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Hanson KM, Macdonald SJ. Dynamic changes in gene expression through aging in Drosophila melanogaster heads. G3 (BETHESDA, MD.) 2025; 15:jkaf039. [PMID: 39992875 PMCID: PMC12005168 DOI: 10.1093/g3journal/jkaf039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2024] [Revised: 02/07/2025] [Accepted: 02/14/2025] [Indexed: 02/26/2025]
Abstract
Work in many systems has shown large-scale changes in gene expression during aging. However, many studies employ just 2 arbitrarily chosen timepoints to measure expression and can only observe an increase or a decrease in expression between "young" and "old" animals, failing to capture any dynamic, nonlinear changes that occur throughout the aging process. We used RNA sequencing to measure expression in male head tissue at 15 timepoints through the lifespan of an inbred Drosophila melanogaster strain. We detected >6,000 significant, age-related genes, nearly all of which have been seen in previous Drosophila aging expression studies and that include several known to harbor lifespan-altering mutations. We grouped our gene set into 28 clusters via their temporal expression change, observing a diversity of trajectories; some clusters show a linear change over time, while others show more complex, nonlinear patterns. Notably, reanalysis of our dataset comparing the earliest and latest timepoints-mimicking a 2-timepoint design-revealed fewer differentially expressed genes (around 4,500). Additionally, those genes exhibiting complex expression trajectories in our multitimepoint analysis were most impacted in this reanalysis; their identification, and the inferred change in gene expression with age, was often dependent on the timepoints chosen. Informed by our trajectory-based clusters, we executed a series of gene enrichment analyses, identifying enriched functions/pathways in all clusters, including the commonly seen increase in stress- and immune-related gene expression with age. Finally, we developed a pair of accessible Shiny apps to enable exploration of our differential expression and gene enrichment results.
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Affiliation(s)
- Katherine M Hanson
- Department of Molecular Biosciences and Center for Genomics, University of Kansas, 1200 Sunnyside Avenue, Lawrence, KS 66045, USA
| | - Stuart J Macdonald
- Department of Molecular Biosciences and Center for Genomics, University of Kansas, 1200 Sunnyside Avenue, Lawrence, KS 66045, USA
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Chen Z, Wu X, Yang Q, Zhao H, Ying H, Liu H, Wang C, Zheng R, Lin H, Wang S, Li M, Wang T, Zhao Z, Xu M, Chen Y, Xu Y, Lu J, Ning G, Wang W, Luo S, Au Yeung SL, Bi Y, Zheng J. The Effect of SGLT2 Inhibition on Brain-related Phenotypes and Aging: A Drug Target Mendelian Randomization Study. J Clin Endocrinol Metab 2025; 110:1096-1104. [PMID: 39270733 PMCID: PMC11913115 DOI: 10.1210/clinem/dgae635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2024] [Revised: 08/06/2024] [Accepted: 09/12/2024] [Indexed: 09/15/2024]
Abstract
INTRODUCTION An observational study suggested sodium-glucose cotransporter 2 (SGLT2) inhibitors might promote healthy aging. However, whether brain-related phenotypes mediate this association is still a question. We applied Mendelian randomization (MR) to investigate the effect of SGLT2 inhibition on chronological age, biological age, and cognition and explore the mediation effects of brain imaging-derived phenotypes (IDPs). METHODS We selected genetic variants associated with both expression levels of SLC5A2 (Genotype-Tissue Expression and eQTLGen data; n = 129 to 31 684) and hemoglobin A1c (HbA1c) levels (UK Biobank; n = 344 182) and used them to proxy the effect of SGLT2 inhibition. Aging-related outcomes, including parental longevity (n = 389 166) and epigenetic clocks (n = 34 710), and cognitive phenotypes, including cognitive function (n = 300 486) and intelligence (n = 269 867) were derived from genome-wide association studies. Two-step MR was conducted to explore the associations between SGLT2 inhibition, IDPs, and aging outcomes and cognition. RESULTS SGLT2 inhibition was associated with longer father's attained age [years of life increase per SD (6.75 mmol/mol) reduction in HbA1c levels = 6.21, 95% confidence interval (CI) 1.27-11.15], better cognitive function (beta = .17, 95% CI 0.03-0.31), and higher intelligence (beta = .47, 95% CI 0.19-0.75). Two-step MR identified 2 IDPs as mediators linking SGLT2 inhibition with chronological age (total proportion of mediation = 22.6%), where 4 and 5 IDPs were mediators for SGLT2 inhibition on cognitive function and intelligence, respectively (total proportion of mediation = 61.6% and 68.6%, respectively). CONCLUSION Our study supported that SGLT2 inhibition increases father's attained age, cognitive function, and intelligence, which was mediated through brain images of different brain regions. Future studies are needed to investigate whether a similar effect could be observed for users of SGLT2 inhibitors.
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Affiliation(s)
- Zhihe Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xueyan Wu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Qianqian Yang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Huiling Zhao
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Oakfield House, Bristol BS8 2BN, UK
| | - Hui Ying
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Haoyu Liu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Chaoyue Wang
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Ruizhi Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Hong Lin
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Shuangyuan Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yuhong Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Shan Luo
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administration Region 999077, China
| | - Shiu Lun Au Yeung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administration Region 999077, China
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Oakfield House, Bristol BS8 2BN, UK
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3
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Liu H, Abedini A, Ha E, Ma Z, Sheng X, Dumoulin B, Qiu C, Aranyi T, Li S, Dittrich N, Chen HC, Tao R, Tarng DC, Hsieh FJ, Chen SA, Yang SF, Lee MY, Kwok PY, Wu JY, Chen CH, Khan A, Limdi NA, Wei WQ, Walunas TL, Karlson EW, Kenny EE, Luo Y, Kottyan L, Connolly JJ, Jarvik GP, Weng C, Shang N, Cole JB, Mercader JM, Mandla R, Majarian TD, Florez JC, Haas ME, Lotta LA, Regeneron Genetics Center, GHS-RGC DiscovEHR Collaboration, Drivas TG, Penn Medicine BioBank, Vy HMT, Nadkarni GN, Wiley LK, Wilson MP, Gignoux CR, Rasheed H, Thomas LF, Åsvold BO, Brumpton BM, Hallan SI, Hveem K, Zheng J, Hellwege JN, Zawistowski M, Zöllner S, Franceschini N, Hu H, Zhou J, Kiryluk K, Ritchie MD, Palmer M, Edwards TL, Voight BF, Hung AM, Susztak K. Kidney multiome-based genetic scorecard reveals convergent coding and regulatory variants. Science 2025; 387:eadp4753. [PMID: 39913582 PMCID: PMC12013656 DOI: 10.1126/science.adp4753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Collaborators] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 11/20/2024] [Indexed: 02/17/2025]
Abstract
Kidney dysfunction is a major cause of mortality, but its genetic architecture remains elusive. In this study, we conducted a multiancestry genome-wide association study in 2.2 million individuals and identified 1026 (97 previously unknown) independent loci. Ancestry-specific analysis indicated an attenuation of newly identified signals on common variants in European ancestry populations and the power of population diversity for further discoveries. We defined genotype effects on allele-specific gene expression and regulatory circuitries in more than 700 human kidneys and 237,000 cells. We found 1363 coding variants disrupting 782 genes, with 601 genes also targeted by regulatory variants and convergence in 161 genes. Integrating 32 types of genetic information, we present the "Kidney Disease Genetic Scorecard" for prioritizing potentially causal genes, cell types, and druggable targets for kidney disease.
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Affiliation(s)
- Hongbo Liu
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Penn-CHOP Kidney Innovation Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Amin Abedini
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Eunji Ha
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ziyuan Ma
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Xin Sheng
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou, Zhejiang, China
- Department of Nephrology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
| | - Bernhard Dumoulin
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Chengxiang Qiu
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Tamas Aranyi
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Molecular Life Sciences, HUN-REN Research Center for Natural Sciences, Budapest, Hungary
- Department of Molecular Biology, Semmelweis University, Budapest, Hungary
| | - Shen Li
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicole Dittrich
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Federal University of São Paulo, São Paulo, Brazil
| | - Hua-Chang Chen
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Der-Cherng Tarng
- Institute of Clinical Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Division of Nephrology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
| | - Feng-Jen Hsieh
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan, ROC
| | - Shih-Ann Chen
- Cardiovascular Center, Taichung Veterans General Hospital, Taichung, Taiwan, ROC
- National Chung Hsing University, Taichung, Taiwan, ROC
- Heart Rhythm Center, Division of Cardiology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
- Department of Internal Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
| | - Shun-Fa Yang
- Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan, ROC
- Department of Medical Research, Chung Shan Medical University Hospital, Taichung, Taiwan, ROC
| | - Mei-Yueh Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan, ROC
- School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC
- Department of Internal Medicine, Kaohsiung Medical University Gangshan Hospital, Kaohsiung, Taiwan, ROC
| | - Pui-Yan Kwok
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan, ROC
- Institute for Human Genetics, University of California, San Francisco, CA, USA
| | - Jer-Yuarn Wu
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan, ROC
| | - Chien-Hsiun Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan, ROC
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Nita A. Limdi
- Department of Neurology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Theresa L. Walunas
- Department of Medicine, Division of General Internal Medicine and Center for Health Information Partnerships, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Eimear E. Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of General Internal Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yuan Luo
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Leah Kottyan
- The Center for Autoimmune Genomics and Etiology, Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | - John J. Connolly
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Gail P. Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Ning Shang
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Joanne B. Cole
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Endocrinology, Boston Children’s Hospital, Boston, MA, USA
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Josep M. Mercader
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ravi Mandla
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine and Cardiovascular Research Institute, Cardiology Division, University of California, San Francisco, CA, USA
- Graduate Program in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy D. Majarian
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Vertex Pharmaceuticals, Boston, MA, USA
| | - Jose C. Florez
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Mary E. Haas
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Luca A. Lotta
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | | | | | - Theodore G. Drivas
- Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | | | - Ha My T. Vy
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Girish N. Nadkarni
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Hasso Plattner Institute of Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Laura K. Wiley
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Melissa P. Wilson
- Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Christopher R. Gignoux
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Humaira Rasheed
- KGJebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Laurent F. Thomas
- KGJebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
| | - Bjørn Olav Åsvold
- KGJebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Ben M. Brumpton
- KGJebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Clinic of Thoracic and Occupational Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Stein I. Hallan
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Nephrology, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Kristian Hveem
- KGJebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jie Zheng
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jacklyn N. Hellwege
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Matthew Zawistowski
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Sebastian Zöllner
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Hailong Hu
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Jianfu Zhou
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Marylyn D. Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Palmer
- Pathology and Laboratory Medicine at the Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Todd L. Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Benjamin F. Voight
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Adriana M. Hung
- Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- VA Tennessee Valley Healthcare System, Clinical Sciences Research and Development, Nashville, TN, USA
| | - Katalin Susztak
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Penn-CHOP Kidney Innovation Center, University of Pennsylvania, Philadelphia, PA, USA
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Collaborators
Aris Baras, Gonçalo Abecasis, Adolfo Ferrando, Giovanni Coppola, Andrew Deubler, Aris Economides, Luca A Lotta, John D Overton, Jeffrey G Reid, Alan Shuldiner, Katherine Siminovitch, Jason Portnoy, Marcus B Jones, Lyndon Mitnaul, Alison Fenney, Jonathan Marchini, Manuel Allen Revez Ferreira, Maya Ghoussaini, Mona Nafde, William Salerno, John D Overton, Christina Beechert, Erin Fuller, Laura M Cremona, Eugene Kalyuskin, Hang Du, Caitlin Forsythe, Zhenhua Gu, Kristy Guevara, Michael Lattari, Alexander Lopez, Kia Manoochehri, Prathyusha Challa, Manasi Pradhan, Raymond Reynoso, Ricardo Schiavo, Maria Sotiropoulos Padilla, Chenggu Wang, Sarah E Wolf, Hang Du, Kristy Guevara, Amelia Averitt, Nilanjana Banerjee, Dadong Li, Sameer Malhotra, Justin Mower, Mudasar Sarwar, Deepika Sharma, Sean Yu, Aaron Zhang, Muhammad Aqeel, Jeffrey G Reid, Mona Nafde, Manan Goyal, George Mitra, Sanjay Sreeram, Rouel Lanche, Vrushali Mahajan, Sai Lakshmi Vasireddy, Gisu Eom, Krishna Pawan Punuru, Sujit Gokhale, Benjamin Sultan, Pooja Mule, Eliot Austin, Xiaodong Bai, Lance Zhang, Sean O'Keeffe, Razvan Panea, Evan Edelstein, Ayesha Rasool, William Salerno, Evan K Maxwell, Boris Boutkov, Alexander Gorovits, Ju Guan, Lukas Habegger, Alicia Hawes, Olga Krasheninina, Samantha Zarate, Adam J Mansfield, Lukas Habegger, Gonçalo Abecasis, Joshua Backman, Kathy Burch, Adrian Campos, Liron Ganel, Sheila Gaynor, Benjamin Geraghty, Arkopravo Ghosh, Salvador Romero Martinez, Christopher Gillies, Lauren Gurski, Joseph Herman, Eric Jorgenson, Tyler Joseph, Michael Kessler, Jack Kosmicki, Adam Locke, Priyanka Nakka, Jonathan Marchini, Karl Landheer, Olivier Delaneau, Maya Ghoussaini, Anthony Marcketta, Joelle Mbatchou, Arden Moscati, Aditeya Pandey, Anita Pandit, Jonathan Ross, Carlo Sidore, Eli Stahl, Timothy Thornton, Sailaja Vedantam, Rujin Wang, Kuan-Han Wu, Bin Ye, Blair Zhang, Andrey Ziyatdinov, Yuxin Zou, Jingning Zhang, Kyoko Watanabe, Mira Tang, Frank Wendt, Suganthi Balasubramanian, Suying Bao, Kathie Sun, Chuanyi Zhang, Adolfo Ferrando, Giovanni Coppola, Luca A Lotta, Alan Shuldiner, Katherine Siminovitch, Brian Hobbs, Jon Silver, William Palmer, Rita Guerreiro, Amit Joshi, Antoine Baldassari, Cristen Willer, Sarah Graham, Ernst Mayerhofer, Erola Pairo Castineira, Mary Haas, Niek Verweij, George Hindy, Jonas Bovijn, Tanima De, Parsa Akbari, Luanluan Sun, Olukayode Sosina, Arthur Gilly, Peter Dornbos, Juan Rodriguez-Flores, Moeen Riaz, Manav Kapoor, Gannie Tzoneva, Momodou W Jallow, Anna Alkelai, Ariane Ayer, Veera Rajagopal, Sahar Gelfman, Vijay Kumar, Jacqueline Otto, Neelroop Parikshak, Aysegul Guvenek, Jose Bras, Silvia Alvarez, Jessie Brown, Jing He, Hossein Khiabanian, Joana Revez, Kimberly Skead, Valentina Zavala, Jae Soon Sul, Lei Chen, Sam Choi, Amy Damask, Nan Lin, Charles Paulding, Marcus B Jones, Esteban Chen, Michelle G LeBlanc, Jason Mighty, Jennifer Rico-Varela, Nirupama Nishtala, Nadia Rana, Jaimee Hernandez, Alison Fenney, Randi Schwartz, Jody Hankins, Anna Han, Samuel Hart, Ann Perez-Beals, Gina Solari, Johannie Rivera-Picart, Michelle Pagan, Sunilbe Siceron, Adam Buchanan, David J Carey, Christa L Martin, Michelle Meyer, Kyle Retterer, David Rolston, Daniel J Rader, Marylyn D Ritchie, JoEllen Weaver, Nawar Naseer, Giorgio Sirugo, Afiya Poindexter, Yi-An Ko, Kyle P Nerz, Meghan Livingstone, Fred Vadivieso, Stephanie DerOhannessian, Teo Tran, Julia Stephanowski, Salma Santos, Ned Haubein, Joseph Dunn, Anurag Verma, Colleen Morse Kripke, Marjorie Risman, Renae Judy, Colin Wollack, Shefali S Verma, Scott M Damrauer, Yuki Bradford, Scott M Dudek, Theodore G Drivas,
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4
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Xiang Y, Tanwar V, Singh P, Follette LL, Narayan V, Kapahi P. Early menarche and childbirth accelerate aging-related outcomes and age-related diseases: Evidence for antagonistic pleiotropy in humans. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2024.09.23.24314197. [PMID: 39398990 PMCID: PMC11469407 DOI: 10.1101/2024.09.23.24314197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/15/2024]
Abstract
Aging can be understood as a consequence of the declining force of natural selection with age. Consistent with this, the antagonistic pleiotropy theory of aging proposes that aging arises from trade-offs that favor early growth and reproduction. However, evidence supporting antagonistic pleiotropy in humans remains limited. Using Mendelian Randomization (MR), we demonstrated that later ages of menarche or first childbirth were genetically associated with longer parental lifespan, decreased frailty index, slower epigenetic aging, later menopause, and reduced facial aging. Moreover, later menarche or first childbirth were also genetically associated with a lower risk of several age-related diseases, including late-onset Alzheimer's disease (LOAD), type 2 diabetes, heart disease, essential hypertension, and chronic obstructive pulmonary disease (COPD). We validated the associations between the age of menarche, childbirth, and the number of childbirths with several age-related outcomes in the UK Biobank by conducting regression analysis of nearly 200,000 subjects. Our results demonstrated that menarche before the age 11 and childbirth before 21 significantly accelerated the risk of several diseases, and almost doubled the risk for diabetes, heart failure, and quadrupled the risk of obesity, supporting the antagonistic pleiotropy theory. We identified 126 significant single nucleotide polymorphisms (SNPs) that influenced age-related outcomes, some of which were involved in known longevity pathways, including IGF1, growth hormone, AMPK, and mTOR signaling. Our study also identified higher BMI as a mediating factor in causing the increased risk of certain diseases, such as type 2 diabetes and heart failure, in women with early menarche or early pregnancy, emphasizing the importance of the thrifty gene hypothesis in explaining in part the mechanisms behind antagonistic pleiotropy. Our study highlights the complex relationship between genetic legacies and modern diseases, emphasizing the need for gender-sensitive healthcare strategies that consider the unique connections between female reproductive health and aging.
