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Ray NR, Kunkle BW, Hamilton‐Nelson K, Kurup JT, Rajabli F, Qiao M, Vardarajan BN, Cosacak MI, Kizil C, Jean‐Francois M, Cuccaro M, Reyes‐Dumeyer D, Cantwell L, Kuzma A, Vance JM, Gao S, Hendrie HC, Baiyewu O, Ogunniyi A, Akinyemi RO, Lee W, Martin ER, Wang L, Beecham GW, Bush WS, Xu W, Jin F, Wang L, Farrer LA, Haines JL, Byrd GS, Schellenberg GD, Mayeux R, Pericak‐Vance MA, Reitz C. Extended genome-wide association study employing the African genome resources panel identifies novel susceptibility loci for Alzheimer's disease in individuals of African ancestry. Alzheimers Dement 2024; 20:5247-5261. [PMID: 38958117 PMCID: PMC11350055 DOI: 10.1002/alz.13880] [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: 09/20/2023] [Revised: 04/03/2024] [Accepted: 04/12/2024] [Indexed: 07/04/2024]
Abstract
INTRODUCTION Despite a two-fold risk, individuals of African ancestry have been underrepresented in Alzheimer's disease (AD) genomics efforts. METHODS Genome-wide association studies (GWAS) of 2,903 AD cases and 6,265 controls of African ancestry. Within-dataset results were meta-analyzed, followed by functional genomics analyses. RESULTS A novel AD-risk locus was identified in MPDZ on chromosome (chr) 9p23 (rs141610415, MAF = 0.002, p = 3.68×10-9). Two additional novel common and nine rare loci were identified with suggestive associations (P < 9×10-7). Comparison of association and linkage disequilibrium (LD) patterns between datasets with higher and lower degrees of African ancestry showed differential association patterns at chr12q23.2 (ASCL1), suggesting that this association is modulated by regional origin of local African ancestry. DISCUSSION These analyses identified novel AD-associated loci in individuals of African ancestry and suggest that degree of African ancestry modulates some associations. Increased sample sets covering as much African genetic diversity as possible will be critical to identify additional loci and deconvolute local genetic ancestry effects. HIGHLIGHTS Genetic ancestry significantly impacts risk of Alzheimer's Disease (AD). Although individuals of African ancestry are twice as likely to develop AD, they are vastly underrepresented in AD genomics studies. The Alzheimer's Disease Genetics Consortium has previously identified 16 common and rare genetic loci associated with AD in African American individuals. The current analyses significantly expand this effort by increasing the sample size and extending ancestral diversity by including populations from continental Africa. Single variant meta-analysis identified a novel genome-wide significant AD-risk locus in individuals of African ancestry at the MPDZ gene, and 11 additional novel loci with suggestive genome-wide significance at p < 9×10-7. Comparison of African American datasets with samples of higher degree of African ancestry demonstrated differing patterns of association and linkage disequilibrium at one of these loci, suggesting that degree and/or geographic origin of African ancestry modulates the effect at this locus. These findings illustrate the importance of increasing number and ancestral diversity of African ancestry samples in AD genomics studies to fully disentangle the genetic architecture underlying AD, and yield more effective ancestry-informed genetic screening tools and therapeutic interventions.
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Mani A. Update in genetic and epigenetic causes of hypertension. Cell Mol Life Sci 2024; 81:201. [PMID: 38691164 PMCID: PMC11062952 DOI: 10.1007/s00018-024-05220-4] [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: 01/19/2024] [Revised: 03/27/2024] [Accepted: 03/29/2024] [Indexed: 05/03/2024]
Abstract
Hypertension is a heritable disease that affects one-fourth of the population and accounts for about 50% of cardiovascular deaths. The genetic basis of hypertension is multifaceted, involving both monogenic and most commonly complex polygenic forms. With the advent of the human genome project, genome-wide association studies (GWAS) have identified a plethora of loci linked to hypertension by examining common genetic variations. It's notable, however, that the majority of these genetic variants do not affect the protein-coding sequences, posing a considerable obstacle in pinpointing the actual genes responsible for hypertension. Despite these challenges, precise mapping of GWAS-identified loci is emerging as a promising strategy to reveal novel genes and potential targets for the pharmacological management of blood pressure. This review provides insight into the monogenic and polygenic causes of hypertension. Special attention is given to PRDM6, among the earliest functionally characterized GWAS-identified genes. Moreover, this review delves into the roles of genes contributing to renal and vascular forms of hypertension, offering insights into their genetic and epigenetic mechanisms of action.
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Affiliation(s)
- Arya Mani
- Department of Internal Medicine, Yale University School of Medicine, Yale Cardiovascular Research Center, 300 George Street, New Haven, CT, 06511, USA.
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA.
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3
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Chaudhary R, Straub AC, Aggor FE, Onasanya I, Richardson J, Strollo P, Reis SE, Olafiranye O. CYB5R3 T117S Genetic Mutation Is Associated With Major Adverse Cardiovascular and Cerebrovascular Events in Black Adults. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2024; 17:e004271. [PMID: 38353123 PMCID: PMC11021138 DOI: 10.1161/circgen.123.004271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Affiliation(s)
- Rahul Chaudhary
- Dept of Medicine, Division of Cardiology, Heart & Vascular Institute, Univ of Pittsburgh School of Medicine
| | - Adam C. Straub
- Dept of Pharmacology & Chemical Biology, Univ of Pittsburgh, Pittsburgh, PA
- Heart, Lung, Blood and Vascular Medicine Institute, Univ of Pittsburgh, Pittsburgh, PA
| | - Felix E.Y. Aggor
- Dept of Medicine, Division of Cardiology, Heart & Vascular Institute, Univ of Pittsburgh School of Medicine
| | | | | | - Patrick Strollo
- Heart, Lung, Blood and Vascular Medicine Institute, Univ of Pittsburgh, Pittsburgh, PA
- Dept of Medicine, VA Pittsburgh Healthcare System, Pittsburgh, PA
| | - Steven E. Reis
- Dept of Medicine, Division of Cardiology, Heart & Vascular Institute, Univ of Pittsburgh School of Medicine
| | - Oladipupo Olafiranye
- Dept of Medicine, Division of Cardiology, Univ of Texas Southwestern Medical Center & VA North Texas Healthcare System, Dallas, TX
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4
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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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Yao J, Ning F, Wang W, Zhang D. DNA Methylation Mediated the Association of Body Mass Index With Blood Pressure in Chinese Monozygotic Twins. Twin Res Hum Genet 2024; 27:18-29. [PMID: 38291711 DOI: 10.1017/thg.2024.3] [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: 02/01/2024]
Abstract
Obesity is an established risk factor for hypertension, but the mechanisms are only partially understood. We examined whether body mass index (BMI)-related DNA methylation (DNAm) variation would mediate the association of BMI with blood pressure (BP). We first conducted a genomewide DNA methylation analysis in monozygotic twin pairs to detect BMI-related DNAm variation and then evaluated the mediating effect of DNAm on the relationship between BMI and BP levels using the causal inference test (CIT) method and mediation analysis. Ontology enrichment analysis was performed for CpGs using the GREAT tool. A total of 60 twin pairs for BMI and systolic blood pressure (SBP) and 58 twin pairs for BMI and diastolic blood pressure (DBP) were included. BMI was positively associated with SBP (β = 1.86, p = .0004). The association between BMI and DNAm of 85 CpGs reached p < 1×10-4 level. Eleven BMI-related differentially methylated regions (DMRs) within LNCPRESS1, OGDHL, RNU1-44P, NPHS1, ECEL1P2, LLGL2, RNY4P15, MOGAT3, PHACTR3, and BAI2 were found. Of the 85 CpGs, 9 mapped to C10orf71-AS1, NDUFB5P1, KRT80, BAI2, ABCA2, PEX11G and FGF4 were significantly associated with SBP levels. Of the 9 CpGs, 2 within ABCA2 negatively mediated the association between BMI and SBP, with a mediating effect of -0.24 (95% CI [-0.65, -0.01]). BMI was also positively associated with DBP (β = 0.60, p = .0495). The association between BMI and DNAm of 193 CpGs reached p < 1×10-4 level. Twenty-five BMI-related DMRs within OGDHL, POU4F2, ECEL1P2, TTC6, SMPD4, EP400, TUBA1C and AGAP2 were found. Of the 193 CpGs, 33 mapped to ABCA2, ADORA2B, CTNNBIP1, KDM4B, NAA60, RSPH6A, SLC25A19 and STIL were significantly associated with DBP levels. Of the 33 CpGs, 12 within ABCA2, SLC25A19, KDM4B, PTPRN2, DNASE1, TFCP2L1, LMNB2 and C10orf71-AS1 negatively mediated the association between BMI and DBP, with a total mediation effect of -0.66 (95% CI [-1.07, -0.30]). Interestingly, BMI might also negatively mediate the association between the DNAm of most CpG mediators mentioned above and BP. The mediating effect of DNAm was also found when stratified by sex. In conclusion, DNAm variation may partially negatively mediate the association of BMI with BP. Our findings may provide new clues to further elucidate the pathogenesis of obesity to hypertension and identify new diagnostic biomarkers and therapeutic targets for hypertension.
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Affiliation(s)
- Jie Yao
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China
- Jiangsu Health Development Research Center, Nanjing, Jiangsu Province, China
| | - Feng Ning
- Qingdao Centers for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China
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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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7
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Jeng XJ, Hu Y, Venkat V, Lu TP, Tzeng JY. Transfer learning with false negative control improves polygenic risk prediction. PLoS Genet 2023; 19:e1010597. [PMID: 38011285 PMCID: PMC10723713 DOI: 10.1371/journal.pgen.1010597] [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: 01/01/2023] [Revised: 12/15/2023] [Accepted: 11/09/2023] [Indexed: 11/29/2023] Open
Abstract
Polygenic risk score (PRS) is a quantity that aggregates the effects of variants across the genome and estimates an individual's genetic predisposition for a given trait. PRS analysis typically contains two input data sets: base data for effect size estimation and target data for individual-level prediction. Given the availability of large-scale base data, it becomes more common that the ancestral background of base and target data do not perfectly match. In this paper, we treat the GWAS summary information obtained in the base data as knowledge learned from a pre-trained model, and adopt a transfer learning framework to effectively leverage the knowledge learned from the base data that may or may not have similar ancestral background as the target samples to build prediction models for target individuals. Our proposed transfer learning framework consists of two main steps: (1) conducting false negative control (FNC) marginal screening to extract useful knowledge from the base data; and (2) performing joint model training to integrate the knowledge extracted from base data with the target training data for accurate trans-data prediction. This new approach can significantly enhance the computational and statistical efficiency of joint-model training, alleviate over-fitting, and facilitate more accurate trans-data prediction when heterogeneity level between target and base data sets is small or high.
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Affiliation(s)
- Xinge Jessie Jeng
- Department of Statistics, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Yifei Hu
- Department of Statistics, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Vaishnavi Venkat
- Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Tzu-Pin Lu
- Institute of Health Data Analytics and Statistics, National Taiwan University, Taipei, Taiwan
- Department of Public Health, National Taiwan University, Taipei, Taiwan
| | - Jung-Ying Tzeng
- Department of Statistics, North Carolina State University, Raleigh, North Carolina, United States of America
- Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, United States of America
- Institute of Health Data Analytics and Statistics, National Taiwan University, Taipei, Taiwan
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8
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Doumatey AP, Bentley AR, Akinyemi R, Olanrewaju TO, Adeyemo A, Rotimi C. Genes, environment, and African ancestry in cardiometabolic disorders. Trends Endocrinol Metab 2023; 34:601-621. [PMID: 37598069 PMCID: PMC10548552 DOI: 10.1016/j.tem.2023.07.007] [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: 05/19/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/21/2023]
Abstract
The past two decades have been characterized by a substantial global increase in cardiometabolic diseases, but the prevalence and incidence of these diseases and related traits differ across populations. African ancestry populations are among the most affected yet least included in research. Populations of African descent manifest significant genetic and environmental diversity and this under-representation is a missed opportunity for discovery and could exacerbate existing health disparities and curtail equitable implementation of precision medicine. Here, we discuss cardiometabolic diseases and traits in the context of African descent populations, including both genetic and environmental contributors and emphasizing novel discoveries. We also review new initiatives to include more individuals of African descent in genomics to address current gaps in the field.
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Affiliation(s)
- Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Rufus Akinyemi
- Neuroscience and Ageing Research Unit, Institute for Advanced Medical Research and Training and Centre for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria; Department of Neurology, University College Hospital, Ibadan, Nigeria
| | - Timothy O Olanrewaju
- Division of Nephrology, Department of Medicine, University of Ilorin & University of Ilorin Teaching Hospital, Ilorin, Nigeria
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Charles Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
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9
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Ray NR, Kunkle BW, Hamilton-Nelson K, Kurup JT, Rajabli F, Cosacak MI, Kizil C, Jean-Francois M, Cuccaro M, Reyes-Dumeyer D, Cantwell L, Kuzma A, Vance JM, Gao S, Hendrie HC, Baiyewu O, Ogunniyi A, Akinyemi RO, Lee WP, Martin ER, Wang LS, Beecham GW, Bush WS, Farrer LA, Haines JL, Byrd GS, Schellenberg GD, Mayeux R, Pericak-Vance MA, Reitz C. Extended genome-wide association study employing the African Genome Resources Panel identifies novel susceptibility loci for Alzheimer's Disease in individuals of African ancestry. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.29.23294774. [PMID: 37693582 PMCID: PMC10491365 DOI: 10.1101/2023.08.29.23294774] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
INTRODUCTION Despite a two-fold increased risk, individuals of African ancestry have been significantly underrepresented in Alzheimer's Disease (AD) genomics efforts. METHODS GWAS of 2,903 AD cases and 6,265 cognitive controls of African ancestry. Within-dataset results were meta-analyzed, followed by gene-based and pathway analyses, and analysis of RNAseq and whole-genome sequencing data. RESULTS A novel AD risk locus was identified in MPDZ on chromosome 9p23 (rs141610415, MAF=.002, P =3.68×10 -9 ). Two additional novel common and nine novel rare loci approached genome-wide significance at P <9×10 -7 . Comparison of association and LD patterns between datasets with higher and lower degrees of African ancestry showed differential association patterns at chr12q23.2 ( ASCL1 ), suggesting that the association is modulated by regional origin of local African ancestry. DISCUSSION Increased sample sizes and sample sets from Africa covering as much African genetic diversity as possible will be critical to identify additional disease-associated loci and improve deconvolution of local genetic ancestry effects.
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10
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Kim HJ, Son HY, Park P, Yun JM, Kwon H, Cho B, Kim JI, Park JH. A genome-wide by PM 10 exposure interaction study for blood pressure in Korean adults. Sci Rep 2023; 13:13060. [PMID: 37567956 PMCID: PMC10421905 DOI: 10.1038/s41598-023-40155-z] [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: 02/22/2023] [Accepted: 08/05/2023] [Indexed: 08/13/2023] Open
Abstract
Blood pressure (BP) is a typical complex trait, and the genetic susceptibility of individuals to changes in BP induced by air pollution exposure is different. Although interactions of exposure to air pollutants with several candidate genes have been identified, genome-wide interaction studies (GWISs) are needed to understand the association between them with BP. Therefore, we aimed to discover the unique genetic loci for BP that interact with exposure to air pollutants in Korean adults. We ultimately included 1868 participants in the discovery step and classified them into groups of those with low-to-moderate exposure and high exposure to average annual concentration of particulate matter with an aerodynamic diameter ≤ 10 μm (PM10). Because none of the single nucleotide polymorphisms (SNPs) achieved a genome-wide level of significance of pint < 5 × 10-8 for either systolic BP (SBP) or diastolic BP (DBP), we considered the top 10 ranking SNPs for each BP trait. To validate these suggestive SNPs, we finally selected six genetic variants for SBP and five variants for DBP, respectively. In a replication result for SBP, only one SNP (rs12914147) located in an intergenic region of the NR2F2 showed a significant interaction. We also identified several genetic susceptibility loci (e.g., CHST11, TEK, and ITGA1) implicated in candidate mechanisms such as inflammation and oxidative stress in the discovery step, although their interaction effects were not replicated. Our study reports the first GWIS finding to our knowledge, and the association between exposure to PM10 and BP levels may be determined in part by several newly discovered genetic suggestive loci, including NR2F2.
