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Kanki M, Nath AP, Xiang R, Yiallourou S, Fuller PJ, Cole TJ, Cánovas R, Young MJ. Poor sleep and shift work associate with increased blood pressure and inflammation in UK Biobank participants. Nat Commun 2023; 14:7096. [PMID: 37925459 PMCID: PMC10625529 DOI: 10.1038/s41467-023-42758-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 10/19/2023] [Indexed: 11/06/2023] Open
Abstract
Disrupted circadian rhythms have been linked to an increased risk of hypertension and cardiovascular disease. However, many studies show inconsistent findings and are not sufficiently powered for targeted subgroup analyses. Using the UK Biobank cohort, we evaluate the association between circadian rhythm-disrupting behaviours, blood pressure (SBP, DBP) and inflammatory markers in >350,000 adults with European white British ancestry. The independent U-shaped relationship between sleep length and SBP/DBP is most prominent with a low inflammatory status. Poor sleep quality and permanent night shift work are also positively associated with SBP/DBP. Although fully adjusting for BMI in the linear regression model attenuated effect sizes, these associations remain significant. Two-sample Mendelian Randomisation (MR) analyses support a potential causal effect of long sleep, short sleep, chronotype, daytime napping and sleep duration on SBP/DBP. Thus, in the current study, we present a positive association between circadian rhythm-disrupting behaviours and SBP/DBP regulation in males and females that is largely independent of age.
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Affiliation(s)
- Monica Kanki
- Cardiovascular Endocrinology Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Department of Medicine (Alfred Health), Central Clinical School, Monash University, Clayton, VIC, Australia
| | - Artika P Nath
- Cambridge-Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Ruidong Xiang
- Cambridge-Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Stephanie Yiallourou
- Turner Institute for Brain and Mental Health, Department of Central Clinical School, Monash University, Clayton, VIC, Australia
| | - Peter J Fuller
- Centre of Endocrinology and Metabolism, Hudson Institute of Medical Research, Clayton, VIC, Australia
| | - Timothy J Cole
- Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC, Australia
| | - Rodrigo Cánovas
- Cambridge-Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Health and Biosecurity, Australian e-Health Research Centre, CSIRO, Melbourne, VIC, Australia
| | - Morag J Young
- Cardiovascular Endocrinology Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
- Department of Cardiometabolic Health, University of Melbourne, Melbourne, VIC, Australia.
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2
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Xu Y, Ritchie SC, Liang Y, Timmers PRHJ, Pietzner M, Lannelongue L, Lambert SA, Tahir UA, May-Wilson S, Foguet C, Johansson Å, Surendran P, Nath AP, Persyn E, Peters JE, Oliver-Williams C, Deng S, Prins B, Luan J, Bomba L, Soranzo N, Di Angelantonio E, Pirastu N, Tai ES, van Dam RM, Parkinson H, Davenport EE, Paul DS, Yau C, Gerszten RE, Mälarstig A, Danesh J, Sim X, Langenberg C, Wilson JF, Butterworth AS, Inouye M. An atlas of genetic scores to predict multi-omic traits. Nature 2023; 616:123-131. [PMID: 36991119 PMCID: PMC10323211 DOI: 10.1038/s41586-023-05844-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 02/15/2023] [Indexed: 03/30/2023]
Abstract
The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1. Here we examine a large cohort (the INTERVAL study2; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores.
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Affiliation(s)
- Yu Xu
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
| | - Scott C Ritchie
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Yujian Liang
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Paul R H J Timmers
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Maik Pietzner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Loïc Lannelongue
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Samuel A Lambert
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Usman A Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Carles Foguet
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Praveen Surendran
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Artika P Nath
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Elodie Persyn
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - James E Peters
- Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, UK
| | - Clare Oliver-Williams
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Shuliang Deng
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Bram Prins
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Lorenzo Bomba
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- BioMarin Pharmaceutical, Novato, CA, USA
| | - Nicole Soranzo
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Genomics Research Centre, Human Technopole, Milan, Italy
| | - Emanuele Di Angelantonio
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Science Research Centre, Human Technopole, Milan, Italy
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- Genomics Research Centre, Human Technopole, Milan, Italy
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Departments of Exercise and Nutrition Sciences and Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Helen Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | | | - Dirk S Paul
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Christopher Yau
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Health Data Research UK, London, UK
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Broad Institute of Harvard University and Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Anders Mälarstig
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Pfizer Worldwide Research, Development and Medical, Stockholm, Sweden
| | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
- The Alan Turing Institute, London, UK.
