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Candore G, Accardi G, Aiello A, Baggio G, Bellini T, Calabrese V, Carreca AP, Carreca I, Masucci A, Cattaneo M, Dato S, Bona DD, Fabris L, Gambino C, Lorenzo GD, Francescschi C, Ligotti ME, Manfrinato MC, Puca AA, Tamburello M, Vassallo R, Caruso C. Sex and Gender in Ageing and Longevity: Highlights From an International Course. Transl Med UniSa 2024; 26:15-29. [PMID: 38560614 PMCID: PMC10980291 DOI: 10.37825/2239-9747.1049] [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: 12/21/2023] [Accepted: 02/03/2024] [Indexed: 04/04/2024] Open
Abstract
Gender medicine is a multidisciplinary science and represents an important perspective for pathophysiological and clinical studies in the third millennium. Here, it is provided an overview of the topics discussed in a recent course on the Role of Sex and Gender in Ageing and Longevity. The paper highlights three themes discussed in the course, i.e., the interaction of gender/sex with, i) the pathophysiology of age-related diseases; ii), the role of genetics and epigenetics in ageing and longevity and, iii) the immune responses of older people to pathogens, vaccines, autoantigens, and allergens. Although largely unexplored, it is clear that sex and gender are modulators of disease biology and treatment outcomes. It is becoming evident that men and women should no longer be considered as subgroups, but as biologically distinct groups of patients deserving consideration for specific therapeutic approaches.
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Affiliation(s)
- Giuseppina Candore
- Laboratory of Immunopathology and Immunosenescence, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo,
Italy
- Department of Laboratory Medicine, University Hospital “P.Giaccone”, Palermo,
Italy
| | - Giulia Accardi
- Laboratory of Immunopathology and Immunosenescence, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo,
Italy
| | - Anna Aiello
- Laboratory of Immunopathology and Immunosenescence, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo,
Italy
| | - Giovannella Baggio
- Italian Center for Studies on Gender Health and Medicine, Padua University-Hospital, Padua,
Italy
| | - Tiziana Bellini
- University Center for Studies on Gender Medicine, University of Ferrara, Ferrara,
Italy
- Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara,
Italy
| | - Vittorio Calabrese
- Department of Biomedical and Biotechnological Sciences, University of Catania,
Italy
| | | | - Ignazio Carreca
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, Palermo,
Italy
| | - Anna Masucci
- Department of Laboratory Medicine, University Hospital “P.Giaccone”, Palermo,
Italy
- Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo,
Italy
| | | | - Serena Dato
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende,
Italy
| | - Danilo D. Bona
- Department of Medical and Surgical Sciences, University of Foggia, Foggia,
Italy
| | - Luca Fabris
- Italian Center for Studies on Gender Health and Medicine, Padua University-Hospital, Padua,
Italy
- Department of Medicine, University of Padua, Padua,
Italy
- Department of Internal Medicine, Digestive Disease Section, Yale University, New Haven, CT,
USA
| | - Caterina Gambino
- Department of Laboratory Medicine, University Hospital “P.Giaccone”, Palermo,
Italy
- Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo,
Italy
| | - Gabriele D. Lorenzo
- Department of Health Promotion Sciences, Maternal and Infant Care, Internal Medicine and Medical Specialties, University of Palermo, Palermo,
Italy
| | - Claudio Francescschi
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod,