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Affiliation(s)
- Yifan Xiang
- The Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, CA 94945
| | - Vineeta Tanwar
- The Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, CA 94945
| | - Parminder Singh
- The Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, CA 94945
| | | | - Vikram Narayan
- The Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, CA 94945
| | - Pankaj Kapahi
- The Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, CA 94945
- Department of Urology, University of California, San Francisco, 400 Parnassus Avenue, San Francisco, CA 94143
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5
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Castro C, Delwarde C, Shi Y, Roh J. Geroscience in heart failure: the search for therapeutic targets in the shared pathobiology of human aging and heart failure. THE JOURNAL OF CARDIOVASCULAR AGING 2025; 5:10.20517/jca.2024.15. [PMID: 40297496 PMCID: PMC12036312 DOI: 10.20517/jca.2024.15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/30/2025]
Abstract
Age is a major risk factor for heart failure, but one that has been historically viewed as non-modifiable. Emerging evidence suggests that the biology of aging is malleable, and can potentially be intervened upon to treat age-associated chronic diseases, such as heart failure. While aging biology represents a new frontier for therapeutic target discovery in heart failure, the challenges of translating Geroscience research to the clinic are multifold. In this review, we propose a strategy that prioritizes initial target discovery in human biology. We review the rationale for starting with human omics, which has generated important insights into the shared (patho)biology of human aging and heart failure. We then discuss how this knowledge can be leveraged to identify the mechanisms of aging biology most relevant to heart failure. Lastly, we provide examples of how this human-first Geroscience approach, when paired with rigorous functional assessments in preclinical models, is leading to early-stage clinical development of gerotherapeutic approaches for heart failure.
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Affiliation(s)
- Claire Castro
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Constance Delwarde
- Center for Interdisciplinary Cardiovascular Sciences, Brigham and Women’s Hospital, Boston, MA 02115, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Yanxi Shi
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jason Roh
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
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6
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Gurinovich A, Song Z, Bae H, Leshchyk A, Li M, Lords H, Andersen SL, Nygaard M, Christensen K, Daw EW, Arbeev KG, Brent MR, Perls TT, Sebastiani P. SNP rs6543176 is associated with extreme human longevity but increased risk for cancer. GeroScience 2025:10.1007/s11357-024-01478-5. [PMID: 39751714 DOI: 10.1007/s11357-024-01478-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2024] [Accepted: 12/14/2024] [Indexed: 01/04/2025] Open
Abstract
Using whole-genome sequencing (WGS) might offer insights into rare genetic variants associated with healthy aging and extreme longevity (EL), potentially pointing to useful therapeutic targets. In this study, we conducted a genome-wide association study using WGS data from the Long Life Family Study and identified a novel longevity-associated variant rs6543176 in the SLC9A2 gene. This SNP also showed a significant association with reduced hypertension risk and an increased, though not statistically significant, cancer risk. The association with cancer risk was replicated in the UK Biobank and FinnGen. Metabolomic analyses linked the rs6543176 longevity allele to higher serine levels, potentially associated with delayed mortality. Our findings warrant further investigation of SLC9A2's role in both longevity and cancer susceptibility, and they highlight the need for careful evaluation in developing anti-aging therapies based on EL-associated alleles.
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Affiliation(s)
- Anastasia Gurinovich
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, 02111, USA.
- Department of Medicine, Tufts University, Boston, MA, 02111, USA.
| | - Zeyuan Song
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, 02111, USA
- Department of Medicine, Tufts University, Boston, MA, 02111, USA
| | - Harold Bae
- Biostatistics Program, College of Health, Oregon State University, Corvallis, OR, 97331, USA
| | - Anastasia Leshchyk
- Bioinformatics Program, Faculty of Computing & Data Sciences, Boston University, Boston, MA, 02215, USA
- Department of Medicine, Computational Biomedicine Section, School of Medicine, Boston University, Chobanian & Avedisian, Boston, MA, 02118, USA
| | - Mengze Li
- Bioinformatics Program, Faculty of Computing & Data Sciences, Boston University, Boston, MA, 02215, USA
- Department of Medicine, Computational Biomedicine Section, School of Medicine, Boston University, Chobanian & Avedisian, Boston, MA, 02118, USA
| | - Hannah Lords
- Bioinformatics Program, Faculty of Computing & Data Sciences, Boston University, Boston, MA, 02215, USA
- Department of Medicine, Computational Biomedicine Section, School of Medicine, Boston University, Chobanian & Avedisian, Boston, MA, 02118, USA
| | - Stacy L Andersen
- Department of Medicine, Section of Geriatrics, School of Medicine, Boston University, Chobanian & Avedisian, Boston, MA, 02118, USA
| | - Marianne Nygaard
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Kaare Christensen
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
- Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark
| | - E Warwick Daw
- Division of Statistical Genomics, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Konstantin G Arbeev
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27708, USA
| | - Michael R Brent
- Division of Computational and Data Sciences, Center for Genome Sciences and Systems Biology, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Thomas T Perls
- Department of Medicine, Section of Geriatrics, School of Medicine, Boston University, Chobanian & Avedisian, Boston, MA, 02118, USA
| | - Paola Sebastiani
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, 02111, USA
- Department of Medicine, Tufts University, Boston, MA, 02111, USA
- Data Intensive Study Center, Tufts University, Medford, MA, 02155, USA
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7
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Zhao X, Wu X, He L, Xiao J, Xiang R, Sha L, Tang M, Hao Y, Qu Y, Xiao C, Qin C, Hou J, Deng Q, Zhu J, Zheng S, Zhou J, Yu T, Yang B, Song X, Han T, Liao J, Zhang T, Fan M, Li J, Jiang X. Leisure-Time Physical Activity, Sedentary Behavior, and Biological Aging: Evidence From Genetic Correlation and Mendelian Randomization Analyses. Scand J Med Sci Sports 2025; 35:e70014. [PMID: 39794269 PMCID: PMC11723829 DOI: 10.1111/sms.70014] [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: 09/01/2024] [Revised: 11/14/2024] [Accepted: 12/27/2024] [Indexed: 01/13/2025]
Abstract
Physical inactivity and sedentary behavior are associated with higher risks of age-related morbidity and mortality. However, whether they causally contribute to accelerating biological aging has not been fully elucidated. Utilizing the largest available genome-wide association study (GWAS) summary data, we implemented a comprehensive analytical framework to investigate the associations between genetically predicted moderate-to-vigorous leisure-time physical activity (MVPA), leisure screen time (LST), and four epigenetic age acceleration (EAA) measures: HannumAgeAccel, intrinsic HorvathAgeAccel, PhenoAgeAccel, and GrimAgeAccel. Shared genetic backgrounds across these traits were quantified through genetic correlation analysis. Overall and independent associations were assessed through univariable and multivariable Mendelian randomization (MR). A recently developed tissue-partitioned MR approach was further adopted to explore potential tissue-specific pathways that contribute to the observed associations. Among the four EAA measures investigated, consistent results were identified for PhenoAgeAccel and GrimAgeAccel. These two measures were negatively genetically correlated with MVPA (rg = -0.18 to -0.29) and positively genetically correlated with LST (rg = 0.22-0.37). Univariable MR yielded a robust effect of genetically predicted LST on GrimAgeAccel (βIVW = 0.69, p = 1.10 × 10-7), while genetically predicted MVPA (βIVW = -1.02, p = 1.50 × 10-2) and LST (βIVW = 0.37, p = 1.90 × 10-2) showed marginal effects on PhenoAgeAccel. Multivariable MR suggested an independent association between genetically predicted LST and GrimAgeAccel after accounting for MVPA and other important confounders. Tissue-partitioned MR suggested skeletal muscle tissue associated variants to be predominantly responsible for driving the effect of LST on GrimAgeAccel. Findings support sedentary lifestyles as a modifiable risk factor in accelerating epigenetic aging, emphasizing the need for preventive strategies to reduce sedentary screen time for healthy aging.
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Affiliation(s)
- Xunying Zhao
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Xueyao Wu
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
- Division of Cancer Epidemiology and GeneticsNational Cancer InstituteRockvilleMarylandUSA
| | - Lin He
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Jinyu Xiao
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Rong Xiang
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduChina
| | - Linna Sha
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduChina
| | - Mingshuang Tang
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Yu Hao
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Yang Qu
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Changfeng Xiao
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Chenjiarui Qin
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduChina
| | - Jiaojiao Hou
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Qin Deng
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduChina
| | - Jiangbo Zhu
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduChina
| | - Sirui Zheng
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduChina
| | - Jinyu Zhou
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduChina
| | - Ting Yu
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Bin Yang
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduChina
| | - Xin Song
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Tao Han
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduChina
| | - Jiaqiang Liao
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Tao Zhang
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Mengyu Fan
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Jiayuan Li
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
| | - Xia Jiang
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduSichuanChina
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth HospitalSichuan UniversityChengduChina
- Department of Clinical Neuroscience, Center for Molecular MedicineKarolinska InstitutetSolnaStockholmSweden
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8
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Hanson KM, Macdonald SJ. Dynamic Changes in Gene Expression Through Aging in Drosophila melanogaster Heads. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.11.627977. [PMID: 39764034 PMCID: PMC11702523 DOI: 10.1101/2024.12.11.627977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/14/2025]
Abstract
Work in many systems has shown large-scale changes in gene expression during aging. However, many studies employ just two, arbitrarily-chosen timepoints at which to measure expression, and can only observe an increase or a decrease in expression between "young" and "old" animals, failing to capture any dynamic, non-linear changes that occur throughout the aging process. We used RNA sequencing to measure expression in male head tissue at 15 timepoints through the lifespan of an inbred Drosophila melanogaster strain. We detected >6,000 significant, age-related genes, nearly all of which have been seen in previous fly aging expression studies, and which include several known to harbor lifespan-altering mutations. We grouped our gene set into 28 clusters via their temporal expression change, observing a diversity of trajectories; some clusters show a linear change over time, while others show more complex, non-linear patterns. Notably, re-analysis of our dataset comparing the earliest and latest timepoints - mimicking a two-timepoint design - revealed fewer differentially-expressed genes (around 4,500). Additionally, those genes exhibiting complex expression trajectories in our multi-timepoint analysis were most impacted in this re-analysis; Their identification, and the inferred change in gene expression with age, was often dependent on the timepoints chosen. Informed by our trajectory-based clusters, we executed a series of gene enrichment analyses, identifying enriched functions/pathways in all clusters, including the commonly seen increase in stress- and immune-related gene expression with age. Finally, we developed a pair of accessible shiny apps to enable exploration of our differential expression and gene enrichment results.
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Affiliation(s)
- Katherine M Hanson
- Department of Molecular Biosciences and Center for Genomics, University of Kansas, 1200 Sunnyside Avenue, Lawrence, KS 66045, USA
| | - Stuart J Macdonald
- Department of Molecular Biosciences and Center for Genomics, University of Kansas, 1200 Sunnyside Avenue, Lawrence, KS 66045, USA
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9
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Pemmasani SK, R G S, V S, Bhattacharyya R, Patel C, Gupta AK, Acharya A. Genetic variants associated with longevity in long-living Indians. NPJ AGING 2024; 10:51. [PMID: 39567526 PMCID: PMC11579347 DOI: 10.1038/s41514-024-00179-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2024] [Accepted: 10/25/2024] [Indexed: 11/22/2024]
Abstract
Genetic factors play a significant role in determining an individual's longevity. The present study was aimed at identifying genetic variants associated with longevity in Indian population. Long living individuals (LLIs), aged 85+, were compared with younger controls, aged 18-49 years, using data from GenomegaDB, a genetic database of Indians living in India. An in-house developed custom chip, having variants associated with various cancers, cardiovascular, neurological, gastro-intestinal, metabolic and auto-immune disorders, was used to generate genotype data. Logistic regression analysis with sex and top three genetic principal components as covariates resulted in 9 variants to be significantly associated with longevity at a p-value threshold of 5 × 10-4. Alleles associated with slower heart rate (rs365990, MYH6), decreased risk of osteoporosis and short body height (rs2982570, ESR1), decreased risk of schizophrenia (rs1339227, RIMS1-KCNQ5) and decreased risk of anxiety and neuroticism (rs391957, HSPA5) were found to have higher frequency in LLIs. Alleles associated with increased risk of atrial fibrillation (rs3903239, GORAB-PRRX1) and biliary disorders (rs2002042, ABCC2) were found to have lower frequency. The G allele of rs2802292 from FOXO3A gene, associated with longevity in Japanese, German and French centenarians, was also found to be significant in this population (P = 0.032). Pathway enrichment analysis revealed that the genes involved in oxidative stress, apoptosis, DNA damage repair, glucose metabolism and energy metabolism were significantly involved in affecting the longevity. Results of our study demonstrate the genetic basis of healthy aging and longevity in the population.
