coronary artery disease (CAD) and its risk factors. The GUCY1A3 gene encoding the α1 subunit of the soluble guanylyl cyclase (sGC) resides at one of these loci and has been strongly associated with blood pressure and CAD risk. More recently, further genes in the pathway encoding the endothelial nitric oxide synthase, the phosphodiesterases 3A and 5A, and the inositol 1,4,5-trisphosphate receptor I-associated protein (IRAG), i.e., NOS3, PDE3A, PDE5A, and MRVI1, respectively, were likewise identified as CAD risk genes. In this review, we highlight the genetic findings linking variants in NO-cGMP signaling and cardiovascular disease, discuss the potential underlying mechanisms which might propagate the development of atherosclerosis, and speculate about therapeutic implications.
Collapse
Affiliation(s)
- Jana Wobst
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany; Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK) e.V., partner site Munich Heart Alliance, Munich, Germany
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany; Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK) e.V., partner site Munich Heart Alliance, Munich, Germany
| | - Thorsten Kessler
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany; Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK) e.V., partner site Munich Heart Alliance, Munich, Germany.
| |
Collapse
|
162
|
Abstract
The majority of gene loci that have been associated with type 2 diabetes play a role in pancreatic islet function. To evaluate the role of islet gene expression in the etiology of diabetes, we sensitized a genetically diverse mouse population with a Western diet high in fat (45% kcal) and sucrose (34%) and carried out genome-wide association mapping of diabetes-related phenotypes. We quantified mRNA abundance in the islets and identified 18,820 expression QTL. We applied mediation analysis to identify candidate causal driver genes at loci that affect the abundance of numerous transcripts. These include two genes previously associated with monogenic diabetes (PDX1 and HNF4A), as well as three genes with nominal association with diabetes-related traits in humans (FAM83E, IL6ST, and SAT2). We grouped transcripts into gene modules and mapped regulatory loci for modules enriched with transcripts specific for α-cells, and another specific for δ-cells. However, no single module enriched for β-cell-specific transcripts, suggesting heterogeneity of gene expression patterns within the β-cell population. A module enriched in transcripts associated with branched-chain amino acid metabolism was the most strongly correlated with physiological traits that reflect insulin resistance. Although the mice in this study were not overtly diabetic, the analysis of pancreatic islet gene expression under dietary-induced stress enabled us to identify correlated variation in groups of genes that are functionally linked to diabetes-associated physiological traits. Our analysis suggests an expected degree of concordance between diabetes-associated loci in the mouse and those found in human populations, and demonstrates how the mouse can provide evidence to support nominal associations found in human genome-wide association mapping.
Collapse
|
163
|
Franzén O, Ermel R, Sukhavasi K, Jain R, Jain A, Betsholtz C, Giannarelli C, Kovacic JC, Ruusalepp A, Skogsberg J, Hao K, Schadt EE, Björkegren JL. Global analysis of A-to-I RNA editing reveals association with common disease variants. PeerJ 2018; 6:e4466. [PMID: 29527417 PMCID: PMC5844249 DOI: 10.7717/peerj.4466] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Accepted: 02/15/2018] [Indexed: 01/04/2023] Open
Abstract
RNA editing modifies transcripts and may alter their regulation or function. In humans, the most common modification is adenosine to inosine (A-to-I). We examined the global characteristics of RNA editing in 4,301 human tissue samples. More than 1.6 million A-to-I edits were identified in 62% of all protein-coding transcripts. mRNA recoding was extremely rare; only 11 novel recoding sites were uncovered. Thirty single nucleotide polymorphisms from genome-wide association studies were associated with RNA editing; one that influences type 2 diabetes (rs2028299) was associated with editing in ARPIN. Twenty-five genes, including LRP11 and PLIN5, had editing sites that were associated with plasma lipid levels. Our findings provide new insights into the genetic regulation of RNA editing and establish a rich catalogue for further exploration of this process.
Collapse
Affiliation(s)
- Oscar Franzén
- Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge, Sweden
| | - Raili Ermel
- Department of Cardiac Surgery, Tartu University Hospital, Tartu, Estonia
| | - Katyayani Sukhavasi
- Department of Pathophysiology, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Rajeev Jain
- Department of Pathophysiology, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Anamika Jain
- Department of Pathophysiology, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Christer Betsholtz
- Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge, Sweden
- Department of Immunology, Genetics and Pathology, Uppsala Universitet, Uppsala, Sweden
| | - Chiara Giannarelli
- Cardiovascular Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Institute of Genomics and Multiscale Biology, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Jason C. Kovacic
- Cardiovascular Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Arno Ruusalepp
- Department of Cardiac Surgery, Tartu University Hospital, Tartu, Estonia
- Department of Pathophysiology, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
- Clinical Gene Networks AB, Stockholm, Sweden
| | - Josefin Skogsberg
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden
| | - Ke Hao
- Institute of Genomics and Multiscale Biology, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Eric E. Schadt
- Institute of Genomics and Multiscale Biology, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Clinical Gene Networks AB, Stockholm, Sweden
| | - Johan L.M. Björkegren
- Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge, Sweden
- Department of Pathophysiology, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
- Institute of Genomics and Multiscale Biology, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Clinical Gene Networks AB, Stockholm, Sweden
| |
Collapse
|
164
|
Genetic study links components of the autonomous nervous system to heart-rate profile during exercise. Nat Commun 2018; 9:898. [PMID: 29497042 PMCID: PMC5832790 DOI: 10.1038/s41467-018-03395-6] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Accepted: 02/09/2018] [Indexed: 01/01/2023] Open
Abstract
Heart rate (HR) responds to exercise by increasing during exercise and recovering after exercise. As such, HR is an important predictor of mortality that researchers believe is modulated by the autonomic nervous system. However, the mechanistic basis underlying inter-individual differences has yet to be explained. Here, we perform a large-scale genome-wide analysis of HR increase and HR recovery in 58,818 UK Biobank individuals. Twenty-five independent SNPs in 23 loci are identified to be associated (p < 8.3 × 10−9) with HR increase or HR recovery. A total of 36 candidate causal genes are prioritized that are enriched for pathways related to neuron biology. No evidence is found of a causal relationship with mortality or cardiovascular diseases. However, a nominal association with parental lifespan requires further study. In conclusion, the findings provide new biological and clinical insight into the mechanistic underpinnings of HR response to exercise. The results also underscore the role of the autonomous nervous system in HR recovery. Response of the heart rate (HR) to exercise is associated with cardiac fitness and risk of cardiac death. Here, in a genome-wide association study, Verweij et al. identify 23 loci for HR increase during exercise or HR recovery, and highlight pleiotropy with blood pressure by polygenic risk score analysis.
Collapse
|
165
|
Lempiäinen H, Brænne I, Michoel T, Tragante V, Vilne B, Webb TR, Kyriakou T, Eichner J, Zeng L, Willenborg C, Franzen O, Ruusalepp A, Goel A, van der Laan SW, Biegert C, Hamby S, Talukdar HA, Foroughi Asl H, Pasterkamp G, Watkins H, Samani NJ, Wittenberger T, Erdmann J, Schunkert H, Asselbergs FW, Björkegren JLM. Network analysis of coronary artery disease risk genes elucidates disease mechanisms and druggable targets. Sci Rep 2018; 8:3434. [PMID: 29467471 PMCID: PMC5821758 DOI: 10.1038/s41598-018-20721-6] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Accepted: 12/06/2017] [Indexed: 12/23/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified over two hundred chromosomal loci that modulate risk of coronary artery disease (CAD). The genes affected by variants at these loci are largely unknown and an untapped resource to improve our understanding of CAD pathophysiology and identify potential therapeutic targets. Here, we prioritized 68 genes as the most likely causal genes at genome-wide significant loci identified by GWAS of CAD and examined their regulatory roles in 286 metabolic and vascular tissue gene-protein sub-networks (“modules”). The modules and genes within were scored for CAD druggability potential. The scoring enriched for targets of cardiometabolic drugs currently in clinical use and in-depth analysis of the top-scoring modules validated established and revealed novel target tissues, biological processes, and druggable targets. This study provides an unprecedented resource of tissue-defined gene–protein interactions directly affected by genetic variance in CAD risk loci.
