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Grilo LF, Zimmerman KD, Puppala S, Chan J, Huber HF, Li G, Jadhav AYL, Wang B, Li C, Clarke GD, Register TC, Oliveira PJ, Nathanielsz PW, Olivier M, Pereira SP, Cox LA. Cardiac Molecular Analysis Reveals Aging-Associated Metabolic Alterations Promoting Glycosaminoglycans Accumulation via Hexosamine Biosynthetic Pathway. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2309211. [PMID: 39119859 DOI: 10.1002/advs.202309211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 07/17/2024] [Indexed: 08/10/2024]
Abstract
Age is a prominent risk factor for cardiometabolic disease, often leading to heart structural and functional changes. However, precise molecular mechanisms underlying cardiac remodeling and dysfunction exclusively resulting from physiological aging remain elusive. Previous research demonstrated age-related functional alterations in baboons, analogous to humans. The goal of this study is to identify early cardiac molecular alterations preceding functional adaptations, shedding light on the regulation of age-associated changes. Unbiased transcriptomics of left ventricle samples are performed from female baboons aged 7.5-22.1 years (human equivalent ≈30-88 years). Weighted-gene correlation network and pathway enrichment analyses are performed, with histological validation. Modules of transcripts negatively correlated with age implicated declined metabolism-oxidative phosphorylation, tricarboxylic acid cycle, glycolysis, and fatty-acid β-oxidation. Transcripts positively correlated with age suggested a metabolic shift toward glucose-dependent anabolic pathways, including hexosamine biosynthetic pathway (HBP). This shift is associated with increased glycosaminoglycan synthesis, modification, precursor synthesis via HBP, and extracellular matrix accumulation, verified histologically. Upregulated extracellular matrix-induced signaling coincided with glycosaminoglycan accumulation, followed by cardiac hypertrophy-related pathways. Overall, these findings revealed a transcriptional shift in metabolism favoring glycosaminoglycan accumulation through HBP before cardiac hypertrophy. Unveiling this metabolic shift provides potential targets for age-related cardiac diseases, offering novel insights into early age-related mechanisms.
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Affiliation(s)
- Luís F Grilo
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, 3060, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, 3060, Portugal
- Institute for Interdisciplinary Research, PDBEB - Doctoral Programme in Experimental Biology and Biomedicine, University of Coimbra, Coimbra, 3060, Portugal
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
| | - Kip D Zimmerman
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Sobha Puppala
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Jeannie Chan
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Hillary F Huber
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, 78245, USA
| | - Ge Li
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
| | - Avinash Y L Jadhav
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
| | - Benlian Wang
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
| | - Cun Li
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, WY, 82071, USA
| | - Geoffrey D Clarke
- Department of Radiology, University of Texas Health Science Center, San Antonio, TX, 78229, USA
| | - Thomas C Register
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Paulo J Oliveira
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, 3060, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, 3060, Portugal
| | - Peter W Nathanielsz
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, WY, 82071, USA
| | - Michael Olivier
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Susana P Pereira
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, 3060, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, 3060, Portugal
- Laboratory of Metabolism and Exercise (LaMetEx), Research Centre in Physical Activity, Health and Leisure (CIAFEL), Laboratory for Integrative and Translational Research in Population Health (ITR), Faculty of Sports, University of Porto, Porto, 4050, Portugal
| | - Laura A Cox
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, 78245, USA
- Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
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2
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Huang D, Shang W, Xu M, Wan Q, Zhang J, Tang X, Shen Y, Wang Y, Yu Y. Genome-Wide Methylation Analysis Reveals a KCNK3-Prominent Causal Cascade on Hypertension. Circ Res 2024; 135:e76-e93. [PMID: 38841840 DOI: 10.1161/circresaha.124.324455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 05/22/2024] [Indexed: 06/07/2024]
Abstract
BACKGROUND Despite advances in understanding hypertension's genetic structure, how noncoding genetic variants influence it remains unclear. Studying their interaction with DNA methylation is crucial to deciphering this complex disease's genetic mechanisms. METHODS We investigated the genetic and epigenetic interplay in hypertension using whole-genome bisulfite sequencing. Methylation profiling in 918 males revealed allele-specific methylation and methylation quantitative trait loci. We engineered rs1275988T/C mutant mice using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein 9), bred them for homozygosity, and subjected them to a high-salt diet. Telemetry captured their cardiovascular metrics. Protein-DNA interactions were elucidated using DNA pull-downs, mass spectrometry, and Western blots. A wire myograph assessed vascular function, and analysis of the Kcnk3 gene methylation highlighted the mutation's role in hypertension. RESULTS We discovered that DNA methylation-associated genetic effects, especially in non-cytosine-phosphate-guanine (non-CpG) island and noncoding distal regulatory regions, significantly contribute to hypertension predisposition. We identified distinct methylation quantitative trait locus patterns in the hypertensive population and observed that the onset of hypertension is influenced by the transmission of genetic effects through the demethylation process. By evidence-driven prioritization and in vivo experiments, we unearthed rs1275988 in a cell type-specific enhancer as a notable hypertension causal variant, intensifying hypertension through the modulation of local DNA methylation and consequential alterations in Kcnk3 gene expression and vascular remodeling. When exposed to a high-salt diet, mice with the rs1275988C/C genotype exhibited exacerbated hypertension and significant vascular remodeling, underscored by increased aortic wall thickness. The C allele of rs1275988 was associated with elevated DNA methylation levels, driving down the expression of the Kcnk3 gene by attenuating Nr2f2 (nuclear receptor subfamily 2 group F member 2) binding at the enhancer locus. CONCLUSIONS Our research reveals new insights into the complex interplay between genetic variations and DNA methylation in hypertension. We underscore hypomethylation's potential in hypertension onset and identify rs1275988 as a causal variant in vascular remodeling. This work advances our understanding of hypertension's molecular mechanisms and encourages personalized health care strategies.
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Affiliation(s)
- Dandan Huang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
- School of Food Science and Technology, Jiangnan University, Wuxi, China (D.H.)
| | - Wenlong Shang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Mengtong Xu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Qiangyou Wan
- Academy of Integrative Medicine, Shanghai University of Traditional Chinese Medicine (Q.W.)
| | - Jin Zhang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Xiaofeng Tang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Yujun Shen
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Yan Wang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Ying Yu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
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3
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Murphy MB, Yang Z, Subati T, Farber-Eger E, Kim K, Blackwell DJ, Fleming MR, Stark JM, Van Amburg JC, Woodall KK, Van Beusecum JP, Agrawal V, Smart CD, Pitzer A, Atkinson JB, Fogo AB, Bastarache JA, Kirabo A, Wells QS, Madhur MS, Barnett JV, Murray KT. LNK/SH2B3 loss of function increases susceptibility to murine and human atrial fibrillation. Cardiovasc Res 2024; 120:899-913. [PMID: 38377486 PMCID: PMC11218690 DOI: 10.1093/cvr/cvae036] [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: 04/28/2023] [Revised: 08/31/2023] [Accepted: 10/07/2023] [Indexed: 02/22/2024] Open
Abstract
AIMS The lymphocyte adaptor protein (LNK) is a negative regulator of cytokine and growth factor signalling. The rs3184504 variant in SH2B3 reduces LNK function and is linked to cardiovascular, inflammatory, and haematologic disorders, including stroke. In mice, deletion of Lnk causes inflammation and oxidative stress. We hypothesized that Lnk-/- mice are susceptible to atrial fibrillation (AF) and that rs3184504 is associated with AF and AF-related stroke in humans. During inflammation, reactive lipid dicarbonyls are the major components of oxidative injury, and we further hypothesized that these mediators are critical drivers of the AF substrate in Lnk-/- mice. METHODS AND RESULTS Lnk-/- or wild-type (WT) mice were treated with vehicle or 2-hydroxybenzylamine (2-HOBA), a dicarbonyl scavenger, for 3 months. Compared with WT, Lnk-/- mice displayed increased AF duration that was prevented by 2-HOBA. In the Lnk-/- atria, action potentials were prolonged with reduced transient outward K+ current, increased late Na+ current, and reduced peak Na+ current, pro-arrhythmic effects that were inhibited by 2-HOBA. Mitochondrial dysfunction, especially for Complex I, was evident in Lnk-/- atria, while scavenging lipid dicarbonyls prevented this abnormality. Tumour necrosis factor-α (TNF-α) and interleukin-1 beta (IL-1β) were elevated in Lnk-/- plasma and atrial tissue, respectively, both of which caused electrical and bioenergetic remodelling in vitro. Inhibition of soluble TNF-α prevented electrical remodelling and AF susceptibility, while IL-1β inhibition improved mitochondrial respiration but had no effect on AF susceptibility. In a large database of genotyped patients, rs3184504 was associated with AF, as well as AF-related stroke. CONCLUSION These findings identify a novel role for LNK in the pathophysiology of AF in both experimental mice and humans. Moreover, reactive lipid dicarbonyls are critical to the inflammatory AF substrate in Lnk-/- mice and mediate the pro-arrhythmic effects of pro-inflammatory cytokines, primarily through electrical remodelling.
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MESH Headings
- Animals
- Female
- Humans
- Male
- Action Potentials/drug effects
- Adaptor Proteins, Signal Transducing/genetics
- Adaptor Proteins, Signal Transducing/metabolism
- Atrial Fibrillation/metabolism
- Atrial Fibrillation/physiopathology
- Atrial Fibrillation/genetics
- Benzylamines/pharmacology
- Disease Models, Animal
- Genetic Predisposition to Disease
- Heart Rate/drug effects
- Inflammation Mediators/metabolism
- Interleukin-1beta/metabolism
- Interleukin-1beta/genetics
- Intracellular Signaling Peptides and Proteins/genetics
- Intracellular Signaling Peptides and Proteins/metabolism
- Mice, Inbred C57BL
- Mice, Knockout
- Mitochondria, Heart/metabolism
- Mitochondria, Heart/pathology
- Mitochondria, Heart/drug effects
- Myocytes, Cardiac/metabolism
- Myocytes, Cardiac/drug effects
- Myocytes, Cardiac/pathology
- Oxidative Stress/drug effects
- Phenotype
- Signal Transduction
- Tumor Necrosis Factor-alpha/metabolism
- Tumor Necrosis Factor-alpha/genetics
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Affiliation(s)
- Matthew B Murphy
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Zhenjiang Yang
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Tuerdi Subati
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Eric Farber-Eger
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
| | - Kyungsoo Kim
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Daniel J Blackwell
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Matthew R Fleming
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
| | - Joshua M Stark
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Joseph C Van Amburg
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Kaylen K Woodall
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Justin P Van Beusecum
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Vineet Agrawal
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
| | - Charles D Smart
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Ashley Pitzer
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - James B Atkinson
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University School of Medicine, 1161 21 Avenue South, Nashville, TN 37232, USA
| | - Agnes B Fogo
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University School of Medicine, 1161 21 Avenue South, Nashville, TN 37232, USA
| | - Julie A Bastarache
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
| | - Annet Kirabo
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Quinn S Wells
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, USA
| | - Meena S Madhur
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Joey V Barnett
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Katherine T Murray
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
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4
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Yaacov O, Mathiyalagan P, Berk-Rauch HE, Ganesh SK, Zhu L, Hoffmann TJ, Iribarren C, Risch N, Lee D, Chakravarti A. Identification of the Molecular Components of Enhancer-Mediated Gene Expression Variation in Multiple Tissues Regulating Blood Pressure. Hypertension 2024; 81:1500-1510. [PMID: 38747164 PMCID: PMC11168860 DOI: 10.1161/hypertensionaha.123.22538] [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: 12/13/2023] [Accepted: 04/24/2024] [Indexed: 06/14/2024]
Abstract
BACKGROUND Inter-individual variation in blood pressure (BP) arises in part from sequence variants within enhancers modulating the expression of causal genes. We propose that these genes, active in tissues relevant to BP physiology, can be identified from tissue-level epigenomic data and genotypes of BP-phenotyped individuals. METHODS We used chromatin accessibility data from the heart, adrenal, kidney, and artery to identify cis-regulatory elements (CREs) in these tissues and estimate the impact of common human single-nucleotide variants within these CREs on gene expression, using machine learning methods. To identify causal genes, we performed a gene-wise association test. We conducted analyses in 2 separate large-scale cohorts: 77 822 individuals from the Genetic Epidemiology Research on Adult Health and Aging and 315 270 individuals from the UK Biobank. RESULTS We identified 309, 259, 331, and 367 genes (false discovery rate <0.05) for diastolic BP and 191, 184, 204, and 204 genes for systolic BP in the artery, kidney, heart, and adrenal, respectively, in Genetic Epidemiology Research on Adult Health and Aging; 50% to 70% of these genes were replicated in the UK Biobank, significantly higher than the 12% to 15% expected by chance (P<0.0001). These results enabled tissue expression prediction of these 988 to 2875 putative BP genes in individuals of both cohorts to construct an expression polygenic score. This score explained ≈27% of the reported single-nucleotide variant heritability, substantially higher than expected from prior studies. CONCLUSIONS Our work demonstrates the power of tissue-restricted comprehensive CRE analysis, followed by CRE-based expression prediction, for understanding BP regulation in relevant tissues and provides dual-modality supporting evidence, CRE and expression, for the causality genes.
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Affiliation(s)
- Or Yaacov
- Center for Human Genetics and Genomics, NYU Grossman School of Medicine, New York, NY, USA
| | - Prabhu Mathiyalagan
- Center for Human Genetics and Genomics, NYU Grossman School of Medicine, New York, NY, USA
- Benthos Prime Central, Houston, TX, USA
| | - Hanna E. Berk-Rauch
- Center for Human Genetics and Genomics, NYU Grossman School of Medicine, New York, NY, USA
| | - Santhi K. Ganesh
- Department of Internal Medicine & Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Luke Zhu
- Center for Human Genetics and Genomics, NYU Grossman School of Medicine, New York, NY, USA
| | - Thomas J. Hoffmann
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Carlos Iribarren
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Neil Risch
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Dongwon Lee
- Department of Pediatrics, Division of Nephrology, Boston Children’s Hospital, Boston & Harvard Medical School, Boston, MA, USA
| | - Aravinda Chakravarti
- Center for Human Genetics and Genomics, NYU Grossman School of Medicine, New York, NY, USA
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5
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Pandey KN. Genetic and Epigenetic Mechanisms Regulating Blood Pressure and Kidney Dysfunction. Hypertension 2024; 81:1424-1437. [PMID: 38545780 PMCID: PMC11168895 DOI: 10.1161/hypertensionaha.124.22072] [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] [Indexed: 04/20/2024]
Abstract
The pioneering work of Dr Lewis K. Dahl established a relationship between kidney, salt, and high blood pressure (BP), which led to the major genetic-based experimental model of hypertension. BP, a heritable quantitative trait affected by numerous biological and environmental stimuli, is a major cause of morbidity and mortality worldwide and is considered to be a primary modifiable factor in renal, cardiovascular, and cerebrovascular diseases. Genome-wide association studies have identified monogenic and polygenic variants affecting BP in humans. Single nucleotide polymorphisms identified in genome-wide association studies have quantified the heritability of BP and the effect of genetics on hypertensive phenotype. Changes in the transcriptional program of genes may represent consequential determinants of BP, so understanding the mechanisms of the disease process has become a priority in the field. At the molecular level, the onset of hypertension is associated with reprogramming of gene expression influenced by epigenomics. This review highlights the specific genetic variants, mutations, and epigenetic factors associated with high BP and how these mechanisms affect the regulation of hypertension and kidney dysfunction.
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Affiliation(s)
- Kailash N. Pandey
- Department of Physiology, Tulane University Health Sciences Center, School of Medicine, New Orleans, LA
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6
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Amiri Roudbar M, Rosengren MK, Mousavi SF, Fegraeus K, Naboulsi R, Meadows JRS, Lindgren G. Effect of an endothelial regulatory module on plasma proteomics in exercising horses. COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY. PART D, GENOMICS & PROTEOMICS 2024; 52:101265. [PMID: 38906044 DOI: 10.1016/j.cbd.2024.101265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 06/04/2024] [Accepted: 06/04/2024] [Indexed: 06/23/2024]
Abstract
Elite performing exercise requires an intricate modulation of the blood pressure to support the working muscles with oxygen. We have previously identified a genomic regulatory module that associates with differences in blood pressures of importance for elite performance in racehorses. This study aimed to determine the effect of the regulatory module on the protein repertoire. We sampled plasma from 12 Coldblooded trotters divided into two endothelial regulatory module haplotype groups, a sub-elite performing haplotype (SPH) and an elite performing haplotype (EPH), each at rest and exercise. The haplotype groups and their interaction were interrogated in two analyses, i) individual paired ratio analysis for identifying differentially abundant proteins of exercise (DAPE) and interaction (DAPI) between haplotype and exercise, and ii) unpaired ratio analysis for identifying differentially abundant protein of haplotype (DAPH). The proteomics analyses revealed a widespread change in plasma protein content during exercise, with a decreased tendency in protein abundance that is mainly related to lung function, tissue fluids, metabolism, calcium ion pathway and cellular energy metabolism. Furthermore, we provide the first investigation of the proteome variation due to the interaction between exercise and related blood pressure haplotypes, which this difference was related to a faster switch to the lipoprotein and lipid metabolism during exercise for EPH. The molecular signatures identified in the present study contribute to an improved understanding of exercise-related blood pressure regulation.
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Affiliation(s)
- Mahmoud Amiri Roudbar
- Department of Animal Science, Safiabad-Dezful Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Dezful 333, Iran.
| | - Maria K Rosengren
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
| | - Seyedeh Fatemeh Mousavi
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
| | - Kim Fegraeus
- Department of Medical Sciences, Science for Life Laboratory, Uppsala University, Sweden.
| | - Rakan Naboulsi
- Department of Women's and Children's Health, Karolinska Institute, Tomtebodavägen 18A, Stockholm 17177, Sweden.
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132 Uppsala, Sweden.
| | - Gabriella Lindgren
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden; Center for Animal Breeding and Genetics, Department of Biosystems, KU Leuven, 3001 Leuven, Belgium.
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7
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MacCarthy G, Pazoki R. Using Machine Learning to Evaluate the Value of Genetic Liabilities in the Classification of Hypertension within the UK Biobank. J Clin Med 2024; 13:2955. [PMID: 38792496 PMCID: PMC11122671 DOI: 10.3390/jcm13102955] [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: 03/18/2024] [Revised: 05/01/2024] [Accepted: 05/07/2024] [Indexed: 05/26/2024] Open
Abstract
Background and Objective: Hypertension increases the risk of cardiovascular diseases (CVD) such as stroke, heart attack, heart failure, and kidney disease, contributing to global disease burden and premature mortality. Previous studies have utilized statistical and machine learning techniques to develop hypertension prediction models. Only a few have included genetic liabilities and evaluated their predictive values. This study aimed to develop an effective hypertension classification model and investigate the potential influence of genetic liability for multiple risk factors linked to CVD on hypertension risk using the random forest and the neural network. Materials and Methods: The study involved 244,718 European participants, who were divided into training and testing sets. Genetic liabilities were constructed using genetic variants associated with CVD risk factors obtained from genome-wide association studies (GWAS). Various combinations of machine learning models before and after feature selection were tested to develop the best classification model. The models were evaluated using area under the curve (AUC), calibration, and net reclassification improvement in the testing set. Results: The models without genetic liabilities achieved AUCs of 0.70 and 0.72 using the random forest and the neural network methods, respectively. Adding genetic liabilities improved the AUC for the random forest but not for the neural network. The best classification model was achieved when feature selection and classification were performed using random forest (AUC = 0.71, Spiegelhalter z score = 0.10, p-value = 0.92, calibration slope = 0.99). This model included genetic liabilities for total cholesterol and low-density lipoprotein (LDL). Conclusions: The study highlighted that incorporating genetic liabilities for lipids in a machine learning model may provide incremental value for hypertension classification beyond baseline characteristics.