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Affiliation(s)
- Hyun-Jin Kim
- National Cancer Control Institute, National Cancer Center, Goyang, South Korea
| | - Ho-Young Son
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, South Korea
| | - Philiip Park
- National Cancer Control Institute, National Cancer Center, Goyang, South Korea
| | - Jae Moon Yun
- Department of Family Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Hyuktae Kwon
- Department of Family Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Belong Cho
- Department of Family Medicine, Seoul National University Hospital, Seoul, South Korea
- Department of Family Medicine, Seoul National University College of Medicine, 103 Daehakro, Yeongun-Dong, Jongno-Gu, Seoul, 03080, South Korea
| | - Jong-Il Kim
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, South Korea.
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, South Korea.
- Department of Biochemistry & Molecular Biology, Seoul National University College of Medicine, 103 Daehakro, Yeongun-Dong, Jongno-Gu, Seoul, 03080, South Korea.
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea.
| | - Jin-Ho Park
- Department of Family Medicine, Seoul National University Hospital, Seoul, South Korea.
- Department of Family Medicine, Seoul National University College of Medicine, 103 Daehakro, Yeongun-Dong, Jongno-Gu, Seoul, 03080, South Korea.
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11
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Qiao J, Wu Y, Zhang S, Xu Y, Zhang J, Zeng P, Wang T. Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes. BMC Genomics 2023; 24:324. [PMID: 37312035 DOI: 10.1186/s12864-023-09425-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 06/01/2023] [Indexed: 06/15/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear. RESULTS By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection. CONCLUSIONS Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.
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Affiliation(s)
- Jiahao Qiao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yuxuan Wu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Shuo Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yue Xu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Jinhui Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
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12
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Shang L, Zhao W, Wang YZ, Li Z, Choi JJ, Kho M, Mosley TH, Kardia SLR, Smith JA, Zhou X. meQTL mapping in the GENOA study reveals genetic determinants of DNA methylation in African Americans. Nat Commun 2023; 14:2711. [PMID: 37169753 PMCID: PMC10175543 DOI: 10.1038/s41467-023-37961-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 04/07/2023] [Indexed: 05/13/2023] Open
Abstract
Identifying genetic variants that are associated with variation in DNA methylation, an analysis commonly referred to as methylation quantitative trait locus (meQTL) mapping, is an important first step towards understanding the genetic architecture underlying epigenetic variation. Most existing meQTL mapping studies have focused on individuals of European ancestry and are underrepresented in other populations, with a particular absence of large studies in populations with African ancestry. We fill this critical knowledge gap by performing a large-scale cis-meQTL mapping study in 961 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. We identify a total of 4,565,687 cis-acting meQTLs in 320,965 meCpGs. We find that 45% of meCpGs harbor multiple independent meQTLs, suggesting potential polygenic genetic architecture underlying methylation variation. A large percentage of the cis-meQTLs also colocalize with cis-expression QTLs (eQTLs) in the same population. Importantly, the identified cis-meQTLs explain a substantial proportion (median = 24.6%) of methylation variation. In addition, the cis-meQTL associated CpG sites mediate a substantial proportion (median = 24.9%) of SNP effects underlying gene expression. Overall, our results represent an important step toward revealing the co-regulation of methylation and gene expression, facilitating the functional interpretation of epigenetic and gene regulation underlying common diseases in African Americans.
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Affiliation(s)
- Lulu Shang
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Yi Zhe Wang
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Zheng Li
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jerome J Choi
- Population Health Sciences, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, 53726, USA
| | - Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Thomas H Mosley
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, 39126, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA.
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA.
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13
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Wang W, Yao J, Li W, Wu Y, Duan H, Xu C, Tian X, Li S, Tan Q, Zhang D. Epigenome-wide association study in Chinese monozygotic twins identifies DNA methylation loci associated with blood pressure. Clin Epigenetics 2023; 15:38. [PMID: 36869404 PMCID: PMC9985232 DOI: 10.1186/s13148-023-01457-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 02/24/2023] [Indexed: 03/05/2023] Open
Abstract
BACKGROUND Hypertension is a crucial risk factor for developing cardiovascular disease and reducing life expectancy. We aimed to detect DNA methylation (DNAm) variants potentially related to systolic blood pressure (SBP) and diastolic blood pressure (DBP) by conducting epigenome-wide association studies in 60 and 59 Chinese monozygotic twin pairs, respectively. METHODS Genome-wide DNA methylation profiling in whole blood of twins was performed using Reduced Representation Bisulfite Sequencing, yielding 551,447 raw CpGs. Association between DNAm of single CpG and blood pressure was tested by applying generalized estimation equation. Differentially methylated regions (DMRs) were identified by comb-P approach. Inference about Causation through Examination of Familial Confounding was utilized to perform the causal inference. Ontology enrichment analysis was performed using Genomic Regions Enrichment of Annotations Tool. Candidate CpGs were quantified using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data. RESULTS The median age of twins was 52 years (95% range 40, 66). For SBP, 31 top CpGs (p < 1 × 10-4) and 8 DMRs were identified, with several DMRs within NFATC1, CADM2, IRX1, COL5A1, and LRAT. For DBP, 43 top CpGs (p < 1 × 10-4) and 12 DMRs were identified, with several DMRs within WNT3A, CNOT10, and DAB2IP. Important pathways, such as Notch signaling pathway, p53 pathway by glucose deprivation, and Wnt signaling pathway, were significantly enriched for SBP and DBP. Causal inference analysis suggested that DNAm at top CpGs within NDE1, MYH11, SRRM1P2, and SMPD4 influenced SBP, while SBP influenced DNAm at CpGs within TNK2. DNAm at top CpGs within WNT3A influenced DBP, while DBP influenced DNAm at CpGs within GNA14. Three CpGs mapped to WNT3A and one CpG mapped to COL5A1 were validated in a community population, with a hypermethylated and hypomethylated direction in hypertension cases, respectively. Gene expression analysis by WGCNA further identified some common genes and enrichment terms. CONCLUSION We detect many DNAm variants that may be associated with blood pressure in whole blood, particularly the loci within WNT3A and COL5A1. Our findings provide new clues to the epigenetic modification underlying hypertension pathogenesis.
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Affiliation(s)
- Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China
| | - Jie Yao
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China
- Jiangsu Health Development Research Center, Nanjing, Jiangsu, China
| | - Weilong Li
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Yili Wu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Shuxia Li
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Qihua Tan
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China.
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14
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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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Udosen B, Soremekun O, Kamiza A, Machipisa T, Cheickna C, Omotuyi O, Soliman M, Wélé M, Nashiru O, Chikowore T, Fatumo S. Meta-Analysis and Multivariate GWAS Analyses in 80,950 Individuals of African Ancestry Identify Novel Variants Associated with Blood Pressure Traits. Int J Mol Sci 2023; 24:2164. [PMID: 36768488 PMCID: PMC9916484 DOI: 10.3390/ijms24032164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 12/24/2022] [Accepted: 01/03/2023] [Indexed: 01/25/2023] Open
Abstract
High blood pressure (HBP) has been implicated as a major risk factor for cardiovascular diseases in several populations, including individuals of African ancestry. Despite the elevated burden of HBP-induced cardiovascular diseases in Africa and other populations of African descent, limited genetic studies have been carried out to explore the genetic mechanism driving this phenomenon. We performed genome-wide association univariate and multivariate analyses of both systolic (SBP) and diastolic blood pressure (DBP) traits in 80,950 individuals of African ancestry. We used summary statistics data from six independent cohorts, including the African Partnership for Chronic Disease Research (APCDR), the UK Biobank, and the Million Veteran Program (MVP). FUMA was used to annotate, prioritize, visualize, and interpret our findings to gain a better understanding of the molecular mechanism(s) underlying the genetics of BP traits. Finally, we undertook a Bayesian fine-mapping analysis to identify potential causal variants. Our meta-analysis identified 10 independent variants associated with SBP and 9 with DBP traits. Whilst our multivariate GWAS method identified 21 independent signals, 18 of these SNPs have been previously identified. SBP was linked to gene sets involved in biological processes such as synapse assembly and cell-cell adhesion via plasma membrane adhesion. Of the 19 independent SNPs identified in the BP meta-analysis, only 11 variants had posterior probability (PP) of > 50%, including one novel variant: rs562545 (MOBP, PP = 77%). To facilitate further research and fine-mapping of high-risk loci/variants in highly susceptible groups for cardiovascular disease and other related traits, large-scale genomic datasets are needed. Our findings highlight the importance of including ancestrally diverse populations in large GWASs and the need for diversity in genetic research.
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Affiliation(s)
- Brenda Udosen
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe 7545, Uganda; (B.U.); (O.S.); (A.K.)
- The African Center of Excellence in Bioinformatics of Bamako (ACE-B), University of Sciences, Techniques and Technologies of Bamako, Bamako 3206, Mali; (C.C.); (M.W.)
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja 901101, Nigeria;
| | - Opeyemi Soremekun
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe 7545, Uganda; (B.U.); (O.S.); (A.K.)
- Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, Westville Campus, University of KwaZulu-Natal, Durban 4001, South Africa;
| | - Abram Kamiza
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe 7545, Uganda; (B.U.); (O.S.); (A.K.)
- Malawi Epidemiology and Intervention Research Unit, Lilongwe P.O. Box 46, Malawi
| | - Tafadzwa Machipisa
- Hatter Institute for Cardiovascular Diseases Research in Africa (HICRA), Department of Medicine, University of Cape Town, Cape Town 7701, South Africa;
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, ON L8L 2X2, Canada
| | - Cisse Cheickna
- The African Center of Excellence in Bioinformatics of Bamako (ACE-B), University of Sciences, Techniques and Technologies of Bamako, Bamako 3206, Mali; (C.C.); (M.W.)
- Department of Biological Sciences, Faculty of Sciences and Techniques, University of Sciences, Techniques and Technologies of Bamako, Bamako 3206, Mali
| | - Olaposi Omotuyi
- Institute for Drug Research and Development, S.E. Bogoro Center, Afe Babalola University, Ado Ekiti 360101, Nigeria;
| | - Mahmoud Soliman
- Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, Westville Campus, University of KwaZulu-Natal, Durban 4001, South Africa;
| | - Mamadou Wélé
- The African Center of Excellence in Bioinformatics of Bamako (ACE-B), University of Sciences, Techniques and Technologies of Bamako, Bamako 3206, Mali; (C.C.); (M.W.)
- Department of Biological Sciences, Faculty of Sciences and Techniques, University of Sciences, Techniques and Technologies of Bamako, Bamako 3206, Mali
| | - Oyekanmi Nashiru
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja 901101, Nigeria;
| | - Tinashe Chikowore
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2050, South Africa;
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Pediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2050, South Africa
| | - Segun Fatumo
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe 7545, Uganda; (B.U.); (O.S.); (A.K.)
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja 901101, Nigeria;
- Segun Fatumo, Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
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Malinowska JK, Żuradzki T. Towards the multileveled and processual conceptualisation of racialised individuals in biomedical research. SYNTHESE 2022; 201:11. [PMID: 36591336 PMCID: PMC9795162 DOI: 10.1007/s11229-022-04004-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 12/09/2022] [Indexed: 06/17/2023]
Abstract
In this paper, we discuss the processes of racialisation on the example of biomedical research. We argue that applying the concept of racialisation in biomedical research can be much more precise, informative and suitable than currently used categories, such as race and ethnicity. For this purpose, we construct a model of the different processes affecting and co-shaping the racialisation of an individual, and consider these in relation to biomedical research, particularly to studies on hypertension. We finish with a discussion on the potential application of our proposition to institutional guidelines on the use of racial categories in biomedical research.
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Affiliation(s)
| | - Tomasz Żuradzki
- Institute of Philosophy & Interdisciplinary Centre for Ethics, Jagiellonian University, ul. Grodzka 52, 31-044 Kraków, Poland
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17
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Abramova M, Churnosova M, Efremova O, Aristova I, Reshetnikov E, Polonikov A, Churnosov M, Ponomarenko I. Effects of Pre-Pregnancy Overweight/Obesity on the Pattern of Association of Hypertension Susceptibility Genes with Preeclampsia. Life (Basel) 2022; 12:life12122018. [PMID: 36556383 PMCID: PMC9784908 DOI: 10.3390/life12122018] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 11/21/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022] Open
Abstract
The aim of this study was to explore the effects of pre-pregnancy overweight/obesity on the pattern of association of hypertension susceptibility genes with preeclampsia (PE). Ten single-nucleotide polymorphisms (SNPs) of the 10 genome-wide association studies (GWAS)-significant hypertension/blood pressure (BP) candidate genes were genotyped in 950 pregnant women divided into two cohorts according to their pre-pregnancy body mass index (preBMI): preBMI ≥ 25 (162 with PE and 159 control) and preBMI < 25 (290 with PE and 339 control). The PLINK software package was utilized to study the association (analyzed four genetic models using logistic regression). The functionality of PE-correlated loci was analyzed by performing an in silico database analysis. Two SNP hypertension/BP genes, rs805303 BAG6 (OR: 0.36−0.66) and rs167479 RGL3 (OR: 1.86), in subjects with preBMI ≥ 25 were associated with PE. No association between the studied SNPs and PE in the preBMI < 25 group was determined. Further analysis showed that two PE-associated SNPs are functional (have weighty eQTL, sQTL, regulatory, and missense values) and could be potentially implicated in PE development. In conclusion, this study was the first to discover the modifying influence of overweight/obesity on the pattern of association of GWAS-significant hypertension/BP susceptibility genes with PE: these genes are linked with PE in preBMI ≥ 25 pregnant women and are not PE-involved in the preBMI < 25 group.
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Affiliation(s)
- Maria Abramova
- 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
| | - Olesya Efremova
- Department of Medical Genetics, Kharkiv National Medical University, 61022 Kharkov, Ukraine
- Grishchenko Clinic of Reproductive Medicine, 61052 Kharkov, Ukraine
| | - Inna Aristova
- 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
| | - Alexey Polonikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
- Department of Biology, Medical Genetics and Ecology and Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
- Correspondence:
| | - Irina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
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18
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Hall R, Yuan S, Wood K, Katona M, Straub AC. Cytochrome b5 reductases: Redox regulators of cell homeostasis. J Biol Chem 2022; 298:102654. [PMID: 36441026 PMCID: PMC9706631 DOI: 10.1016/j.jbc.2022.102654] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 10/24/2022] [Accepted: 10/26/2022] [Indexed: 11/06/2022] Open
Abstract
The cytochrome-b5 reductase (CYB5R) family of flavoproteins is known to regulate reduction-oxidation (redox) balance in cells. The five enzyme members are highly compartmentalized at the subcellular level and function as "redox switches" enabling the reduction of several substrates, such as heme and coenzyme Q. Critical insight into the physiological and pathophysiological significance of CYB5R enzymes has been gleaned from several human genetic variants that cause congenital disease and a broad spectrum of chronic human diseases. Among the CYB5R genetic variants, CYB5R3 is well-characterized and deficiency in expression and activity is associated with type II methemoglobinemia, cancer, neurodegenerative disorders, diabetes, and cardiovascular disease. Importantly, pharmacological and genetic-based strategies are underway to target CYB5R3 to circumvent disease onset and mitigate severity. Despite our knowledge of CYB5R3 in human health and disease, the other reductases in the CYB5R family have been understudied, providing an opportunity to unravel critical function(s) for these enzymes in physiology and disease. In this review, we aim to provide the broad scientific community an up-to-date overview of the molecular, cellular, physiological, and pathophysiological roles of CYB5R proteins.
