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Grilo LF, Zimmerman KD, Puppala S, Chan J, Huber HF, Li G, Jadhav AYL, Wang B, Li C, Clarke GD, Register TC, Oliveira PJ, Nathanielsz PW, Olivier M, Pereira SP, Cox LA. Cardiac Molecular Analysis Reveals Aging-Associated Metabolic Alterations Promoting Glycosaminoglycans Accumulation via Hexosamine Biosynthetic Pathway. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2309211. [PMID: 39119859 DOI: 10.1002/advs.202309211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 07/17/2024] [Indexed: 08/10/2024]
Abstract
Age is a prominent risk factor for cardiometabolic disease, often leading to heart structural and functional changes. However, precise molecular mechanisms underlying cardiac remodeling and dysfunction exclusively resulting from physiological aging remain elusive. Previous research demonstrated age-related functional alterations in baboons, analogous to humans. The goal of this study is to identify early cardiac molecular alterations preceding functional adaptations, shedding light on the regulation of age-associated changes. Unbiased transcriptomics of left ventricle samples are performed from female baboons aged 7.5-22.1 years (human equivalent ≈30-88 years). Weighted-gene correlation network and pathway enrichment analyses are performed, with histological validation. Modules of transcripts negatively correlated with age implicated declined metabolism-oxidative phosphorylation, tricarboxylic acid cycle, glycolysis, and fatty-acid β-oxidation. Transcripts positively correlated with age suggested a metabolic shift toward glucose-dependent anabolic pathways, including hexosamine biosynthetic pathway (HBP). This shift is associated with increased glycosaminoglycan synthesis, modification, precursor synthesis via HBP, and extracellular matrix accumulation, verified histologically. Upregulated extracellular matrix-induced signaling coincided with glycosaminoglycan accumulation, followed by cardiac hypertrophy-related pathways. Overall, these findings revealed a transcriptional shift in metabolism favoring glycosaminoglycan accumulation through HBP before cardiac hypertrophy. Unveiling this metabolic shift provides potential targets for age-related cardiac diseases, offering novel insights into early age-related mechanisms.
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Affiliation(s)
- Luís F Grilo
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, 3060, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, 3060, Portugal
- Institute for Interdisciplinary Research, PDBEB - Doctoral Programme in Experimental Biology and Biomedicine, University of Coimbra, Coimbra, 3060, Portugal
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
| | - Kip D Zimmerman
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Sobha Puppala
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Jeannie Chan
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Hillary F Huber
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, 78245, USA
| | - Ge Li
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
| | - Avinash Y L Jadhav
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
| | - Benlian Wang
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
| | - Cun Li
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, WY, 82071, USA
| | - Geoffrey D Clarke
- Department of Radiology, University of Texas Health Science Center, San Antonio, TX, 78229, USA
| | - Thomas C Register
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Paulo J Oliveira
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, 3060, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, 3060, Portugal
| | - Peter W Nathanielsz
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, WY, 82071, USA
| | - Michael Olivier
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Susana P Pereira
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, 3060, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, 3060, Portugal
- Laboratory of Metabolism and Exercise (LaMetEx), Research Centre in Physical Activity, Health and Leisure (CIAFEL), Laboratory for Integrative and Translational Research in Population Health (ITR), Faculty of Sports, University of Porto, Porto, 4050, Portugal
| | - Laura A Cox
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, 78245, USA
- Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
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2
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Venkatesh SS, Ganjgahi H, Palmer DS, Coley K, Linchangco GV, Hui Q, Wilson P, Ho YL, Cho K, Arumäe K, Wittemans LBL, Nellåker C, Vainik U, Sun YV, Holmes C, Lindgren CM, Nicholson G. Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records. Nat Commun 2024; 15:5801. [PMID: 38987242 PMCID: PMC11237142 DOI: 10.1038/s41467-024-49998-0] [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: 01/25/2023] [Accepted: 06/25/2024] [Indexed: 07/12/2024] Open
Abstract
Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood.