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Affiliation(s)
- Gideon MacCarthy
- Cardiovascular and Metabolic Research Group, Division of Biomedical Sciences, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London UB8 3PH, UK
| | - Raha Pazoki
- Cardiovascular and Metabolic Research Group, Division of Biomedical Sciences, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London UB8 3PH, UK
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary’s Campus, Norfolk Place, Imperial College London, London W2 1PG, UK
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8
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Skampardoni I, Nasrallah IM, Abdulkadir A, Wen J, Melhem R, Mamourian E, Erus G, Doshi J, Singh A, Yang Z, Cui Y, Hwang G, Ren Z, Pomponio R, Srinivasan D, Govindarajan ST, Parmpi P, Wittfeld K, Grabe HJ, Bülow R, Frenzel S, Tosun D, Bilgel M, An Y, Marcus DS, LaMontagne P, Heckbert SR, Austin TR, Launer LJ, Sotiras A, Espeland MA, Masters CL, Maruff P, Fripp J, Johnson SC, Morris JC, Albert MS, Bryan RN, Yaffe K, Völzke H, Ferrucci L, Benzinger TL, Ezzati A, Shinohara RT, Fan Y, Resnick SM, Habes M, Wolk D, Shou H, Nikita K, Davatzikos C. Genetic and Clinical Correlates of AI-Based Brain Aging Patterns in Cognitively Unimpaired Individuals. JAMA Psychiatry 2024; 81:456-467. [PMID: 38353984 PMCID: PMC10867779 DOI: 10.1001/jamapsychiatry.2023.5599] [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: 06/03/2023] [Accepted: 11/29/2023] [Indexed: 02/17/2024]
Abstract
Importance Brain aging elicits complex neuroanatomical changes influenced by multiple age-related pathologies. Understanding the heterogeneity of structural brain changes in aging may provide insights into preclinical stages of neurodegenerative diseases. Objective To derive subgroups with common patterns of variation in participants without diagnosed cognitive impairment (WODCI) in a data-driven manner and relate them to genetics, biomedical measures, and cognitive decline trajectories. Design, Setting, and Participants Data acquisition for this cohort study was performed from 1999 to 2020. Data consolidation and harmonization were conducted from July 2017 to July 2021. Age-specific subgroups of structural brain measures were modeled in 4 decade-long intervals spanning ages 45 to 85 years using a deep learning, semisupervised clustering method leveraging generative adversarial networks. Data were analyzed from July 2021 to February 2023 and were drawn from the Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) international consortium. Individuals WODCI at baseline spanning ages 45 to 85 years were included, with greater than 50 000 data time points. Exposures Individuals WODCI at baseline scan. Main Outcomes and Measures Three subgroups, consistent across decades, were identified within the WODCI population. Associations with genetics, cardiovascular risk factors (CVRFs), amyloid β (Aβ), and future cognitive decline were assessed. Results In a sample of 27 402 individuals (mean [SD] age, 63.0 [8.3] years; 15 146 female [55%]) WODCI, 3 subgroups were identified in contrast with the reference group: a typical aging subgroup, A1, with a specific pattern of modest atrophy and white matter hyperintensity (WMH) load, and 2 accelerated aging subgroups, A2 and A3, with characteristics that were more distinct at age 65 years and older. A2 was associated with hypertension, WMH, and vascular disease-related genetic variants and was enriched for Aβ positivity (ages ≥65 years) and apolipoprotein E (APOE) ε4 carriers. A3 showed severe, widespread atrophy, moderate presence of CVRFs, and greater cognitive decline. Genetic variants associated with A1 were protective for WMH (rs7209235: mean [SD] B = -0.07 [0.01]; P value = 2.31 × 10-9) and Alzheimer disease (rs72932727: mean [SD] B = 0.1 [0.02]; P value = 6.49 × 10-9), whereas the converse was observed for A2 (rs7209235: mean [SD] B = 0.1 [0.01]; P value = 1.73 × 10-15 and rs72932727: mean [SD] B = -0.09 [0.02]; P value = 4.05 × 10-7, respectively); variants in A3 were associated with regional atrophy (rs167684: mean [SD] B = 0.08 [0.01]; P value = 7.22 × 10-12) and white matter integrity measures (rs1636250: mean [SD] B = 0.06 [0.01]; P value = 4.90 × 10-7). Conclusions and Relevance The 3 subgroups showed distinct associations with CVRFs, genetics, and subsequent cognitive decline. These subgroups likely reflect multiple underlying neuropathologic processes and affect susceptibility to Alzheimer disease, paving pathways toward patient stratification at early asymptomatic stages and promoting precision medicine in clinical trials and health care.
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Affiliation(s)
- Ioanna Skampardoni
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
- School of Electrical and Computer Engineering, National Technical University of Athens, Greece
| | - Ilya M. Nasrallah
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
- Department of Radiology, University of Pennsylvania, Philadelphia
| | - Ahmed Abdulkadir
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Junhao Wen
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
- Laboratory of AI and Biomedical Science, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles
| | - Randa Melhem
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Elizabeth Mamourian
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Guray Erus
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Jimit Doshi
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Ashish Singh
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Zhijian Yang
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Yuhan Cui
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Gyujoon Hwang
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Zheng Ren
- Laboratory of AI and Biomedical Science, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles
| | - Raymond Pomponio
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Dhivya Srinivasan
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | | | - Paraskevi Parmpi
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Germany
- German Centre for Neurodegenerative Diseases, Site Greifswald, Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Germany
- German Centre for Neurodegenerative Diseases, Site Greifswald, Greifswald, Germany
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Germany
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| | - Daniel S. Marcus
- Department of Radiology, Washington University School of Medicine, St Louis, Missouri
| | - Pamela LaMontagne
- Department of Radiology, Washington University School of Medicine, St Louis, Missouri
| | - Susan R. Heckbert
- Cardiovascular Health Research Unit, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
| | - Thomas R. Austin
- Cardiovascular Health Research Unit, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
| | - Lenore J. Launer
- Neuroepidemiology Section, Intramural Research Program, National Institute on Aging, Bethesda, Maryland
| | - Aristeidis Sotiras
- Department of Radiology and Institute of Informatics, Washington University in St Louis, St Louis, Missouri
| | - Mark A. Espeland
- Sticht Centre for Healthy Aging and Alzheimer’s Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Colin L. Masters
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Paul Maruff
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Jurgen Fripp
- CSIRO Health and Biosecurity, Australian e-Health Research Centre CSIRO, Brisbane, Queensland, Australia
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison
| | - John C. Morris
- Knight Alzheimer Disease Research Centre, Washington University in St Louis, St Louis, Missouri
| | - Marilyn S. Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - R. Nick Bryan
- Department of Radiology, University of Pennsylvania, Philadelphia
| | - Kristine Yaffe
- Departments of Neurology, Psychiatry and Epidemiology and Biostatistics, University of California San Francisco, San Francisco
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| | - Tammie L.S. Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Ali Ezzati
- Department of Neurology, University of California, Irvine
| | - Russell T. Shinohara
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, & Informatics, University of Pennsylvania, Philadelphia
| | - Yong Fan
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| | - Mohamad Habes
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
| | - David Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia
| | - Haochang Shou
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, & Informatics, University of Pennsylvania, Philadelphia
| | - Konstantina Nikita
- School of Electrical and Computer Engineering, National Technical University of Athens, Greece
| | - Christos Davatzikos
- Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
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9
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Keaton JM, Kamali Z, Xie T, Vaez A, Williams A, Goleva SB, Ani A, Evangelou E, Hellwege JN, Yengo L, Young WJ, Traylor M, Giri A, Zheng Z, Zeng J, Chasman DI, Morris AP, Caulfield MJ, Hwang SJ, Kooner JS, Conen D, Attia JR, Morrison AC, Loos RJF, Kristiansson K, Schmidt R, Hicks AA, Pramstaller PP, Nelson CP, Samani NJ, Risch L, Gyllensten U, Melander O, Riese H, Wilson JF, Campbell H, Rich SS, Psaty BM, Lu Y, Rotter JI, Guo X, Rice KM, Vollenweider P, Sundström J, Langenberg C, Tobin MD, Giedraitis V, Luan J, Tuomilehto J, Kutalik Z, Ripatti S, Salomaa V, Girotto G, Trompet S, Jukema JW, van der Harst P, Ridker PM, Giulianini F, Vitart V, Goel A, Watkins H, Harris SE, Deary IJ, van der Most PJ, Oldehinkel AJ, Keavney BD, Hayward C, Campbell A, Boehnke M, Scott LJ, Boutin T, Mamasoula C, Järvelin MR, Peters A, Gieger C, Lakatta EG, Cucca F, Hui J, Knekt P, Enroth S, De Borst MH, Polašek O, Concas MP, Catamo E, Cocca M, Li-Gao R, Hofer E, Schmidt H, Spedicati B, Waldenberger M, Strachan DP, Laan M, Teumer A, Dörr M, Gudnason V, Cook JP, Ruggiero D, Kolcic I, Boerwinkle E, Traglia M, Lehtimäki T, Raitakari OT, Johnson AD, Newton-Cheh C, Brown MJ, Dominiczak AF, Sever PJ, Poulter N, Chambers JC, Elosua R, Siscovick D, Esko T, Metspalu A, Strawbridge RJ, Laakso M, Hamsten A, Hottenga JJ, de Geus E, Morris AD, Palmer CNA, Nolte IM, Milaneschi Y, Marten J, Wright A, Zeggini E, Howson JMM, O'Donnell CJ, Spector T, Nalls MA, Simonsick EM, Liu Y, van Duijn CM, Butterworth AS, Danesh JN, Menni C, Wareham NJ, Khaw KT, Sun YV, Wilson PWF, Cho K, Visscher PM, Denny JC, Levy D, Edwards TL, Munroe PB, Snieder H, Warren HR. Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits. Nat Genet 2024; 56:778-791. [PMID: 38689001 PMCID: PMC11096100 DOI: 10.1038/s41588-024-01714-w] [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: 03/01/2022] [Accepted: 03/11/2024] [Indexed: 05/02/2024]
Abstract
Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10-8) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5-18.2 mmHg, P = 2.22 × 10-126) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54-9.70; P = 4.13 × 10-44) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781-0.801) to 0.826 (95% CI, 0.817-0.836, ∆AUROC, 0.035, P = 1.98 × 10-34). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research.
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Affiliation(s)
- Jacob M Keaton
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Zoha Kamali
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Tian Xie
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Ahmad Vaez
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran.
| | - Ariel Williams
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Slavina B Goleva
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alireza Ani
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, Ioannina, Greece
| | - Jacklyn N Hellwege
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
| | - Loic Yengo
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - William J Young
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK
| | - Matthew Traylor
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Department of Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Ayush Giri
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Jian Zeng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Daniel I Chasman
- Division of Preventive Medicine Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
| | - Mark J Caulfield
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Shih-Jen Hwang
- Population Sciences Branch, NHLBI Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Jaspal S Kooner
- National Heart and Lung Institute, Imperial College London, London, UK
| | - David Conen
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - John R Attia
- Faculty of Health and Medicine, University of Newcastle, New Lambton Heights, Newcastle, New South Wales, Australia
| | - 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
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kati Kristiansson
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | | | - Andrew A Hicks
- Institute for Biomedicine, Eurac Research, Bolzano, Italy
- University of Lübeck, Lübeck, Germany
| | - Peter P Pramstaller
- Institute for Biomedicine, Eurac Research, Bolzano, Italy
- University of Lübeck, Lübeck, Germany
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Lorenz Risch
- Faculty of Medical Sciences, Private University of the Principality of Liechtenstein, Triesen, Liechtenstein
- Department of Laboratory Medicine, Dr. Risch Anstalt, Vaduz, Liechtenstein
| | - Ulf Gyllensten
- Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Olle Melander
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | - Harriette Riese
- Interdisciplinary Center Psychopathology and Emotional Regulation (ICPE), Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Yingchang Lu
- Vanderbilt Genetic Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Johan Sundström
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, Leicester, UK
- Leicester NIHR Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Vilmantas Giedraitis
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Jaakko Tuomilehto
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Zoltan Kutalik
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Giorgia Girotto
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
- Institute for Maternal and Child Health - IRCCS, Burlo Garofolo, Trieste, Italy
| | - Stella Trompet
- Department Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Pim van der Harst
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Paul M Ridker
- Division of Preventive Medicine Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Franco Giulianini
- Division of Preventive Medicine Brigham and Women's Hospital, Boston, MA, USA
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland
| | - Anuj Goel
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Hugh Watkins
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Sarah E Harris
- Lothian Birth Cohorts Group, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Lothian Birth Cohorts Group, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Albertine J Oldehinkel
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Bernard D Keavney
- Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Manchester Heart Institute, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland
- Centre for Genomic and Experimental Medicine, IGC, University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, IGC, University of Edinburgh, Edinburgh, UK
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Laura J Scott
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Thibaud Boutin
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland
| | | | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Lehrstuhl für Epidemiologie, Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie (IBE), Ludwig-Maximilians-Universität München, Neuherberg, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Edward G Lakatta
- Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Francesco Cucca
- Institute of Genetic and Biomedical Research, National Research Council (CNR), Monserrato, Italy
| | - Jennie Hui
- Busselton Population Medical Research Institute, Perth, Western Australia, Australia
- School of Population and Global Health, The University of Western Australia, Nedlands, Western Australia, Australia
| | - Paul Knekt
- Population Health Unit, Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Stefan Enroth
- Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Uppsala University, Uppsala, Sweden
| | - Martin H De Borst
- Department of Medicine, Division of Nephrology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Ozren Polašek
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS, Burlo Garofolo, Trieste, Italy
| | - Eulalia Catamo
- Institute for Maternal and Child Health - IRCCS, Burlo Garofolo, Trieste, Italy
| | - Massimiliano Cocca
- Institute for Maternal and Child Health - IRCCS, Burlo Garofolo, Trieste, Italy
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Helena Schmidt
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz, Graz, Austria
| | - Beatrice Spedicati
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - David P Strachan
- Population Health Sciences Institute St George's, University of London, London, UK
| | - Maris Laan
- Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Marcus Dörr
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Kopavogur, Iceland
| | - James P Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Daniela Ruggiero
- IRCCS Neuromed, Pozzilli, Italy
- Institute of Genetics and Biophysics - 'A. Buzzati-Traverso', National Research Council of Italy, Naples, Italy
| | - Ivana Kolcic
- Algebra University College, Zagreb, Croatia
- Department of Public Health, University of Split School of Medicine, Split, Croatia
| | - 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
| | - Michela Traglia
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - 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
| | - Andrew D Johnson
- Population Sciences Branch, NHLBI Framingham Heart Study, Framingham, MA, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Christopher Newton-Cheh
- Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Morris J Brown
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Anna F Dominiczak
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Peter J Sever
- International Centre for Circulatory Health, Imperial College London, London, UK
| | - Neil Poulter
- School of Public Health, Imperial College London, London, UK
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
| | - Roberto Elosua
- Hospital del Mar Research Institute (IMIM), Barcelona, Spain
- CIBER Enfermedades Cardiovasculares (CIBERCV), Barcelona, Spain
- Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain
| | | | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Rona J Strawbridge
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
- Health Data Research UK, Glasgow, UK
- Division of Cardiovascular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Kuopio University Hospital, Kuopio, Finland
| | - Anders Hamsten
- Division of Cardiovascular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands
| | - Eco de Geus
- Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centre, Amsterdam, the Netherlands
| | - Andrew D Morris
- Data Science, University of Edinburgh, Edinburgh, UK
- Health Data Research UK, London, UK
| | - Colin N A Palmer
- Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Yuri Milaneschi
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Jonathan Marten
- Centre for Genomic and Experimental Medicine, IGC, University of Edinburgh, Edinburgh, UK
| | - Alan Wright
- Centre for Genomic and Experimental Medicine, IGC, University of Edinburgh, Edinburgh, UK
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Munich, Germany
| | - Joanna M M Howson
- Department of Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Christopher J O'Donnell
- VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tim Spector
- Department of Twin Research, King's College London, London, UK
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias, NIA/NINDS, NIH, Bethesda, MD, USA
- Laboratory of Neurogenetics, NIA, NIH, Bethesda, MD, USA
- DataTecnica LLC, Washington, DC, USA
| | - Eleanor M Simonsick
- Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Yongmei Liu
- Division of Cardiology, Duke University School of Medicine, Durham, NC, USA
| | - Cornelia M van Duijn
- Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK
| | - John N Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK
- Department of Human Genetics, The Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, London, UK
| | | | - Kay-Tee Khaw
- Department of Public Health and Primary Care, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, Georgia, USA
- VA Atlanta Healthcare System, Decatur, GA, USA
| | - Peter W F Wilson
- Emory Clinical Cardiovascular Research Institute, Atlanta, GA, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Kelly Cho
- Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Cardiovascular Health Research Unit, Departments of Medicine and Epidemiology, University of Washington, Seattle, WA, USA
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Joshua C Denny
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Daniel Levy
- Population Sciences Branch, NHLBI Framingham Heart Study, Framingham, MA, USA
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Helen R Warren
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
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10
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Enduru N, Fernandes BS, Zhao Z. Dissecting the shared genetic architecture between Alzheimer's disease and frailty: a cross-trait meta-analyses of genome-wide association studies. Front Genet 2024; 15:1376050. [PMID: 38706793 PMCID: PMC11069310 DOI: 10.3389/fgene.2024.1376050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 04/04/2024] [Indexed: 05/07/2024] Open
Abstract
Introduction: Frailty is the most common medical condition affecting the aging population, and its prevalence increases in the population aged 65 or more. Frailty is commonly diagnosed using the frailty index (FI) or frailty phenotype (FP) assessments. Observational studies have indicated the association of frailty with Alzheimer's disease (AD). However, the shared genetic and biological mechanism of these comorbidity has not been studied. Methods: To assess the genetic relationship between AD and frailty, we examined it at single nucleotide polymorphism (SNP), gene, and pathway levels. Results: Overall, 16 genome-wide significant loci (15 unique loci) (p meta-analysis < 5 × 10-8) and 22 genes (21 unique genes) were identified between AD and frailty using cross-trait meta-analysis. The 8 shared loci implicated 11 genes: CLRN1-AS1, CRHR1, FERMT2, GRK4, LINC01929, LRFN2, MADD, RP11-368P15.1, RP11-166N6.2, RNA5SP459, and ZNF652 between AD and FI, and 8 shared loci between AD and FFS implicated 11 genes: AFF3, C1QTNF4, CLEC16A, FAM180B, FBXL19, GRK4, LINC01104, MAD1L1, RGS12, ZDHHC5, and ZNF521. The loci 4p16.3 (GRK4) was identified in both meta-analyses. The colocalization analysis supported the results of our meta-analysis in these loci. The gene-based analysis revealed 80 genes between AD and frailty, and 4 genes were initially identified in our meta-analyses: C1QTNF4, CRHR1, MAD1L1, and RGS12. The pathway analysis showed enrichment for lipoprotein particle plasma, amyloid fibril formation, protein kinase regulator, and tau protein binding. Conclusion: Overall, our results provide new insights into the genetics of AD and frailty, suggesting the existence of non-causal shared genetic mechanisms between these conditions.