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Affiliation(s)
- Robert Hall
- Heart, Lung, Blood and Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Shuai Yuan
- Heart, Lung, Blood and Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Katherine Wood
- Heart, Lung, Blood and Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Mate Katona
- Heart, Lung, Blood and Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Adam C Straub
- Heart, Lung, Blood and Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; Center for Microvascular Research, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
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19
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Churnosov M, Abramova M, Reshetnikov E, Lyashenko IV, Efremova O, Churnosova M, Ponomarenko I. Polymorphisms of hypertension susceptibility genes as a risk factors of preeclampsia in the Caucasian population of central Russia. Placenta 2022; 129:51-61. [PMID: 36219912 DOI: 10.1016/j.placenta.2022.09.010] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 08/18/2022] [Accepted: 09/14/2022] [Indexed: 12/14/2022]
Abstract
INTRODUCTION The study was designed to assess the effects of hypertension (HT) susceptibility genes polymorphisms in the development of preeclampsia (PE) in Caucasians from Central Russia. METHODS PE patients (n = 452) and women control group (n = 498) were genotyped for 10 polymorphisms of HT/blood pressure (BP) susceptibility genes (according to the previously published GWAS in Caucasian populations) including AC026703.1 (rs1173771), HFE (rs1799945), BAG6 (rs805303), PLCE1 (rs932764), OBFC1 (rs4387287), ARHGAP42 (rs633185), CERS5 (rs7302981), ATP2B1 (rs2681472), TBX2 (rs8068318) and RGL3 (rs167479). A logistic regression method was applied to search for associations between SNPs and PE. The relationship between SNP-SNP interactions and PE risk was analyzed by performing MB-MDR. RESULTS The rs1799945 gene in HFE significantly independently increased the risk of developing PE (OR = 2.24) and rs805303 in BAG6 was associated with a reduced risk in the occurrence of PE (OR = 0.55-0.78). Among the 10 SNPs examined, nine SNPs were associated with PEs within the 10 most significant SNP-SNP interaction models. Loci rs7302981 CERS5, rs805303 BAG6 and rs932764 PLCE1 contributed to the largest number of epistatic models (50% or more). DISCUSSION The present study is the first to report an association between polymorphisms of HT/BP susceptibility genes important for GWAS and the risk of PE in Caucasians from Central Russia. Our pathway-based functional annotation of the PE risk variants highlights the potential regulatory function (epigenetic/eQTL/sQTL/non-synonymous) that nine genetic risk markers and their 115 highly correlated variants exert on 155 genes. The study shows that these genes may function cooperatively in key signaling pathways in PE biology.
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Affiliation(s)
- Mikhail Churnosov
- Belgorod State National Research University, Department of Medical Biological Disciplines, Belgorod, Russia.
| | - Maria Abramova
- Belgorod State National Research University, Department of Medical Biological Disciplines, Belgorod, Russia
| | - Evgeny Reshetnikov
- Belgorod State National Research University, Department of Medical Biological Disciplines, Belgorod, Russia
| | - Igor V Lyashenko
- Belgorod State National Research University, Department of English Philology and Cross-cultural Communication, Belgorod, Russia
| | - Olesya Efremova
- Kharkiv National Medical University, Department of Medical Genetics, Kharkov, Ukraine; Grishchenko Clinic of Reproductive Medicine, Kharkov, Ukraine
| | - Maria Churnosova
- Belgorod State National Research University, Department of Medical Biological Disciplines, Belgorod, Russia
| | - Irina Ponomarenko
- Belgorod State National Research University, Department of Medical Biological Disciplines, Belgorod, Russia
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20
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Seligowski AV, Misganaw B, Duffy LA, Ressler KJ, Guffanti G. Leveraging Large-Scale Genetics of PTSD and Cardiovascular Disease to Demonstrate Robust Shared Risk and Improve Risk Prediction Accuracy. Am J Psychiatry 2022; 179:814-823. [PMID: 36069022 PMCID: PMC9633348 DOI: 10.1176/appi.ajp.21111113] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
OBJECTIVE Individuals with posttraumatic stress disorder (PTSD) are significantly more likely to be diagnosed with cardiovascular disease (CVD) (e.g., myocardial infarction, stroke). The evidence for this link is so compelling that the National Institutes of Health convened a working group to determine gaps in the literature, including the need for large-scale genomic studies to identify shared genetic risk. The aim of the present study was to address some of these gaps by utilizing PTSD and CVD genome-wide association study (GWAS) summary statistics in a large biobank sample to determine the shared genetic risk of PTSD and CVD. METHODS A large health care biobank data set was used (N=36,412), combined with GWAS summary statistics from publicly available large-scale PTSD and CVD studies. Disease phenotypes (e.g., PTSD) were collected from electronic health records. De-identified genetic data from the biobank were genotyped using Illumina SNP array. Summary statistics data sets were processed with the following quality-control criteria: 1) SNP heritability h2 >0.05, 2) compute z-statistics (z=beta/SE or z=log(OR)/SE), 3) filter nonvariable SNPs (0 RESULTS Significant genetic correlations were found between PTSD and CVD (rG=0.24, SE=0.06), and Mendelian randomization analyses indicated a potential causal link from PTSD to hypertension (β=0.20, SE=0.04), but not the reverse. PTSD summary statistics significantly predicted PTSD diagnostic status (R2=0.27), and this was significantly improved by incorporating summary statistics from CVD and major depressive disorder (R2=1.30). Further, pathway enrichment analyses indicated that genetic variants involved in shared PTSD-CVD risk included those involved in postsynaptic structure, synapse organization, and interleukin-7-mediated signaling pathways. CONCLUSIONS The results from this study suggest that PTSD and CVD may share genetic risk. Further, these results implicate PTSD as a risk factor leading to the development of hypertension and coronary artery disease. Additional research is needed to determine the clinical utility of these findings.
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Affiliation(s)
- Antonia V. Seligowski
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- McLean Hospital, Belmont, MA, USA
| | - Burook Misganaw
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- McLean Hospital, Belmont, MA, USA
| | | | - Kerry J. Ressler
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- McLean Hospital, Belmont, MA, USA
| | - Guia Guffanti
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- McLean Hospital, Belmont, MA, USA
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21
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Tomaszewski M, Morris AP, Howson JMM, Franceschini N, Eales JM, Xu X, Dikalov S, Guzik TJ, Humphreys BD, Harrap S, Charchar FJ. Kidney omics in hypertension: from statistical associations to biological mechanisms and clinical applications. Kidney Int 2022; 102:492-505. [PMID: 35690124 PMCID: PMC9886011 DOI: 10.1016/j.kint.2022.04.045] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 03/10/2022] [Accepted: 04/22/2022] [Indexed: 02/06/2023]
Abstract
Hypertension is a major cardiovascular disease risk factor and contributor to premature death globally. Family-based investigations confirmed a significant heritable component of blood pressure (BP), whereas genome-wide association studies revealed >1000 common and rare genetic variants associated with BP and/or hypertension. The kidney is not only an organ of key relevance to BP regulation and the development of hypertension, but it also acts as the tissue mediator of genetic predisposition to hypertension. The identity of kidney genes, pathways, and related mechanisms underlying the genetic associations with BP has started to emerge through integration of genomics with kidney transcriptomics, epigenomics, and other omics as well as through applications of causal inference, such as Mendelian randomization. Single-cell methods further enabled mapping of BP-associated kidney genes to cell types, and in conjunction with other omics, started to illuminate the biological mechanisms underpinning associations of BP-associated genetic variants and kidney genes. Polygenic risk scores derived from genome-wide association studies and refined on kidney omics hold the promise of enhanced diagnostic prediction, whereas kidney omics-informed drug discovery is likely to contribute new therapeutic opportunities for hypertension and hypertension-mediated kidney damage.
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Affiliation(s)
- Maciej Tomaszewski
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK; Manchester Heart Centre and Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK.
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
| | - Joanna M M Howson
- Department of Genetics, Novo Nordisk Research Centre Oxford, Novo Nordisk Ltd, Oxford, UK
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
| | - James M Eales
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Xiaoguang Xu
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sergey Dikalov
- Division of Clinical Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Tomasz J Guzik
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK; Department of Internal and Agricultural Medicine, Jagiellonian University College of Medicine, Kraków, Poland
| | - Benjamin D Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Stephen Harrap
- Department of Anatomy and Physiology, University of Melbourne, Melbourne, Victoria, Australia
| | - Fadi J Charchar
- Department of Anatomy and Physiology, University of Melbourne, Melbourne, Victoria, Australia; Health Innovation and Transformation Centre, School of Science, Psychology and Sport, Federation University Australia, Ballarat, Victoria, Australia; Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
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22
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Kelly TN, Sun X, He KY, Brown MR, Taliun SAG, Hellwege JN, Irvin MR, Mi X, Brody JA, Franceschini N, Guo X, Hwang SJ, de Vries PS, Gao Y, Moscati A, Nadkarni GN, Yanek LR, Elfassy T, Smith JA, Chung RH, Beitelshees AL, Patki A, Aslibekyan S, Blobner BM, Peralta JM, Assimes TL, Palmas WR, Liu C, Bress AP, Huang Z, Becker LC, Hwa CM, O'Connell JR, Carlson JC, Warren HR, Das S, Giri A, Martin LW, Craig Johnson W, Fox ER, Bottinger EP, Razavi AC, Vaidya D, Chuang LM, Chang YPC, Naseri T, Jain D, Kang HM, Hung AM, Srinivasasainagendra V, Snively BM, Gu D, Montasser ME, Reupena MS, Heavner BD, LeFaive J, Hixson JE, Rice KM, Wang FF, Nielsen JB, Huang J, Khan AT, Zhou W, Nierenberg JL, Laurie CC, Armstrong ND, Shi M, Pan Y, Stilp AM, Emery L, Wong Q, Hawley NL, Minster RL, Curran JE, Munroe PB, Weeks DE, North KE, Tracy RP, Kenny EE, Shimbo D, Chakravarti A, Rich SS, Reiner AP, Blangero J, Redline S, Mitchell BD, Rao DC, Ida Chen YD, Kardia SLR, Kaplan RC, Mathias RA, He J, Psaty BM, Fornage M, Loos RJF, Correa A, Boerwinkle E, Rotter JI, Kooperberg C, Edwards TL, Abecasis GR, Zhu X, Levy D, Arnett DK, Morrison AC. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. Hypertension 2022; 79:1656-1667. [PMID: 35652341 PMCID: PMC9593435 DOI: 10.1161/hypertensionaha.122.19324] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 05/12/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. METHODS We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. RESULTS Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (P<5×10-8). Among them, a rare intergenic variant at novel locus, LOC100506274, was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; P=4.99×10-8) but not stage-2 analysis (P=0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; P=4.18×10-7) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; P=7.28×10-23). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (P<1×10-6 and P<1×10-4, respectively). DISCUSSION We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.
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Affiliation(s)
- Tanika N Kelly
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
- Translational Sciences Institute (T.N.K., J.H.), Tulane University, New Orleans, LA
| | - Xiao Sun
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Karen Y He
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH (K.Y.H., X.Z.)
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Sarah A Gagliano Taliun
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Jacklyn N Hellwege
- Division of Genetic Medicine, Department of Medicine (J.N.H.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | - Marguerite R Irvin
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Xuenan Mi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.E.N.), University of Washington, Seattle' WA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill (N.F.)
| | - 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 (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Shih-Jen Hwang
- National Heart, Lung and Blood Institute, Population Sciences Branch, National Institutes of Health, Framingham, MA (S.-J.H.)
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Yan Gao
- Department of Physiology and Biophysics (Y.G., E.E.K., R.J.F.L.), University of Mississippi Medical Center, Jackson' MS
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Girish N Nadkarni
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
- Department of Medicine (G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine (L.R.Y., D.V.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Tali Elfassy
- Division of Epidemiology, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami' FL (T.E.)
| | - Jennifer A Smith
- Department of Epidemiology (J.A.S., S.L.R.K.), University of Michigan, Ann Arbor' MI
| | - Ren-Hua Chung
- Institute of Population Sciences, National Health Research Institutes, Taiwan (R.-H.C.)
| | - Amber L Beitelshees
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Amit Patki
- Department of Biostatistics (A.P., V.S.), University of Alabama at Birmingham' AL
| | - Stella Aslibekyan
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Brandon M Blobner
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services (B.M.P.), University of Washington, Seattle' WA
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
| | - Juan M Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Themistocles L Assimes
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford' CA (T.L.A.)
- Division of Cardiology Medicine, Palo Alto VA HealthCare System, Palo Alto' CA (T.L.A.)
| | - Walter R Palmas
- Division of General Medicine, Department of Medicine, Columbia University, New York, NY (W.R.P.)
| | - Chunyu Liu
- Department of Biostatistics, Boston University, Boston' MA (C.L.)
| | - Adam P Bress
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City' UT (A.P.B.)
| | - Zhijie Huang
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Lewis C Becker
- Division of Cardiology, Department of Medicine (L.C.B.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Chii-Min Hwa
- Taichung Veterans General Hospital, Taichung, Taiwan (C.-M.H.)
| | - Jeffrey R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Jenna C Carlson
- Department of Biostatistics, Graduate School of Public Health (J.C.C.), University of Pittsburgh, PA
| | - Helen R Warren
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Centre (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
| | - Sayantan Das
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Ayush Giri
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University, Nashville, TN (A.G.)
| | - Lisa W Martin
- Division of Cardiology, Department of Medicine, George Washington University, Washington, DC (L.W.M.)
| | - W Craig Johnson
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Ervin R Fox
- Division of Cardiology, Department of Medicine (E.R.F.), University of Mississippi Medical Center, Jackson' MS
| | - Erwin P Bottinger
- Hasso Plattner Institute for Digital Health at Mount Sinai (E.P.B.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Alexander C Razavi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Dhananjay Vaidya
- Division of General Internal Medicine, Department of Medicine (L.R.Y., D.V.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei' Taiwan (L.-M.C.)
| | - Yen-Pei C Chang
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Take Naseri
- Ministry of Health, Government of Samoa, Apia' Samoa (T.N.)
| | - Deepti Jain
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Hyun Min Kang
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Adriana M Hung
- Division of Nephrology and Hypertension, Department of Medicine (A.M.H.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | | | - Beverly M Snively
- Division of Public Health Sciences, Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC (B.M.S.)
| | - Dongfeng Gu
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (D.G., J.H.)
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | | | - Benjamin D Heavner
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Jonathon LeFaive
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - James E Hixson
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Kenneth M Rice
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Fei Fei Wang
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Jonas B Nielsen
- Department of Internal Medicine: Cardiology (J.B.N.), University of Michigan, Ann Arbor' MI
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark (J.B.N.)
| | - Jianfeng Huang
- Translational Sciences Institute (T.N.K., J.H.), Tulane University, New Orleans, LA
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (D.G., J.H.)
| | - Alyna T Khan
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics (W.Z.), University of Michigan, Ann Arbor' MI
| | - Jovia L Nierenberg
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Cathy C Laurie
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Nicole D Armstrong
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Mengyao Shi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Yang Pan
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Adrienne M Stilp
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Leslie Emery
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Quenna Wong
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Nicola L Hawley
- Department of Chronic Disease Epidemiology, Yale University, New Haven, CT (N.L.H.)
| | - Ryan L Minster
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Patricia B Munroe
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Centre (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
| | - Daniel E Weeks
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
- Department of Biostatistics (D.E.W.), University of Pittsburgh, PA
| | - Kari E North
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.E.N.), University of Washington, Seattle' WA
| | - Russell P Tracy
- Department of Pathology & Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington' VT (R.P.T.)
| | - Eimear E Kenny
- Department of Physiology and Biophysics (Y.G., E.E.K., R.J.F.L.), University of Mississippi Medical Center, Jackson' MS
- Department of Genetics and Genomics (E.E.K.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Daichi Shimbo
- Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY (D.S.)
| | - Aravinda Chakravarti
- Department of Medicine (A.C.), University of Mississippi Medical Center, Jackson' MS
| | - Stephen S Rich
- Center for Public Health, University of Virginia, Charlottesville' VA (S.S.R.)