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3
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Foguet C, Xu Y, Ritchie SC, Lambert SA, Persyn E, Nath AP, Davenport EE, Roberts DJ, Paul DS, Di Angelantonio E, Danesh J, Butterworth AS, Yau C, Inouye M. Genetically personalised organ-specific metabolic models in health and disease. Nat Commun 2022; 13:7356. [PMID: 36446790 PMCID: PMC9708841 DOI: 10.1038/s41467-022-35017-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 11/15/2022] [Indexed: 11/30/2022] Open
Abstract
Understanding how genetic variants influence disease risk and complex traits (variant-to-function) is one of the major challenges in human genetics. Here we present a model-driven framework to leverage human genome-scale metabolic networks to define how genetic variants affect biochemical reaction fluxes across major human tissues, including skeletal muscle, adipose, liver, brain and heart. As proof of concept, we build personalised organ-specific metabolic flux models for 524,615 individuals of the INTERVAL and UK Biobank cohorts and perform a fluxome-wide association study (FWAS) to identify 4312 associations between personalised flux values and the concentration of metabolites in blood. Furthermore, we apply FWAS to identify 92 metabolic fluxes associated with the risk of developing coronary artery disease, many of which are linked to processes previously described to play in role in the disease. Our work demonstrates that genetically personalised metabolic models can elucidate the downstream effects of genetic variants on biochemical reactions involved in common human diseases.
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Affiliation(s)
- Carles Foguet
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
| | - Yu Xu
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Scott C Ritchie
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Samuel A Lambert
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Elodie Persyn
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Artika P Nath
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | | | - David J Roberts
- BRC Haematology Theme, Radcliffe Department of Medicine, and NHSBT-Oxford, John Radcliffe Hospital, Oxford, UK
- National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK
- NHS Blood and Transplant, John Radcliffe Hospital, Oxford, UK
| | - Dirk S Paul
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
| | - Emanuele Di Angelantonio
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK
- Health Data Science Centre, Human Technopole, Milan, Italy
| | - John Danesh
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Hinxton, UK
- National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK
| | - Adam S Butterworth
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK
| | - Christopher Yau
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, OX3 9DU, UK
- Health Data Research UK, Gibbs Building, 215 Euston Road, London, NW1 2BE, UK
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK.
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
- The Alan Turing Institute, London, UK.
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4
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Huang QQ, Tang HHF, Teo SM, Mok D, Ritchie SC, Nath AP, Brozynska M, Salim A, Bakshi A, Holt BJ, Khor CC, Sly PD, Holt PG, Holt KE, Inouye M. Neonatal genetics of gene expression reveal potential origins of autoimmune and allergic disease risk. Nat Commun 2020; 11:3761. [PMID: 32724101 PMCID: PMC7387553 DOI: 10.1038/s41467-020-17477-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Accepted: 06/29/2020] [Indexed: 12/12/2022] Open
Abstract
Chronic immune-mediated diseases of adulthood often originate in early childhood. To investigate genetic associations between neonatal immunity and disease, we map expression quantitative trait loci (eQTLs) in resting myeloid cells and CD4+ T cells from cord blood samples, as well as in response to lipopolysaccharide (LPS) or phytohemagglutinin (PHA) stimulation, respectively. Cis-eQTLs are largely specific to cell type or stimulation, and 31% and 52% of genes with cis-eQTLs have response eQTLs (reQTLs) in myeloid cells and T cells, respectively. We identified cis regulatory factors acting as mediators of trans effects. There is extensive colocalisation between condition-specific neonatal cis-eQTLs and variants associated with immune-mediated diseases, in particular CTSH had widespread colocalisation across diseases. Mendelian randomisation shows causal neonatal gene expression effects on disease risk for BTN3A2, HLA-C and others. Our study elucidates the genetics of gene expression in neonatal immune cells, and aetiological origins of autoimmune and allergic diseases. Some immune-mediated diseases may originate in early childhood. The authors mapped eQTLs and response eQTLs to various stimuli in neonatal myeloid cells and T cells, and revealed their potential role in immune-mediated diseases using colocalisation and Mendelian randomisation.