Russia
- Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod,
Russia
| | - Mattia E. Ligotti
- Department of Research, ISMETT-IRCCS Mediterranean Institute for Transplants and Highly Specialized Therapies, Palermo,
Italy
| | - Maria C. Manfrinato
- University Center for Studies on Gender Medicine, University of Ferrara, Ferrara,
Italy
- Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara,
Italy
| | - Annibale A. Puca
- Cardiovascular Department, IRCCS MultiMedica, Milan,
Italy
- Department of Medicine, Surgery and Dentistry, University of Salerno, Salerno,
Italy
| | - Martina Tamburello
- Department of Laboratory Medicine, University Hospital “P.Giaccone”, Palermo,
Italy
- Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo,
Italy
| | - Roberta Vassallo
- Department of Laboratory Medicine, University Hospital “P.Giaccone”, Palermo,
Italy
- Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo,
Italy
| | - Calogero Caruso
- Laboratory of Immunopathology and Immunosenescence, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo,
Italy
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Zeng Y, Chen H, Liu X, Song Z, Yao Y, Lei X, Lv X, Cheng L, Chen Z, Bai C, Yin Z, Lv Y, Lu J, Li J, Land KC, Yashin A, O'Rand AM, Sun L, Yang Z, Tao W, Gu J, Gottschalk W, Tan Q, Christensen K, Hesketh T, Tian XL, Yang H, Egidi V, Caselli G, Robine JM, Wang H, Shi X, Vaupel JW, Lutz MW, Nie C, Min J. Genetic associations with longevity are on average stronger in females than in males. Heliyon 2024; 10:e23691. [PMID: 38192771 PMCID: PMC10772631 DOI: 10.1016/j.heliyon.2023.e23691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 11/30/2023] [Accepted: 12/09/2023] [Indexed: 01/10/2024] Open
Abstract
It is long observed that females tend to live longer than males in nearly every country. However, the underlying mechanism remains elusive. In this study, we discovered that genetic associations with longevity are on average stronger in females than in males through bio-demographic analyses of genome-wide association studies (GWAS) dataset of 2178 centenarians and 2299 middle-age controls of Chinese Longitudinal Healthy Longevity Study (CLHLS). This discovery is replicated across North and South regions of China, and is further confirmed by North-South discovery/replication analyses of different and independent datasets of Chinese healthy aging candidate genes with CLHLS participants who are not in CLHLS GWAS, including 2972 centenarians and 1992 middle-age controls. Our polygenic risk score analyses of eight exclusive groups of sex-specific genes, analyses of sex-specific and not-sex-specific individual genes, and Genome-wide Complex Trait Analysis using all SNPs all reconfirm that genetic associations with longevity are on average stronger in females than in males. Our discovery/replication analyses are based on genetic datasets of in total 5150 centenarians and compatible middle-age controls, which comprises the worldwide largest sample of centenarians. The present study's findings may partially explain the well-known male-female health-survival paradox and suggest that genetic variants may be associated with different reactions between males and females to the same vaccine, drug treatment and/or nutritional intervention. Thus, our findings provide evidence to steer away from traditional view that "one-size-fits-all" for clinical interventions, and to consider sex differences for improving healthcare efficiency. We suggest future investigations focusing on effects of interactions between sex-specific genetic variants and environment on longevity as well as biological function.