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (A.P.R., C.K.)
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA (S.R.)
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore' MD (B.D.M.)
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R.)
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Sharon L R Kardia
- Department of Epidemiology (J.A.S., S.L.R.K.), University of Michigan, Ann Arbor' MI
| | - Robert C Kaplan
- Division of Social Medicine, Albert Einstein College of Medicine, Bronx, NY (R.C.K.)
| | - Rasika A Mathias
- Division of Allergy & Clinical Immunology, Department of Medicine (R.A.M.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jiang He
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Bruce M Psaty
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
- Kaiser Permanente Washington Health Research Institute, Seattle' WA (B.M.P.)
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine (M.F.), The University of Texas Health Science Center at Houston' Houston' TX
- Human Genetics Center (M.F.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Ruth J F Loos
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
- The Mindich Child Health and Development Institute (R.J.F.L.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Adolfo Correa
- Center for Human Genetics and Genomics, New York University Grossman School of Medicine, New York, NY (A.C.)
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX (E.B.)
| | - 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 (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (A.P.R., C.K.)
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine (T.L.E.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | - Gonçalo R Abecasis
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH (K.Y.H., X.Z.)
| | - Daniel Levy
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY (D.K.A.)
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
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23
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Kurniansyah N, Goodman MO, Kelly TN, Elfassy T, Wiggins KL, Bis JC, Guo X, Palmas W, Taylor KD, Lin HJ, Haessler J, Gao Y, Shimbo D, Smith JA, Yu B, Feofanova EV, Smit RAJ, Wang Z, Hwang SJ, Liu S, Wassertheil-Smoller S, Manson JE, Lloyd-Jones DM, Rich SS, Loos RJF, Redline S, Correa A, Kooperberg C, Fornage M, Kaplan RC, Psaty BM, Rotter JI, Arnett DK, Morrison AC, Franceschini N, Levy D, Sofer T. A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood. Nat Commun 2022; 13:3549. [PMID: 35729114 PMCID: PMC9213527 DOI: 10.1038/s41467-022-31080-2] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 05/31/2022] [Indexed: 12/12/2022] Open
Abstract
In a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease.
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Affiliation(s)
- Nuzulul Kurniansyah
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Matthew O Goodman
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Tali Elfassy
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kerri L Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 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
| | - Walter Palmas
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Kent D Taylor
- 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
| | - Henry J Lin
- 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
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Yan Gao
- The Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Daichi Shimbo
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Bing Yu
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Elena V Feofanova
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Roelof A J Smit
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shih-Jen Hwang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Simin Liu
- Center for Global Cardiometabolic Health and Departments of Epidemiology, Medicine, and Surgery, Brown University, Providence, RI, USA
| | - Sylvia Wassertheil-Smoller
- Department of Epidemiology & Population Health, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - JoAnn E Manson
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Adolfo Correa
- Departments of Medicine and Pediatrics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Robert C Kaplan
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, 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
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Daniel Levy
- The Population Sciences Branch of the National Heart, Lung and Blood Institute, Bethesda, MD, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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24
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Jung J, Kim H. Shared genetic etiology and antagonistic relationship of plasma renin activity and systolic blood pressure in a Korean cohorts. Genomics 2022; 114:110334. [PMID: 35278618 DOI: 10.1016/j.ygeno.2022.110334] [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: 11/08/2021] [Revised: 02/11/2022] [Accepted: 03/06/2022] [Indexed: 01/14/2023]
Abstract
Despite extensive studies on blood pressure, its genetic risk factors remain uncertain. Even one of the most researched blood pressure-related traits - renin - is not fully understood genetically. Here, we determine the genetic relationship and associated predisposition between blood pressure and baseline renin. In 8840 Korean individuals, we observed a strong negative genome-wide genetic correlation (rg = -0.484) between systolic blood pressure (SBP) and plasma renin activity (PRA), suggesting that antagonistic genetic signals explain the variance in the two traits. We found 51 significant pleiotropic SNPs affecting the two traits, which could contribute to the Renin-Angiotensin-Aldosterone System (RAAS). Our findings provide insight into studies on RAAS by identifying the genome-wide relationship and susceptibility loci of SBP and PRA.
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Affiliation(s)
- Jaehoon Jung
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 151-742, Republic of Korea; eGnome, 26 Beobwon-ro, Songpa-gu, Seoul 05836, Republic of Korea.
| | - Heebal Kim
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 151-742, Republic of Korea; eGnome, 26 Beobwon-ro, Songpa-gu, Seoul 05836, Republic of Korea; Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-742, Republic of Korea.
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25
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Luo S, Zheng N, Lang B. ULK4 in Neurodevelopmental and Neuropsychiatric Disorders. Front Cell Dev Biol 2022; 10:873706. [PMID: 35493088 PMCID: PMC9039724 DOI: 10.3389/fcell.2022.873706] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 03/29/2022] [Indexed: 11/21/2022] Open
Abstract
The gene Unc51-like kinase 4 (ULK4) belongs to the Unc-51-like serine/threonine kinase family and is assumed to encode a pseudokinase with unclear function. Recently, emerging evidence has suggested that ULK4 may be etiologically involved in a spectrum of neuropsychiatric disorders including schizophrenia, but the underlying mechanism remains unaddressed. Here, we summarize the key findings of the structure and function of the ULK4 protein to provide comprehensive insights to better understand ULK4-related neurodevelopmental and neuropsychiatric disorders and to aid in the development of a ULK4-based therapeutic strategy.
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Affiliation(s)
- Shilin Luo
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China
- Hunan Provincial Engineering Research Center of Translational Medicine and Innovative Drug, Changsha, China
| | - Nanxi Zheng
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- *Correspondence: Nanxi Zheng, ; Bing Lang,
| | - Bing Lang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- *Correspondence: Nanxi Zheng, ; Bing Lang,
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Zhu X, Zhu L, Wang H, Cooper RS, Chakravarti A. Genome-wide pleiotropy analysis identifies novel blood pressure variants and improves its polygenic risk scores. Genet Epidemiol 2022; 46:105-121. [PMID: 34989438 PMCID: PMC8863647 DOI: 10.1002/gepi.22440] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 12/07/2021] [Indexed: 01/21/2023]
Abstract
Systolic and diastolic blood pressure (S/DBP) are highly correlated modifiable risk factors for cardiovascular disease (CVD). We report here a bidirectional Mendelian Randomization (MR) and horizontal pleiotropy analysis of S/DBP summary statistics from the UK Biobank (UKB)-International Consortium for Blood Pressure (ICBP) (UKB-ICBP) BP genome-wide association study and construct a composite genetic risk score (GRS) by including pleiotropic variants. The composite GRS captures greater (1.11-3.26 fold) heritability for BP traits and increases (1.09- and 2.01-fold) Nagelkerke's R2 for hypertension and CVD. We replicated 118 novel BP horizontal pleiotropic variants including 18 novel BP loci using summary statistics from the Million Veteran Program (MVP) study. An additional 219 novel BP signals and 40 novel loci were identified after a meta-analysis of the UKB-ICBP and MVP summary statistics but without further independent replication. Our study provides further insight into BP regulation and provides a novel way to construct a GRS by including pleiotropic variants for other complex diseases.
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Affiliation(s)
- Xiaofeng Zhu
- Department of Population and Quantitative Health SciencesCase Western Reserve UniversityClevelandOhioUSA
| | - Luke Zhu
- Department of Medicine, Center for Human Genetics & GenomicsNew York University Langone HealthNew YorkNew YorkUSA
| | - Heming Wang
- Division of Sleep and Circadian DisordersBrigham and Women's HospitalBostonMassachusettsUSA
| | - Richard S. Cooper
- Department of Public Health Sciences, Stritch School of MedicineLoyola University ChicagoMaywoodIllinoisUSA
| | - Aravinda Chakravarti
- Department of Medicine, Center for Human Genetics & GenomicsNew York University Langone HealthNew YorkNew YorkUSA
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27
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He KY, Kelly TN, Wang H, Liang J, Zhu L, Cade BE, Assimes TL, Becker LC, Beitelshees AL, Bielak LF, Bress AP, Brody JA, Chang YPC, Chang YC, de Vries PS, Duggirala R, Fox ER, Franceschini N, Furniss AL, Gao Y, Guo X, Haessler J, Hung YJ, Hwang SJ, Irvin MR, Kalyani RR, Liu CT, Liu C, Martin LW, Montasser ME, Muntner PM, Mwasongwe S, Naseri T, Palmas W, Reupena MS, Rice KM, Sheu WHH, Shimbo D, Smith JA, Snively BM, Yanek LR, Zhao W, Blangero J, Boerwinkle E, Chen YDI, Correa A, Cupples LA, Curran JE, Fornage M, He J, Hou L, Kaplan RC, Kardia SLR, Kenny EE, Kooperberg C, Lloyd-Jones D, Loos RJF, Mathias RA, McGarvey ST, Mitchell BD, North KE, Peyser PA, Psaty BM, Raffield LM, Rao DC, Redline S, Reiner AP, Rich SS, Rotter JI, Taylor KD, Tracy R, Vasan RS, Morrison AC, Levy D, Chakravarti A, Arnett DK, Zhu X. Rare coding variants in RCN3 are associated with blood pressure. BMC Genomics 2022; 23:148. [PMID: 35183128 PMCID: PMC8858539 DOI: 10.1186/s12864-022-08356-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 02/01/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND While large genome-wide association studies have identified nearly one thousand loci associated with variation in blood pressure, rare variant identification is still a challenge. In family-based cohorts, genome-wide linkage scans have been successful in identifying rare genetic variants for blood pressure. This study aims to identify low frequency and rare genetic variants within previously reported linkage regions on chromosomes 1 and 19 in African American families from the Trans-Omics for Precision Medicine (TOPMed) program. Genetic association analyses weighted by linkage evidence were completed with whole genome sequencing data within and across TOPMed ancestral groups consisting of 60,388 individuals of European, African, East Asian, Hispanic, and Samoan ancestries. RESULTS Associations of low frequency and rare variants in RCN3 and multiple other genes were observed for blood pressure traits in TOPMed samples. The association of low frequency and rare coding variants in RCN3 was further replicated in UK Biobank samples (N = 403,522), and reached genome-wide significance for diastolic blood pressure (p = 2.01 × 10- 7). CONCLUSIONS Low frequency and rare variants in RCN3 contributes blood pressure variation. This study demonstrates that focusing association analyses in linkage regions greatly reduces multiple-testing burden and improves power to identify novel rare variants associated with blood pressure traits.
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Affiliation(s)
- Karen Y He
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Cleveland, OH, 44106, USA
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Jingjing Liang
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Cleveland, OH, 44106, USA
| | - Luke Zhu
- Center for Human Genetics & Genomics, New York University Grossman School of Medicine, New York, NY, USA
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Themistocles L Assimes
- Department of Medicine (Division of Cardiovascular Medicine), Stanford University, Palo Alto, CA, USA
| | - Lewis C Becker
- GeneSTAR Research Program, Department of Medicine, Divisions of Cardiology and General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Amber L Beitelshees
- Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Adam P Bress
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Yen-Pei Christy Chang
- Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yi-Cheng Chang
- Graduate Institute of Medical Genomics and Proteomics, National Taiwan University, Taipei City, Taiwan
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Ervin R Fox
- Division of Cardiovascular Diseases, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Nora Franceschini
- Department of Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - Anna L Furniss
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Yan Gao
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, 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
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Yi-Jen Hung
- Institute of Preventive Medicine, National Defense Medical Center, New Taipei City, Taiwan
| | - Shih-Jen Hwang
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Marguerite Ryan Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AB, USA
| | - Rita R Kalyani
- GeneSTAR Research Program, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ching-Ti Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Chunyu Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Lisa Warsinger Martin
- Division of Cardiology, Department of Medicine, George Washington University, Washington, DC, USA
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Paul M Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AB, USA
| | | | - Take Naseri
- Ministry of Health, Government of Samoa, Apia, Samoa
| | - Walter Palmas
- Division of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
| | | | - Kenneth M Rice
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Wayne H-H Sheu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung City, Taiwan
| | - Daichi Shimbo
- Division of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Beverly M Snively
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Department of Medicine, Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - 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
| | - Yii-Der Ida Chen
- 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
- Division of Genomic Outcomes, Department of Pediatrics, Harbor-UCLA Medical Center Professor of Pediatrics, UCLA, Torrance, CA, USA
| | - Adolfo Correa
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - L Adrienne Cupples
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Myriam Fornage
- 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
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Donald Lloyd-Jones
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rasika A Mathias
- GeneSTAR Research Program, Department of Medicine, Divisions of Allergy and Clinical Immunology and General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Stephen T McGarvey
- International Health Institute and Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA
- Department of Anthropology, Brown University, Providence, RI, USA
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Veterans Affairs Medical Center, Baltimore, MD, USA
| | - Kari E North
- Department of Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - D C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 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
| | - Kent D Taylor
- 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
| | - Russell Tracy
- Department of Pathology & Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
| | - Ramachandran S Vasan
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, School of Medicine, Boston University, Boston, MA, USA
| | - 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
| | - Daniel Levy
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Aravinda Chakravarti
- Center for Human Genetics & Genomics, New York University Grossman School of Medicine, New York, NY, USA
| | - Donna K Arnett
- University of Kentucky College of Public Health, Lexington, KY, USA
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Cleveland, OH, 44106, USA.
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Maj C, Salvi E, Citterio L, Borisov O, Simonini M, Glorioso V, Barlassina C, Glorioso N, Thijs L, Kuznetsova T, Cappuccio FP, Zhang ZY, Staessen JA, Cusi D, Lanzani C, Manunta P. Dissecting the Polygenic Basis of Primary Hypertension: Identification of Key Pathway-Specific Components. Front Cardiovasc Med 2022; 9:814502. [PMID: 35252394 PMCID: PMC8888857 DOI: 10.3389/fcvm.2022.814502] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 01/19/2022] [Indexed: 12/11/2022] Open
Abstract
Introduction and Objectives Genome-wide association studies have identified a high number of genetic loci associated with hypertension suggesting the presence of an underlying polygenic architecture. In this study, we aimed to dissect the polygenic component of primary hypertension searching also for pathway-specific components. Methods The polygenic risk score (PRS) models, based on the UK biobank genetic signals for hypertension status, were obtained on a target Italian case/control cohort including 561 cases and 731 hyper-normal controls from HYPERGENES, and were then applied to an independent validation cohort composed by multi-countries European-based samples including 1,284 cases and 960 hyper-normal controls. Results The resulting genome-wide PRS was capable of stratifying the individuals for hypertension risk by comparing between individuals in the last PRS decile and the median decile: we observed an odds ratio (OR) of 3.62, CI = [2.01, 6.32] (P = 9.01E-07) and 3.22, 95% CI = [2.06, 5.10] (P = 6.47E-08) in the target and validation cohorts, respectively. The relatively high case/control ORs across PRS quantiles corroborates the presence of strong polygenic components which could be driven by an enrichment of risk alleles within the cases but also by potential enrichment of protective alleles in the old normotensive controls. Moreover, novel pathway-specific PRS revealed an enrichment of the polygenic signal attributable to specific biological pathways. Among those the most significantly associated with hypertension status was the calcium signaling pathway together with other mainly related such as the phosphatidylinositol/inositol phosphate pathways. Conclusions The development of pathway-specific PRS could prioritize biological mechanisms, according to their contribution to the genetic susceptibility, whose regulations might be a potential pharmacological preventive target.