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Affiliation(s)
- Qin Qin Huang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia. .,Department of Clinical Pathology, University of Melbourne, Parkville, VIC, 3010, Australia. .,Department of Human Genetics, Wellcome Sanger Institute, Cambridge, UK.
| | - Howard H F Tang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,School of BioSciences, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Shu Mei Teo
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Danny Mok
- Telethon Kids Institute, The University of Western Australia, Perth, WA, 6009, Australia
| | - Scott C Ritchie
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.,British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Artika P Nath
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Marta Brozynska
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Agus Salim
- Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.,School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC, 3010, Australia.,Melbourne School of Population and Global Health, Carlton, VIC, 3053, Australia
| | - Andrew Bakshi
- Monash Biomedicine Discovery Institute, Prostate Cancer Research Group, Department of Anatomy and Developmental Biology, Monash University, Clayton, VIC, 3800, Australia
| | - Barbara J Holt
- Telethon Kids Institute, The University of Western Australia, Perth, WA, 6009, Australia
| | - Chiea Chuen Khor
- Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672, Singapore.,Singapore Eye Research Institute, Singapore, Singapore.,Duke-NUS Medical School, Singapore, Singapore
| | - Peter D Sly
- Child Health Research Centre, The University of Queensland, Brisbane, QLD, 4101, Australia
| | - Patrick G Holt
- Telethon Kids Institute, The University of Western Australia, Perth, WA, 6009, Australia.,Child Health Research Centre, The University of Queensland, Brisbane, QLD, 4101, Australia
| | - Kathryn E Holt
- Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia.,The London School of Hygiene and Tropical Medicine, London, WC1E 7TH, UK
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia. .,Department of Clinical Pathology, University of Melbourne, Parkville, VIC, 3010, Australia. .,Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK. .,British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. .,National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK. .,The Alan Turing Institute, London, UK. .,British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK. .,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
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5
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Nath AP, Ritchie SC, Grinberg NF, Tang HHF, Huang QQ, Teo SM, Ahola-Olli AV, Würtz P, Havulinna AS, Santalahti K, Pitkänen N, Lehtimäki T, Kähönen M, Lyytikäinen LP, Raitoharju E, Seppälä I, Sarin AP, Ripatti S, Palotie A, Perola M, Viikari JS, Jalkanen S, Maksimow M, Salmi M, Wallace C, Raitakari OT, Salomaa V, Abraham G, Kettunen J, Inouye M. Multivariate Genome-wide Association Analysis of a Cytokine Network Reveals Variants with Widespread Immune, Haematological, and Cardiometabolic Pleiotropy. Am J Hum Genet 2019; 105:1076-1090. [PMID: 31679650 DOI: 10.1016/j.ajhg.2019.10.001] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 09/30/2019] [Indexed: 01/18/2023] Open
Abstract
Cytokines are essential regulatory components of the immune system, and their aberrant levels have been linked to many disease states. Despite increasing evidence that cytokines operate in concert, many of the physiological interactions between cytokines, and the shared genetic architecture that underlies them, remain unknown. Here, we aimed to identify and characterize genetic variants with pleiotropic effects on cytokines. Using three population-based cohorts (n = 9,263), we performed multivariate genome-wide association studies (GWAS) for a correlation network of 11 circulating cytokines, then combined our results in meta-analysis. We identified a total of eight loci significantly associated with the cytokine network, of which two (PDGFRB and ABO) had not been detected previously. In addition, conditional analyses revealed a further four secondary signals at three known cytokine loci. Integration, through the use of Bayesian colocalization analysis, of publicly available GWAS summary statistics with the cytokine network associations revealed shared causal variants between the eight cytokine loci and other traits; in particular, cytokine network variants at the ABO, SERPINE2, and ZFPM2 loci showed pleiotropic effects on the production of immune-related proteins, on metabolic traits such as lipoprotein and lipid levels, on blood-cell-related traits such as platelet count, and on disease traits such as coronary artery disease and type 2 diabetes.