Collapse
Affiliation(s)
| | | | - Tom Michoel
- Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.,Clinical Gene Networks AB, Stockholm, Sweden
| | - Vinicius Tragante
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Baiba Vilne
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany.,DZHK (German Centre for Cardiovascular Research), Munich Heart Alliance, Munich, Germany
| | - Tom R Webb
- Department of Cardiovascular Sciences, University of Leicester and NIHR Leicester Biomedical Research Centre, Leicester, United Kingdom
| | - Theodosios Kyriakou
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, John Radcliffe Hospital, Oxford, United Kingdom
| | | | - Lingyao Zeng
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany
| | | | - Oscar Franzen
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
| | | | - Anuj Goel
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, John Radcliffe Hospital, Oxford, United Kingdom
| | - Sander W van der Laan
- Laboratory of Experimental Cardiology, Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | | | - Stephen Hamby
- Department of Cardiovascular Sciences, University of Leicester and NIHR Leicester Biomedical Research Centre, Leicester, United Kingdom
| | - Husain A Talukdar
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Hassan Foroughi Asl
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | | | - Gerard Pasterkamp
- Laboratory of Experimental Cardiology, Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.,Laboratory of Clinical Chemistry and Hematology, Division Laboratories and Pharmacy, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, John Radcliffe Hospital, Oxford, United Kingdom
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester and NIHR Leicester Biomedical Research Centre, Leicester, United Kingdom
| | | | | | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany.,DZHK (German Centre for Cardiovascular Research), Munich Heart Alliance, Munich, Germany
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.,Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Johan L M Björkegren
- Clinical Gene Networks AB, Stockholm, Sweden. .,Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA. .,Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden.
| |
Collapse
|
166
|
Vitali C, Khetarpal SA, Rader DJ. HDL Cholesterol Metabolism and the Risk of CHD: New Insights from Human Genetics. Curr Cardiol Rep 2017; 19:132. [PMID: 29103089 DOI: 10.1007/s11886-017-0940-0] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
PURPOSE OF REVIEW Elevated high-density lipoprotein cholesterol levels in the blood (HDL-C) represent one of the strongest epidemiological surrogates for protection against coronary heart disease (CHD), but recent human genetic and pharmacological intervention studies have raised controversy about the causality of this relationship. Here, we review recent discoveries from human genome studies using new analytic tools as well as relevant animal studies that have both addressed, and in some cases, fueled this controversy. RECENT FINDINGS Methodologic developments in genotyping and sequencing, such as genome-wide association studies (GWAS), exome sequencing, and exome array genotyping, have been applied to the study of HDL-C and risk of CHD in large, multi-ethnic populations. Some of these efforts focused on population-wide variation in common variants have uncovered new polymorphisms at novel loci associated with HDL-C and, in some cases, CHD risk. Other efforts have discovered loss-of-function variants for the first time in genes previously implicated in HDL metabolism through common variant studies or animal models. These studies have allowed the genetic relationship between these pathways, HDL-C and CHD to be explored in humans for the first time through analysis tools such as Mendelian randomization. We explore these discoveries for selected key HDL-C genes CETP, LCAT, LIPG, SCARB1, and novel loci implicated from GWAS including GALNT2, KLF14, and TTC39B. Recent human genetics findings have identified new nodes regulating HDL metabolism while reshaping our current understanding of known candidate genes to HDL and CHD risk through the study of critical variants across model systems. Despite their effect on HDL-C, variants in many of the reviewed genes were found to lack any association with CHD. These data collectively indicate that HDL-C concentration, which represents a static picture of a very dynamic and heterogeneous metabolic milieu, is unlikely to be itself causally protective against CHD. In this context, human genetics represent an extremely valuable tool to further explore the biological mechanisms regulating HDL metabolism and investigate what role, if any, HDL plays in the pathogenesis of CHD.
Collapse
Affiliation(s)
- Cecilia Vitali
- Perelman School of Medicine at the University of Pennsylvania, 11-162 TRC, 3400 Civic Center Blvd, Philadelphia, PA, 19104, USA
| | - Sumeet A Khetarpal
- Perelman School of Medicine at the University of Pennsylvania, 11-162 TRC, 3400 Civic Center Blvd, Philadelphia, PA, 19104, USA
| | - Daniel J Rader
- Perelman School of Medicine at the University of Pennsylvania, 11-162 TRC, 3400 Civic Center Blvd, Philadelphia, PA, 19104, USA. .,Departments of Genetics and Medicine, Cardiovascular Institute, and Institute for Translational Medicine and Therapeutics, Perelman School of Medicine at the University of Pennsylvania, 11-125 TRC, 3400 Civic Center Blvd, Philadelphia, PA, 19104, USA.
| |
Collapse
|
167
|
Sajuthi SP, Sharma NK, Comeau ME, Chou JW, Bowden DW, Freedman BI, Langefeld CD, Parks JS, Das SK. Genetic regulation of adipose tissue transcript expression is involved in modulating serum triglyceride and HDL-cholesterol. Gene 2017; 632:50-58. [PMID: 28844666 DOI: 10.1016/j.gene.2017.08.019] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Revised: 07/06/2017] [Accepted: 08/23/2017] [Indexed: 10/19/2022]
Abstract
Dyslipidemia is a major contributor to the increased cardiovascular disease and mortality associated with obesity and type 2 diabetes. We hypothesized that variation in expression of adipose tissue transcripts is associated with serum lipid concentrations in African Americans (AAs), and common genetic variants regulate expression levels of these transcripts. Fasting serum lipid levels, genome-wide transcript expression profiles of subcutaneous adipose tissue, and genome-wide SNP genotypes were analyzed in a cohort of non-diabetic AAs (N=250). Serum triglyceride (TRIG) and high density lipoprotein-cholesterol (HDL-C) levels were associated (FDR<0.01) with expression level of 1021 and 1875 adipose tissue transcripts, respectively, but none associated with total cholesterol or LDL-C levels. Serum HDL-C-associated transcripts were enriched for salient biological pathways, including branched-chain amino acid degradation, and oxidative phosphorylation. Genes in immuno-inflammatory pathways were activated among individuals with higher serum TRIG levels. We identified significant cis-regulatory SNPs (cis-eSNPs) for 449 serum lipid-associated transcripts in adipose tissue. The cis-eSNPs of 12 genes were nominally associated (p<0.001) with serum lipid level in genome wide association studies in Global Lipids Genetics Consortium (GLGC) cohorts. Allelic effect direction of cis-eSNPs on expression of MARCH2, BEST1 and TMEM258 matched with effect direction of these SNP alleles on serum TRIG or HDL-C levels in GLGC cohorts. These data suggest that expressions of serum lipid-associated transcripts in adipose tissue are dependent on common cis-eSNPs in African Americans. Thus, genetically-mediated transcriptional regulation in adipose tissue may play a role in reducing HDL-C and increasing TRIG in serum.
Collapse
Affiliation(s)
- Satria P Sajuthi
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27157, United States
| | - Neeraj K Sharma
- Department of Internal Medicine, Section on Endocrinology and Metabolism, Wake Forest School of Medicine, Winston-Salem, NC 27157, United States
| | - Mary E Comeau
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27157, United States
| | - Jeff W Chou
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27157, United States
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC 27157, United States
| | - Barry I Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC 27157, United States
| | - Carl D Langefeld
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27157, United States
| | - John S Parks
- Department of Internal Medicine, Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27157, United States
| | - Swapan K Das
- Department of Internal Medicine, Section on Endocrinology and Metabolism, Wake Forest School of Medicine, Winston-Salem, NC 27157, United States.
| |
Collapse
|
168
|
Larson NB, McDonnell SK, Fogarty Z, Larson MC, Cheville J, Riska S, Baheti S, Weber AM, Nair AA, Wang L, O’Brien D, Davila J, Schaid DJ, Thibodeau SN. Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci. Oncotarget 2017; 8:85896-85908. [PMID: 29156765 PMCID: PMC5689655 DOI: 10.18632/oncotarget.20717] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Accepted: 07/29/2017] [Indexed: 12/19/2022] Open
Abstract
Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis-acting associations due to study limitations. While trans-eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans-eQTL associations are mediated by cis-regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis-mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans-eQTL associations that were significantly mediated by cis-regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B, and target trans-genes with known HNF response elements (MIA2, SRC, SEMA6A, KIF12). We additionally identified evidence of cis-acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1. The majority of these cis-mediator relationships demonstrated trans-eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.
Collapse
Affiliation(s)
- Nicholas B. Larson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Shannon K. McDonnell
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Zach Fogarty
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Melissa C. Larson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - John Cheville
- Division of Anatomic Pathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Shaun Riska
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Saurabh Baheti
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Alexandra M. Weber
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Asha A. Nair
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Liang Wang
- Department of Pathology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Daniel O’Brien
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Jaime Davila
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Daniel J. Schaid
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Stephen N. Thibodeau
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| |
Collapse
|
169
|
Fadason T, Ekblad C, Ingram JR, Schierding WS, O'Sullivan JM. Physical Interactions and Expression Quantitative Traits Loci Identify Regulatory Connections for Obesity and Type 2 Diabetes Associated SNPs. Front Genet 2017; 8:150. [PMID: 29081791 PMCID: PMC5645506 DOI: 10.3389/fgene.2017.00150] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2017] [Accepted: 09/28/2017] [Indexed: 12/25/2022] Open
Abstract
The mechanisms that underlie the association between obesity and type 2 diabetes are not fully understood. Here, we investigated the role of the 3D genome organization in the pathogeneses of obesity and type-2 diabetes. We interpreted the combined and differential impacts of 196 diabetes and 390 obesity associated single nucleotide polymorphisms (SNPs) by integrating data on the genes with which they physically interact (as captured by Hi-C) and the functional [i.e., expression quantitative trait loci (eQTL)] outcomes associated with these interactions. We identified 861 spatially regulated genes (e.g., AP3S2, ELP5, SVIP, IRS1, FADS2, WFS1, RBM6, HORMAD1, PYROXD2), which are enriched in tissues (e.g., adipose, skeletal muscle, pancreas) and biological processes and canonical pathways (e.g., lipid metabolism, leptin, and glucose-insulin signaling pathways) that are important for the pathogenesis of type 2 diabetes and obesity. Our discovery-based approach also identifies enrichment for eQTL SNP-gene interactions in tissues that are not classically associated with diabetes or obesity. We propose that the combinatorial action of active obesity and diabetes spatial eQTL SNPs on their gene pairs within different tissues reduces the ability of these tissues to contribute to the maintenance of a healthy energy metabolism.