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Affiliation(s)
- Carlo Maj
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University of Bonn, Bonn, Germany
- *Correspondence: Carlo Maj
| | - Erika Salvi
- Neuroalgology Unit, Fondazione IRCCS Istituto Neurologico “Carlo Besta”, Milan, Italy
| | - Lorena Citterio
- Genomics of Renal Diseases and Hypertension Unit, Istituto di Ricovero e Cura a Carattere Scientifico IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Oleg Borisov
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University of Bonn, Bonn, Germany
| | - Marco Simonini
- Genomics of Renal Diseases and Hypertension Unit, Istituto di Ricovero e Cura a Carattere Scientifico IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Valeria Glorioso
- Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy
| | | | - Nicola Glorioso
- Department of Clinical and Experimental Medicine, Hypertension and Related Diseases Centre, University of Sassari, Sassari, Italy
| | - Lutgarde Thijs
- Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Tatiana Kuznetsova
- Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Francesco P. Cappuccio
- Warwick Medical School, and UHCW NHS Trust, University of Warwick, Coventry, United Kingdom
| | - Zhen-Yu Zhang
- Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Jan A. Staessen
- Research Institute Alliance for the Promotion of Preventive Medicine (APPREMED), Mechelen, Belgium
- Biomedical Science Group, Faculty of Medicine, University of Leuven, Leuven, Belgium
| | - Daniele Cusi
- Institute of Biomedical Technologies Milano National Research Council of Italy (CNR), Milano, Italy
- Bio4Dreams Scientific Unit, Bio4Dreams-Business Nursery for Life Sciences, Milano, Italy
| | - Chiara Lanzani
- Genomics of Renal Diseases and Hypertension Unit, Istituto di Ricovero e Cura a Carattere Scientifico IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Paolo Manunta
- Genomics of Renal Diseases and Hypertension Unit, Istituto di Ricovero e Cura a Carattere Scientifico IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
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Chaudhary M. Novel methylation mark and essential hypertension. JOURNAL OF GENETIC ENGINEERING AND BIOTECHNOLOGY 2022; 20:11. [PMID: 35061109 PMCID: PMC8777530 DOI: 10.1186/s43141-022-00301-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 01/14/2022] [Indexed: 12/11/2022]
Abstract
Background Essential hypertension (EH) is an important risk factor for various cardiovascular, cerebral and renal disorders. It is a multi-factorial trait which occurs through complex interplay between genetic, epigenetic, and environmental factors. Even after advancement of technology and deciphering the involvement of multiple signalling pathways in blood pressure regulation, it still remains as a huge global concern. Main body of the abstract Genome-wide association studies (GWAS) have revealed EH-associated genetic variants but these solely cannot explain the variability in blood pressure indicating the involvement of additional factors. The etiopathogenesis of hypertension has now advanced to the level of epigenomics where aberrant DNA methylation is the most defined epigenetic mechanism to be involved in gene regulation. Though role of DNA methylation in cancer and other mechanisms is deeply studied but this mechanism is in infancy in relation to hypertension. Generally, 5-methylcytosine (5mC) levels are being targeted at both individual gene and global level to find association with the disease. But recently, with advanced sequencing techniques another methylation mark, N6-methyladenine (6mA) was found and studied in humans which was earlier considered to be absent in case of eukaryotes. Relation of aberrant 6mA levels with cancer and stem cell fate has drawn attention to target 6mA levels with hypertension too. Conclusion Recent studies targeting hypertension has suggested 6mA levels as novel marker and its demethylase, ALKBH1 as probable therapeutic target to prevent hypertension through epigenetic programming. This review compiles different methylation studies and suggests targeting of both 5mC and 6mA levels to cover role of methylation in hypertension in broader scenario.
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30
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Nakano S, Nishikawa M, Kobayashi T, Harlin EW, Ito T, Sato K, Sugiyama T, Yamakawa H, Nagase T, Ueda H. The Rho guanine nucleotide exchange factor PLEKHG1 is activated by interaction with and phosphorylation by Src family kinase member FYN. J Biol Chem 2022; 298:101579. [PMID: 35031323 PMCID: PMC8819033 DOI: 10.1016/j.jbc.2022.101579] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 12/20/2021] [Accepted: 12/22/2021] [Indexed: 01/01/2023] Open
Abstract
Rho family small GTPases (Rho) regulate various cell motility processes by spatiotemporally controlling the actin cytoskeleton. Some Rho-specific guanine nucleotide exchange factors (RhoGEFs) are regulated via tyrosine phosphorylation by Src family tyrosine kinase (SFK). We also previously reported that PLEKHG2, a RhoGEF for the GTPases Rac1 and Cdc42, is tyrosine-phosphorylated by SRC. However, the details of the mechanisms by which SFK regulates RhoGEFs are not well understood. In this study, we found for the first time that PLEKHG1, which has very high homology to the Dbl and pleckstrin homology domains of PLEKHG2, activates Cdc42 following activation by FYN, a member of the SFK family. We also show that this activation of PLEKHG1 by FYN requires interaction between these two proteins and FYN-induced tyrosine phosphorylation of PLEKHG1. We also found that the region containing the Src homology 3 and Src homology 2 domains of FYN is required for this interaction. Finally, we demonstrated that tyrosine phosphorylation of Tyr-720 and Tyr-801 in PLEKHG1 is important for the activation of PLEKHG1. These results suggest that FYN is a regulator of PLEKHG1 and may regulate cell morphology through Rho signaling via the interaction with and tyrosine phosphorylation of PLEKHG1.
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Affiliation(s)
- Shun Nakano
- United Graduate School of Drug Discovery and Medical Information Sciences, Gifu University, Gifu, Japan
| | - Masashi Nishikawa
- United Graduate School of Drug Discovery and Medical Information Sciences, Gifu University, Gifu, Japan
| | | | - Eka Wahyuni Harlin
- Graduate School of Natural Science and Technology, Gifu University, Gifu, Japan
| | - Takuya Ito
- Graduate School of Natural Science and Technology, Gifu University, Gifu, Japan
| | - Katsuya Sato
- Department of Molecular Pathobiochemistry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Tsuyoshi Sugiyama
- Faculty of Pharmacy, Gifu University of Medical Science, Kani, Gifu, Japan
| | | | | | - Hiroshi Ueda
- United Graduate School of Drug Discovery and Medical Information Sciences, Gifu University, Gifu, Japan; Graduate School of Natural Science and Technology, Gifu University, Gifu, Japan.
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31
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Miller EC, Wilczek A, Bello NA, Tom S, Wapner R, Suh Y. Pregnancy, preeclampsia and maternal aging: From epidemiology to functional genomics. Ageing Res Rev 2022; 73:101535. [PMID: 34871806 PMCID: PMC8827396 DOI: 10.1016/j.arr.2021.101535] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 11/15/2021] [Accepted: 12/01/2021] [Indexed: 01/03/2023]
Abstract
Women live longer than men but experience greater disability and a longer period of illness as they age. Despite clear sex differences in aging, the impact of pregnancy and its complications, such as preeclampsia, on aging is an underexplored area of geroscience. This review summarizes our current knowledge about the complex links between pregnancy and age-related diseases, including evidence from epidemiology, clinical research, and genetics. We discuss the relationship between normal and pathological pregnancy and maternal aging, using preeclampsia as a primary example. We review the results of human genetics studies of preeclampsia, including genome wide association studies (GWAS), and attempted to catalog genes involved in preeclampsia as a gateway to mechanisms underlying an increased risk of later life cardio- and neuro- vascular events. Lastly, we discuss challenges in interpreting the GWAS of preeclampsia and provide a functional genomics framework for future research needed to fully realize the promise of GWAS in identifying targets for geroprotective prevention and therapeutics against preeclampsia.
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Affiliation(s)
- Eliza C. Miller
- Department of Neurology, Division of Stroke and Cerebrovascular Disease, Columbia University Irving Medical Center, New York, NY, USA
| | - Ashley Wilczek
- Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY, USA
| | - Natalie A. Bello
- Department of Medicine, Division of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Sarah Tom
- Department of Neurology, Division of Neurology Clinical Outcomes Research and Population Science and the Department of Epidemiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Ronald Wapner
- Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY, USA.
| | - Yousin Suh
- Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY, USA; Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY, USA.
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Kaur H, Crawford DC, Liang J, Benchek P, Zhu X, Kallianpur AR, Bush WS. Replication of European hypertension associations in a case-control study of 9,534 African Americans. PLoS One 2021; 16:e0259962. [PMID: 34793544 PMCID: PMC8601554 DOI: 10.1371/journal.pone.0259962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 10/29/2021] [Indexed: 12/01/2022] Open
Abstract
Objective Hypertension is more prevalent in African Americans (AA) than other ethnic groups. Genome-wide association studies (GWAS) have identified loci associated with hypertension and other cardio-metabolic traits like type 2 diabetes, coronary artery disease, and body mass index (BMI), however the AA population is underrepresented in these studies. In this study, we examined a large AA cohort for the generalizability of 14 Metabochip array SNPs with previously reported European hypertension associations. Methods To evaluate associations, we analyzed genotype data of 14 SNPs for their associations with a diagnosis of hypertension, systolic blood pressure (SBP), and diastolic blood pressure (DBP) in a case-control study of an AA population (N = 9,534). We also performed an age-stratified analysis (>30, 30≥59 and ≥60 years) following the hypertension definition described by the 8th Joint National Committee (JNC). Associations were adjusted for BMI, age, age2, sex, clinical confounders, and genetic ancestry using multivariable regression models to estimate odds ratios (ORs) and beta-coefficients. Analyses stratified by sex were also conducted. Meta-analyses (including both BioVU and COGENT-BP cohorts) were performed using a random-effects model. Results We found rs880315 to be associated with systolic hypertension (SBP≥140 mmHg) in the entire cohort (OR = 1.14, p = 0.003) and within women only (OR = 1.16, p = 0.012). Variant rs17080093 associated with lower SBP and DBP (β = -2.99, p = 0.0352 and - β = 1.69, p = 0.0184) among younger individuals, particularly in younger women (β = -3.92, p = 0.0025 and β = -1.87, p = 0.0241 for SBP and DBP respectively). SNP rs1530440 associated with higher SBP and DBP measurements (younger individuals β = 4.1, p = 0.039 and β = 2.5, p = 0.043 for SBP and DBP; (younger women β = 4.5, p = 0.025 and β = 2.9, p = 0.028 for SBP and DBP), and hypertension risk in older women (OR = 1.4, p = 0.050). rs16948048 increases hypertension risk in younger individuals (OR = 1.31, p = 0.011). Among mid-age women rs880315 associated with higher risk of hypertension (OR = 1.20, p = 0.027). rs1361831 associated with DBP (β = -1.96, p = 0.02) among individuals older than 60 years. rs3096277 increases hypertension risk among older individuals (OR = 1.26 p = 0.0015), however, this variant also reduces SBP among younger women (β = -2.63, p = 0.0102). Conclusion These findings suggest that European-descent and AA populations share genetic loci that contribute to blood pressure traits and hypertension. However, the OR and beta-coefficient estimates differ, and some are age-dependent. Additional genetic studies of hypertension in AA are warranted to identify new loci associated with hypertension and blood pressure traits in this population.
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Affiliation(s)
- Harpreet Kaur
- Genomic Medicine Institute, Cleveland Clinic/Lerner Research Institute, Cleveland, OH, United States of America
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, United States of America
| | - Dana C. Crawford
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, United States of America
| | - Jingjing Liang
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, United States of America
| | - Penelope Benchek
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, United States of America
| | | | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, United States of America
| | - Asha R. Kallianpur
- Genomic Medicine Institute, Cleveland Clinic/Lerner Research Institute, Cleveland, OH, United States of America
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, United States of America
| | - William S. Bush
- Genomic Medicine Institute, Cleveland Clinic/Lerner Research Institute, Cleveland, OH, United States of America
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, United States of America
- * E-mail:
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Singh S, Brandenburg JT, Choudhury A, Gómez-Olivé FX, Ramsay M. Systematic Review of Genomic Associations with Blood Pressure and Hypertension in Populations with African-Ancestry. Front Genet 2021; 12:699445. [PMID: 34745203 PMCID: PMC8564494 DOI: 10.3389/fgene.2021.699445] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 09/10/2021] [Indexed: 11/25/2022] Open
Abstract
Background: Despite hypertension being highly prevalent in individuals with African-ancestry, they are under-represented in large genome-wide association studies. Inclusion of African participants is essential to better understand genetic associations with blood pressure-related traits in Africans. This systematic review critically evaluates existing studies with African-ancestry participants and identifies knowledge gaps. Methods: We followed the PRISMA protocol, HuGE Review handbook to identify literature on original research, in English, on genetic association studies for blood pressure-related traits (systolic and diastolic blood pressure, pulse and mean-arterial pressure, and hypertension) in populations with African-ancestry (January 2007 to April 2020). A narrative synthesis of the evidence was conducted. Results: Twelve studies with African-ancestry participants met the eligibility criteria, within which 10 studies met the additional genetic association data criteria (i.e., reporting only on African-ancestry participants). Across the five blood pressure-related traits, 26 genome-wide significantly associated SNPs were identified, with six SNPs linked to more than one trait, illustrating pleiotropic effects. Among the SNP associations, 12 had not previously been described in non-African studies. Discussion: The limited number of relevant studies highlights the dearth of genomic association studies on participants with African-ancestry, especially those located within Africa. Variations in study methodology, participant inclusion, adjustment for covariates (e.g., antihypertensive medication) and relatively small sample sizes make comparisons challenging, and have resulted in fewer significant associations, compared to large European studies. Regional variation in the prevalence and associated risk factors of hypertension across Africa makes a compelling argument to develop African cohorts to facilitate large genomic studies, using African-centric arrays. Data harmonisation and comparable study designs, such as described in the H3Africa CHAIR initiative, provide a good example toward achieving this goal. Other relevant information: SS and J-TB were funded by the South African National Research Foundation. MR is a South African Research Chair in Genomics and Bioinformatics of African populations hosted by the University of the Witwatersrand, funded by the Department of Science and Innovation, and administered by the NRF. This review was registered at PROSPERO (registration number: CRD42020179221) and OSF (registration DOI: 10.17605/OSF.IO/QT2HA).