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Affiliation(s)
- Samvida S Venkatesh
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
| | - Habib Ganjgahi
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Duncan S Palmer
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Kayesha Coley
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Gregorio V Linchangco
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Qin Hui
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Peter Wilson
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Veterans Affairs Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kadri Arumäe
- Institute of Psychology, Faculty of Social Sciences, University of Tartu, Tartu, Estonia
| | - Laura B L Wittemans
- Novo Nordisk Research Centre Oxford, Oxford, UK
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Christoffer Nellåker
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Uku Vainik
- Institute of Psychology, Faculty of Social Sciences, University of Tartu, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, Faculty of Science and Technology, University of Tartu, Tartu, Estonia
- Department of Neurology and Neurosurgery, Faculty of Medicine and Health Sciences, University of McGill, Montreal, Canada
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Chris Holmes
- Department of Statistics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, Medical Sciences Division, University of Oxford, Oxford, UK
- The Alan Turing Institute, London, UK
| | - Cecilia M Lindgren
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK.
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
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3
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Grilo LF, Zimmerman KD, Puppala S, Chan J, Huber HF, Li G, Jadhav AYL, Wang B, Li C, Clarke GD, Register TC, Oliveira PJ, Nathanielsz PW, Olivier M, Pereira SP, Cox LA. Cardiac Molecular Analysis Reveals Aging-Associated Metabolic Alterations Promoting Glycosaminoglycans Accumulation Via Hexosamine Biosynthetic Pathway. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.17.567640. [PMID: 38014295 PMCID: PMC10680868 DOI: 10.1101/2023.11.17.567640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Age is a prominent risk factor for cardiometabolic disease, and often leads to heart structural and functional changes. However, precise molecular mechanisms underlying cardiac remodeling and dysfunction resulting from physiological aging per se remain elusive. Understanding these mechanisms requires biological models with optimal translation to humans. Previous research demonstrated that baboons undergo age-related reduction in ejection fraction and increased heart sphericity, mirroring changes observed in humans. The goal of this study was to identify early cardiac molecular alterations that precede functional adaptations, shedding light on the regulation of age-associated changes. We performed unbiased transcriptomics of left ventricle (LV) samples from female baboons aged 7.5-22.1 years (human equivalent ~30-88 years). Weighted-gene correlation network and pathway enrichment analyses were performed to identify potential age-associated mechanisms in LV, with histological validation. Myocardial modules of transcripts negatively associated with age were primarily enriched for cardiac metabolism, including oxidative phosphorylation, tricarboxylic acid cycle, glycolysis, and fatty-acid β-oxidation. Transcripts positively correlated with age suggest upregulation of glucose uptake, pentose phosphate pathway, and hexosamine biosynthetic pathway (HBP), indicating a metabolic shift towards glucose-dependent anabolic pathways. Upregulation of HBP commonly results in increased glycosaminoglycan precursor synthesis. Transcripts involved in glycosaminoglycan synthesis, modification, and intermediate metabolism were also upregulated in older animals, while glycosaminoglycan degradation transcripts were downregulated with age. These alterations would promote glycosaminoglycan accumulation, which was verified histologically. Upregulation of extracellular matrix (ECM)-induced signaling pathways temporally coincided with glycosaminoglycan accumulation. We found a subsequent upregulation of cardiac hypertrophy-related pathways and an increase in cardiomyocyte width. Overall, our findings revealed a transcriptional shift in metabolism from catabolic to anabolic pathways that leads to ECM glycosaminoglycan accumulation through HBP prior to upregulation of transcripts of cardiac hypertrophy-related pathways. This study illuminates cellular mechanisms that precede development of cardiac hypertrophy, providing novel potential targets to remediate age-related cardiac diseases.
