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Broadaway KA, Brotman SM, Rosen JD, Currin KW, Alkhawaja AA, Etheridge AS, Wright F, Gallins P, Jima D, Zhou YH, Love MI, Innocenti F, Mohlke KL. Liver eQTL meta-analysis illuminates potential molecular mechanisms of cardiometabolic traits. Am J Hum Genet 2024:S0002-9297(24)00261-1. [PMID: 39173627 DOI: 10.1016/j.ajhg.2024.07.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 07/24/2024] [Accepted: 07/25/2024] [Indexed: 08/24/2024] Open
Abstract
Understanding the molecular mechanisms of complex traits is essential for developing targeted interventions. We analyzed liver expression quantitative-trait locus (eQTL) meta-analysis data on 1,183 participants to identify conditionally distinct signals. We found 9,013 eQTL signals for 6,564 genes; 23% of eGenes had two signals, and 6% had three or more signals. We then integrated the eQTL results with data from 29 cardiometabolic genome-wide association study (GWAS) traits and identified 1,582 GWAS-eQTL colocalizations for 747 eGenes. Non-primary eQTL signals accounted for 17% of all colocalizations. Isolating signals by conditional analysis prior to coloc resulted in 37% more colocalizations than using marginal eQTL and GWAS data, highlighting the importance of signal isolation. Isolating signals also led to stronger evidence of colocalization: among 343 eQTL-GWAS signal pairs in multi-signal regions, analyses that isolated the signals of interest resulted in higher posterior probability of colocalization for 41% of tests. Leveraging allelic heterogeneity, we predicted causal effects of gene expression on liver traits for four genes. To predict functional variants and regulatory elements, we colocalized eQTL with liver chromatin accessibility QTL (caQTL) and found 391 colocalizations, including 73 with non-primary eQTL signals and 60 eQTL signals that colocalized with both a caQTL and a GWAS signal. Finally, we used publicly available massively parallel reporter assays in HepG2 to highlight 14 eQTL signals that include at least one expression-modulating variant. This multi-faceted approach to unraveling the genetic underpinnings of liver-related traits could lead to therapeutic development.
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Affiliation(s)
- K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Sarah M Brotman
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jonathan D Rosen
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Abdalla A Alkhawaja
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Amy S Etheridge
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Fred Wright
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA; Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA; Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA
| | - Paul Gallins
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
| | - Dereje Jima
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
| | - Yi-Hui Zhou
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA; Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
| | - Michael I Love
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Federico Innocenti
- Eshelman School of Pharmacy, Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
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2
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Choucair I, Mallela DP, Hilser JR, Hartiala JA, Nemet I, Gogonea V, Li L, Lusis AJ, Fischbach MA, Tang WW, Allayee H, Hazen SL. Comprehensive Clinical and Genetic Analyses of Circulating Bile Acids and Their Associations With Diabetes and Its Indices. Diabetes 2024; 73:1215-1228. [PMID: 38701355 PMCID: PMC11262044 DOI: 10.2337/db23-0676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 04/24/2024] [Indexed: 05/05/2024]
Abstract
Bile acids (BAs) are cholesterol-derived compounds that regulate glucose, lipid, and energy metabolism. Despite their significance in glucose homeostasis, the association between specific BA molecular species and their synthetic pathways with diabetes is unclear. Here, we used a recently validated, stable-isotope dilution, high-performance liquid chromatography with tandem mass spectrometry method to quantify a panel of BAs in fasting plasma from 2,145 study participants and explored structural and genetic determinants of BAs linked to diabetes, insulin resistance, and obesity. Multiple 12α-hydroxylated BAs were associated with diabetes (adjusted odds ratio [aOR] range, 1.3-1.9; P < 0.05 for all) and insulin resistance (aOR range, 1.3-2.2; P < 0.05 for all). Conversely, multiple 6α-hydroxylated BAs and isolithocholic acid (iso-LCA) were inversely associated with diabetes and obesity (aOR range, 0.3-0.9; P < 0.05 for all). Genome-wide association studies revealed multiple genome-wide significant loci linked with 9 of the 14 diabetes-associated BAs, including a locus for iso-LCA (rs11866815). Mendelian randomization analyses showed genetically elevated deoxycholic acid levels were causally associated with higher BMI, and iso-LCA levels were causally associated with reduced BMI and diabetes risk. In conclusion, comprehensive, large-scale, quantitative mass spectrometry and genetics analyses show circulating levels of multiple structurally specific BAs, especially DCA and iso-LCA, are clinically associated with and genetically linked to obesity and diabetes. ARTICLE HIGHLIGHTS
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Affiliation(s)
- Ibrahim Choucair
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
- Center for Microbiome and Human Health, Cleveland Clinic, Cleveland, OH
| | - Deepthi P. Mallela
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
- Center for Microbiome and Human Health, Cleveland Clinic, Cleveland, OH
| | - James R. Hilser
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Jaana A. Hartiala
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Ina Nemet
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
- Center for Microbiome and Human Health, Cleveland Clinic, Cleveland, OH
| | - Valentin Gogonea
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
- Center for Microbiome and Human Health, Cleveland Clinic, Cleveland, OH
- Department of Chemistry, Cleveland State University, Cleveland, OH
| | - Lin Li
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
- Center for Microbiome and Human Health, Cleveland Clinic, Cleveland, OH
| | - Aldons J. Lusis
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA
- Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA
| | | | - W.H. Wilson Tang
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
- Center for Microbiome and Human Health, Cleveland Clinic, Cleveland, OH
- Department of Cardiovascular Medicine, Heart Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH
| | - Hooman Allayee
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Stanley L. Hazen
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
- Center for Microbiome and Human Health, Cleveland Clinic, Cleveland, OH
- Department of Cardiovascular Medicine, Heart Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH
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3
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Lee PC, Jung IH, Thussu S, Patel V, Wagoner R, Burks KH, Amrute J, Elenbaas JS, Kang CJ, Young EP, Scherer PE, Stitziel NO. Instrumental variable and colocalization analyses identify endotrophin and HTRA1 as potential therapeutic targets for coronary artery disease. iScience 2024; 27:110104. [PMID: 38989470 PMCID: PMC11233907 DOI: 10.1016/j.isci.2024.110104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 03/26/2024] [Accepted: 05/22/2024] [Indexed: 07/12/2024] Open
Abstract
Coronary artery disease (CAD) remains a leading cause of disease burden globally, and there is a persistent need for new therapeutic targets. Instrumental variable (IV) and genetic colocalization analyses can help identify novel therapeutic targets for human disease by nominating causal genes in genome-wide association study (GWAS) loci. We conducted cis-IV analyses for 20,125 genes and 1,746 plasma proteins with CAD using molecular trait quantitative trait loci variant (QTLs) data from three different studies. 19 proteins and 119 genes were significantly associated with CAD risk by IV analyses and demonstrated evidence of genetic colocalization. Notably, our analyses validated well-established targets such as PCSK9 and ANGPTL4 while also identifying HTRA1 and endotrophin (a cleavage product of COL6A3) as proteins whose levels are causally associated with CAD risk. Further experimental studies are needed to confirm the causal role of the genes and proteins identified through our multiomic cis-IV analyses on human disease.
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Affiliation(s)
- Paul C. Lee
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - In-Hyuk Jung
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Shreeya Thussu
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Ved Patel
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Ryan Wagoner
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Kendall H. Burks
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Junedh Amrute
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Jared S. Elenbaas
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Chul Joo Kang
- McDonnell Genome Institute, Washington University School of Medicine, Saint Louis, MO 63108, USA
| | - Erica P. Young
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
- McDonnell Genome Institute, Washington University School of Medicine, Saint Louis, MO 63108, USA
| | - Philipp E. Scherer
- Touchstone Diabetes Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Nathan O. Stitziel
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
- McDonnell Genome Institute, Washington University School of Medicine, Saint Louis, MO 63108, USA
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110, USA
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Reed JN, Huang J, Li Y, Ma L, Banka D, Wabitsch M, Wang T, Ding W, Björkegren JL, Civelek M. Systems genetics analysis of human body fat distribution genes identifies adipocyte processes. Life Sci Alliance 2024; 7:e202402603. [PMID: 38702075 PMCID: PMC11068934 DOI: 10.26508/lsa.202402603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 04/19/2024] [Accepted: 04/22/2024] [Indexed: 05/06/2024] Open
Abstract
Excess abdominal fat is a sexually dimorphic risk factor for cardio-metabolic disease and is approximated by the waist-to-hip ratio adjusted for body mass index (WHRadjBMI). Whereas this trait is highly heritable, few causal genes are known. We aimed to identify novel drivers of WHRadjBMI using systems genetics. We used two independent cohorts of adipose tissue gene expression and constructed sex- and depot-specific Bayesian networks to model gene-gene interactions from 8,492 genes. Using key driver analysis, we identified genes that, in silico and putatively in vitro, regulate many others. 51-119 key drivers in each network were replicated in both cohorts. In other cell types, 23 of these genes are found in crucial adipocyte pathways: Wnt signaling or mitochondrial function. We overexpressed or down-regulated seven key driver genes in human subcutaneous pre-adipocytes. Key driver genes ANAPC2 and RSPO1 inhibited adipogenesis, whereas PSME3 increased adipogenesis. RSPO1 increased Wnt signaling activity. In differentiated adipocytes, MIGA1 and UBR1 down-regulation led to mitochondrial dysfunction. These five genes regulate adipocyte function, and we hypothesize that they regulate fat distribution.
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Affiliation(s)
- Jordan N Reed
- https://ror.org/0153tk833 Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
- https://ror.org/0153tk833 Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jiansheng Huang
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Yong Li
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Lijiang Ma
- https://ror.org/04a9tmd77 Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dhanush Banka
- https://ror.org/0153tk833 Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - Martin Wabitsch
- Division of Paediatric Endocrinology and Diabetes, Department of Paediatrics and Adolescent Medicine, Ulm University Medical Centre, Ulm, Germany
| | - Tianfang Wang
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Wen Ding
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Johan Lm Björkegren
- https://ror.org/04a9tmd77 Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Mete Civelek
- https://ror.org/0153tk833 Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
- https://ror.org/0153tk833 Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
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5
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Khan M, Ludl AA, Bankier S, Björkegren JLM, Michoel T. Prediction of causal genes at GWAS loci with pleiotropic gene regulatory effects using sets of correlated instrumental variables. ARXIV 2024:arXiv:2401.06261v2. [PMID: 38259344 PMCID: PMC10802687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Multivariate Mendelian randomization (MVMR) is a statistical technique that uses sets of genetic instruments to estimate the direct causal effects of multiple exposures on an outcome of interest. At genomic loci with pleiotropic gene regulatory effects, that is, loci where the same genetic variants are associated to multiple nearby genes, MVMR can potentially be used to predict candidate causal genes. However, consensus in the field dictates that the genetic instruments in MVMR must be independent (not in linkage disequilibrium), which is usually not possible when considering a group of candidate genes from the same locus. Here we used causal inference theory to show that MVMR with correlated instruments satisfies the instrumental set condition. This is a classical result by Brito and Pearl (2002) for structural equation models that guarantees the identifiability of individual causal effects in situations where multiple exposures collectively, but not individually, separate a set of instrumental variables from an outcome variable. Extensive simulations confirmed the validity and usefulness of these theoretical results. Importantly, the causal effect estimates remained unbiased and their variance small even when instruments are highly correlated, while bias introduced by horizontal pleiotropy or LD matrix sampling error was comparable to standard MR. We applied MVMR with correlated instrumental variable sets at genome-wide significant loci for coronary artery disease (CAD) risk using expression Quantitative Trait Loci (eQTL) data from seven vascular and metabolic tissues in the STARNET study. Our method predicts causal genes at twelve loci, each associated with multiple colocated genes in multiple tissues. We confirm causal roles for PHACTR1 and ADAMTS7 in arterial tissues, among others. However, the extensive degree of regulatory pleiotropy across tissues and the limited number of causal variants in each locus still require that MVMR is run on a tissue-by-tissue basis, and testing all gene-tissue pairs with cis-eQTL associations at a given locus in a single model to predict causal gene-tissue combinations remains infeasible. Our results show that within tissues, MVMR with dependent, as opposed to independent, sets of instrumental variables significantly expands the scope for predicting causal genes in disease risk loci with pleiotropic regulatory effects. However, considering risk loci with regulatory pleiotropy that also spans across tissues remains an unsolved problem.
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Affiliation(s)
- Mariyam Khan
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Adriaan-Alexander Ludl
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Sean Bankier
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Johan LM Björkegren
- Department of Medicine (Huddinge), Karolinska Institutet, Huddinge, Sweden
- Department of Genetics & Genomic Sciences/Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tom Michoel
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
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6
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Mocci G, Sukhavasi K, Örd T, Bankier S, Singha P, Arasu UT, Agbabiaje OO, Mäkinen P, Ma L, Hodonsky CJ, Aherrahrou R, Muhl L, Liu J, Gustafsson S, Byandelger B, Wang Y, Koplev S, Lendahl U, Owens GK, Leeper NJ, Pasterkamp G, Vanlandewijck M, Michoel T, Ruusalepp A, Hao K, Ylä-Herttuala S, Väli M, Järve H, Mokry M, Civelek M, Miller CJ, Kovacic JC, Kaikkonen MU, Betsholtz C, Björkegren JL. Single-Cell Gene-Regulatory Networks of Advanced Symptomatic Atherosclerosis. Circ Res 2024; 134:1405-1423. [PMID: 38639096 PMCID: PMC11122742 DOI: 10.1161/circresaha.123.323184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 04/01/2024] [Accepted: 04/04/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND While our understanding of the single-cell gene expression patterns underlying the transformation of vascular cell types during the progression of atherosclerosis is rapidly improving, the clinical and pathophysiological relevance of these changes remains poorly understood. METHODS Single-cell RNA sequencing data generated with SmartSeq2 (≈8000 genes/cell) in 16 588 single cells isolated during atherosclerosis progression in Ldlr-/-Apob100/100 mice with human-like plasma lipoproteins and from humans with asymptomatic and symptomatic carotid plaques was clustered into multiple subtypes. For clinical and pathophysiological context, the advanced-stage and symptomatic subtype clusters were integrated with 135 tissue-specific (atherosclerotic aortic wall, mammary artery, liver, skeletal muscle, and visceral and subcutaneous, fat) gene-regulatory networks (GRNs) inferred from 600 coronary artery disease patients in the STARNET (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task) study. RESULTS Advanced stages of atherosclerosis progression and symptomatic carotid plaques were largely characterized by 3 smooth muscle cells (SMCs), and 3 macrophage subtype clusters with extracellular matrix organization/osteogenic (SMC), and M1-type proinflammatory/Trem2-high lipid-associated (macrophage) phenotypes. Integrative analysis of these 6 clusters with STARNET revealed significant enrichments of 3 arterial wall GRNs: GRN33 (macrophage), GRN39 (SMC), and GRN122 (macrophage) with major contributions to coronary artery disease heritability and strong associations with clinical scores of coronary atherosclerosis severity. The presence and pathophysiological relevance of GRN39 were verified in 5 independent RNAseq data sets obtained from the human coronary and aortic artery, and primary SMCs and by targeting its top-key drivers, FRZB and ALCAM in cultured human coronary artery SMCs. CONCLUSIONS By identifying and integrating the most gene-rich single-cell subclusters of atherosclerosis to date with a coronary artery disease framework of GRNs, GRN39 was identified and independently validated as being critical for the transformation of contractile SMCs into an osteogenic phenotype promoting advanced, symptomatic atherosclerosis.
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MESH Headings
- Humans
- Single-Cell Analysis
- Animals
- Gene Regulatory Networks
- Atherosclerosis/genetics
- Atherosclerosis/metabolism
- Atherosclerosis/pathology
- Mice
- Myocytes, Smooth Muscle/metabolism
- Myocytes, Smooth Muscle/pathology
- Male
- Plaque, Atherosclerotic
- Disease Progression
- Female
- Macrophages/metabolism
- Macrophages/pathology
- Mice, Knockout
- Receptors, LDL/genetics
- Receptors, LDL/metabolism
- Mice, Inbred C57BL
- Muscle, Smooth, Vascular/metabolism
- Muscle, Smooth, Vascular/pathology
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Affiliation(s)
- Giuseppe Mocci
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Katyayani Sukhavasi
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Estonia (K.S., A.R., H.J.)
| | - Tiit Örd
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Sean Bankier
- Computational Biology Unit, Department of Informatics, University of Bergen, Norway (S.B., T.M.)
| | - Prosanta Singha
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Uma Thanigai Arasu
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Olayinka Oluwasegun Agbabiaje
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Petri Mäkinen
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York (L. Ma, S.K., K.H., J.L.M.B.)
| | - Chani J. Hodonsky
- Robert M. Berne Cardiovascular Research Center (C.J.H., G.K.O., C.J.M.), University of Virginia, Charlottesville
- Center for Public Health Genomics (C.J.H., R.A., M.C.), University of Virginia, Charlottesville
| | - Redouane Aherrahrou
- Center for Public Health Genomics (C.J.H., R.A., M.C.), University of Virginia, Charlottesville
- Department of Biomedical Engineering (R.A., M.C.), University of Virginia, Charlottesville
| | - Lars Muhl
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Jianping Liu
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Sonja Gustafsson
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Byambajav Byandelger
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Ying Wang
- Division of Vascular Surgery, Department of Surgery, Stanford University School of Medicine, CA (Y.W., N.J.L.)
- Stanford Cardiovascular Institute, Stanford University, CA (Y.W., N.J.L.)
| | - Simon Koplev
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York (L. Ma, S.K., K.H., J.L.M.B.)