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Affiliation(s)
| | | | - Suraj V
- Mapmygenome India Limited, Hyderabad, India
| | | | - Chetan Patel
- SRISTI - Society for Research and Initiatives for Sustainable Technologies and Institutions, Ahmedabad, India
| | - Anil Kumar Gupta
- SRISTI - Society for Research and Initiatives for Sustainable Technologies and Institutions, Ahmedabad, India
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10
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Chen S, Chen W, Wang X, Liu S. Mendelian randomization analyses support causal relationships between gut microbiome and longevity. J Transl Med 2024; 22:1032. [PMID: 39548551 PMCID: PMC11568586 DOI: 10.1186/s12967-024-05823-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2024] [Accepted: 10/31/2024] [Indexed: 11/18/2024] Open
Abstract
BACKGROUND Gut microbiome plays a significant role in longevity, and dysbiosis is indeed one of the hallmarks of aging. However, the causal relationship between gut microbiota and human longevity or aging remains elusive. METHODS Our study assessed the causal relationships between gut microbiome and longevity using Mendelian Randomization (MR). Summary statistics for the gut microbiome were obtained from four genome-wide association study (GWAS) meta-analysis of the MiBioGen consortium (N = 18,340), Dutch Microbiome Project (N = 7738), German individuals (N = 8956), and Finland individuals (N = 5959). Summary statistics for Longevity were obtained from Five GWAS meta-analysis, including Human healthspan (N = 300,447), Longevity (N = 36,745), Lifespans (N = 1,012,240), Parental longevity (N = 389,166), and Frailty (one of the primary aging-linked physiological hallmarks, N = 175,226). RESULTS Our findings reveal several noteworthy associations, including a negative correlation between Bacteroides massiliensis and longevity, whereas the genus Subdoligranulum and Alistipes, as well as species Alistipes senegalensis and Alistipes shahii, exhibited positive associations with specific longevity traits. Moreover, the microbial pathway of coenzyme A biosynthesis I, pyruvate fermentation to acetate and lactate II, and pentose phosphate pathway exhibited positive associations with two or more traits linked to longevity. Conversely, the TCA cycle VIII (helicobacter) pathway consistently demonstrated a negative correlation with lifespan and parental longevity. CONCLUSIONS Our findings of this MR study indicated many significant associations between gut microbiome and longevity. These microbial taxa and pathways may potentially play a protective role in promoting longevity or have a suppressive effect on lifespan.
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Affiliation(s)
- Shu Chen
- Department of Pathology, The Seven Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
| | - Wei Chen
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
| | - Xudong Wang
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
| | - Sheng Liu
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China.
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11
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Hilsabeck TAU, Narayan VP, Wilson KA, Carrera EM, Raftery D, Promislow D, Brem RB, Campisi J, Kapahi P. Systems biology approaches identify metabolic signatures of dietary lifespan and healthspan across species. Nat Commun 2024; 15:9330. [PMID: 39472442 PMCID: PMC11522498 DOI: 10.1038/s41467-024-52909-y] [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: 04/11/2024] [Accepted: 09/18/2024] [Indexed: 11/02/2024] Open
Abstract
Dietary restriction (DR) is a potent method to enhance lifespan and healthspan, but individual responses are influenced by genetic variations. Understanding how metabolism-related genetic differences impact longevity and healthspan are unclear. To investigate this, we used metabolites as markers to reveal how different genotypes respond to diet to influence longevity and healthspan traits. We analyzed data from Drosophila Genetic Reference Panel (DGRP) strains raised under AL and DR conditions, combining metabolomic, phenotypic, and genome-wide information. We employed two computational and complementary methods across species-random forest modeling within the DGRP as our primary analysis and Mendelian randomization in human cohorts as a secondary analysis. We pinpointed key traits with cross-species relevance as well as underlying heterogeneity and pleiotropy that influence lifespan and healthspan. Notably, orotate was linked to parental age at death in humans and blocked the DR lifespan extension in flies, while threonine supplementation extended lifespan, in a strain- and sex-specific manner. Thus, utilizing natural genetic variation data from flies and humans, we employed a systems biology approach to elucidate potential therapeutic pathways and metabolomic targets for diet-dependent changes in lifespan and healthspan.
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Affiliation(s)
- Tyler A U Hilsabeck
- Buck Institute for Research on Aging, Novato, CA, 94945, USA
- Davis School of Gerontology, University of Southern California, University Park, University Park, Los Angeles, CA, 90089, USA
- Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
| | - Vikram P Narayan
- Buck Institute for Research on Aging, Novato, CA, 94945, USA
- Department of Biology & Chemistry, Embry-Riddle Aeronautical University, Prescott, AZ, 86301, USA
| | - Kenneth A Wilson
- Buck Institute for Research on Aging, Novato, CA, 94945, USA
- Davis School of Gerontology, University of Southern California, University Park, University Park, Los Angeles, CA, 90089, USA
| | - Enrique M Carrera
- Buck Institute for Research on Aging, Novato, CA, 94945, USA
- Dominican University of California, San Rafael, CA, 94901, USA
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
| | - Daniel Promislow
- Department of Pathology, University of Washington, Seattle, WA, 98195, USA
- Department of Biology, University of Washington, Seattle, WA, 98195, USA
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, 02111, USA
| | - Rachel B Brem
- Buck Institute for Research on Aging, Novato, CA, 94945, USA
- Davis School of Gerontology, University of Southern California, University Park, University Park, Los Angeles, CA, 90089, USA
- Department of Plant and Microbial Biology, University of California, Berkeley, CA, 94720, USA
| | - Judith Campisi
- Buck Institute for Research on Aging, Novato, CA, 94945, USA
| | - Pankaj Kapahi
- Buck Institute for Research on Aging, Novato, CA, 94945, USA.
- Davis School of Gerontology, University of Southern California, University Park, University Park, Los Angeles, CA, 90089, USA.
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12
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Jiesisibieke ZL, Schooling CM. Impact of Alcohol Consumption on Lifespan: a Mendelian randomization study in Europeans. Sci Rep 2024; 14:25321. [PMID: 39455599 PMCID: PMC11511936 DOI: 10.1038/s41598-024-73333-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 09/16/2024] [Indexed: 10/28/2024] Open
Abstract
Alcohol is widely used but recognized as a risk factor for several adverse health outcomes based on observational studies. How alcohol affects lifespan remains controversial, with no trial to make such an assessment available or likely. We conducted a Mendelian randomization (MR) to assess the effect of alcohol on lifespan in men and women, including a possible role of smoking and education. Strong (p < 5e- 8), independent (r2 < 0.001) genetic predictors of alcohol consumption in 2,428,851 participants of European ancestry from the Sequencing Consortium of Alcohol and Nicotine use (GSCAN) consortium genome wide association study (GWAS) were applied to sex-specific GWAS of lifespan (paternal and maternal attained age) and age at recruitment to the UK Biobank. We used multivariable MR to allow for smoking and education, with systolic and diastolic blood pressure as control outcomes. Inverse variance weighted was the primary analysis with sensitivity analysis. Alcohol consumption decreased lifespan overall (- 1.09 years (logged alcoholic drinks per week), - 1.89 to - 0.3) and in men (- 1.47 years, - 2.55 to - 0.38), which remained evident after adjusting for smoking (- 1.81 years, - 3.3 to - 0.32) and education (- 1.85 years, - 3.12 to - 0.58). Estimates from sensitivity analysis were similar, and when using the genetic variant physiologically associated with alcohol use. Alcohol consumption was associated with higher blood pressure as expected. Our study indicates that alcohol does not provide any advantages for men or women but could shorten lifespan. Appropriate interventions should be implemented.
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Affiliation(s)
- Zhu Liduzi Jiesisibieke
- School of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, 7 Sassoon Road, Pokfulam, Hong Kong, Hong Kong
| | - C Mary Schooling
- School of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, 7 Sassoon Road, Pokfulam, Hong Kong, Hong Kong.
- Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA.
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13
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Fan B, Zhao JV. Utilizing genetics and proteomics to assess the role of antihypertensive drugs in human longevity and the underlying pathways: a Mendelian randomization study. EUROPEAN HEART JOURNAL. CARDIOVASCULAR PHARMACOTHERAPY 2024; 10:537-546. [PMID: 38769606 DOI: 10.1093/ehjcvp/pvae038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 04/24/2024] [Accepted: 05/07/2024] [Indexed: 05/22/2024]
Abstract
BACKGROUND Antihypertensive drugs are known to lower cardiovascular mortality, but the role of different types of antihypertensive drugs in lifespan has not been clarified. Moreover, the underlying mechanisms remain unclear. METHODS AND RESULTS To minimize confounding, we used Mendelian randomization to assess the role of different antihypertensive drug classes in longevity and examined the pathways via proteins. Genetic variants associated with systolic blood pressure (SBP) corresponding to drug-target genes were used as genetic instruments. The genetic associations with lifespan were obtained from a large genome-wide association study including 1 million European participants from UK Biobank and LifeGen. For significant antihypertensive drug classes, we performed sex-specific analysis, drug-target analysis, and colocalization. To examine the mediation pathways, we assessed the associations of 2291 plasma proteins with lifespan, and examined the associations of drug classes with the proteins affecting lifespan. After correcting for multiple testing, genetically proxied beta-blockers (BBs), calcium channel blockers (CCBs), and vasodilators were related to longer life years (BBs: 2.03, 95% CI 0.78-3.28 per 5 mmHg reduction in SBP, CCBs: 3.40, 95% CI 1.47-5.33, and vasodilators: 2.92, 95% CI 1.08-4.77). The beneficial effects of BBs and CCBs were more obvious in men. ADRB1, CACNA2D2, CACNB3, CPT1A, CPT2, and EDNRA genes were related to extended lifespan, with CPT2 further supported by colocalization evidence. Eighty-six proteins were related to lifespan, of which four proteins were affected by CCBs. CDH1 may mediate the association between CCBs and lifespan. CONCLUSIONS Beta-blockers, CCBs, and vasodilators may prolong lifespan, with potential sex differences for BBs and CCBs. The role of CCBs in lifespan is partly mediated by CDH1. Prioritizing the potential protein targets can provide new insights into healthy aging.
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Affiliation(s)
- Bohan Fan
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Jie V Zhao
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong SAR, China
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14
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Yang H, Hou C, Chen W, Zeng Y, Qu Y, Sun Y, Hu Y, Tang X, Song H. Disease Modules Associated with Unfavorable Sleep Patterns and Their Genetic Determinants: A Prospective Cohort Study of the UK Biobank. PHENOMICS (CHAM, SWITZERLAND) 2024; 4:415-429. [PMID: 39723226 PMCID: PMC11666895 DOI: 10.1007/s43657-023-00144-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 10/23/2023] [Accepted: 11/02/2023] [Indexed: 12/28/2024]
Abstract
Despite the established associations between sleep-related traits and major diseases, comprehensive assessment on affected disease modules and their genetic determinants is lacking. Using multiple correspondence analysis and the k-means clustering algorithm, 235,826 eligible participants were clustered into distinct unfavorable sleep patterns [short sleep duration (n = 10,073), snoring (22,419), insomnia (102,771), insomnia and snoring (62,909)] and favorable sleep pattern groups (37,654). The associations of unfavorable sleep patterns with 134 diseases were estimated using Cox regression models; and comorbidity network analyses were applied for disease module identification. Genetic determinants associated with each disease module were identified by genome-wide association studies (GWAS). During an average follow-up of 10.80 years, unfavorable sleep patterns featured by 'short sleep duration', 'snoring', 'insomnia', and 'insomnia and snoring' were associated with increased risk of 0, 9, 10, and 19 diseases, respectively. Furthermore, comorbidity network analyses categorized these affected diseases into three disease modules, characterized by predominant diseases related to digestive system, circulatory and endocrine systems (snoring-related patterns only), and musculoskeletal system (insomnia-related patterns only). Using the number of affected diseases, as an index of a person's susceptibility to each disease module [i.e., susceptible score (SS)], GWAS analyses identified five, one, and three significant loci associated with the residual SS of these aforementioned disease modules, respectively, which mapped to several potential biological pathways, including those related to hormone regulation and catecholamine uptake. In conclusion, individuals with unfavorable sleep patterns, particularly snoring and insomnia, had increased risk of multiple diseases. The identification of three major disease modules with their relevant genetic determinants may facilitate strategy development for precision prevention of future health decline. Supplementary Information The online version contains supplementary material available at 10.1007/s43657-023-00144-8.
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Affiliation(s)
- Huazhen Yang
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Can Hou
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Wenwen Chen
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Yu Zeng
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Yuanyuan Qu
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Yajing Sun
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Yao Hu
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Xiangdong Tang
- Sleep Medicine Center, Department of Respiratory and Critical Care Medicine, Mental Health Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610000 China
| | - Huan Song
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
- Center of Public Health Sciences, Faculty of Medicine, University of Iceland, 102 Reykjavík, Iceland
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15
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von Berg J, McArdle PF, Häppölä P, Haessler J, Kooperberg C, Lemmens R, Pezzini A, Thijs V, Pulit SL, Kittner SJ, Mitchell BD, de Ridder J, van der Laan SW. Evidence of survival bias in the association between APOE-Є4 and age at ischemic stroke onset. Front Genet 2024; 15:1392061. [PMID: 39286457 PMCID: PMC11403718 DOI: 10.3389/fgene.2024.1392061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 06/18/2024] [Indexed: 09/19/2024] Open
Abstract
Introduction Large genome-wide association studies (GWASs) using case-control study designs have now identified tens of loci associated with ischemic stroke (IS). As a complement to these studies, we performed GWAS in a case-only design to identify loci influencing the age at onset (AAO) of ischemic stroke. Methods Analyses were conducted in a discovery cohort of 10,857 ischemic stroke cases using a linear regression framework. We meta-analyzed all SNPs with p-value <1 x 10-5 in a sexcombined or sex-stratified analysis using summary data from two additional replication cohorts. Results In the women-only meta-analysis, we detected significant evidence for the association of AAO with rs429358, an exonic variant in apolipoprotein E (APOE) that encodes for the APOE-Є4 allele. Each copy of the rs429358:T>C allele was associated with a 1.29-year earlier stroke AAO (meta p-value = 2.48 x 10-11). This APOE variant has previously been associated with increased mortality and ischemic stroke AAO. We hypothesized that the association with AAO may reflect a survival bias attributable to an age-related decrease in mortality among APOE-Є4 carriers and have no association to stroke AAO per se. A simulation study showed that a variant associated with overall mortality might indeed be detected with an AAO analysis. A variant with a 2-fold increase in mortality risk would lead to an observed effect of AAO that is comparable to what we found. Discussion In conclusion, we detected a robust association of the APOE locus with stroke AAO and provided simulations to suggest that this association may be unrelated to ischemic stroke per se but related to a general survival bias.
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Affiliation(s)
- Joanna von Berg
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Oncode Institute, Utrecht, Netherlands
| | - Patrick F. McArdle
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Paavo Häppölä
- Institute for Molecular Medicine Finland FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | | | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, United States
| | - Robin Lemmens
- University Hospitals Leuven, Department of Neurology, Leuven, Belgium
- KU Leuven–University of Leuven, Department of Neurosciences, Experimental Neurology, Leuven, Belgium
| | - Alessandro Pezzini
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Stroke Care Program, Department of Emergency, Parma University Hospital, Parma, Italy
| | - Vincent Thijs
- Stroke Theme, The Florey, Heidelberg, VIC, Australia
- Department of Medicine, University of Melbourne, Melbourne, VIC, Australia
- Department of Neurology, Austin Health, Heidelberg, VIC, Australia
| | - Sara L. Pulit
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Steven J. Kittner
- Geriatric Research and Education Clinical Center, VA Maryland Healthcare System, Baltimore, MD, United States
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Braxton D. Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Geriatric Research and Education Clinical Center, VA Maryland Healthcare System, Baltimore, MD, United States
| | - Jeroen de Ridder
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Oncode Institute, Utrecht, Netherlands
| | - Sander W. van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Center of Population Health and Genomics, University of Virginia, Charlottesville, VA, United States
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16
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Jackson RJ, Hyman BT, Serrano-Pozo A. Multifaceted roles of APOE in Alzheimer disease. Nat Rev Neurol 2024; 20:457-474. [PMID: 38906999 DOI: 10.1038/s41582-024-00988-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/24/2024] [Indexed: 06/23/2024]
Abstract
For the past three decades, apolipoprotein E (APOE) has been known as the single greatest genetic modulator of sporadic Alzheimer disease (AD) risk, influencing both the average age of onset and the lifetime risk of developing AD. The APOEε4 allele significantly increases AD risk, whereas the ε2 allele is protective relative to the most common ε3 allele. However, large differences in effect size exist across ethnoracial groups that are likely to depend on both global genetic ancestry and local genetic ancestry, as well as gene-environment interactions. Although early studies linked APOE to amyloid-β - one of the two culprit aggregation-prone proteins that define AD - in the past decade, mounting work has associated APOE with other neurodegenerative proteinopathies and broader ageing-related brain changes, such as neuroinflammation, energy metabolism failure, loss of myelin integrity and increased blood-brain barrier permeability, with potential implications for longevity and resilience to pathological protein aggregates. Novel mouse models and other technological advances have also enabled a number of therapeutic approaches aimed at either attenuating the APOEε4-linked increased AD risk or enhancing the APOEε2-linked AD protection. This Review summarizes this progress and highlights areas for future research towards the development of APOE-directed therapeutics.