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Affiliation(s)
- S Singh
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Division of Human Genetics, School of Pathology, National Health Laboratory Service and Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - J-T Brandenburg
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - A Choudhury
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - F X Gómez-Olivé
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - M Ramsay
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Division of Human Genetics, School of Pathology, National Health Laboratory Service and Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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34
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Wang H, Noordam R, Cade BE, Schwander K, Winkler TW, Lee J, Sung YJ, Bentley AR, Manning AK, Aschard H, Kilpeläinen TO, Ilkov M, Brown MR, Horimoto AR, Richard M, Bartz TM, Vojinovic D, Lim E, Nierenberg JL, Liu Y, Chitrala K, Rankinen T, Musani SK, Franceschini N, Rauramaa R, Alver M, Zee PC, Harris SE, van der Most PJ, Nolte IM, Munroe PB, Palmer ND, Kühnel B, Weiss S, Wen W, Hall KA, Lyytikäinen LP, O'Connell J, Eiriksdottir G, Launer LJ, de Vries PS, Arking DE, Chen H, Boerwinkle E, Krieger JE, Schreiner PJ, Sidney S, Shikany JM, Rice K, Chen YDI, Gharib SA, Bis JC, Luik AI, Ikram MA, Uitterlinden AG, Amin N, Xu H, Levy D, He J, Lohman KK, Zonderman AB, Rice TK, Sims M, Wilson G, Sofer T, Rich SS, Palmas W, Yao J, Guo X, Rotter JI, Biermasz NR, Mook-Kanamori DO, Martin LW, Barac A, Wallace RB, Gottlieb DJ, Komulainen P, Heikkinen S, Mägi R, Milani L, Metspalu A, Starr JM, Milaneschi Y, Waken RJ, Gao C, Waldenberger M, Peters A, Strauch K, Meitinger T, Roenneberg T, Völker U, Dörr M, Shu XO, Mukherjee S, Hillman DR, Kähönen M, Wagenknecht LE, Gieger C, Grabe HJ, Zheng W, Palmer LJ, Lehtimäki T, Gudnason V, Morrison AC, Pereira AC, Fornage M, Psaty BM, van Duijn CM, Liu CT, Kelly TN, Evans MK, Bouchard C, Fox ER, Kooperberg C, Zhu X, Lakka TA, Esko T, North KE, Deary IJ, Snieder H, Penninx BWJH, Gauderman WJ, Rao DC, Redline S, van Heemst D. Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure. Mol Psychiatry 2021; 26:6293-6304. [PMID: 33859359 PMCID: PMC8517040 DOI: 10.1038/s41380-021-01087-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 03/18/2021] [Accepted: 03/29/2021] [Indexed: 02/02/2023]
Abstract
Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 Pjoint < 5 × 10-8), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (Pint < 5 × 10-8). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (Pint = 2 × 10-6). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (Pint < 10-3). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.
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Affiliation(s)
- Heming Wang
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Karen Schwander
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Jiwon Lee
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Joint Carnegie Mellon University-University of Pittsburgh PhD Program in Computational Biology, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yun Ju Sung
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alisa K Manning
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hugues Aschard
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
- Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Institut Pasteur, Paris, France
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Environmental Medicine and Public Health, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Andrea R Horimoto
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, Brazil
| | - Melissa Richard
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Elise Lim
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jovia L Nierenberg
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Yongmei Liu
- Division of Cardiology, Department of Medicine, Duke Molecular Physiology Institute Duke University School of Medicine, Durham, NC, USA
| | - Kumaraswamynaidu Chitrala
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Solomon K Musani
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Rainer Rauramaa
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Maris Alver
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland
| | - Phyllis C Zee
- Division of Sleep Medicine, Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Sarah E Harris
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - 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
- National Institute for Health Research Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, London, UK
| | | | - Brigitte Kühnel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
- German Center for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Kelly A Hall
- School of Public Health, The University of Adelaide, Adelaide, SA, Australia
| | - Leo-Pekka Lyytikäinen
- 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
| | - Jeff O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Han Chen
- 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
- Center for Precision Health, School of Public Health & School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - 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
| | - Jose E Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, Brazil
| | - Pamela J Schreiner
- Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | | | - James M Shikany
- Division of Preventive Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Kenneth Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Yii-Der Ida Chen
- 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
| | - Sina A Gharib
- Computational Medicine Core, Center for Lung Biology, UW Medicine Sleep Center, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Annemarie I Luik
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Hanfei Xu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Daniel Levy
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute Framingham Heart Study, Framingham, MA, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Kurt K Lohman
- Division of Cardiology, Department of Medicine, Duke Molecular Physiology Institute Duke University School of Medicine, Durham, NC, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Treva K Rice
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Mario Sims
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Gregory Wilson
- JHS Graduate Training and Education Center, Jackson State University, Jackson, MS, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Walter Palmas
- Division of General Medicine, Department of Medicine, Columbia University, New York, NY, USA
| | - Jie Yao
- 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
| | - 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
| | - Nienke R Biermasz
- Division of Endocrinology, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Lisa W Martin
- George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Ana Barac
- MedStar Heart and Vascular Institute, Washington, DC, USA
| | - Robert B Wallace
- Department of Epidemiology, University of Iowa College of Public Health, Iowa City, IA, USA
| | - Daniel J Gottlieb
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | - Pirjo Komulainen
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Sami Heikkinen
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Finland
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - John M Starr
- Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, UK
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Neuroscience and Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit, Amsterdam, HJ, The Netherlands
| | - R J Waken
- Division of Cardiology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Chuan Gao
- Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Till Roenneberg
- Institute and Polyclinic for Occupational-, Social- and Environmental Medicine, LMU Munich, Munich, Germany
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
- German Center for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
| | - Marcus Dörr
- German Center for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Sutapa Mukherjee
- Sleep Health Service, Respiratory and Sleep Services, Southern Adelaide Local Health Network, Adelaide, SA, Australia
- Adelaide Institute for Sleep Health, Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
| | - David R Hillman
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Lynne E Wagenknecht
- Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
| | - Hans J Grabe
- Department Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Lyle J Palmer
- School of Public Health, The University of Adelaide, Adelaide, SA, Australia
| | - 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
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - 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
| | - Alexandre C Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, Brazil
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Myriam Fornage
- 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
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Cardiovascular Health Research Unit, Departments of Epidemiology and Health Services, University of Washington, Seattle, WA, USA
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Ervin R Fox
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Timo A Lakka
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Ian J Deary
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Neuroscience and Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit, Amsterdam, HJ, The Netherlands
| | - W James Gauderman
- Division of Biostatistics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Pulmonary Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands.
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Aguiar VRC, Augusto DG, Castelli EC, Hollenbach JA, Meyer D, Nunes K, Petzl-Erler ML. An immunogenetic view of COVID-19. Genet Mol Biol 2021; 44:e20210036. [PMID: 34436508 PMCID: PMC8388242 DOI: 10.1590/1678-4685-gmb-2021-0036] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 06/12/2021] [Indexed: 02/06/2023] Open
Abstract
Meeting the challenges brought by the COVID-19 pandemic requires an interdisciplinary approach. In this context, integrating knowledge of immune function with an understanding of how genetic variation influences the nature of immunity is a key challenge. Immunogenetics can help explain the heterogeneity of susceptibility and protection to the viral infection and disease progression. Here, we review the knowledge developed so far, discussing fundamental genes for triggering the innate and adaptive immune responses associated with a viral infection, especially with the SARS-CoV-2 mechanisms. We emphasize the role of the HLA and KIR genes, discussing what has been uncovered about their role in COVID-19 and addressing methodological challenges of studying these genes. Finally, we comment on questions that arise when studying admixed populations, highlighting the case of Brazil. We argue that the interplay between immunology and an understanding of genetic associations can provide an important contribution to our knowledge of COVID-19.
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Affiliation(s)
- Vitor R. C. Aguiar
- Universidade de São Paulo, Departamento de Genética e Biologia
Evolutiva, São Paulo, SP, Brazil
| | - Danillo G. Augusto
- University of California, UCSF Weill Institute for Neurosciences,
Department of Neurology, San Francisco, CA, USA
- Universidade Federal do Paraná, Departamento de Genética, Curitiba,
PR, Brazil
| | - Erick C. Castelli
- Universidade Estadual Paulista, Faculdade de Medicina de Botucatu,
Departamento de Patologia, Botucatu, SP, Brazil
| | - Jill A. Hollenbach
- University of California, UCSF Weill Institute for Neurosciences,
Department of Neurology, San Francisco, CA, USA
| | - Diogo Meyer
- Universidade de São Paulo, Departamento de Genética e Biologia
Evolutiva, São Paulo, SP, Brazil
| | - Kelly Nunes
- Universidade de São Paulo, Departamento de Genética e Biologia
Evolutiva, São Paulo, SP, Brazil
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36
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Zhu X. Mendelian randomization and pleiotropy analysis. QUANTITATIVE BIOLOGY 2021; 9:122-132. [PMID: 34386270 PMCID: PMC8356909 DOI: 10.1007/s40484-020-0216-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 05/16/2020] [Accepted: 05/21/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Mendelian randomization (MR) analysis has become popular in inferring and estimating the causality of an exposure on an outcome due to the success of genome wide association studies. Many statistical approaches have been developed and each of these methods require specific assumptions. RESULTS In this article, we review the pros and cons of these methods. We use an example of high-density lipoprotein cholesterol on coronary artery disease to illuminate the challenges in Mendelian randomization investigation. CONCLUSION The current available MR approaches allow us to study causality among risk factors and outcomes. However, novel approaches are desirable for overcoming multiple source confounding of risk factors and an outcome in MR analysis.
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Affiliation(s)
- Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
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37
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Zhu X, Li X, Xu R, Wang T. An iterative approach to detect pleiotropy and perform Mendelian Randomization analysis using GWAS summary statistics. Bioinformatics 2021; 37:1390-1400. [PMID: 33226062 DOI: 10.1093/bioinformatics/btaa985] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 11/04/2020] [Accepted: 11/11/2020] [Indexed: 01/01/2023] Open
Abstract
MOTIVATION The overall association evidence of a genetic variant with multiple traits can be evaluated by cross-phenotype association analysis using summary statistics from genome-wide association studies. Further dissecting the association pathways from a variant to multiple traits is important to understand the biological causal relationships among complex traits. RESULTS Here, we introduce a flexible and computationally efficient Iterative Mendelian Randomization and Pleiotropy (IMRP) approach to simultaneously search for horizontal pleiotropic variants and estimate causal effect. Extensive simulations and real data applications suggest that IMRP has similar or better performance than existing Mendelian Randomization methods for both causal effect estimation and pleiotropic variant detection. The developed pleiotropy test is further extended to detect colocalization for multiple variants at a locus. IMRP will greatly facilitate our understanding of causal relationships underlying complex traits, in particular, when a large number of genetic instrumental variables are used for evaluating multiple traits. AVAILABILITY AND IMPLEMENTATION The software IMRP is available at https://github.com/XiaofengZhuCase/IMRP. The simulation codes can be downloaded at http://hal.case.edu/∼xxz10/zhu-web/ under the link: MR Simulations software. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Xiaoyin Li
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Rong Xu
- Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Tao Wang
- Division of Biostatistics, Department of Epidemiology and Population Health, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY 10461, USA.,Division of Epidemiology, Department of Epidemiology and Population Health, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY 10461, USA
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38
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Sumner JA, Maihofer AX, Michopoulos V, Rothbaum AO, Almli LM, Andreassen OA, Ashley-Koch AE, Baker DG, Beckham JC, Bradley B, Breen G, Coleman JRI, Dale AM, Dennis MF, Feeny NC, Franz CE, Garrett ME, Gillespie CF, Guffanti G, Hauser MA, Hemmings SMJ, Jovanovic T, Kimbrel NA, Kremen WS, Lawford BR, Logue MW, Lori A, Lyons MJ, Maples-Keller J, Mavissakalian MR, McGlinchey RE, Mehta D, Mellor R, Milberg W, Miller MW, Morris CP, Panizzon MS, Ressler KJ, Risbrough VB, Rothbaum BO, Roy-Byrne P, Seedat S, Smith AK, Stevens JS, van den Heuvel LL, Voisey J, Young RM, Zoellner LA, Nievergelt CM, Wolf EJ. Examining Individual and Synergistic Contributions of PTSD and Genetics to Blood Pressure: A Trans-Ethnic Meta-Analysis. Front Neurosci 2021; 15:678503. [PMID: 34248484 PMCID: PMC8262489 DOI: 10.3389/fnins.2021.678503] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 05/10/2021] [Indexed: 11/13/2022] Open
Abstract
Growing research suggests that posttraumatic stress disorder (PTSD) may be a risk factor for poor cardiovascular health, and yet our understanding of who might be at greatest risk of adverse cardiovascular outcomes after trauma is limited. In this study, we conducted the first examination of the individual and synergistic contributions of PTSD symptoms and blood pressure genetics to continuous blood pressure levels. We harnessed the power of the Psychiatric Genomics Consortium-PTSD Physical Health Working Group and investigated these associations across 11 studies of 72,224 trauma-exposed individuals of European (n = 70,870) and African (n = 1,354) ancestry. Genetic contributions to blood pressure were modeled via polygenic scores (PGS) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) that were derived from a prior trans-ethnic blood pressure genome-wide association study (GWAS). Results of trans-ethnic meta-analyses revealed significant main effects of the PGS on blood pressure levels [SBP: β = 2.83, standard error (SE) = 0.06, p < 1E-20; DBP: β = 1.32, SE = 0.04, p < 1E-20]. Significant main effects of PTSD symptoms were also detected for SBP and DBP in trans-ethnic meta-analyses, though there was significant heterogeneity in these results. When including data from the largest contributing study - United Kingdom Biobank - PTSD symptoms were negatively associated with SBP levels (β = -1.46, SE = 0.44, p = 9.8E-4) and positively associated with DBP levels (β = 0.70, SE = 0.26, p = 8.1E-3). However, when excluding the United Kingdom Biobank cohort in trans-ethnic meta-analyses, there was a nominally significant positive association between PTSD symptoms and SBP levels (β = 2.81, SE = 1.13, p = 0.01); no significant association was observed for DBP (β = 0.43, SE = 0.78, p = 0.58). Blood pressure PGS did not significantly moderate the associations between PTSD symptoms and blood pressure levels in meta-analyses. Additional research is needed to better understand the extent to which PTSD is associated with high blood pressure and how genetic as well as contextual factors may play a role in influencing cardiovascular risk.