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, United Kingdom (S.K.)
| | - Urban Lendahl
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Gary K. Owens
- Robert M. Berne Cardiovascular Research Center (C.J.H., G.K.O., C.J.M.), University of Virginia, Charlottesville
| | - Nicholas J. Leeper
- Division of Vascular Surgery, Department of Surgery, Stanford University School of Medicine, CA (Y.W., N.J.L.)
- Stanford Cardiovascular Institute, Stanford University, CA (Y.W., N.J.L.)
| | - Gerard Pasterkamp
- Laboratory of Experimental Cardiology (G.P., M.M.), University Medical Center Utrecht, the Netherlands
- Central Diagnostics Laboratory (G.P., M.M.), University Medical Center Utrecht, the Netherlands
| | - Michael Vanlandewijck
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Tom Michoel
- Computational Biology Unit, Department of Informatics, University of Bergen, Norway (S.B., T.M.)
| | - Arno Ruusalepp
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Estonia (K.S., A.R., H.J.)
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York (L. Ma, S.K., K.H., J.L.M.B.)
| | - Seppo Ylä-Herttuala
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Marika Väli
- Department of Immunology, Genetics, and Pathology, Rudbeck Laboratory, Uppsala University, Sweden (M.V., C.B.)
- Department of Pathological anatomy and Forensic medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Estonia (M.V.)
| | - Heli Järve
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Estonia (K.S., A.R., H.J.)
| | - Michal Mokry
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
- Laboratory of Experimental Cardiology (G.P., M.M.), University Medical Center Utrecht, the Netherlands
| | - Mete Civelek
- Center for Public Health Genomics (C.J.H., R.A., M.C.), University of Virginia, Charlottesville
- Department of Biomedical Engineering (R.A., M.C.), University of Virginia, Charlottesville
| | - Clint J. Miller
- Robert M. Berne Cardiovascular Research Center (C.J.H., G.K.O., C.J.M.), University of Virginia, Charlottesville
| | - Jason C. Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York (J.C.K.)
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia (J.C.K.)
- St. Vincent’s Clinical School, University of NSW, Sydney, Australia (J.C.K.)
| | - Minna U. Kaikkonen
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Christer Betsholtz
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
- Department of Immunology, Genetics, and Pathology, Rudbeck Laboratory, Uppsala University, Sweden (M.V., C.B.)
| | - Johan L.M. Björkegren
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York (L. Ma, S.K., K.H., J.L.M.B.)
- Clinical Gene Networks AB, Stockholm, Sweden (J.L.M.B.)
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7
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Li T, Wu Y, Yang J, Jing J, Ma C, Sun L. N6-methyladenosine-associated genetic variants in NECTIN2 and HPCAL1 are risk factors for abdominal aortic aneurysm. iScience 2024; 27:109419. [PMID: 38510151 PMCID: PMC10952030 DOI: 10.1016/j.isci.2024.109419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 01/07/2024] [Accepted: 03/01/2024] [Indexed: 03/22/2024] Open
Abstract
Although N6-methyladenosine (m6A) modification has been implicated in the pathogenesis of abdominal aortic aneurysm (AAA), the relationship between m6A-associated single nucleotide polymorphisms (m6A-SNPs) and AAA remains unknown. This study used integrative multi-omics analysis and clinical validation approaches to systematically identify potential m6A-SNPs connected with AAA risk. We found that rs6859 and rs10198139 could modulate the expression of local genes, NECTIN2 and HPCAL1, respectively, which exhibited upregulation in AAA tissues, and their risk variants were significantly correlated with an increased susceptibility to AAA. Incorporating rs6859 and rs10198139 improved the efficiency of AAA risk prediction compared to the model considering only conventional risk factors. Additionally, these two SNPs were predicted to be located within the regulatory sequences, and rs6859 showed a substantial impact on m6A modification levels. Our findings suggest that m6A-SNPs rs6859 and rs10198139 confer an elevated risk of AAA, possibly by promoting local gene expression through an m6A-mediated manner.
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Affiliation(s)
- Tan Li
- Department of Cardiovascular Ultrasound, the First Hospital of China Medical University, Shenyang 110001, China
- Clinical Medical Research Center of Imaging in Liaoning Province, the First Hospital of China Medical University, Shenyang 110001, China
| | - Yijun Wu
- Tumor Etiology and Screening Department of Cancer Institute and General Surgery, the First Hospital of China Medical University, Shenyang 110001, China
- Key Laboratory of Cancer Etiology and Prevention in Liaoning Education Department, the First Hospital of China Medical University, Shenyang 110001, China
| | - Jun Yang
- Department of Cardiovascular Ultrasound, the First Hospital of China Medical University, Shenyang 110001, China
- Clinical Medical Research Center of Imaging in Liaoning Province, the First Hospital of China Medical University, Shenyang 110001, China
| | - Jingjing Jing
- Tumor Etiology and Screening Department of Cancer Institute and General Surgery, the First Hospital of China Medical University, Shenyang 110001, China
- Key Laboratory of Cancer Etiology and Prevention in Liaoning Education Department, the First Hospital of China Medical University, Shenyang 110001, China
| | - Chunyan Ma
- Department of Cardiovascular Ultrasound, the First Hospital of China Medical University, Shenyang 110001, China
- Clinical Medical Research Center of Imaging in Liaoning Province, the First Hospital of China Medical University, Shenyang 110001, China
| | - Liping Sun
- Tumor Etiology and Screening Department of Cancer Institute and General Surgery, the First Hospital of China Medical University, Shenyang 110001, China
- Key Laboratory of Cancer Etiology and Prevention in Liaoning Education Department, the First Hospital of China Medical University, Shenyang 110001, China
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8
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Gao H, Zhang M, Baylis RA, Wang F, Björkegren JLM, Kovacic JJ, Ruusalepp A, Leeper NJ. Computational protocol to identify shared transcriptional risks and mutually beneficial compounds between diseases. STAR Protoc 2024; 5:102883. [PMID: 38354084 PMCID: PMC10876979 DOI: 10.1016/j.xpro.2024.102883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 12/29/2023] [Accepted: 01/26/2024] [Indexed: 02/16/2024] Open
Abstract
The accumulation of omics and biobank resources allows for a genome-wide understanding of the shared pathologic mechanisms between diseases and for strategies to identify drugs that could be repurposed as novel treatments. Here, we present a computational protocol, implemented as a Snakemake workflow, to identify shared transcriptional processes and screen compounds that could result in mutual benefit. This protocol also includes a description of a pharmacovigilance study designed to validate the effect of compounds using electronic health records. For complete details on the use and execution of this protocol, please refer to Gao et al.1 and Baylis et al.2.
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Affiliation(s)
- Hua Gao
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford, CA 94305, USA.
| | - Mao Zhang
- Stanford Cardiovascular Institute, Stanford, CA 94305, USA
| | - Richard A Baylis
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford, CA 94305, USA; Department of Medicine, Division of Cardiology, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Fudi Wang
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford, CA 94305, USA
| | - Johan L M Björkegren
- Department of Medicine, Karolinska Institute, Huddinge, Sweden; Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jason J Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA; Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia; St. Vincent's Clinical School, University of NSW, Sydney, NSW, Australia
| | - Arno Ruusalepp
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Tartu, Estonia
| | - Nicholas J Leeper
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford, CA 94305, USA; Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
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9
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Prapiadou S, Živković L, Thorand B, George MJ, van der Laan SW, Malik R, Herder C, Koenig W, Ueland T, Kleveland O, Aukrust P, Gullestad L, Bernhagen J, Pasterkamp G, Peters A, Hingorani AD, Rosand J, Dichgans M, Anderson CD, Georgakis MK. Proteogenomic Data Integration Reveals CXCL10 as a Potentially Downstream Causal Mediator for IL-6 Signaling on Atherosclerosis. Circulation 2024; 149:669-683. [PMID: 38152968 PMCID: PMC10922752 DOI: 10.1161/circulationaha.123.064974] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 11/17/2023] [Indexed: 12/29/2023]
Abstract
BACKGROUND Genetic and experimental studies support a causal involvement of IL-6 (interleukin-6) signaling in atheroprogression. Although trials targeting IL-6 signaling are underway, any benefits must be balanced against an impaired host immune response. Dissecting the mechanisms that mediate the effects of IL-6 signaling on atherosclerosis could offer insights about novel drug targets with more specific effects. METHODS Leveraging data from 522 681 individuals, we constructed a genetic instrument of 26 variants in the gene encoding the IL-6R (IL-6 receptor) that proxied for pharmacological IL-6R inhibition. Using Mendelian randomization, we assessed its effects on 3281 plasma proteins quantified with an aptamer-based assay in the INTERVAL cohort (n=3301). Using mediation Mendelian randomization, we explored proteomic mediators of the effects of genetically proxied IL-6 signaling on coronary artery disease, large artery atherosclerotic stroke, and peripheral artery disease. For significant mediators, we tested associations of their circulating levels with incident cardiovascular events in a population-based study (n=1704) and explored the histological, transcriptomic, and cellular phenotypes correlated with their expression levels in samples from human atherosclerotic lesions. RESULTS We found significant effects of genetically proxied IL-6 signaling on 70 circulating proteins involved in cytokine production/regulation and immune cell recruitment/differentiation, which correlated with the proteomic effects of pharmacological IL-6R inhibition in a clinical trial. Among the 70 significant proteins, genetically proxied circulating levels of CXCL10 (C-X-C motif chemokine ligand 10) were associated with risk of coronary artery disease, large artery atherosclerotic stroke, and peripheral artery disease, with up to 67% of the effects of genetically downregulated IL-6 signaling on these end points mediated by decreases in CXCL10. Higher midlife circulating CXCL10 levels were associated with a larger number of cardiovascular events over 20 years, whereas higher CXCL10 expression in human atherosclerotic lesions correlated with a larger lipid core and a transcriptomic profile reflecting immune cell infiltration, adaptive immune system activation, and cytokine signaling. CONCLUSIONS Integrating multiomics data, we found a proteomic signature of IL-6 signaling activation and mediators of its effects on cardiovascular disease. Our analyses suggest the interferon-γ-inducible chemokine CXCL10 to be a potentially causal mediator for atherosclerosis in 3 vascular compartments and, as such, could serve as a promising drug target for atheroprotection.
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Affiliation(s)
- Savvina Prapiadou
- University of Patras School of Medicine, Patras, Greece
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Luka Živković
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Marc J. George
- Department of Clinical Pharmacology, Division of Medicine, University College London, London, United Kingdom
| | - Sander W. van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Rainer Malik
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research, Partner Düsseldorf, Neuherberg, Germany
| | - Wolfgang Koenig
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
- German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Thor Ueland
- Thrombosis Research Center (TREC), Division of internal medicine, University hospital of North Norway, Tromsø, Norway
- Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ola Kleveland
- Clinic of Cardiology, St Olavs Hospital, Trondheim, Norway
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Pål Aukrust
- Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Lars Gullestad
- Department of Cardiology Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Jürgen Bernhagen
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximilians-University Munich, Munich, Germany
- Munich Heart Alliance, German Center for Cardiovascular Health (DZHK e.V., partner-site Munich), Munich, Germany
| | - Aroon D. Hingorani
- Department of Clinical Pharmacology, Division of Medicine, University College London, London, United Kingdom
- Centre for Translational Genomics, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Jonathan Rosand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital Rikshospitalet, Oslo, Norway
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany
| | - Christopher D. Anderson
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Marios K. Georgakis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
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10
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Shahjahan, Dey JK, Dey SK. Translational bioinformatics approach to combat cardiovascular disease and cancers. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2024; 139:221-261. [PMID: 38448136 DOI: 10.1016/bs.apcsb.2023.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Bioinformatics is an interconnected subject of science dealing with diverse fields including biology, chemistry, physics, statistics, mathematics, and computer science as the key fields to answer complicated physiological problems. Key intention of bioinformatics is to store, analyze, organize, and retrieve essential information about genome, proteome, transcriptome, metabolome, as well as organisms to investigate the biological system along with its dynamics, if any. The outcome of bioinformatics depends on the type, quantity, and quality of the raw data provided and the algorithm employed to analyze the same. Despite several approved medicines available, cardiovascular disorders (CVDs) and cancers comprises of the two leading causes of human deaths. Understanding the unknown facts of both these non-communicable disorders is inevitable to discover new pathways, find new drug targets, and eventually newer drugs to combat them successfully. Since, all these goals involve complex investigation and handling of various types of macro- and small- molecules of the human body, bioinformatics plays a key role in such processes. Results from such investigation has direct human application and thus we call this filed as translational bioinformatics. Current book chapter thus deals with diverse scope and applications of this translational bioinformatics to find cure, diagnosis, and understanding the mechanisms of CVDs and cancers. Developing complex yet small or long algorithms to address such problems is very common in translational bioinformatics. Structure-based drug discovery or AI-guided invention of novel antibodies that too with super-high accuracy, speed, and involvement of considerably low amount of investment are some of the astonishing features of the translational bioinformatics and its applications in the fields of CVDs and cancers.
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Affiliation(s)
- Shahjahan
- Laboratory for Structural Biology of Membrane Proteins, Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
| | - Joy Kumar Dey
- Central Council for Research in Homoeopathy, Ministry of Ayush, Govt. of India, New Delhi, Delhi, India
| | - Sanjay Kumar Dey
- Laboratory for Structural Biology of Membrane Proteins, Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India.
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11
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Oliveri A, Rebernick RJ, Kuppa A, Pant A, Chen Y, Du X, Cushing KC, Bell HN, Raut C, Prabhu P, Chen VL, Halligan BD, Speliotes EK. Comprehensive genetic study of the insulin resistance marker TG:HDL-C in the UK Biobank. Nat Genet 2024; 56:212-221. [PMID: 38200128 PMCID: PMC10923176 DOI: 10.1038/s41588-023-01625-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 11/28/2023] [Indexed: 01/12/2024]
Abstract
Insulin resistance (IR) is a well-established risk factor for metabolic disease. The ratio of triglycerides to high-density lipoprotein cholesterol (TG:HDL-C) is a surrogate marker of IR. We conducted a genome-wide association study of the TG:HDL-C ratio in 402,398 Europeans within the UK Biobank. We identified 369 independent SNPs, of which 114 had a false discovery rate-adjusted P value < 0.05 in other genome-wide studies of IR making them high-confidence IR-associated loci. Seventy-two of these 114 loci have not been previously associated with IR. These 114 loci cluster into five groups upon phenome-wide analysis and are enriched for candidate genes important in insulin signaling, adipocyte physiology and protein metabolism. We created a polygenic-risk score from the high-confidence IR-associated loci using 51,550 European individuals in the Michigan Genomics Initiative. We identified associations with diabetes, hyperglyceridemia, hypertension, nonalcoholic fatty liver disease and ischemic heart disease. Collectively, this study provides insight into the genes, pathways, tissues and subtypes critical in IR.
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Affiliation(s)
- Antonino Oliveri
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Ryan J Rebernick
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Annapurna Kuppa
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Asmita Pant
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Yanhua Chen
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Xiaomeng Du
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Kelly C Cushing
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Hannah N Bell
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA
| | - Chinmay Raut
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Ponnandy Prabhu
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Vincent L Chen
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Brian D Halligan
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Elizabeth K Speliotes
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
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12
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Hodonsky CJ, Turner AW, Khan MD, Barrientos NB, Methorst R, Ma L, Lopez NG, Mosquera JV, Auguste G, Farber E, Ma WF, Wong D, Onengut-Gumuscu S, Kavousi M, Peyser PA, van der Laan SW, Leeper NJ, Kovacic JC, Björkegren JLM, Miller CL. Multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci. CELL GENOMICS 2024; 4:100465. [PMID: 38190101 PMCID: PMC10794848 DOI: 10.1016/j.xgen.2023.100465] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 09/07/2023] [Accepted: 11/19/2023] [Indexed: 01/09/2024]
Abstract
Genome-wide association studies (GWASs) have identified hundreds of risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWASs, and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotypes to identify quantitative trait loci for expression (eQTLs) and splicing (sQTLs) in coronary arteries from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary artery; 19% exhibited cell-type-specific expression. Colocalization revealed subgroups of eGenes unique to CAD and blood pressure GWAS. Fine-mapping highlighted additional eGenes, including TBX20 and IL5. We also identified sQTLs for 1,690 genes, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing to accurately identify disease-relevant isoform expression. Our work provides a patient-derived coronary artery eQTL resource and exemplifies the need for diverse study populations and multifaceted approaches to characterize gene regulation in disease processes.
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Affiliation(s)
- Chani J Hodonsky
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Adam W Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Mohammad Daud Khan
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Nelson B Barrientos
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Ruben Methorst
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Nicolas G Lopez
- Division of Vascular Surgery, Department of Surgery, Stanford University, Stanford, CA 94305, USA
| | - Jose Verdezoto Mosquera
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
| | - Gaëlle Auguste
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Emily Farber
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Wei Feng Ma
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Medical Scientist Training Program, Department of Pathology, University of Virginia, Charlottesville, VA 22908, USA
| | - Doris Wong
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, 3000 CA Rotterdam, the Netherlands
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan, Ann Arbor, MI 48019, USA
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Nicholas J Leeper
- Division of Vascular Surgery, Department of Surgery, Stanford University, Stanford, CA 94305, USA
| | - Jason C Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia; St. Vincent's Clinical School, University of New South Wales, Sydney, NSW 2052, Australia
| | - 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 10029, USA; Department of Medicine, Huddinge, Karolinska Institutet, 141 52 Huddinge, Sweden
| | - Clint L Miller
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Division of Vascular Surgery, Department of Surgery, Stanford University, Stanford, CA 94305, USA; Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA.