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Affiliation(s)
- Rosemary J Jackson
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Bradley T Hyman
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA.
| | - Alberto Serrano-Pozo
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA.
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17
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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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18
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Ni X, Su H, Li GH, Li R, Lan R, Lv Y, Pang G, Zhang W, Yang Z, Hu C. Specific differences and novel key regulatory genes of sex in influencing exceptional longevity phenotypes. Diabetes Metab Syndr 2024; 18:103039. [PMID: 38762968 DOI: 10.1016/j.dsx.2024.103039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 05/08/2024] [Accepted: 05/10/2024] [Indexed: 05/21/2024]
Abstract
BACKGROUND AND AIMS Although the life expectancy of women systematically and robustly exceeds that of men, specific differences and molecular mechanisms of sex in influencing longevity phenotypes remain largely unknown. Therefore, we performed transcriptome sequencing of peripheral blood samples to explore regulatory mechanisms of healthy longevity by incorporating sex data. METHODS We selected 34 exceptional longevity (age: 98.26 ± 2.45 years) and 16 controls (age: 52.81 ± 9.78) without advanced outcomes from 1363 longevity and 692 controls recruited from Nanning of Guangxi for RNA sequencing 1. The transcriptome sequencing 1 data of 50 samples were compared by longevity and sex to screen differentially expressed genes (DEGs). Then, 121 aging samples (40-110 years old) without advanced outcomes from 355 longevity and 294 controls recruited from Dongxing of Guangxi were selected for RNA sequencing 2. The genes associated with aging from the transcriptome sequencing 2 of 121 aging samples were filtered out. Finally, the gender-related longevity candidate genes and their possible metabolic pathways were verified by cell model of aging and a real-time polymerase chain reaction (RT-PCR). RESULTS Metabolism differs between male and female and plays a key role in longevity. Moreover, the principal findings of this study revealed a novel key gene, UGT2B11, that plays an important role in regulating lipid metabolism through the peroxisome proliferator activated receptor gamma (PPARG) signalling pathway and ultimately improving lifespan, particularly in females. CONCLUSION The findings suggest specific differences in metabolism affecting exceptional longevity phenotypes between the sexes and offer novel therapeutic targets to extend lifespan by regulating lipid homeostasis.
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Affiliation(s)
- Xiaolin Ni
- Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Peking Union Medical College, Beijing, 100005, PR China; The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, 100730, PR China.
| | - Huabin Su
- Jiangbin Hospital, Guangxi Zhuang Autonomous Region, 530021, PR China
| | - Gong-Hua Li
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650201, PR China
| | - Rongqiao Li
- Jiangbin Hospital, Guangxi Zhuang Autonomous Region, 530021, PR China
| | - Rushu Lan
- Jiangbin Hospital, Guangxi Zhuang Autonomous Region, 530021, PR China
| | - Yuan Lv
- Jiangbin Hospital, Guangxi Zhuang Autonomous Region, 530021, PR China
| | - Guofang Pang
- Jiangbin Hospital, Guangxi Zhuang Autonomous Region, 530021, PR China
| | - Wei Zhang
- Jiangbin Hospital, Guangxi Zhuang Autonomous Region, 530021, PR China
| | - Ze Yang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, 100730, PR China.
| | - Caiyou Hu
- Jiangbin Hospital, Guangxi Zhuang Autonomous Region, 530021, PR China.
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19
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Zhao JV, Yao M, Liu Z. Using genetics and proteomics data to identify proteins causally related to COVID-19, healthspan and lifespan: a Mendelian randomization study. Aging (Albany NY) 2024; 16:6384-6416. [PMID: 38575325 PMCID: PMC11042960 DOI: 10.18632/aging.205711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 01/24/2024] [Indexed: 04/06/2024]
Abstract
BACKGROUND COVID-19 pandemic poses a heavy burden on public health and accounts for substantial mortality and morbidity. Proteins are building blocks of life, but specific proteins causally related to COVID-19, healthspan and lifespan have not been systematically examined. METHODS We conducted a Mendelian randomization study to assess the effects of 1,361 plasma proteins on COVID-19, healthspan and lifespan, using large GWAS of severe COVID-19 (up to 13,769 cases and 1,072,442 controls), COVID-19 hospitalization (32,519 cases and 2,062,805 controls) and SARS-COV2 infection (122,616 cases and 2,475,240 controls), healthspan (n = 300,477) and parental lifespan (~0.8 million of European ancestry). RESULTS We identified 35, 43, and 63 proteins for severe COVID, COVID-19 hospitalization, and SARS-COV2 infection, and 4, 32, and 19 proteins for healthspan, father's attained age, and mother's attained age. In addition to some proteins reported previously, such as SFTPD related to severe COVID-19, we identified novel proteins involved in inflammation and immunity (such as ICAM-2 and ICAM-5 which affect COVID-19 risk, CXCL9, HLA-DRA and LILRB4 for healthspan and lifespan), apoptosis (such as FGFR2 and ERBB4 which affect COVID-19 risk and FOXO3 which affect lifespan) and metabolism (such as PCSK9 which lowers lifespan). We found 2, 2 and 3 proteins shared between COVID-19 and healthspan/lifespan, such as CXADR and LEFTY2, shared between severe COVID-19 and healthspan/lifespan. Three proteins affecting COVID-19 and seven proteins affecting healthspan/lifespan are targeted by existing drugs. CONCLUSIONS Our study provided novel insights into protein targets affecting COVID-19, healthspan and lifespan, with implications for developing new treatment and drug repurposing.
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Affiliation(s)
- Jie V. Zhao
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong SAR, China
| | - Minhao Yao
- Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong SAR, China
| | - Zhonghua Liu
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
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Wu Y, Zhang CY, Liu X, Wang L, Li M, Li Y, Xiao X. Shared genetic architecture and causal relationship between sleep behaviors and lifespan. Transl Psychiatry 2024; 14:108. [PMID: 38388528 PMCID: PMC10883970 DOI: 10.1038/s41398-024-02826-x] [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: 07/18/2023] [Revised: 02/07/2024] [Accepted: 02/13/2024] [Indexed: 02/24/2024] Open
Abstract
Poor sleep health is associated with a wide array of increased risk for cardiovascular, metabolic and mental health problems as well as all-cause mortality in observational studies, suggesting potential links between sleep health and lifespan. However, it has yet to be determined whether sleep health is genetically or/and causally associated with lifespan. In this study, we firstly studied the genome-wide genetic association between four sleep behaviors (short sleep duration, long sleep duration, insomnia, and sleep chronotype) and lifespan using GWAS summary statistics, and both sleep duration time and insomnia were negatively correlated with lifespan. Then, two-sample Mendelian randomization (MR) and multivariable MR analyses were applied to explore the causal effects between sleep behaviors and lifespan. We found that genetically predicted short sleep duration was causally and negatively associated with lifespan in univariable and multivariable MR analyses, and this effect was partially mediated by coronary artery disease (CAD), type 2 diabetes (T2D) and depression. In contrast, we found that insomnia had no causal effects on lifespan. Our results further confirmed the negative effects of short sleep duration on lifespan and suggested that extension of sleep may benefit the physical health of individuals with sleep loss. Further attention should be given to such public health issues.
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Affiliation(s)
- Yong Wu
- Research Center for Mental Health and Neuroscience, Wuhan Mental Health Center, Wuhan, Hubei, China
- Affiliated Wuhan Mental Health Center, Jianghan University, Wuhan, Hubei, China
| | - Chu-Yi Zhang
- Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xiaolan Liu
- Research Center for Mental Health and Neuroscience, Wuhan Mental Health Center, Wuhan, Hubei, China
- Affiliated Wuhan Mental Health Center, Jianghan University, Wuhan, Hubei, China
| | - Lu Wang
- Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Ming Li
- Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Yi Li
- Research Center for Mental Health and Neuroscience, Wuhan Mental Health Center, Wuhan, Hubei, China.
- Affiliated Wuhan Mental Health Center, Jianghan University, Wuhan, Hubei, China.
- Research Center for Psychological and Health Sciences, China University of Geosciences, Wuhan, Hubei, China.
| | - Xiao Xiao
- Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China.
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21
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Lozupone M, Solfrizzi V, Sardone R, Dibello V, Castellana F, Zupo R, Lampignano L, Bortone I, Daniele A, Panza F. The epigenetics of frailty. Epigenomics 2024; 16:189-202. [PMID: 38112012 DOI: 10.2217/epi-2023-0279] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2023] Open
Abstract
The conceptual change of frailty, from a physical to a biopsychosocial phenotype, expanded the field of frailty, including social and behavioral domains with critical interaction between different frailty models. Environmental exposures - including physical exercise, psychosocial factors and diet - may play a role in the frailty pathophysiology. Complex underlying mechanisms involve the progressive interactions of genetics with epigenetics and of multimorbidity with environmental factors. Here we review the literature on possible mechanisms explaining the association between epigenetic hallmarks (i.e., global DNA methylation, DNA methylation age acceleration and microRNAs) and frailty, considered as biomarkers of aging. Frailty could be considered the result of environmental epigenetic factors on biological aging, caused by conflicting DNA methylation age and chronological age.
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Affiliation(s)
- Madia Lozupone
- Department of Translational Biomedicine & Neuroscience 'DiBraiN', University of Bari Aldo Moro, Bari, Italy
| | - Vincenzo Solfrizzi
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
| | | | - Vittorio Dibello
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
- Department of Orofacial Pain & Dysfunction, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam & Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Fabio Castellana
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
| | - Roberta Zupo
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
| | | | - Ilaria Bortone
- Department of Translational Biomedicine & Neuroscience 'DiBraiN', University of Bari Aldo Moro, Bari, Italy
| | - Antonio Daniele
- Department of Neuroscience, Catholic University of Sacred Heart, Rome, Italy
- Neurology Unit, IRCCS Fondazione Policlinico Universitario A. Gemelli, Rome, Italy
| | - Francesco Panza
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
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22
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Chen S, Zhang Z, Liu S, Chen T, Lu Z, Zhao W, Mou X, Liu S. Consistent signatures in the human gut microbiome of longevous populations. Gut Microbes 2024; 16:2393756. [PMID: 39197040 PMCID: PMC11364081 DOI: 10.1080/19490976.2024.2393756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 08/09/2024] [Accepted: 08/13/2024] [Indexed: 08/30/2024] Open
Abstract
Gut microbiota of centenarians has garnered significant attention in recent years, with most studies concentrating on the analysis of microbial composition. However, there is still limited knowledge regarding the consistent signatures of specific species and their biological functions, as well as the potential causal relationship between gut microbiota and longevity. To address this, we performed the fecal metagenomic analysis of eight longevous populations at the species and functional level, and employed the Mendelian randomization (MR) analysis to infer the causal associations between microbial taxa and longevity-related traits. We observed that several species including Eisenbergiella tayi, Methanobrevibacter smithii, Hungatella hathewayi, and Desulfovibrio fairfieldensis were consistently enriched in the gut microbiota of long-lived individuals compared to younger elderly and young adults across multiple cohorts. Analysis of microbial pathways and enzymes indicated that E. tayi plays a role in the protein N-glycosylation, while M. smithii is involved in the 3-dehydroquinate and chorismate biosynthesis. Furthermore, H. hathewayi makes a distinct contribution to the purine nucleobase degradation I pathway, potentially assisting the elderly in maintaining purine homeostasis. D. fairfieldensis contributes to the menaquinone (vitamin K2) biosynthesis, which may help prevent age-related diseases such as osteoporosis-induced fractures. According to MR results, Hungatella was significantly positively correlated with parental longevity, and Desulfovibrio also exhibited positive associations with lifespan and multiple traits related to parental longevity. Additionally, Alistipes and Akkermansia muciniphila were consistently enriched in the gut microbiota of the three largest cohorts of long-lived individuals, and MR analysis also suggests their potential causal relationships with longevity. Our findings reveal longevity-associated gut microbial signatures, which are informative for understanding the role of microbiota in regulating longevity and aging.
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Affiliation(s)
- Shu Chen
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
- Department of Pathology, the Seven Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Zhao Zhang
- Research and Development Center, Center of Human Microecology Engineering and Technology of Guangdong Province, Guangzhou, Guangdong, China
| | - Sanxin Liu
- Department of Neurology, the Third Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Tao Chen
- Research and Development Center, Center of Human Microecology Engineering and Technology of Guangdong Province, Guangzhou, Guangdong, China
| | - Zhengqi Lu
- Department of Neurology, the Third Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wenjing Zhao
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Xiangyu Mou
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Sheng Liu
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
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23
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Schooling CM, Kwok MK, Zhao JV. The relationship of fatty acids to ischaemic heart disease and lifespan in men and women using Mendelian randomization. Int J Epidemiol 2023; 52:1845-1852. [PMID: 37536998 DOI: 10.1093/ije/dyad108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 07/20/2023] [Indexed: 08/05/2023] Open
Abstract
BACKGROUND Observationally, polyunsaturated fatty acids (PUFAs) have health benefits compared with saturated fatty acids (SFAs); randomized controlled trials suggest fewer benefits. We used uni- and multi-variable Mendelian randomization to assess the association of major fatty acids and their sub-species with ischaemic heart disease (IHD) overall and sex-specifically and with lifespan sex-specifically, given differing lifespan by sex. METHODS We obtained strong (P <5x10-8), independent (r2<0.001) genetic predictors of fatty acids from genome-wide association studies (GWAS) in a random subset of 114 999 UK Biobank participants. We applied these genetic predictors to the Cardiogram IHD GWAS (cases = 60 801, controls = 123 504) and to the Finngen consortium GWAS (cases = 31 640, controls = 187 152) for replication and to the UK Biobank for sex-specific IHD and for lifespan based on parental attained age (fathers = 415 311, mothers = 412 937). We used sensitivity analysis and assessed sex differences where applicable. RESULTS PUFAs were associated with IHD [odds ratio 1.23, 95% confidence interval (CI) 1.05 to 1.44] and lifespan in men (-0.76 years, 95% CI -1.34 to -0.17) but not women (0.20, 95% CI -0.32 to 0.70). Findings were similar for omega-6 fatty acids and linoleic acid. Independent associations of SFAs, mono-unsaturated fatty acids or omega-3 fatty acids with IHD overall or lifespan in men and women were limited. CONCLUSIONS PUFAs, via specific subspecies, may contribute to disparities in lifespan by sex. Sex-specific dietary advice might be a start towards personalized public health and addressing inequities.