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Affiliation(s)
- Luís F. Grilo
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Portugal
- University of Coimbra, Institute for Interdisciplinary Research, PDBEB - Doctoral Programme in Experimental Biology and Biomedicine
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Kip D. Zimmerman
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Sobha Puppala
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Jeannie Chan
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Hillary F. Huber
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Ge Li
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Avinash Y. L. Jadhav
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Benlian Wang
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Cun Li
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, Wyoming, USA
| | - Geoffrey D. Clarke
- Department of Radiology, University of Texas Health Science Center, San Antonio, Texas
| | - Thomas C. Register
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Paulo J. Oliveira
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Portugal
| | - Peter W. Nathanielsz
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, Wyoming, USA
| | - Michael Olivier
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Susana P. Pereira
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Portugal
- Laboratory of Metabolism and Exercise (LaMetEx), Research Centre in Physical Activity, Health and Leisure (CIAFEL), Laboratory for Integrative and Translational Research in Population Health (ITR), Faculty of Sports, University of Porto, Porto, Portugal
| | - Laura A. Cox
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
- Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
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4
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He D, Liu H, Wei W, Zhao Y, Cai Q, Shi S, Chu X, Qin X, Zhang N, Xu P, Zhang F. A longitudinal genome-wide association study of bone mineral density mean and variability in the UK Biobank. Osteoporos Int 2023; 34:1907-1916. [PMID: 37500982 DOI: 10.1007/s00198-023-06852-1] [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: 03/02/2023] [Accepted: 07/06/2023] [Indexed: 07/29/2023]
Abstract
Bone mineral density (BMD) is an essential predictor of osteoporosis and fracture. We conducted a genome-wide trajectory analysis of BMD and analyzed the BMD change. PURPOSE This study aimed to identify the genetic architecture and potential biomarkers of BMD. METHODS Our analysis included 141,261 white participants from the UK Biobank with heel BMD phenotype data. We used a genome-wide trajectory analysis tool, TrajGWAS, to conduct a genome-wide association study (GWAS) of BMD. Then, we validated our findings in previously reported BMD genetic associations and performed replication analysis in the Asian participants. Finally, gene-set enrichment analysis (GSEA) of the identified candidate genes was conducted using the FUMA platform. RESULTS A total of 52 genes associated with BMD trajectory mean were identified, of which the top three significant genes were WNT16 (P = 1.31 × 10-126), FAM3C (P = 4.18 × 10-108), and CPED1 (P = 8.48 × 10-106). In addition, 114 genes associated with BMD within-subject variability were also identified, such as AC092079.1 (P = 2.72 × 10-13) and RGS7 (P = 4.72 × 10-10). The associations for these candidate genes were confirmed in the previous GWASs and replicated successfully in the Asian participants. GSEA results of BMD change identified multiple GO terms related to skeletal development, such as SKELETAL SYSTEM DEVELOPMENT (Padjusted = 2.45 × 10-3) and REGULATION OF OSSIFICATION (Padjusted = 2.45 × 10-3). KEGG enrichment analysis showed that these genes were mainly enriched in WNT SIGNALING PATHWAY. CONCLUSIONS Our findings indicated that the CPED1-WNT16-FAM3C locus plays a significant role in BMD mean trajectories and identified several novel candidate genes contributing to BMD within-subject variability, facilitating the understanding of the genetic architecture of BMD.
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Affiliation(s)
- Dan He
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
- School of Public Health, Xi'an Jiaotong University Health Science Center, No.76 Yan Ta West Road, Xi'an, 710061, China
| | - Huan Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
- School of Public Health, Xi'an Jiaotong University Health Science Center, No.76 Yan Ta West Road, Xi'an, 710061, China
| | - Wenming Wei
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
- School of Public Health, Xi'an Jiaotong University Health Science Center, No.76 Yan Ta West Road, Xi'an, 710061, China
| | - Yijing Zhao
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
- School of Public Health, Xi'an Jiaotong University Health Science Center, No.76 Yan Ta West Road, Xi'an, 710061, China
| | - Qingqing Cai
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
- School of Public Health, Xi'an Jiaotong University Health Science Center, No.76 Yan Ta West Road, Xi'an, 710061, China
| | - Sirong Shi
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
- School of Public Health, Xi'an Jiaotong University Health Science Center, No.76 Yan Ta West Road, Xi'an, 710061, China
| | - Xiaoge Chu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
- School of Public Health, Xi'an Jiaotong University Health Science Center, No.76 Yan Ta West Road, Xi'an, 710061, China
| | - Xiaoyue Qin
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
- School of Public Health, Xi'an Jiaotong University Health Science Center, No.76 Yan Ta West Road, Xi'an, 710061, China
| | - Na Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
- School of Public Health, Xi'an Jiaotong University Health Science Center, No.76 Yan Ta West Road, Xi'an, 710061, China
| | - Peng Xu
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, 710054, Shanxi, China.
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, 710061, China.
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China.
- School of Public Health, Xi'an Jiaotong University Health Science Center, No.76 Yan Ta West Road, Xi'an, 710061, China.