Collapse
Affiliation(s)
- Tayaza Fadason
- Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Cameron Ekblad
- Liggins Institute, University of Auckland, Auckland, New Zealand
| | | | | | | |
Collapse
|
170
|
Fullard JF, Giambartolomei C, Hauberg ME, Xu K, Voloudakis G, Shao Z, Bare C, Dudley JT, Mattheisen M, Robakis NK, Haroutunian V, Roussos P. Open chromatin profiling of human postmortem brain infers functional roles for non-coding schizophrenia loci. Hum Mol Genet 2017; 26:1942-1951. [PMID: 28335009 DOI: 10.1093/hmg/ddx103] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2017] [Accepted: 03/10/2017] [Indexed: 01/03/2023] Open
Abstract
Open chromatin provides access to DNA-binding proteins for the correct spatiotemporal regulation of gene expression. Mapping chromatin accessibility has been widely used to identify the location of cis regulatory elements (CREs) including promoters and enhancers. CREs show tissue- and cell-type specificity and disease-associated variants are often enriched for CREs in the tissues and cells that pertain to a given disease. To better understand the role of CREs in neuropsychiatric disorders we applied the Assay for Transposase Accessible Chromatin followed by sequencing (ATAC-seq) to neuronal and non-neuronal nuclei isolated from frozen postmortem human brain by fluorescence-activated nuclear sorting (FANS). Most of the identified open chromatin regions (OCRs) are differentially accessible between neurons and non-neurons, and show enrichment with known cell type markers, promoters and enhancers. Relative to those of non-neurons, neuronal OCRs are more evolutionarily conserved and are enriched in distal regulatory elements. Transcription factor (TF) footprinting analysis identifies differences in the regulome between neuronal and non-neuronal cells and ascribes putative functional roles to a number of non-coding schizophrenia (SCZ) risk variants. Among the identified variants is a Single Nucleotide Polymorphism (SNP) proximal to the gene encoding SNX19. In vitro experiments reveal that this SNP leads to an increase in transcriptional activity. As elevated expression of SNX19 has been associated with SCZ, our data provide evidence that the identified SNP contributes to disease. These results represent the first analysis of OCRs and TF-binding sites in distinct populations of postmortem human brain cells and further our understanding of the regulome and the impact of neuropsychiatric disease-associated genetic risk variants.
Collapse
Affiliation(s)
- John F Fullard
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Claudia Giambartolomei
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mads E Hauberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Department of Biomedicine.,Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark.,The Lundbeck Foundation Initiative of Integrative Psychiatric Research (iPSYCH), Denmark
| | - Ke Xu
- Department of Genetics and Genomic Science and Institute for Multiscale Biology
| | - Georgios Voloudakis
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Zhiping Shao
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Department of Neuroscience.,Center for Molecular Biology and Genetics of Neurodegeneration
| | - Christopher Bare
- Flow Cytometry Center of Research Excellence, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Joel T Dudley
- Department of Genetics and Genomic Science and Institute for Multiscale Biology
| | - Manuel Mattheisen
- Department of Biomedicine.,Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark.,The Lundbeck Foundation Initiative of Integrative Psychiatric Research (iPSYCH), Denmark
| | - Nikolaos K Robakis
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Department of Neuroscience.,Center for Molecular Biology and Genetics of Neurodegeneration
| | - Vahram Haroutunian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Department of Neuroscience.,Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA
| | - Panos Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Department of Genetics and Genomic Science and Institute for Multiscale Biology.,Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA
| |
Collapse
|
171
|
Kraja AT, Cook JP, Warren HR, Surendran P, Liu C, Evangelou E, Manning AK, Grarup N, Drenos F, Sim X, Smith AV, Amin N, Blakemore AIF, Bork-Jensen J, Brandslund I, Farmaki AE, Fava C, Ferreira T, Herzig KH, Giri A, Giulianini F, Grove ML, Guo X, Harris SE, Have CT, Havulinna AS, Zhang H, Jørgensen ME, Käräjämäki A, Kooperberg C, Linneberg A, Little L, Liu Y, Bonnycastle LL, Lu Y, Mägi R, Mahajan A, Malerba G, Marioni RE, Mei H, Menni C, Morrison AC, Padmanabhan S, Palmas W, Poveda A, Rauramaa R, Rayner NW, Riaz M, Rice K, Richard MA, Smith JA, Southam L, Stančáková A, Stirrups KE, Tragante V, Tuomi T, Tzoulaki I, Varga TV, Weiss S, Yiorkas AM, Young R, Zhang W, Barnes MR, Cabrera CP, Gao H, Boehnke M, Boerwinkle E, Chambers JC, Connell JM, Christensen CK, de Boer RA, Deary IJ, Dedoussis G, Deloukas P, Dominiczak AF, Dörr M, Joehanes R, Edwards TL, Esko T, Fornage M, Franceschini N, Franks PW, Gambaro G, Groop L, Hallmans G, Hansen T, Hayward C, Heikki O, Ingelsson E, Tuomilehto J, Jarvelin MR, Kardia SLR, Karpe F, Kooner JS, Lakka TA, Langenberg C, Lind L, Loos RJF, Laakso M, McCarthy MI, Melander O, Mohlke KL, Morris AP, Palmer CNA, Pedersen O, Polasek O, Poulter NR, Province MA, Psaty BM, Ridker PM, Rotter JI, Rudan I, Salomaa V, Samani NJ, Sever PJ, Skaaby T, Stafford JM, Starr JM, van der Harst P, van der Meer P, van Duijn CM, Vergnaud AC, Gudnason V, Wareham NJ, Wilson JG, Willer CJ, Witte DR, Zeggini E, Saleheen D, Butterworth AS, Danesh J, Asselbergs FW, Wain LV, Ehret GB, Chasman DI, Caulfield MJ, Elliott P, Lindgren CM, Levy D, Newton-Cheh C, Munroe PB, Howson JMM. New Blood Pressure-Associated Loci Identified in Meta-Analyses of 475 000 Individuals. CIRCULATION. CARDIOVASCULAR GENETICS 2017; 10:e001778. [PMID: 29030403 PMCID: PMC5776077 DOI: 10.1161/circgenetics.117.001778] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 08/17/2017] [Indexed: 01/13/2023]
Abstract
BACKGROUND Genome-wide association studies have recently identified >400 loci that harbor DNA sequence variants that influence blood pressure (BP). Our earlier studies identified and validated 56 single nucleotide variants (SNVs) associated with BP from meta-analyses of exome chip genotype data. An additional 100 variants yielded suggestive evidence of association. METHODS AND RESULTS Here, we augment the sample with 140 886 European individuals from the UK Biobank, in whom 77 of the 100 suggestive SNVs were available for association analysis with systolic BP or diastolic BP or pulse pressure. We performed 2 meta-analyses, one in individuals of European, South Asian, African, and Hispanic descent (pan-ancestry, ≈475 000), and the other in the subset of individuals of European descent (≈423 000). Twenty-one SNVs were genome-wide significant (P<5×10-8) for BP, of which 4 are new BP loci: rs9678851 (missense, SLC4A1AP), rs7437940 (AFAP1), rs13303 (missense, STAB1), and rs1055144 (7p15.2). In addition, we identified a potentially independent novel BP-associated SNV, rs3416322 (missense, SYNPO2L) at a known locus, uncorrelated with the previously reported SNVs. Two SNVs are associated with expression levels of nearby genes, and SNVs at 3 loci are associated with other traits. One SNV with a minor allele frequency <0.01, (rs3025380 at DBH) was genome-wide significant. CONCLUSIONS We report 4 novel loci associated with BP regulation, and 1 independent variant at an established BP locus. This analysis highlights several candidate genes with variation that alter protein function or gene expression for potential follow-up.
Collapse
|
172
|
Mumbach MR, Satpathy AT, Boyle EA, Dai C, Gowen BG, Cho SW, Nguyen ML, Rubin AJ, Granja JM, Kazane KR, Wei Y, Nguyen T, Greenside PG, Corces MR, Tycko J, Simeonov DR, Suliman N, Li R, Xu J, Flynn RA, Kundaje A, Khavari PA, Marson A, Corn JE, Quertermous T, Greenleaf WJ, Chang HY. Enhancer connectome in primary human cells identifies target genes of disease-associated DNA elements. Nat Genet 2017; 49:1602-1612. [PMID: 28945252 DOI: 10.1038/ng.3963] [Citation(s) in RCA: 319] [Impact Index Per Article: 45.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Accepted: 09/01/2017] [Indexed: 12/14/2022]
Abstract
The challenge of linking intergenic mutations to target genes has limited molecular understanding of human diseases. Here we show that H3K27ac HiChIP generates high-resolution contact maps of active enhancers and target genes in rare primary human T cell subtypes and coronary artery smooth muscle cells. Differentiation of naive T cells into T helper 17 cells or regulatory T cells creates subtype-specific enhancer-promoter interactions, specifically at regions of shared DNA accessibility. These data provide a principled means of assigning molecular functions to autoimmune and cardiovascular disease risk variants, linking hundreds of noncoding variants to putative gene targets. Target genes identified with HiChIP are further supported by CRISPR interference and activation at linked enhancers, by the presence of expression quantitative trait loci, and by allele-specific enhancer loops in patient-derived primary cells. The majority of disease-associated enhancers contact genes beyond the nearest gene in the linear genome, leading to a fourfold increase in the number of potential target genes for autoimmune and cardiovascular diseases.