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Affiliation(s)
- Artika P Nath
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom; Department of Microbiology and Immunology, University of Melbourne, Parkville, Victoria 3010, Australia.
| | - Scott C Ritchie
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom
| | - Nastasiya F Grinberg
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Department of Medicine, University of Cambridge, Cambridge CB2 0AW, United Kingdom
| | - Howard Ho-Fung Tang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia
| | - Qin Qin Huang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Department of Clinical Pathology, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Shu Mei Teo
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom
| | - Ari V Ahola-Olli
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA; Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
| | - Peter Würtz
- Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki 00014, Finland; Nightingale Health Ltd., Helsinki 00300, Finland
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; National Institute of Health and Welfare, Helsinki 00271, Finland
| | - Kristiina Santalahti
- Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Mika Kähönen
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland; Department of Clinical Physiology, Tampere University Hospital, Tampere 33521, Finland
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; National Institute of Health and Welfare, Helsinki 00271, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA; Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114, USA; Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Markus Perola
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; National Institute of Health and Welfare, Helsinki 00271, Finland
| | - Jorma S Viikari
- Department of Medicine, University of Turku, Turku 20520, Finland; Division of Medicine, Turku University Hospital, Turku 20520, Finland
| | - Sirpa Jalkanen
- Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Mikael Maksimow
- Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Marko Salmi
- Medicity Research Laboratory and Institute of Biomedicine, University of Turku, Turku 20520, Finland
| | - Chris Wallace
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Department of Medicine, University of Cambridge, Cambridge CB2 0AW, United Kingdom; MRC Biostatistics Unit, Institute of Public Health, Cambridge CB2 0SR, United Kingdom
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland; The Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland
| | - Veikko Salomaa
- Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Gad Abraham
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom; Department of Clinical Pathology, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Johannes Kettunen
- Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland; Computational Medicine, Centre for Life Course Health Research, University of Oulu, Oulu 90014, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio 70211, Finland; Biocenter Oulu, University of Oulu, Oulu 90014, Finland
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom; Department of Clinical Pathology, University of Melbourne, Parkville, Victoria 3010, Australia; The Alan Turing Institute, London, United Kingdom.
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6
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Bhalala OG, Nath AP, Inouye M, Sibley CR. Identification of expression quantitative trait loci associated with schizophrenia and affective disorders in normal brain tissue. PLoS Genet 2018; 14:e1007607. [PMID: 30142156 PMCID: PMC6126875 DOI: 10.1371/journal.pgen.1007607] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 09/06/2018] [Accepted: 08/02/2018] [Indexed: 01/12/2023] Open
Abstract
Schizophrenia and the affective disorders, here comprising bipolar disorder and major depressive disorder, are psychiatric illnesses that lead to significant morbidity and mortality worldwide. Whilst understanding of their pathobiology remains limited, large case-control studies have recently identified single nucleotide polymorphisms (SNPs) associated with these disorders. However, discerning the functional effects of these SNPs has been difficult as the associated causal genes are unknown. Here we evaluated whether schizophrenia and affective disorder associated-SNPs are correlated with gene expression within human brain tissue. Specifically, to identify expression quantitative trait loci (eQTLs), we leveraged disorder-associated SNPs identified from 11 genome-wide association studies with gene expression levels in post-mortem, neurologically-normal tissue from two independent human brain tissue expression datasets (UK Brain Expression Consortium (UKBEC) and Genotype-Tissue Expression (GTEx)). Utilizing stringent multi-region meta-analyses, we identified 2,224 cis-eQTLs associated with expression of 40 genes, including 11 non-coding RNAs. One cis-eQTL, rs16969968, results in a functionally disruptive missense mutation in CHRNA5, a schizophrenia-implicated gene. Importantly, comparing across tissues, we find that blood eQTLs capture < 10% of brain cis-eQTLs. Contrastingly, > 30% of brain-associated eQTLs are significant in tibial nerve. This study identifies putatively causal genes whose expression in region-specific tissue may contribute to the risk of schizophrenia and affective disorders.