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Affiliation(s)
- Nitesh Enduru
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Brisa S. Fernandes
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Zhongming Zhao
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
- Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, United States
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11
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Zhang J. Hereditary causes of hypertension due to increased sodium transport. Curr Opin Pediatr 2024; 36:211-218. [PMID: 37909881 DOI: 10.1097/mop.0000000000001304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2023]
Abstract
PURPOSE OF REVIEW Hypertension, commonly known as high blood pressure, is a widespread health condition affecting a large number of individuals across the globe. Although lifestyle choices and environmental factors are known to have a significant impact on its development, there is growing recognition of the influence of genetic factors in the pathogenesis of hypertension. This review specifically focuses on the hereditary causes of hypertension that are associated with increased sodium transport through the thiazide-sensitive NaCl cotransporter (NCC) or amiloride-sensitive epithelial sodium channel (ENaC), crucial mechanisms involved in regulating blood pressure in the kidneys. By examining genetic mutations and signaling molecules linked to the dysregulation of sodium transport, this review aims to deepen our understanding of the hereditary causes of hypertension and shed light on potential therapeutic targets. RECENT FINDINGS Liddle syndrome (LS) is a genetic disorder that typically manifests early in life and is characterized by hypertension, hypokalemic metabolic alkalosis, hyporeninemia, and suppressed aldosterone secretion. This condition is primarily caused by gain-of-function mutations in ENaC. In contrast, Pseudohypoaldosteronism type II (PHAII) is marked by hyperkalemia and hypertension, alongside other clinical features such as hyperchloremia, metabolic acidosis, and suppressed plasma renin levels. PHAII results from overactivations of NCC, brought about by gain-of-function mutations in its upstream signaling molecules, including WNK1 (with no lysine (K) 1), WNK4, Kelch-like 3 (KLHL3), and cullin3 (CUL3). SUMMARY NCC and ENaC are integral components, and their malfunctions lead to disorders like LS and PHAII, hereditary causes of hypertension. Current treatments for LS involve ENaC blockers (e.g., triamterene and amiloride) in conjunction with low-sodium diets, effectively normalizing blood pressure and potassium levels. In PHAII, thiazide diuretics, which inhibit NCC, are the mainstay treatment, albeit with some limitations and potential side effects. Ongoing research in developing alternative treatments, including small molecules targeting key regulators, holds promise for more effective and tailored hypertension solutions.
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Affiliation(s)
- Jinwei Zhang
- Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian
- State Key Laboratory of Chemical Biology, Research Center of Chemical Kinomics, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
- Institute of Biomedical and Clinical Sciences, Medical School, Faculty of Health and Life Sciences, University of Exeter, Hatherly Laboratories, Exeter, UK
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12
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Reay WR, Clarke E, Eslick S, Riveros C, Holliday EG, McEvoy MA, Peel R, Hancock S, Scott RJ, Attia JR, Collins CE, Cairns MJ. Using Genetics to Inform Interventions Related to Sodium and Potassium in Hypertension. Circulation 2024; 149:1019-1032. [PMID: 38131187 PMCID: PMC10962430 DOI: 10.1161/circulationaha.123.065394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 11/28/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Hypertension is a key risk factor for major adverse cardiovascular events but remains difficult to treat in many individuals. Dietary interventions are an effective approach to lower blood pressure (BP) but are not equally effective across all individuals. BP is heritable, and genetics may be a useful tool to overcome treatment response heterogeneity. We investigated whether the genetics of BP could be used to identify individuals with hypertension who may receive a particular benefit from lowering sodium intake and boosting potassium levels. METHODS In this observational genetic study, we leveraged cross-sectional data from up to 296 475 genotyped individuals drawn from the UK Biobank cohort for whom BP and urinary electrolytes (sodium and potassium), biomarkers of sodium and potassium intake, were measured. Biologically directed genetic scores for BP were constructed specifically among pathways related to sodium and potassium biology (pharmagenic enrichment scores), as well as unannotated genome-wide scores (conventional polygenic scores). We then tested whether there was a gene-by-environment interaction between urinary electrolytes and these genetic scores on BP. RESULTS Genetic risk and urinary electrolytes both independently correlated with BP. However, urinary sodium was associated with a larger BP increase among individuals with higher genetic risk in sodium- and potassium-related pathways than in those with comparatively lower genetic risk. For example, each SD in urinary sodium was associated with a 1.47-mm Hg increase in systolic BP for those in the top 10% of the distribution of genetic risk in sodium and potassium transport pathways versus a 0.97-mm Hg systolic BP increase in the lowest 10% (P=1.95×10-3). This interaction with urinary sodium remained when considering estimated glomerular filtration rate and indexing sodium to urinary creatinine. There was no strong evidence of an interaction between urinary sodium and a standard genome-wide polygenic score of BP. CONCLUSIONS The data suggest that genetic risk in sodium and potassium pathways could be used in a precision medicine model to direct interventions more specifically in the management of hypertension. Intervention studies are warranted.
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Affiliation(s)
- William R. Reay
- Schools of Biomedical Sciences and Pharmacy (W.R.R., R.J.S., M.J.C.), The University of Newcastle, Callaghan, NSW, Australia
- Precision Medicine Research Program (W.R.R., M.J.C.), New Lambton, NSW, Australia
| | - Erin Clarke
- Health Sciences (E.C., S.E., C.E.C.), The University of Newcastle, Callaghan, NSW, Australia
- Food and Nutrition Research Program (E.C., C.E.C.), New Lambton, NSW, Australia
| | - Shaun Eslick
- Health Sciences (E.C., S.E., C.E.C.), The University of Newcastle, Callaghan, NSW, Australia
| | - Carlos Riveros
- Hunter Medical Research Institute (C.R., E.G.H., J.R.A.), New Lambton, NSW, Australia
| | - Elizabeth G. Holliday
- Medicine and Public Health (E.G.H., R.P., S.H., J.R.A.), The University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute (C.R., E.G.H., J.R.A.), New Lambton, NSW, Australia
| | - Mark A. McEvoy
- Rural Health School, La Trobe University, Bendigo, Victoria, Australia (M.A.M.)
| | - Roseanne Peel
- Medicine and Public Health (E.G.H., R.P., S.H., J.R.A.), The University of Newcastle, Callaghan, NSW, Australia
| | - Stephen Hancock
- Medicine and Public Health (E.G.H., R.P., S.H., J.R.A.), The University of Newcastle, Callaghan, NSW, Australia
| | - Rodney J. Scott
- Schools of Biomedical Sciences and Pharmacy (W.R.R., R.J.S., M.J.C.), The University of Newcastle, Callaghan, NSW, Australia
- Cancer Detection and Therapy Research Program (R.J.S.), New Lambton, NSW, Australia
| | - John R. Attia
- Medicine and Public Health (E.G.H., R.P., S.H., J.R.A.), The University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute (C.R., E.G.H., J.R.A.), New Lambton, NSW, Australia
| | - Clare E. Collins
- Health Sciences (E.C., S.E., C.E.C.), The University of Newcastle, Callaghan, NSW, Australia
- Food and Nutrition Research Program (E.C., C.E.C.), New Lambton, NSW, Australia
| | - Murray J. Cairns
- Schools of Biomedical Sciences and Pharmacy (W.R.R., R.J.S., M.J.C.), The University of Newcastle, Callaghan, NSW, Australia
- Precision Medicine Research Program (W.R.R., M.J.C.), New Lambton, NSW, Australia
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13
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Xu X, Khunsriraksakul C, Eales JM, Rubin S, Scannali D, Saluja S, Talavera D, Markus H, Wang L, Drzal M, Maan A, Lay AC, Prestes PR, Regan J, Diwadkar AR, Denniff M, Rempega G, Ryszawy J, Król R, Dormer JP, Szulinska M, Walczak M, Antczak A, Matías-García PR, Waldenberger M, Woolf AS, Keavney B, Zukowska-Szczechowska E, Wystrychowski W, Zywiec J, Bogdanski P, Danser AHJ, Samani NJ, Guzik TJ, Morris AP, Liu DJ, Charchar FJ, Tomaszewski M. Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets. Nat Commun 2024; 15:2359. [PMID: 38504097 PMCID: PMC10950894 DOI: 10.1038/s41467-024-46132-y] [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: 07/26/2023] [Accepted: 02/14/2024] [Indexed: 03/21/2024] Open
Abstract
Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.
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Affiliation(s)
- Xiaoguang Xu
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | | | - James M Eales
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sebastien Rubin
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - David Scannali
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sushant Saluja
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - David Talavera
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Havell Markus
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Lida Wang
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Maciej Drzal
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Akhlaq Maan
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Abigail C Lay
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Priscilla R Prestes
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Australia
| | - Jeniece Regan
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Avantika R Diwadkar
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Matthew Denniff
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Grzegorz Rempega
- Department of Urology, Medical University of Silesia, Katowice, Poland
| | - Jakub Ryszawy
- Department of Urology, Medical University of Silesia, Katowice, Poland
| | - Robert Król
- Department of General, Vascular and Transplant Surgery, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland
| | - John P Dormer
- Department of Cellular Pathology, University Hospitals of Leicester, Leicester, UK
| | - Monika Szulinska
- Department of Obesity, Metabolic Disorders Treatment and Clinical Dietetics, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - Marta Walczak
- Department of Internal Diseases, Metabolic Disorders and Arterial Hypertension, Poznan University of Medical Sciences, Poznan, Poland
| | - Andrzej Antczak
- Department of Urology and Uro-oncology, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - Pamela R Matías-García
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Melanie Waldenberger
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Adrian S Woolf
- Division of Cell Matrix Biology and Regenerative Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Royal Manchester Children's Hospital and Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Bernard Keavney
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
- Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust Manchester, Manchester Royal Infirmary, Manchester, UK
| | | | - Wojciech Wystrychowski
- Department of General, Vascular and Transplant Surgery, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland
| | - Joanna Zywiec
- Department of Internal Medicine, Diabetology and Nephrology, Zabrze, Medical University of Silesia, Katowice, Poland
| | - Pawel Bogdanski
- Department of Obesity, Metabolic Disorders Treatment and Clinical Dietetics, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - A H Jan Danser
- Department of Internal Medicine, Division of Pharmacology and Vascular Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Tomasz J Guzik
- Department of Internal Medicine, Jagiellonian University Medical College, Kraków, Poland
- Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
- Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Kraków, Poland
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal & Dermatological Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Dajiang J Liu
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Fadi J Charchar
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Australia
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Department of Physiology, University of Melbourne, Melbourne, Australia
| | - Maciej Tomaszewski
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK.
- Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust Manchester, Manchester Royal Infirmary, Manchester, UK.
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14
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Yang ML, Xu C, Gupte T, Hoffmann TJ, Iribarren C, Zhou X, Ganesh SK. Sex-specific genetic architecture of blood pressure. Nat Med 2024; 30:818-828. [PMID: 38459180 DOI: 10.1038/s41591-024-02858-2] [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: 01/17/2023] [Accepted: 02/05/2024] [Indexed: 03/10/2024]
Abstract
The genetic and genomic basis of sex differences in blood pressure (BP) traits remain unstudied at scale. Here, we conducted sex-stratified and combined-sex genome-wide association studies of BP traits using the UK Biobank resource, identifying 1,346 previously reported and 29 new BP trait-associated loci. Among associated loci, 412 were female-specific (Pfemale ≤ 5 × 10-8; Pmale > 5 × 10-8) and 142 were male-specific (Pmale ≤ 5 × 10-8; Pfemale > 5 × 10-8); these sex-specific loci were enriched for hormone-related transcription factors, in particular, estrogen receptor 1. Analyses of gene-by-sex interactions and sexually dimorphic effects identified four genomic regions, showing female-specific associations with diastolic BP or pulse pressure, including the chromosome 13q34-COL4A1/COL4A2 locus. Notably, female-specific pulse pressure-associated loci exhibited enriched acetylated histone H3 Lys27 modifications in arterial tissues and a female-specific association with fibromuscular dysplasia, a female-biased vascular disease; colocalization signals included Chr13q34: COL4A1/COL4A2, Chr9p21: CDKN2B-AS1 and Chr4q32.1: MAP9 regions. Sex-specific and sex-biased polygenic associations of BP traits were associated with multiple cardiovascular traits. These findings suggest potentially clinically significant and BP sex-specific pleiotropic effects on cardiovascular diseases.
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Affiliation(s)
- Min-Lee Yang
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Chang Xu
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Trisha Gupte
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Thomas J Hoffmann
- Department of Epidemiology & Biostatistics, and Institute for Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - Xiang Zhou
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Santhi K Ganesh
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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15
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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 DOI: 10.1161/cir.0000000000001209] [Citation(s) in RCA: 124] [Impact Index Per Article: 124.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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16
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Gomes B, Singh A, O'Sullivan JW, Schnurr TM, Goddard PC, Loong S, Amar D, Hughes JW, Kostur M, Haddad F, Salerno M, Foo R, Montgomery SB, Parikh VN, Meder B, Ashley EA. Genetic architecture of cardiac dynamic flow volumes. Nat Genet 2024; 56:245-257. [PMID: 38082205 DOI: 10.1038/s41588-023-01587-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 10/23/2023] [Indexed: 02/04/2024]
Abstract
Cardiac blood flow is a critical determinant of human health. However, the definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep-learning system to extract cardiac flow and volumes from phase-contrast cardiac magnetic resonance imaging. A mixed-linear model applied to 37,653 individuals from the UK Biobank reveals genome-wide significant associations across cardiac dynamic flow volumes spanning from aortic forward velocity to aortic regurgitation fraction. Mendelian randomization reveals a causal role for aortic root size in aortic valve regurgitation. Among the most significant contributing variants, localizing genes (near ELN, PRDM6 and ADAMTS7) are implicated in connective tissue and blood pressure pathways. Here we show that DeepFlow cardiac flow phenotyping at scale, combined with genotyping data, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function.
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Affiliation(s)
- Bruna Gomes
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
- Informatics for Life, Heidelberg, Germany
| | - Aditya Singh
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Jack W O'Sullivan
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Theresia M Schnurr
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Pagé C Goddard
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Shaun Loong
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - David Amar
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - J Weston Hughes
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Mykhailo Kostur
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Francois Haddad
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Michael Salerno
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Roger Foo
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Stephen B Montgomery
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Victoria N Parikh
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Benjamin Meder
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
- Informatics for Life, Heidelberg, Germany
| | - Euan A Ashley
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA.
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17
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Liu W, Yang C, Lei F, Huang X, Cai J, Chen S, She ZG, Li H. Major lipids and lipoprotein levels and risk of blood pressure elevation: a Mendelian Randomisation study. EBioMedicine 2024; 100:104964. [PMID: 38181703 PMCID: PMC10789600 DOI: 10.1016/j.ebiom.2023.104964] [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: 05/04/2023] [Revised: 12/21/2023] [Accepted: 12/26/2023] [Indexed: 01/07/2024] Open
Abstract
BACKGROUND Quantitative nuclear magnetic resonance (NMR) metabolomics techniques provide detailed measurements of lipoprotein particle concentration. Metabolic dysfunction often represents a cluster of conditions, including dyslipidaemia, hypertension, and diabetes, that increase the risk of cardiovascular diseases (CVDs). However, the causal relationship between lipid profiles and blood pressure (BP) remains unclear. We performed a Mendelian Randomisation (MR) study to disentangle and prioritize the potential causal effects of major lipids, lipoprotein particles, and circulating metabolites on BP and pulse pressure (PP). METHODS We employed single-nucleotide polymorphisms (SNPs) associated with major lipids, lipoprotein particles, and other metabolites from the UK Biobank as instrumental variables. Summary-level data for BP and PP were obtained from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. Two-sample MR and MR Bayesian model averaging approaches (MR-BMA) were conducted to analyse and rank causal associations. FINDINGS Genetically predicted TG was the most likely causal exposure among the major lipids to increase systolic blood pressure (SBP) and diastolic blood pressure (DBP), with marginal inclusion probabilities (MIPs) of 0.993 and 0.847, respectively. Among the majority of lipoproteins and their containing lipids, including major lipids, genetically elevated TG in small high-density lipoproteins (S_HDL_TG) had the strongest association with the increase of SBP and DBP, with MIPs of 0.416 and 0.397, respectively. HDL cholesterol (HDL_C) and low-density lipoprotein cholesterol (LDL_C) were potential causal factors for PP elevation among the major lipids (MIP = 0.927 for HDL_C and MIP = 0.718 for LDL_C). Within the sub-lipoproteins, genetically predicted atherogenic lipoprotein particles (i.e., sub-very low-density lipoprotein (VLDL), intermediate-density lipoprotein (IDL), and LDL particles) had the most likely causal impact on increasing PP. INTERPRETATION This study provides genetic evidence for the causality of lipids on BP indicators. However, the effect size on SBP, DBP, and PP varies depending on the lipids' components and sizes. Understanding this potential relationship may inform the potential benefits of comprehensive management of lipid profiles for BP control. FUNDING Key Research and Development Program of Hubei Province, Science and Technology Innovation Project of Huanggang Central Hospital of Yangtze University, the Hubei Industrial Technology Research Institute of Heart-Brain Diseases, and the Hubei Provincial Engineering Research Centre of Comprehensive Care for Heart-Brain Diseases.
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Affiliation(s)
- Weifang Liu
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Chengzhang Yang
- Department of Cardiology, Huanggang Central Hospital of Yangtze University, Huanggang, China; Huanggang Institute of Translational Medicine, Huanggang, China
| | - Fang Lei
- Institute of Model Animal, Wuhan University, Wuhan, China; Medical Science Research Centre, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xuewei Huang
- Institute of Model Animal, Wuhan University, Wuhan, China; Department of Cardiology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Jingjing Cai
- Institute of Model Animal, Wuhan University, Wuhan, China; Department of Cardiology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Shaoze Chen
- Department of Cardiology, Huanggang Central Hospital of Yangtze University, Huanggang, China.
| | - Zhi-Gang She
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China; Institute of Model Animal, Wuhan University, Wuhan, China.
| | - Hongliang Li
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China; Institute of Model Animal, Wuhan University, Wuhan, China.
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18
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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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19
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Ahles A, Engelhardt S. Genetic Variants of Adrenoceptors. Handb Exp Pharmacol 2024; 285:27-54. [PMID: 37578621 DOI: 10.1007/164_2023_676] [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] [Indexed: 08/15/2023]
Abstract
Adrenoceptors are class A G-protein-coupled receptors grouped into three families (α1-, α2-, and β-adrenoceptors), each one including three members. All nine corresponding adrenoceptor genes display genetic variation in their coding and adjacent non-coding genomic region. Coding variants, i.e., nucleotide exchanges within the transcribed and translated receptor sequence, may result in a difference in amino acid sequence thus altering receptor function and signaling. Such variants have been intensely studied in vitro in overexpression systems and addressed in candidate-gene studies for distinct clinical parameters. In recent years, large cohorts were analyzed in genome-wide association studies (GWAS), where variants are detected as significant in context with specific traits. These studies identified two of the in-depth characterized 18 coding variants in adrenoceptors as repeatedly statistically significant genetic risk factors - p.Arg389Gly in the β1- and p.Thr164Ile in the β2-adrenoceptor, along with 56 variants in the non-coding regions adjacent to the adrenoceptor gene loci, the functional role of which is largely unknown at present. This chapter summarizes current knowledge on the two coding variants in adrenoceptors that have been consistently validated in GWAS and provides a prospective overview on the numerous non-coding variants more recently attributed to adrenoceptor gene loci.
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Affiliation(s)
- Andrea Ahles
- Institute of Pharmacology and Toxicology, Technical University of Munich (TUM), Munich, Germany
| | - Stefan Engelhardt
- Institute of Pharmacology and Toxicology, Technical University of Munich (TUM), Munich, Germany.
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany.