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13
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Kurt Z, Cheng J, Barrere-Cain R, McQuillen CN, Saleem Z, Hsu N, Jiang N, Pan C, Franzén O, Koplev S, Wang S, Björkegren J, Lusis AJ, Blencowe M, Yang X. Shared and distinct pathways and networks genetically linked to coronary artery disease between human and mouse. eLife 2023; 12:RP88266. [PMID: 38060277 PMCID: PMC10703441 DOI: 10.7554/elife.88266] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023] Open
Abstract
Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.
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Affiliation(s)
- Zeyneb Kurt
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
- The Information School at the University of SheffieldSheffieldUnited Kingdom
| | - Jenny Cheng
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
- Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Rio Barrere-Cain
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Caden N McQuillen
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Zara Saleem
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Neil Hsu
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Nuoya Jiang
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Calvin Pan
- Department of Medicine, Division of Cardiology, University of California, Los AngelesLos AngelesUnited States
| | - Oscar Franzén
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount SinaiNew YorkUnited States
| | - Simon Koplev
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount SinaiNew YorkUnited States
| | - Susanna Wang
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Johan Björkegren
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount SinaiNew YorkUnited States
- Department of Medicine, (Huddinge), Karolinska InstitutetHuddingeSweden
| | - Aldons J Lusis
- Department of Medicine, Division of Cardiology, University of California, Los AngelesLos AngelesUnited States
- Departments of Human Genetics & Microbiology, Immunology, and Molecular Genetics, UCLALos AngelesUnited States
- Cardiovascular Research Laboratory, David Geffen School of Medicine, UCLALos AngelesUnited States
| | - Montgomery Blencowe
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
- Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
- Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los AngelesLos AngelesUnited States
- Interdepartmental Program of Bioinformatics, University of California, Los AngelesLos AngelesUnited States
- Department of Molecular and Medical Pharmacology, University of California, Los AngelesLos AngelesUnited States
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14
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Stacey SN, Zink F, Halldorsson GH, Stefansdottir L, Gudjonsson SA, Einarsson G, Hjörleifsson G, Eiriksdottir T, Helgadottir A, Björnsdottir G, Thorgeirsson TE, Olafsdottir TA, Jonsdottir I, Gretarsdottir S, Tragante V, Magnusson MK, Jonsson H, Gudmundsson J, Olafsson S, Holm H, Gudbjartsson DF, Sulem P, Helgason A, Thorsteinsdottir U, Tryggvadottir L, Rafnar T, Melsted P, Ulfarsson MÖ, Vidarsson B, Thorleifsson G, Stefansson K. Genetics and epidemiology of mutational barcode-defined clonal hematopoiesis. Nat Genet 2023; 55:2149-2159. [PMID: 37932435 PMCID: PMC10703693 DOI: 10.1038/s41588-023-01555-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 09/28/2023] [Indexed: 11/08/2023]
Abstract
Clonal hematopoiesis (CH) arises when a substantial proportion of mature blood cells is derived from a single hematopoietic stem cell lineage. Using whole-genome sequencing of 45,510 Icelandic and 130,709 UK Biobank participants combined with a mutational barcode method, we identified 16,306 people with CH. Prevalence approaches 50% in elderly participants. Smoking demonstrates a dosage-dependent impact on risk of CH. CH associates with several smoking-related diseases. Contrary to published claims, we find no evidence that CH is associated with cardiovascular disease. We provide evidence that CH is driven by genes that are commonly mutated in myeloid neoplasia and implicate several new driver genes. The presence and nature of a driver mutation alters the risk profile for hematological disorders. Nevertheless, most CH cases have no known driver mutations. A CH genome-wide association study identified 25 loci, including 19 not implicated previously in CH. Splicing, protein and expression quantitative trait loci were identified for CD164 and TCL1A.
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Affiliation(s)
| | | | - Gisli H Halldorsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | | | | | | | - Thorunn A Olafsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Ingileif Jonsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Immunology, Landspitali University Hospital, Reykjavik, Iceland
| | | | | | - Magnus K Magnusson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Agnar Helgason
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Department of Anthropology, University of Iceland, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Pall Melsted
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Magnus Ö Ulfarsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Brynjar Vidarsson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Hematology, Landspitali University Hospital, Reykjavik, Iceland
| | | | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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15
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Cheng J, Cheng M, Lusis AJ, Yang X. Gene Regulatory Networks in Coronary Artery Disease. Curr Atheroscler Rep 2023; 25:1013-1023. [PMID: 38008808 DOI: 10.1007/s11883-023-01170-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/09/2023] [Indexed: 11/28/2023]
Abstract
PURPOSE OF REVIEW Coronary artery disease is a complex disorder and the leading cause of mortality worldwide. As technologies for the generation of high-throughput multiomics data have advanced, gene regulatory network modeling has become an increasingly powerful tool in understanding coronary artery disease. This review summarizes recent and novel gene regulatory network tools for bulk tissue and single cell data, existing databases for network construction, and applications of gene regulatory networks in coronary artery disease. RECENT FINDINGS New gene regulatory network tools can integrate multiomics data to elucidate complex disease mechanisms at unprecedented cellular and spatial resolutions. At the same time, updates to coronary artery disease expression data in existing databases have enabled researchers to build gene regulatory networks to study novel disease mechanisms. Gene regulatory networks have proven extremely useful in understanding CAD heritability beyond what is explained by GWAS loci and in identifying mechanisms and key driver genes underlying disease onset and progression. Gene regulatory networks can holistically and comprehensively address the complex nature of coronary artery disease. In this review, we discuss key algorithmic approaches to construct gene regulatory networks and highlight state-of-the-art methods that model specific modes of gene regulation. We also explore recent applications of these tools in coronary artery disease patient data repositories to understand disease heritability and shared and distinct disease mechanisms and key driver genes across tissues, between sexes, and between species.
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Grants
- DK120342, HL148577, and HL147883 (AJL). NS111378, NS117148, HL147883 (XY) NIH HHS
- DK120342, HL148577, and HL147883 (AJL). NS111378, NS117148, HL147883 (XY) NIH HHS
- DK120342, HL148577, and HL147883 (AJL). NS111378, NS117148, HL147883 (XY) NIH HHS
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Affiliation(s)
- Jenny Cheng
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
- Molecular, Cellular and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Michael Cheng
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Aldons J Lusis
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, 650 Charles E Young Drive South, Los Angeles, CA, 90095, USA.
- Departments of Human Genetics & Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, 650 Charles E. Young Drive South, Los Angeles, CA, 90095, USA.
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
- Molecular, Cellular and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
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16
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Russo MA, Garaci E, Frustaci A, Fini M, Costantini C, Oikonomou V, Nunzi E, Puccetti P, Romani L. Host-microbe tryptophan partitioning in cardiovascular diseases. Pharmacol Res 2023; 198:106994. [PMID: 37972721 DOI: 10.1016/j.phrs.2023.106994] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/27/2023] [Accepted: 11/13/2023] [Indexed: 11/19/2023]
Abstract
The functional interdependencies between the molecular components of a biological process demand for a network medicine platform that integrates systems biology and network science, to explore the interactions among biological components in health and disease. Access to large-scale omics datasets (genomics, transcriptomics, proteomics, metabolomics, metagenomics, phenomics, etc.) has significantly advanced our opportunity along this direction. Studies utilizing these techniques have begun to provide us with a deeper understanding of how the interaction between the intestinal microbes and their host affects the cardiovascular system in health and disease. Within the framework of a multiomics network approach, we highlight here how tryptophan metabolism may orchestrate the host-microbes interaction in cardiovascular diseases and the implications for precision medicine and therapeutics, including nutritional interventions.
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Affiliation(s)
- Matteo Antonio Russo
- University San Raffaele and Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele, 00166 Rome, Italy
| | - Enrico Garaci
- University San Raffaele and Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele, 00166 Rome, Italy
| | - Andrea Frustaci
- University San Raffaele and Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele, 00166 Rome, Italy
| | - Massimo Fini
- University San Raffaele and Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele, 00166 Rome, Italy
| | - Claudio Costantini
- Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Vasileios Oikonomou
- Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Emilia Nunzi
- Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Paolo Puccetti
- Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Luigina Romani
- University San Raffaele and Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele, 00166 Rome, Italy; Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy.
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17
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Savić R, Yang J, Koplev S, An MC, Patel PL, O'Brien RN, Dubose BN, Dodatko T, Rogatsky E, Sukhavasi K, Ermel R, Ruusalepp A, Houten SM, Kovacic JC, Stewart AF, Yohn CB, Schadt EE, Laberge RM, Björkegren JLM, Tu Z, Argmann C. Integration of transcriptomes of senescent cell models with multi-tissue patient samples reveals reduced COL6A3 as an inducer of senescence. Cell Rep 2023; 42:113371. [PMID: 37938972 PMCID: PMC10955802 DOI: 10.1016/j.celrep.2023.113371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 05/23/2023] [Accepted: 10/17/2023] [Indexed: 11/10/2023] Open
Abstract
Senescent cells are a major contributor to age-dependent cardiovascular tissue dysfunction, but knowledge of their in vivo cell markers and tissue context is lacking. To reveal tissue-relevant senescence biology, we integrate the transcriptomes of 10 experimental senescence cell models with a 224 multi-tissue gene co-expression network based on RNA-seq data of seven tissues biopsies from ∼600 coronary artery disease (CAD) patients. We identify 56 senescence-associated modules, many enriched in CAD GWAS genes and correlated with cardiometabolic traits-which supports universality of senescence gene programs across tissues and in CAD. Cross-tissue network analyses reveal 86 candidate senescence-associated secretory phenotype (SASP) factors, including COL6A3. Experimental knockdown of COL6A3 induces transcriptional changes that overlap the majority of the experimental senescence models, with cell-cycle arrest linked to modulation of DREAM complex-targeted genes. We provide a transcriptomic resource for cellular senescence and identify candidate biomarkers, SASP factors, and potential drivers of senescence in human tissues.
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Affiliation(s)
- Radoslav Savić
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Jialiang Yang
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Simon Koplev
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK
| | - Mahru C An
- UNITY Biotechnology, South San Francisco, CA 94080, USA
| | | | | | | | - Tetyana Dodatko
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Eduard Rogatsky
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Katyayani Sukhavasi
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Raili Ermel
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Arno Ruusalepp
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia; Clinical Gene Networks AB, Stockholm, Sweden
| | - Sander M Houten
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Jason C Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA; Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia; St. Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Andrew F Stewart
- Diabetes Obesity Metabolism Institute, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Eric E Schadt
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | | | - Johan L M Björkegren
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA; Clinical Gene Networks AB, Stockholm, Sweden; Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Zhidong Tu
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Carmen Argmann
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA.
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18
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Diez Benavente E, Karnewar S, Buono M, Mili E, Hartman RJ, Kapteijn D, Slenders L, Daniels M, Aherrahrou R, Reinberger T, Mol BM, de Borst GJ, de Kleijn DP, Prange KH, Depuydt MA, de Winther MP, Kuiper J, Björkegren JL, Erdmann J, Civelek M, Mokry M, Owens GK, Pasterkamp G, den Ruijter HM. Female Gene Networks Are Expressed in Myofibroblast-Like Smooth Muscle Cells in Vulnerable Atherosclerotic Plaques. Arterioscler Thromb Vasc Biol 2023; 43:1836-1850. [PMID: 37589136 PMCID: PMC10521798 DOI: 10.1161/atvbaha.123.319325] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/10/2023] [Indexed: 08/18/2023]
Abstract
BACKGROUND Women presenting with coronary artery disease more often present with fibrous atherosclerotic plaques, which are currently understudied. Phenotypically modulated smooth muscle cells (SMCs) contribute to atherosclerosis in women. How these phenotypically modulated SMCs shape female versus male plaques is unknown. METHODS Gene regulatory networks were created using RNAseq gene expression data from human carotid atherosclerotic plaques. The networks were prioritized based on sex bias, relevance for smooth muscle biology, and coronary artery disease genetic enrichment. Network expression was linked to histologically determined plaque phenotypes. In addition, their expression in plaque cell types was studied at single-cell resolution using single-cell RNAseq. Finally, their relevance for disease progression was studied in female and male Apoe-/- mice fed a Western diet for 18 and 30 weeks. RESULTS Here, we identify multiple sex-stratified gene regulatory networks from human carotid atherosclerotic plaques. Prioritization of the female networks identified 2 main SMC gene regulatory networks in late-stage atherosclerosis. Single-cell RNA sequencing mapped these female networks to 2 SMC phenotypes: a phenotypically modulated myofibroblast-like SMC network and a contractile SMC network. The myofibroblast-like network was mostly expressed in plaques that were vulnerable in women. Finally, the mice ortholog of key driver gene MFGE8 (milk fat globule EGF and factor V/VIII domain containing) showed retained expression in advanced plaques from female mice but was downregulated in male mice during atherosclerosis progression. CONCLUSIONS Female atherosclerosis is characterized by gene regulatory networks that are active in fibrous vulnerable plaques rich in myofibroblast-like SMCs.
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Affiliation(s)
- Ernest Diez Benavente
- Laboratory of Experimental Cardiology (E.D.B., M.B., E.M., R.J.G.H., D.K., M.D., H.M.d.R.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Santosh Karnewar
- Robert M. Berne Cardiovascular Research Center (S.K., G.K.O.), University of Virginia, Charlottesville
| | - Michele Buono
- Laboratory of Experimental Cardiology (E.D.B., M.B., E.M., R.J.G.H., D.K., M.D., H.M.d.R.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Eloi Mili
- Laboratory of Experimental Cardiology (E.D.B., M.B., E.M., R.J.G.H., D.K., M.D., H.M.d.R.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Robin J.G. Hartman
- Laboratory of Experimental Cardiology (E.D.B., M.B., E.M., R.J.G.H., D.K., M.D., H.M.d.R.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Daniek Kapteijn
- Laboratory of Experimental Cardiology (E.D.B., M.B., E.M., R.J.G.H., D.K., M.D., H.M.d.R.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Lotte Slenders
- Central Diagnostic Laboratory (L.S., M.M., G.P.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Mark Daniels
- Laboratory of Experimental Cardiology (E.D.B., M.B., E.M., R.J.G.H., D.K., M.D., H.M.d.R.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Redouane Aherrahrou
- Center for Public Health Genomics (R.A., M.C.), University of Virginia, Charlottesville
- Institute for Cardiogenetics, University of Lübeck, Germany (R.A., T.R., J.E.)
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland (R.A.)
| | - Tobias Reinberger
- Institute for Cardiogenetics, University of Lübeck, Germany (R.A., T.R., J.E.)
| | - Barend M. Mol
- Department of Vascular Surgery (B.M.M., G.J.d.B., D.P.V.d.K.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Gert J. de Borst
- Department of Vascular Surgery (B.M.M., G.J.d.B., D.P.V.d.K.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Dominique P.V. de Kleijn
- Department of Vascular Surgery (B.M.M., G.J.d.B., D.P.V.d.K.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Koen H.M. Prange
- Experimental Vascular Biology, Department of Medical Biochemistry, Amsterdam University Medical Centers — location AMC, University of Amsterdam, Netherlands (K.H.M.P., M.P.J.d.W.)
| | - Marie A.C. Depuydt
- Division of BioTherapeutics, Leiden Academic Centre for Drug Research, Leiden University, the Netherlands (M.A.C.D., J.K.)
| | - Menno P.J. de Winther
- Experimental Vascular Biology, Department of Medical Biochemistry, Amsterdam University Medical Centers — location AMC, University of Amsterdam, Netherlands (K.H.M.P., M.P.J.d.W.)
| | - Johan Kuiper
- Division of BioTherapeutics, Leiden Academic Centre for Drug Research, Leiden University, the Netherlands (M.A.C.D., J.K.)
| | - Johan L.M. Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York (J.L.M.B.)
- Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden (J.L.M.B.)
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Germany (R.A., T.R., J.E.)
| | - Mete Civelek
- Center for Public Health Genomics (R.A., M.C.), University of Virginia, Charlottesville
- Department of Biomedical Engineering (M.C.)
- University of Virginia, Charlottesville (M.C.)
| | - Michal Mokry
- Central Diagnostic Laboratory (L.S., M.M., G.P.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Gary K. Owens
- Robert M. Berne Cardiovascular Research Center (S.K., G.K.O.), University of Virginia, Charlottesville
| | - Gerard Pasterkamp
- Central Diagnostic Laboratory (L.S., M.M., G.P.), University Medical Centre Utrecht, Utrecht University, the Netherlands
| | - Hester M. den Ruijter
- Laboratory of Experimental Cardiology (E.D.B., M.B., E.M., R.J.G.H., D.K., M.D., H.M.d.R.), University Medical Centre Utrecht, Utrecht University, the Netherlands
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19
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Kavousi M, Bos MM, Barnes HJ, Lino Cardenas CL, Wong D, Lu H, Hodonsky CJ, Landsmeer LPL, Turner AW, Kho M, Hasbani NR, de Vries PS, Bowden DW, Chopade S, Deelen J, Benavente ED, Guo X, Hofer E, Hwang SJ, Lutz SM, Lyytikäinen LP, Slenders L, Smith AV, Stanislawski MA, van Setten J, Wong Q, Yanek LR, Becker DM, Beekman M, Budoff MJ, Feitosa MF, Finan C, Hilliard AT, Kardia SLR, Kovacic JC, Kral BG, Langefeld CD, Launer LJ, Malik S, Hoesein FAAM, Mokry M, Schmidt R, Smith JA, Taylor KD, Terry JG, van der Grond J, van Meurs J, Vliegenthart R, Xu J, Young KA, Zilhão NR, Zweiker R, Assimes TL, Becker LC, Bos D, Carr JJ, Cupples LA, de Kleijn DPV, de Winther M, den Ruijter HM, Fornage M, Freedman BI, Gudnason V, Hingorani AD, Hokanson JE, Ikram MA, Išgum I, Jacobs DR, Kähönen M, Lange LA, Lehtimäki T, Pasterkamp G, Raitakari OT, Schmidt H, Slagboom PE, Uitterlinden AG, Vernooij MW, Bis JC, Franceschini N, Psaty BM, Post WS, Rotter JI, Björkegren JLM, O'Donnell CJ, Bielak LF, Peyser PA, Malhotra R, van der Laan SW, Miller CL. Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification. Nat Genet 2023; 55:1651-1664. [PMID: 37770635 PMCID: PMC10601987 DOI: 10.1038/s41588-023-01518-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 08/29/2023] [Indexed: 09/30/2023]
Abstract
Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.