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5
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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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6
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Unfolding of hidden white blood cell count phenotypes for gene discovery using latent class mixed modeling. Genes Immun 2018; 20:555-565. [PMID: 30459343 DOI: 10.1038/s41435-018-0051-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 09/24/2018] [Accepted: 10/24/2018] [Indexed: 12/26/2022]
Abstract
Resting-state white blood cell (WBC) count is a marker of inflammation and immune system health. There is evidence that WBC count is not fixed over time and there is heterogeneity in WBC trajectory that is associated with morbidity and mortality. Latent class mixed modeling (LCMM) is a method that can identify unobserved heterogeneity in longitudinal data and attempts to classify individuals into groups based on a linear model of repeated measurements. We applied LCMM to repeated WBC count measures derived from electronic medical records of participants of the National Human Genetics Research Institute (NHRGI) electronic MEdical Record and GEnomics (eMERGE) network study, revealing two WBC count trajectory phenotypes. Advancing these phenotypes to GWAS, we found genetic associations between trajectory class membership and regions on chromosome 1p34.3 and chromosome 11q13.4. The chromosome 1 region contains CSF3R, which encodes the granulocyte colony-stimulating factor receptor. This protein is a major factor in neutrophil stimulation and proliferation. The association on chromosome 11 contain genes RNF169 and XRRA1; both involved in the regulation of double-strand break DNA repair.
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Lamballais S, Sajjad A, Leening MJG, Gaillard R, Franco OH, Mattace‐Raso FUS, Jaddoe VWV, Roza SJ, Tiemeier H, Ikram MA. Association of Blood Pressure and Arterial Stiffness With Cognition in 2 Population-Based Child and Adult Cohorts. J Am Heart Assoc 2018; 7:e009847. [PMID: 30608188 PMCID: PMC6404174 DOI: 10.1161/jaha.118.009847] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Accepted: 09/07/2018] [Indexed: 12/27/2022]
Abstract
Background High blood pressure levels and higher arterial stiffness have been shown to be associated with lower cognition during adulthood, possibly by accumulative changes over time. However, vascular factors may already affect the brain during early life. Methods and Results We examined the relation between cognition and vascular factors within 5853 children from the Generation R Study (mean age 6.2 years) and 5187 adults from the Rotterdam Study (mean age 61.8 years). Diastolic and systolic blood pressure and arterial stiffness were assessed, the latter by measuring pulse-wave velocity and pulse pressure. For cognition, the Generation R Study relied on nonverbal intelligence, whereas the Rotterdam Study relied on a cognitive test battery to calculate the g-factor, a measure of global cognition. In the Generation R Study, standardized diastolic blood pressure showed a significant association with standardized nonverbal intelligence (β=-0.030, 95% confidence interval=[-0.054; -0.005]) after full adjustment. This association held up after excluding the top diastolic blood pressure decile (β=-0.042 [-0.075; -0.009]), suggesting that the relation holds in normotensives. Within the Rotterdam Study, standardized cognition associated linearly with standardized systolic blood pressure (β=-0.036 [-0.060; -0.012]), standardized pulse-wave velocity (β=-0.064 [-0.095; -0.033]), and standardized pulse pressure (β=-0.044 [-0.069; -0.020], and nonlinearly with standardized diastolic blood pressure (quadratic term β=-0.032 [-0.049; -0.015]) after full adjustment. Conclusions Blood pressure and cognition may already be related in the general population during early childhood, albeit differently than during adulthood.
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Affiliation(s)
- Sander Lamballais
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- The Generation R Study GroupErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
| | - Ayesha Sajjad
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
| | - Maarten J. G. Leening
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- Department of CardiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- Department of Clinical EpidemiologyHarvard T. H. Chan School of Public HealthBostonMA
| | - Romy Gaillard
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- The Generation R Study GroupErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
| | - Oscar H. Franco
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
| | - Francesco U. S. Mattace‐Raso
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- Department of Internal MedicineErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
| | - Vincent W. V. Jaddoe
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- The Generation R Study GroupErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- Department of PediatricsErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
| | - Sabine J. Roza
- Department of PsychiatryErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
| | - Henning Tiemeier
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- Department of PsychiatryErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- Department of Child and Adolescent Psychiatry and PsychologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- Department of Social & Behavioral SciencesHarvard T. H. Chan School of Public HealthBostonMA
| | - M. Arfan Ikram
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- Department of RadiologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
- Department of NeurologyErasmus MC University Medical Center RotterdamRotterdamThe Netherlands
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