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20
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Singh S, Choudhury A, Hazelhurst S, Crowther NJ, Boua PR, Sorgho H, Agongo G, Nonterah EA, Micklesfield LK, Norris SA, Kisiangani I, Mohamed S, Gómez-Olivé FX, Tollman SM, Choma S, Brandenburg JT, Ramsay M. Genome-wide association study meta-analysis of blood pressure traits and hypertension in sub-Saharan African populations: an AWI-Gen study. Nat Commun 2023; 14:8376. [PMID: 38104120 PMCID: PMC10725455 DOI: 10.1038/s41467-023-44079-0] [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: 01/31/2023] [Accepted: 11/29/2023] [Indexed: 12/19/2023] Open
Abstract
Most hypertension-related genome-wide association studies (GWASs) focus on non-African populations, despite hypertension (a major risk factor for cardiovascular disease) being highly prevalent in Africa. The AWI-Gen study GWAS meta-analysis for blood pressure (BP)-related traits (systolic and diastolic BP, pulse pressure, mean-arterial pressure and hypertension) from three sub-Saharan African geographic regions (N = 10,775), identifies two novel genome-wide significant signals (p < 5E-08): systolic BP near P2RY1 (rs77846204; intergenic variant, p = 4.95E-08) and pulse pressure near LINC01256 (rs80141533; intergenic variant, p = 1.76E-08). No genome-wide signals are detected for the AWI-Gen GWAS meta-analysis with previous African-ancestry GWASs (UK Biobank (African), Uganda Genome Resource). Suggestive signals (p < 5E-06) are observed for all traits, with 29 SNPs associating with more than one trait and several replicating known associations. Polygenic risk scores (PRSs) developed from studies on different ancestries have limited transferability, with multi-ancestry PRS providing better prediction. This study provides insights into the genetics of BP variation in African populations.
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Affiliation(s)
- Surina Singh
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - Nigel J Crowther
- Department of Chemical Pathology, National Health Laboratory Service, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Palwendé R Boua
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Sante, Ouagadougou, Burkina Faso
| | - Hermann Sorgho
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Sante, Ouagadougou, Burkina Faso
| | - Godfred Agongo
- Department of Biochemistry and Forensic Sciences, School of Chemical and Biochemical Sciences, C.K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana
- Navrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana
| | - Engelbert A Nonterah
- Navrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana
- Julius Global Health, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Lisa K Micklesfield
- SAMRC Developmental Pathways for Health Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Shane A Norris
- SAMRC Developmental Pathways for Health Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Health and Human Development, University of Southampton, Southampton, UK
| | | | - Shukri Mohamed
- African Population and Health Research Center, Nairobi, Kenya
| | - Francesc X Gómez-Olivé
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Stephen M Tollman
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Solomon Choma
- Department of Medical Science, Public Health and Health Promotion, School of Health Care Sciences, Faculty of Health Sciences, University of Limpopo, Polokwane, South Africa
| | - J-T Brandenburg
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Strengthening Oncology Services, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
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21
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Khan A, Shang N, Nestor JG, Weng C, Hripcsak G, Harris PC, Gharavi AG, Kiryluk K. Polygenic risk alters the penetrance of monogenic kidney disease. Nat Commun 2023; 14:8318. [PMID: 38097619 PMCID: PMC10721887 DOI: 10.1038/s41467-023-43878-9] [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: 07/11/2023] [Accepted: 11/22/2023] [Indexed: 12/17/2023] Open
Abstract
Chronic kidney disease (CKD) is determined by an interplay of monogenic, polygenic, and environmental risks. Autosomal dominant polycystic kidney disease (ADPKD) and COL4A-associated nephropathy (COL4A-AN) represent the most common forms of monogenic kidney diseases. These disorders have incomplete penetrance and variable expressivity, and we hypothesize that polygenic factors explain some of this variability. By combining SNP array, exome/genome sequence, and electronic health record data from the UK Biobank and All-of-Us cohorts, we demonstrate that the genome-wide polygenic score (GPS) significantly predicts CKD among ADPKD monogenic variant carriers. Compared to the middle tertile of the GPS for noncarriers, ADPKD variant carriers in the top tertile have a 54-fold increased risk of CKD, while ADPKD variant carriers in the bottom tertile have only a 3-fold increased risk of CKD. Similarly, the GPS significantly predicts CKD in COL4A-AN carriers. The carriers in the top tertile of the GPS have a 2.5-fold higher risk of CKD, while the risk for carriers in the bottom tertile is not different from the average population risk. These results suggest that accounting for polygenic risk improves risk stratification in monogenic kidney disease.
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Affiliation(s)
- Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Ning Shang
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Jordan G Nestor
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Peter C Harris
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Ali G Gharavi
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA.
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22
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Fayed MS, Saleh MA, Sabri NA, Elkholy AA. β1-adrenergic receptor polymorphisms: a possible genetic predictor of bisoprolol response in acute coronary syndrome. Future Sci OA 2023; 9:FSO895. [PMID: 37753361 PMCID: PMC10518825 DOI: 10.2144/fsoa-2023-0113] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 08/04/2023] [Indexed: 09/28/2023] Open
Abstract
Aim To investigate the association between beta1-adrenergic receptor (ADRB1) polymorphisms and response to bisoprolol treatment in beta-blocker naive patients with acute coronary syndrome (ACS). Patients & methods Seventy-seven patients received bisoprolol for four weeks. Blood pressure and heart rate were measured at baseline and during treatment. TaqMan allelic discrimination method was utilized for ADRB1 Ser49Gly and Arg389Gly genotyping. Results Arg389Arg carriers showed greater reductions in systolic and diastolic blood pressure (-8.5% ± 7.8% vs -0.76% ± 8.7%, p = 0.000218), and (-9.5% ± 9.7% vs -0.80% ± 11.5%, p = 0.000149), respectively, compared with Gly389 carriers. No statistical difference was found for study's outcomes based on codon 49. Conclusion Arg389Gly polymorphism is a promising bisoprolol response predictor in ACS patients.
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Affiliation(s)
- Mohamed S Fayed
- Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, 11566, Egypt
| | - Mohamed Ayman Saleh
- Department of Cardiology, Faculty of Medicine, Ain Shams University, Cairo, 1181, Egypt
| | - Nagwa A Sabri
- Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, 11566, Egypt
| | - Amal A Elkholy
- Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, 11566, Egypt
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23
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Rios FJ, Sarafian RD, Camargo LL, Montezano AC, Touyz RM. Recent Advances in Understanding the Mechanistic Role of Transient Receptor Potential Ion Channels in Patients With Hypertension. Can J Cardiol 2023; 39:1859-1873. [PMID: 37865227 DOI: 10.1016/j.cjca.2023.10.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 10/17/2023] [Accepted: 10/17/2023] [Indexed: 10/23/2023] Open
Abstract
The transient receptor potential (TRP) channel superfamily is a group of nonselective cation channels that function as cellular sensors for a wide range of physical, chemical, and environmental stimuli. According to sequence homology, TRP channels are categorized into 6 subfamilies: TRP canonical, TRP vanilloid, TRP melastatin, TRP ankyrin, TRP mucolipin, and TRP polycystin. They are widely expressed in different cell types and tissues and have essential roles in various physiological and pathological processes by regulating the concentration of ions (Ca2+, Mg2+, Na+, and K+) and influencing intracellular signalling pathways. Human data and experimental models indicate the importance of TRP channels in vascular homeostasis and hypertension. Furthermore, TRP channels have emerged as key players in oxidative stress and inflammation, important in the pathophysiology of cardiovascular diseases, including hypertension. In this review, we present an overview of the TRP channels with a focus on their role in hypertension. In particular, we highlight mechanisms activated by TRP channels in vascular smooth muscle and endothelial cells and discuss their contribution to processes underlying vascular dysfunction in hypertension.
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Affiliation(s)
- Francisco J Rios
- Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
| | - Raquel D Sarafian
- Institute of Biosciences, Department of Genetics and Evolutionary Biology, University of Sao Paulo, Sao Paulo, Brazil
| | - Livia L Camargo
- Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
| | - Augusto C Montezano
- Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
| | - Rhian M Touyz
- Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Medicine, McGill University, Montreal, Quebec, Canada.
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24
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Lecluze E, Lettre G. Association Analyses of Predicted Loss-of-Function Variants Prioritized 15 Genes as Blood Pressure Regulators. Can J Cardiol 2023; 39:1888-1897. [PMID: 37451613 DOI: 10.1016/j.cjca.2023.07.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 06/26/2023] [Accepted: 07/07/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Hypertension, clinically defined by elevated blood pressure (BP), is an important cause of mortality and morbidity worldwide. Many risk factors for hypertension are known, including a positive family history, which suggests that genetics contribute to interindividual BP variation. Genome-wide association studies (GWAS) have identified > 1000 loci associated with BP, yet the identity of the genes responsible for these associations remains largely unknown. METHODS To pinpoint genes that causally affect variation of BP in humans, we analyzed predicted loss-of-function (pLoF) variants in the UK Biobank whole-exome sequencing dataset (n = 454,709 participants, 6% non-European ancestry). We analyzed genetic associations between systolic or diastolic BP (SBP/DBP) and single pLoF variants (additive and recessive genetic models) as well as with the burden of very rare pLoF variants (minor allele frequency [MAF] < 0.01%). RESULTS Single pLoF variants in 10 genes were associated with BP (ANKDD1B, ENPEP, PNCK, BTN3A2, C1orf145 [OBSCN-AS1], CASP9, DBH, KIAA1161 [MYORG], OR4X1, and TMC3). We also found a burden of rare pLoF variants in 5 additional genes associated with BP (TTN, NOS3, FES, SMAD6, COL21A1). Except for PNCK, which is located on the X-chromosome, these genes map near variants previously associated with BP by GWAS, validating the study of pLoF variants to prioritize causal genes at GWAS loci. CONCLUSIONS Our study highlights 15 genes that likely modulate BP in humans, including 5 genes that harbour pLoF variants associated with lower BP.
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Affiliation(s)
- Estelle Lecluze
- Montreal Heart Institute, Montréal, Québec, Canada; Faculté de Médecine, Université de Montréal, Montréal, Québec, Canada
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, Québec, Canada; Faculté de Médecine, Université de Montréal, Montréal, Québec, Canada.
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25
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Lee D, Han SK, Yaacov O, Berk-Rauch H, Mathiyalagan P, Ganesh SK, Chakravarti A. Tissue-specific and tissue-agnostic effects of genome sequence variation modulating blood pressure. Cell Rep 2023; 42:113351. [PMID: 37910504 PMCID: PMC10726310 DOI: 10.1016/j.celrep.2023.113351] [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: 10/25/2022] [Revised: 09/21/2023] [Accepted: 10/11/2023] [Indexed: 11/03/2023] Open
Abstract
Genome-wide association studies (GWASs) have identified numerous variants associated with polygenic traits and diseases. However, with few exceptions, a mechanistic understanding of which variants affect which genes in which tissues to modulate trait variation is lacking. Here, we present genomic analyses to explain trait heritability of blood pressure (BP) through the genetics of transcriptional regulation using GWASs, multiomics data from different tissues, and machine learning approaches. Approximately 500,000 predicted regulatory variants across four tissues explain 33.4% of variant heritability: 2.5%, 5.3%, 7.7%, and 11.8% for kidney-, adrenal-, heart-, and artery-specific variants, respectively. Variation in the enhancers involved shows greater tissue specificity than in the genes they regulate, suggesting that gene regulatory networks perturbed by enhancer variants in a tissue relevant to a phenotype are the major source of interindividual variation in BP. Thus, our study provides an approach to scan human tissue and cell types for their physiological contribution to any trait.
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Affiliation(s)
- Dongwon Lee
- Department of Pediatrics, Division of Nephrology, Boston Children's Hospital, Boston & Harvard Medical School, Boston, MA, USA.
| | - Seong Kyu Han
- Department of Pediatrics, Division of Nephrology, Boston Children's Hospital, Boston & Harvard Medical School, Boston, MA, USA
| | - Or Yaacov
- Center for Human Genetics and Genomics, New York University Grossman School of Medicine, New York, NY, USA
| | - Hanna Berk-Rauch
- Center for Human Genetics and Genomics, New York University Grossman School of Medicine, New York, NY, USA
| | - Prabhu Mathiyalagan
- Center for Human Genetics and Genomics, New York University Grossman School of Medicine, New York, NY, USA
| | - Santhi K Ganesh
- Department of Internal Medicine & Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Aravinda Chakravarti
- Center for Human Genetics and Genomics, New York University Grossman School of Medicine, New York, NY, USA.
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26
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Grilo LF, Zimmerman KD, Puppala S, Chan J, Huber HF, Li G, Jadhav AYL, Wang B, Li C, Clarke GD, Register TC, Oliveira PJ, Nathanielsz PW, Olivier M, Pereira SP, Cox LA. Cardiac Molecular Analysis Reveals Aging-Associated Metabolic Alterations Promoting Glycosaminoglycans Accumulation Via Hexosamine Biosynthetic Pathway. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.17.567640. [PMID: 38014295 PMCID: PMC10680868 DOI: 10.1101/2023.11.17.567640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Age is a prominent risk factor for cardiometabolic disease, and often leads to heart structural and functional changes. However, precise molecular mechanisms underlying cardiac remodeling and dysfunction resulting from physiological aging per se remain elusive. Understanding these mechanisms requires biological models with optimal translation to humans. Previous research demonstrated that baboons undergo age-related reduction in ejection fraction and increased heart sphericity, mirroring changes observed in humans. The goal of this study was to identify early cardiac molecular alterations that precede functional adaptations, shedding light on the regulation of age-associated changes. We performed unbiased transcriptomics of left ventricle (LV) samples from female baboons aged 7.5-22.1 years (human equivalent ~30-88 years). Weighted-gene correlation network and pathway enrichment analyses were performed to identify potential age-associated mechanisms in LV, with histological validation. Myocardial modules of transcripts negatively associated with age were primarily enriched for cardiac metabolism, including oxidative phosphorylation, tricarboxylic acid cycle, glycolysis, and fatty-acid β-oxidation. Transcripts positively correlated with age suggest upregulation of glucose uptake, pentose phosphate pathway, and hexosamine biosynthetic pathway (HBP), indicating a metabolic shift towards glucose-dependent anabolic pathways. Upregulation of HBP commonly results in increased glycosaminoglycan precursor synthesis. Transcripts involved in glycosaminoglycan synthesis, modification, and intermediate metabolism were also upregulated in older animals, while glycosaminoglycan degradation transcripts were downregulated with age. These alterations would promote glycosaminoglycan accumulation, which was verified histologically. Upregulation of extracellular matrix (ECM)-induced signaling pathways temporally coincided with glycosaminoglycan accumulation. We found a subsequent upregulation of cardiac hypertrophy-related pathways and an increase in cardiomyocyte width. Overall, our findings revealed a transcriptional shift in metabolism from catabolic to anabolic pathways that leads to ECM glycosaminoglycan accumulation through HBP prior to upregulation of transcripts of cardiac hypertrophy-related pathways. This study illuminates cellular mechanisms that precede development of cardiac hypertrophy, providing novel potential targets to remediate age-related cardiac diseases.
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Affiliation(s)
- Luís F. Grilo
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Portugal
- University of Coimbra, Institute for Interdisciplinary Research, PDBEB - Doctoral Programme in Experimental Biology and Biomedicine
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Kip D. Zimmerman
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Sobha Puppala
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Jeannie Chan
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Hillary F. Huber
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Ge Li
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Avinash Y. L. Jadhav
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Benlian Wang
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Cun Li
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, Wyoming, USA
| | - Geoffrey D. Clarke
- Department of Radiology, University of Texas Health Science Center, San Antonio, Texas
| | - Thomas C. Register
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Paulo J. Oliveira
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Portugal
| | - Peter W. Nathanielsz
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, Wyoming, USA
| | - Michael Olivier
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Susana P. Pereira
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Portugal
- Laboratory of Metabolism and Exercise (LaMetEx), Research Centre in Physical Activity, Health and Leisure (CIAFEL), Laboratory for Integrative and Translational Research in Population Health (ITR), Faculty of Sports, University of Porto, Porto, Portugal
| | - Laura A. Cox
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
- Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
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27
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Lin E, Kuo PH, Liu YL, Wang TJ, Yang AC, Tsai SJ. The cysteine-altering p.R544C variant in the NOTCH3 gene is a probable candidate for blood pressure and relevant traits in the Taiwan Biobank. J Neurol 2023; 270:5536-5544. [PMID: 37526664 DOI: 10.1007/s00415-023-11909-6] [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: 12/05/2022] [Revised: 06/17/2023] [Accepted: 07/27/2023] [Indexed: 08/02/2023]
Abstract
BACKGROUND The cysteine-altering variants in NOTCH3 have been suggested to be associated with stroke, dementia, and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), where aberrant blood pressure levels represent the characteristics of these diseases. We aimed to assess whether the cysteine-altering p.Arg544Cys (p.R544C; rs201118034) variant and common single nucleotide variants (SNVs) in NOTCH3 could contribute to systolic and diastolic blood pressure and related phenotypes in the Taiwan Biobank. METHODS We employed a discovery sample of 68,925 individuals, an independent replication sample of 45,676 individuals, and a combined/total sample of 114,601 individuals; all from the Taiwan Biobank. Blood pressure, such as systolic and diastolic blood pressure, was measured for all participants. Association was evaluated using a general linear model, where results were considered statistically significant if the P value < 0.05 divided by the number of independent tests per model. RESULTS From our analysis, we identified and replicated three novel candidates for blood pressure that have not previously been reported: the cysteine-altering p.R544C variant for systolic blood pressure, the common SNV rs11669950 for diastolic blood pressure, and the common SNV rs4808235 for diastolic blood pressure. We also generalized two previously identified SNVs (i.e., rs10418305 and rs7408868) in NOTCH3 for blood pressure in European and non-Taiwanese East Asian populations to the Taiwanese population. Moreover, the participants with NOTCH3 p.R544C had an increased stroke frequency (P < 1.0 × 10-5) and a higher dementia frequency (P = 2.0 × 10-4) compared with the whole Taiwan Biobank population in the combined/total sample. CONCLUSION NOTCH3 is a strong candidate for a role in stroke, dementia, and CADASIL, which has previously been linked to blood pressure changes. While our preliminary study suggests that NOTCH3 p.R544C may influence blood pressure, stroke, and dementia in the Taiwan Biobank, replication in a well-powered external sample is required. This study also underlines considerable prospects of detecting novel genetic biomarkers in underrepresented worldwide populations.
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Affiliation(s)
- Eugene Lin
- Department of Biostatistics, University of Washington, 3980 15th Avenue NE, Box 351617, Seattle, WA, 98195, USA.
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, 98195, USA.
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, 40402, Taiwan.
| | - Po-Hsiu Kuo
- Department of Public Health, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, 10617, Taiwan
- Department of Psychiatry, National Taiwan University Hospital, Taipei, 100, Taiwan
| | - Yu-Li Liu
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli County, 35053, Taiwan
| | - Tso-Jen Wang
- Taoyuan Psychiatric Center, Ministry of Health and Welfare, Taoyuan, 33058, Taiwan
| | - Albert C Yang
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Shih-Pai Road, Sec. 2, Taipei, 11217, Taiwan.
- Division of Psychiatry, National Yang Ming Chiao Tung University, Taipei, 112304, Taiwan.
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28
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Bjornsdottir G, Chalmer MA, Stefansdottir L, Skuladottir AT, Einarsson G, Andresdottir M, Beyter D, Ferkingstad E, Gretarsdottir S, Halldorsson BV, Halldorsson GH, Helgadottir A, Helgason H, Hjorleifsson Eldjarn G, Jonasdottir A, Jonasdottir A, Jonsdottir I, Knowlton KU, Nadauld LD, Lund SH, Magnusson OT, Melsted P, Moore KHS, Oddsson A, Olason PI, Sigurdsson A, Stefansson OA, Saemundsdottir J, Sveinbjornsson G, Tragante V, Unnsteinsdottir U, Walters GB, Zink F, Rødevand L, Andreassen OA, Igland J, Lie RT, Haavik J, Banasik K, Brunak S, Didriksen M, T Bruun M, Erikstrup C, Kogelman LJA, Nielsen KR, Sørensen E, Pedersen OB, Ullum H, Masson G, Thorsteinsdottir U, Olesen J, Ludvigsson P, Thorarensen O, Bjornsdottir A, Sigurdardottir GR, Sveinsson OA, Ostrowski SR, Holm H, Gudbjartsson DF, Thorleifsson G, Sulem P, Stefansson H, Thorgeirsson TE, Hansen TF, Stefansson K. Rare variants with large effects provide functional insights into the pathology of migraine subtypes, with and without aura. Nat Genet 2023; 55:1843-1853. [PMID: 37884687 PMCID: PMC10632135 DOI: 10.1038/s41588-023-01538-0] [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: 12/02/2022] [Accepted: 09/18/2023] [Indexed: 10/28/2023]
Abstract
Migraine is a complex neurovascular disease with a range of severity and symptoms, yet mostly studied as one phenotype in genome-wide association studies (GWAS). Here we combine large GWAS datasets from six European populations to study the main migraine subtypes, migraine with aura (MA) and migraine without aura (MO). We identified four new MA-associated variants (in PRRT2, PALMD, ABO and LRRK2) and classified 13 MO-associated variants. Rare variants with large effects highlight three genes. A rare frameshift variant in brain-expressed PRRT2 confers large risk of MA and epilepsy, but not MO. A burden test of rare loss-of-function variants in SCN11A, encoding a neuron-expressed sodium channel with a key role in pain sensation, shows strong protection against migraine. Finally, a rare variant with cis-regulatory effects on KCNK5 confers large protection against migraine and brain aneurysms. Our findings offer new insights with therapeutic potential into the complex biology of migraine and its subtypes.