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Affiliation(s)
- Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
| | - Maxime M Bos
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Hanna J Barnes
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Christian L Lino Cardenas
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Doris Wong
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Haojie Lu
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Chani J Hodonsky
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Lennart P L Landsmeer
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Adam W Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea
| | - Natalie R Hasbani
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Center at Houston, Houston, TX, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Center at Houston, Houston, TX, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Sandesh Chopade
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- University College London British Heart Foundation Research Accelerator Centre, London, UK
| | - Joris Deelen
- Biomedical Data Sciences, Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Max Planck Institute for Biology of Aging, Cologne, Germany
| | - Ernest Diez Benavente
- Laboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Edith Hofer
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University of Graz, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | | | - Sharon M Lutz
- Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care, Boston, MA, USA
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Lotte Slenders
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Albert V Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Icelandic Heart Association, Kopavogur, Iceland
| | - Maggie A Stanislawski
- Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Jessica van Setten
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Quenna Wong
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Diane M Becker
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marian Beekman
- Biomedical Data Sciences, Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Matthew J Budoff
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Mary F Feitosa
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Chris Finan
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- University College London British Heart Foundation Research Accelerator Centre, London, UK
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | | | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jason C Kovacic
- Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia
- St Vincent's Clinical School, University of NSW, Sydney, New South Wales, Australia
- The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Brian G Kral
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences and Data Science, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Shaista Malik
- Susan Samueli Integrative Health Institute, Department of Medicine, University of California Irvine, Irvine, CA, USA
| | | | - Michal Mokry
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Laboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Reinhold Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University of Graz, Graz, Austria
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - James G Terry
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeroen van der Grond
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Joyce van Meurs
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jianzhao Xu
- Department of Biochemistry, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Kendra A Young
- Department of Epidemiology, University of Colorado, Anschutz Medical Campus, Denver, CO, USA
| | | | - Robert Zweiker
- Department of Internal Medicine, Division of Cardiology, Medical University of Graz, Graz, Austria
| | - Themistocles L Assimes
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Lewis C Becker
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Bos
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - J Jeffrey Carr
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - L Adrienne Cupples
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - Dominique P V de Kleijn
- Department of Vascular Surgery, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Menno de Winther
- Department of Medical Biochemistry, Experimental Vascular Biology, Amsterdam Cardiovascular Sciences: Atherosclerosis and Ischemic syndromes, Amsterdam Infection and Immunity: Inflammatory diseases, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Hester M den Ruijter
- Laboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Myriam Fornage
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Barry I Freedman
- Department of Internal Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, School of Public Health, University of Iceland, Reykjavik, Iceland
| | - Aroon D Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- University College London British Heart Foundation Research Accelerator Centre, London, UK
| | - John E Hokanson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Ivana Išgum
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Leslie A Lange
- Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Helena Schmidt
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Medical University of Graz, Graz, Austria
| | - P Eline Slagboom
- Biomedical Data Sciences, Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Vascular Surgery, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Departments of Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Wendy S Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, 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 City, NY, USA
- Department of Medicine, Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge, Sweden
| | - Christopher J O'Donnell
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Cardiology Section, Department of Medicine, Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Rajeev Malhotra
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Clint L Miller
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA.
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA.
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20
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Kurt Z, Cheng J, McQuillen CN, Saleem Z, Hsu N, Jiang N, Barrere-Cain R, Pan C, Franzen O, Koplev S, Wang S, Bjorkegren J, Lusis AJ, Blencowe M, Yang X. Shared and distinct pathways and networks genetically linked to coronary artery disease between human and mouse. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.08.544148. [PMID: 37333408 PMCID: PMC10274918 DOI: 10.1101/2023.06.08.544148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.
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Affiliation(s)
- Zeyneb Kurt
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
- Department of Computer and Information Sciences, University of Northumbria, Ellison Pl, Newcastle upon Tyne NE1 8ST, UK
| | - Jenny Cheng
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
- Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
| | - Caden N. McQuillen
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
| | - Zara Saleem
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
| | - Neil Hsu
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
| | - Nuoya Jiang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
| | - Rio Barrere-Cain
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
| | - Calvin Pan
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, 650 Charles E Young Drive South, Los Angeles, CA 90095-1679, USA
| | - Oscar Franzen
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029-6574, US
| | - Simon Koplev
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029-6574, US
| | - Susanna Wang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
| | - Johan Bjorkegren
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029-6574, US
- Department of Medicine, (Huddinge), Karolinska Institutet, 141 57 Huddinge, Sweden
| | - Aldons J. Lusis
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, 650 Charles E Young Drive South, Los Angeles, CA 90095-1679, USA
- Departments of Human Genetics & Microbiology, Immunology, and Molecular Genetics, UCLA, CA 90095, USA
- Cardiovascular Research Laboratory, David Geffen School of Medicine, UCLA, CA 90095
| | - Montgomery Blencowe
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
- Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
- Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
- Interdepartmental Program of Bioinformatics, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA
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21
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Baylis RA, Gao H, Wang F, Bell CF, Luo L, Björkegren JL, Leeper NJ. Identifying shared transcriptional risk patterns between atherosclerosis and cancer. iScience 2023; 26:107513. [PMID: 37636064 PMCID: PMC10448075 DOI: 10.1016/j.isci.2023.107513] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/18/2023] [Accepted: 07/27/2023] [Indexed: 08/29/2023] Open
Abstract
Cancer and cardiovascular disease (CVD) are the leading causes of death worldwide. Numerous overlapping pathophysiologic mechanisms have been hypothesized to drive the development of both diseases. Further investigation of these common pathways could allow for the identification of mutually detrimental processes and therapeutic targeting to derive mutual benefit. In this study, we intersect transcriptomic datasets correlated with disease severity or patient outcomes for both cancer and atherosclerotic CVD. These analyses confirmed numerous pathways known to underlie both diseases, such as inflammation and hypoxia, but also identified several novel shared pathways. We used these to explore common translational targets by applying the drug prediction software, OCTAD, to identify compounds that simultaneously reverse the gene expression signature for both diseases. These analyses suggest that certain tumor-specific therapeutic approaches may be implemented so that they avoid cardiovascular consequences, and in some cases may even be used to simultaneously target co-prevalent cancer and atherosclerosis.
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Affiliation(s)
- Richard A. Baylis
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford, CA, USA
- Department of Medicine, Division of Cardiology, University of California, San Francisco, CA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Hua Gao
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford, CA, USA
| | - Fudi Wang
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford, CA, USA
| | - Caitlin F. Bell
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Lingfeng Luo
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford, CA, USA
| | - Johan L.M. Björkegren
- Department of Medicine, Karolinska Institute, Huddinge, Sweden
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nicholas J. Leeper
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
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22
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Reed JN, Huang J, Li Y, Ma L, Banka D, Wabitsch M, Wang T, Ding W, Björkegren JLM, Civelek M. Systems genetics analysis of human body fat distribution genes identifies Wnt signaling and mitochondrial activity in adipocytes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.06.556534. [PMID: 37732278 PMCID: PMC10508754 DOI: 10.1101/2023.09.06.556534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
BACKGROUND Excess fat in the abdomen is a sexually dimorphic risk factor for cardio-metabolic disease. The relative storage between abdominal and lower-body subcutaneous adipose tissue depots is approximated by the waist-to-hip ratio adjusted for body mass index (WHRadjBMI). Genome-wide association studies (GWAS) identified 346 loci near 495 genes associated with WHRadjBMI. Most of these genes have unknown roles in fat distribution, but many are expressed and putatively act in adipose tissue. We aimed to identify novel sex- and depot-specific drivers of WHRadjBMI using a systems genetics approach. METHODS We used two independent cohorts of adipose tissue gene expression with 362 - 444 males and 147 - 219 females, primarily of European ancestry. We constructed sex- and depot- specific Bayesian networks to model the gene-gene interactions from 8,492 adipose tissue genes. Key driver analysis identified genes that, in silico and putatively in vitro, regulate many others, including the 495 WHRadjBMI GWAS genes. Key driver gene function was determined by perturbing their expression in human subcutaneous pre-adipocytes using lenti-virus or siRNA. RESULTS 51 - 119 key drivers in each network were replicated in both cohorts. We used single-cell expression data to select replicated key drivers expressed in adipocyte precursors and mature adipocytes, prioritized genes which have not been previously studied in adipose tissue, and used public human and mouse data to nominate 53 novel key driver genes (10 - 21 from each network) that may regulate fat distribution by altering adipocyte function. In other cell types, 23 of these genes are found in crucial adipocyte pathways: Wnt signaling or mitochondrial function. We selected seven genes whose expression is highly correlated with WHRadjBMI to further study their effects on adipogenesis/Wnt signaling (ANAPC2, PSME3, RSPO1, TYRO3) or mitochondrial function (C1QTNF3, MIGA1, PSME3, UBR1).Adipogenesis was inhibited in cells overexpressing ANAPC2 and RSPO1 compared to controls. RSPO1 results are consistent with a positive correlation between gene expression in the subcutaneous depot and WHRadjBMI, therefore lower relative storage in the subcutaneous depot. RSPO1 inhibited adipogenesis by increasing β-catenin activation and Wnt-related transcription, thus repressing PPARG and CEBPA. PSME3 overexpression led to more adipogenesis than controls. In differentiated adipocytes, MIGA1 and UBR1 downregulation led to mitochondrial dysfunction, with lower oxygen consumption than controls; MIGA1 knockdown also lowered UCP1 expression. SUMMARY ANAPC2, MIGA1, PSME3, RSPO1, and UBR1 affect adipocyte function and may drive body fat distribution.
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23
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Bankier S, Wang L, Crawford A, Morgan RA, Ruusalepp A, Andrew R, Björkegren JLM, Walker BR, Michoel T. Plasma cortisol-linked gene networks in hepatic and adipose tissues implicate corticosteroid-binding globulin in modulating tissue glucocorticoid action and cardiovascular risk. Front Endocrinol (Lausanne) 2023; 14:1186252. [PMID: 37745713 PMCID: PMC10513085 DOI: 10.3389/fendo.2023.1186252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 07/14/2023] [Indexed: 09/26/2023] Open
Abstract
Genome-wide association meta-analysis (GWAMA) by the Cortisol Network (CORNET) consortium identified genetic variants spanning the SERPINA6/SERPINA1 locus on chromosome 14 associated with morning plasma cortisol, cardiovascular disease (CVD), and SERPINA6 mRNA expression encoding corticosteroid-binding globulin (CBG) in the liver. These and other findings indicate that higher plasma cortisol levels are causally associated with CVD; however, the mechanisms by which variations in CBG lead to CVD are undetermined. Using genomic and transcriptomic data from The Stockholm Tartu Atherosclerosis Reverse Networks Engineering Task (STARNET) study, we identified plasma cortisol-linked single-nucleotide polymorphisms (SNPs) that are trans-associated with genes from seven different vascular and metabolic tissues, finding the highest representation of trans-genes in the liver, subcutaneous fat, and visceral abdominal fat, [false discovery rate (FDR) = 15%]. We identified a subset of cortisol-associated trans-genes that are putatively regulated by the glucocorticoid receptor (GR), the primary transcription factor activated by cortisol. Using causal inference, we identified GR-regulated trans-genes that are responsible for the regulation of tissue-specific gene networks. Cis-expression Quantitative Trait Loci (eQTLs) were used as genetic instruments for identification of pairwise causal relationships from which gene networks could be reconstructed. Gene networks were identified in the liver, subcutaneous fat, and visceral abdominal fat, including a high confidence gene network specific to subcutaneous adipose (FDR = 10%) under the regulation of the interferon regulatory transcription factor, IRF2. These data identify a plausible pathway through which variation in the liver CBG production perturbs cortisol-regulated gene networks in peripheral tissues and thereby promote CVD.
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Affiliation(s)
- Sean Bankier
- University/BHF Centre for Cardiovascular Science, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
- Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Edinburgh, United Kingdom
| | - Lingfei Wang
- Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew Crawford
- University/BHF Centre for Cardiovascular Science, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Ruth A. Morgan
- University/BHF Centre for Cardiovascular Science, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
- SRUC, The Roslin Institute, Edinburgh, United Kingdom
| | - Arno Ruusalepp
- Department of Cardiac Surgery, Tartu University Hospital, Tartu, Estonia
- Department of Cardiology, Institute of Clinical Medicine, Tartu University, Tartu, Estonia
- Clinical Gene Networks AB, Stockholm, Sweden
| | - Ruth Andrew
- University/BHF Centre for Cardiovascular Science, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Johan L. M. Björkegren
- Clinical Gene Networks AB, Stockholm, Sweden
- Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Brian R. Walker
- University/BHF Centre for Cardiovascular Science, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
- Clinical and Translational Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Tom Michoel
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
- Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Edinburgh, United Kingdom
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24
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Shapiro D, Lee K, Asmussen J, Bourquard T, Lichtarge O. Evolutionary Action-Machine Learning Model Identifies Candidate Genes Associated With Early-Onset Coronary Artery Disease. J Am Heart Assoc 2023; 12:e029103. [PMID: 37642027 PMCID: PMC10547338 DOI: 10.1161/jaha.122.029103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 07/11/2023] [Indexed: 08/31/2023]
Abstract
Background Coronary artery disease is a primary cause of death around the world, with both genetic and environmental risk factors. Although genome-wide association studies have linked >100 unique loci to its genetic basis, these only explain a fraction of disease heritability. Methods and Results To find additional gene drivers of coronary artery disease, we applied machine learning to quantitative evolutionary information on the impact of coding variants in whole exomes from the Myocardial Infarction Genetics Consortium. Using ensemble-based supervised learning, the Evolutionary Action-Machine Learning framework ranked each gene's ability to classify case and control samples and identified 79 significant associations. These were connected to known risk loci; enriched in cardiovascular processes like lipid metabolism, blood clotting, and inflammation; and enriched for cardiovascular phenotypes in knockout mouse models. Among them, INPP5F and MST1R are examples of potentially novel coronary artery disease risk genes that modulate immune signaling in response to cardiac stress. Conclusions We concluded that machine learning on the functional impact of coding variants, based on a massive amount of evolutionary information, has the power to suggest novel coronary artery disease risk genes for mechanistic and therapeutic discoveries in cardiovascular biology, and should also apply in other complex polygenic diseases.
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Affiliation(s)
- Dillon Shapiro
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTXUSA
| | - Kwanghyuk Lee
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTXUSA
| | - Jennifer Asmussen
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTXUSA
| | - Thomas Bourquard
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTXUSA
| | - Olivier Lichtarge
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTXUSA
- Computational & Integrative Biomedical Research CenterBaylor College of MedicineHoustonTXUSA
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25
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von Scheidt M, Bauer S, Ma A, Hao K, Kessler T, Vilne B, Wang Y, Hodonsky CJ, Ghosh SK, Mokry M, Gao H, Kawai K, Sakamoto A, Kaiser J, Bongiovanni D, Fleig J, Oldenbuettel L, Chen Z, Moggio A, Sager HB, Hecker JS, Bassermann F, Maegdefessel L, Miller CL, Koenig W, Zeiher AM, Dimmeler S, Graw M, Braun C, Ruusalepp A, Leeper NJ, Kovacic JC, Björkegren JL, Schunkert H. Leukocytes carrying Clonal Hematopoiesis of Indeterminate Potential (CHIP) Mutations invade Human Atherosclerotic Plaques. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.22.23292754. [PMID: 37546840 PMCID: PMC10402238 DOI: 10.1101/2023.07.22.23292754] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Background Leukocyte progenitors derived from clonal hematopoiesis of undetermined potential (CHIP) are associated with increased cardiovascular events. However, the prevalence and functional relevance of CHIP in coronary artery disease (CAD) are unclear, and cells affected by CHIP have not been detected in human atherosclerotic plaques. Methods CHIP mutations in blood and tissues were identified by targeted deep-DNA-sequencing (DNAseq: coverage >3,000) and whole-genome-sequencing (WGS: coverage >35). CHIP-mutated leukocytes were visualized in human atherosclerotic plaques by mutaFISH™. Functional relevance of CHIP mutations was studied by RNAseq. Results DNAseq of whole blood from 540 deceased CAD patients of the Munich cardIovaScular StudIes biObaNk (MISSION) identified 253 (46.9%) CHIP mutation carriers (mean age 78.3 years). DNAseq on myocardium, atherosclerotic coronary and carotid arteries detected identical CHIP mutations in 18 out of 25 mutation carriers in tissue DNA. MutaFISH™ visualized individual macrophages carrying DNMT3A CHIP mutations in human atherosclerotic plaques. Studying monocyte-derived macrophages from Stockholm-Tartu Atherosclerosis Reverse Networks Engineering Task (STARNET; n=941) by WGS revealed CHIP mutations in 14.2% (mean age 67.1 years). RNAseq of these macrophages revealed that expression patterns in CHIP mutation carriers differed substantially from those of non-carriers. Moreover, patterns were different depending on the underlying mutations, e.g. those carrying TET2 mutations predominantly displayed upregulated inflammatory signaling whereas ASXL1 mutations showed stronger effects on metabolic pathways. Conclusions Deep-DNA-sequencing reveals a high prevalence of CHIP mutations in whole blood of CAD patients. CHIP-affected leukocytes invade plaques in human coronary arteries. RNAseq data obtained from macrophages of CHIP-affected patients suggest that pro-atherosclerotic signaling differs depending on the underlying mutations. Further studies are necessary to understand whether specific pathways affected by CHIP mutations may be targeted for personalized treatment.