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Affiliation(s)
- Oneil G. Bhalala
- Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- The Royal Melbourne Hospital, Melbourne Health, Parkville, Victoria, Australia
- * E-mail: (OGB); (CRS)
| | - Artika P. Nath
- Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Microbiology and Immunology, The Peter Doherty Institute, University of Melbourne, Parkville, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | | | - Michael Inouye
- Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- The Alan Turing Institute, British Library, London, United Kingdom
| | - Christopher R. Sibley
- Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia
- Department of Molecular Neuroscience, University College London Institute of Neurology, Russell Square House, Russell Square, London, United Kingdom
- Department of Medicine, Division of Brain Sciences, Imperial College London, Burlington Danes, London, United Kingdom
- * E-mail: (OGB); (CRS)
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7
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Holt KE, McAdam P, Thai PVK, Thuong NTT, Ha DTM, Lan NN, Lan NH, Nhu NTQ, Hai HT, Ha VTN, Thwaites G, Edwards DJ, Nath AP, Pham K, Ascher DB, Farrar J, Khor CC, Teo YY, Inouye M, Caws M, Dunstan SJ. Frequent transmission of the Mycobacterium tuberculosis Beijing lineage and positive selection for the EsxW Beijing variant in Vietnam. Nat Genet 2018; 50:849-856. [PMID: 29785015 PMCID: PMC6143168 DOI: 10.1038/s41588-018-0117-9] [Citation(s) in RCA: 126] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 03/22/2018] [Indexed: 12/19/2022]
Abstract
To examine the transmission dynamics of Mycobacterium tuberculosis (Mtb) isolated from tuberculosis patients in Ho Chi Minh City, Vietnam, we sequenced the whole genomes of 1,635 isolates and compared these with 3,144 isolates from elsewhere. The data identify an underlying burden of disease caused by the endemic Mtb lineage 1 associated with the activation of long-term latent infection, and a threefold higher burden associated with the more recently introduced Beijing lineage and lineage 4 Mtb strains. We find that Beijing lineage Mtb is frequently transferred between Vietnam and other countries, and detect higher levels of transmission of Beijing lineage strains within this host population than the endemic lineage 1 Mtb. Screening for parallel evolution of Beijing lineage-associated SNPs in other Mtb lineages as a signal of positive selection, we identify an alteration in the ESX-5 type VII-secreted protein EsxW, which could potentially contribute to the enhanced transmission of Beijing lineage Mtb in Vietnamese and other host populations.
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Affiliation(s)
- Kathryn E Holt
- Department of Biochemistry and Molecular Biology, Bio 21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia.
| | - Paul McAdam
- Department of Biochemistry and Molecular Biology, Bio 21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia
| | - Phan Vuong Khac Thai
- Pham Ngoc Thach Hospital for Tuberculosis and Lung Disease, Ho Chi Minh City, Vietnam
| | | | - Dang Thi Minh Ha
- Pham Ngoc Thach Hospital for Tuberculosis and Lung Disease, Ho Chi Minh City, Vietnam
| | - Nguyen Ngoc Lan
- Pham Ngoc Thach Hospital for Tuberculosis and Lung Disease, Ho Chi Minh City, Vietnam
| | - Nguyen Huu Lan
- Pham Ngoc Thach Hospital for Tuberculosis and Lung Disease, Ho Chi Minh City, Vietnam
| | | | - Hoang Thanh Hai
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Vu Thi Ngoc Ha
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Guy Thwaites
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam.,Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, Oxford University, Oxford, UK
| | - David J Edwards
- Department of Biochemistry and Molecular Biology, Bio 21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia
| | - Artika P Nath
- Department of Microbiology and Immunology, University of Melbourne, Parkville, Victoria, Australia.,Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Kym Pham
- Department of Clinical Pathology, University of Melbourne, Parkville, Victoria, Australia
| | - David B Ascher
- Department of Biochemistry and Molecular Biology, Bio 21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia
| | - Jeremy Farrar
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam.,Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, Oxford University, Oxford, UK
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Singapore, Singapore.,Singapore Eye Research Institute, Singapore, Singapore
| | - Yik Ying Teo
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Michael Inouye
- Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.,Department of Clinical Pathology, University of Melbourne, Parkville, Victoria, Australia.,Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratories, Cambridge, UK
| | - Maxine Caws
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK.,Birat-Nepal Medical Trust, Kathmandu, Nepal
| | - Sarah J Dunstan
- Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, Victoria, Australia.