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Affiliation(s)
| | - Mona A Chalmer
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Rigshospitalet-Glostrup, Copenhagen, Denmark
| | | | | | | | | | | | | | | | - Bjarni V Halldorsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Reykjavik University, School of Technology, Reykjavik, Iceland
| | - Gisli H Halldorsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Hannes Helgason
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural 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
| | | | | | - Sigrun H Lund
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Physical Sciences, School of Engineering and Natural 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
| | | | | | | | | | | | | | | | | | | | | | | | - Linn Rødevand
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jannicke Igland
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
- Department of Health and Social Science, Centre for Evidence-Based Practice, Western Norway University of Applied Science, Bergen, Norway
| | - Rolv T Lie
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen, Norway
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maria Didriksen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Mie T Bruun
- Department of Clinical Immunology, Odense University Hospital, Odense, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine Health, Aarhus University, Aarhus, Denmark
| | - Lisette J A Kogelman
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Rigshospitalet-Glostrup, Copenhagen, Denmark
| | - Kaspar R Nielsen
- Department of Clinical Immunology, Aalborg University Hospital, Aalborg, Denmark
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Erik Sørensen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Ole B Pedersen
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Jes Olesen
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Rigshospitalet-Glostrup, Copenhagen, Denmark
| | - Petur Ludvigsson
- Department of Pediatrics, Landspitali University Hostpital, Reykjavik, Iceland
| | - Olafur Thorarensen
- Department of Pediatrics, Landspitali University Hostpital, Reykjavik, Iceland
| | | | | | - Olafur A Sveinsson
- Laeknasetrid Clinic, Reykjavik, Iceland
- Department of Neurology, Landspitali University Hospital, Reykjavik, Iceland
| | - Sisse R Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - 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
| | | | | | | | | | - Thomas F Hansen
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Rigshospitalet-Glostrup, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - 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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Li B, Qu Y, Fan Z, Gong X, Xu H, Wu L, Yan C. Causal relationships between blood lipids and major psychiatric disorders: Univariable and multivariable mendelian randomization analysis. BMC Med Genomics 2023; 16:250. [PMID: 37853421 PMCID: PMC10585856 DOI: 10.1186/s12920-023-01692-8] [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: 02/17/2023] [Accepted: 10/05/2023] [Indexed: 10/20/2023] Open
Abstract
BACKGROUND Whether the positive associations of blood lipids with psychiatric disorders are causal is uncertain. We conducted this two-sample Mendelian randomization (MR) analysis to comprehensively investigate associations of blood lipids with psychiatric disorders. METHODS Univariable and multivariable models were established for MR analyses. Inverse variance-weighted (IVW) MR was employed as the main approach; weighted median and MR-Egger were used as sensitivity analysis methods. The possibility of violating MR assumptions was evaluated utilizing several sensitivity analyses, including heterogeneity statistics, horizontal pleiotropy statistics, single SNP analysis, leave-one-out analysis and MR-PRESSO analysis. As instrumental variables, we screened 362 independent single-nucleotide polymorphisms (SNP) related to blood lipids from a recent genome-wide association study involving 76,627 individuals of European ancestry, with a genome-wide significance level of p < 5 × 10- 8. Summary-level information for the six psychiatric disorders was extracted from Psychiatric Genomics Consortium and Alzheimer Disease Genetics Consortium. RESULTS We observed eight significant associations in univariable MR analysis, four of which were corroborated by multivariable MR (MVMR) analysis modified for the other three lipid traits: high-density lipoprotein cholesterol (HDL-C) level with the risk of PTSD (OR = 0.91, 95% CI = 0.85-0.97, p = 0.002) and AD (OR = 0.79, 95% CI = 0.71-0.88, p < 0.001) and triglycerides (TG) level with the risk of MDD (OR = 1.02, 95% CI = 1.003-1.03, p = 0.01) and panic disorder (OR = 0.83, 95% CI = 0.74-0.92, p < 0.001). In addition, four associations were not significant in MVMR analysis after adjustment for three lipid traits: total cholesterol (TC) level with the risk of PTSD, low-density lipoprotein cholesterol (LDL-C) level with the risk of MDD and AD and TG level with the risk of AD. CONCLUSIONS Our results show that blood lipids and psychiatric disorders may be related in a causal manner. This shows that abnormal blood lipid levels may act as reliable biomarker of psychiatric disorders and as suitable targets for their prevention and treatment.
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Affiliation(s)
- Bozhi Li
- Integrative Medicine Research Center, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Yue Qu
- Integrative Medicine Research Center, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Zhixin Fan
- Integrative Medicine Research Center, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Xiayu Gong
- Integrative Medicine Research Center, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Hanfang Xu
- Integrative Medicine Research Center, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Lili Wu
- Integrative Medicine Research Center, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
| | - Can Yan
- Integrative Medicine Research Center, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
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Sohail M, Palma-Martínez MJ, Chong AY, Quinto-Cortés CD, Barberena-Jonas C, Medina-Muñoz SG, Ragsdale A, Delgado-Sánchez G, Cruz-Hervert LP, Ferreyra-Reyes L, Ferreira-Guerrero E, Mongua-Rodríguez N, Canizales-Quintero S, Jimenez-Kaufmann A, Moreno-Macías H, Aguilar-Salinas CA, Auckland K, Cortés A, Acuña-Alonzo V, Gignoux CR, Wojcik GL, Ioannidis AG, Fernández-Valverde SL, Hill AVS, Tusié-Luna MT, Mentzer AJ, Novembre J, García-García L, Moreno-Estrada A. Mexican Biobank advances population and medical genomics of diverse ancestries. Nature 2023; 622:775-783. [PMID: 37821706 PMCID: PMC10600006 DOI: 10.1038/s41586-023-06560-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 08/22/2023] [Indexed: 10/13/2023]
Abstract
Latin America continues to be severely underrepresented in genomics research, and fine-scale genetic histories and complex trait architectures remain hidden owing to insufficient data1. To fill this gap, the Mexican Biobank project genotyped 6,057 individuals from 898 rural and urban localities across all 32 states in Mexico at a resolution of 1.8 million genome-wide markers with linked complex trait and disease information creating a valuable nationwide genotype-phenotype database. Here, using ancestry deconvolution and inference of identity-by-descent segments, we inferred ancestral population sizes across Mesoamerican regions over time, unravelling Indigenous, colonial and postcolonial demographic dynamics2-6. We observed variation in runs of homozygosity among genomic regions with different ancestries reflecting distinct demographic histories and, in turn, different distributions of rare deleterious variants. We conducted genome-wide association studies (GWAS) for 22 complex traits and found that several traits are better predicted using the Mexican Biobank GWAS compared to the UK Biobank GWAS7,8. We identified genetic and environmental factors associating with trait variation, such as the length of the genome in runs of homozygosity as a predictor for body mass index, triglycerides, glucose and height. This study provides insights into the genetic histories of individuals in Mexico and dissects their complex trait architectures, both crucial for making precision and preventive medicine initiatives accessible worldwide.
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Affiliation(s)
- Mashaal Sohail
- Unidad de Genómica Avanzada (UGA-LANGEBIO), Centro de Investigación y Estudios Avanzados del IPN (Cinvestav), Irapuato, Mexico.
- Department of Human Genetics, University of Chicago, Chicago, IL, USA.
- Centro de Ciencias Genómicas (CCG), Universidad Nacional Autónoma de México (UNAM), Cuernavaca, Mexico.
| | - María J Palma-Martínez
- Unidad de Genómica Avanzada (UGA-LANGEBIO), Centro de Investigación y Estudios Avanzados del IPN (Cinvestav), Irapuato, Mexico
| | - Amanda Y Chong
- The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Consuelo D Quinto-Cortés
- Unidad de Genómica Avanzada (UGA-LANGEBIO), Centro de Investigación y Estudios Avanzados del IPN (Cinvestav), Irapuato, Mexico
| | - Carmina Barberena-Jonas
- Unidad de Genómica Avanzada (UGA-LANGEBIO), Centro de Investigación y Estudios Avanzados del IPN (Cinvestav), Irapuato, Mexico
| | - Santiago G Medina-Muñoz
- Unidad de Genómica Avanzada (UGA-LANGEBIO), Centro de Investigación y Estudios Avanzados del IPN (Cinvestav), Irapuato, Mexico
| | - Aaron Ragsdale
- Unidad de Genómica Avanzada (UGA-LANGEBIO), Centro de Investigación y Estudios Avanzados del IPN (Cinvestav), Irapuato, Mexico
- Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Luis Pablo Cruz-Hervert
- Instituto Nacional de Salud Pública (INSP), Cuernavaca, Mexico
- División de Estudios de Posgrado e Investigación, Facultad de Odontología, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
| | | | | | | | | | - Andrés Jimenez-Kaufmann
- Unidad de Genómica Avanzada (UGA-LANGEBIO), Centro de Investigación y Estudios Avanzados del IPN (Cinvestav), Irapuato, Mexico
| | - Hortensia Moreno-Macías
- Unidad de Biología Molecular y Medicina Genómica, Instituto de Investigaciones Biomédicas UNAM/Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
- Universidad Autónoma Metropolitana, Mexico City, Mexico
| | - Carlos A Aguilar-Salinas
- Division de Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Kathryn Auckland
- The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Adrián Cortés
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | | | - Christopher R Gignoux
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Genevieve L Wojcik
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Selene L Fernández-Valverde
- Unidad de Genómica Avanzada (UGA-LANGEBIO), Centro de Investigación y Estudios Avanzados del IPN (Cinvestav), Irapuato, Mexico
- School of Biotechnology and Biomolecular Sciences and the RNA Institute, The University of New South Wales, Sydney, New South Wales, Australia
| | - Adrian V S Hill
- The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- The Jenner Institute, University of Oxford, Oxford, UK
| | - María Teresa Tusié-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto de Investigaciones Biomédicas UNAM/Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Alexander J Mentzer
- The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | | | - Andrés Moreno-Estrada
- Unidad de Genómica Avanzada (UGA-LANGEBIO), Centro de Investigación y Estudios Avanzados del IPN (Cinvestav), Irapuato, Mexico.
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Seryapina AA, Malyavko AA, Polityko YK, Yanshole LV, Tsentalovich YP, Markel AL. Metabolic profile of blood serum in experimental arterial hypertension. Vavilovskii Zhurnal Genet Selektsii 2023; 27:530-538. [PMID: 37867609 PMCID: PMC10587007 DOI: 10.18699/vjgb-23-64] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 03/01/2023] [Accepted: 03/02/2023] [Indexed: 10/24/2023] Open
Abstract
The etiology of essential hypertension is intricate, since it employs simultaneously various body systems related to the regulation of blood pressure in one way or another: the sympathetic nervous system, renin-angiotensin-aldosterone and hypothalamic-pituitary-adrenal systems, renal and endothelial mechanisms. The pathogenesis of hypertension is influenced by a variety of both genetic and environmental factors, which determines the heterogeneity of the disease in human population. Hence, there is a need to perform research on experimental models - inbred animal strains, one of them being ISIAH rat strain, which is designed to simulate inherited stress-induced arterial hypertension as close as possible to primary (or essential) hypertension in humans. To determine specific markers of diseases, various omics technologies are applied, including metabolomics, which makes it possible to evaluate the content of low-molecular compounds - amino acids, lipids, carbohydrates, nucleic acids fragments - in biological samples available for clinical analysis (blood and urine). We analyzed the metabolic profile of the blood serum of male ISIAH rats with a genetic stress-dependent form of arterial hypertension in comparison with the normotensive WAG rats. Using the method of nuclear magnetic resonance spectroscopy (NMR spectroscopy), 56 metabolites in blood serum samples were identified, 18 of which were shown to have significant interstrain differences in serum concentrations. Statistical analysis of the data obtained showed that the hypertensive status of ISIAH rats is characterized by increased concentrations of leucine, isoleucine, valine, myo-inositol, isobutyrate, glutamate, glutamine, ornithine and creatine phosphate, and reduced concentrations of 2-hydroxyisobutyrate, betaine, tyrosine and tryptophan. Such a ratio of the metabolite concentrations is associated with changes in the regulation of glucose metabolism (metabolic markers - leucine, isoleucine, valine, myo-inositol), of nitric oxide synthesis (ornithine) and catecholamine pathway (tyrosine), and with inflammatory processes (metabolic markers - betaine, tryptophan), all of these changes being typical for hypertensive status. Thus, metabolic profiling of the stress-dependent form of arterial hypertension seems to be an important result for a personalized approach to the prevention and treatment of hypertensive disease.
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Affiliation(s)
- A A Seryapina
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - A A Malyavko
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Yu K Polityko
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - L V Yanshole
- International Tomography Center of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Yu P Tsentalovich
- International Tomography Center of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - A L Markel
- Novosibirsk State University, Novosibirsk, Russia
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Webber D, Cao J, Dominguez D, Gladman DD, Knight A, Levy DM, Liao F, Ng L, Paterson AD, Touma Z, Wither J, Urowitz M, Silverman ED, Hiraki LT. Genetics of osteonecrosis in children and adults with systemic lupus erythematosus. Rheumatology (Oxford) 2023; 62:3205-3212. [PMID: 36651668 DOI: 10.1093/rheumatology/kead016] [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] [Received: 08/23/2022] [Accepted: 12/19/2022] [Indexed: 01/19/2023] Open
Abstract
OBJECTIVES Genetics plays an important role in SLE risk, as well as osteonecrosis (ON), a significant and often debilitating complication of SLE. We aimed to identify genetic risk loci for ON in people with childhood-onset (cSLE) and adult-onset (aSLE) SLE. METHODS We enrolled participants from two tertiary care centres who met classification criteria for SLE. Participants had prospectively collected clinical data and were genotyped on a multiethnic array. Un-genotyped single nucleotide polymorphisms (SNPs) were imputed, and ancestry was inferred using principal components (PCs). Our outcome was symptomatic ON confirmed by imaging. We completed time-to-ON and logistic regression of ON genome-wide association studies (GWASs) with covariates for sex, age of SLE diagnosis, five PCs for ancestry, corticosteroid use and selected SLE manifestations. We conducted separate analyses for cSLE and aSLE and meta-analysed results using inverse-variance weighting. Genome-wide significance was P < 5 × 10-8. RESULTS The study included 940 participants with SLE, 87% female and 56% with cSLE. ON was present in 7.6% (n = 71). Median age of SLE diagnosis was 16.9 years (interquartile range [IQR]: 13.5, 29.3), with median follow-up of 8.0 years (IQR: 4.2, 15.7). Meta-GWAS of cSLE and aSLE time-to-ON of 4 431 911 SNPs identified a significant Chr.2 SNP, rs34118383 (minor allele frequency = 0.18), intronic to WIPF1 (hazard ratio = 3.2 [95% CI: 2.2, 4.8]; P = 1.0 × 10-8). CONCLUSION We identified an intronic WIPF1 variant associated with a 3.2 times increased hazard for ON (95% CI: 2.2, 4.8; P = 1.0 × 10-8) during SLE follow-up, independent of corticosteroid exposure. The effect of the SNP on time-to-ON was similar in cSLE and aSLE. This novel discovery represents a potential ON risk locus. Our results warrant replication.
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Affiliation(s)
- Declan Webber
- Division of Rheumatology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Jingjing Cao
- Genetics & Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada
| | - Daniela Dominguez
- Division of Rheumatology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Dafna D Gladman
- Schroeder Arthritis Institute, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Andrea Knight
- Division of Rheumatology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Paediatrics, University of Toronto, Toronto, ON, Canada
- Neurosciences and Mental Health, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada
| | - Deborah M Levy
- Division of Rheumatology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Paediatrics, University of Toronto, Toronto, ON, Canada
| | - Fangming Liao
- Division of Rheumatology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Lawrence Ng
- Division of Rheumatology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Andrew D Paterson
- Genetics & Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada
| | - Zahi Touma
- Schroeder Arthritis Institute, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Joan Wither
- Schroeder Arthritis Institute, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
- Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Murray Urowitz
- Schroeder Arthritis Institute, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Earl D Silverman
- Division of Rheumatology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Paediatrics, University of Toronto, Toronto, ON, Canada
| | - Linda T Hiraki
- Division of Rheumatology, The Hospital for Sick Children, Toronto, ON, Canada
- Genetics & Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Paediatrics, University of Toronto, Toronto, ON, Canada
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Zhang Z, Li L, Hu Z, Zhou L, Zhang Z, Xiong Y, Yao Y. Causal effects between atrial fibrillation and heart failure: evidence from a bidirectional Mendelian randomization study. BMC Med Genomics 2023; 16:187. [PMID: 37580781 PMCID: PMC10424396 DOI: 10.1186/s12920-023-01606-8] [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] [Received: 03/31/2023] [Accepted: 07/12/2023] [Indexed: 08/16/2023] Open
Abstract
BACKGROUND Observational studies have suggested a close association between atrial fibrillation (AF) and heart failure (HF), yet the causal effect remains uncertain. In this study, we employed a bidirectional Mendelian randomization analysis to investigate the causal effect of one disease on the other. METHODS Genetic instrumental variables were obtained from large-scale summary-level genome-wide association studies of AF (n = 1,030,836) and HF(n = 1,665,481), respectively. Two-sample Mendelian randomization was conducted to establish causal inferences. Inverse-variance weighted (IVW) was the primary estimate, while additional analyses including MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO), MR-Egger, and Weighted median were performed to validate robustness and identify pleiotropy. RESULTS After accounting for confounding variables, MR analysis suggested a potential causal relationship between AF and HF. An augmented genetic predisposition to atrial fibrillation was associated with an elevated risk of heart failure (odds ratio (OR) = 1.18, 95% confidence interval (CI):1.14-1.22). Likewise, genetically determined heart failure also increased the risk of heart failure (OR = 1.44, 95%CI:1.23-1.68). The robustness of the findings was corroborated through MR sensitivity analyses, and the causal estimates remained consistent when the instrument P-value threshold was tightened. CONCLUSIONS Our bidirectional Mendelian randomization study supports a reciprocal causal relationship between AF and HF. The shared genetic profile of these conditions may provide crucial insights into potential therapeutic targets for the prevention and progression of both disorders. These findings underscore the necessity for further investigation into the underlying molecular mechanisms linking AF and HF, as well as the potential for personalized treatment strategies grounded in genetic profiling.
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Affiliation(s)
- Zhuxin Zhang
- Fuwai Hospital, National Center for Cardiovascular Diseases, National Key Laboratory, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Le Li
- Fuwai Hospital, National Center for Cardiovascular Diseases, National Key Laboratory, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhao Hu
- Fuwai Hospital, National Center for Cardiovascular Diseases, National Key Laboratory, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Likun Zhou
- Fuwai Hospital, National Center for Cardiovascular Diseases, National Key Laboratory, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhenhao Zhang
- Fuwai Hospital, National Center for Cardiovascular Diseases, National Key Laboratory, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yulong Xiong
- Fuwai Hospital, National Center for Cardiovascular Diseases, National Key Laboratory, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yan Yao
- Fuwai Hospital, National Center for Cardiovascular Diseases, National Key Laboratory, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
- Cardiac Arrhythmia Center, Chinese Academy of Medical Sciences, Fu Wai Hospital, Beijing, 100037, China.