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Affiliation(s)
- Moritz von Scheidt
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Sabine Bauer
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Angela Ma
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Thorsten Kessler
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Baiba Vilne
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Bioinformatics Lab, Riga Stradiņš University, Riga, Latvia
- SIA Net-OMICS, Riga, Latvia
| | - Ying Wang
- Department of Pathology and Laboratory Medicine, Centre for Heart Lung Innovation, University of British Columbia, Vancouver, Canada
| | - Chani J. Hodonsky
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | | | - Michal Mokry
- Laboratory of Experimental Cardiology, Department of Cardiology, University Medical Center Utrecht, University Utrecht, Utrecht, Netherlands
- Central Diagnostics Laboratory, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hua Gao
- Division of Vascular Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, USA
| | | | - Atsushi Sakamoto
- CVPath Institute, Inc, Gaithersburg, USA
- Division of Cardiology, Internal Medicine III, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Juliane Kaiser
- Institute of Legal Medicine, Faculty of Medicine, LMU Munich, Germany
| | - Dario Bongiovanni
- Department of Internal Medicine I, Cardiology, University Hospital Augsburg, University of Augsburg, Germany
- Department of Cardiovascular Medicine, Humanitas Clinical and Research Center IRCCS and Humanitas University, Rozzano, Milan, Italy
| | - Julia Fleig
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
| | - Lilith Oldenbuettel
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
| | - Zhifen Chen
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Aldo Moggio
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Hendrik B. Sager
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Judith S. Hecker
- Department of Medicine III, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Florian Bassermann
- Department of Medicine III, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Lars Maegdefessel
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Department for Vascular and Endovascular Surgery, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany
| | - Clint L. Miller
- Center for Public Health Genomics, Department of Public Health Sciences, Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Wolfgang Koenig
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Andreas M. Zeiher
- Institute for Cardiovascular Regeneration, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
| | - Stefanie Dimmeler
- Institute for Cardiovascular Regeneration, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
| | - Matthias Graw
- Institute of Legal Medicine, Faculty of Medicine, LMU Munich, Germany
| | - Christian Braun
- Institute of Legal Medicine, Faculty of Medicine, LMU Munich, Germany
| | - Arno Ruusalepp
- Department of Cardiac Surgery, The Heart Clinic, Tartu University Hospital, Tartu, Estonia
- Clinical Gene Networks AB, Stockholm, Sweden
- Institute of Clinical Medicine, Faculty of Medicine, Tartu University, Tartu, Estonia
| | - Nicholas J. Leeper
- Central Diagnostics Laboratory, University Medical Center Utrecht, Utrecht, The Netherlands
- Stanford Cardiovascular Institute, Stanford University, Stanford, USA
| | - Jason C. Kovacic
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia
- St. Vincent’s Clinical School, University of New South Wales, Sydney, Australia
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Johan L.M. Björkegren
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
- Clinical Gene Networks AB, Stockholm, Sweden
- Department of Medicine, Huddinge, Karolinska Institutet, Karolinska Universitetssjukhuset, Stockholm, Sweden
| | - Heribert Schunkert
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
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26
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Sen P, Orešič M. Integrating Omics Data in Genome-Scale Metabolic Modeling: A Methodological Perspective for Precision Medicine. Metabolites 2023; 13:855. [PMID: 37512562 PMCID: PMC10383060 DOI: 10.3390/metabo13070855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/11/2023] [Accepted: 07/17/2023] [Indexed: 07/30/2023] Open
Abstract
Recent advancements in omics technologies have generated a wealth of biological data. Integrating these data within mathematical models is essential to fully leverage their potential. Genome-scale metabolic models (GEMs) provide a robust framework for studying complex biological systems. GEMs have significantly contributed to our understanding of human metabolism, including the intrinsic relationship between the gut microbiome and the host metabolism. In this review, we highlight the contributions of GEMs and discuss the critical challenges that must be overcome to ensure their reproducibility and enhance their prediction accuracy, particularly in the context of precision medicine. We also explore the role of machine learning in addressing these challenges within GEMs. The integration of omics data with GEMs has the potential to lead to new insights, and to advance our understanding of molecular mechanisms in human health and disease.
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Affiliation(s)
- Partho Sen
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, FI-20520 Turku, Finland
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, 702 81 Örebro, Sweden
| | - Matej Orešič
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, FI-20520 Turku, Finland
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, 702 81 Örebro, Sweden
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27
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Lee WJ, Cheng H, Whitney BM, Nance RM, Britton SR, Jordahl K, Lindstrom S, Ruderman SA, Kitahata MM, Saag MS, Willig AL, Burkholder G, Eron JJ, Kovacic JC, Björkegren JLM, Mathews WC, Cachay E, Feinstein MJ, Budoff M, Hunt PW, Moore RD, Keruly J, McCaul ME, Chander G, Webel A, Mayer KH, Delaney JA, Crane PK, Martinez C, Crane HM, Hao K, Peter I. Polygenic risk scores point toward potential genetic mechanisms of type 2 myocardial infarction in people with HIV. Int J Cardiol 2023; 383:15-23. [PMID: 37149004 PMCID: PMC10247524 DOI: 10.1016/j.ijcard.2023.04.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 04/03/2023] [Accepted: 04/30/2023] [Indexed: 05/08/2023]
Abstract
BACKGROUND People with human immunodeficiency virus (HIV) infection (PWH) are at higher risk of myocardial infarction (MI) than those without HIV. About half of MIs in PWH are type 2 (T2MI), resulting from mismatch between myocardial oxygen supply and demand, in contrast to type 1 MI (T1MI), which is due to primary plaque rupture or coronary thrombosis. Despite worse survival and rising incidence in the general population, evidence-based treatment recommendations for T2MI are lacking. We used polygenic risk scores (PRS) to explore genetic mechanisms of T2MI compared to T1MI in PWH. METHODS We derived 115 PRS for MI-related traits in 9541 PWH enrolled in the Centers for AIDS Research Network of Integrated Clinical Systems cohort with adjudicated T1MI and T2MI. We applied multivariate logistic regression analyses to determine the association with T1MI and T2MI. Based on initial findings, we performed gene set enrichment analysis of the top variants composing PRS associated with T2MI. RESULTS We found that T1MI was strongly associated with PRS for cardiovascular disease, lipid profiles, and metabolic traits. In contrast, PRS for alcohol dependence and cholecystitis, significantly enriched in energy metabolism pathways, were predictive of T2MI risk. The association remained after the adjustment for actual alcohol consumption. CONCLUSIONS We demonstrate distinct genetic traits associated with T1MI and T2MI among PWH further highlighting their etiological differences and supporting the role of energy regulation in T2MI pathogenesis.
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Affiliation(s)
- Won Jun Lee
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY, New York, USA
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY, New York, USA
| | - Bridget M Whitney
- Department of Medicine, University of Washington School of Public Health, Seattle, WA, USA
| | - Robin M Nance
- Department of Medicine, University of Washington School of Public Health, Seattle, WA, USA
| | - Sierra R Britton
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY, New York, USA; Department of Population Health Sciences, Weill Cornell Medical College of Cornell University, New York, NY, USA
| | - Kristina Jordahl
- Department of Epidemiology, University of Washington School of Medicine, Seattle, WA, USA
| | - Sara Lindstrom
- Department of Epidemiology, University of Washington School of Medicine, Seattle, WA, USA
| | - Stephanie A Ruderman
- Department of Epidemiology, University of Washington School of Medicine, Seattle, WA, USA
| | - Mari M Kitahata
- Department of Medicine, University of Washington School of Public Health, Seattle, WA, USA
| | - Michael S Saag
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Amanda L Willig
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Greer Burkholder
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Joseph J Eron
- Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jason C Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, NY, New York, USA; Victor Chang Cardiac Research Institute, Darlinghurst, Australia; St Vincent's Clinical School, University of NSW, Australia
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY, New York, USA; Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | | | - Edward Cachay
- Department of Medicine, University of California San Diego, San Diego, CA, USA
| | - Matthew J Feinstein
- Department of Medicine, Northwestern University Feinberg School of Medicine, Evanston, IL, USA
| | - Mathew Budoff
- Deparment of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Peter W Hunt
- Division of Experimental Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Richard D Moore
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jeanne Keruly
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Mary E McCaul
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Geetanjali Chander
- Department of Medicine, University of Washington School of Public Health, Seattle, WA, USA; Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Allison Webel
- Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH, USA; School of Nursing, University of Washington, Seattle, WA, USA
| | | | - Joseph A Delaney
- Department of Medicine, University of Washington School of Public Health, Seattle, WA, USA; College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Manitoba, Canada
| | - Paul K Crane
- Department of Medicine, University of Washington School of Public Health, Seattle, WA, USA
| | - Claudia Martinez
- Department of Medicine, Division of Cardiology, University of Miami Miller School of Medicine, Florida, USA
| | - Heidi M Crane
- Department of Medicine, University of Washington School of Public Health, Seattle, WA, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY, New York, USA
| | - Inga Peter
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY, New York, USA.
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28
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Kristjansson RP, Oskarsson GR, Skuladottir A, Oddsson A, Rognvaldsson S, Sveinbjornsson G, Lund SH, Jensson BO, Styrmisdottir EL, Halldorsson GH, Ferkingstad E, Eldjarn GH, Beyter D, Kristmundsdottir S, Juliusson K, Fridriksdottir R, Arnadottir GA, Katrinardottir H, Snorradottir MH, Tragante V, Stefansdottir L, Ivarsdottir EV, Bjornsdottir G, Halldorsson BV, Thorleifsson G, Ludviksson BR, Onundarson PT, Saevarsdottir S, Melsted P, Norddahl GL, Bjornsdottir US, Olafsdottir T, Gudbjartsson DF, Thorsteinsdottir U, Jonsdottir I, Sulem P, Stefansson K. Sequence variant affects GCSAML splicing, mast cell specific proteins, and risk of urticaria. Commun Biol 2023; 6:703. [PMID: 37430141 DOI: 10.1038/s42003-023-05079-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 06/28/2023] [Indexed: 07/12/2023] Open
Abstract
Urticaria is a skin disorder characterized by outbreaks of raised pruritic wheals. In order to identify sequence variants associated with urticaria, we performed a meta-analysis of genome-wide association studies for urticaria with a total of 40,694 cases and 1,230,001 controls from Iceland, the UK, Finland, and Japan. We also performed transcriptome- and proteome-wide analyses in Iceland and the UK. We found nine sequence variants at nine loci associating with urticaria. The variants are at genes participating in type 2 immune responses and/or mast cell biology (CBLB, FCER1A, GCSAML, STAT6, TPSD1, ZFPM1), the innate immunity (C4), and NF-κB signaling. The most significant association was observed for the splice-donor variant rs56043070[A] (hg38: chr1:247556467) in GCSAML (MAF = 6.6%, OR = 1.24 (95%CI: 1.20-1.28), P-value = 3.6 × 10-44). We assessed the effects of the variants on transcripts, and levels of proteins relevant to urticaria pathophysiology. Our results emphasize the role of type 2 immune response and mast cell activation in the pathogenesis of urticaria. Our findings may point to an IgE-independent urticaria pathway that could help address unmet clinical need.
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Affiliation(s)
| | - Gudjon R Oskarsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | | | | | | | | | | | | | - Snædis Kristmundsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
| | | | | | | | | | | | | | | | - Erna V Ivarsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Bjarni V Halldorsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
| | | | - Bjorn R Ludviksson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Immunology, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | - Pall T Onundarson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Laboratory Hematology, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | - Saedis Saevarsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Rheumatology Unit, Department of Medicine, Karolinska Institutet, Solna, Stockholm, Sweden
- Department of Medicine, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | - Pall Melsted
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Unnur S Bjornsdottir
- Department of Medicine, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
- The Medical Center Mjodd, Reykjavik, Iceland
| | - Thorunn Olafsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Ingileif Jonsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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29
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Aberra YT, Ma L, Björkegren JLM, Civelek M. Predicting mechanisms of action at genetic loci associated with discordant effects on type 2 diabetes and abdominal fat accumulation. eLife 2023; 12:e79834. [PMID: 37326626 PMCID: PMC10275637 DOI: 10.7554/elife.79834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 05/31/2023] [Indexed: 06/17/2023] Open
Abstract
Obesity is a major risk factor for cardiovascular disease, stroke, and type 2 diabetes (T2D). Excessive accumulation of fat in the abdomen further increases T2D risk. Abdominal obesity is measured by calculating the ratio of waist-to-hip circumference adjusted for the body-mass index (WHRadjBMI), a trait with a significant genetic inheritance. Genetic loci associated with WHRadjBMI identified in genome-wide association studies are predicted to act through adipose tissues, but many of the exact molecular mechanisms underlying fat distribution and its consequences for T2D risk are poorly understood. Further, mechanisms that uncouple the genetic inheritance of abdominal obesity from T2D risk have not yet been described. Here we utilize multi-omic data to predict mechanisms of action at loci associated with discordant effects on abdominal obesity and T2D risk. We find six genetic signals in five loci associated with protection from T2D but also with increased abdominal obesity. We predict the tissues of action at these discordant loci and the likely effector Genes (eGenes) at three discordant loci, from which we predict significant involvement of adipose biology. We then evaluate the relationship between adipose gene expression of eGenes with adipogenesis, obesity, and diabetic physiological phenotypes. By integrating these analyses with prior literature, we propose models that resolve the discordant associations at two of the five loci. While experimental validation is required to validate predictions, these hypotheses provide potential mechanisms underlying T2D risk stratification within abdominal obesity.
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Affiliation(s)
- Yonathan Tamrat Aberra
- Department of Biomedical Engineering, University of VirginiaCharlottesvilleUnited States
- Center for Public Health Genomics, University of VirginiaCharlottesvilleUnited States
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount SinaiNew YorkUnited States
| | - Johan LM Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount SinaiNew YorkUnited States
- Department of Medicine, Karolinska Institutet, HuddingeStockholmSweden
| | - Mete Civelek
- Department of Biomedical Engineering, University of VirginiaCharlottesvilleUnited States
- Center for Public Health Genomics, University of VirginiaCharlottesvilleUnited States
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30
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Khan SU, Saeed S, Alsuhaibani AM, Fatima S, Ur Rehman K, Zaman U, Ullah M, Refati MS, Lu K. Advances and Challenges for GWAS Analysis in Cardiac Diseases: A Focus on Coronary Artery Disease (CAD). Curr Probl Cardiol 2023:101821. [PMID: 37211304 DOI: 10.1016/j.cpcardiol.2023.101821] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 05/16/2023] [Indexed: 05/23/2023]
Abstract
The achievement of genome-wide association studies (GWAS) has rapidly progressed our understanding of the etiology of coronary artery disease (CAD). It unlocks new strategies to strengthen the stalling of CAD drug development. In this review, we highlighted the recent drawbacks, mainly pointing out those involved in identifying causal genes and interpreting the connections between disease pathology and risk variants. We also benchmark the novel insights into the biological mechanism behind the disease primarily based on outcomes of GWAS. Furthermore, we also shed light on the successful discovery of novel treatment targets by introducing various layers of "omics" data and applying systems genetics strategies. Lastly, we discuss in-depth the significance of precision medicine that is helpful to improve through GWAS analysis in cardiovascular research.
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Affiliation(s)
- Shahid Ullah Khan
- Integrative Science Center of Germplasm Creation in Western China (CHONGQING) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Beibei, Chongqing 400715, China; Engineering Research Center of South Upland Agriculture, Ministry of Education, Chongqing 400715, China; Women Medical and Dental College, Khyber Medical University, Peshawar, KPK, Pakistan
| | - Sumbul Saeed
- Centre for Cell Factories and Biopolymers (CCFB), Griffith Institute for Drug Discovery, Griffith University, Nathan, QLD, 4111, Australia
| | - Amnah Mohammed Alsuhaibani
- Department of Physical Sport Science, College of Education, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
| | - Sumaya Fatima
- Research Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China
| | - Khalil Ur Rehman
- Institute of Chemical Sciences, Gomal University, Dera Ismail Khan 29050, Pakistan
| | - Umber Zaman
- Institute of Chemical Sciences, Gomal University, Dera Ismail Khan 29050, Pakistan
| | - Muneeb Ullah
- Department of Pharmacy, Kohat University of Science and Technology, 26000, KPK, Pakistan
| | - Moamen S Refati
- Department of Chemistry, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
| | - Kun Lu
- Integrative Science Center of Germplasm Creation in Western China (CHONGQING) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Beibei, Chongqing 400715, China; Engineering Research Center of South Upland Agriculture, Ministry of Education, Chongqing 400715, China.