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Affiliation(s)
- Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, 100871, China
- Center for the Study of Aging and Human Development, Medical School of Duke University, Durham, NC, USA, 27710
| | - Huashuai Chen
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, 100871, China
- Business School of Xiangtan University, Xiangtan, 411105, China
| | | | - Zijun Song
- The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Yao Yao
- Center for the Study of Aging and Human Development, Medical School of Duke University, Durham, NC, USA, 27710
| | - Xiaoyan Lei
- Center for the Study of Aging and Human Development, Medical School of Duke University, Durham, NC, USA, 27710
| | - Xiaozhen Lv
- French National Institute of Health and Medical Research (INSERM) and Ecole Pratique des Hautes Etudes (EPHE) FR, Italy
| | - Lingguo Cheng
- School of Business, Nanjing University, Nanjing, 210093, China
| | | | - Chen Bai
- Center for the Study of Aging and Human Development, Medical School of Duke University, Durham, NC, USA, 27710
| | - Zhaoxue Yin
- Division of Non-Communicable Disease Control and Community Health, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Yuebin Lv
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Jiehua Lu
- Department of Sociology, Peking University, Beijing, 100871, China
| | - Jianxin Li
- Department of Sociology, Peking University, Beijing, 100871, China
| | - Kenneth C. Land
- Duke Population Research Institute's Center for Population Health and Aging, Duke University, Durham, NC, USA, 27710
| | - Anatoliy Yashin
- Duke Population Research Institute's Center for Population Health and Aging, Duke University, Durham, NC, USA, 27710
| | - Angela M. O'Rand
- Duke Population Research Institute's Center for Population Health and Aging, Duke University, Durham, NC, USA, 27710
| | - Liang Sun
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, 100730, China
| | - Ze Yang
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, 100730, China
| | - Wei Tao
- School of Life Sciences, Peking University, Beijing, 100871, China
| | - Jun Gu
- School of Life Sciences, Peking University, Beijing, 100871, China
| | - William Gottschalk
- Department of Neurology, Medical Center, Duke University, Durham, NC, USA, 27710
| | - Qihua Tan
- University of Southern Denmark, Odense, DK-5000, Denmark
| | | | - Therese Hesketh
- Institute for Global Health, University College London, London, UK
- Institute for Global Health, School of Public Health, Zhejiang University, Hangzhou, 310058, China
| | - Xiao-Li Tian
- Human Aging Research Institute and School of Life Science, Nanchang University, Jiangxi, 330031, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, 518083, China
- James D. Watson Institute of Genome Sciences, Hangzhou 310008, China310058
| | - Viviana Egidi
- Department of Statistical Sciences, University of Rome La Sapienza, Roma, 00161, Italy
| | - Graziella Caselli
- Department of Statistical Sciences, University of Rome La Sapienza, Roma, 00161, Italy
| | - Jean-Marie Robine
- French National Institute of Health and Medical Research (INSERM) and Ecole Pratique des Hautes Etudes (EPHE) FR, Italy
| | - Huali Wang
- The Third Affiliated Hospital of Health Science Center, Peking University, Italy
| | - Xiaoming Shi
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | | | - Michael W. Lutz
- Department of Neurology, Medical Center, Duke University, Durham, NC, USA, 27710
| | - Chao Nie
- BGI-Shenzhen, Shenzhen, 518083, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, 518083, China
| | - Junxia Min
- The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
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Xing Y, Liu J, Gao Y, Zhu Y, Zhang Y, Ma H. Stronger Associations of TyG Index with Diabetes Than TyG-Obesity-Related Parameters: More Pronounced in Young, Middle-Aged, and Women. Diabetes Metab Syndr Obes 2023; 16:3795-3805. [PMID: 38028992 PMCID: PMC10676865 DOI: 10.2147/dmso.s433493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 11/07/2023] [Indexed: 12/01/2023] Open
Abstract
Purpose The triglyceride glucose (TyG) index and TyG-related indicators have been proposed as a marker of insulin resistance. It is unclear which is the best indicator to predict diabetes mellitus (DM) in Chinese. This study aimed to investigate the predictive value of different biomarkers for the incidence of DM. Patients and methods Between January 2017 and December 2020, 5575 subjects who underwent health examinations in Hebei General Hospital were retrospectively included. The primary endpoint was new onset DM. Results During a median follow-up of 3.03 years, 133(2.39%) individuals developed DM. Multivariable cox proportional hazards models revealed that TyG index and TyG-related parameters were positively associated with DM risk. As the interaction analyses showed, there were significant interactions with sex and age levels in relation to DM risk (both P for interaction <0.05). Risk prediction for DM was significantly improved by adding TyG index to the baseline model using conventional diabetic risk factors in predicting DM at follow-up. Conclusion This population-based cohort study suggested a causal relationship between TyG index and DM after adjusting for other confounding factors. This independent and significant association was more apparent in females and subjects younger than 65 years. Compared with the TyG-BMI, TyG-WC, TyG-WHtR, the TyG index was a more effective predictor of DM.