Collapse
Affiliation(s)
- Maxwell R Mumbach
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Ansuman T Satpathy
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA.,Department of Pathology, Stanford University School of Medicine, Stanford, California, USA
| | - Evan A Boyle
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Chao Dai
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
| | - Benjamin G Gowen
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, California, USA.,Innovative Genomics Institute, University of California, Berkeley, Berkeley, California, USA
| | - Seung Woo Cho
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
| | - Michelle L Nguyen
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, California, USA
| | - Adam J Rubin
- Program in Epithelial Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Jeffrey M Granja
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Katelynn R Kazane
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, California, USA.,Innovative Genomics Institute, University of California, Berkeley, Berkeley, California, USA
| | - Yuning Wei
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
| | - Trieu Nguyen
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Peyton G Greenside
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - M Ryan Corces
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
| | - Josh Tycko
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Dimitre R Simeonov
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, California, USA.,Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, California, USA
| | - Nabeela Suliman
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Rui Li
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
| | - Jin Xu
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
| | - Ryan A Flynn
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Paul A Khavari
- Program in Epithelial Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Alexander Marson
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, California, USA.,Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, California, USA.,Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Jacob E Corn
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, California, USA.,Innovative Genomics Institute, University of California, Berkeley, Berkeley, California, USA
| | - Thomas Quertermous
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - William J Greenleaf
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, California, USA.,Chan Zuckerberg Biohub, San Francisco, California, USA.,Department of Applied Physics, Stanford University, Stanford, California, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA.,Program in Epithelial Biology, Stanford University School of Medicine, Stanford, California, USA
| |
Collapse
|
173
|
Fagny M, Paulson JN, Kuijjer ML, Sonawane AR, Chen CY, Lopes-Ramos CM, Glass K, Quackenbush J, Platig J. Exploring regulation in tissues with eQTL networks. Proc Natl Acad Sci U S A 2017; 114:E7841-E7850. [PMID: 28851834 PMCID: PMC5604022 DOI: 10.1073/pnas.1707375114] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Characterizing the collective regulatory impact of genetic variants on complex phenotypes is a major challenge in developing a genotype to phenotype map. Using expression quantitative trait locus (eQTL) analyses, we constructed bipartite networks in which edges represent significant associations between genetic variants and gene expression levels and found that the network structure informs regulatory function. We show, in 13 tissues, that these eQTL networks are organized into dense, highly modular communities grouping genes often involved in coherent biological processes. We find communities representing shared processes across tissues, as well as communities associated with tissue-specific processes that coalesce around variants in tissue-specific active chromatin regions. Node centrality is also highly informative, with the global and community hubs differing in regulatory potential and likelihood of being disease associated.
Collapse
Affiliation(s)
- Maud Fagny
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| | - Joseph N Paulson
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| | - Marieke L Kuijjer
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| | - Abhijeet R Sonawane
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School Boston, MA 02115
| | - Cho-Yi Chen
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| | - Camila M Lopes-Ramos
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| | - Kimberly Glass
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School Boston, MA 02115
| | - John Quackenbush
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115;
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02115
| | - John Platig
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115;
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| |
Collapse
|
174
|
Morgan RA, Beck KR, Nixon M, Homer NZM, Crawford AA, Melchers D, Houtman R, Meijer OC, Stomby A, Anderson AJ, Upreti R, Stimson RH, Olsson T, Michoel T, Cohain A, Ruusalepp A, Schadt EE, Björkegren JLM, Andrew R, Kenyon CJ, Hadoke PWF, Odermatt A, Keen JA, Walker BR. Carbonyl reductase 1 catalyzes 20β-reduction of glucocorticoids, modulating receptor activation and metabolic complications of obesity. Sci Rep 2017; 7:10633. [PMID: 28878267 PMCID: PMC5587574 DOI: 10.1038/s41598-017-10410-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Accepted: 08/08/2017] [Indexed: 01/02/2023] Open
Abstract
Carbonyl Reductase 1 (CBR1) is a ubiquitously expressed cytosolic enzyme important in exogenous drug metabolism but the physiological function of which is unknown. Here, we describe a role for CBR1 in metabolism of glucocorticoids. CBR1 catalyzes the NADPH- dependent production of 20β-dihydrocortisol (20β-DHF) from cortisol. CBR1 provides the major route of cortisol metabolism in horses and is up-regulated in adipose tissue in obesity in horses, humans and mice. We demonstrate that 20β-DHF is a weak endogenous agonist of the human glucocorticoid receptor (GR). Pharmacological inhibition of CBR1 in diet-induced obesity in mice results in more marked glucose intolerance with evidence for enhanced hepatic GR signaling. These findings suggest that CBR1 generating 20β-dihydrocortisol is a novel pathway modulating GR activation and providing enzymatic protection against excessive GR activation in obesity.
Collapse
Affiliation(s)
- Ruth A Morgan
- University/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK. .,Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK.
| | - Katharina R Beck
- Division of Molecular and Systems Toxicology, Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
| | - Mark Nixon
- University/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Natalie Z M Homer
- Mass Spectrometry Core Laboratory, Wellcome Trust Clinical Research Facility, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Andrew A Crawford
- University/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK.,School of Social and Community Medicine, University of Bristol, Bristol, UK
| | | | - René Houtman
- PamGene International, Den Bosch, The Netherlands
| | - Onno C Meijer
- Department of Internal Medicine, Division Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
| | - Andreas Stomby
- Department of Public Health and Clinical Medicine, Umeå University, 901 87, Umeå, Sweden
| | - Anna J Anderson
- University/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Rita Upreti
- University/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Roland H Stimson
- University/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Tommy Olsson
- Department of Public Health and Clinical Medicine, Umeå University, 901 87, Umeå, Sweden
| | - Tom Michoel
- The Roslin Institute, University of Edinburgh, Easter Bush Campus, Edinburgh, UK
| | - Ariella Cohain
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Arno Ruusalepp
- Department of Physiology, Institute of Biomedicine and Translation Medicine, University of Tartu, Tartu, Estonia.,Clinical Gene Networks AB, Stockholm, Sweden.,Department of Cardiac Surgery, Tartu University Hospital, Tartu, Estonia
| | - Eric E Schadt
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA.,Department of Physiology, Institute of Biomedicine and Translation Medicine, University of Tartu, Tartu, Estonia.,Clinical Gene Networks AB, Stockholm, Sweden.,Department of Cardiac Surgery, Tartu University Hospital, Tartu, Estonia.,Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institute, Stockholm, Sweden
| | - Ruth Andrew
- University/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK.,Mass Spectrometry Core Laboratory, Wellcome Trust Clinical Research Facility, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Christopher J Kenyon
- University/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Patrick W F Hadoke
- University/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Alex Odermatt
- Division of Molecular and Systems Toxicology, Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
| | - John A Keen
- Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Brian R Walker
- University/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK.,Mass Spectrometry Core Laboratory, Wellcome Trust Clinical Research Facility, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| |
Collapse
|
175
|
Peng S, Deyssenroth MA, Di Narzo AF, Lambertini L, Marsit CJ, Chen J, Hao K. Expression quantitative trait loci (eQTLs) in human placentas suggest developmental origins of complex diseases. Hum Mol Genet 2017; 26:3432-3441. [PMID: 28854703 PMCID: PMC5886245 DOI: 10.1093/hmg/ddx265] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 06/08/2017] [Accepted: 07/04/2017] [Indexed: 12/16/2022] Open
Abstract
Epidemiologic studies support that at least part of the risk of chronic diseases in childhood and even adulthood may have an in utero origin, and the placenta is a key organ that plays a pivotal role in fetal growth and development. The transcriptomes of 159 human placenta tissues were profiled by genome-wide RNA sequencing (Illumina High-Seq 2500), and linked to fetal genotypes assessed by a high density single nucleotide polymorphism (SNP) genotyping array (Illumina MegaEx). Expression quantitative trait loci (eQTLs) across all annotated transcripts were mapped and examined for enrichment for disease susceptibility loci annotated in the genome-wide association studies (GWAS) catalog. We discovered 3218 cis- and 35 trans-eQTLs at ≤10% false discovery rate in human placentas. Among the 16 439 known disease loci of genome-wide significance, 835 were placental eSNPs (enrichment fold = 1.68, P = 7.41e-42). Stronger effect sizes were observed between GWAS SNPs and gene expression in placentas than what has been reported in other tissues, such as the correlation between asthma risk allele, rs7216389-T and Gasdermin-B (GSDMB) in placenta (r2=27%) versus lung (r2=6%). Finally, our results suggest the placental eQTLs may mediate the function of GWAS loci on postnatal disease susceptibility. Results suggest that transcripts in placenta are under tight genetic control, and that placental gene networks may influence postnatal risk of multiple human diseases lending support for the Developmental Origins of Health and Disease.
Collapse
Affiliation(s)
- Shouneng Peng
- Department of Genetics and Genomic Sciences
- Icahn Institute of Genomics and Multiscale Biology
| | | | - Antonio F. Di Narzo
- Department of Genetics and Genomic Sciences
- Icahn Institute of Genomics and Multiscale Biology
| | - Luca Lambertini
- Department of Environmental Medicine and Public Health
- Department of Obstetrics, Gynecology and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Carmen J. Marsit
- Department of Environmental Health, Emory University, Atlanta, GA 30322, USA
| | - Jia Chen
- Department of Environmental Medicine and Public Health
- Department of Pediatrics
- Department of Oncological Sciences
- Department of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences
- Icahn Institute of Genomics and Multiscale Biology
| |
Collapse
|
176
|
Shu L, Chan KHK, Zhang G, Huan T, Kurt Z, Zhao Y, Codoni V, Trégouët DA, Yang J, Wilson JG, Luo X, Levy D, Lusis AJ, Liu S, Yang X. Shared genetic regulatory networks for cardiovascular disease and type 2 diabetes in multiple populations of diverse ethnicities in the United States. PLoS Genet 2017; 13:e1007040. [PMID: 28957322 PMCID: PMC5634657 DOI: 10.1371/journal.pgen.1007040] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Revised: 10/10/2017] [Accepted: 09/21/2017] [Indexed: 12/18/2022] Open
Abstract
Cardiovascular diseases (CVD) and type 2 diabetes (T2D) are closely interrelated complex diseases likely sharing overlapping pathogenesis driven by aberrant activities in gene networks. However, the molecular circuitries underlying the pathogenic commonalities remain poorly understood. We sought to identify the shared gene networks and their key intervening drivers for both CVD and T2D by conducting a comprehensive integrative analysis driven by five multi-ethnic genome-wide association studies (GWAS) for CVD and T2D, expression quantitative trait loci (eQTLs), ENCODE, and tissue-specific gene network models (both co-expression and graphical models) from CVD and T2D relevant tissues. We identified pathways regulating the metabolism of lipids, glucose, and branched-chain amino acids, along with those governing oxidation, extracellular matrix, immune response, and neuronal system as shared pathogenic processes for both diseases. Further, we uncovered 15 key drivers including HMGCR, CAV1, IGF1 and PCOLCE, whose network neighbors collectively account for approximately 35% of known GWAS hits for CVD and 22% for T2D. Finally, we cross-validated the regulatory role of the top key drivers using in vitro siRNA knockdown, in vivo gene knockout, and two Hybrid Mouse Diversity Panels each comprised of >100 strains. Findings from this in-depth assessment of genetic and functional data from multiple human cohorts provide strong support that common sets of tissue-specific molecular networks drive the pathogenesis of both CVD and T2D across ethnicities and help prioritize new therapeutic avenues for both CVD and T2D.