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Affiliation(s)
- C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
- City University of New York, Graduate School of Public Health and Health Policy, New York, NY, USA
| | - Man Ki Kwok
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Jie V Zhao
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
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24
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Liang Y, Luo S, Wong THT, He B, Schooling CM, Au Yeung SL. Association of iron homeostasis biomarkers in type 2 diabetes and glycaemic traits: a bidirectional two-sample Mendelian randomization study. Int J Epidemiol 2023; 52:1914-1925. [PMID: 37400992 DOI: 10.1093/ije/dyad093] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 06/14/2023] [Indexed: 07/05/2023] Open
Abstract
BACKGROUND Mendelian randomization (MR) studies show iron positively associated with type 2 diabetes (T2D) but included potentially biasing hereditary haemochromatosis variants and did not assess reverse causality. METHODS We assessed the relation of iron homeostasis with T2D and glycaemic traits bidirectionally, using genome-wide association studies (GWAS) of iron homeostasis biomarkers [ferritin, serum iron, total iron-binding capacity (TIBC), transferrin saturation (TSAT) (n ≤ 246 139)], T2D (DIAMANTE n = 933 970 and FinnGen n = 300 483), and glycaemic traits [fasting glucose (FG), 2-h glucose, glycated haemoglobin (HbA1c) and fasting insulin (FI) (n ≤ 209 605)]. Inverse variance weighting (IVW) was the main analysis, supplemented with sensitivity analyses and assessment of mediation by hepcidin. RESULTS Iron homeostasis biomarkers were largely unrelated to T2D, although serum iron was potentially associated with higher T2D [odds ratio: 1.07 per standard deviation; 95% confidence interval (CI): 0.99 to 1.16; P-value: 0.078) in DIAMANTE only. Higher ferritin, serum iron, TSAT and lower TIBC likely decreased HbA1c, but were not associated with other glycaemic traits. Liability to T2D likely increased TIBC (0.03 per log odds; 95% CI: 0.01 to 0.05; P-value: 0.005), FI likely increased ferritin (0.29 per log pmol/L; 95% CI: 0.12 to 0.47; P-value: 8.72 x 10-4). FG likely increased serum iron (0.06 per mmol/L; 95% CI: 0.001 to 0.12; P-value: 0.046). Hepcidin did not mediate these associations. CONCLUSION It is unlikely that ferritin, TSAT and TIBC cause T2D although an association for serum iron could not be excluded. Glycaemic traits and liability to T2D may affect iron homeostasis, but mediation by hepcidin is unlikely. Corresponding mechanistic studies are warranted.
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Affiliation(s)
- Ying Liang
- School of Public Health, LKS Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Shan Luo
- School of Public Health, LKS Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Tommy Hon Ting Wong
- School of Public Health, LKS Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Baoting He
- School of Public Health, LKS Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - C Mary Schooling
- School of Public Health, LKS Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
- School of Public Health and Health Policy, City University of New York, New York, NY, USA
| | - Shiu Lun Au Yeung
- School of Public Health, LKS Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
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25
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Kwok MK, Schooling CM. Unraveling Potential Sex-Specific Effects of Cardiovascular Medications on Longevity Using Mendelian Randomization. J Am Heart Assoc 2023; 12:e030943. [PMID: 38108247 PMCID: PMC10863757 DOI: 10.1161/jaha.123.030943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 10/18/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND Establishing the sex-specific efficacy of cardiovascular medications is pivotal to evidence-based clinical practice, potentially closing the gender gap in longevity. Trials large enough to establish sex differences are unavailable. This study evaluated sex-specific effects of commonly prescribed cardiovascular medications on lifespan. METHODS AND RESULTS In a two-sample Mendelian randomization study, established genetic variants mimicking effects of lipid-lowering drugs, antihypertensives, and diabetes drugs were applied to genetic associations with lifespan proxied by UK Biobank maternal (n=412 937) and paternal (n=415 311) attained age. Estimates were obtained using inverse variance weighting, with sensitivity analyses where possible. For lipid-lowering drugs, genetically mimicked PCSK9 (proprotein convertase subtilisin/kexin type 9) inhibitors were associated with longer lifespan, particularly in men (2.39 years per SD low-density lipoprotein cholesterol reduction [95% CI, 0.42-4.36], P for interaction=0.14). Genetically mimicked treatments targeting APOC3, LPL, or possibly LDLR were associated with longer lifespan in both sexes. For antihypertensives, genetically mimicked β-blockers and calcium channel blockers were associated with longer lifespan, particularly in men (P for interaction=0.17 for β-blockers and 0.31 for calcium channel blockers). For diabetes drugs, genetically mimicked metformin was associated with longer lifespan in both sexes. No associations were found for genetically mimicked statins, ezetimibe, or angiotensin-converting enzyme inhibitors. CONCLUSIONS PCSK9 inhibitors, β-blockers, and calcium channel blockers may prolong lifespan in the general population, particularly men. Treatments targeting APOC3, LPL, or LDLR and metformin may be relevant to both sexes. Whether other null findings are attributable to lack of efficacy requires investigation. Further investigation of repurposing should be conducted.
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Affiliation(s)
- Man Ki Kwok
- School of Nursing and Health Studies, Hong Kong Metropolitan UniversityHong KongChina
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong KongHong KongChina
| | - C. Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong KongHong KongChina
- City University of New York Graduate School of Public Health and Health PolicyNew YorkNY
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Chen H, Zhou X, Hu J, Li S, Wang Z, Zhu T, Cheng H, Zhang G. Genetic insights into the association of statin and newer nonstatin drug target genes with human longevity: a Mendelian randomization analysis. Lipids Health Dis 2023; 22:220. [PMID: 38082436 PMCID: PMC10714481 DOI: 10.1186/s12944-023-01983-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 12/01/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND It remains controversial whether the long-term use of statins or newer nonstatin drugs has a positive effect on human longevity. Therefore, this study aimed to investigate the genetic associations between different lipid-lowering therapeutic gene targets and human longevity. METHODS Two-sample Mendelian randomization analyses were conducted. The exposures comprised genetic variants that proxy nine drug target genes mimicking lipid-lowering effects (LDLR, HMGCR, PCKS9, NPC1L1, APOB, CETP, LPL, APOC3, and ANGPTL3). Two large-scale genome-wide association study (GWAS) summary datasets of human lifespan, including up to 500,193 European individuals, were used as outcomes. The inverse-variance weighting method was applied as the main approach. Sensitivity tests were conducted to evaluate the robustness, heterogeneity, and pleiotropy of the results. Causal effects were further validated using expression quantitative trait locus (eQTL) data. RESULTS Genetically proxied LDLR variants, which mimic the effects of lowering low-density lipoprotein cholesterol (LDL-C), were associated with extended lifespan. This association was replicated in the validation set and was further confirmed in the eQTL summary data of blood and liver tissues. Mediation analysis revealed that the genetic mimicry of LDLR enhancement extended lifespan by reducing the risk of major coronary heart disease, accounting for 22.8% of the mediation effect. The genetically proxied CETP and APOC3 inhibitions also showed causal effects on increased life expectancy in both outcome datasets. The lipid-lowering variants of HMGCR, PCKS9, LPL, and APOB were associated with longer lifespans but did not causally increase extreme longevity. No statistical evidence was detected to support an association between NPC1L1 and lifespan. CONCLUSION This study suggests that LDLR is a promising genetic target for human longevity. Lipid-related gene targets, such as PCSK9, CETP, and APOC3, might potentially regulate human lifespan, thus offering promising prospects for developing newer nonstatin therapies.
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Affiliation(s)
- Han Chen
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China.
- Branch of Health Promotion and Education, Jiangsu Anti-aging Association, Nanjing, People's Republic of China.
| | - Xiaoying Zhou
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China
| | - Jingwen Hu
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China
| | - Shuo Li
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China
| | - Zi Wang
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China
| | - Tong Zhu
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China
| | - Hong Cheng
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China
| | - Guoxin Zhang
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China.
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Hilsabeck TAU, Narayan VP, Wilson KA, Carrera E, Raftery D, Promislow D, Brem RB, Campisi J, Kapahi P. Systems biology and machine learning approaches identify metabolites that influence dietary lifespan and healthspan responses across flies and humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.09.548232. [PMID: 37503266 PMCID: PMC10369897 DOI: 10.1101/2023.07.09.548232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Dietary restriction (DR) is a potent method to enhance lifespan and healthspan, but individual responses are influenced by genetic variations. Understanding how metabolism-related genetic differences impact longevity and healthspan are unclear. To investigate this, we used metabolites as markers to reveal how different genotypes respond to diet to influence longevity and healthspan traits. We analyzed data from Drosophila Genetic Reference Panel strains raised under AL and DR conditions, combining metabolomic, phenotypic, and genome-wide information. Employing two computational methods across species-random forest modeling within the DGRP and Mendelian randomization in the UK Biobank-we pinpointed key traits with cross-species relevance that influence lifespan and healthspan. Notably, orotate was linked to parental age at death in humans and counteracted DR effects in flies, while threonine extended lifespan, in a strain- and sex-specific manner. Thus, utilizing natural genetic variation data from flies and humans, we employed a systems biology approach to elucidate potential therapeutic pathways and metabolomic targets for diet-dependent changes in lifespan and healthspan.
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Schooling CM, Fei K, Zhao JV. Selection bias as an explanation for the observed protective association of childhood adiposity with breast cancer. J Clin Epidemiol 2023; 164:104-111. [PMID: 37783402 DOI: 10.1016/j.jclinepi.2023.09.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 09/09/2023] [Accepted: 09/26/2023] [Indexed: 10/04/2023]
Abstract
OBJECTIVES Recalled childhood adiposity is inversely associated with breast cancer observationally, including in Mendelian randomization (MR) studies. Breast cancer studies recruited in adulthood only include survivors of childhood adiposity and breast cancer or a competing risk. We assessed recalled childhood adiposity on participant reported sibling and maternal breast cancer to ensure ascertainment of nonsurvivors. STUDY DESIGN AND SETTING We obtained independent strong genetic predictors of recalled childhood adiposity for women and their associations with participant reported own, sibling and maternal breast cancer from UK Biobank genome wide association studies. RESULTS Recalled childhood adiposity in women was inversely associated with own breast cancer using Mendelian randomization inverse variance weighting (odds ratio (OR) 0.66, 95% confidence interval (CI) 0.52-0.84) but less clearly related to participant reported sibling (OR 0.89, 95% CI 0.69-1.14) or maternal breast cancer (OR 0.84, 95% CI 0.67-1.05). CONCLUSION Weaker inverse associations of recalled childhood adiposity with breast cancer with more comprehensive ascertainment of cases before recruitment suggests the inverse association of recalled childhood adiposity with breast cancer could be partly selection bias from preferential selection of survivors. Greater consideration of survival bias in public health relevant causal inferences would be helpful.
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Affiliation(s)
- C Mary Schooling
- Environmental, Occupational, and Geospatial Health Sciences, CUNY School of Public Health, 55 West 125th St, New York, NY 10027, USA; School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong, China.
| | - Kezhen Fei
- Environmental, Occupational, and Geospatial Health Sciences, CUNY School of Public Health, 55 West 125th St, New York, NY 10027, USA
| | - Jie V Zhao
- School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong, China
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von Berg J, McArdle PF, Häppölä P, Haessler J, Kooperberg C, Lemmens R, Pezzini A, Thijs V, on behalf of SiGN, FinnGen, Women’s Health Initiative, Pulit SL, Kittner SJ, Mitchell BD, de Ridder J, van der Laan SW. Evidence of survival bias in the association between APOE-ϵ4 and age of ischemic stroke onset. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.01.23294385. [PMID: 38076909 PMCID: PMC10705635 DOI: 10.1101/2023.12.01.23294385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Large genome-wide association studies (GWAS) employing case-control study designs have now identified tens of loci associated with ischemic stroke (IS). As a complement to these studies, we performed GWAS in a case-only design to identify loci influencing age at onset (AAO) of ischemic stroke. Analyses were conducted in a Discovery cohort of 10,857 ischemic stroke cases using a linear regression framework. We meta-analyzed all SNPs with p-value < 1×10-5 in a sex-combined or sex-stratified analysis using summary data from two additional replication cohorts. In the women-only meta-analysis, we detected significant evidence for association of AAO with rs429358, an exonic variant in APOE that encodes for the APOE-ϵ4 allele. Each copy of the rs429358:T>C allele was associated with a 1.29 years earlier stroke AOO (meta p-value = 2.48×10-11). This APOE variant has previously been associated with increased mortality and ischemic stroke AAO. We hypothesized that the association with AAO may reflect a survival bias attributable to an age-related decline in mortality among APOE-ϵ4 carriers and have no association to stroke AAO per se. Using a simulation study, we found that a variant associated with overall mortality might indeed be detected with an AAO analysis. A variant with a two-fold increase on mortality risk would lead to an observed effect of AAO that is comparable to what we found. In conclusion, we detected a robust association of the APOE locus with stroke AAO and provided simulations to suggest that this association may be unrelated to ischemic stroke per se but related to a general survival bias.
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Affiliation(s)
- Joanna von Berg
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | - Patrick F. McArdle
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Paavo Häppölä
- Institute for Molecular Medicine Finland FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | | | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seatle, WA, USA
| | - Robin Lemmens
- University Hospitals Leuven, Department of Neurology, Leuven, Belgium
- KU Leuven - University of Leuven, Department of Neurosciences, Experimental Neurology, Leuven, Belgium
| | - Alessandro Pezzini
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Stroke Care Program, Department of Emergency, Parma University Hospital, Parma, Italy
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Vincent Thijs
- Stroke Theme, The Florey, Heidelberg, Victoria, Australia
- Department of Medicine, University of Melbourne, Victoria, Australia
- Department of Neurology, Austin Health, Heidelberg, Victoria, Australia
| | | | - Sara L. Pulit
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Steven J. Kittner
- Geriatric Research and Education Clinical Center, VA Maryland Health Care System, Baltimore, MD, USA
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Braxton D. Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatric Research and Education Clinical Center, VA Maryland Health Care System, Baltimore, MD, USA
| | - Jeroen de Ridder
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | - Sander W. van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Center of Population Health and Genomics, University of Virginia, Charlottesville, VA, USA
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30
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Zhu Y, Ryu S, Tare A, Barzilai N, Atzmon G, Suh Y. Targeted sequencing of the 9p21.3 region reveals association with reduced disease risks in Ashkenazi Jewish centenarians. Aging Cell 2023; 22:e13962. [PMID: 37605876 PMCID: PMC10577543 DOI: 10.1111/acel.13962] [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: 05/05/2023] [Revised: 07/22/2023] [Accepted: 08/01/2023] [Indexed: 08/23/2023] Open
Abstract
Genome-wide association studies (GWAS) have pinpointed the chromosomal locus 9p21.3 as a genetic hotspot for various age-related disorders. Common genetic variants in this locus are linked to multiple traits, including coronary artery diseases, cancers, and diabetes. Centenarians are known for their reduced risk and delayed onset of these conditions. To investigate whether this evasion of disease risks involves diminished genetic risks in the 9p21.3 locus, we sequenced this region in an Ashkenazi Jewish centenarian cohort (centenarians: n = 450, healthy controls: n = 500). Risk alleles associated with cancers, glaucoma, CAD, and T2D showed a significant depletion in centenarians. Furthermore, the risk and non-risk genotypes are linked to two distinct low-frequency variant profiles, enriched in controls and centenarians, respectively. Our findings provide evidence that the extreme longevity cohort is associated with collectively lower risks of multiple age-related diseases in the 9p21.3 locus.