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8
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Nath AP, Ritchie SC, Byars SG, Fearnley LG, Havulinna AS, Joensuu A, Kangas AJ, Soininen P, Wennerström A, Milani L, Metspalu A, Männistö S, Würtz P, Kettunen J, Raitoharju E, Kähönen M, Juonala M, Palotie A, Ala-Korpela M, Ripatti S, Lehtimäki T, Abraham G, Raitakari O, Salomaa V, Perola M, Inouye M. An interaction map of circulating metabolites, immune gene networks, and their genetic regulation. Genome Biol 2017; 18:146. [PMID: 28764798 PMCID: PMC5540552 DOI: 10.1186/s13059-017-1279-y] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Accepted: 07/14/2017] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Immunometabolism plays a central role in many cardiometabolic diseases. However, a robust map of immune-related gene networks in circulating human cells, their interactions with metabolites, and their genetic control is still lacking. Here, we integrate blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts (total N = 2168), including a subset of individuals with matched multi-omic data at 7-year follow-up. RESULTS We identify topologically replicable gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules show complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, small molecules, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) reveal five modules with mQTLs that have both cis and trans effects. The strongest mQTL is in ARHGEF3 (rs1354034) and affects a module enriched for platelet function, independent of platelet counts. Modules of mast cell/basophil and neutrophil function show temporally stable metabolite associations over 7-year follow-up, providing evidence that these modules and their constituent gene products may play central roles in metabolic inflammation. Furthermore, the strongest mQTL in ARHGEF3 also displays clear temporal stability, supporting widespread trans effects at this locus. CONCLUSIONS This study provides a detailed map of natural variation at the blood immunometabolic interface and its genetic basis, and may facilitate subsequent studies to explain inter-individual variation in cardiometabolic disease.
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Affiliation(s)
- Artika P Nath
- Department of Microbiology and Immunology, The University of Melbourne, Parkville, 3010, Victoria, Australia.,Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Scott C Ritchie
- Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.,Department of Pathology, The University of Melbourne, Parkville, 3010, Victoria, Australia
| | - Sean G Byars
- Department of Pathology, The University of Melbourne, Parkville, 3010, Victoria, Australia.,School of BioSciences, The University of Melbourne, Parkville, 3010, Victoria, Australia
| | - Liam G Fearnley
- Department of Pathology, The University of Melbourne, Parkville, 3010, Victoria, Australia.,School of BioSciences, The University of Melbourne, Parkville, 3010, Victoria, Australia
| | - Aki S Havulinna
- National Institute for Health and Welfare, Helsinki, 00271, Finland.,Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, 00014, Finland
| | - Anni Joensuu
- National Institute for Health and Welfare, Helsinki, 00271, Finland
| | - Antti J Kangas
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, 90014, Finland
| | - Pasi Soininen
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, 90014, Finland.,NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, 70211, Finland
| | | | - Lili Milani
- University of Tartu, Estonian Genome Center, Tartu, 51010, Estonia
| | - Andres Metspalu
- University of Tartu, Estonian Genome Center, Tartu, 51010, Estonia
| | - Satu Männistö
- National Institute for Health and Welfare, Helsinki, 00271, Finland
| | - Peter Würtz
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, 90014, Finland.,Diabetes and Obesity Research Program, University of Helsinki, Helsinki, Finland
| | - Johannes Kettunen
- National Institute for Health and Welfare, Helsinki, 00271, Finland.,Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, 90014, Finland.,NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, 70211, Finland.,Biocenter Oulu, University of Oulu, Oulu, 90014, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, 33014, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere and Tampere University Hospital, FI-33521, Tampere, Finland
| | - Markus Juonala
- Department of Medicine, University of Turku and Division of Medicine, Turku University Hospital, FI-20520, Turku, Finland.,Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, 00014, Finland.,Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.,Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Mika Ala-Korpela
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, 90014, Finland.,NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, 70211, Finland.,Biocenter Oulu, University of Oulu, Oulu, 90014, Finland.,Computational Medicine, School of Social and Community Medicine, University of Bristol, Bristol, BS8 1TH, UK.,Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, 00014, Finland.,Department of Public Health, University of Helsinki, Helsinki, 00014, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, 33014, Tampere, Finland
| | - Gad Abraham
- Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.,Department of Pathology, The University of Melbourne, Parkville, 3010, Victoria, Australia.,School of BioSciences, The University of Melbourne, Parkville, 3010, Victoria, Australia
| | - Olli Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, 20520, Finland.,Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, 20520, Finland
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, 00271, Finland
| | - Markus Perola
- National Institute for Health and Welfare, Helsinki, 00271, Finland.,Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, 00014, Finland.,University of Tartu, Estonian Genome Center, Tartu, 51010, Estonia
| | - Michael Inouye
- Department of Microbiology and Immunology, The University of Melbourne, Parkville, 3010, Victoria, Australia. .,Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia. .,Department of Pathology, The University of Melbourne, Parkville, 3010, Victoria, Australia. .,School of BioSciences, The University of Melbourne, Parkville, 3010, Victoria, Australia.