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Affiliation(s)
- Yuling Xing
- Department of Endocrinology, Hebei General Hospital, Shijiazhuang, People’s Republic of China
| | - Jing Liu
- Department of Endocrinology, Hebei General Hospital, Shijiazhuang, People’s Republic of China
| | - Yu Gao
- Department of Endocrinology, Affiliated Hospital of Chengde Medical University, Chengde, People’s Republic of China
| | - Yajun Zhu
- Department of Endocrinology, Hebei General Hospital, Shijiazhuang, People’s Republic of China
| | - Yunjia Zhang
- Department of Endocrinology, Hebei General Hospital, Shijiazhuang, People’s Republic of China
| | - Huijuan Ma
- Department of Endocrinology, The First Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China
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Ajnakina O, Shamsutdinova D, Stahl D, Steptoe A. Polygenic Propensity for Longevity, APOE-ε4 Status, Dementia Diagnosis, and Risk for Cause-Specific Mortality: A Large Population-Based Longitudinal Study of Older Adults. J Gerontol A Biol Sci Med Sci 2023; 78:1973-1982. [PMID: 37434484 PMCID: PMC10613005 DOI: 10.1093/gerona/glad168] [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: 09/29/2022] [Indexed: 07/13/2023] Open
Abstract
To deepen the understanding of genetic mechanisms influencing mortality risk, we investigated the impact of genetic predisposition to longevity and APOE-ε4, on all-cause mortality and specific causes of mortality. We further investigated the mediating effects of dementia on these relationships. Using data on 7 131 adults aged ≥50 years (mean = 64.7 years, standard deviation [SD] = 9.5) from the English Longitudinal Study of Aging, genetic predisposition to longevity was calculated using the polygenic score approach (PGSlongevity). APOE-ε4 status was defined according to the absence or presence of ε4 alleles. The causes of death were ascertained from the National Health Service central register, which was classified into cardiovascular diseases, cancers, respiratory illness, and all other causes of mortality. Of the entire sample, 1 234 (17.3%) died during an average 10-year follow-up. One-SD increase in PGSlongevity was associated with a reduced risk for all-cause mortality (hazard ratio [HR] = 0.93, 95% confidence interval [CI]: 0.88-0.98, p = .010) and mortalities due to other causes (HR = 0.81, 95% CI: 0.71-0.93, p = .002) in the following 10 years. In gender-stratified analyses, APOE-ε4 status was associated with a reduced risk for all-cause mortality and mortalities related to cancers in women. Mediation analyses estimated that the percent excess risk of APOE-ε4 on other causes of mortality risk explained by the dementia diagnosis was 24%, which increased to 34% when the sample was restricted to adults who were aged ≤75 years old. To reduce the mortality rate in adults who are aged ≥50 years old, it is essential to prevent dementia onset in the general population.