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Affiliation(s)
- Yizhou Zhu
- Department of Obstetrics and GynecologyColumbia UniversityNew York CityNew YorkUSA
| | - Seungjin Ryu
- Department of Pharmacology, College of MedicineHallym UniversityChuncheonGangwonKorea
| | - Archana Tare
- Department of GeneticsAlbert Einstein College of MedicineBronxNew YorkUSA
| | - Nir Barzilai
- Department of GeneticsAlbert Einstein College of MedicineBronxNew YorkUSA
- Institute for Aging ResearchAlbert Einstein College of MedicineBronxNew YorkUSA
- Department of MedicineAlbert Einstein College of MedicineBronxNew YorkUSA
| | - Gil Atzmon
- Department of GeneticsAlbert Einstein College of MedicineBronxNew YorkUSA
- Department of MedicineAlbert Einstein College of MedicineBronxNew YorkUSA
- Department of Human Biology, Faculty of Natural SciencesUniversity of HaifaHaifaIsrael
| | - Yousin Suh
- Department of Obstetrics and GynecologyColumbia UniversityNew York CityNew YorkUSA
- Department of Genetics and DevelopmentColumbia UniversityNew York CityNew YorkUSA
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31
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Schwenke JM, Thorball CW, Schoepf IC, Ryom L, Hasse B, Lamy O, Calmy A, Wandeler G, Marzolini C, Kahlert CR, Bernasconi E, Kouyos RD, Günthard HF, Ledergerber B, Fellay J, Burkhalter F, Tarr PE. Association of a Polygenic Risk Score With Osteoporosis in People Living With HIV: The Swiss HIV Cohort Study. J Infect Dis 2023; 228:742-750. [PMID: 37225667 PMCID: PMC10503954 DOI: 10.1093/infdis/jiad179] [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: 02/10/2023] [Revised: 05/14/2023] [Accepted: 06/23/2023] [Indexed: 05/26/2023] Open
Abstract
BACKGROUND Bone mineral density (BMD) loss may be accelerated in people with HIV (PLWH). It is unknown whether a polygenic risk score (PRS) is associated with low BMD in PLWH. METHODS Swiss HIV Cohort Study participants of self-reported European descent underwent ≥2 per-protocol dual x-ray absorptiometry (DXA) measurements ≥2 years apart (2011-2020). Univariable and multivariable odds ratios (ORs) for DXA-defined osteoporosis were based on traditional and HIV-related risk factors and a genome-wide PRS built from 9413 single-nucleotide polymorphisms associated with low BMD in the general population. Controls were free from osteoporosis/osteopenia on all DXA measurements. RESULTS We included 438 participants: 149 with osteoporosis and 289 controls (median age, 53 years; 82% male, 95% with suppressed HIV RNA). Participants with unfavorable osteoporosis PRS (top vs bottom quintile) had univariable and multivariable-adjusted osteoporosis ORs of 4.76 (95% CI, 2.34-9.67) and 4.13 (1.86-9.18), respectively. For comparison, hepatitis C seropositivity, 5-year tenofovir disoproxil fumarate exposure, and parent history of hip fracture yielded univariable osteoporosis ORs of 2.26 (1.37-3.74), 1.84 (1.40-2.43), and 1.54 (0.82-2.9). CONCLUSIONS In PLWH in Switzerland, osteoporosis was independently associated with a BMD-associated PRS after adjustment for established risk factors, including exposure to tenofovir disoproxil fumarate.
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Affiliation(s)
- Johannes M Schwenke
- University Department of Medicine and Infectious Diseases Service, Kantonsspital Baselland, University of Basel, Bruderholz
| | - Christian W Thorball
- Precision Medicine Unit, Lausanne University Hospital, University of Lausanne
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne
| | - Isabella C Schoepf
- University Department of Medicine and Infectious Diseases Service, Kantonsspital Baselland, University of Basel, Bruderholz
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Switzerland
| | - Lene Ryom
- CHIP, Centre of Excellence for Health, Immunity and Infections, Rigshospitalet, University of Copenhagen
- Department of Infectious Diseases, Hvidovre University Hospital, Denmark
| | - Barbara Hasse
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich
| | - Olivier Lamy
- Bone Unit, Lausanne University Hospital, University of Lausanne
| | | | - Gilles Wandeler
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Switzerland
| | - Catia Marzolini
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel
| | | | - Enos Bernasconi
- Division of Infectious Diseases, Ospedale Regionale Lugano, University of Geneva and Università della Svizzera italiana, Lugano
| | - Roger D Kouyos
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich
- Institute of Medical Virology, University of Zurich
| | - Huldrych F Günthard
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich
- Institute of Medical Virology, University of Zurich
| | - Bruno Ledergerber
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich
| | - Jacques Fellay
- Precision Medicine Unit, Lausanne University Hospital, University of Lausanne
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne
| | - Felix Burkhalter
- University Department of Nephrology and Dialysis, Kantonsspital Baselland, University of Basel,Bruderholz, Switzerland
| | - Philip E Tarr
- University Department of Medicine and Infectious Diseases Service, Kantonsspital Baselland, University of Basel, Bruderholz
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32
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Rosoff DB, Mavromatis LA, Bell AS, Wagner J, Jung J, Marioni RE, Davey Smith G, Horvath S, Lohoff FW. Multivariate genome-wide analysis of aging-related traits identifies novel loci and new drug targets for healthy aging. NATURE AGING 2023; 3:1020-1035. [PMID: 37550455 PMCID: PMC10432278 DOI: 10.1038/s43587-023-00455-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 06/07/2023] [Indexed: 08/09/2023]
Abstract
The concept of aging is complex, including many related phenotypes such as healthspan, lifespan, extreme longevity, frailty and epigenetic aging, suggesting shared biological underpinnings; however, aging-related endpoints have been primarily assessed individually. Using data from these traits and multivariate genome-wide association study methods, we modeled their underlying genetic factor ('mvAge'). mvAge (effective n = ~1.9 million participants of European ancestry) identified 52 independent variants in 38 genomic loci. Twenty variants were novel (not reported in input genome-wide association studies). Transcriptomic imputation identified age-relevant genes, including VEGFA and PHB1. Drug-target Mendelian randomization with metformin target genes showed a beneficial impact on mvAge (P value = 8.41 × 10-5). Similarly, genetically proxied thiazolidinediones (P value = 3.50 × 10-10), proprotein convertase subtilisin/kexin 9 inhibition (P value = 1.62 × 10-6), angiopoietin-like protein 4, beta blockers and calcium channel blockers also had beneficial Mendelian randomization estimates. Extending the drug-target Mendelian randomization framework to 3,947 protein-coding genes prioritized 122 targets. Together, these findings will inform future studies aimed at improving healthy aging.
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Affiliation(s)
- Daniel B Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
- NIH-Oxford-Cambridge Scholars Program; Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Lucas A Mavromatis
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Andrew S Bell
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Josephin Wagner
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Jeesun Jung
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Steve Horvath
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- San Diego Institute of Science, Alto Labs, San Diego, CA, USA
| | - Falk W Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
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33
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Ng JCM, Schooling CM. Effect of basal metabolic rate on lifespan: a sex-specific Mendelian randomization study. Sci Rep 2023; 13:7761. [PMID: 37173352 PMCID: PMC10182013 DOI: 10.1038/s41598-023-34410-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 04/29/2023] [Indexed: 05/15/2023] Open
Abstract
Observationally, the association of basal metabolic rate (BMR) with mortality is mixed, although some ageing theories suggest that higher BMR should reduce lifespan. It remains unclear whether a causal association exists. In this one-sample Mendelian randomization study, we aimed to estimate the casual effect of BMR on parental attained age, a proxy for lifespan, using two-sample Mendelian randomization methods. We obtained genetic variants strongly (p-value < 5 × 10-8) and independently (r2 < 0.001) predicting BMR from the UK Biobank and applied them to a genome-wide association study of parental attained age based on the UK Biobank. We meta-analyzed genetic variant-specific Wald ratios using inverse-variance weighting with multiplicative random effects by sex, supplemented by sensitivity analysis. A total of 178 and 180 genetic variants predicting BMR in men and women were available for father's and mother's attained age, respectively. Genetically predicted BMR was inversely associated with father's and mother's attained age (years of life lost per unit increase in effect size of genetically predicted BMR, 0.46 and 1.36; 95% confidence interval 0.07-0.85 and 0.89-1.82), with a stronger association in women than men. In conclusion, higher BMR might reduce lifespan. The underlying pathways linking to major causes of death and relevant interventions warrant further investigation.
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Affiliation(s)
- Jack C M Ng
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
- Department of Environmental, Occupational, and Geospatial Health Sciences, Graduate School of Public Health and Health Policy, The City University of New York, 55 West 125th St, New York, NY, 10027, USA.
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34
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Menotti A, Puddu PE. Focus on age at death in field epidemiology. Aging Clin Exp Res 2023; 35:1187-1194. [PMID: 37145267 DOI: 10.1007/s40520-023-02416-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 04/12/2023] [Indexed: 05/06/2023]
Abstract
Age at death (AD) is an old metric recently re-evaluated for the study of longevity and mainly used in demography. Developed experience using AD in field epidemiology is summarized with cohorts followed-up for variable periods of time, frequently until extinction or close to extinction, a must to correctly adopt this metric. For practical purposes, a small number of examples is reported condensing previously published results to highlight various aspects of the problem. AD became the alternative of overall death rates when comparing cohorts reaching extinction or near extinction. AD was useful to characterize different causes of death in order to describe their natural history and possible etiology. With the use of multiple linear regression, a large number of possible determinants of AD were identified and some combinations of them resulted in large estimated differences in AD of 10 years or more across individuals. AD is a powerful tool to study population samples followed-up until extinction or near extinction. It allows to compare the life-long experience of different populations, to compare the role of different causes of death and to study the determinants of AD that are conditioning longevity.
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35
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Hamilton F, Mentzer AJ, Parks T, Baillie JK, Smith GD, Ghazal P, Timpson NJ. Variation in ERAP2 has opposing effects on severe respiratory infection and autoimmune disease. Am J Hum Genet 2023; 110:691-702. [PMID: 36889308 PMCID: PMC10119032 DOI: 10.1016/j.ajhg.2023.02.008] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 02/06/2023] [Indexed: 03/09/2023] Open
Abstract
ERAP2 is an aminopeptidase involved in immunological antigen presentation. Genotype data in human samples from before and after the Black Death, an epidemic due to Yersinia pestis, have marked changes in allele frequency of the single-nucleotide polymorphism (SNP) rs2549794, with the T allele suggested to be deleterious during this period, while ERAP2 is also implicated in autoimmune diseases. This study explored the association between variation at ERAP2 and (1) infection, (2) autoimmune disease, and (3) parental longevity. Genome-wide association studies (GWASs) of these outcomes were identified in contemporary cohorts (UK Biobank, FinnGen, and GenOMICC). Effect estimates were extracted for rs2549794 and rs2248374, a haplotype tagging SNP. Additionally, cis expression and protein quantitative trait loci (QTLs) for ERAP2 were used in Mendelian randomization (MR) analyses. Consistent with decreased survival in the Black Death, the T allele of rs2549794 showed evidence of association with respiratory infection (odds ratio; OR for pneumonia 1.03; 95% CI 1.01-1.05). Effect estimates were larger for more severe phenotypes (OR for critical care admission with pneumonia 1.08; 95% CI 1.02-1.14). In contrast, opposing effects were identified for Crohn disease (OR 0.86; 95% CI 0.82-0.90). This allele was shown to associate with decreased ERAP2 expression and protein levels, independent of haplotype. MR analyses suggest that ERAP2 expression may be mediating disease associations. Decreased ERAP2 expression is associated with severe respiratory infection with an opposing association with autoimmune diseases. These data support the hypothesis of balancing selection at this locus driven by autoimmune and infectious disease.
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Affiliation(s)
- Fergus Hamilton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Infection Science, North Bristol NHS Trust, Bristol, UK.
| | | | - Tom Parks
- Wellcome Centre For Human Genetics, University of Oxford, Oxford, UK; Department of Infectious Disease, Imperial College London, London, UK
| | - J Kenneth Baillie
- Baillie Gifford Pandemic Science Hub, Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK; Roslin Institute, University of Edinburgh, Edinburgh, UK; Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, UK
| | | | | | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Posis AIB, Bellettiere J, Salem RM, LaMonte MJ, Manson JE, Casanova R, LaCroix AZ, Shadyab AH. Associations of Accelerometer-Measured Physical Activity and Sedentary Time With All-Cause Mortality by Genetic Predisposition for Longevity. J Aging Phys Act 2023; 31:265-275. [PMID: 36002033 PMCID: PMC9950283 DOI: 10.1123/japa.2022-0067] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 07/08/2022] [Accepted: 07/20/2022] [Indexed: 11/18/2022]
Abstract
The goal of this study was to examine associations between accelerometer-measured physical activity (PA) and sedentary time (ST) with mortality by a genetic risk score (GRS) for longevity. Among 5,446 women, (mean [SD]: age, 78.2 [6.6] years), 1,022 deaths were observed during 33,350 person-years of follow-up. Using multivariable Cox proportional hazards models, higher light PA and moderate to vigorous PA were associated with lower mortality across all GRS for longevity categories (low/medium/high; all ptrend < .001). Higher ST was associated with higher mortality (ptrend across all GRS categories < .001). Interaction tests for PA and ST with the GRS were not statistically significant. Findings support the importance of higher PA and lower ST for reducing mortality risk in older women, regardless of genetic predisposition for longevity.
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Affiliation(s)
- Alexander Ivan B. Posis
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
- School of Public Health, San Diego State University, San Diego, CA, USA
| | - John Bellettiere
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Rany M. Salem
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Michael J. LaMonte
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, State University of New York at Buffalo, Buffalo, NY, USA
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, MA, USA
| | - Ramon Casanova
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston Salem, NC, USA
| | - Andrea Z. LaCroix
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Aladdin H. Shadyab
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
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37
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Shared genetic architecture between attention-deficit/hyperactivity disorder and lifespan. Neuropsychopharmacology 2023; 48:981-990. [PMID: 36906694 PMCID: PMC10209393 DOI: 10.1038/s41386-023-01555-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 02/03/2023] [Accepted: 02/20/2023] [Indexed: 03/13/2023]
Abstract
There is evidence linking ADHD to a reduced life expectancy. The mortality rate in individuals with ADHD is twice that of the general population and it is associated with several factors, such as unhealthy lifestyle behaviors, social adversity, and mental health problems that may in turn increase mortality rates. Since ADHD and lifespan are heritable, we used data from genome-wide association studies (GWAS) of ADHD and parental lifespan, as proxy of individual lifespan, to estimate their genetic correlation, identify genetic loci jointly associated with both phenotypes and assess causality. We confirmed a negative genetic correlation between ADHD and parental lifespan (rg = -0.36, P = 1.41e-16). Nineteen independent loci were jointly associated with both ADHD and parental lifespan, with most of the alleles that increased the risk for ADHD being associated with shorter lifespan. Fifteen loci were novel for ADHD and two were already present in the original GWAS on parental lifespan. Mendelian randomization analyses pointed towards a negative causal effect of ADHD liability on lifespan (P = 1.54e-06; Beta = -0.07), although these results were not confirmed by all sensitivity analyses performed, and further evidence is required. The present study provides the first evidence of a common genetic background between ADHD and lifespan, which may play a role in the reported effect of ADHD on premature mortality risk. These results are consistent with previous epidemiological data describing reduced lifespan in mental disorders and support that ADHD is an important health condition that could negatively affect future life outcomes.
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38
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Akiyama M, Sakaue S, Takahashi A, Ishigaki K, Hirata M, Matsuda K, Momozawa Y, Okada Y, Ninomiya T, The Biobank Japan project KoidoMasaru13MorisakiTakayuki11NagaiAkiko14SagiyaYoji15, Terao C, Murakami Y, Kubo M, Kamatani Y. Genome-wide association study reveals BET1L associated with survival time in the 137,693 Japanese individuals. Commun Biol 2023; 6:143. [PMID: 36737517 PMCID: PMC9898503 DOI: 10.1038/s42003-023-04491-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Accepted: 01/17/2023] [Indexed: 02/05/2023] Open
Abstract
Human lifespan is reported to be heritable. Although previous genome-wide association studies (GWASs) have identified several loci, a limited number of studies have assessed the genetic associations with the real survival information on the participants. We conducted a GWAS to identify loci associated with survival time in the Japanese individuals participated in the BioBank Japan Project by carrying out sex-stratified GWASs involving 78,029 males and 59,664 females. Of them, 31,324 (22.7%) died during the mean follow-up period of 7.44 years. We found a novel locus associated with survival (BET1L; P = 5.89 × 10-9). By integrating with eQTL data, we detected a significant overlap with eQTL of BET1L in skeletal muscle. A gene-set enrichment analysis showed that genes related to the BCAR1 protein-protein interaction subnetwork influence survival time (P = 1.54 × 10-7). These findings offer the candidate genes and biological mechanisms associated with human lifespan.