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9
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Ritchie SC, Würtz P, Nath AP, Abraham G, Havulinna AS, Fearnley LG, Sarin AP, Kangas AJ, Soininen P, Aalto K, Seppälä I, Raitoharju E, Salmi M, Maksimow M, Männistö S, Kähönen M, Juonala M, Ripatti S, Lehtimäki T, Jalkanen S, Perola M, Raitakari O, Salomaa V, Ala-Korpela M, Kettunen J, Inouye M. The Biomarker GlycA Is Associated with Chronic Inflammation and Predicts Long-Term Risk of Severe Infection. Cell Syst 2015; 1:293-301. [PMID: 27136058 DOI: 10.1016/j.cels.2015.09.007] [Citation(s) in RCA: 144] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2015] [Revised: 09/24/2015] [Accepted: 09/28/2015] [Indexed: 11/27/2022]
Abstract
The biomarker glycoprotein acetylation (GlycA) has been shown to predict risk of cardiovascular disease and all-cause mortality. Here, we characterize biological processes associated with GlycA by leveraging population-based omics data and health records from >10,000 individuals. Our analyses show that GlycA levels are chronic within individuals for up to a decade. In apparently healthy individuals, elevated GlycA corresponded to elevation of myriad inflammatory cytokines, as well as a gene coexpression network indicative of increased neutrophil activity, suggesting that individuals with high GlycA may be in a state of chronic inflammatory response. Accordingly, analysis of infection-related hospitalization and death records showed that increased GlycA increased long-term risk of severe non-localized and respiratory infections, particularly septicaemia and pneumonia. In total, our work demonstrates that GlycA is a biomarker for chronic inflammation, neutrophil activity, and risk of future severe infection. It also illustrates the utility of leveraging multi-layered omics data and health records to elucidate the molecular and cellular processes associated with biomarkers.
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Affiliation(s)
- Scott C Ritchie
- Centre for Systems Genomics, School of BioSciences, The University of Melbourne, Parkville, 3010 Victoria, Australia; Department of Pathology, The University of Melbourne, Parkville, 3010 Victoria, Australia
| | - Peter Würtz
- Computational Medicine, Institute of Health Sciences, University of Oulu, Oulu 90014, Finland
| | - Artika P Nath
- Centre for Systems Genomics, School of BioSciences, The University of Melbourne, Parkville, 3010 Victoria, Australia; Department of Microbiology and Immunology, The University of Melbourne, Parkville, 3010 Victoria, Australia
| | - Gad Abraham
- Centre for Systems Genomics, School of BioSciences, The University of Melbourne, Parkville, 3010 Victoria, Australia; Department of Pathology, The University of Melbourne, Parkville, 3010 Victoria, Australia
| | - Aki S Havulinna
- National Institute for Health and Welfare, Helsinki 00271, Finland; Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
| | - Liam G Fearnley
- Centre for Systems Genomics, School of BioSciences, The University of Melbourne, Parkville, 3010 Victoria, Australia; Department of Pathology, The University of Melbourne, Parkville, 3010 Victoria, Australia
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
| | - Antti J Kangas
- Computational Medicine, Institute of Health Sciences, University of Oulu, Oulu 90014, Finland
| | - Pasi Soininen
- Computational Medicine, Institute of Health Sciences, University of Oulu, Oulu 90014, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio 70211, Finland
| | - Kristiina Aalto
- MediCity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories, School of Medicine, University of Tampere, Tampere 33520, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories, School of Medicine, University of Tampere, Tampere 33520, Finland
| | - Marko Salmi
- National Institute for Health and Welfare, Helsinki 00271, Finland; MediCity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Mikael Maksimow
- National Institute for Health and Welfare, Helsinki 00271, Finland; MediCity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Satu Männistö
- National Institute for Health and Welfare, Helsinki 00271, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere and Tampere University Hospital, FI-33521 Tampere, Finland
| | - Markus Juonala
- Department of Medicine, University of Turku and Division of Medicine, Turku University Hospital, FI-20520 Turku, Finland; Murdoch Childrens Research Institute, Parkville, 3052 Victoria, Australia
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, School of Medicine, University of Tampere, Tampere 33520, Finland