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Rouskas K, Katsareli EA, Amerikanou C, Dimopoulos AC, Glentis S, Kalantzi A, Skoulakis A, Panousis N, Ongen H, Bielser D, Planchon A, Romano L, Harokopos V, Reczko M, Moulos P, Griniatsos I, Diamantis T, Dermitzakis ET, Ragoussis J, Dedoussis G, Dimas AS. Identifying novel regulatory effects for clinically relevant genes through the study of the Greek population. BMC Genomics 2023; 24:442. [PMID: 37543566 PMCID: PMC10403965 DOI: 10.1186/s12864-023-09532-w] [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: 03/02/2023] [Accepted: 07/25/2023] [Indexed: 08/07/2023] Open
Abstract
BACKGROUND Expression quantitative trait loci (eQTL) studies provide insights into regulatory mechanisms underlying disease risk. Expanding studies of gene regulation to underexplored populations and to medically relevant tissues offers potential to reveal yet unknown regulatory variants and to better understand disease mechanisms. Here, we performed eQTL mapping in subcutaneous (S) and visceral (V) adipose tissue from 106 Greek individuals (Greek Metabolic study, GM) and compared our findings to those from the Genotype-Tissue Expression (GTEx) resource. RESULTS We identified 1,930 and 1,515 eGenes in S and V respectively, over 13% of which are not observed in GTEx adipose tissue, and that do not arise due to different ancestry. We report additional context-specific regulatory effects in genes of clinical interest (e.g. oncogene ST7) and in genes regulating responses to environmental stimuli (e.g. MIR21, SNX33). We suggest that a fraction of the reported differences across populations is due to environmental effects on gene expression, driving context-specific eQTLs, and suggest that environmental effects can determine the penetrance of disease variants thus shaping disease risk. We report that over half of GM eQTLs colocalize with GWAS SNPs and of these colocalizations 41% are not detected in GTEx. We also highlight the clinical relevance of S adipose tissue by revealing that inflammatory processes are upregulated in individuals with obesity, not only in V, but also in S tissue. CONCLUSIONS By focusing on an understudied population, our results provide further candidate genes for investigation regarding their role in adipose tissue biology and their contribution to disease risk and pathogenesis.
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Affiliation(s)
- Konstantinos Rouskas
- Institute for Bioinnovation, Biomedical Sciences Research Center 'Alexander Fleming', Vari, Greece
- Institute of Applied Biosciences, Centre for Research & Technology Hellas, Thessaloniki, Greece
| | - Efthymia A Katsareli
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Charalampia Amerikanou
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Alexandros C Dimopoulos
- Institute for Fundamental Biomedical Science, Biomedical Sciences Research Center 'Alexander Fleming', Vari, Greece
- Hellenic Naval Academy, Hatzikyriakou Avenue, Pireaus, Greece
| | - Stavros Glentis
- Institute for Bioinnovation, Biomedical Sciences Research Center 'Alexander Fleming', Vari, Greece
- Pediatric Hematology/Oncology Unit (POHemU), First Department of Pediatrics, University of Athens, Aghia Sophia Children's Hospital, Athens, Greece
| | - Alexandra Kalantzi
- Institute for Bioinnovation, Biomedical Sciences Research Center 'Alexander Fleming', Vari, Greece
| | - Anargyros Skoulakis
- Institute for Bioinnovation, Biomedical Sciences Research Center 'Alexander Fleming', Vari, Greece
| | | | - Halit Ongen
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
- Swiss Institute of Bioinformatics, University of Geneva, Geneva, Switzerland
- Institute of Genetics and Genomics in Geneva, University of Geneva, Geneva, Switzerland
| | - Deborah Bielser
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Alexandra Planchon
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Luciana Romano
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Vaggelis Harokopos
- Institute for Bioinnovation, Biomedical Sciences Research Center 'Alexander Fleming', Vari, Greece
| | - Martin Reczko
- Institute for Fundamental Biomedical Science, Biomedical Sciences Research Center 'Alexander Fleming', Vari, Greece
| | - Panagiotis Moulos
- Institute for Fundamental Biomedical Science, Biomedical Sciences Research Center 'Alexander Fleming', Vari, Greece
- Center of New Biotechnologies & Precision Medicine, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Ioannis Griniatsos
- First Department of Surgery, National and Kapodistrian University of Athens, Medical School, Laiko Hospital, Athens, Greece
| | - Theodoros Diamantis
- First Department of Surgery, National and Kapodistrian University of Athens, Medical School, Laiko Hospital, Athens, Greece
| | - Emmanouil T Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Jiannis Ragoussis
- Department of Human Genetics, McGill University Genome Centre, McGill University, Montréal, QC, Canada
- Department of Bioengineering, McGill University, Montréal, QC, Canada
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Antigone S Dimas
- Institute for Bioinnovation, Biomedical Sciences Research Center 'Alexander Fleming', Vari, Greece.
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van de Vegte YJ, Eppinga RN, van der Ende MY, Hagemeijer YP, Mahendran Y, Salfati E, Smith AV, Tan VY, Arking DE, Ntalla I, Appel EV, Schurmann C, Brody JA, Rueedi R, Polasek O, Sveinbjornsson G, Lecoeur C, Ladenvall C, Zhao JH, Isaacs A, Wang L, Luan J, Hwang SJ, Mononen N, Auro K, Jackson AU, Bielak LF, Zeng L, Shah N, Nethander M, Campbell A, Rankinen T, Pechlivanis S, Qi L, Zhao W, Rizzi F, Tanaka T, Robino A, Cocca M, Lange L, Müller-Nurasyid M, Roselli C, Zhang W, Kleber ME, Guo X, Lin HJ, Pavani F, Galesloot TE, Noordam R, Milaneschi Y, Schraut KE, den Hoed M, Degenhardt F, Trompet S, van den Berg ME, Pistis G, Tham YC, Weiss S, Sim XS, Li HL, van der Most PJ, Nolte IM, Lyytikäinen LP, Said MA, Witte DR, Iribarren C, Launer L, Ring SM, de Vries PS, Sever P, Linneberg A, Bottinger EP, Padmanabhan S, Psaty BM, Sotoodehnia N, Kolcic I, Arnar DO, Gudbjartsson DF, Holm H, Balkau B, Silva CT, Newton-Cheh CH, Nikus K, Salo P, Mohlke KL, Peyser PA, Schunkert H, Lorentzon M, Lahti J, Rao DC, Cornelis MC, Faul JD, Smith JA, Stolarz-Skrzypek K, Bandinelli S, Concas MP, Sinagra G, Meitinger T, Waldenberger M, Sinner MF, Strauch K, Delgado GE, Taylor KD, Yao J, Foco L, Melander O, de Graaf J, de Mutsert R, de Geus EJC, Johansson Å, Joshi PK, Lind L, Franke A, Macfarlane PW, Tarasov KV, Tan N, Felix SB, Tai ES, Quek DQ, Snieder H, Ormel J, Ingelsson M, Lindgren C, Morris AP, Raitakari OT, Hansen T, Assimes T, Gudnason V, Timpson NJ, Morrison AC, Munroe PB, Strachan DP, Grarup N, Loos RJF, Heckbert SR, Vollenweider P, Hayward C, Stefansson K, Froguel P, Groop L, Wareham NJ, van Duijn CM, Feitosa MF, O'Donnell CJ, Kähönen M, Perola M, Boehnke M, Kardia SLR, Erdmann J, Palmer CNA, Ohlsson C, Porteous DJ, Eriksson JG, Bouchard C, Moebus S, Kraft P, Weir DR, Cusi D, Ferrucci L, Ulivi S, Girotto G, Correa A, Kääb S, Peters A, Chambers JC, Kooner JS, März W, Rotter JI, Hicks AA, Smith JG, Kiemeney LALM, Mook-Kanamori DO, Penninx BWJH, Gyllensten U, Wilson JF, Burgess S, Sundström J, Lieb W, Jukema JW, Eijgelsheim M, Lakatta ELM, Cheng CY, Dörr M, Wong TY, Sabanayagam C, Oldehinkel AJ, Riese H, Lehtimäki T, Verweij N, van der Harst P. Genetic insights into resting heart rate and its role in cardiovascular disease. Nat Commun 2023; 14:4646. [PMID: 37532724 PMCID: PMC10397318 DOI: 10.1038/s41467-023-39521-2] [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: 06/06/2022] [Accepted: 06/16/2023] [Indexed: 08/04/2023] Open
Abstract
Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.
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Affiliation(s)
- Yordi J van de Vegte
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands
| | - Ruben N Eppinga
- Department of Cardiology, Isala Zwolle ziekenhuis, Zwolle, 8025 AB, the Netherlands
| | - M Yldau van der Ende
- Department of Cardiology, University medical Center Utrecht, Utrecht, 3584 Cx, the Netherlands
| | - Yanick P Hagemeijer
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands
- Analytical Biochemistry, University of Groningen, Groningen, 9713 AV, the Netherlands
| | - Yuvaraj Mahendran
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine Science, University of Copenhagen, Copenhagen Ø, 2100, Denmark
| | - Elias Salfati
- Department of Medicine, Stanford University School of Medicine, Stanford, 94305, USA
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
| | - Albert V Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI48109, USA
| | - Vanessa Y Tan
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, BS82BN, UK
- MRC Integrative Epidemiology, University of Bristol, Bristol, BS82BN, UK
| | - Dan E Arking
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, 21215, USA
| | - Ioanna Ntalla
- Clinical Pharmacology and Precision Medicine, William Harvey Research Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Emil V Appel
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine Science, University of Copenhagen, Copenhagen Ø, 2100, Denmark
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, 10029, USA
| | | | - Rico Rueedi
- Department of Computational Biology, University of Lausanne, Lausanne, 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - Ozren Polasek
- Department of Public Health, University of Split School of Medicine, Split, 21000, Croatia
- Algebra LAB, Algebra University College, Zagreb, 10000, Croatia
| | | | - Cecile Lecoeur
- UMR 8199, University of Lille Nord de France, Lille, 59000, France
| | - Claes Ladenvall
- Clinial Genomics Uppsala, Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, 75185, Sweden
- Lund University Diabetes Center, Department of Clinical Sciences, Lund University, Malmö, 20502, Sweden
| | - Jing Hua Zhao
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, CB2 0BB, UK
| | - Aaron Isaacs
- CARIM School for Cardiovascular Diseases, Maastricht Centre for Systems Biology (MaCSBio), Department of Physiology, Maastricht University, Maastricht, 6229ER, Netherlands
| | - Lihua Wang
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63108-2212, Campus Box 8506, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Shih-Jen Hwang
- Division of Intramural Research, National Heart Lung and Blood Institute, NIH, USA, Framingham, 1702, USA
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, FI-33014, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FI-33014, Finland
| | - Kirsi Auro
- Department of Health, unit of genetics and biomarkers, , National Institute for Health and Welfare, Finland, Helsinki, FI-00290, Finland
- Department of molecular medicine, University of Helsinki, Helsinki, FI-00290, Finland
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Lawrence F Bielak
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Linyao Zeng
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Munich, 80636, Germany
| | - Nabi Shah
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, DD1 9SY, UK
- Pharmacogenetics Research Lab, Department of Pharmacy, COMSATS University Islamabad, Abbottabad, 22060, Pakistan
| | - Maria Nethander
- Sahlgrenska Osteoporosis Centre, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, 41345, Sweden
- Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, 40530, Sweden
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Usher Institute for Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Sonali Pechlivanis
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, 45122, Germany
| | - Lu Qi
- Department of Epidemiology, Tulane University, New Orleans, LA, 70112, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Federica Rizzi
- Unit of Biomedicine, Bio4Dreams-Business Nursery for Life Sciences, Milano, 20121, Italy
| | - Toshiko Tanaka
- Longitudinal Study Section, National Institute on Aging, Baltimore, 21224, USA
| | - Antonietta Robino
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, 34137, Italy
| | - Massimiliano Cocca
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, 34137, Italy
| | - Leslie Lange
- Medicine, University of Colorado Anschutz Medical Campus, Aurora, 80045, USA
| | - Martina Müller-Nurasyid
- IBE, Ludwig-Maximilians-University Munich, LMU Munich, Munich, 81377, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, 55101, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Carolina Roselli
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02142, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
| | - Marcus E Kleber
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68167, Germany
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, 68163, Germany
| | - Xiuqing Guo
- Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Henry J Lin
- Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Francesca Pavani
- Institute for Biomedicine, Eurac Research, Bolzano, 39100, Italy
| | | | - Raymond Noordam
- Department of Internal Medicine, section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health, Amsterdam UMC, Amsterdam UMC, Vrije Universiteit, Amsterdam, Amsterdam, 1081 HL, the Netherlands
| | - Katharina E Schraut
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, Scotland, UK
| | - Marcel den Hoed
- The Beijer laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and Science for Life Laboratory, Uppsala, 75237, Sweden
| | - Frauke Degenhardt
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, 24105, Germany
| | - Stella Trompet
- Department of Internal Medicine, section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
- Department of Cardiology, Leiden University Medical Center, Leiden, ZA, 2333, the Netherlands
| | - Marten E van den Berg
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015GD, the Netherlands
| | - Giorgio Pistis
- Institute of Genetics and Biomedic Research (IRGB), Italian National Research Council (CNR), Monserrato, (CA), 9042, Italy
- Center for Statistical Genetics, University of Michigan, Ann Arbor, 48109, USA
| | - Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, 17475, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, 17475, Germany
| | - Xueling S Sim
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, 117549, Singapore
| | - Hengtong L Li
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, FI-33014, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FI-33014, Finland
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB2 0SL, UK
| | - M Abdullah Said
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands
| | - Daniel R Witte
- Department of Public Health, Aarhus University, Aarhus C, 8000, Denmark
| | - Carlos Iribarren
- Division of Research, Kaiser Permenente of Northern California, Oakland, 94612, USA
- The Scripps Research Institute, La Jolla, 10550, USA
| | | | - Susan M Ring
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, BS82BN, UK
- MRC Integrative Epidemiology, University of Bristol, Bristol, BS82BN, UK
| | - Paul S de Vries
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, School of Public Health, Houston, 77030, USA
| | - Peter Sever
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, 2400, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, 2200, Denmark
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, 10029, USA
- Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, 10029, USA
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Bruce M Psaty
- Departments of Medicine, Epidemiology and Health Systems and Population Health, University of Washington, Seattle, 98195, USA
| | - Nona Sotoodehnia
- Medicine and Epidemiology, University of Washington, Seattle, 98195, USA
| | - Ivana Kolcic
- Department of Public Health, University of Split School of Medicine, Split, 21000, Croatia
- Algebra LAB, Algebra University College, Zagreb, 10000, Croatia
| | - David O Arnar
- deCODE genetics / Amgen Inc., Reykjavik, 102, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, 101, Iceland
- Department of Medicine, Landspitali-The National University Hospital of Iceland, Reykjavik, 101, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics / Amgen Inc., Reykjavik, 102, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Hilma Holm
- deCODE genetics / Amgen Inc., Reykjavik, 102, Iceland
| | - Beverley Balkau
- Centre for Research in Epidemiology and Population Health, Institut national de la santé et de la recherche médicale, Villejuif, 94800, France
- UMRS 1018, University Versailles Saint-Quentin-en-Yvelines, Versailles, 78035, France
- UMRS 1018, University Paris Sud, Villejuif, 94807, France
| | - Claudia T Silva
- Genetic Epidemiology Unit, Dept. of Epidemiology, Erasmus University Medical Center, Rotterdam, 3000CA, Netherlands
| | | | - Kjell Nikus
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere, FI-33521, Finland
- Department of Cardiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FI-33014, Finland
| | - Perttu Salo
- Department of Health, unit of genetics and biomarkers, , National Institute for Health and Welfare, Finland, Helsinki, FI-00290, Finland
- Department of molecular medicine, University of Helsinki, Helsinki, FI-00290, Finland
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Heribert Schunkert
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Munich, 80636, Germany
- Deutsches Zentrum für Herz- und Kreislauferkrankungen (DZHK), Partner Site Munich Heart Alliance, Munich, 80636, Germany
| | - Mattias Lorentzon
- Sahlgrenska Osteoporosis Centre, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, 41345, Sweden
- Region Västra Götaland, Geriatric Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Mölndal, 43180, Sweden
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, 3000, Australia
| | - Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, 00014, Finland
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University, St. Louis, MO, 63110, USA
| | | | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Katarzyna Stolarz-Skrzypek
- Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University Medical College, Kraków, 31-008, Poland
| | - Stefania Bandinelli
- Geriatric Unit, Unità sanitaria locale Toscana Centro, Florence, 50142, Italy
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, 34137, Italy
| | - Gianfranco Sinagra
- Cardiovascular Department, "Ospedali Riuniti and University of Trieste", Trieste, 34149, Italy
| | - Thomas Meitinger
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, München, 81675, Germany
- Institute of Human Genetics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- German Centre for Cardiovascular Research (DZHK), partner site: Munich Heart Alliance, Munich, 80802, Germany
| | - Moritz F Sinner
- German Centre for Cardiovascular Research (DZHK), partner site: Munich Heart Alliance, Munich, 80802, Germany
- Department of Cardiology, University Hospital, LMU Munich, Munich, 81377, Germany
| | - Konstantin Strauch
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, 55101, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, 81377, Germany
| | - Graciela E Delgado
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68167, Germany
| | - Kent D Taylor
- Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Jie Yao
- Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Luisa Foco
- Institute for Biomedicine, Eurac Research, Bolzano, 39100, Italy
| | - Olle Melander
- Department of Internal Medicine, Clinical Sciences, Lund University and Skåne University Hospital, Malmo, 221 85, Sweden
- Lund University Diabetes Center, Lund University, Malmö, 221 85, Sweden
| | | | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
| | - Eco J C de Geus
- Biological Psychology, EMGO+ Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University, Amsterdam, 1081 BT, the Netherlands
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, 75108, Sweden
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, Scotland, UK
| | - Lars Lind
- Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University Hospital, Uppsala, 75237, Sweden
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, 24105, Germany
| | - Peter W Macfarlane
- Institute of Health and Wellbeing, Faculty of Medicine, University of Glasgow, Glasgow, G12 0XH, UK
| | - Kirill V Tarasov
- Laboratory of Cardiovascular Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA
| | - Nicholas Tan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
| | - Stephan B Felix
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, 17475, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, 17475, Germany
| | - E-Shyong Tai
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Debra Q Quek
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Johan Ormel
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Martin Ingelsson
- Department of Public Health and Caring Sciences, Molecular Geriatrics, Uppsala University, Uppsala, 75237, Sweden
| | - Cecilia Lindgren
- Genetic and Genomic Epidemiology Unit, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Andrew P Morris
- Genetic and Genomic Epidemiology Unit, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, FI-20521, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, FI-20521, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, FI-20521, Finland
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine Science, University of Copenhagen, Copenhagen Ø, 2100, Denmark
| | - Themistocles Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, 94305, USA
| | - Vilmundur Gudnason
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
- Icelandic Heart Association, Kopavogur, 201, Iceland
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School,, University of Bristol, Bristol, BS8 2BN, UK
| | - Alanna C Morrison
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, School of Public Health, Houston, 77030, USA
| | - Patricia B Munroe
- Clinical Pharmacology and Precision Medicine, William Harvey Research Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- NIHR Barts Biomedical Research Centre, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - David P Strachan
- Population Health Research Institute, St George's, University of London, London, SW17 0RE, UK
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine Science, University of Copenhagen, Copenhagen Ø, 2100, Denmark
| | - Ruth J F Loos
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine Science, University of Copenhagen, Copenhagen Ø, 2100, Denmark
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, 10029, USA
- The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, 10029, USA
| | - Susan R Heckbert
- Department of Epidemiology, University of Washington, Seattle, 98195, USA
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University hospital, Lausanne, 1015, Switzerland
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, Scotland, UK
| | - Kari Stefansson
- deCODE genetics / Amgen Inc., Reykjavik, 102, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Philippe Froguel
- Department of Metabolism, Imperial College London, London, W12 0HS, UK
- Inserm/CNRS UMR 1283/8199, Pasteur Institute of Lille, Lille University Hospital, EGID, Lille, 59000, France
- University of Lille, Lille, 59000, France
| | - Leif Groop
- Lund University Diabetes Center, Department of Clinical Sciences, Lund University, Malmö, 20502, Sweden
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, 00290, Finland
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Dept. of Epidemiology, Erasmus University Medical Center, Rotterdam, 3000CA, Netherlands
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63108-2212, Campus Box 8506, USA
| | - Christopher J O'Donnell
- Cardiology Section, VA Boston Healthcare System, Harvard Medical School, Boston, MA, 02132, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, FI-33521, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FI-33521, Finland
| | - Markus Perola
- Department of Health, unit of genetics and biomarkers, , National Institute for Health and Welfare, Finland, Helsinki, FI-00290, Finland
- Department of molecular medicine, University of Helsinki, Helsinki, FI-00290, Finland
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Lübeck, 23562, Germany
| | - Colin N A Palmer
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, DD1 9SY, UK
| | - Claes Ohlsson
- Sahlgrenska Osteoporosis Centre, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, 41345, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, Gothenburg, 41345, Sweden
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Johan G Eriksson
- Department of General practice and primary care, University of Helsinki, Helsinki, 00014, Finland
- Department of Obstetrics and Gynecology, National University of Singapore, Singapore, 119228, Singapore
- Public health Research Program, Folkhalsan Research Center, Helsinki, 000250, Finland
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Susanne Moebus
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, 45122, Germany
- Centre for Urban Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, 45122, Germany
| | - Peter Kraft
- Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02112, USA
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Daniele Cusi
- Unit of Biomedicine, Bio4Dreams-Business Nursery for Life Sciences, Milano, 20121, Italy
- Institute of Biomedical Technologies, National Research Council of Italy, Segrate, (MI), 20090, Italy
| | - Luigi Ferrucci
- Longitudinal Study Section, National Institute on Aging, Baltimore, 21224, USA
| | - Sheila Ulivi
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, 34137, Italy
| | - Giorgia Girotto
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, 34137, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, 34149, Italy
| | - Adolfo Correa
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, 39216, USA
| | - Stefan Kääb
- German Centre for Cardiovascular Research (DZHK), partner site: Munich Heart Alliance, Munich, 80802, Germany
- Department of Cardiology, University Hospital, LMU Munich, Munich, 81377, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- German Centre for Cardiovascular Research (DZHK), partner site: Munich Heart Alliance, Munich, 80802, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, 81377, Germany
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK
| | - Winfried März
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68167, Germany
- Synlab Academy, Synlab Holding Deutschland GmbH, Mannheim, 68161, Germany
| | - Jerome I Rotter
- Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Andrew A Hicks
- Institute for Biomedicine, Eurac Research, Bolzano, 39100, Italy
| | - J Gustav Smith
- Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, 221 85, Sweden
- Wallenberg Center for Molecular Medicine and Lund University Diabetes Center, Lund University, Lund, 221 84, Sweden
- The Wallenberg Laboratory/Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg University and the Department of Cardiology, Sahlgrenska University Hospital, Gothenburg, 413 45, Sweden
| | | | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health, Amsterdam UMC, Amsterdam UMC, Vrije Universiteit, Amsterdam, Amsterdam, 1081 HL, the Netherlands
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, 75108, Sweden
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, Scotland, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, Scotland, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, CB2 0SR, UK
| | - Johan Sundström
- Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University Hospital, Uppsala, 75237, Sweden
| | - Wolfgang Lieb
- Institute of Epidemiology and Biobank PopGen, Kiel University, Kiel, 24105, Germany
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, ZA, 2333, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, ZA, 2333, the Netherlands
- Netherlands Heart Institute, Utrecht, 3511 EP, the Netherlands
| | - Mark Eijgelsheim
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015GD, the Netherlands
- Department of Nephrology, University Medical Center Groningen, Groningen, 9700RB, the Netherlands
| | - Edward L M Lakatta
- Laboratory of Cardiovascular Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Marcus Dörr
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, 17475, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
- Tsinghua Medicine, Tsinghua University, Beijing, 100084, China
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
| | - Albertine J Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Harriette Riese
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, FI-33014, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FI-33014, Finland
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands.