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Affiliation(s)
- Olesya Ajnakina
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Diana Shamsutdinova
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Daniel Stahl
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Andrew Steptoe
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
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Dato S, De Rango F, Crocco P, Pallotti S, Belloy ME, Le Guen Y, Greicius MD, Passarino G, Rose G, Napolioni V. Sex- and APOE-specific genetic risk factors for late-onset Alzheimer's disease: Evidence from gene-gene interaction of longevity-related loci. Aging Cell 2023; 22:e13938. [PMID: 37621137 PMCID: PMC10497850 DOI: 10.1111/acel.13938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 07/01/2023] [Accepted: 07/12/2023] [Indexed: 08/26/2023] Open
Abstract
Advanced age is the largest risk factor for late-onset Alzheimer's disease (LOAD), a disease in which susceptibility correlates to almost all hallmarks of aging. Shared genetic signatures between LOAD and longevity were frequently hypothesized, likely characterized by distinctive epistatic and pleiotropic interactions. Here, we applied a multidimensional reduction approach to detect gene-gene interactions affecting LOAD in a large dataset of genomic variants harbored by genes in the insulin/IGF1 signaling, DNA repair, and oxidative stress pathways, previously investigated in human longevity. The dataset was generated from a collection of publicly available Genome Wide Association Studies, comprising a total of 2,469 gene variants genotyped in 20,766 subjects of Northwestern European ancestry (11,038 LOAD cases and 9,728 controls). The stratified analysis according to APOE*4 status and sex corroborated evidence that pathways leading to longevity also contribute to LOAD. Among the significantly interacting genes, PTPN1, TXNRD1, and IGF1R were already found enriched in gene-gene interactions affecting survival to old age. Furthermore, interacting variants associated with LOAD in a sex- and APOE-specific way. Indeed, while in APOE*4 female carriers we found several inter-pathway interactions, no significant epistasis was found in APOE*4 negative females; conversely, in males, significant intra- and inter-pathways epistasis emerged according to APOE*4 status. These findings suggest that interactions of risk factors may drive different trajectories of cognitive aging. Beyond helping to disentangle the genetic architecture of LOAD, such knowledge may improve precision in predicting the risk of dementia and enable effective sex- and APOE-stratified preventive and therapeutic interventions for LOAD.
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Affiliation(s)
- Serena Dato
- Department of Biology, Ecology and Earth SciencesUniversity of CalabriaRendeItaly
| | - Francesco De Rango
- Department of Biology, Ecology and Earth SciencesUniversity of CalabriaRendeItaly
| | - Paolina Crocco
- Department of Biology, Ecology and Earth SciencesUniversity of CalabriaRendeItaly
| | - Stefano Pallotti
- Genomic And Molecular Epidemiology (GAME) Lab., School of Biosciences and Veterinary MedicineUniversity of CamerinoCamerinoItaly
| | - Michael E. Belloy
- Department of Neurology and Neurological Sciences, School of MedicineStanford UniversityStanfordCaliforniaUSA
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, School of MedicineStanford UniversityStanfordCaliforniaUSA
| | - Michael D. Greicius
- Department of Neurology and Neurological Sciences, School of MedicineStanford UniversityStanfordCaliforniaUSA
| | - Giuseppe Passarino
- Department of Biology, Ecology and Earth SciencesUniversity of CalabriaRendeItaly
| | - Giuseppina Rose
- Department of Biology, Ecology and Earth SciencesUniversity of CalabriaRendeItaly
| | - Valerio Napolioni
- Genomic And Molecular Epidemiology (GAME) Lab., School of Biosciences and Veterinary MedicineUniversity of CamerinoCamerinoItaly
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Carland C, Png G, Malarstig A, Kho PF, Gustafsson S, Michaelsson K, Lind L, Tsafantakis E, Karaleftheri M, Dedoussis G, Ramisch A, Macdonald-Dunlop E, Klaric L, Joshi PK, Chen Y, Björck HM, Eriksson P, Carrasco-Zanini J, Wheeler E, Suhre K, Gilly A, Zeggini E, Viñuela A, Dermitzakis ET, Wilson JF, Langenberg C, Thareja G, Halama A, Schmidt F, Zanetti D, Assimes T. Proteomic analysis of 92 circulating proteins and their effects in cardiometabolic diseases. Clin Proteomics 2023; 20:31. [PMID: 37550624 PMCID: PMC10405520 DOI: 10.1186/s12014-023-09421-0] [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: 02/23/2023] [Accepted: 07/17/2023] [Indexed: 08/09/2023] Open
Abstract
BACKGROUND Human plasma contains a wide variety of circulating proteins. These proteins can be important clinical biomarkers in disease and also possible drug targets. Large scale genomics studies of circulating proteins can identify genetic variants that lead to relative protein abundance. METHODS We conducted a meta-analysis on genome-wide association studies of autosomal chromosomes in 22,997 individuals of primarily European ancestry across 12 cohorts to identify protein quantitative trait loci (pQTL) for 92 cardiometabolic associated plasma proteins. RESULTS We identified 503 (337 cis and 166 trans) conditionally independent pQTLs, including several novel variants not reported in the literature. We conducted a sex-stratified analysis and found that 118 (23.5%) of pQTLs demonstrated heterogeneity between sexes. The direction of effect was preserved but there were differences in effect size and significance. Additionally, we annotate trans-pQTLs with nearest genes and report plausible biological relationships. Using Mendelian randomization, we identified causal associations for 18 proteins across 19 phenotypes, of which 10 have additional genetic colocalization evidence. We highlight proteins associated with a constellation of cardiometabolic traits including angiopoietin-related protein 7 (ANGPTL7) and Semaphorin 3F (SEMA3F). CONCLUSION Through large-scale analysis of protein quantitative trait loci, we provide a comprehensive overview of common variants associated with plasma proteins. We highlight possible biological relationships which may serve as a basis for further investigation into possible causal roles in cardiometabolic diseases.