| | - Sirpa Jalkanen
- MediCity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Markus Perola
- National Institute for Health and Welfare, Helsinki 00271, Finland; Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
| | - Olli Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki 00271, Finland
| | - Mika Ala-Korpela
- Computational Medicine, Institute of Health Sciences, University of Oulu, Oulu 90014, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio 70211, Finland; Oulu University Hospital, Oulu 90220, Finland; Computational Medicine, School of Social and Community Medicine, University of Bristol, Bristol BS8 1TH, UK; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
| | - Johannes Kettunen
- Computational Medicine, Institute of Health Sciences, University of Oulu, Oulu 90014, Finland; National Institute for Health and Welfare, Helsinki 00271, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio 70211, Finland.
| | - Michael Inouye
- Centre for Systems Genomics, School of BioSciences, The University of Melbourne, Parkville, 3010 Victoria, Australia; Department of Pathology, The University of Melbourne, Parkville, 3010 Victoria, Australia; Department of Microbiology and Immunology, The University of Melbourne, Parkville, 3010 Victoria, Australia.
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10
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Preininger M, Arafat D, Kim J, Nath AP, Idaghdour Y, Brigham KL, Gibson G. Blood-informative transcripts define nine common axes of peripheral blood gene expression. PLoS Genet 2013; 9:e1003362. [PMID: 23516379 PMCID: PMC3597511 DOI: 10.1371/journal.pgen.1003362] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2012] [Accepted: 01/18/2013] [Indexed: 11/19/2022] Open
Abstract
We describe a novel approach to capturing the covariance structure of peripheral blood gene expression that relies on the identification of highly conserved Axes of variation. Starting with a comparison of microarray transcriptome profiles for a new dataset of 189 healthy adult participants in the Emory-Georgia Tech Center for Health Discovery and Well-Being (CHDWB) cohort, with a previously published study of 208 adult Moroccans, we identify nine Axes each with between 99 and 1,028 strongly co-regulated transcripts in common. Each axis is enriched for gene ontology categories related to sub-classes of blood and immune function, including T-cell and B-cell physiology and innate, adaptive, and anti-viral responses. Conservation of the Axes is demonstrated in each of five additional population-based gene expression profiling studies, one of which is robustly associated with Body Mass Index in the CHDWB as well as Finnish and Australian cohorts. Furthermore, ten tightly co-regulated genes can be used to define each Axis as "Blood Informative Transcripts" (BITs), generating scores that define an individual with respect to the represented immune activity and blood physiology. We show that environmental factors, including lifestyle differences in Morocco and infection leading to active or latent tuberculosis, significantly impact specific axes, but that there is also significant heritability for the Axis scores. In the context of personalized medicine, reanalysis of the longitudinal profile of one individual during and after infection with two respiratory viruses demonstrates that specific axes also characterize clinical incidents. This mode of analysis suggests the view that, rather than unique subsets of genes marking each class of disease, differential expression reflects movement along the major normal Axes in response to environmental and genetic stimuli.
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Affiliation(s)
- Marcela Preininger
- Center for Integrative Genomics, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Dalia Arafat
- Center for Integrative Genomics, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Jinhee Kim
- Center for Integrative Genomics, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Artika P. Nath
- Center for Integrative Genomics, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Youssef Idaghdour
- Saint Justine Children's Hospital, University of Montreal, Montreal, Quebec, Canada
| | - Kenneth L. Brigham
- Center for Health Discovery and Well Being, Emory University Midtown Hospital, Atlanta, Georgia, United States of America
| | - Greg Gibson
- Center for Integrative Genomics, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America
- * E-mail:
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