Collapse
Affiliation(s)
- Le Shu
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Kei Hang K. Chan
- Departments of Epidemiology and Medicine and Center for Global Cardiometabolic Health, Brown University, Providence, RI, United States of America
- Hong Kong Institute of Diabetes and Obesity, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Guanglin Zhang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Tianxiao Huan
- The Framingham Heart Study, Framingham, MA, USA and the Population Sciences Branch, National Heart, Lung, and Blood Institute, Bethesda, MD, United States of America
| | - Zeyneb Kurt
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Yuqi Zhao
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Veronica Codoni
- Sorbonne Universités, UPMC Univ. Paris 06, INSERM, UMR_S 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris, France
- ICAN Institute for Cardiometabolism and Nutrition, Paris, France
| | - David-Alexandre Trégouët
- Sorbonne Universités, UPMC Univ. Paris 06, INSERM, UMR_S 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris, France
- ICAN Institute for Cardiometabolism and Nutrition, Paris, France
| | | | - Jun Yang
- Department of Public Health, Hangzhou Normal University School of Medicine, Hangzhou, China
- Collaborative Innovation Center for the Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, United States of America
| | - Xi Luo
- Department of Biostatistics, Brown University, Providence, RI, United States of America
| | - Daniel Levy
- The Framingham Heart Study, Framingham, MA, USA and the Population Sciences Branch, National Heart, Lung, and Blood Institute, Bethesda, MD, United States of America
| | - Aldons J. Lusis
- Departments of Medicine, Human Genetics, and Microbiology, Immunology, and Molecular Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Simin Liu
- Departments of Epidemiology and Medicine and Center for Global Cardiometabolic Health, Brown University, Providence, RI, United States of America
- Department of Endocrinology, Guangdong General Hospital/Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, United States of America
- Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, Los Angeles, CA, United States of America
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, United States of America
| |
Collapse
|
177
|
Nelson CP, Goel A, Butterworth AS, Kanoni S, Webb TR, Marouli E, Zeng L, Ntalla I, Lai FY, Hopewell JC, Giannakopoulou O, Jiang T, Hamby SE, Di Angelantonio E, Assimes TL, Bottinger EP, Chambers JC, Clarke R, Palmer CNA, Cubbon RM, Ellinor P, Ermel R, Evangelou E, Franks PW, Grace C, Gu D, Hingorani AD, Howson JMM, Ingelsson E, Kastrati A, Kessler T, Kyriakou T, Lehtimäki T, Lu X, Lu Y, März W, McPherson R, Metspalu A, Pujades-Rodriguez M, Ruusalepp A, Schadt EE, Schmidt AF, Sweeting MJ, Zalloua PA, AlGhalayini K, Keavney BD, Kooner JS, Loos RJF, Patel RS, Rutter MK, Tomaszewski M, Tzoulaki I, Zeggini E, Erdmann J, Dedoussis G, Björkegren JLM, Schunkert H, Farrall M, Danesh J, Samani NJ, Watkins H, Deloukas P. Association analyses based on false discovery rate implicate new loci for coronary artery disease. Nat Genet 2017; 49:1385-1391. [PMID: 28714975 DOI: 10.1038/ng.3913] [Citation(s) in RCA: 451] [Impact Index Per Article: 64.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Accepted: 06/15/2017] [Indexed: 02/08/2023]
Abstract
Genome-wide association studies (GWAS) in coronary artery disease (CAD) had identified 66 loci at 'genome-wide significance' (P < 5 × 10-8) at the time of this analysis, but a much larger number of putative loci at a false discovery rate (FDR) of 5% (refs. 1,2,3,4). Here we leverage an interim release of UK Biobank (UKBB) data to evaluate the validity of the FDR approach. We tested a CAD phenotype inclusive of angina (SOFT; ncases = 10,801) as well as a stricter definition without angina (HARD; ncases = 6,482) and selected cases with the former phenotype to conduct a meta-analysis using the two most recent CAD GWAS. This approach identified 13 new loci at genome-wide significance, 12 of which were on our previous list of loci meeting the 5% FDR threshold, thus providing strong support that the remaining loci identified by FDR represent genuine signals. The 304 independent variants associated at 5% FDR in this study explain 21.2% of CAD heritability and identify 243 loci that implicate pathways in blood vessel morphogenesis as well as lipid metabolism, nitric oxide signaling and inflammation.
Collapse
Affiliation(s)
- Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Leicester, UK
| | - Anuj Goel
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Adam S Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts &the London Medical School, Queen Mary University of London, London, UK
- Centre for Genomic Health, Queen Mary University of London, London, UK
| | - Tom R Webb
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Leicester, UK
| | - Eirini Marouli
- William Harvey Research Institute, Barts &the London Medical School, Queen Mary University of London, London, UK
- Centre for Genomic Health, Queen Mary University of London, London, UK
| | - Lingyao Zeng
- German Heart Center Munich, Clinic at Technische Universität München and Deutsches Zentrum für Herz- und Kreislauferkrankungen (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Ioanna Ntalla
- William Harvey Research Institute, Barts &the London Medical School, Queen Mary University of London, London, UK
- Centre for Genomic Health, Queen Mary University of London, London, UK
| | - Florence Y Lai
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Leicester, UK
| | - Jemma C Hopewell
- CTSU, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Olga Giannakopoulou
- William Harvey Research Institute, Barts &the London Medical School, Queen Mary University of London, London, UK
- Centre for Genomic Health, Queen Mary University of London, London, UK
| | - Tao Jiang
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Stephen E Hamby
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Leicester, UK
| | - Emanuele Di Angelantonio
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Themistocles L Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Erwin P Bottinger
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
- Imperial College Healthcare NHS Trust, London, UK
| | - Robert Clarke
- CTSU, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Colin N A Palmer
- Molecular and Clinical Medicine, Biomedical Research Institute, University of Dundee, Ninewells Hospital, Dundee, UK
- Pharmacogenomics Centre, Biomedical Research Institute, University of Dundee, Ninewells Hospital, Dundee, UK
| | - Richard M Cubbon
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Patrick Ellinor
- Cardiac Arrhythmia Service and Cardiovascular Research Center, Broad Institute of Harvard and Massachusetts Institute of Technology, Boston, Massachusetts, USA
| | - Raili Ermel
- Department of Cardiac Surgery, Tartu University Hospital, Tartu, Estonia
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Paul W Franks
- Department of Clinical Sciences, Genetic &Molecular Epidemiology Unit, Lund University Diabetes Center, Skåne University Hospital, Lund University, Malmö, Sweden
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
- Department of Public Health and Clinical Medicine, Unit of Medicine, Umeå University, Umeå, Sweden
| | - Christopher Grace
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Dongfeng Gu
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Aroon D Hingorani
- Institute of Cardiovascular Science, University College London,London, UK
| | - Joanna M M Howson
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Erik Ingelsson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Adnan Kastrati
- German Heart Center Munich, Clinic at Technische Universität München and Deutsches Zentrum für Herz- und Kreislauferkrankungen (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Thorsten Kessler
- German Heart Center Munich, Clinic at Technische Universität München and Deutsches Zentrum für Herz- und Kreislauferkrankungen (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Theodosios Kyriakou
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Xiangfeng Lu
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Yingchang Lu
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Winfried März
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
- Medical Clinic V (Nephrology, Rheumatology, Hypertensiology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Academy, Synlab Holding Deutschland GmbH, Mannheim, Germany
| | - Ruth McPherson
- Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, Ontario, Canada
| | | | | | - Arno Ruusalepp
- Department of Cardiac Surgery, Tartu University Hospital, Tartu, Estonia
- Clinical Gene Networks AB, Stockholm, Sweden
| | - Eric E Schadt
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Amand F Schmidt
- Institute of Cardiovascular Science, University College London,London, UK
| | - Michael J Sweeting
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Pierre A Zalloua
- Lebanese American University, School of Medicine, Beirut, Lebanon
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Kamal AlGhalayini
- Department of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Bernard D Keavney
- Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
- Imperial College Healthcare NHS Trust, London, UK
- Cardiovascular Science, National Heart and Lung Institute, Imperial College London, London, UK
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Mindich Child Health Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Riyaz S Patel
- Farr Institute of Health Informatics, UCL, London, UK
- Bart's Heart Centre, St Bartholomew's Hospital, London, UK
| | - Martin K Rutter
- Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Manchester Diabetes Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Maciej Tomaszewski
- Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Medicine, Central Manchester NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | | | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), partner site Hamburg/Lübeck/Kiel, Lübeck, Germany
- University Heart Center Lübeck, Lübeck, Germany
| | - George Dedoussis
- Department of Nutrition-Dietetics, Harokopio University, Athens, Greece
| | - Johan L M Björkegren
- Clinical Gene Networks AB, Stockholm, Sweden
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Heribert Schunkert
- German Heart Center Munich, Clinic at Technische Universität München and Deutsches Zentrum für Herz- und Kreislauferkrankungen (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Martin Farrall
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - John Danesh
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Leicester, UK
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Panos Deloukas
- William Harvey Research Institute, Barts &the London Medical School, Queen Mary University of London, London, UK
- Centre for Genomic Health, Queen Mary University of London, London, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| |
Collapse
|
178
|
Wang L, Michoel T. Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data. PLoS Comput Biol 2017; 13:e1005703. [PMID: 28821014 PMCID: PMC5576763 DOI: 10.1371/journal.pcbi.1005703] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Revised: 08/30/2017] [Accepted: 07/26/2017] [Indexed: 02/07/2023] Open
Abstract
Mapping gene expression as a quantitative trait using whole genome-sequencing and transcriptome analysis allows to discover the functional consequences of genetic variation. We developed a novel method and ultra-fast software Findr for higly accurate causal inference between gene expression traits using cis-regulatory DNA variations as causal anchors, which improves current methods by taking into consideration hidden confounders and weak regulations. Findr outperformed existing methods on the DREAM5 Systems Genetics challenge and on the prediction of microRNA and transcription factor targets in human lymphoblastoid cells, while being nearly a million times faster. Findr is publicly available at https://github.com/lingfeiwang/findr. Understanding how genetic variation between individuals determines variation in observable traits or disease risk is one of the core aims of genetics. It is known that genetic variation often affects gene regulatory DNA elements and directly causes variation in expression of nearby genes. This effect in turn cascades down to other genes via the complex pathways and gene interaction networks that ultimately govern how cells operate in an ever changing environment. In theory, when genetic variation and gene expression levels are measured simultaneously in a large number of individuals, the causal effects of genes on each other can be inferred using statistical models similar to those used in randomized controlled trials. We developed a novel method and ultra-fast software Findr which, unlike existing methods, takes into account the complex but unknown network context when predicting causality between specific gene pairs. Findr’s predictions have a significantly higher overlap with known gene networks compared to existing methods, using both simulated and real data. Findr is also nearly a million times faster, and hence the only software in its class that can handle modern datasets where the expression levels of ten-thousands of genes are simultaneously measured in hundreds to thousands of individuals.