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Affiliation(s)
- Masato Akiyama
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.177174.30000 0001 2242 4849Department of Ocular Pathology and Imaging Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, 812-8582 Japan
| | - Saori Sakaue
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.136593.b0000 0004 0373 3971Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871 Japan
| | - Atsushi Takahashi
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.410796.d0000 0004 0378 8307Department of Genomic Medicine, Research Institute, National Cerebral and Cardiovascular Center, Osaka, 564-8565 Japan
| | - Kazuyoshi Ishigaki
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan
| | - Makoto Hirata
- grid.26999.3d0000 0001 2151 536XLaboratory of Genome Technology, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, 108-8639 Japan
| | - Koichi Matsuda
- grid.26999.3d0000 0001 2151 536XLaboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, The University of Tokyo, Tokyo, 108-8639 Japan
| | - Yukihide Momozawa
- grid.509459.40000 0004 0472 0267Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan
| | - Yukinori Okada
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.136593.b0000 0004 0373 3971Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan
| | - Toshiharu Ninomiya
- grid.177174.30000 0001 2242 4849Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Fukuoka, 812-8582 Japan
| | | | - Chikashi Terao
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan
| | - Yoshinori Murakami
- grid.26999.3d0000 0001 2151 536XDivision of Molecular Pathology, The Institute of Medical Science, The University of Tokyo, Tokyo, 108-8639 Japan
| | - Michiaki Kubo
- grid.509459.40000 0004 0472 0267RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan. .,Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan. .,Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, 108-8639, Japan.
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Genetic scores for predicting longevity in the Croatian oldest-old population. PLoS One 2023; 18:e0279971. [PMID: 36735720 PMCID: PMC9897585 DOI: 10.1371/journal.pone.0279971] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 12/19/2022] [Indexed: 02/04/2023] Open
Abstract
Longevity is a hallmark of successful ageing and a complex trait with a significant genetic component. In this study, 43 single nucleotide polymorphisms (SNPs) were chosen from the literature and genotyped in a Croatian oldest-old sample (85+ years, sample size (N) = 314), in order to determine whether any of these SNPs have a significant effect on reaching the age thresholds for longevity (90+ years, N = 212) and extreme longevity (95+ years, N = 84). The best models were selected for both survival ages using multivariate logistic regression. In the model for reaching age 90, nine SNPs explained 20% of variance for survival to that age, while the 95-year model included five SNPs accounting for 9.3% of variance. The two SNPs that showed the most significant association (p ≤ 0.01) with longevity were TERC rs16847897 and GHRHR rs2267723. Unweighted and weighted Genetic Longevity Scores (uGLS and wGLS) were calculated and their predictive power was tested. All four scores showed significant correlation with age at death (p ≤ 0.01). They also passed the ROC curve test with at least 50% predictive ability, but wGLS90 stood out as the most accurate score, with a 69% chance of accurately predicting survival to the age of 90.
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Schoepf IC, Thorball CW, Kovari H, Ledergerber B, Buechel RR, Calmy A, Weber R, Kaufmann PA, Nkoulou R, Schwenke JM, Braun DL, Fellay J, Tarr PE. Polygenic Risk Scores for Prediction of Subclinical Coronary Artery Disease in Persons With Human Immunodeficiency Virus (HIV): The Swiss HIV Cohort Study. Clin Infect Dis 2023; 76:48-56. [PMID: 36097729 DOI: 10.1093/cid/ciac758] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 08/16/2022] [Accepted: 09/08/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND In people with human immunodeficiency virus (HIV) (PWH), individual polygenic risk scores (PRSs) are associated with coronary artery disease (CAD) events. Whether PRSs are associated with subclinical CAD is unknown. METHODS In Swiss HIV Cohort Study participants of European descent, we defined subclinical CAD as presence of soft, mixed, or high-risk plaque (SMHRP) on coronary computed tomography (CT) angiography, or as participants in the top tertile of the study population's coronary artery calcium (CAC) score, using noncontrast CT. We obtained univariable and multivariable odds ratios (ORs) for subclinical CAD endpoints based on nongenetic risk factors, and validated genome-wide PRSs built from single nucleotide polymorphisms associated with CAD, carotid intima-media thickness (IMT), or longevity in the general population. RESULTS We included 345 genotyped participants (median age, 53 years; 89% male; 96% suppressed HIV RNA); 172 and 127 participants had SMHRP and CAC, respectively. CAD-associated PRS and IMT-associated PRS were associated with SMHRP and CAC (all P < .01), but longevity PRS was not. Participants with unfavorable CAD-PRS (top quintile) had an adjusted SMHRP OR = 2.58 (95% confidence interval [CI], 1.18-5.67), and a CAC OR = 3.95 (95% CI, 1.45-10.77) vs. bottom quintile. Unfavorable nongenetic risk (top vs. bottom quintile) was associated with adjusted SMHRP OR = 24.01 (95% CI, 9.75-59.11), and a CAC-OR = 65.07 (95% CI, 18.48-229.15). Area under the receiver operating characteristic curve increased when we added CAD-PRS to nongenetic risk factors (SMHRP: 0.75 and 0.78, respectively; CAC: 0.80 and 0.83, respectively). CONCLUSIONS In Swiss PWH, subclinical CAD is independently associated with an individual CAD-associated PRS. Combining nongenetic and genetic cardiovascular risk factors provided the most powerful subclinical CAD prediction.
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Affiliation(s)
- Isabella C Schoepf
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland.,Hepatology, Department for Visceral Surgery and Medicine, Bern University Hospital, University of Bern, Bern, Switzerland.,University Department of Medicine and Infectious Diseases Service, Kantonsspital Baselland, University of Basel, Bruderholz, Switzerland
| | - Christian W Thorball
- Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Helen Kovari
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Bruno Ledergerber
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Ronny R Buechel
- Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Alexandra Calmy
- Division of Infectious Disease, Geneva University Hospital, Geneva, Switzerland
| | - Rainer Weber
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Philipp A Kaufmann
- Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - René Nkoulou
- Division of Cardiology, University Hospital Geneva, University of Geneva, Geneva, Switzerland
| | - Johannes M Schwenke
- University Department of Medicine and Infectious Diseases Service, Kantonsspital Baselland, University of Basel, Bruderholz, Switzerland
| | - Dominique L Braun
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Jacques Fellay
- Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Philip E Tarr
- University Department of Medicine and Infectious Diseases Service, Kantonsspital Baselland, University of Basel, Bruderholz, Switzerland
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Libiseller-Egger J, Phelan JE, Attia ZI, Benavente ED, Campino S, Friedman PA, Lopez-Jimenez F, Leon DA, Clark TG. Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes. Sci Rep 2022; 12:22625. [PMID: 36587059 PMCID: PMC9805465 DOI: 10.1038/s41598-022-27254-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 12/28/2022] [Indexed: 01/01/2023] Open
Abstract
Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age ("delta age") to be associated with mortality and co-morbidities. However, despite being crucial for understanding underlying individual risk, the genetic underpinning of delta age is unknown. In this work we performed a genome-wide association study using UK Biobank data (n=34,432) and identified eight loci associated with delta age ([Formula: see text]), including genes linked to cardiovascular disease (CVD) (e.g. SCN5A) and (heart) muscle development (e.g. TTN). Our results indicate that the genetic basis of cardiovascular ageing is predominantly determined by genes directly involved with the cardiovascular system rather than those connected to more general mechanisms of ageing. Our insights inform the epidemiology of CVD, with implications for preventative and precision medicine.
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Affiliation(s)
- Julian Libiseller-Egger
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Jody E Phelan
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Zachi I Attia
- Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Ernest Diez Benavente
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Susana Campino
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Paul A Friedman
- Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, MN, USA
| | | | - David A Leon
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
- Department of Community Medicine, UiT the Arctic University of Norway, Tromsø, Norway
| | - Taane G Clark
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
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42
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Kunizheva SS, Volobaev VP, Plotnikova MY, Kupriyanova DA, Kuznetsova IL, Tyazhelova TV, Rogaev EI. Current Trends and Approaches to the Search for Genetic Determinants of Aging and Longevity. RUSS J GENET+ 2022; 58:1427-1443. [PMID: 36590179 PMCID: PMC9794410 DOI: 10.1134/s1022795422120067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 07/06/2022] [Accepted: 07/07/2022] [Indexed: 12/29/2022]
Abstract
Aging is a natural process of extinction of the body and the main aspect that determines the life expectancy for individuals who have survived to the post-reproductive period. The process of aging is accompanied by certain physiological, immune, and metabolic changes in the body, as well as the development of age-related diseases. The contribution of genetic factors to human life expectancy is estimated at about 25-30%. Despite the success in identifying genes and metabolic pathways that may be involved in the life extension process in model organisms, the key question remains to what extent these data can be extrapolated to humans, for example, because of the complexity of its biological and sociocultural systems, as well as possible species differences in life expectancy and causes of mortality. New molecular genetic methods have significantly expanded the possibilities for searching for genetic factors of human life expectancy and identifying metabolic pathways of aging, the interaction of genes and transcription factors, the regulation of gene expression at the level of transcription, and epigenetic modifications. The review presents the latest research and current strategies for studying the genetic basis of human aging and longevity: the study of individual candidate genes in genetic population studies, variations identified by the GWAS method, immunogenetic differences in aging, and genomic studies to identify factors of "healthy aging." Understanding the mechanisms of the interaction between factors affecting the life expectancy and the possibility of their regulation can become the basis for developing comprehensive measures to achieve healthy longevity. Supplementary Information The online version contains supplementary material available at 10.1134/S1022795422120067.
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Affiliation(s)
- S. S. Kunizheva
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
- Moscow State University, 119234 Moscow, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | - V. P. Volobaev
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
| | - M. Yu. Plotnikova
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
- Moscow State University, 119234 Moscow, Russia
| | - D. A. Kupriyanova
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
| | - I. L. Kuznetsova
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | - T. V. Tyazhelova
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | - E. I. Rogaev
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
- Moscow State University, 119234 Moscow, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
- University of Massachusetts Chan Medical School, 01545 Shrewsbury, MA United States
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Erdman VV, Karimov DD, Tuktarova IA, Timasheva YR, Nasibullin TR, Korytina GF. Alu Deletions in LAMA2 and CDH4 Genes Are Key Components of Polygenic Predictors of Longevity. Int J Mol Sci 2022; 23:13492. [PMID: 36362280 PMCID: PMC9657309 DOI: 10.3390/ijms232113492] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 10/27/2022] [Accepted: 10/31/2022] [Indexed: 10/18/2023] Open
Abstract
Longevity is a unique human phenomenon and a highly stable trait, characterized by polygenicity. The longevity phenotype occurs due to the ability to successfully withstand the age-related genomic instability triggered by Alu elements. The purpose of our cross-sectional study was to evaluate the combined contribution of ACE*Ya5ACE, CDH4*Yb8NBC516, COL13A1*Ya5ac1986, HECW1*Ya5NBC182, LAMA2*Ya5-MLS19, PLAT*TPA25, PKHD1L1*Yb8AC702, SEMA6A*Yb8NBC597, STK38L*Ya5ac2145 and TEAD1*Ya5ac2013 Alu elements to longevity. The study group included 2054 unrelated individuals aged from 18 to 113 years who are ethnic Tatars from Russia. We analyzed the dynamics of the allele and genotype frequencies of the studied Alu polymorphic loci in the age groups of young (18-44 years old), middle-aged (45-59 years old), elderly (60-74 years old), old seniors (75-89 years old) and long-livers (90-113 years old). Most significant changes in allele and genotype frequencies were observed between the long-livers and other groups. The search for polygenic predictors of longevity was performed using the APSampler program. Attaining longevity was associated with the combinations LAMA2*ID + CDH4*D (OR = 2.23, PBonf = 1.90 × 10-2) and CDH4*DD + LAMA2*ID + HECW1*D (OR = 4.58, PBonf = 9.00 × 10-3) among persons aged between 18 and 89 years, LAMA2*ID + CDH4*D + SEMA6A*I for individuals below 75 years of age (OR = 3.13, PBonf = 2.00 × 10-2), LAMA2*ID + HECW1*I for elderly people aged 60 and older (OR = 3.13, PBonf = 2.00 × 10-2) and CDH4*DD + LAMA2*D + HECW1*D (OR = 4.21, PBonf = 2.60 × 10-2) and CDH4*DD + LAMA2*D + ACE*I (OR = 3.68, PBonf = 1.90 × 10-2) among old seniors (75-89 years old). The key elements of combinations associated with longevity were the deletion alleles of CDH4 and LAMA2 genes. Our results point to the significance for human longevity of the Alu polymorphic loci in CDH4, LAMA2, HECW1, SEMA6A and ACE genes, involved in the integration systems.
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Affiliation(s)
- Vera V. Erdman
- Institute of Biochemistry and Genetics, Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences, 450054 Ufa, Russia
| | - Denis D. Karimov
- Ufa Research Institute of Labor Medicine and Human Ecology, 450106 Ufa, Russia
| | - Ilsia A. Tuktarova
- Institute of Biochemistry and Genetics, Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences, 450054 Ufa, Russia
| | - Yanina R. Timasheva
- Institute of Biochemistry and Genetics, Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences, 450054 Ufa, Russia
| | - Timur R. Nasibullin
- Institute of Biochemistry and Genetics, Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences, 450054 Ufa, Russia
| | - Gulnaz F. Korytina
- Institute of Biochemistry and Genetics, Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences, 450054 Ufa, Russia
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44
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Yang G, Au Yeung SL, Schooling CM. Sex differences in the association of fasting glucose with HbA1c, and their consequences for mortality: A Mendelian randomization study. EBioMedicine 2022; 84:104259. [PMID: 36179552 PMCID: PMC9520189 DOI: 10.1016/j.ebiom.2022.104259] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/18/2022] [Accepted: 08/28/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Hemoglobin A1c (HbA1c) is used for diabetes diagnosis and management. HbA1c also represents iron-related erythrocyte properties which differ by sex. We investigated erythrocyte properties on HbA1c and glucose, and whether corresponding consequences for mortality differed by sex. METHODS In this two-sample Mendelian randomization study using the largest publicly available European descent summary statistics, we assessed sex-specific associations of iron (n=163,511) and hemoglobin (188,076 women/162,398 men) with HbA1c (185,022 women/159,160 men) and fasting glucose (73,089 women/67,506 men), of fasting glucose with HbA1c and diabetes (cases=6,589 women/10,686 men, controls=187,137 women/155,780 men), and of fasting glucose (n=140,595), HbA1c (n=146,806) and liability to diabetes (74,124 cases/824,006 controls) with parental attained age (412,937 mothers/415,311 fathers). FINDINGS Iron and hemoglobin were inversely associated with HbA1c but not fasting glucose. Fasting glucose was more strongly associated with HbA1c and diabetes in women (1.65 standard deviation (SD) per mmol/L [95% confidence interval 1.58, 1.72]; odds ratio (OR) 7.36 per mmol/L [4.12, 10.98]) than men (0.89 [0.81, 0.98]; OR 2.79 [1.96, 4.98]). The inverse associations of HbA1c and liability to diabetes with lifespan were possibly stronger in men (-1.80 years per percentage [-2.77, -0.42]; -0.93 years per logOR [-1.23, -0.59]) than women (-0.80 [-2.69, 0.66]; -0.44 [-0.62, -0.26]). INTERPRETATION HbA1c underestimates fasting glucose in men compared with women, possibly due to erythrocyte properties. Whether HbA1c and liability to diabetes reduce lifespan more in men than women because diagnostic and management criteria involving HbA1c mean that glycemia in men is under-treated compared to women needs urgent investigation. FUNDING None.
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Affiliation(s)
- Guoyi Yang
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Shiu Lun Au Yeung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Catherine Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China; Graduate School of Public Health and Health Policy, City University of New York, New York, United States.