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Affiliation(s)
- Jennifer A. Sumner
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States,*Correspondence: Jennifer A. Sumner,
| | - Adam X. Maihofer
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States,Veterans Affairs San Diego Healthcare System, VA Center of Excellence for Stress and Mental Health (CESAMH), San Diego, CA, United States
| | - Vasiliki Michopoulos
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States,Yerkes National Primate Research Center, Atlanta, GA, United States
| | - Alex O. Rothbaum
- Department of Psychological Sciences, Case Western Reserve University, Cleveland, OH, United States
| | - Lynn M. Almli
- National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Ole A. Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | | | - Dewleen G. Baker
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States,Veterans Affairs San Diego Healthcare System, VA Center of Excellence for Stress and Mental Health (CESAMH), San Diego, CA, United States
| | - Jean C. Beckham
- Durham VA Health Care System, Durham, NC, United States,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States,VA Mid-Atlantic Mental Illness Research, Education, and Clinical Center (MIRECC), Genetics Research Laboratory, Durham, NC, United States
| | - Bekh Bradley
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States,Atlanta VA Health Care System, Decatur, GA, United States
| | - Gerome Breen
- Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom,NIHR BRC at the Maudsley, King’s College London, London, United Kingdom
| | - Jonathan R. I. Coleman
- Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom,NIHR BRC at the Maudsley, King’s College London, London, United Kingdom
| | - Anders M. Dale
- Department of Radiology, University of California, San Diego, San Diego, CA, United States,Department of Neurosciences, University of California, San Diego, San Diego, CA, United States
| | - Michelle F. Dennis
- Durham VA Health Care System, Durham, NC, United States,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States,VA Mid-Atlantic Mental Illness Research, Education, and Clinical Center (MIRECC), Genetics Research Laboratory, Durham, NC, United States
| | - Norah C. Feeny
- Department of Psychological Sciences, Case Western Reserve University, Cleveland, OH, United States
| | - Carol E. Franz
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
| | - Melanie E. Garrett
- Duke Molecular Physiology Institute, Duke University, Durham, NC, United States
| | - Charles F. Gillespie
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
| | - Guia Guffanti
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States,McLean Hospital, Belmont, MA, United States
| | - Michael A. Hauser
- Duke Molecular Physiology Institute, Duke University, Durham, NC, United States
| | - Sian M. J. Hemmings
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa,South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Faculty of Medicine & Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Tanja Jovanovic
- Department of Psychiatry and Behavioral Neurosciences, School of Medicine, Wayne State University, Detroit, MI, United States
| | - Nathan A. Kimbrel
- Durham VA Health Care System, Durham, NC, United States,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States,VA Mid-Atlantic Mental Illness Research, Education, and Clinical Center (MIRECC), Genetics Research Laboratory, Durham, NC, United States
| | - William S. Kremen
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States,Veterans Affairs San Diego Healthcare System, VA Center of Excellence for Stress and Mental Health (CESAMH), San Diego, CA, United States
| | - Bruce R. Lawford
- School of Biomedical Sciences, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Mark W. Logue
- National Center for PTSD, Behavioral Science Division, VA Boston Healthcare System, Boston, MA, United States,Department of Psychiatry, Boston University School of Medicine, Boston, MA, United States,Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States,Biomedical Genetics, Boston University School of Medicine, Boston, MA, United States
| | - Adriana Lori
- Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, United States
| | - Michael J. Lyons
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, United States
| | - Jessica Maples-Keller
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
| | | | | | - Divya Mehta
- Center for Genomics and Personalised Health, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Rebecca Mellor
- Gallipoli Medical Research Foundation, Greenslopes Private Hospital, Brisbane, QLD, Australia
| | - William Milberg
- GRECC/TRACTS, VA Boston Healthcare System, Boston, MA, United States
| | - Mark W. Miller
- National Center for PTSD, Behavioral Science Division, VA Boston Healthcare System, Boston, MA, United States,Department of Psychiatry, Boston University School of Medicine, Boston, MA, United States
| | - Charles Phillip Morris
- School of Biomedical Sciences, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
| | - Kerry J. Ressler
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United States,McLean Hospital, Belmont, MA, United States
| | - Victoria B. Risbrough
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States,Veterans Affairs San Diego Healthcare System, VA Center of Excellence for Stress and Mental Health (CESAMH), San Diego, CA, United States
| | - Barbara O. Rothbaum
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
| | - Peter Roy-Byrne
- Department of Psychology, University of Washington, Seattle, WA, United States
| | - Soraya Seedat
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa,South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Faculty of Medicine & Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Alicia K. Smith
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States,Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, United States
| | - Jennifer S. Stevens
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
| | - Leigh Luella van den Heuvel
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa,South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Faculty of Medicine & Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Joanne Voisey
- School of Biomedical Sciences, Queensland University of Technology, Kelvin Grove, QLD, Australia,Center for Genomics and Personalised Health, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Ross McD Young
- School of Psychology and Counseling, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Lori A. Zoellner
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | - Caroline M. Nievergelt
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States,Veterans Affairs San Diego Healthcare System, VA Center of Excellence for Stress and Mental Health (CESAMH), San Diego, CA, United States
| | - Erika J. Wolf
- National Center for PTSD, Behavioral Science Division, VA Boston Healthcare System, Boston, MA, United States,Department of Psychiatry, Boston University School of Medicine, Boston, MA, United States
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Liao C, Liu H, Luo X. The emerging roles of exosomal miRNAs in nasopharyngeal carcinoma. Am J Cancer Res 2021; 11:2508-2520. [PMID: 34249413 PMCID: PMC8263644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Accepted: 04/13/2021] [Indexed: 06/13/2023] Open
Abstract
Nasopharyngeal carcinoma (NPC) is a unique subtype of head and neck cancer that is endemic to Southern China and Southeast Asia. Due to the concealed location and intrinsic invasiveness of this disease, majority of NPC patients are diagnosed with advanced stages (III and IV) and poor prognosis. Chemoradiotherapy resistance is a major problem for NPC patients, leading to incomplete local elimination, recurrence and metastasis. Therefore, it is of great significance to seek novel biomarkers and effective therapeutic regimen for clinical management of this deadly cancer. Exosomes are tiny membrane vesicles with a lipid bilayer secreted by most cells in the body, which are widely distributed in various body fluids. They are functionally active in different physiopathological process by carrying and transmitting important signal molecules such as miRNA, mRNA, protein, lipid, etc. Exosomal miRNAs play an important role in tumorigenesis and development of NPC. They are extensively involved in NPC cell proliferation, migration, invasion, neovascularization, radiotherapy resistance and the regulation of tumor immune microenvironment through intercellular communication and control of gene expression. Moreover, exosomal miRNAs can be used as valuable biomarkers for early diagnosis and therapeutic targets of NPC.
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Affiliation(s)
- Chaoliang Liao
- Key Laboratory of Carcinogenesis and Invasion, Chinese Ministry of Education, Department of Radiology, Xiangya Hospital, Central South UniversityChangsha 410078, Hunan, PR China
- Cancer Research Institute, School of Basic Medicine, Central South UniversityChangsha 410078, Hunan, PR China
- Key Laboratory of Carcinogenesis, Chinese Ministry of HealthChangsha 410078, Hunan, PR China
| | - Huiwen Liu
- Key Laboratory of Carcinogenesis and Invasion, Chinese Ministry of Education, Department of Radiology, Xiangya Hospital, Central South UniversityChangsha 410078, Hunan, PR China
- Cancer Research Institute, School of Basic Medicine, Central South UniversityChangsha 410078, Hunan, PR China
- Key Laboratory of Carcinogenesis, Chinese Ministry of HealthChangsha 410078, Hunan, PR China
| | - Xiangjian Luo
- Key Laboratory of Carcinogenesis and Invasion, Chinese Ministry of Education, Department of Radiology, Xiangya Hospital, Central South UniversityChangsha 410078, Hunan, PR China
- Cancer Research Institute, School of Basic Medicine, Central South UniversityChangsha 410078, Hunan, PR China
- Key Laboratory of Carcinogenesis, Chinese Ministry of HealthChangsha 410078, Hunan, PR China
- Molecular Imaging Research Center of Central South UniversityChangsha 410078, Hunan, PR China
- Hunan Key Laboratory of Oncotarget Gene, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South UniversityChangsha 410078, Hunan, China
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40
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African genetic diversity and adaptation inform a precision medicine agenda. Nat Rev Genet 2021; 22:284-306. [PMID: 33432191 DOI: 10.1038/s41576-020-00306-8] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/02/2020] [Indexed: 01/29/2023]
Abstract
The deep evolutionary history of African populations, since the emergence of modern humans more than 300,000 years ago, has resulted in high genetic diversity and considerable population structure. Selected genetic variants have increased in frequency due to environmental adaptation, but recent exposures to novel pathogens and changes in lifestyle render some of them with properties leading to present health liabilities. The unique discoverability potential from African genomic studies promises invaluable contributions to understanding the genomic and molecular basis of health and disease. Globally, African populations are understudied, and precision medicine approaches are largely based on data from European and Asian-ancestry populations, which limits the transferability of findings to the continent of Africa. Africa needs innovative precision medicine solutions based on African data that use knowledge and implementation strategies aligned to its climatic, cultural, economic and genomic diversity.
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41
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Mabhida SE, Mashatola L, Kaur M, Sharma JR, Apalata T, Muhamed B, Benjeddou M, Johnson R. Hypertension in African Populations: Review and Computational Insights. Genes (Basel) 2021; 12:genes12040532. [PMID: 33917487 PMCID: PMC8067483 DOI: 10.3390/genes12040532] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 03/17/2021] [Accepted: 03/18/2021] [Indexed: 01/11/2023] Open
Abstract
Hypertension (HTN) is a persistent public health problem affecting approximately 1.3 billion individuals globally. Treatment-resistant hypertension (TRH) is defined as high blood pressure (BP) in a hypertensive patient that remains above goal despite use of ≥3 antihypertensive agents of different classes including a diuretic. Despite a plethora of treatment options available, only 31.0% of individuals have their HTN controlled. Interindividual genetic variability to drug response might explain this disappointing outcome because of genetic polymorphisms. Additionally, the poor knowledge of pathophysiological mechanisms underlying hypertensive disease and the long-term interaction of antihypertensive drugs with blood pressure control mechanisms further aggravates the problem. Furthermore, in Africa, there is a paucity of pharmacogenomic data on the treatment of resistant hypertension. Therefore, identification of genetic signals having the potential to predict the response of a drug for a given individual in an African population has been the subject of intensive investigation. In this review, we aim to systematically extract and discuss African evidence on the genetic variation, and pharmacogenomics towards the treatment of HTN. Furthermore, in silico methods are utilized to elucidate biological processes that will aid in identifying novel drug targets for the treatment of resistant hypertension in an African population. To provide an expanded view of genetic variants associated with the development of HTN, this study was performed using publicly available databases such as PubMed, Scopus, Web of Science, African Journal Online, PharmGKB searching for relevant papers between 1984 and 2020. A total of 2784 articles were reviewed, and only 42 studies were included following the inclusion criteria. Twenty studies reported associations with HTN and genes such as AGT (rs699), ACE (rs1799752), NOS3 (rs1799983), MTHFR (rs1801133), AGTR1 (rs5186), while twenty-two studies did not show any association within the African population. Thereafter, an in silico predictive approach was utilized to identify several genes including CLCNKB, CYPB11B2, SH2B2, STK9, and TBX5 which may act as potential drug targets because they are involved in pathways known to influence blood pressure. Next, co-expressed genes were identified as they are controlled by the same transcriptional regulatory program and may potentially be more effective as multiple drug targets in the treatment regimens for HTN. Genes belonging to the co-expressed gene cluster, ACE, AGT, AGTR1, AGTR2, and NOS3 as well as CSK and ADRG1 showed enrichment of G-protein-coupled receptor activity, the classical targets of drug discovery, which mediate cellular signaling processes. The latter is of importance, as the targeting of co-regulatory gene clusters will allow for the development of more effective HTN drug targets that could decrease the prevalence of both controlled and TRH.
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Affiliation(s)
- Sihle E. Mabhida
- Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg 7505, South Africa; (S.E.M.); (J.R.S.)
- Department of Biotechnology, Faculty of Natural Science, University of the Western Cape, Private Bag X17, Bellville, Cape Town 7535, South Africa;
| | - Lebohang Mashatola
- School of Molecular and Cell Biology, University of the Witwatersrand, Private Bag 3, Johannesburg 2050, South Africa; (L.M.); (M.K.)
| | - Mandeep Kaur
- School of Molecular and Cell Biology, University of the Witwatersrand, Private Bag 3, Johannesburg 2050, South Africa; (L.M.); (M.K.)
| | - Jyoti R. Sharma
- Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg 7505, South Africa; (S.E.M.); (J.R.S.)
| | - Teke Apalata
- Division of Medical Microbiology, Department of Laboratory-Medicine and Pathology, Faculty of Health Sciences, Walter Sisulu University and National Health Laboratory Services, Mthatha 5100, South Africa;
| | - Babu Muhamed
- Hatter Institute for Cardiovascular Diseases Research in Africa, Department of Medicine, University of Cape Town, Cape Town 7535, South Africa;
- Children’s National Health System, Division of Cardiology, Washington, DC 20010, USA
| | - Mongi Benjeddou
- Department of Biotechnology, Faculty of Natural Science, University of the Western Cape, Private Bag X17, Bellville, Cape Town 7535, South Africa;
| | - Rabia Johnson
- Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg 7505, South Africa; (S.E.M.); (J.R.S.)
- Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg 7505, South Africa
- Correspondence: ; Tel.: +27-21-938-0866
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Gouveia MH, Bentley AR, Leonard H, Meeks KAC, Ekoru K, Chen G, Nalls MA, Simonsick EM, Tarazona-Santos E, Lima-Costa MF, Adeyemo A, Shriner D, Rotimi CN. Trans-ethnic meta-analysis identifies new loci associated with longitudinal blood pressure traits. Sci Rep 2021; 11:4075. [PMID: 33603002 PMCID: PMC7893038 DOI: 10.1038/s41598-021-83450-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 01/25/2021] [Indexed: 01/09/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified thousands of genetic loci associated with cross-sectional blood pressure (BP) traits; however, GWAS based on longitudinal BP have been underexplored. We performed ethnic-specific and trans-ethnic GWAS meta-analysis using longitudinal and cross-sectional BP data of 33,720 individuals from five cohorts in the US and one in Brazil. In addition to identifying several known loci, we identified thirteen novel loci with nine based on longitudinal and four on cross-sectional BP traits. Most of the novel loci were ethnic- or study-specific, with the majority identified in African Americans (AA). Four of these discoveries showed additional evidence of association in independent datasets, including an intergenic variant (rs4060030, p = 7.3 × 10–9) with reported regulatory function. We observed a high correlation between the meta-analysis results for baseline and longitudinal average BP (rho = 0.48). BP trajectory results were more correlated with those of average BP (rho = 0.35) than baseline BP(rho = 0.18). Heritability estimates trended higher for longitudinal traits than for cross-sectional traits, providing evidence for different genetic architectures. Furthermore, the longitudinal data identified up to 20% more BP known associations than did cross-sectional data. Our analyses of longitudinal BP data in diverse ethnic groups identified novel BP loci associated with BP trajectory, indicating a need for further longitudinal GWAS on BP and other age-related traits.
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Affiliation(s)
- Mateus H Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Hampton Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA.,Data Tecnica International, Glen Echo, MD, 20812, USA
| | - Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Kenneth Ekoru
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Michael A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA.,Data Tecnica International, Glen Echo, MD, 20812, USA
| | - Eleanor M Simonsick
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Eduardo Tarazona-Santos
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil
| | | | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA. .,Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Building 12A/Room 4047, Bethesda, MD, 20814, USA.
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA. .,Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Building 12A/Room 4047, Bethesda, MD, 20814, USA.
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43
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Saleem M, Barturen‐Larrea P, Gomez JA. Emerging roles of Sox6 in the renal and cardiovascular system. Physiol Rep 2020; 8:e14604. [PMID: 33230925 PMCID: PMC7683808 DOI: 10.14814/phy2.14604] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 09/16/2020] [Accepted: 09/17/2020] [Indexed: 12/15/2022] Open
Abstract
The function of Sex-determining Region Y (SRY)-related high-mobility-group box (Sox) family of transcription factors in cell fate decisions during embryonic development are well-established. Accumulating evidence indicates that the Sox family of transcription factors are fundamental in adult tissue homeostasis, regeneration, and physiology. The SoxD subfamily of genes are expressed in various cell types of different organs during embryogenesis and adulthood and have been involved in cell-fate determination, cellular proliferation and survival, differentiation, and terminal maturation in a number of cell lineages. The dysregulation in the function of SoxD proteins (i.e. Sox5, Sox6, Sox13, and Sox23) have been implicated in different disease conditions such as chondrodysplasia, cancer, diabetes, hypertension, autoimmune diseases, osteoarthritis among others. In this minireview, we present recent developments related to the transcription factor Sox6, which is involved in a number of diseases such as diabetic nephropathy, adipogenesis, cardiomyopathy, inflammatory bowel disease, and cancer. Sox6 has been implicated in the regulation of renin expression and JG cell recruitment in mice during sodium depletion and dehydration. We provide a current perspective of Sox6 research developments in last five years, and the implications of Sox6 functions in cardiovascular physiology and disease conditions.