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Affiliation(s)
- Corinne Carland
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Grace Png
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Anders Malarstig
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Pfizer Worldwide Research, Development and Medical, Stockholm, Sweden
| | - Pik Fang Kho
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford Cardiovascular Institute, Palo Alto, CA, USA
| | - Stefan Gustafsson
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Karl Michaelsson
- Department of Surgical Sciences, Medical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Lars Lind
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | | | | | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University of Athens, Athens, Greece
| | - Anna Ramisch
- Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva Medical School, Geneva, Switzerland
| | - Erin Macdonald-Dunlop
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
| | - Lucija Klaric
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Scotland
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
| | - Yan Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Hanna M Björck
- Cardiovascular Medicine, Medicine, Karolinska Institute, Stockholm, Sweden
| | - Per Eriksson
- Cardiovascular Medicine, Medicine, Karolinska Institute, Stockholm, Sweden
| | | | - Eleanor Wheeler
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Karsten Suhre
- Bioinformatics Core, Cornell Medicine - Qatar Research, Doha, Qatar
| | - Arthur Gilly
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Munich, Germany
| | - Ana Viñuela
- Biosciences Institute, Faculty of Medical Sciences, University of Newcastle, Newcastle, UK
| | - Emmanouil T Dermitzakis
- Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva Medical School, Geneva, Switzerland
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Scotland
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Computational medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Gaurav Thareja
- Bioinformatics Core, Cornell Medicine - Qatar Research, Doha, Qatar
| | - Anna Halama
- Bioinformatics Core, Cornell Medicine - Qatar Research, Doha, Qatar
| | - Frank Schmidt
- Proteomics Core, Research, Weill Cornell Medicine - Qatar, Doha, Qatar
| | - Daniela Zanetti
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford Cardiovascular Institute, Palo Alto, CA, USA
| | - Themistocles Assimes
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford Cardiovascular Institute, Palo Alto, CA, USA.