Collapse
Affiliation(s)
- Lingfei Wang
- Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Easter Bush, Midlothian, United Kingdom
| | - Tom Michoel
- Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Easter Bush, Midlothian, United Kingdom
- * E-mail:
| |
Collapse
|
179
|
|
180
|
The Genetic Architecture of Coronary Artery Disease: Current Knowledge and Future Opportunities. Curr Atheroscler Rep 2017; 19:6. [PMID: 28130654 DOI: 10.1007/s11883-017-0641-6] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
PURPOSE OF REVIEW We provide an overview of our current understanding of the genetic architecture of coronary artery disease (CAD) and discuss areas of research that provide excellent opportunities for further exploration. RECENT FINDINGS Large-scale studies in human populations, coupled with rapid advances in genetic technologies over the last decade, have clearly established the association of common genetic variation with risk of CAD. However, the effect sizes of the susceptibility alleles are for the most part modest and collectively explain only a small fraction of the overall heritability. By comparison, evidence that rare variants make a substantial contribution to risk of CAD has been somewhat disappointing thus far, suggesting that other biological mechanisms have yet to be discovered. Emerging data suggests that novel pathways involved in the development of CAD can be identified through complementary and integrative systems genetics strategies in mice or humans. There is also convincing evidence that gut bacteria play a previously unrecognized role in the development of CAD, particularly through metabolism of certain dietary nutrients that lead to proatherogenic metabolites in the circulation. A major effort is now underway to functionally understand the newly discovered genetic and biological associations for CAD, which could lead to the development of potentially novel therapeutic strategies. Other important areas of investigation for understanding the pathophysiology of CAD, including epistatic interactions between genes or with either sex and environmental factors, have not been studied on a broad scope and represent additional opportunities for future studies.
Collapse
|
181
|
Anderson WD, DeCicco D, Schwaber JS, Vadigepalli R. A data-driven modeling approach to identify disease-specific multi-organ networks driving physiological dysregulation. PLoS Comput Biol 2017; 13:e1005627. [PMID: 28732007 PMCID: PMC5521738 DOI: 10.1371/journal.pcbi.1005627] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2017] [Accepted: 06/14/2017] [Indexed: 02/02/2023] Open
Abstract
Multiple physiological systems interact throughout the development of a complex disease. Knowledge of the dynamics and connectivity of interactions across physiological systems could facilitate the prevention or mitigation of organ damage underlying complex diseases, many of which are currently refractory to available therapeutics (e.g., hypertension). We studied the regulatory interactions operating within and across organs throughout disease development by integrating in vivo analysis of gene expression dynamics with a reverse engineering approach to infer data-driven dynamic network models of multi-organ gene regulatory influences. We obtained experimental data on the expression of 22 genes across five organs, over a time span that encompassed the development of autonomic nervous system dysfunction and hypertension. We pursued a unique approach for identification of continuous-time models that jointly described the dynamics and structure of multi-organ networks by estimating a sparse subset of ∼12,000 possible gene regulatory interactions. Our analyses revealed that an autonomic dysfunction-specific multi-organ sequence of gene expression activation patterns was associated with a distinct gene regulatory network. We analyzed the model structures for adaptation motifs, and identified disease-specific network motifs involving genes that exhibited aberrant temporal dynamics. Bioinformatic analyses identified disease-specific single nucleotide variants within or near transcription factor binding sites upstream of key genes implicated in maintaining physiological homeostasis. Our approach illustrates a novel framework for investigating the pathogenesis through model-based analysis of multi-organ system dynamics and network properties. Our results yielded novel candidate molecular targets driving the development of cardiovascular disease, metabolic syndrome, and immune dysfunction. Complex diseases such as hypertension often involve maladaptive autonomic nervous system control over the cardiovascular, renal, hepatic, immune, and endocrine systems. We studied the pathogenesis of physiological homeostasis by examining the temporal dynamics of gene expression levels from multiple organs in an animal model of autonomic dysfunction characterized by cardiovascular disease, metabolic dysregulation, and immune system aberrations. We employed a data-driven modeling approach to jointly predict continuous gene expression dynamics and gene regulatory interactions across organs in the disease and control phenotypes. We combined our analyses of multi-organ gene regulatory network dynamics and connectivity with bioinformatic analyses of genetic mutations that could regulate gene expression. Our multi-organ modeling approach to investigate the mechanisms of complex disease pathogenesis revealed novel candidates for therapeutic interventions against the development and progression of complex diseases involving autonomic nervous system dysfunction.
Collapse
Affiliation(s)
- Warren D. Anderson
- Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology, Anatomy, and Cell Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Danielle DeCicco
- Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology, Anatomy, and Cell Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - James S. Schwaber
- Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology, Anatomy, and Cell Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Rajanikanth Vadigepalli
- Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology, Anatomy, and Cell Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- * E-mail:
| |
Collapse
|
182
|
Howson JMM, Zhao W, Barnes DR, Ho WK, Young R, Paul DS, Waite LL, Freitag DF, Fauman EB, Salfati EL, Sun BB, Eicher JD, Johnson AD, Sheu WHH, Nielsen SF, Lin WY, Surendran P, Malarstig A, Wilk JB, Tybjærg-Hansen A, Rasmussen KL, Kamstrup PR, Deloukas P, Erdmann J, Kathiresan S, Samani NJ, Schunkert H, Watkins H, Do R, Rader DJ, Johnson JA, Hazen SL, Quyyumi AA, Spertus JA, Pepine CJ, Franceschini N, Justice A, Reiner AP, Buyske S, Hindorff LA, Carty CL, North KE, Kooperberg C, Boerwinkle E, Young K, Graff M, Peters U, Absher D, Hsiung CA, Lee WJ, Taylor KD, Chen YH, Lee IT, Guo X, Chung RH, Hung YJ, Rotter JI, Juang JMJ, Quertermous T, Wang TD, Rasheed A, Frossard P, Alam DS, Majumder AAS, Di Angelantonio E, Chowdhury R, Chen YDI, Nordestgaard BG, Assimes TL, Danesh J, Butterworth AS, Saleheen D. Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms. Nat Genet 2017; 49:1113-1119. [PMID: 28530674 PMCID: PMC5555387 DOI: 10.1038/ng.3874] [Citation(s) in RCA: 223] [Impact Index Per Article: 31.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 04/26/2017] [Indexed: 12/16/2022]
Abstract
Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10-8, in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.