- Department of Cardiology, University medical Center Utrecht, Utrecht, 3584 Cx, the Netherlands.
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands.
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Oliveros W, Delfosse K, Lato DF, Kiriakopulos K, Mokhtaridoost M, Said A, McMurray BJ, Browning JW, Mattioli K, Meng G, Ellis J, Mital S, Melé M, Maass PG. Systematic characterization of regulatory variants of blood pressure genes. CELL GENOMICS 2023; 3:100330. [PMID: 37492106 PMCID: PMC10363820 DOI: 10.1016/j.xgen.2023.100330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 03/29/2023] [Accepted: 04/28/2023] [Indexed: 07/27/2023]
Abstract
High blood pressure (BP) is the major risk factor for cardiovascular disease. Genome-wide association studies have identified genetic variants for BP, but functional insights into causality and related molecular mechanisms lag behind. We functionally characterize 4,608 genetic variants in linkage with 135 BP loci in vascular smooth muscle cells and cardiomyocytes by massively parallel reporter assays. High densities of regulatory variants at BP loci (i.e., ULK4, MAP4, CFDP1, PDE5A) indicate that multiple variants drive genetic association. Regulatory variants are enriched in repeats, alter cardiovascular-related transcription factor motifs, and spatially converge with genes controlling specific cardiovascular pathways. Using heuristic scoring, we define likely causal variants, and CRISPR prime editing finally determines causal variants for KCNK9, SFXN2, and PCGF6, which are candidates for developing high BP. Our systems-level approach provides a catalog of functionally relevant variants and their genomic architecture in two trait-relevant cell lines for a better understanding of BP gene regulation.
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Affiliation(s)
- Winona Oliveros
- Life Sciences Department, Barcelona Supercomputing Center, 08034 Barcelona, Catalonia, Spain
| | - Kate Delfosse
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Daniella F. Lato
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Katerina Kiriakopulos
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Milad Mokhtaridoost
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Abdelrahman Said
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Brandon J. McMurray
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Jared W.L. Browning
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Kaia Mattioli
- Division of Genetics, Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Guoliang Meng
- Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - James Ellis
- Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Seema Mital
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Ted Rogers Centre for Heart Research, Toronto, ON M5G 1X8, Canada
- Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON M5G 0A4, Canada
| | - Marta Melé
- Life Sciences Department, Barcelona Supercomputing Center, 08034 Barcelona, Catalonia, Spain
| | - Philipp G. Maass
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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Jiang C, Melles RB, Sangani P, Hoffmann TJ, Hysi PG, Glymour MM, Jorgenson E, Lachke SA, Choquet H. Association of Behavioral and Clinical Risk Factors With Cataract: A Two-Sample Mendelian Randomization Study. Invest Ophthalmol Vis Sci 2023; 64:19. [PMID: 37459064 PMCID: PMC10362921 DOI: 10.1167/iovs.64.10.19] [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: 04/09/2023] [Accepted: 06/26/2023] [Indexed: 07/20/2023] Open
Abstract
Purpose To investigate the association of genetically determined primary open-angle glaucoma (POAG), myopic refractive error (RE), type 2 diabetes (T2D), blood pressure (BP), body mass index (BMI), cigarette smoking, and alcohol consumption with the risk of age-related cataract. Methods To assess potential causal effects of clinical or behavioral factors on cataract risk, we conducted two-sample Mendelian randomization analyses. Genetic instruments, based on common genetic variants associated with risk factors at genome-wide significance (P < 5 × 10-8), were derived from published genome-wide association studies (GWAS). For age-related cataract, we used GWAS summary statistics from our previous GWAS conducted in the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort (28,092 cataract cases and 50,487 controls; all non-Hispanic whites) or in the UK Biobank (31,852 cataract cases and 428,084 controls; all European-descent individuals). We used the inverse-variance weighted (IVW) method as our primary source of Mendelian randomization estimates and conducted common sensitivity analyses. Results We found that genetically determined POAG and mean spherical equivalent RE were significantly associated with cataract risk (IVW model: odds ratio [OR] = 1.04; 95% confidence interval [CI], 1.01-1.08; P = 0.018; per diopter more hyperopic: OR = 0.92; 95% CI, 0.89-0.93; P = 6.51 × 10-13, respectively). In contrast, genetically determined T2D, BP, BMI, cigarette smoking, or alcohol consumption were not associated with cataract risk (P > 0.05). Conclusions Our results provide evidence that genetic risks for POAG and myopia may be causal risk factors for age-related cataract. These results are consistent with previous observational studies reporting associations of myopia with cataract risk. This information may support population cataract risk stratification and screening strategies.
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Affiliation(s)
- Chen Jiang
- Kaiser Permanente Northern California (KPNC), Division of Research, Oakland, California, United States
| | - Ronald B. Melles
- KPNC, Department of Ophthalmology, Redwood City, California, United States
| | - Poorab Sangani
- KPNC, Department of Ophthalmology, South San Francisco, California, United States
| | - Thomas J. Hoffmann
- Institute for Human Genetics, UCSF, San Francisco, California, United States
- Department of Epidemiology and Biostatistics, UCSF, San Francisco, California, United States
| | - Pirro G. Hysi
- King's College London, Section of Ophthalmology, School of Life Course Sciences, London, United Kingdom
- King's College London, Department of Twin Research and Genetic Epidemiology, London, United Kingdom
- University College London, Great Ormond Street Hospital Institute of Child Health, London, United Kingdom
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, UCSF, San Francisco, California, United States
| | - Eric Jorgenson
- Regeneron Genetics Center, Tarrytown, New York, United States
| | - Salil A. Lachke
- Department of Biological Sciences, University of Delaware, Newark, Delaware, United States
- Center for Bioinformatics and Computational Biology, University of Delaware, Newark, Delaware, United States
| | - Hélène Choquet
- Kaiser Permanente Northern California (KPNC), Division of Research, Oakland, California, United States
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Hellwege JN, Stallings SC, Piekos JA, Jasper EA, Aronoff DM, Edwards TL, Velez Edwards DR. Association of genetically-predicted placental gene expression with adult blood pressure traits. J Hypertens 2023; 41:1024-1032. [PMID: 37016918 PMCID: PMC10287061 DOI: 10.1097/hjh.0000000000003427] [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] [Indexed: 04/06/2023]
Abstract
OBJECTIVE Blood pressure is a complex, polygenic trait, and the need to identify prehypertensive risks and new gene targets for blood pressure control therapies or prevention continues. We hypothesize a developmental origins model of blood pressure traits through the life course where the placenta is a conduit mediating genomic and nongenomic transmission of disease risk. Genetic control of placental gene expression has recently been described through expression quantitative trait loci (eQTL) studies which have identified associations with childhood phenotypes. METHODS We conducted a transcriptome-wide gene expression analysis estimating the predicted gene expression of placental tissue in adult individuals with genome-wide association study (GWAS) blood pressure summary statistics. We constructed predicted expression models of 15 154 genes from reference placenta eQTL data and investigated whether genetically-predicted gene expression in placental tissue is associated with blood pressure traits using published GWAS summary statistics. Functional annotation of significant genes was generated using FUMA. RESULTS We identified 18, 9, and 21 genes where predicted expression in placenta was significantly associated with systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP), respectively. There were 14 gene-tissue associations (13 unique genes) significant only in placenta. CONCLUSIONS In this meta-analysis using S-PrediXcan and GWAS summary statistics, the predicted expression in placenta of 48 genes was statistically significantly associated with blood pressure traits. Notable findings included the association of FGFR1 expression with increased SBP and PP. This evidence of gene expression variation in placenta preceding the onset of adult blood pressure phenotypes is an example of extreme preclinical biological changes which may benefit from intervention.
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Affiliation(s)
- Jacklyn N Hellwege
- Department of Medicine, Division of Genetic Medicine
- Vanderbilt Genetics Institute
| | - Sarah C Stallings
- Department of Medicine, Division of Genetic Medicine
- Vanderbilt Genetics Institute
| | - Jacqueline A Piekos
- Vanderbilt Genetics Institute
- Department of Obstetrics and Gynecology, Division of Quantitative Sciences
| | - Elizabeth A Jasper
- Department of Obstetrics and Gynecology, Division of Quantitative Sciences
| | - David M Aronoff
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Todd L Edwards
- Vanderbilt Genetics Institute
- Department of Medicine, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Digna R Velez Edwards
- Vanderbilt Genetics Institute
- Department of Obstetrics and Gynecology, Division of Quantitative Sciences
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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Tang X, Lai CH, Malhi NK, Chadha R, Luo Y, Liu X, Yuan D, Tapia A, Abdollahi M, Zhang G, Calandrelli R, Shiu YT, Wang ZV, Rhee JW, Zhong S, Natarajan R, Chen ZB. Genetic Deletion of the LINC00520 Homolog in Mouse Aggravates Angiotensin II-Induced Hypertension. Noncoding RNA 2023; 9:31. [PMID: 37218991 PMCID: PMC10204496 DOI: 10.3390/ncrna9030031] [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: 03/26/2023] [Revised: 05/08/2023] [Accepted: 05/09/2023] [Indexed: 05/24/2023] Open
Abstract
(1) Background: Hypertension is a complex, multifactorial disease that is caused by genetic and environmental factors. Apart from genetic predisposition, the mechanisms involved in this disease have yet to be fully understood. We previously reported that LEENE (lncRNA enhancing endothelial nitric oxide expression, transcribed from LINC00520 in the human genome) regulates endothelial cell (EC) function by promoting the expression of endothelial nitric oxide synthase (eNOS) and vascular growth factor receptor 2 (VEGFR2). Mice with genetic deletion of the LEENE/LINC00520 homologous region exhibited impaired angiogenesis and tissue regeneration in a diabetic hindlimb ischemia model. However, the role of LEENE in blood pressure regulation is unknown. (2) Methods: We subjected mice with genetic ablation of leene and wild-type littermates to Angiotensin II (AngII) and monitored their blood pressure and examined their hearts and kidneys. We used RNA-sequencing to identify potential leene-regulated molecular pathways in ECs that contributed to the observed phenotype. We further performed in vitro experiments with murine and human ECs and ex vivo experiments with murine aortic rings to validate the select mechanism. (3) Results: We identified an exacerbated hypertensive phenotype of leene-KO mice in the AngII model, evidenced by higher systolic and diastolic blood pressure. At the organ level, we observed aggravated hypertrophy and fibrosis in the heart and kidney. Moreover, the overexpression of human LEENE RNA, in part, restored the signaling pathways impaired by leene deletion in murine ECs. Additionally, Axitinib, a tyrosine kinase inhibitor that selectively inhibits VEGFR suppresses LEENE in human ECs. (4) Conclusions: Our study suggests LEENE as a potential regulator in blood pressure control, possibly through its function in ECs.
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Affiliation(s)
- Xiaofang Tang
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Chih-Hung Lai
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
- Cardiovascular Center, Taichung Veterans General Hospital, Taichung 40705, Taiwan
- Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei 40705, Taiwan
| | - Naseeb K. Malhi
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Rahuljeet Chadha
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91010, USA
| | - Yingjun Luo
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Xuejing Liu
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Dongqiang Yuan
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Alonso Tapia
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Maryam Abdollahi
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Guangyu Zhang
- Department of Diabetes and Cancer Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Riccardo Calandrelli
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Yan-Ting Shiu
- Division of Nephrology & Hypertension, University of Utah, Salt Lake City, UT 84132, USA
- Veterans Affairs Salt Lake City Healthcare System, Salt Lake City, UT 84132, USA
| | - Zhao V. Wang
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
- Department of Diabetes and Cancer Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - June-Wha Rhee
- Department of Medicine, City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA
| | - Sheng Zhong
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Rama Natarajan
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Zhen Bouman Chen
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
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Khan A, Shang N, Nestor JG, Weng C, Hripcsak G, Harris PC, Gharavi AG, Kiryluk K. Polygenic risk affects the penetrance of monogenic kidney disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.07.23289614. [PMID: 37214819 PMCID: PMC10197721 DOI: 10.1101/2023.05.07.23289614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Background Chronic kidney disease (CKD) is a genetically complex disease determined by an interplay of monogenic, polygenic, and environmental risks. Most forms of monogenic kidney diseases have incomplete penetrance and variable expressivity. It is presently unknown if some of the variability in penetrance can be attributed to polygenic factors. Methods Using the UK Biobank (N=469,835 participants) and the All of Us (N=98,622 participants) datasets, we examined two most common forms of monogenic kidney disorders, autosomal dominant polycystic kidney disease (ADPKD) caused by deleterious variants in the PKD1 or PKD2 genes, and COL4A-associated nephropathy (COL4A-AN caused by deleterious variants in COL4A3, COL4A4, or COL4A5 genes). We used the eMERGE-III electronic CKD phenotype to define cases (estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m2 or kidney failure) and controls (eGFR >90 mL/min/1.73m2 in the absence of kidney disease diagnoses). The effects of the genome-wide polygenic score (GPS) for CKD were tested in monogenic variant carriers and non-carriers using logistic regression controlling for age, sex, diabetes, and genetic ancestry. Results As expected, the carriers of known pathogenic and rare predicted loss-of-function variants in PKD1 or PKD2 had a high risk of CKD (ORmeta=17.1, 95% CI: 11.1-26.4, P=1.8E-37). The GPS was comparably predictive of CKD in both ADPKD variant carriers (ORmeta=2.28 per SD, 95%CI: 1.55-3.37, P=2.6E-05) and non-carriers (ORmeta=1.72 per SD, 95% CI=1.69-1.76, P< E-300) independent of age, sex, diabetes, and genetic ancestry. Compared to the middle tertile of the GPS distribution for non-carriers, ADPKD variant carriers in the top tertile had a 54-fold increased risk of CKD, while ADPKD variant carriers in the bottom tertile had only a 3-fold increased risk of CKD. Similarly, the GPS was predictive of CKD in both COL4-AN variant carriers (ORmeta=1.78, 95% CI=1.22-2.58, P=2.38E-03) and non-carriers (ORmeta=1.70, 95%CI: 1.68-1.73 P Conclusions Variable penetrance of kidney disease in ADPKD and COL4-AN is partially explained by differences in polygenic risk profiles. Accounting for polygenic factors has the potential to improve risk stratification in monogenic kidney disease and may have implications for genetic counseling.