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31
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Merchant JP, Zhu K, Henrion MYR, Zaidi SSA, Lau B, Moein S, Alamprese ML, Pearse RV, Bennett DA, Ertekin-Taner N, Young-Pearse TL, Chang R. Predictive network analysis identifies JMJD6 and other potential key drivers in Alzheimer's disease. Commun Biol 2023; 6:503. [PMID: 37188718 PMCID: PMC10185548 DOI: 10.1038/s42003-023-04791-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 03/31/2023] [Indexed: 05/17/2023] Open
Abstract
Despite decades of genetic studies on late-onset Alzheimer's disease, the underlying molecular mechanisms remain unclear. To better comprehend its complex etiology, we use an integrative approach to build robust predictive (causal) network models using two large human multi-omics datasets. We delineate bulk-tissue gene expression into single cell-type gene expression and integrate clinical and pathologic traits, single nucleotide variation, and deconvoluted gene expression for the construction of cell type-specific predictive network models. Here, we focus on neuron-specific network models and prioritize 19 predicted key drivers modulating Alzheimer's pathology, which we then validate by knockdown in human induced pluripotent stem cell-derived neurons. We find that neuronal knockdown of 10 of the 19 targets significantly modulates levels of amyloid-beta and/or phosphorylated tau peptides, most notably JMJD6. We also confirm our network structure by RNA sequencing in the neurons following knockdown of each of the 10 targets, which additionally predicts that they are upstream regulators of REST and VGF. Our work thus identifies robust neuronal key drivers of the Alzheimer's-associated network state which may represent therapeutic targets with relevance to both amyloid and tau pathology in Alzheimer's disease.
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Affiliation(s)
- Julie P Merchant
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Neuroscience Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kuixi Zhu
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Marc Y R Henrion
- Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, Pembroke Place, L3 5QA, UK
- Malawi-Liverpool-Wellcome Trust Clinical Research Programme, PO Box 30096, Blantyre, Malawi
| | - Syed S A Zaidi
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Branden Lau
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
- Arizona Research Labs, Genetics Core, University of Arizona, Tucson, AZ, USA
| | - Sara Moein
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Melissa L Alamprese
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Richard V Pearse
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, USA
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL, USA
| | - Tracy L Young-Pearse
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Harvard Stem Cell Institute, Harvard University, Boston, MA, USA.
| | - Rui Chang
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA.
- Department of Neurology, University of Arizona, Tucson, AZ, USA.
- INTelico Therapeutics LLC, Tucson, AZ, USA.
- PATH Biotech LLC, Tucson, AZ, USA.
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Wong D, Auguste G, Cardenas CLL, Turner AW, Chen Y, Song Y, Ma L, Perry RN, Aherrahrou R, Kuppusamy M, Yang C, Mosquera JV, Dube CJ, Khan MD, Palmore M, Kalra JK, Kavousi M, Peyser PA, Matic L, Hedin U, Manichaikul A, Sonkusare SK, Civelek M, Kovacic JC, Björkegren JL, Malhotra R, Miller CL. FHL5 Controls Vascular Disease-Associated Gene Programs in Smooth Muscle Cells. Circ Res 2023; 132:1144-1161. [PMID: 37017084 PMCID: PMC10147587 DOI: 10.1161/circresaha.122.321692] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 03/21/2023] [Indexed: 04/06/2023]
Abstract
BACKGROUND Genome-wide association studies have identified hundreds of loci associated with common vascular diseases, such as coronary artery disease, myocardial infarction, and hypertension. However, the lack of mechanistic insights for many GWAS loci limits their translation into the clinic. Among these loci with unknown functions is UFL1-four-and-a-half LIM (LIN-11, Isl-1, MEC-3) domain 5 (FHL5; chr6q16.1), which reached genome-wide significance in a recent coronary artery disease/ myocardial infarction GWAS meta-analysis. UFL1-FHL5 is also associated with several vascular diseases, consistent with the widespread pleiotropy observed for GWAS loci. METHODS We apply a multimodal approach leveraging statistical fine-mapping, epigenomic profiling, and ex vivo analysis of human coronary artery tissues to implicate FHL5 as the top candidate causal gene. We unravel the molecular mechanisms of the cross-phenotype genetic associations through in vitro functional analyses and epigenomic profiling experiments in coronary artery smooth muscle cells. RESULTS We prioritized FHL5 as the top candidate causal gene at the UFL1-FHL5 locus through expression quantitative trait locus colocalization methods. FHL5 gene expression was enriched in the smooth muscle cells and pericyte population in human artery tissues with coexpression network analyses supporting a functional role in regulating smooth muscle cell contraction. Unexpectedly, under procalcifying conditions, FHL5 overexpression promoted vascular calcification and dysregulated processes related to extracellular matrix organization and calcium handling. Lastly, by mapping FHL5 binding sites and inferring FHL5 target gene function using artery tissue gene regulatory network analyses, we highlight regulatory interactions between FHL5 and downstream coronary artery disease/myocardial infarction loci, such as FOXL1 and FN1 that have roles in vascular remodeling. CONCLUSIONS Taken together, these studies provide mechanistic insights into the pleiotropic genetic associations of UFL1-FHL5. We show that FHL5 mediates vascular disease risk through transcriptional regulation of downstream vascular remodeling gene programs. These transacting mechanisms may explain a portion of the heritable risk for complex vascular diseases.
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Affiliation(s)
- Doris Wong
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
| | - Gaëlle Auguste
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Christian L. Lino Cardenas
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Adam W. Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Yixuan Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Yipei Song
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - R. Noah Perry
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Redouane Aherrahrou
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Maniselvan Kuppusamy
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
| | - Chaojie Yang
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Jose Verdezoto Mosquera
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Collin J. Dube
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, Virginia, USA
| | - Mohammad Daud Khan
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Meredith Palmore
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Jaspreet K. Kalra
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, The Netherlands
| | | | - Ljubica Matic
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Ulf Hedin
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Ani Manichaikul
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA
| | - Swapnil K. Sonkusare
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Mete Civelek
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Jason C. Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, USA
- Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia
- St. Vincent’s Clinical School, University of New South Wales, Sydney, Australia
| | - 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
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Huddinge, Sweden
| | - Rajeev Malhotra
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Clint L. Miller
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
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Jurrjens AW, Seldin MM, Giles C, Meikle PJ, Drew BG, Calkin AC. The potential of integrating human and mouse discovery platforms to advance our understanding of cardiometabolic diseases. eLife 2023; 12:e86139. [PMID: 37000167 PMCID: PMC10065800 DOI: 10.7554/elife.86139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 03/15/2023] [Indexed: 04/01/2023] Open
Abstract
Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery.
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Affiliation(s)
- Aaron W Jurrjens
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
| | - Marcus M Seldin
- Department of Biological Chemistry and Center for Epigenetics and Metabolism, University of California, Irvine, Irvine, United States
| | - Corey Giles
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, Australia
| | - Peter J Meikle
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, Australia
| | - Brian G Drew
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
| | - Anna C Calkin
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
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Prapiadou S, Živković L, Thorand B, George MJ, van der Laan SW, Malik R, Herder C, Koenig W, Ueland T, Kleveland O, Aukrust P, Gullestad L, Bernhagen J, Pasterkamp G, Peters A, Hingorani AD, Rosand J, Dichgans M, Anderson CD, Georgakis MK. Proteogenomic integration reveals CXCL10 as a potentially downstream causal mediator for IL-6 signaling on atherosclerosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.24.23287543. [PMID: 37034659 PMCID: PMC10081435 DOI: 10.1101/2023.03.24.23287543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Background Genetic and experimental studies support a causal involvement of interleukin-6 (IL-6) signaling in atheroprogression. While trials targeting IL-6 signaling are underway, any benefits must be balanced against an impaired host immune response. Dissecting the mechanisms that mediate the effects of IL-6 signaling on atherosclerosis could offer insights about novel drug targets with more specific effects. Methods Leveraging data from 522,681 individuals, we constructed a genetic instrument of 26 variants in the gene encoding the IL-6 receptor (IL-6R) that proxied for pharmacological IL-6R inhibition. Using Mendelian randomization (MR), we assessed its effects on 3,281 plasma proteins quantified with an aptamer-based assay in the INTERVAL cohort (n=3,301). Using mediation MR, we explored proteomic mediators of the effects of genetically proxied IL-6 signaling on coronary artery disease (CAD), large artery atherosclerotic stroke (LAAS), and peripheral artery disease (PAD). For significant mediators, we tested associations of their circulating levels with incident cardiovascular events in a population-based study (n=1,704) and explored the histological, transcriptomic, and cellular phenotypes correlated with their expression levels in samples from human atherosclerotic lesions. Results We found significant effects of genetically proxied IL-6 signaling on 70 circulating proteins involved in cytokine production/regulation and immune cell recruitment/differentiation, which correlated with the proteomic effects of pharmacological IL-6R inhibition in a clinical trial. Among the 70 significant proteins, genetically proxied circulating levels of CXCL10 were associated with risk of CAD, LAAS, and PAD with up to 67% of the effects of genetically downregulated IL-6 signaling on these endpoints mediated by decreases in CXCL10. Higher midlife circulating CXCL10 levels were associated with a larger number of cardiovascular events over 20 years, whereas higher CXCL10 expression in human atherosclerotic lesions correlated with a larger lipid core and a transcriptomic profile reflecting immune cell infiltration, adaptive immune system activation, and cytokine signaling. Conclusions Integrating multiomics data, we found a proteomic signature of IL-6 signaling activation and mediators of its effects on cardiovascular disease. Our analyses suggest the interferon-γ-inducible chemokine CXCL10 to be a potentially causal mediator for atherosclerosis in three vascular compartments and as such could serve as a promising drug target for atheroprotection.
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Affiliation(s)
- Savvina Prapiadou
- University of Patras School of Medicine, Patras, Greece
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Luka Živković
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Marc J. George
- Department of Clinical Pharmacology, Division of Medicine, University College London, London, United Kingdom
| | - Sander W. van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Rainer Malik
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Christian Herder
- German Center for Diabetes Research, Partner Düsseldorf, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
| | - Wolfgang Koenig
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
- German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Thor Ueland
- Thrombosis Research Center (TREC), Division of internal medicine, University hospital of North Norway, Tromsø, Norway
- Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ola Kleveland
- Clinic of Cardiology, St Olavs Hospital, Trondheim, Norway
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Pal Aukrust
- Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Lars Gullestad
- Department of Cardiology Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Jürgen Bernhagen
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximilians-University Munich, Munich, Germany
- Munich Heart Alliance, German Center for Cardiovascular Health (DZHK e.V., partner-site Munich), Munich, Germany
| | - Aroon D. Hingorani
- Department of Clinical Pharmacology, Division of Medicine, University College London, London, United Kingdom
- Centre for Translational Genomics, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Jonathan Rosand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital Rikshospitalet, Oslo, Norway
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany
| | - Christopher D. Anderson
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Marios K. Georgakis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
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Yang G, Mishra M, Perera MA. Multi-Omics Studies in Historically Excluded Populations: The Road to Equity. Clin Pharmacol Ther 2023; 113:541-556. [PMID: 36495075 DOI: 10.1002/cpt.2818] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 12/01/2022] [Indexed: 12/14/2022]
Abstract
Over the past few decades, genomewide association studies (GWASs) have identified the specific genetics variants contributing to many complex diseases by testing millions of genetic variations across the human genome against a variety of phenotypes. However, GWASs are limited in their ability to uncover mechanistic insight given that most significant associations are found in non-coding region of the genome. Furthermore, the lack of diversity in studies has stymied the advance of precision medicine for many historically excluded populations. In this review, we summarize most popular multi-omics approaches (genomics, transcriptomics, proteomics, and metabolomics) related to precision medicine and highlight if diverse populations have been included and how their findings have advance biological understanding of disease and drug response. New methods that incorporate local ancestry have been to improve the power of GWASs for admixed populations (such as African Americans and Latinx). Because most signals from GWAS are in the non-coding region, other machine learning and omics approaches have been developed to identify the potential causative single-nucleotide polymorphisms and genes that explain these phenotypes. These include polygenic risk scores, expression quantitative trait locus mapping, and transcriptome-wide association studies. Analogous protein methods, such as proteins quantitative trait locus mapping, proteome-wide association studies, and metabolomic approaches provide insight into the consequences of genetic variation on protein abundance. Whereas, integrated multi-omics studies have improved our understanding of the mechanisms for genetic association, we still lack the datasets and cohorts for historically excluded populations to provide equity in precision medicine and pharmacogenomics.
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Affiliation(s)
- Guang Yang
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Mrinal Mishra
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Minoli A Perera
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
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Aherrahrou R, Lue D, Perry RN, Aberra YT, Khan MD, Soh JY, Örd T, Singha P, Yang Q, Gilani H, Benavente ED, Wong D, Hinkle J, Ma L, Sheynkman GM, den Ruijter HM, Miller CL, Björkegren JLM, Kaikkonen MU, Civelek M. Genetic Regulation of SMC Gene Expression and Splicing Predict Causal CAD Genes. Circ Res 2023; 132:323-338. [PMID: 36597873 PMCID: PMC9898186 DOI: 10.1161/circresaha.122.321586] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 12/20/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND Coronary artery disease (CAD) is the leading cause of death worldwide. Recent meta-analyses of genome-wide association studies have identified over 175 loci associated with CAD. The majority of these loci are in noncoding regions and are predicted to regulate gene expression. Given that vascular smooth muscle cells (SMCs) play critical roles in the development and progression of CAD, we aimed to identify the subset of the CAD loci associated with the regulation of transcription in distinct SMC phenotypes. METHODS We measured gene expression in SMCs isolated from the ascending aortas of 151 heart transplant donors of various genetic ancestries in quiescent or proliferative conditions and calculated the association of their expression and splicing with ~6.3 million imputed single-nucleotide polymorphism markers across the genome. RESULTS We identified 4910 expression and 4412 splicing quantitative trait loci (sQTLs) representing regions of the genome associated with transcript abundance and splicing. A total of 3660 expression quantitative trait loci (eQTLs) had not been observed in the publicly available Genotype-Tissue Expression dataset. Further, 29 and 880 eQTLs were SMC-specific and sex-biased, respectively. We made these results available for public query on a user-friendly website. To identify the effector transcript(s) regulated by CAD loci, we used 4 distinct colocalization approaches. We identified 84 eQTL and 164 sQTL that colocalized with CAD loci, highlighting the importance of genetic regulation of mRNA splicing as a molecular mechanism for CAD genetic risk. Notably, 20% and 35% of the eQTLs were unique to quiescent or proliferative SMCs, respectively. One CAD locus colocalized with a sex-specific eQTL (TERF2IP), and another locus colocalized with SMC-specific eQTL (ALKBH8). The most significantly associated CAD locus, 9p21, was an sQTL for the long noncoding RNA CDKN2B-AS1, also known as ANRIL, in proliferative SMCs. CONCLUSIONS Collectively, our results provide evidence for the molecular mechanisms of genetic susceptibility to CAD in distinct SMC phenotypes.
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Affiliation(s)
- Rédouane Aherrahrou
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
| | - Dillon Lue
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
| | - R Noah Perry
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
| | - Yonathan Tamrat Aberra
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
| | - Mohammad Daud Khan
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Joon Yuhl Soh
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
| | - Tiit Örd
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Prosanta Singha
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Qianyi Yang
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Huda Gilani
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Ernest Diez Benavente
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, The Netherlands
| | - Doris Wong
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Jameson Hinkle
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, United States of America
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, United States of America
| | - Gloria M Sheynkman
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Cancer Center, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Hester M den Ruijter
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, The Netherlands
| | - Clint L Miller
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Johan LM Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, United States of America
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, United States of America
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Minna U Kaikkonen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Mete Civelek
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
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Chen Z, Lehertshuber C, Schunkert H. Genome Editing in Dyslipidemia and Atherosclerosis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1396:139-156. [DOI: 10.1007/978-981-19-5642-3_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
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Mauersberger C, Sager HB, Wobst J, Dang TA, Lambrecht L, Koplev S, Stroth M, Bettaga N, Schlossmann J, Wunder F, Friebe A, Björkegren JLM, Dietz L, Maas SL, van der Vorst EPC, Sandner P, Soehnlein O, Schunkert H, Kessler T. Loss of soluble guanylyl cyclase in platelets contributes to atherosclerotic plaque formation and vascular inflammation. NATURE CARDIOVASCULAR RESEARCH 2022; 1:1174-1186. [PMID: 37484062 PMCID: PMC10361702 DOI: 10.1038/s44161-022-00175-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 10/27/2022] [Indexed: 07/25/2023]
Abstract
Variants in genes encoding the soluble guanylyl cyclase (sGC) in platelets are associated with coronary artery disease (CAD) risk. Here, by using histology, flow cytometry and intravital microscopy, we show that functional loss of sGC in platelets of atherosclerosis-prone Ldlr-/- mice contributes to atherosclerotic plaque formation, particularly via increasing in vivo leukocyte adhesion to atherosclerotic lesions. In vitro experiments revealed that supernatant from activated platelets lacking sGC promotes leukocyte adhesion to endothelial cells (ECs) by activating ECs. Profiling of platelet-released cytokines indicated that reduced platelet angiopoietin-1 release by sGC-depleted platelets, which was validated in isolated human platelets from carriers of GUCY1A1 risk alleles, enhances leukocyte adhesion to ECs. I mp or ta ntly, p ha rm ac ol ogical sGC stimulation increased platelet angiopoietin-1 release in vitro and reduced leukocyte recruitment and atherosclerotic plaque formation in atherosclerosis-prone Ldlr-/- mice. Therefore, pharmacological sGC stimulation might represent a potential therapeutic strategy to prevent and treat CAD.