Collapse
Affiliation(s)
- Joanna M M Howson
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Wei Zhao
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Daniel R Barnes
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Weang-Kee Ho
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Applied Mathematics, University of Nottingham Malaysia Campus, Semenyih, Malaysia
| | - Robin Young
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - Dirk S Paul
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Lindsay L Waite
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Daniel F Freitag
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Eric B Fauman
- Pfizer Worldwide Research and Development, Cambridge, Massachusetts, USA
| | - Elias L Salfati
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, California, USA
| | - Benjamin B Sun
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - John D Eicher
- National Heart, Lung, and Blood Institute, Population Sciences Branch, Bethesda, Maryland, USA
- NHLBI and Boston University's The Framingham Heart Study, Framingham, Massachusetts, USA
| | - Andrew D Johnson
- National Heart, Lung, and Blood Institute, Population Sciences Branch, Bethesda, Maryland, USA
- NHLBI and Boston University's The Framingham Heart Study, Framingham, Massachusetts, USA
| | - Wayne H H Sheu
- Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
- College of Medicine, National Defense Medical Center, Taipei, Taiwan
| | - Sune F Nielsen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Wei-Yu Lin
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Northern Institute for Cancer Research, Newcastle University, Newcastle-upon-Tyne, UK
| | - Praveen Surendran
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Jemma B Wilk
- Pfizer Worldwide Research and Development, Human Genetics, Cambridge, Massachusetts, USA
| | - Anne Tybjærg-Hansen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Katrine L Rasmussen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Pia R Kamstrup
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Centre for Genomic Health, Queen Mary University of London, London, UK
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), partner site Hamburg/Lübeck/Kiel, Lübeck, Germany
- University Heart Center Lübeck, Lübeck, Germany
| | - Sekar Kathiresan
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - Hugh Watkins
- Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Ron Do
- Charles Bronfman Institute for Personalized Medicine, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Daniel J Rader
- Departments of Genetics, Medicine, and Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Julie A Johnson
- University of Florida College of Pharmacy, Gainesville, Florida, USA
| | - Stanley L Hazen
- Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland, Ohio, USA
| | - Arshed A Quyyumi
- Division of Cardiology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - John A Spertus
- Saint Luke's Mid America Heart Institute, Kansas City, Missouri, USA
- Department of Biomedical and Health Informatics, University of Missouri-Kansas City, Kansas City, Missouri, USA
| | - Carl J Pepine
- College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Anne Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Steven Buyske
- Department of Statistics and Biostatistics, Rutgers University, Piscataway, New Jersey, USA
| | - Lucia A Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, US National Institutes of Health, Bethesda,Maryland, USA
| | - Cara L Carty
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
- Carolina Center for Genome Sciences, Chapel Hill, North Carolina, USA
| | - Charles Kooperberg
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
| | - Kristin Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Chao A Hsiung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan
| | - Wen-Jane Lee
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Ying-Hsiang Chen
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan
| | - I-Te Lee
- School of Medicine, Chung Shan Medical University, Taichung, Taiwan
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Ren-Hua Chung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan
| | - Yi-Jen Hung
- College of Medicine, National Defense Medical Center, Taipei, Taiwan
- Division of Endocrinology and Metabolism, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Jyh-Ming J Juang
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- National Taiwan University College of Medicine, Taipei, Taiwan
| | - Thomas Quertermous
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, California, USA
| | - Tzung-Dau Wang
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- National Taiwan University College of Medicine, Taipei, Taiwan
| | - Asif Rasheed
- Centre for Non-Communicable Disease, Karachi, Pakistan
| | | | - Dewan S Alam
- School of Kinesiology and Health Science, York University, Toronto, Ontario, Canada
| | | | - Emanuele Di Angelantonio
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
| | - Rajiv Chowdhury
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Themistocles L Assimes
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, California, USA
| | - John Danesh
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- Wellcome Trust Sanger Institute, Hinxton, UK
- British Heart Foundation Cambridge Centre of Excellence, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Adam S Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
| | - Danish Saleheen
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Centre for Non-Communicable Disease, Karachi, Pakistan
| |
Collapse
|
183
|
Johnson KW, Shameer K, Glicksberg BS, Readhead B, Sengupta PP, Björkegren JLM, Kovacic JC, Dudley JT. Enabling Precision Cardiology Through Multiscale Biology and Systems Medicine. ACTA ACUST UNITED AC 2017; 2:311-327. [PMID: 30062151 PMCID: PMC6034501 DOI: 10.1016/j.jacbts.2016.11.010] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Revised: 11/29/2016] [Accepted: 11/30/2016] [Indexed: 12/20/2022]
Abstract
The traditional paradigm of cardiovascular disease research derives insight from large-scale, broadly inclusive clinical studies of well-characterized pathologies. These insights are then put into practice according to standardized clinical guidelines. However, stagnation in the development of new cardiovascular therapies and variability in therapeutic response implies that this paradigm is insufficient for reducing the cardiovascular disease burden. In this state-of-the-art review, we examine 3 interconnected ideas we put forth as key concepts for enabling a transition to precision cardiology: 1) precision characterization of cardiovascular disease with machine learning methods; 2) the application of network models of disease to embrace disease complexity; and 3) using insights from the previous 2 ideas to enable pharmacology and polypharmacology systems for more precise drug-to-patient matching and patient-disease stratification. We conclude by exploring the challenges of applying a precision approach to cardiology, which arise from a deficit of the required resources and infrastructure, and emerging evidence for the clinical effectiveness of this nascent approach.
Collapse
Affiliation(s)
- Kipp W Johnson
- Institute for Next Generation Healthcare, Mount Sinai Health System, New York, New York.,Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Khader Shameer
- Institute for Next Generation Healthcare, Mount Sinai Health System, New York, New York.,Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Benjamin S Glicksberg
- Institute for Next Generation Healthcare, Mount Sinai Health System, New York, New York.,Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Ben Readhead
- Institute for Next Generation Healthcare, Mount Sinai Health System, New York, New York.,Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Partho P Sengupta
- The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.,Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York.,Department of Medical Biochemistry and Biophysics Vascular Biology Unit, Karolinska Institutet, Stockholm, Sweden
| | - Jason C Kovacic
- The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.,Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Joel T Dudley
- Institute for Next Generation Healthcare, Mount Sinai Health System, New York, New York.,Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York.,Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
| |
Collapse
|
184
|
Identification of 15 novel risk loci for coronary artery disease and genetic risk of recurrent events, atrial fibrillation and heart failure. Sci Rep 2017; 7:2761. [PMID: 28584231 PMCID: PMC5459820 DOI: 10.1038/s41598-017-03062-8] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Accepted: 04/21/2017] [Indexed: 01/11/2023] Open
Abstract
Coronary artery disease (CAD) is the major cause of morbidity and mortality in the world. Identification of novel genetic determinants may provide new opportunities for developing innovative strategies to predict, prevent and treat CAD. Therefore, we meta-analyzed independent genetic variants passing P <× 10-5 in CARDIoGRAMplusC4D with novel data made available by UK Biobank. Of the 161 genetic variants studied, 71 reached genome wide significance (p < 5 × 10-8) including 15 novel loci. These novel loci include multiple genes that are involved in angiogenesis (TGFB1, ITGB5, CDH13 and RHOA) and 2 independent variants in the TGFB1 locus. We also identified SGEF as a candidate gene in one of the novel CAD loci. SGEF was previously suggested as a therapeutic target based on mouse studies. The genetic risk score of CAD predicted recurrent CAD events and cardiovascular mortality. We also identified significant genetic correlations between CAD and other cardiovascular conditions, including heart failure and atrial fibrillation. In conclusion, we substantially increased the number of loci convincingly associated with CAD and provide additional biological and clinical insights.
Collapse
|
185
|
Hauberg ME, Zhang W, Giambartolomei C, Franzén O, Morris DL, Vyse TJ, Ruusalepp A, Sklar P, Schadt EE, Björkegren JL, Roussos P, Fromer M, Sieberts SK, Johnson JS, Ruderfer DM, Shah HR, Klei LL, Dang KK, Perumal TM, Logsdon BA, Mahajan MC, Mangravite LM, Essioux L, Toyoshiba H, Gur RE, Hahn CG, Lewis DA, Haroutunian V, Peters MA, Lipska BK, Buxbaum JD, Hirai K, Domenici E, Devlin B. Large-Scale Identification of Common Trait and Disease Variants Affecting Gene Expression. Am J Hum Genet 2017; 100:885-894. [PMID: 28552197 DOI: 10.1016/j.ajhg.2017.04.016] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Accepted: 04/26/2017] [Indexed: 12/12/2022] Open
Abstract
Genome-wide association studies (GWASs) have identified a multitude of genetic loci involved with traits and diseases. However, it is often unclear which genes are affected in such loci and whether the associated genetic variants lead to increased or decreased gene function. To mitigate this, we integrated associations of common genetic variants in 57 GWASs with 24 studies of expression quantitative trait loci (eQTLs) from a broad range of tissues by using a Mendelian randomization approach. We discovered a total of 3,484 instances of gene-trait-associated changes in expression at a false-discovery rate < 0.05. These genes were often not closest to the genetic variant and were primarily identified in eQTLs derived from pathophysiologically relevant tissues. For instance, genes with expression changes associated with lipid traits were mostly identified in the liver, and those associated with cardiovascular disease were identified in arterial tissue. The affected genes additionally point to biological processes implicated in the interrogated traits, such as the interleukin-27 pathway in rheumatoid arthritis. Further, comparing trait-associated gene expression changes across traits suggests that pleiotropy is a widespread phenomenon and points to specific instances of both agonistic and antagonistic pleiotropy. For instance, expression of SNX19 and ABCB9 is positively correlated with both the risk of schizophrenia and educational attainment. To facilitate interpretation, we provide this lexicon of how common trait-associated genetic variants alter gene expression in various tissues as the online database GWAS2Genes.