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Affiliation(s)
- Atlas Khan
- Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
| | - Ning Shang
- Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
| | - Jordan G. Nestor
- Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
| | - Chunhua Weng
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Peter C. Harris
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Ali G. Gharavi
- Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
| | - Krzysztof Kiryluk
- Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
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Ivanova T, Churnosova M, Abramova M, Ponomarenko I, Reshetnikov E, Aristova I, Sorokina I, Churnosov M. Risk Effects of rs1799945 Polymorphism of the HFE Gene and Intergenic Interactions of GWAS-Significant Loci for Arterial Hypertension in the Caucasian Population of Central Russia. Int J Mol Sci 2023; 24:ijms24098309. [PMID: 37176017 PMCID: PMC10179076 DOI: 10.3390/ijms24098309] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 04/24/2023] [Accepted: 04/25/2023] [Indexed: 05/15/2023] Open
Abstract
The aim of this case-control replicative study was to investigate the link between GWAS-impact for arterial hypertension (AH) and/or blood pressure (BP) gene polymorphisms and AH risk in Russian subjects (Caucasian population of Central Russia). AH (n = 939) and control (n = 466) cohorts were examined for ten GWAS AH/BP risk loci. The genotypes/alleles of these SNP and their combinations (SNP-SNP interactions) were tested for their association with the AH development using a logistic regression statistical procedure. The genotype GG of the SNP rs1799945 (C/G) HFE was strongly linked with an increased AH risk (ORrecGG = 2.53; 95%CIrecGG1.03-6.23; ppermGG = 0.045). The seven SNPs such as rs1173771 (G/A) AC026703.1, rs1799945 (C/G) HFE, rs805303 (G/A) BAG6, rs932764 (A/G) PLCE1, rs4387287 (C/A) OBFC1, rs7302981 (G/A) CERS5, rs167479 (T/G) RGL3, out of ten regarded loci, were related with AH within eight SNP-SNP interaction models (<0.001 ≤ pperm-interaction ≤ 0.047). Three polymorphisms such as rs8068318 (T/C) TBX2, rs633185 (C/G) ARHGAP42, and rs2681472 (A/G) ATP2B1 were not linked with AH. The pairwise rs805303 (G/A) BAG6-rs7302981 (G/A) CERS5 combination was a priority in determining the susceptibility to AH (included in six out of eight SNP-SNP interaction models [75%] and described 0.82% AH entropy). AH-associated variants are conjecturally functional for 101 genes involved in processes related to the immune system (major histocompatibility complex protein, processing/presentation of antigens, immune system process regulation, etc.). In conclusion, the rs1799945 polymorphism of the HFE gene and intergenic interactions of BAG6, CERS5, AC026703.1, HFE, PLCE1, OBFC1, RGL3 have been linked with AH risky in the Caucasian population of Central Russia.
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Affiliation(s)
- Tatiana Ivanova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Churnosova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Abramova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Irina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Evgeny Reshetnikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Aristova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Sorokina
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
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Evans LM, Arehart CH, Grotzinger AD, Mize TJ, Brasher MS, Stitzel JA, Ehringer MA, Hoeffer CA. Transcriptome-wide gene-gene interaction associations elucidate pathways and functional enrichment of complex traits. PLoS Genet 2023; 19:e1010693. [PMID: 37216417 PMCID: PMC10237671 DOI: 10.1371/journal.pgen.1010693] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 06/02/2023] [Accepted: 03/06/2023] [Indexed: 05/24/2023] Open
Abstract
It remains unknown to what extent gene-gene interactions contribute to complex traits. Here, we introduce a new approach using predicted gene expression to perform exhaustive transcriptome-wide interaction studies (TWISs) for multiple traits across all pairs of genes expressed in several tissue types. Using imputed transcriptomes, we simultaneously reduce the computational challenge and improve interpretability and statistical power. We discover (in the UK Biobank) and replicate (in independent cohorts) several interaction associations, and find several hub genes with numerous interactions. We also demonstrate that TWIS can identify novel associated genes because genes with many or strong interactions have smaller single-locus model effect sizes. Finally, we develop a method to test gene set enrichment of TWIS associations (E-TWIS), finding numerous pathways and networks enriched in interaction associations. Epistasis is may be widespread, and our procedure represents a tractable framework for beginning to explore gene interactions and identify novel genomic targets.
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Affiliation(s)
- Luke M. Evans
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States of America
- Department of Ecology & Evolutionary Biology, University of Colorado Boulder, Boulder, Colorado, United States of America
| | - Christopher H. Arehart
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States of America
- Department of Ecology & Evolutionary Biology, University of Colorado Boulder, Boulder, Colorado, United States of America
| | - Andrew D. Grotzinger
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States of America
- Department of Psychology & Neuroscience, University of Colorado Boulder, Boulder, Colorado, United States of America
| | - Travis J. Mize
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States of America
- Department of Ecology & Evolutionary Biology, University of Colorado Boulder, Boulder, Colorado, United States of America
| | - Maizy S. Brasher
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States of America
- Department of Ecology & Evolutionary Biology, University of Colorado Boulder, Boulder, Colorado, United States of America
| | - Jerry A. Stitzel
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States of America
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, Colorado, United States of America
| | - Marissa A. Ehringer
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States of America
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, Colorado, United States of America
| | - Charles A. Hoeffer
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States of America
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, Colorado, United States of America
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Ivanova T, Churnosova M, Abramova M, Plotnikov D, Ponomarenko I, Reshetnikov E, Aristova I, Sorokina I, Churnosov M. Sex-Specific Features of the Correlation between GWAS-Noticeable Polymorphisms and Hypertension in Europeans of Russia. Int J Mol Sci 2023; 24:ijms24097799. [PMID: 37175507 PMCID: PMC10178435 DOI: 10.3390/ijms24097799] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 04/13/2023] [Accepted: 04/20/2023] [Indexed: 05/15/2023] Open
Abstract
The aim of the study was directed at studying the sex-specific features of the correlation between genome-wide association studies (GWAS)-noticeable polymorphisms and hypertension (HTN). In two groups of European subjects of Russia (n = 1405 in total), such as men (n = 821 in total: n = 564 HTN, n = 257 control) and women (n = 584 in total: n = 375 HTN, n = 209 control), the distribution of ten specially selected polymorphisms (they have confirmed associations of GWAS level with blood pressure (BP) parameters and/or HTN in Europeans) has been considered. The list of studied loci was as follows: (PLCE1) rs932764 A > G, (AC026703.1) rs1173771 G > A, (CERS5) rs7302981 G > A, (HFE) rs1799945 C > G, (OBFC1) rs4387287 C > A, (BAG6) rs805303 G > A, (RGL3) rs167479 T > G, (ARHGAP42) rs633185 C > G, (TBX2) rs8068318 T > C, and (ATP2B1) rs2681472 A > G. The contribution of individual loci and their inter-locus interactions to the HTN susceptibility with bioinformatic interpretation of associative links was evaluated separately in men's and women's cohorts. The men-women differences in involvement in the disease of the BP/HTN-associated GWAS SNPs were detected. Among women, the HTN risk has been associated with HFE rs1799945 C > G (genotype GG was risky; ORGG = 11.15 ppermGG = 0.014) and inter-locus interactions of all 10 examined SNPs as part of 26 intergenic interactions models. In men, the polymorphism BAG6 rs805303 G > A (genotype AA was protective; ORAA = 0.30 ppermAA = 0.0008) and inter-SNPs interactions of eight loci in only seven models have been founded as HTN-correlated. HTN-linked loci and strongly linked SNPs were characterized by pronounced polyvector functionality in both men and women, but at the same time, signaling pathways of HTN-linked genes/SNPs in women and men were similar and were represented mainly by immune mechanisms. As a result, the present study has demonstrated a more pronounced contribution of BP/HTN-associated GWAS SNPs to the HTN susceptibility (due to weightier intergenic interactions) in European women than in men.
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Affiliation(s)
- Tatiana Ivanova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Churnosova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Abramova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Denis Plotnikov
- Genetic Epidemiology Lab, Kazan State Medical University, 420012 Kazan, Russia
| | - Irina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Evgeny Reshetnikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Aristova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Sorokina
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
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Myserlis EP, Georgakis MK, Demel SL, Sekar P, Chung J, Malik R, Hyacinth HI, Comeau ME, Falcone G, Langefeld CD, Rosand J, Woo D, Anderson CD. A Genomic Risk Score Identifies Individuals at High Risk for Intracerebral Hemorrhage. Stroke 2023; 54:973-982. [PMID: 36799223 PMCID: PMC10050100 DOI: 10.1161/strokeaha.122.041701] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 01/11/2023] [Indexed: 02/18/2023]
Abstract
BACKGROUND Intracerebral hemorrhage (ICH) has an estimated heritability of 29%. We developed a genomic risk score for ICH and determined its predictive power in comparison to standard clinical risk factors. METHODS We combined genome-wide association data from individuals of European ancestry for ICH and related traits in a meta-genomic risk score ([metaGRS]; 2.6 million variants). We tested associations with ICH and its predictive performance in addition to clinical risk factors in a held-out validation dataset (842 cases and 796 controls). We tested associations with risk of incident ICH in the population-based UK Biobank cohort (486 784 individuals, 1526 events, median follow-up 11.3 years). RESULTS One SD increment in the metaGRS was significantly associated with 31% higher odds for ICH (95% CI, 1.16-1.48) in age-, sex- and clinical risk factor-adjusted models. The metaGRS identified individuals with almost 5-fold higher odds for ICH in the top score percentile (odds ratio, 4.83 [95% CI, 1.56-21.2]). Predictive models for ICH incorporating the metaGRS in addition to clinical predictors showed superior performance compared to the clinical risk factors alone (c-index, 0.695 versus 0.686). The metaGRS showed similar associations for lobar and nonlobar ICH, independent of the known APOE risk locus for lobar ICH. In the UK Biobank, the metaGRS was associated with higher risk of incident ICH (hazard ratio, 1.15 [95% CI, 1.09-1.21]). The associations were significant within both a relatively high-risk population of antithrombotic medications users, as well as among a relatively low-risk population with a good control of vascular risk factors and no use of anticoagulants. CONCLUSIONS We developed and validated a genomic risk score that predicts lifetime risk of ICH beyond established clinical risk factors among individuals of European ancestry. Whether implementation of the score in risk prognostication models for high-risk populations, such as patients under antithrombotic treatment, could improve clinical decision making should be explored in future studies.
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Affiliation(s)
- Evangelos Pavlos Myserlis
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Henry and Alisson McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Marios K. Georgakis
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Henry and Alisson McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-University (LMU), Munich, Germany
| | - Stacie L. Demel
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Padmini Sekar
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Jaeyoon Chung
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Rainer Malik
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-University (LMU), Munich, Germany
| | - Hyacinth I. Hyacinth
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Mary E. Comeau
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
- Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Guido Falcone
- Division of Neurocritical Care & Emergency Neurology, Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Carl D. Langefeld
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
- Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Jonathan Rosand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Henry and Alisson McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Daniel Woo
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Christopher D. Anderson
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Henry and Alisson McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
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Schaefer JD, Jang SK, Clark DA, Deak JD, Hicks BM, Iacono WG, Liu M, McGue M, Vrieze SI, Wilson S. Associations between polygenic risk of substance use and use disorder and alcohol, cannabis, and nicotine use in adolescence and young adulthood in a longitudinal twin study. Psychol Med 2023; 53:2296-2306. [PMID: 37310313 PMCID: PMC10123833 DOI: 10.1017/s0033291721004116] [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: 02/20/2021] [Revised: 08/12/2021] [Accepted: 09/20/2021] [Indexed: 01/13/2023]
Abstract
BACKGROUND Recent well-powered genome-wide association studies have enhanced prediction of substance use outcomes via polygenic scores (PGSs). Here, we test (1) whether these scores contribute to prediction over-and-above family history, (2) the extent to which PGS prediction reflects inherited genetic variation v. demography (population stratification and assortative mating) and indirect genetic effects of parents (genetic nurture), and (3) whether PGS prediction is mediated by behavioral disinhibition prior to substance use onset. METHODS PGSs for alcohol, cannabis, and nicotine use/use disorder were calculated for Minnesota Twin Family Study participants (N = 2483, 1565 monozygotic/918 dizygotic). Twins' parents were assessed for histories of substance use disorder. Twins were assessed for behavioral disinhibition at age 11 and substance use from ages 14 to 24. PGS prediction of substance use was examined using linear mixed-effects, within-twin pair, and structural equation models. RESULTS Nearly all PGS measures were associated with multiple types of substance use independently of family history. However, most within-pair PGS prediction estimates were substantially smaller than the corresponding between-pair estimates, suggesting that prediction is driven in part by demography and indirect genetic effects of parents. Path analyses indicated the effects of both PGSs and family history on substance use were mediated via disinhibition in preadolescence. CONCLUSIONS PGSs capturing risk of substance use and use disorder can be combined with family history measures to augment prediction of substance use outcomes. Results highlight indirect sources of genetic associations and preadolescent elevations in behavioral disinhibition as two routes through which these scores may relate to substance use.
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Affiliation(s)
| | - Seon-Kyeong Jang
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - D. Angus Clark
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Joseph D. Deak
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Brian M. Hicks
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - William G. Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Mengzhen Liu
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Scott I. Vrieze
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Sylia Wilson
- Institute for Child Development, University of Minnesota, Minneapolis, MN, USA
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Zou M, Mangum KD, Magin JC, Cao HH, Yarboro MT, Shelton EL, Taylor JM, Reese J, Furey TS, Mack CP. Prdm6 drives ductus arteriosus closure by promoting ductus arteriosus smooth muscle cell identity and contractility. JCI Insight 2023; 8:e163454. [PMID: 36749647 PMCID: PMC10077476 DOI: 10.1172/jci.insight.163454] [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: 08/05/2022] [Accepted: 01/23/2023] [Indexed: 02/08/2023] Open
Abstract
Based upon our demonstration that the smooth muscle cell-selective (SMC-selective) putative methyltransferase, Prdm6, interacts with myocardin-related transcription factor-A, we examined Prdm6's role in SMCs in vivo using cell type-specific knockout mouse models. Although SMC-specific depletion of Prdm6 in adult mice was well tolerated, Prdm6 depletion in Wnt1-expressing cells during development resulted in perinatal lethality and a completely penetrant patent ductus arteriosus (DA) phenotype. Lineage tracing experiments in Wnt1Cre2 Prdm6fl/fl ROSA26LacZ mice revealed normal neural crest-derived SMC investment of the outflow tract. In contrast, myography measurements on DA segments isolated from E18.5 embryos indicated that Prdm6 depletion significantly reduced DA tone and contractility. RNA-Seq analyses on DA and ascending aorta samples at E18.5 identified a DA-enriched gene program that included many SMC-selective contractile associated proteins that was downregulated by Prdm6 depletion. Chromatin immunoprecipitation-sequencing experiments in outflow tract SMCs demonstrated that 50% of the genes Prdm6 depletion altered contained Prdm6 binding sites. Finally, using several genome-wide data sets, we identified an SMC-selective enhancer within the Prdm6 third intron that exhibited allele-specific activity, providing evidence that rs17149944 may be the causal SNP for a cardiovascular disease GWAS locus identified within the human PRDM6 gene.
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Affiliation(s)
- Meng Zou
- Department of Pathology and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Kevin D. Mangum
- Department of Pathology and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Justin C. Magin
- Department of Pathology and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Heidi H. Cao
- Department of Pathology and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Michael T. Yarboro
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Elaine L. Shelton
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Joan M. Taylor
- Department of Pathology and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Jeff Reese
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Terrence S. Furey
- Department of Pathology and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Christopher P. Mack
- Department of Pathology and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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D'Antonio M, Nguyen JP, Arthur TD, Matsui H, D'Antonio-Chronowska A, Frazer KA. Fine mapping spatiotemporal mechanisms of genetic variants underlying cardiac traits and disease. Nat Commun 2023; 14:1132. [PMID: 36854752 PMCID: PMC9975214 DOI: 10.1038/s41467-023-36638-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 02/10/2023] [Indexed: 03/02/2023] Open
Abstract
The causal variants and genes underlying thousands of cardiac GWAS signals have yet to be identified. Here, we leverage spatiotemporal information on 966 RNA-seq cardiac samples and perform an expression quantitative trait locus (eQTL) analysis detecting eQTLs considering both eGenes and eIsoforms. We identify 2,578 eQTLs associated with a specific developmental stage-, tissue- and/or cell type. Colocalization between eQTL and GWAS signals of five cardiac traits identified variants with high posterior probabilities for being causal in 210 GWAS loci. Pulse pressure GWAS loci are enriched for colocalization with fetal- and smooth muscle- eQTLs; pulse rate with adult- and cardiac muscle- eQTLs; and atrial fibrillation with cardiac muscle- eQTLs. Fine mapping identifies 79 credible sets with five or fewer SNPs, of which 15 were associated with spatiotemporal eQTLs. Our study shows that many cardiac GWAS variants impact traits and disease in a developmental stage-, tissue- and/or cell type-specific fashion.
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Affiliation(s)
- Matteo D'Antonio
- Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA.
- Division of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA.
- Institute of Genomic Medicine, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA.
| | - Jennifer P Nguyen
- Division of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Timothy D Arthur
- Division of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Hiroko Matsui
- Institute of Genomic Medicine, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | | | - Kelly A Frazer
- Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA.
- Institute of Genomic Medicine, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA.
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Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Fugar S, Generoso G, Heard DG, Hiremath S, Ho JE, Kalani R, Kazi DS, Ko D, Levine DA, Liu J, Ma J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Virani SS, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation 2023; 147:e93-e621. [PMID: 36695182 DOI: 10.1161/cir.0000000000001123] [Citation(s) in RCA: 1355] [Impact Index Per Article: 1355.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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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. Integrative multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.09.23285622. [PMID: 36824883 PMCID: PMC9949190 DOI: 10.1101/2023.02.09.23285622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Genome-wide association studies (GWAS) have identified hundreds of genetic risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWAS and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotype information to identify quantitative trait loci (QTL) for gene expression and splicing in coronary arteries obtained from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary arteries and 19% exhibited cell-type-specific expression. Colocalization analysis with GWAS identified subgroups of eGenes unique to CAD and blood pressure. Fine-mapping highlighted additional eGenes of interest, including TBX20 and IL5 . Splicing (s)QTLs for 1,690 genes were also identified, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing events to accurately identify disease-relevant gene expression. Our work provides the first human coronary artery eQTL resource from a patient sample and exemplifies the necessity of diverse study populations and multi-omic approaches to characterize gene regulation in critical disease processes. Study Design Overview
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Singh S, Choudhury A, Hazelhurst S, Crowther N, Boua P, Sorgho H, Agongo G, Nonterah E, Micklesfield L, Norris S, Kisiangani I, Mohamed S, Gomez-Olive F, Tollman S, Choma S, Brandenburg JT, Ramsay M. Genome-wide Association Study Meta-analysis of Blood Pressure Traits and Hypertension in Sub-Saharan African Populations: An AWI-Gen Study. RESEARCH SQUARE 2023:rs.3.rs-2532794. [PMID: 36824767 PMCID: PMC9949264 DOI: 10.21203/rs.3.rs-2532794/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Most hypertension-related genome-wide association studies (GWAS) focus on non-African populations, despite hypertension (a major risk factor for cardiovascular disease) being highly prevalent in Africa. The AWI-Gen study GWAS meta-analysis for blood pressure-related traits (systolic and diastolic blood pressure, pulse pressure, mean-arterial pressure and hypertension) from three sub-Saharan African geographic regions (N=10,775), identified two genome-wide significant signals (p<5E-08): systolic blood pressure near P2RY1 (rs77846204; intergenic variant, p=4.25E-08) and pulse pressure near Linc01256 (rs80141533; intergenic variant, p=4.25E-08). No genome-wide signals were detected for the AWI-Gen GWAS meta-analysis with previous African-ancestry GWASs (UK Biobank (African), Uganda Genome Resource). Suggestive signals (p<5E-06) were observed for all traits, with 29 displaying pleiotropic effects and several replicating known associations. Polygenic risk scores developed from studies on different ancestries had limited transferability, with multi-ancestry models providing better prediction. This study provides insights into the genetics and physiology of blood pressure variation in African populations.
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Affiliation(s)
- Surina Singh
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), University of the Witwatersrand
| | | | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences & School of Electrical & Information Engineering, University of the Witwatersrand
| | - Nigel Crowther
- 11Department of Chemical Pathology, National Health Laboratory Service
| | - Palwende Boua
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santé
| | - Hermann Sorgho
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santé
| | | | | | | | - Shane Norris
- SAMRC Developmental Pathways For Health Research Unit, Department of Paediatrics & Child Health, University of the Witwatersrand, Johannesburg, South Africa
| | | | | | - Francesc Gomez-Olive
- 8MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand
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