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Affiliation(s)
- Carina Mauersberger
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
- These authors contributed equally: Carina Mauersberger, Hendrik B. Sager
| | - Hendrik B. Sager
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
- These authors contributed equally: Carina Mauersberger, Hendrik B. Sager
| | - Jana Wobst
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
| | - Tan An Dang
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
| | - Laura Lambrecht
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
| | - 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
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK
| | - Marlène Stroth
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
| | - Noomen Bettaga
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
| | - Jens Schlossmann
- Department of Pharmacology and Toxicology, University of Regensburg, Regensburg, Germany
| | - Frank Wunder
- Bayer AG, R&D Pharmaceuticals, Wuppertal, Germany
| | - Andreas Friebe
- Institute of Physiology, Julius Maximilian University of Würzburg, Würzburg, Germany
| | - 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 Medicine, Neo, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Tartu, Estonia
| | - Lisa Dietz
- Bayer AG, R&D Pharmaceuticals, Wuppertal, Germany
| | - Sanne L. Maas
- Institute for Molecular Cardiovascular Research and Interdisciplinary Centre for Clinical Research, Rhine-Westphalia Technical University of Aachen, Aachen, Germany
| | - Emiel P. C. van der Vorst
- Institute for Molecular Cardiovascular Research and Interdisciplinary Centre for Clinical Research, Rhine-Westphalia Technical University of Aachen, Aachen, Germany
- Institute for Cardiovascular Prevention, Ludwig Maximilian University of Munich, Munich, Germany
| | | | - Oliver Soehnlein
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
- Institute for Cardiovascular Prevention, Ludwig Maximilian University of Munich, Munich, Germany
- Institute for Experimental Pathology, University of Münster, Münster, Germany
- Department of Physiology and Pharmacology and Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Heribert Schunkert
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
- These authors jointly supervised this work: Heribert Schunkert, Thorsten Kessler
| | - Thorsten Kessler
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
- These authors jointly supervised this work: Heribert Schunkert, Thorsten Kessler
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39
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Aragam KG, Jiang T, Goel A, Kanoni S, Wolford BN, Atri DS, Weeks EM, Wang M, Hindy G, Zhou W, Grace C, Roselli C, Marston NA, Kamanu FK, Surakka I, Venegas LM, Sherliker P, Koyama S, Ishigaki K, Åsvold BO, Brown MR, Brumpton B, de Vries PS, Giannakopoulou O, Giardoglou P, Gudbjartsson DF, Güldener U, Haider SMI, Helgadottir A, Ibrahim M, Kastrati A, Kessler T, Kyriakou T, Konopka T, Li L, Ma L, Meitinger T, Mucha S, Munz M, Murgia F, Nielsen JB, Nöthen MM, Pang S, Reinberger T, Schnitzler G, Smedley D, Thorleifsson G, von Scheidt M, Ulirsch JC, Arnar DO, Burtt NP, Costanzo MC, Flannick J, Ito K, Jang DK, Kamatani Y, Khera AV, Komuro I, Kullo IJ, Lotta LA, Nelson CP, Roberts R, Thorgeirsson G, Thorsteinsdottir U, Webb TR, Baras A, Björkegren JLM, Boerwinkle E, Dedoussis G, Holm H, Hveem K, Melander O, Morrison AC, Orho-Melander M, Rallidis LS, Ruusalepp A, Sabatine MS, Stefansson K, Zalloua P, Ellinor PT, Farrall M, Danesh J, Ruff CT, Finucane HK, Hopewell JC, Clarke R, Gupta RM, Erdmann J, Samani NJ, Schunkert H, Watkins H, Willer CJ, Deloukas P, Kathiresan S, Butterworth AS. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants. Nat Genet 2022; 54:1803-1815. [PMID: 36474045 PMCID: PMC9729111 DOI: 10.1038/s41588-022-01233-6] [Citation(s) in RCA: 167] [Impact Index Per Article: 83.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 10/17/2022] [Indexed: 12/12/2022]
Abstract
The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.
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Affiliation(s)
- Krishna G Aragam
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA. .,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. .,Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA. .,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Tao Jiang
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Anuj Goel
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Brooke N Wolford
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Deepak S Atri
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Divisions of Cardiovascular Medicine and Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Elle M Weeks
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Minxian Wang
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - George Hindy
- Department of Population Medicine, Qatar University College of Medicine, Doha, Qatar
| | - Wei Zhou
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Christopher Grace
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Carolina Roselli
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nicholas A Marston
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Frederick K Kamanu
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ida Surakka
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
| | - Loreto Muñoz Venegas
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Paul Sherliker
- Medical Research Council Population Health Research Unit, CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama, Japan
| | - Bjørn O Åsvold
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway.,Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim, Norway
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ben Brumpton
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Olga Giannakopoulou
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Panagiota Giardoglou
- Department of Nutrition-Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Ulrich Güldener
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
| | - Syed M Ijlal Haider
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | | | - Maysson Ibrahim
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Adnan Kastrati
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany.,German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | - Thorsten Kessler
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany.,German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | | | - Tomasz Konopka
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Ling Li
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
| | - Lijiang Ma
- Department of Genetics and Genomic Science, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas Meitinger
- German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany.,Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.,Klinikum Rechts der Isar, Institute of Human Genetics, Technical University of Munich, Munich, Germany
| | - Sören Mucha
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Matthias Munz
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Federico Murgia
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Jonas B Nielsen
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA.,Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Markus M Nöthen
- School of Medicine and University Hospital Bonn, Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Shichao Pang
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
| | - Tobias Reinberger
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Gavin Schnitzler
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Damian Smedley
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | | | - Moritz von Scheidt
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany.,German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | - Jacob C Ulirsch
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
| | | | | | - David O Arnar
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Department of Internal Medicine, Division of Cardiology, Landspitali-National University Hospital of Iceland, Hringbraut, Reykjavik, Iceland
| | - Noël P Burtt
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Maria C Costanzo
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jason Flannick
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama, Japan
| | - Dong-Keun Jang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yoichiro Kamatani
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Amit V Khera
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Issei Komuro
- Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Luca A Lotta
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Christopher P Nelson
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Glenfield Hospital, Leicester, UK
| | - Robert Roberts
- Cardiovascular Genomics and Genetics, University of Arizona College of Medicin, Phoenix, AZ, USA
| | - Gudmundur Thorgeirsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Department of Internal Medicine, Division of Cardiology, Landspitali-National University Hospital of Iceland, Hringbraut, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Thomas R Webb
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Glenfield Hospital, Leicester, UK
| | - Aris Baras
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Integrated Cardio Metabolic Centre, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden.,Clinical Gene Networks AB, Stockholm, Sweden
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - George Dedoussis
- Department of Nutrition-Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Hilma Holm
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | - Kristian Hveem
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
| | - Olle Melander
- Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Loukianos S Rallidis
- Second Department of Cardiology, Medical School, National and Kapodistrian University of Athens, University General Hospital Attikon, Athens, Greece
| | - Arno Ruusalepp
- Department of Cardiac Surgery, Tartu University Hospital and Institute of Clinical Medicine, Tartu University, Tartu, Estonia
| | - Marc S Sabatine
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Pierre Zalloua
- Harvard T.H.Chan School of Public Health, Boston, MA, USA.,College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, UAE
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.,Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Martin Farrall
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - John Danesh
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,National Institute for Health and Care Research Cambridge Biomedical Research Centre, Cambridge University Hospitals, Cambridge, UK.,The National Institute for Health and Care Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge, UK.,Human Genetics, Wellcome Sanger Institute, Saffron Walden, UK.,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.,British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge, UK
| | - Christian T Ruff
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Hilary K Finucane
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jemma C Hopewell
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Robert Clarke
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Rajat M Gupta
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Divisions of Cardiovascular Medicine and Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Nilesh J Samani
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Heribert Schunkert
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany.,German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | - Hugh Watkins
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Cristen J Willer
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.,Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA.,Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Panos Deloukas
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, 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
| | | | - Adam S Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. .,National Institute for Health and Care Research Cambridge Biomedical Research Centre, Cambridge University Hospitals, Cambridge, UK. .,The National Institute for Health and Care Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge, UK. .,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK. .,British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge, UK.
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40
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Mokry M, Boltjes A, Slenders L, Bel-Bordes G, Cui K, Brouwer E, Mekke JM, Depuydt MA, Timmerman N, Waissi F, Verwer MC, Turner AW, Khan MD, Hodonsky CJ, Benavente ED, Hartman RJ, van den Dungen NAM, Lansu N, Nagyova E, Prange KH, Kovacic JC, Björkegren JL, Pavlos E, Andreakos E, Schunkert H, Owens GK, Monaco C, Finn AV, Virmani R, Leeper NJ, de Winther MP, Kuiper J, de Borst GJ, Stroes ES, Civelek M, de Kleijn DP, den Ruijter HM, Asselbergs FW, van der Laan SW, Miller CL, Pasterkamp G. Transcriptomic-based clustering of human atherosclerotic plaques identifies subgroups with different underlying biology and clinical presentation. NATURE CARDIOVASCULAR RESEARCH 2022; 1:1140-1155. [PMID: 37920851 PMCID: PMC10621615 DOI: 10.1038/s44161-022-00171-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 10/20/2022] [Indexed: 11/04/2023]
Abstract
Histopathological studies have revealed key processes of atherosclerotic plaque thrombosis. However, the diversity and complexity of lesion types highlight the need for improved sub-phenotyping. Here we analyze the gene expression profiles of 654 advanced human carotid plaques. The unsupervised, transcriptome-driven clustering revealed five dominant plaque types. These plaque phenotypes were associated with clinical presentation and showed differences in cellular compositions. Validation in coronary segments showed that the molecular signature of these plaques was linked to coronary ischemia. One of the plaque types with the most severe clinical symptoms pointed to both inflammatory and fibrotic cell lineages. Further, we did a preliminary analysis of potential circulating biomarkers that mark the different plaques phenotypes. In conclusion, the definition of the plaque at risk for a thrombotic event can be fine-tuned by in-depth transcriptomic-based phenotyping. These differential plaque phenotypes prove clinically relevant for both carotid and coronary artery plaques and point to distinct underlying biology of symptomatic lesions.
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Affiliation(s)
- Michal Mokry
- Central Diagnostics Laboratory, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
- Laboratory of Experimental Cardiology, Department of Cardiology, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Arjan Boltjes
- Central Diagnostics Laboratory, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Lotte Slenders
- Central Diagnostics Laboratory, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Gemma Bel-Bordes
- Central Diagnostics Laboratory, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Kai Cui
- Laboratory of Experimental Cardiology, Department of Cardiology, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Eli Brouwer
- Central Diagnostics Laboratory, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Joost M. Mekke
- Department of Vascular Surgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Marie A.C. Depuydt
- Leiden Academic Centre for Drug Research, Division of Biotherapeutics, Leiden University, Leiden, The Netherlands
| | - Nathalie Timmerman
- Department of Vascular Surgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Farahnaz Waissi
- Department of Vascular Surgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Maarten C Verwer
- Department of Vascular Surgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Adam W. Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Mohammad Daud Khan
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Chani J. Hodonsky
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Ernest Diez Benavente
- Laboratory of Experimental Cardiology, Department of Cardiology, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Robin J.G. Hartman
- Laboratory of Experimental Cardiology, Department of Cardiology, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Noortje A M van den Dungen
- Central Diagnostics Laboratory, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Nico Lansu
- Central Diagnostics Laboratory, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Emilia Nagyova
- Central Diagnostics Laboratory, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Koen H.M. Prange
- Amsterdam University Medical Centers – location AMC, University of Amsterdam, Experimental Vascular Biology, Department of Medical Biochemistry, Amsterdam Cardiovascular Sciences, Amsterdam Infection and Immunity, Amsterdam, The Netherlands
| | - Jason C. Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia; and St Vincent’s Clinical School, University of New South Wales, Australia
| | - Johan L.M. Björkegren
- Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029-6574, USA
| | - Eleftherios Pavlos
- Laboratory of Immunobiology, Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Evangelos Andreakos
- Laboratory of Immunobiology, Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Heribert Schunkert
- Department of Cardiology, German Heart Centre Munich, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | - Gary K. Owens
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, VA, USA
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Claudia Monaco
- Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford
| | | | | | - Nicholas J. Leeper
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA
| | - Menno P.J. de Winther
- Amsterdam University Medical Centers – location AMC, University of Amsterdam, Experimental Vascular Biology, Department of Medical Biochemistry, Amsterdam Cardiovascular Sciences, Amsterdam Infection and Immunity, Amsterdam, The Netherlands
| | - Johan Kuiper
- Leiden Academic Centre for Drug Research, Division of Biotherapeutics, Leiden University, Leiden, The Netherlands
| | - Gert J. de Borst
- Department of Vascular Surgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Erik S.G. Stroes
- Department of Vascular Medicine, Amsterdam University Medical Centers, Location AMC, Amsterdam, the Netherlands
| | - Mete Civelek
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | | | - Hester M. den Ruijter
- Laboratory of Experimental Cardiology, Department of Cardiology, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Folkert W. Asselbergs
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom
| | - Sander W. van der Laan
- Central Diagnostics Laboratory, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Clint L. Miller
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Biomedical Engineering, Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
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Whole genome DNA and RNA sequencing of whole blood elucidates the genetic architecture of gene expression underlying a wide range of diseases. Sci Rep 2022; 12:20167. [PMID: 36424512 PMCID: PMC9686236 DOI: 10.1038/s41598-022-24611-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 11/17/2022] [Indexed: 11/27/2022] Open
Abstract
To create a scientific resource of expression quantitative trail loci (eQTL), we conducted a genome-wide association study (GWAS) using genotypes obtained from whole genome sequencing (WGS) of DNA and gene expression levels from RNA sequencing (RNA-seq) of whole blood in 2622 participants in Framingham Heart Study. We identified 6,778,286 cis-eQTL variant-gene transcript (eGene) pairs at p < 5 × 10-8 (2,855,111 unique cis-eQTL variants and 15,982 unique eGenes) and 1,469,754 trans-eQTL variant-eGene pairs at p < 1e-12 (526,056 unique trans-eQTL variants and 7233 unique eGenes). In addition, 442,379 cis-eQTL variants were associated with expression of 1518 long non-protein coding RNAs (lncRNAs). Gene Ontology (GO) analyses revealed that the top GO terms for cis-eGenes are enriched for immune functions (FDR < 0.05). The cis-eQTL variants are enriched for SNPs reported to be associated with 815 traits in prior GWAS, including cardiovascular disease risk factors. As proof of concept, we used this eQTL resource in conjunction with genetic variants from public GWAS databases in causal inference testing (e.g., COVID-19 severity). After Bonferroni correction, Mendelian randomization analyses identified putative causal associations of 60 eGenes with systolic blood pressure, 13 genes with coronary artery disease, and seven genes with COVID-19 severity. This study created a comprehensive eQTL resource via BioData Catalyst that will be made available to the scientific community. This will advance understanding of the genetic architecture of gene expression underlying a wide range of diseases.
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Wang Y, Gao H, Wang F, Ye Z, Mokry M, Turner AW, Ye J, Koplev S, Luo L, Alsaigh T, Adkar SS, Elishaev M, Gao X, Maegdefessel L, Björkegren JLM, Pasterkamp G, Miller CL, Ross EG, Leeper NJ. Dynamic changes in chromatin accessibility are associated with the atherogenic transitioning of vascular smooth muscle cells. Cardiovasc Res 2022; 118:2792-2804. [PMID: 34849613 PMCID: PMC9586565 DOI: 10.1093/cvr/cvab347] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 11/18/2021] [Indexed: 11/13/2022] Open
Abstract
AIMS De-differentiation and activation of pro-inflammatory pathways are key transitions vascular smooth muscle cells (SMCs) make during atherogenesis. Here, we explored the upstream regulators of this 'atherogenic transition'. METHODS AND RESULTS Genome-wide sequencing studies, including Assay for Transposase-Accessible Chromatin using sequencing and RNA-seq, were performed on cells isolated from both murine SMC-lineage-tracing models of atherosclerosis and human atherosclerotic lesions. At the bulk level, alterations in chromatin accessibility were associated with the atherogenic transitioning of lesional SMCs, especially in relation to genes that govern differentiation status and complement-dependent inflammation. Using computational biology, we observed that a transcription factor previously related to coronary artery disease, Activating transcription factor 3 (ATF3), was predicted to be an upstream regulator of genes altered during the transition. At the single-cell level, our results indicated that ATF3 is a key repressor of SMC transitioning towards the subset of cells that promote vascular inflammation by activating the complement cascade. The expression of ATF3 and complement component C3 was negatively correlated in SMCs from human atherosclerotic lesions, suggesting translational relevance. Phenome-wide association studies indicated that genetic variation that results in reduced expression of ATF3 is correlated with an increased risk for atherosclerosis, and the expression of ATF3 was significantly down-regulated in humans with advanced vascular disease. CONCLUSION Our study indicates that the plasticity of atherosclerotic SMCs may in part be explained by dynamic changes in their chromatin architecture, which in turn may contribute to their maladaptive response to inflammation-induced stress.