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Affiliation(s)
- Mohammad Saleem
- Department of Medicine / Clinical Pharmacology DivisionVanderbilt University Medical CenterNashvilleTNUSA
| | - Pierina Barturen‐Larrea
- Department of Medicine / Clinical Pharmacology DivisionVanderbilt University Medical CenterNashvilleTNUSA
| | - Jose A. Gomez
- Department of Medicine / Clinical Pharmacology DivisionVanderbilt University Medical CenterNashvilleTNUSA
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44
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Gray KJ, Kovacheva VP, Mirzakhani H, Bjonnes AC, Almoguera B, Wilson ML, Ingles SA, Lockwood CJ, Hakonarson H, McElrath TF, Murray JC, Norwitz ER, Karumanchi SA, Bateman BT, Keating BJ, Saxena R. Risk of pre-eclampsia in patients with a maternal genetic predisposition to common medical conditions: a case-control study. BJOG 2020; 128:55-65. [PMID: 32741103 DOI: 10.1111/1471-0528.16441] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2020] [Indexed: 12/17/2022]
Abstract
OBJECTIVE To assess whether women with a genetic predisposition to medical conditions known to increase pre-eclampsia risk have an increased risk of pre-eclampsia in pregnancy. DESIGN Case-control study. SETTING AND POPULATION Pre-eclampsia cases (n = 498) and controls (n = 1864) in women of European ancestry from five US sites genotyped on a cardiovascular gene-centric array. METHODS Significant single-nucleotide polymorphisms (SNPs) from 21 traits in seven disease categories (cardiovascular, inflammatory/autoimmune, insulin resistance, liver, obesity, renal and thrombophilia) with published genome-wide association studies (GWAS) were used to create a genetic instrument for each trait. Multivariable logistic regression was used to test the association of each continuous scaled genetic instrument with pre-eclampsia. Odds of pre-eclampsia were compared across quartiles of the genetic instrument and evaluated for significance. MAIN OUTCOME MEASURES Genetic predisposition to medical conditions and relationship with pre-eclampsia. RESULTS An increasing burden of risk alleles for elevated diastolic blood pressure (DBP) and increased body mass index (BMI) were associated with an increased risk of pre-eclampsia (DBP, overall OR 1.11, 95% CI 1.01-1.21, P = 0.025; BMI, OR 1.10, 95% CI 1.00-1.20, P = 0.042), whereas alleles associated with elevated alkaline phosphatase (ALP) were protective (OR 0.89, 95% CI 0.82-0.97, P = 0.008), driven primarily by pleiotropic effects of variants in the FADS gene region. The effect of DBP genetic loci was even greater in early-onset pre-eclampsia cases (at <34 weeks of gestation, OR 1.30, 95% CI 1.08-1.56, P = 0.005). For other traits, there was no evidence of an association. CONCLUSIONS These results suggest that the underlying genetic architecture of pre-eclampsia may be shared with other disorders, specifically hypertension and obesity. TWEETABLE ABSTRACT A genetic predisposition to increased diastolic blood pressure and obesity increases the risk of pre-eclampsia.
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Affiliation(s)
- K J Gray
- Division of Maternal-Fetal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - V P Kovacheva
- Department of Anesthesiology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - H Mirzakhani
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - A C Bjonnes
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - B Almoguera
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - M L Wilson
- Department of Preventative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - S A Ingles
- Department of Preventative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - C J Lockwood
- Morsani College of Medicine, University of South Florida, Tampa, Florida, USA
| | - H Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Pediatrics, Divisions of Human Genetics and Pulmonary Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - T F McElrath
- Division of Maternal-Fetal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - J C Murray
- Department of Pediatrics, Carver College of Medicine, University of Iowa, Iowa City, Iowa, USA
| | - E R Norwitz
- Department of Obstetrics & Gynecology, Tufts Medical Center, Boston, Massachusetts, USA
| | - S A Karumanchi
- Center for Vascular Biology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.,Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - B T Bateman
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - B J Keating
- Department of Surgery and Pediatrics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - R Saxena
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
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45
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Joseph JJ, Zhou X, Zilbermint M, Stratakis CA, Faucz FR, Lodish MB, Berthon A, Wilson JG, Hsueh WA, Golden SH, Lin S. The Association of ARMC5 with the Renin-Angiotensin-Aldosterone System, Blood Pressure, and Glycemia in African Americans. J Clin Endocrinol Metab 2020; 105:5841631. [PMID: 32436940 PMCID: PMC7308077 DOI: 10.1210/clinem/dgaa290] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Accepted: 05/18/2020] [Indexed: 12/31/2022]
Abstract
CONTEXT Armadillo repeat containing 5 (ARMC5) on chromosome 16 is an adrenal gland tumor suppressor gene associated with primary aldosteronism, especially among African Americans (AAs). We examined the association of ARMC5 variants with aldosterone, plasma renin activity (PRA), blood pressure, glucose, and glycosylated hemoglobin A1c (HbA1c) in community-dwelling AAs. METHODS The Jackson Heart Study is a prospective cardiovascular cohort study in AAs with baseline data collection from 2000 to 2004. Kernel machine method was used to perform a single joint test to analyze for an overall association between the phenotypes of interest (aldosterone, PRA, systolic and diastolic blood pressure [SBP, DBP], glucose, and HbA1c) and the ARMC5 single nucleotide variants (SNVs) adjusted for age, sex, BMI, and medications; followed by Baysian Lasso methodology to identify sets of SNVs in terms of associated haplotypes with specific phenotypes. RESULTS Among 3223 participants (62% female; mean age 55.6 (SD ± 12.8) years), the average SBP and DBP were 127 and 76 mmHg, respectively. The average fasting plasma glucose and HbA1c were 101 mg/dL and 6.0%, respectively. ARMC5 variants were associated with all 6 phenotypes. Haplotype TCGCC (ch16:31476015-31476093) was negatively associated, whereas haplotype CCCCTTGCG (ch16:31477195-31477460) was positively associated with SBP, DBP, and glucose. Haplotypes GGACG (ch16:31477790-31478013) and ACGCG (ch16:31477834-31478113) were negatively associated with aldosterone and positively associated with HbA1c and glucose, respectively. Haplotype GCGCGAGC (ch16:31471193-ch16:31473597(rs114871627) was positively associated with PRA and negatively associated with HbA1c. CONCLUSIONS ARMC5 variants are associated with aldosterone, PRA, blood pressure, fasting glucose, and HbA1c in community-dwelling AAs, suggesting that germline mutations in ARMC5 may underlie cardiometabolic disease in AAs.
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Affiliation(s)
- Joshua J Joseph
- The Ohio State University, Columbus, Ohio
- Correspondence and Reprint Requests: Joshua J. Joseph, MD, Department of Medicine, The Ohio State University Wexner Medical Center, 566 McCampbell Hall, 1581 Dodd Drive, Columbus, OH 43210; Phone: 614-346-8878; Fax: 614-366-0345;
| | | | - Mihail Zilbermint
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Section on Endocrinology and Genetics, The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
- Johns Hopkins Community Physicians at Suburban Hospital, Bethesda, Maryland
| | - Constantine A Stratakis
- Section on Endocrinology and Genetics, The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Fabio R Faucz
- Section on Endocrinology and Genetics, The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Maya B Lodish
- Division of Pediatric Endocrinology and Diabetes, University of California, San Francisco, San Francisco, California
| | - Annabel Berthon
- Institut Cochin, Centre National de la Recherche Scientifique (CNRS), INSERM, Université Paris Descartes, Paris, France
| | - James G Wilson
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
- Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | | | - Sherita H Golden
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Shili Lin
- The Ohio State University, Columbus, Ohio
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46
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Liu X, Mao Z, Li Y, Wu W, Zhang X, Huo W, Yu S, Shen L, Li L, Tu R, Wu H, Li H, He M, Liu L, Wei S, Li W, Wu T, Wang C. Cohort Profile: The Henan Rural Cohort: a prospective study of chronic non-communicable diseases. Int J Epidemiol 2020; 48:1756-1756j. [PMID: 30915440 DOI: 10.1093/ije/dyz039] [Citation(s) in RCA: 180] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Accepted: 03/02/2019] [Indexed: 01/19/2023] Open
Affiliation(s)
- Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Yuqian Li
- Department of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, Zhengzhou, Henan, China
| | - Weidong Wu
- Department of Occupational and Environmental Health, School of Public Health, Xinxiang Medical University, Xinxiang, Henan, China
| | - Xiaomin Zhang
- MOE Key Lab of Environment and Health, School of Public Health, Huazhong University of Science & Technology, Wuhan, Hubei, China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Songcheng Yu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Lijun Shen
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Linlin Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Runqi Tu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Hui Wu
- Department of Occupational and Environmental Health, School of Public Health, Xinxiang Medical University, Xinxiang, Henan, China
| | - Haibin Li
- Department of Occupational and Environmental Health, School of Public Health, Xinxiang Medical University, Xinxiang, Henan, China
| | - Meian He
- MOE Key Lab of Environment and Health, School of Public Health, Huazhong University of Science & Technology, Wuhan, Hubei, China
| | - Li Liu
- MOE Key Lab of Environment and Health, School of Public Health, Huazhong University of Science & Technology, Wuhan, Hubei, China
| | - Sheng Wei
- MOE Key Lab of Environment and Health, School of Public Health, Huazhong University of Science & Technology, Wuhan, Hubei, China
| | - Wenjie Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Tangchun Wu
- MOE Key Lab of Environment and Health, School of Public Health, Huazhong University of Science & Technology, Wuhan, Hubei, China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
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47
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Shi H, Burch KS, Johnson R, Freund MK, Kichaev G, Mancuso N, Manuel AM, Dong N, Pasaniuc B. Localizing Components of Shared Transethnic Genetic Architecture of Complex Traits from GWAS Summary Data. Am J Hum Genet 2020; 106:805-817. [PMID: 32442408 PMCID: PMC7273527 DOI: 10.1016/j.ajhg.2020.04.012] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 04/20/2020] [Indexed: 12/19/2022] Open
Abstract
Despite strong transethnic genetic correlations reported in the literature for many complex traits, the non-transferability of polygenic risk scores across populations suggests the presence of population-specific components of genetic architecture. We propose an approach that models GWAS summary data for one trait in two populations to estimate genome-wide proportions of population-specific/shared causal SNPs. In simulations across various genetic architectures, we show that our approach yields approximately unbiased estimates with in-sample LD and slight upward-bias with out-of-sample LD. We analyze nine complex traits in individuals of East Asian and European ancestry, restricting to common SNPs (MAF > 5%), and find that most common causal SNPs are shared by both populations. Using the genome-wide estimates as priors in an empirical Bayes framework, we perform fine-mapping and observe that high-posterior SNPs (for both the population-specific and shared causal configurations) have highly correlated effects in East Asians and Europeans. In population-specific GWAS risk regions, we observe a 2.8× enrichment of shared high-posterior SNPs, suggesting that population-specific GWAS risk regions harbor shared causal SNPs that are undetected in the other GWASs due to differences in LD, allele frequencies, and/or sample size. Finally, we report enrichments of shared high-posterior SNPs in 53 tissue-specific functional categories and find evidence that SNP-heritability enrichments are driven largely by many low-effect common SNPs.
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Affiliation(s)
- Huwenbo Shi
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Kathryn S Burch
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Ruth Johnson
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Malika K Freund
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Gleb Kichaev
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Astrid M Manuel
- Department of Biological Sciences, Florida International University, Miami, FL 33199, USA
| | - Natalie Dong
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
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48
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Genes dysregulated in the blood of people with Williams syndrome are enriched in protein-coding genes positively selected in humans. Eur J Med Genet 2020; 63:103828. [DOI: 10.1016/j.ejmg.2019.103828] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 11/09/2019] [Accepted: 12/21/2019] [Indexed: 12/29/2022]
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49
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Bueno CT, Pereira AC, Santos HC, Gómez LMG, Horimoto ARVR, Krieger EM, Krieger JE, Santos PCJL. Association of the genetic ancestry with resistant hypertension in the ReHOT (Resistant Hypertension Optimal Treatment) randomized study. Sci Rep 2020; 10:1476. [PMID: 32001805 PMCID: PMC6992613 DOI: 10.1038/s41598-020-58540-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 01/15/2020] [Indexed: 11/09/2022] Open
Abstract
Resistant hypertension (RH) is defined as uncontrolled blood pressure despite treatment with three or more antihypertensive medications, including, if tolerated, a diuretic in adequate doses. It has been widely known that race is associated with blood pressure control. However, intense debate persists as to whether this is solely explained by unadjusted socioeconomical variables or genetic variation. In this scenario, the main aim was to evaluate the association between genetic ancestry and resistant hypertension in a large sample from a multicenter trial of stage II hypertension, the ReHOT study. Samples from 1,358 patients were analyzed, of which 167 were defined as resistant hypertensive. Genetic ancestry was defined using a panel of 192 polymorphic markers. The genetic ancestry was similar in resistant (52.0% European, 36.7% African and 11.3% Amerindian) and nonresistant hypertensive patients (54.0% European, 34.4% African and 11.6% Amerindian) (p > 0.05). However, we observed a statistically suggestive association of African ancestry with resistant hypertension in brown patient group. In conclusion, increased African genetic ancestry was not associated with RH in Brazilian patients from a prospective randomized hypertension clinical trial.
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Affiliation(s)
- Carolina Tosin Bueno
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Alexandre Costa Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Hadassa Campos Santos
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Luz Marina Gómez Gómez
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, São Paulo, Brazil
| | | | - Eduardo Moacyr Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Jose Eduardo Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Paulo Caleb Junior Lima Santos
- Department of Pharmacology - Escola Paulista de Medicina, Universidade Federal de Sao Paulo EPM-Unifesp, São Paulo, Brazil.
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50
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Guo J, Zhong J, Li L, Zhong T, Wang L, Song T, Zhang H. Comparative genome analyses reveal the unique genetic composition and selection signals underlying the phenotypic characteristics of three Chinese domestic goat breeds. Genet Sel Evol 2019; 51:70. [PMID: 31771503 PMCID: PMC6880376 DOI: 10.1186/s12711-019-0512-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 11/15/2019] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND As one of the important livestock species around the world, goats provide abundant meat, milk, and fiber to fulfill basic human needs. However, the genetic loci that underlie phenotypic variations in domestic goats are largely unknown, particularly for economically important traits. In this study, we sequenced the whole genome of 38 goats from three Chinese breeds (Chengdu Brown, Jintang Black, and Tibetan Cashmere) and downloaded the genome sequence data of 30 goats from five other breeds (four non-Chinese and one Chinese breed) and 21 Bezoar ibexes to investigate the genetic composition and selection signatures of the Chinese goat breeds after domestication. RESULTS Based on population structure analysis and FST values (average FST = 0.22), the genetic composition of Chengdu Brown goats differs considerably from that of Bezoar ibexes as a result of geographic isolation. Strikingly, the genes under selection that we identified in Tibetan Cashmere goats were significantly enriched in the categories hair growth and bone and nervous system development, possibly because they are involved in adaptation to high-altitude. In particular, we found a large difference in allele frequency of one novel SNP (c.-253G>A) in the 5'-UTR of FGF5 between Cashmere goats and goat breeds with short hair. The mutation at this site introduces a start codon that results in the occurrence of a premature FGF5 protein and is likely a natural causal variant that is involved in the long hair phenotype of cashmere goats. The haplotype tagged with the AGG-allele in exon 12 of DSG3, which encodes a cell adhesion molecule that is expressed mainly in the skin, was almost fixed in Tibetan Cashmere goats, whereas this locus still segregates in the lowland goat breeds. The pigmentation gene KITLG showed a strong signature of selection in Tibetan Cashmere goats. The genes ASIP and LCORL were identified as being under positive selection in Jintang Black goats. CONCLUSIONS After domestication, geographic isolation of some goat breeds has resulted in distinct genetic structures. Furthermore, our work highlights several positively selected genes that likely contributed to breed-related traits in domestic goats.
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Affiliation(s)
- Jiazhong Guo
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Jie Zhong
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Li Li
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Tao Zhong
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Linjie Wang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Tianzeng Song
- Institute of Animal Science, Tibet Academy of Agricultural and Animal Husbandry Sciences, Lhasa, 850009 China
| | - Hongping Zhang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
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