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45
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Deak JD, Zhou H, Galimberti M, Levey DF, Wendt FR, Sanchez-Roige S, Hatoum AS, Johnson EC, Nunez YZ, Demontis D, Børglum AD, Rajagopal VM, Jennings MV, Kember RL, Justice AC, Edenberg HJ, Agrawal A, Polimanti R, Kranzler HR, Gelernter J. Genome-wide association study in individuals of European and African ancestry and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci. Mol Psychiatry 2022; 27:3970-3979. [PMID: 35879402 PMCID: PMC9718667 DOI: 10.1038/s41380-022-01709-1] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 07/08/2022] [Indexed: 02/07/2023]
Abstract
Despite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci. We performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) ancestry, optimizing genetic informativeness by performing MTAG (Multi-trait analysis of GWAS) with genetically correlated substance use disorders (SUDs). Meta-analysis included seven cohorts: the Million Veteran Program, Psychiatric Genomics Consortium, iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total N = 639,063 (Ncases = 20,686;Neffective = 77,026) across ancestries. OUD cases were defined as having a lifetime OUD diagnosis, and controls as anyone not known to meet OUD criteria. We estimated SNP-heritability (h2SNP) and genetic correlations (rg). Based on genetic correlation, we performed MTAG on OUD, alcohol use disorder (AUD), and cannabis use disorder (CanUD). A leave-one-out polygenic risk score (PRS) analysis was performed to compare OUD and OUD-MTAG PRS as predictors of OUD case status in Yale-Penn 3. The EUR meta-analysis identified three genome-wide significant (GWS; p ≤ 5 × 10-8) lead SNPs-one at FURIN (rs11372849; p = 9.54 × 10-10) and two OPRM1 variants (rs1799971, p = 4.92 × 10-09; rs79704991, p = 1.11 × 10-08; r2 = 0.02). Rs1799971 (p = 4.91 × 10-08) and another OPRM1 variant (rs9478500; p = 1.95 × 10-08; r2 = 0.03) were identified in the cross-ancestry meta-analysis. Estimated h2SNP was 12.75%, with strong rg with CanUD (rg = 0.82; p = 1.14 × 10-47) and AUD (rg = 0.77; p = 6.36 × 10-78). The OUD-MTAG resulted in a GWAS Nequivalent = 128,748 and 18 independent GWS loci, some mapping to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes. The OUD-MTAG PRS accounted for 3.81% of OUD variance (beta = 0.61;s.e. = 0.066; p = 2.00 × 10-16) compared to 2.41% (beta = 0.45; s.e. = 0.058; p = 2.90 × 10-13) explained by the OUD PRS. The current study identified OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. The genetic architecture of OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.
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Affiliation(s)
- Joseph D Deak
- Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Hang Zhou
- Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Marco Galimberti
- Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Daniel F Levey
- Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Frank R Wendt
- Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Sandra Sanchez-Roige
- University of California San Diego, La Jolla, CA, USA
- Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Emma C Johnson
- Washington University St. Louis Medical School, St. Louis, MO, USA
| | - Yaira Z Nunez
- Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Ditte Demontis
- Biomedicine, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Anders D Børglum
- Biomedicine, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Veera M Rajagopal
- Biomedicine, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | | | - Rachel L Kember
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Amy C Justice
- Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | | | - Arpana Agrawal
- Washington University St. Louis Medical School, St. Louis, MO, USA
| | - Renato Polimanti
- Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Henry R Kranzler
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Joel Gelernter
- Yale School of Medicine, New Haven, CT, USA.
- VA Connecticut Healthcare Center, West Haven, CT, USA.
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Torres GG, Dose J, Hasenbein TP, Nygaard M, Krause-Kyora B, Mengel-From J, Christensen K, Andersen-Ranberg K, Kolbe D, Lieb W, Laudes M, Görg S, Schreiber S, Franke A, Caliebe A, Kuhlenbäumer G, Nebel A. Long-Lived Individuals Show a Lower Burden of Variants Predisposing to Age-Related Diseases and a Higher Polygenic Longevity Score. Int J Mol Sci 2022; 23:10949. [PMID: 36142858 PMCID: PMC9504529 DOI: 10.3390/ijms231810949] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/05/2022] [Accepted: 09/07/2022] [Indexed: 11/22/2022] Open
Abstract
Longevity is a complex phenotype influenced by both environmental and genetic factors. The genetic contribution is estimated at about 25%. Despite extensive research efforts, only a few longevity genes have been validated across populations. Long-lived individuals (LLI) reach extreme ages with a relative low prevalence of chronic disability and major age-related diseases (ARDs). We tested whether the protection from ARDs in LLI can partly be attributed to genetic factors by calculating polygenic risk scores (PRSs) for seven common late-life diseases (Alzheimer's disease (AD), atrial fibrillation (AF), coronary artery disease (CAD), colorectal cancer (CRC), ischemic stroke (ISS), Parkinson's disease (PD) and type 2 diabetes (T2D)). The examined sample comprised 1351 German LLI (≥94 years, including 643 centenarians) and 4680 German younger controls. For all ARD-PRSs tested, the LLI had significantly lower scores than the younger control individuals (areas under the curve (AUCs): ISS = 0.59, p = 2.84 × 10-35; AD = 0.59, p = 3.16 × 10-25; AF = 0.57, p = 1.07 × 10-16; CAD = 0.56, p = 1.88 × 10-12; CRC = 0.52, p = 5.85 × 10-3; PD = 0.52, p = 1.91 × 10-3; T2D = 0.51, p = 2.61 × 10-3). We combined the individual ARD-PRSs into a meta-PRS (AUC = 0.64, p = 6.45 × 10-15). We also generated two genome-wide polygenic scores for longevity, one with and one without the TOMM40/APOE/APOC1 gene region (AUC (incl. TOMM40/APOE/APOC1) = 0.56, p = 1.45 × 10-5, seven variants; AUC (excl. TOMM40/APOE/APOC1) = 0.55, p = 9.85 × 10-3, 10,361 variants). Furthermore, the inclusion of nine markers from the excluded region (not in LD with each other) plus the APOE haplotype into the model raised the AUC from 0.55 to 0.61. Thus, our results highlight the importance of TOMM40/APOE/APOC1 as a longevity hub.
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Affiliation(s)
- Guillermo G. Torres
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Janina Dose
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Tim P. Hasenbein
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
- Department of Neurology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Str. 3, 24105 Kiel, Germany
- Institute of Pharmacology and Toxicology, Technical University Munich, Biedersteiner Str. 29, 80802 Munich, Germany
| | - Marianne Nygaard
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, J.B. Winsloews Vej 4, 5000 Odense, Denmark
| | - Ben Krause-Kyora
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Jonas Mengel-From
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, J.B. Winsloews Vej 4, 5000 Odense, Denmark
| | - Kaare Christensen
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, J.B. Winsloews Vej 4, 5000 Odense, Denmark
- Department of Clinical Biochemistry, Odense University Hospital, Kløvervænget 47, 5000 Odense, Denmark
| | - Karen Andersen-Ranberg
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Geriatric Medicine, Odense University Hospital, Kløvervænget 23, 5000 Odense, Denmark
| | - Daniel Kolbe
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Wolfgang Lieb
- Institute of Epidemiology and Biobank Popgen, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Niemannsweg 11, 24105 Kiel, Germany
| | - Matthias Laudes
- Clinic for Internal Medicine I, Division of Endocrinology, Diabetes and Clinical Nutrition, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Straße 3, 24105 Kiel, Germany
| | - Siegfried Görg
- Institute of Transfusion Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Amke Caliebe
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Brunswiker Str. 10, 24105 Kiel, Germany
| | - Gregor Kuhlenbäumer
- Department of Neurology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Str. 3, 24105 Kiel, Germany
| | - Almut Nebel
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
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Korec E, Ungrová L, Hejnar J, Grieblová A, Zelená K. Three new genes associated with longevity in the European Bison. Vet Anim Sci 2022; 17:100266. [PMID: 35957660 PMCID: PMC9361326 DOI: 10.1016/j.vas.2022.100266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Affiliation(s)
- Evžen Korec
- Zoologická zahrada Tábor a.s., Dukelských Hrdinů 19, 170 00, Prague 7, Czech Republic
- Corresponding author.
| | - Lenka Ungrová
- Zoologická zahrada Tábor a.s., Dukelských Hrdinů 19, 170 00, Prague 7, Czech Republic
- Institute of Molecular Genetics of the Czech Academy of Sciences, Vídeňská 1083, 142 20, Prague 4, Czech Republic
| | - Jiří Hejnar
- Institute of Molecular Genetics of the Czech Academy of Sciences, Vídeňská 1083, 142 20, Prague 4, Czech Republic
| | - Adéla Grieblová
- Zoologická zahrada Tábor a.s., Dukelských Hrdinů 19, 170 00, Prague 7, Czech Republic
| | - Kateřina Zelená
- Zoologická zahrada Tábor a.s., Dukelských Hrdinů 19, 170 00, Prague 7, Czech Republic
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Martemucci G, Portincasa P, Di Ciaula A, Mariano M, Centonze V, D'Alessandro AG. Oxidative stress, aging, antioxidant supplementation and their impact on human health: An overview. Mech Ageing Dev 2022; 206:111707. [PMID: 35839856 DOI: 10.1016/j.mad.2022.111707] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 07/06/2022] [Accepted: 07/10/2022] [Indexed: 12/12/2022]
Abstract
Aging is characterized by a progressive loss of tissue and organ function due to genetic and environmental factors, nutrition, and lifestyle. Oxidative stress is one the most important mechanisms of cellular senescence and increased frailty, resulting in several age-linked, noncommunicable diseases. Contributing events include genomic instability, telomere shortening, epigenetic mechanisms, reduced proteome homeostasis, altered stem-cell function, defective intercellular communication, progressive deregulation of nutrient sensing, mitochondrial dysfunction, and metabolic unbalance. These complex events and their interplay can be modulated by dietary habits and the ageing process, acting as potential measures of primary and secondary prevention. Promising nutritional approaches include the Mediterranean diet, the intake of dietary antioxidants, and the restriction of caloric intake. A comprehensive understanding of the ageing processes should promote new biomarkers of risk or diagnosis, but also beneficial treatments oriented to increase lifespan.
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Affiliation(s)
- Giovanni Martemucci
- Department of Agricultural and Environmental Sciences, University of Bari Aldo Moro, Via G. Amendola, 165/A, 70126 Bari, Italy
| | - Piero Portincasa
- Clinica Medica "A. Murri", Department of Biomedical Sciences and Human Oncology, University of Bari Aldo Moro, Bari, Italy
| | - Agostino Di Ciaula
- Clinica Medica "A. Murri", Department of Biomedical Sciences and Human Oncology, University of Bari Aldo Moro, Bari, Italy.
| | - Michele Mariano
- Unità Operativa Complessa di Radiodiagnostica Universitaria, Policlinico di Bari, Piazza Giulio Cesare, 11, 70124 Bari, Italy
| | - Vincenzo Centonze
- Clinica Medica "A. Murri", Department of Biomedical Sciences and Human Oncology, University of Bari Aldo Moro, Bari, Italy
| | - Angela Gabriella D'Alessandro
- Department of Agricultural and Environmental Sciences, University of Bari Aldo Moro, Via G. Amendola, 165/A, 70126 Bari, Italy
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Hu M, Wang X, Tan J, Yang J, Gao X, Yang Y. Causal Associations between Paternal Longevity and Risks of Cardiovascular Diseases. J Cardiovasc Dev Dis 2022; 9:jcdd9080233. [PMID: 35893225 PMCID: PMC9332106 DOI: 10.3390/jcdd9080233] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/18/2022] [Accepted: 07/21/2022] [Indexed: 01/01/2023] Open
Abstract
Background: Observational studies have suggested that paternal longevity is associated with reduced risks of cardiovascular diseases, yet the causal association remains to be determined. Objectives: To investigate whether Mendelian randomization (MR) results support a causal role of paternal longevity for risks of cardiovascular diseases. Methods: Genetic variants associated with paternal longevity and cardiovascular diseases were obtained from public genome-wide association study data. We used inverse variance weighted MR under a random-effects model to provide causal estimates between paternal longevity and cardiovascular diseases. Results: Paternal longevity was associated with decreased risks of coronary heart disease (odds ratio (OR): 0.08; 95% confidence interval (CI): 0.02–0.37; p = 0.001) and peripheral artery disease (OR: 0.15; 95% CI: 0.03–0.65; p = 0.011). No significant differences were observed in hypertension, atrial fibrillation, heart failure, transient ischemic attack, ischemic stroke, or cardiac death. The weighted median method revealed consistent results between genetically instrumented paternal longevity and decreased risk of coronary heart disease and peripheral artery disease. No significant differences were observed in the MR-Egger results. Multivariable MR consistently indicated causal associations between paternal longevity and decreased cardiovascular diseases. The leave-one-out analysis suggested that the causal associations were not affected by individual single-nucleotide polymorphisms. The intercept of the MR-Egger estimator and funnel plot revealed no indication of horizontal pleiotropic effects. Conclusions: Our MR analyses supported a causal role of paternal longevity for decreased risks of coronary heart disease and peripheral artery disease, which highlighted the need for better monitoring and intervention of cardiovascular diseases in populations with premature paternal death.
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Affiliation(s)
- Mengjin Hu
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China; (M.H.); (J.T.); (J.Y.)
| | - Xiaoning Wang
- School of Medicine, Shandong University, Jinan 250012, China;
| | - Jiangshan Tan
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China; (M.H.); (J.T.); (J.Y.)
| | - Jingang Yang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China; (M.H.); (J.T.); (J.Y.)
| | - Xiaojin Gao
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China; (M.H.); (J.T.); (J.Y.)
- Correspondence: (X.G.); (Y.Y.); Tel.: +86-13810644383 (X.G.); +86-13701151408 (Y.Y.)
| | - Yuejin Yang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China; (M.H.); (J.T.); (J.Y.)
- Correspondence: (X.G.); (Y.Y.); Tel.: +86-13810644383 (X.G.); +86-13701151408 (Y.Y.)
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50
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Hu D, Li Y, Zhang D, Ding J, Song Z, Min J, Zeng Y, Nie C. Genetic trade-offs between complex diseases and longevity. Aging Cell 2022; 21:e13654. [PMID: 35754110 PMCID: PMC9282840 DOI: 10.1111/acel.13654] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 02/28/2022] [Accepted: 05/26/2022] [Indexed: 11/30/2022] Open
Abstract
Longevity was influenced by many complex diseases and traits. However, the relationships between human longevity and genetic risks of complex diseases were not broadly studied. Here, we constructed polygenic risk scores (PRSs) for 225 complex diseases/traits and evaluated their relationships with human longevity in a cohort with 2178 centenarians and 2299 middle‐aged individuals. Lower genetic risks of stroke and hypotension were observed in centenarians, while higher genetic risks of schizophrenia (SCZ) and type 2 diabetes (T2D) were detected in long‐lived individuals. We further stratified PRSs into cell‐type groups and significance‐level groups. The results showed that the immune component of SCZ genetic risk was positively linked to longevity, and the renal component of T2D genetic risk was the most deleterious. Additionally, SNPs with very small p‐values (p ≤ 1x10‐5) for SCZ and T2D were negatively correlated with longevity. While for the less significant SNPs (1x10‐5 < p ≤ 0.05), their effects on disease and longevity were positively correlated. Overall, we identified genetically informed positive and negative factors for human longevity, gained more insights on the accumulation of disease risk alleles during evolution, and provided evidence for the theory of genetic trade‐offs between complex diseases and longevity.
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Affiliation(s)
- Dingxue Hu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.,BGI-Shenzhen, Shenzhen, China
| | - Yan Li
- BGI-Shenzhen, Shenzhen, China
| | | | | | - Zijun Song
- The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China
| | - Junxia Min
- The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China.,Center for the Study of Aging and Human Development and Geriatrics Division, Medical School of Duke University, Durham, North Carolina, USA
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