Collapse
|
186
|
Mirza N, Appleton R, Burn S, du Plessis D, Duncan R, Farah JO, Feenstra B, Hviid A, Josan V, Mohanraj R, Shukralla A, Sills GJ, Marson AG, Pirmohamed M. Genetic regulation of gene expression in the epileptic human hippocampus. Hum Mol Genet 2017; 26:1759-1769. [PMID: 28334860 PMCID: PMC5411756 DOI: 10.1093/hmg/ddx061] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 12/12/2016] [Accepted: 02/16/2017] [Indexed: 01/21/2023] Open
Abstract
Epilepsy is a serious and common neurological disorder. Expression quantitative loci (eQTL) analysis is a vital aid for the identification and interpretation of disease-risk loci. Many eQTLs operate in a tissue- and condition-specific manner. We have performed the first genome-wide cis-eQTL analysis of human hippocampal tissue to include not only normal (n = 22) but also epileptic (n = 22) samples. We demonstrate that disease-associated variants from an epilepsy GWAS meta-analysis and a febrile seizures (FS) GWAS are significantly more enriched with epilepsy-eQTLs than with normal hippocampal eQTLs from two larger independent published studies. In contrast, GWAS meta-analyses of two other brain diseases associated with hippocampal pathology (Alzheimer's disease and schizophrenia) are more enriched with normal hippocampal eQTLs than with epilepsy-eQTLs. These observations suggest that an eQTL analysis that includes disease-affected brain tissue is advantageous for detecting additional risk SNPs for the afflicting and closely related disorders, but not for distinct diseases affecting the same brain regions. We also show that epilepsy eQTLs are enriched within epilepsy-causing genes: an epilepsy cis-gene is significantly more likely to be a causal gene for a Mendelian epilepsy syndrome than to be a causal gene for another Mendelian disorder. Epilepsy cis-genes, compared to normal hippocampal cis-genes, are more enriched within epilepsy-causing genes. Hence, we utilize the epilepsy eQTL data for the functional interpretation of epilepsy disease-risk variants and, thereby, highlight novel potential causal genes for sporadic epilepsy. In conclusion, an epilepsy-eQTL analysis is superior to normal hippocampal tissue eQTL analyses for identifying the variants and genes underlying epilepsy.
Collapse
Affiliation(s)
- Nasir Mirza
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool L69 3GL, UK
| | - Richard Appleton
- The Roald Dahl EEG Unit, Paediatric Neurosciences Foundation, Alder Hey Children's NHS Foundation Trust, Liverpool L12 2AP, UK
| | - Sasha Burn
- Department of Neurosurgery, Alder Hey Children's NHS Foundation Trust, Liverpool L12 2AP, UK
| | - Daniel du Plessis
- Department of Cellular Pathology, Salford Royal NHS Foundation Trust, Salford M6 8HD, UK
| | - Roderick Duncan
- Department of Neurology, Christchurch Hospital, Christchurch 8140, New Zealand
| | - Jibril Osman Farah
- Department of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool L9 7LJ, UK
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Anders Hviid
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Vivek Josan
- Department of Neurosurgery, Salford Royal NHS Foundation Trust, Salford M6 8HD, UK
| | - Rajiv Mohanraj
- Department of Neurology, Salford Royal NHS Foundation Trust, Salford M6 8HD, UK
| | - Arif Shukralla
- Department of Neurology, Salford Royal NHS Foundation Trust, Salford M6 8HD, UK
| | - Graeme J. Sills
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool L69 3GL, UK
| | - Anthony G. Marson
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool L69 3GL, UK
| | - Munir Pirmohamed
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool L69 3GL, UK
| |
Collapse
|
187
|
Arneson D, Shu L, Tsai B, Barrere-Cain R, Sun C, Yang X. Multidimensional Integrative Genomics Approaches to Dissecting Cardiovascular Disease. Front Cardiovasc Med 2017; 4:8. [PMID: 28289683 PMCID: PMC5327355 DOI: 10.3389/fcvm.2017.00008] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 02/09/2017] [Indexed: 12/19/2022] Open
Abstract
Elucidating the mechanisms of complex diseases such as cardiovascular disease (CVD) remains a significant challenge due to multidimensional alterations at molecular, cellular, tissue, and organ levels. To better understand CVD and offer insights into the underlying mechanisms and potential therapeutic strategies, data from multiple omics types (genomics, epigenomics, transcriptomics, metabolomics, proteomics, microbiomics) from both humans and model organisms have become available. However, individual omics data types capture only a fraction of the molecular mechanisms. To address this challenge, there have been numerous efforts to develop integrative genomics methods that can leverage multidimensional information from diverse data types to derive comprehensive molecular insights. In this review, we summarize recent methodological advances in multidimensional omics integration, exemplify their applications in cardiovascular research, and pinpoint challenges and future directions in this incipient field.
Collapse
Affiliation(s)
- Douglas Arneson
- Department of Integrative Biology and Physiology, University of California Los Angeles, Los Angeles, CA, USA; Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Le Shu
- Department of Integrative Biology and Physiology, University of California Los Angeles, Los Angeles, CA, USA; Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Brandon Tsai
- Department of Integrative Biology and Physiology, University of California Los Angeles , Los Angeles, CA , USA
| | - Rio Barrere-Cain
- Department of Integrative Biology and Physiology, University of California Los Angeles , Los Angeles, CA , USA
| | - Christine Sun
- Department of Integrative Biology and Physiology, University of California Los Angeles , Los Angeles, CA , USA
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California Los Angeles, Los Angeles, CA, USA; Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA; Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA; Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA; Molecular Biology Institute, University of California Los Angeles, Los Angeles, CA, USA
| |
Collapse
|
188
|
Decreased STARD10 Expression Is Associated with Defective Insulin Secretion in Humans and Mice. Am J Hum Genet 2017; 100:238-256. [PMID: 28132686 PMCID: PMC5294761 DOI: 10.1016/j.ajhg.2017.01.011] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2016] [Accepted: 12/20/2016] [Indexed: 12/30/2022] Open
Abstract
Genetic variants near ARAP1 (CENTD2) and STARD10 influence type 2 diabetes (T2D) risk. The risk alleles impair glucose-induced insulin secretion and, paradoxically but characteristically, are associated with decreased proinsulin:insulin ratios, indicating improved proinsulin conversion. Neither the identity of the causal variants nor the gene(s) through which risk is conferred have been firmly established. Whereas ARAP1 encodes a GTPase activating protein, STARD10 is a member of the steroidogenic acute regulatory protein (StAR)-related lipid transfer protein family. By integrating genetic fine-mapping and epigenomic annotation data and performing promoter-reporter and chromatin conformational capture (3C) studies in β cell lines, we localize the causal variant(s) at this locus to a 5 kb region that overlaps a stretch-enhancer active in islets. This region contains several highly correlated T2D-risk variants, including the rs140130268 indel. Expression QTL analysis of islet transcriptomes from three independent subject groups demonstrated that T2D-risk allele carriers displayed reduced levels of STARD10 mRNA, with no concomitant change in ARAP1 mRNA levels. Correspondingly, β-cell-selective deletion of StarD10 in mice led to impaired glucose-stimulated Ca2+ dynamics and insulin secretion and recapitulated the pattern of improved proinsulin processing observed at the human GWAS signal. Conversely, overexpression of StarD10 in the adult β cell improved glucose tolerance in high fat-fed animals. In contrast, manipulation of Arap1 in β cells had no impact on insulin secretion or proinsulin conversion in mice. This convergence of human and murine data provides compelling evidence that the T2D risk associated with variation at this locus is mediated through reduction in STARD10 expression in the β cell.
Collapse
|
189
|
Cohain A, Divaraniya AA, Zhu K, Scarpa JR, Kasarskis A, Zhu J, Chang R, Dudley JT, Schadt EE. EXPLORING THE REPRODUCIBILITY OF PROBABILISTIC CAUSAL MOLECULAR NETWORK MODELS. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2017; 22:120-131. [PMID: 27896968 PMCID: PMC5161348 DOI: 10.1142/9789813207813_0013] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Network reconstruction algorithms are increasingly being employed in biomedical and life sciences research to integrate large-scale, high-dimensional data informing on living systems. One particular class of probabilistic causal networks being applied to model the complexity and causal structure of biological data is Bayesian networks (BNs). BNs provide an elegant mathematical framework for not only inferring causal relationships among many different molecular and higher order phenotypes, but also for incorporating highly diverse priors that provide an efficient path for incorporating existing knowledge. While significant methodological developments have broadly enabled the application of BNs to generate and validate meaningful biological hypotheses, the reproducibility of BNs in this context has not been systematically explored. In this study, we aim to determine the criteria for generating reproducible BNs in the context of transcription-based regulatory networks. We utilize two unique tissues from independent datasets, whole blood from the GTEx Consortium and liver from the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Team (STARNET) study. We evaluated the reproducibility of the BNs by creating networks on data subsampled at different levels from each cohort and comparing these networks to the BNs constructed using the complete data. To help validate our results, we used simulated networks at varying sample sizes. Our study indicates that reproducibility of BNs in biological research is an issue worthy of further consideration, especially in light of the many publications that now employ findings from such constructs without appropriate attention paid to reproducibility. We find that while edge-to-edge reproducibility is strongly dependent on sample size, identification of more highly connected key driver nodes in BNs can be carried out with high confidence across a range of sample sizes.
Collapse
Affiliation(s)
- Ariella Cohain
- Icahn Institute and Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1498, New York, NY, 10029, USA*Co-first Authors
| | | | | | | | | | | | | | | | | |
Collapse
|
190
|
Affiliation(s)
- Maaike Kockx
- aANZAC Research Institute bDepartment of Cardiology, Concord Repatriation General Hospital; University of Sydney, Sydney, New South Wales, Australia
| | | |
Collapse
|