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Affiliation(s)
- Ying Wang
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, 300 Pasteur drive, Stanford, CA 94305, USA
- Stanford Cardiovascular Institute, Stanford University, 265 Campus Drive, Stanford, CA 94305, USA
| | - Hua Gao
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, 300 Pasteur drive, Stanford, CA 94305, USA
- Stanford Cardiovascular Institute, Stanford University, 265 Campus Drive, Stanford, CA 94305, USA
| | - Fudi Wang
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, 300 Pasteur drive, Stanford, CA 94305, USA
- Stanford Cardiovascular Institute, Stanford University, 265 Campus Drive, Stanford, CA 94305, USA
| | - Zhongde Ye
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, 300 Pasteur drive, Stanford, CA 94305, USA
- Stanford Cardiovascular Institute, Stanford University, 265 Campus Drive, Stanford, CA 94305, USA
| | - Michal Mokry
- Department of Cardiology and Laboratory of Clinical Chemistry, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX, the Netherlands
| | - Adam W Turner
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, 1335 Lee St, Charlottesville, VA 22908, USA
| | - Jianqin Ye
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, 300 Pasteur drive, Stanford, CA 94305, USA
| | - Simon Koplev
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge CB2 0RE, UK
| | - Lingfeng Luo
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, 300 Pasteur drive, Stanford, CA 94305, USA
- Stanford Cardiovascular Institute, Stanford University, 265 Campus Drive, Stanford, CA 94305, USA
| | - Tom Alsaigh
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, 300 Pasteur drive, Stanford, CA 94305, USA
- Department of Cardiovascular Medicine, Stanford University School of Medicine, 870 Quarry Road Extension, Stanford, CA 94305, USA
| | - Shaunak S Adkar
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, 300 Pasteur drive, Stanford, CA 94305, USA
| | - Maria Elishaev
- Department of Pathology and Laboratory Medicine, Centre for Heart Lung Innvoation, University of British Columbia, 166-1081 Burrard St, Vancouver, BC V6Z 1Y6, Canada
| | - Xiangyu Gao
- Department of Pathology and Laboratory Medicine, Centre for Heart Lung Innvoation, University of British Columbia, 166-1081 Burrard St, Vancouver, BC V6Z 1Y6, Canada
| | - Lars Maegdefessel
- Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University Munich, and the German Center for Cardiovascular Research (DZHK partner site), Biedersteiner Str. 29, Munich 80802, Germany
- Department of Internal Medicine, Center for Molecular Medicine, Karolinska Institute, Visionsgatan 18, Stockholm 171 76, Sweden
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY 10029, USA
| | - Gerard Pasterkamp
- Department of Cardiology and Laboratory of Clinical Chemistry, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX, the Netherlands
| | - Clint L Miller
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, 1335 Lee St, Charlottesville, VA 22908, USA
| | - Elsie G Ross
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, 300 Pasteur drive, Stanford, CA 94305, USA
- Stanford Cardiovascular Institute, Stanford University, 265 Campus Drive, Stanford, CA 94305, USA
| | - Nicholas J Leeper
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, 300 Pasteur drive, Stanford, CA 94305, USA
- Stanford Cardiovascular Institute, Stanford University, 265 Campus Drive, Stanford, CA 94305, USA
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Girard D, Vandiedonck C. How dysregulation of the immune system promotes diabetes mellitus and cardiovascular risk complications. Front Cardiovasc Med 2022; 9:991716. [PMID: 36247456 PMCID: PMC9556991 DOI: 10.3389/fcvm.2022.991716] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 08/30/2022] [Indexed: 12/15/2022] Open
Abstract
Diabetes mellitus (DM) is a chronic metabolic disorder characterized by persistent hyperglycemia due to insulin resistance or failure to produce insulin. Patients with DM develop microvascular complications that include chronic kidney disease and retinopathy, and macrovascular complications that mainly consist in an accelerated and more severe atherosclerosis compared to the general population, increasing the risk of cardiovascular (CV) events, such as stroke or myocardial infarction by 2- to 4-fold. DM is commonly associated with a low-grade chronic inflammation that is a known causal factor in its development and its complications. Moreover, it is now well-established that inflammation and immune cells play a major role in both atherosclerosis genesis and progression, as well as in CV event occurrence. In this review, after a brief presentation of DM physiopathology and its macrovascular complications, we will describe the immune system dysregulation present in patients with type 1 or type 2 diabetes and discuss its role in DM cardiovascular complications development. More specifically, we will review the metabolic changes and aberrant activation that occur in the immune cells driving the chronic inflammation through cytokine and chemokine secretion, thus promoting atherosclerosis onset and progression in a DM context. Finally, we will discuss how genetics and recent systemic approaches bring new insights into the mechanisms behind these inflammatory dysregulations and pave the way toward precision medicine.
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Affiliation(s)
- Diane Girard
- Université Paris Cité, INSERM UMR-S1151, CNRS UMR-S8253, Institut Necker Enfants Malades, IMMEDIAB Laboratory, Paris, France
- Université Paris Cité, Institut Hors-Mur du Diabète, Faculté de Santé, Paris, France
| | - Claire Vandiedonck
- Université Paris Cité, INSERM UMR-S1151, CNRS UMR-S8253, Institut Necker Enfants Malades, IMMEDIAB Laboratory, Paris, France
- Université Paris Cité, Institut Hors-Mur du Diabète, Faculté de Santé, Paris, France
- *Correspondence: Claire Vandiedonck
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O'Donnell CJ, Bradner JE. Bridging the Gap to Translating Genome-Wide Discoveries Into Therapies to Prevent and Treat Atherosclerotic Cardiovascular Disease. Circulation 2022; 146:930-933. [PMID: 36121912 DOI: 10.1161/circulationaha.122.060998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Affiliation(s)
- Christopher J O'Donnell
- Novartis Institutes for BioMedical Research, Cambridge, MA (C.J.O., J.E.B.).,Cardiology Section, VA Boston Healthcare System, Harvard Medical School, MA (C.J.O.)
| | - James E Bradner
- Novartis Institutes for BioMedical Research, Cambridge, MA (C.J.O., J.E.B.)
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Voloudakis G, Vicari JM, Venkatesh S, Hoffman GE, Dobrindt K, Zhang W, Beckmann ND, Higgins CA, Argyriou S, Jiang S, Hoagland D, Gao L, Corvelo A, Cho K, Lee KM, Bian J, Lee JS, Iyengar SK, Luoh SW, Akbarian S, Striker R, Assimes TL, Schadt EE, Lynch JA, Merad M, tenOever BR, Charney AW, Brennand KJ, Fullard JF, Roussos P. A translational genomics approach identifies IL10RB as the top candidate gene target for COVID-19 susceptibility. NPJ Genom Med 2022; 7:52. [PMID: 36064543 PMCID: PMC9441828 DOI: 10.1038/s41525-022-00324-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 08/19/2022] [Indexed: 02/06/2023] Open
Abstract
Recent efforts have identified genetic loci that are associated with coronavirus disease 2019 (COVID-19) infection rates and disease outcome severity. Translating these genetic findings into druggable genes that reduce COVID-19 host susceptibility is a critical next step. Using a translational genomics approach that integrates COVID-19 genetic susceptibility variants, multi-tissue genetically regulated gene expression (GReX), and perturbagen signatures, we identified IL10RB as the top candidate gene target for COVID-19 host susceptibility. In a series of validation steps, we show that predicted GReX upregulation of IL10RB and higher IL10RB expression in COVID-19 patient blood is associated with worse COVID-19 outcomes and that in vitro IL10RB overexpression is associated with increased viral load and activation of disease-relevant molecular pathways.
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Affiliation(s)
- Georgios Voloudakis
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA.
| | - James M Vicari
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sanan Venkatesh
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA
| | - Gabriel E Hoffman
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kristina Dobrindt
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Wen Zhang
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Noam D Beckmann
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Christina A Higgins
- Department of Microbiology, Grossman School of Medicine, New York University, New York, NY, USA
- Department of Medicine, Grossman School of Medicine, New York University, New York, NY, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University, New York, NY, USA
| | - Stathis Argyriou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shan Jiang
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daisy Hoagland
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Virus Engineering Center for Therapeutics and Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lina Gao
- Biostatistics Shared Resources, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- VA Portland Health Care System, Portland, OR, USA
| | | | - Kelly Cho
- VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kyung Min Lee
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Jiantao Bian
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Division of Epidemiology, University of Utah, Salt Lake City, UT, USA
| | - Jennifer S Lee
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Sudha K Iyengar
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- VA Northeast Ohio Healthcare System, Cleveland VA Medical Center, Cleveland, OH, USA
| | - Shiuh-Wen Luoh
- VA Portland Health Care System, Portland, OR, USA
- Department of Medicine, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert Striker
- Division of Infectious Diseases, Department of Medicine, University of Wisconsin, Madison, WI, USA
- William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Themistocles L Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Eric E Schadt
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Sema4, Stamford, CT, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Division of Epidemiology, University of Utah, Salt Lake City, UT, USA
| | - Miriam Merad
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Benjamin R tenOever
- Department of Microbiology, Grossman School of Medicine, New York University, New York, NY, USA
- Department of Medicine, Grossman School of Medicine, New York University, New York, NY, USA
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Virus Engineering Center for Therapeutics and Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alexander W Charney
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kristen J Brennand
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - John F Fullard
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA.
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Frąk W, Wojtasińska A, Lisińska W, Młynarska E, Franczyk B, Rysz J. Pathophysiology of Cardiovascular Diseases: New Insights into Molecular Mechanisms of Atherosclerosis, Arterial Hypertension, and Coronary Artery Disease. Biomedicines 2022; 10:biomedicines10081938. [PMID: 36009488 PMCID: PMC9405799 DOI: 10.3390/biomedicines10081938] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/04/2022] [Accepted: 08/06/2022] [Indexed: 12/12/2022] Open
Abstract
Cardiovascular diseases (CVDs) are disorders associated with the heart and circulatory system. Atherosclerosis is its major underlying cause. CVDs are chronic and can remain hidden for a long time. Moreover, CVDs are the leading cause of global morbidity and mortality, thus creating a major public health concern. This review summarizes the available information on the pathophysiological implications of CVDs, focusing on coronary artery disease along with atherosclerosis as its major cause and arterial hypertension. We discuss the endothelium dysfunction, inflammatory factors, and oxidation associated with atherosclerosis. Mechanisms such as dysfunction of the endothelium and inflammation, which have been identified as critical pathways for development of coronary artery disease, have become easier to diagnose in recent years. Relatively recently, evidence has been found indicating that interactions of the molecular and cellular elements such as matrix metalloproteinases, elements of the immune system, and oxidative stress are involved in the pathophysiology of arterial hypertension. Many studies have revealed several important inflammatory and genetic risk factors associated with CVDs. However, further investigation is crucial to improve our knowledge of CVDs progression and, more importantly, accelerate basic research to improve our understanding of the mechanism of pathophysiology.
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47
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Schwarz T, Boltz T, Hou K, Bot M, Duan C, Loohuis LO, Boks MP, Kahn RS, Ophoff RA, Pasaniuc B. Powerful eQTL mapping through low-coverage RNA sequencing. HGG ADVANCES 2022; 3:100103. [PMID: 35519825 PMCID: PMC9062329 DOI: 10.1016/j.xhgg.2022.100103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 03/29/2022] [Indexed: 11/30/2022] Open
Abstract
Mapping genetic variants that regulate gene expression (eQTL mapping) in large-scale RNA sequencing (RNA-seq) studies is often employed to understand functional consequences of regulatory variants. However, the high cost of RNA-seq limits sample size, sequencing depth, and, therefore, discovery power in eQTL studies. In this work, we demonstrate that, given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample and increasing the number of individuals sequenced in the assay. We perform RNA-seq of whole-blood tissue across 1,490 individuals at low coverage (5.9 million reads/sample) and show that the effective power is higher than that of an RNA-seq study of 570 individuals at moderate coverage (13.9 million reads/sample). Next, we leverage synthetic datasets derived from real RNA-seq data (50 million reads/sample) to explore the interplay of coverage and number individuals in eQTL studies, and show that a 10-fold reduction in coverage leads to only a 2.5-fold reduction in statistical power to identify eQTLs. Our work suggests that lowering coverage while increasing the number of individuals in RNA-seq is an effective approach to increase discovery power in eQTL studies.
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Affiliation(s)
- Tommer Schwarz
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Toni Boltz
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Merel Bot
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Chenda Duan
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Loes Olde Loohuis
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Marco P. Boks
- Department of Psychiatry, Brain Center University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands
| | - René S. Kahn
- Department of Psychiatry, Brain Center University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands
- Department of Psychiatry, Icahn School of Medicine, Mount Sinai, NY, USA
| | - Roel A. Ophoff
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
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48
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A human adipose tissue cell-type transcriptome atlas. Cell Rep 2022; 40:111046. [PMID: 35830816 DOI: 10.1016/j.celrep.2022.111046] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 04/29/2022] [Accepted: 06/13/2022] [Indexed: 12/19/2022] Open
Abstract
The importance of defining cell-type-specific genes is well acknowledged. Technological advances facilitate high-resolution sequencing of single cells, but practical challenges remain. Adipose tissue is composed primarily of adipocytes, large buoyant cells requiring extensive, artefact-generating processing for separation and analysis. Thus, adipocyte data are frequently absent from single-cell RNA sequencing (scRNA-seq) datasets, despite being the primary functional cell type. Here, we decipher cell-type-enriched transcriptomes from unfractionated human adipose tissue RNA-seq data. We profile all major constituent cell types, using 527 visceral adipose tissue (VAT) or 646 subcutaneous adipose tissue (SAT) samples, identifying over 2,300 cell-type-enriched transcripts. Sex-subset analysis uncovers a panel of male-only cell-type-enriched genes. By resolving expression profiles of genes differentially expressed between SAT and VAT, we identify mesothelial cells as the primary driver of this variation. This study provides an accessible method to profile cell-type-enriched transcriptomes using bulk RNA-seq, generating a roadmap for adipose tissue biology.
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49
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Ma L, Bryce NS, Turner AW, Di Narzo AF, Rahman K, Xu Y, Ermel R, Sukhavasi K, d’Escamard V, Chandel N, V’Gangula B, Wolhuter K, Kadian-Dodov D, Franzen O, Ruusalepp A, Hao K, Miller CL, Björkegren JLM, Kovacic JC. The HDAC9-associated risk locus promotes coronary artery disease by governing TWIST1. PLoS Genet 2022; 18:e1010261. [PMID: 35714152 PMCID: PMC9246173 DOI: 10.1371/journal.pgen.1010261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 06/30/2022] [Accepted: 05/17/2022] [Indexed: 11/18/2022] Open
Abstract
Genome wide association studies (GWAS) have identified thousands of single nucleotide polymorphisms (SNPs) associated with the risk of common disorders. However, since the large majority of these risk SNPs reside outside gene-coding regions, GWAS generally provide no information about causal mechanisms regarding the specific gene(s) that are affected or the tissue(s) in which these candidate gene(s) exert their effect. The ‘gold standard’ method for understanding causal genes and their mechanisms of action are laborious basic science studies often involving sophisticated knockin or knockout mouse lines, however, these types of studies are impractical as a high-throughput means to understand the many risk variants that cause complex diseases like coronary artery disease (CAD). As a solution, we developed a streamlined, data-driven informatics pipeline to gain mechanistic insights on complex genetic loci. The pipeline begins by understanding the SNPs in a given locus in terms of their relative location and linkage disequilibrium relationships, and then identifies nearby expression quantitative trait loci (eQTLs) to determine their relative independence and the likely tissues that mediate their disease-causal effects. The pipeline then seeks to understand associations with other disease-relevant genes, disease sub-phenotypes, potential causality (Mendelian randomization), and the regulatory and functional involvement of these genes in gene regulatory co-expression networks (GRNs). Here, we applied this pipeline to understand a cluster of SNPs associated with CAD within and immediately adjacent to the gene encoding HDAC9. Our pipeline demonstrated, and validated, that this locus is causal for CAD by modulation of TWIST1 expression levels in the arterial wall, and by also governing a GRN related to metabolic function in skeletal muscle. Our results reconciled numerous prior studies, and also provided clear evidence that this locus does not govern HDAC9 expression, structure or function. This pipeline should be considered as a powerful and efficient way to understand GWAS risk loci in a manner that better reflects the highly complex nature of genetic risk associated with common disorders.
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Affiliation(s)
- Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Nicole S. Bryce
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia; St Vincent’s Clinical School, University of NSW, Sydney, Australia
| | - Adam W. Turner
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, Unites States of America
| | - Antonio F. Di Narzo
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Karishma Rahman
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Yang Xu
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Raili Ermel
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Katyayani Sukhavasi
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Valentina d’Escamard
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Nirupama Chandel
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Bhargavi V’Gangula
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Kathryn Wolhuter
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia; St Vincent’s Clinical School, University of NSW, Sydney, Australia
| | - Daniella Kadian-Dodov
- Zena and Michael A. Wiener Cardiovascular Institute and Marie-Josée and Henry R, Kravis Center for Cardiovascular Health Icahn School of Medicine at Mount Sinai, New York, New York, Unites States of America
| | - Oscar Franzen
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Arno Ruusalepp
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Respiratory Medicine, Shanghai Tenth People’s Hospital, Tongji University, Shanghai, China
| | - Clint L. Miller
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, Unites States of America
| | - Johan L. M. Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Jason C. Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia; St Vincent’s Clinical School, University of NSW, Sydney, Australia
- Zena and Michael A. Wiener Cardiovascular Institute and Marie-Josée and Henry R, Kravis Center for Cardiovascular Health Icahn School of Medicine at Mount Sinai, New York, New York, Unites States of America
- * E-mail:
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50
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Genetic architecture of band neutrophil fraction in Iceland. Commun Biol 2022; 5:525. [PMID: 35650273 PMCID: PMC9160026 DOI: 10.1038/s42003-022-03462-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Accepted: 05/09/2022] [Indexed: 11/22/2022] Open
Abstract
The characteristic lobulated nuclear morphology of granulocytes is partially determined by composition of nuclear envelope proteins. Abnormal nuclear morphology is primarily observed as an increased number of hypolobulated immature neutrophils, called band cells, during infection or in rare envelopathies like Pelger-Huët anomaly. To search for sequence variants affecting nuclear morphology of granulocytes, we performed a genome-wide association study using band neutrophil fraction from 88,101 Icelanders. We describe 13 sequence variants affecting band neutrophil fraction at nine loci. Five of the variants are at the Lamin B receptor (LBR) locus, encoding an inner nuclear membrane protein. Mutations in LBR are linked to Pelger-Huët anomaly. In addition, we identify cosegregation of a rare stop-gain sequence variant in LBR and Pelger Huët anomaly in an Icelandic eight generation pedigree, initially reported in 1963. Two of the other loci include genes which, like LBR, play a role in the nuclear membrane function and integrity. These GWAS results highlight the role proteins of the inner nuclear membrane have as important for neutrophil nuclear morphology. A GWAS in Iceland reveals that variants in inner nuclear membrane proteins are associated with nuclear morphology of granulocytes and band neutrophil fraction.
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