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7
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Zhou J, Li X, Gao X, Wei Y, Ye L, Liu S, Ye J, Qiu Y, Zheng X, Chen C, Wang J, Kraus VB, Lv Y, Mao C, Shi X. Leisure Activities, Genetic Risk, and Frailty: Evidence from the Chinese Adults Aged 80 Years or Older. Gerontology 2023; 69:961-971. [PMID: 37075711 PMCID: PMC10791136 DOI: 10.1159/000530665] [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: 11/29/2022] [Accepted: 04/04/2023] [Indexed: 04/21/2023] Open
Abstract
INTRODUCTION About half of adults aged ≥80 years suffer from frailty. Exercise is considered effective in preventing frailty but may be inapplicable to adults aged ≥80 years due to physical limitations. As an alternative, we aimed to explore the association of leisure activities with frailty and identify potential interaction with established polygenic risk score (PRS) among adults aged ≥80 years. METHODS Analyses were performed in a prospective cohort study of 7,471 community-living older adults aged ≥80 years who were recruited between 2002 and 2014 from 23 provinces in China. Leisure activity was assessed using a seven-question leisure activity index and frailty was defined as a frailty index ≥0.25 using a validated 39-item health-related scale. The PRS was constructed using 59 single-nucleotide polymorphisms associated with frailty in a subsample of 2,541 older adults. Cox proportional hazards models were used to explore the associations of leisure activities, PRS with frailty. RESULTS The mean age of participants was 89.4 ± 6.6 years (range: 80-116). In total, 2,930 cases of frailty were identified during 42,216 person-years of follow-up. Each 1 unit increase in the leisure activity index was associated with 12% lower risk of frailty (hazard ratio: 0.88 [95% confidence interval, 0.85-0.91]). Participants with high genetic risk (PRS >2.47 × 10-4) suffered from 26% higher risk of frailty. Interaction between leisure activity and genetic risk was not observed. CONCLUSION Evidence is presented for the independent association of leisure activities and genetic risk with frailty. Engagement in leisure activities is suggested to be associated with lower risk of frailty across all levels of genetic risk among adults aged ≥80 years.
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Affiliation(s)
- Jinhui Zhou
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xinwei Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Xiang Gao
- Department of Nutrition and Food Hygiene, School of Public Health, Fudan University, Shanghai, China
| | - Yuan Wei
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Lihong Ye
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Sixin Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jiaming Ye
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Yidan Qiu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China
| | - Xulin Zheng
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Chen Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jun Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Virginia Byers Kraus
- Duke Molecular Physiology Institute and Division of Rheumatology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Yuebin Lv
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Chen Mao
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
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8
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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: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [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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9
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Liu X, Zou L, Nie C, Qin Y, Tong X, Wang J, Yang H, Xu X, Jin X, Xiao L, Zhang T, Min J, Zeng Y, Jia H, Hou Y. Mendelian randomization analyses reveal causal relationships between the human microbiome and longevity. Sci Rep 2023; 13:5127. [PMID: 36991009 PMCID: PMC10052271 DOI: 10.1038/s41598-023-31115-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 03/07/2023] [Indexed: 03/31/2023] Open
Abstract
Although recent studies have revealed the association between the human microbiome especially gut microbiota and longevity, their causality remains unclear. Here, we assess the causal relationships between the human microbiome (gut and oral microbiota) and longevity, by leveraging bidirectional two-sample Mendelian randomization (MR) analyses based on genome-wide association studies (GWAS) summary statistics of the gut and oral microbiome from the 4D-SZ cohort and longevity from the CLHLS cohort. We found that some disease-protected gut microbiota such as Coriobacteriaceae and Oxalobacter as well as the probiotic Lactobacillus amylovorus were related to increased odds of longevity, whereas the other gut microbiota such as colorectal cancer pathogen Fusobacterium nucleatum, Coprococcus, Streptococcus, Lactobacillus, and Neisseria were negatively associated with longevity. The reverse MR analysis further revealed genetically longevous individuals tended to have higher abundances of Prevotella and Paraprevotella but lower abundances of Bacteroides and Fusobacterium species. Few overlaps of gut microbiota-longevity interactions were identified across different populations. We also identified abundant links between the oral microbiome and longevity. The additional analysis suggested that centenarians genetically had a lower gut microbial diversity, but no difference in oral microbiota. Our findings strongly implicate these bacteria to play a role in human longevity and underscore the relocation of commensal microbes among different body sites that would need to be monitored for long and healthy life.
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Affiliation(s)
- Xiaomin Liu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Chao Nie
- BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Xin Tong
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Jian Wang
- BGI-Shenzhen, Shenzhen, 518083, China
- James D. Watson Institute of Genome Sciences, Hangzhou, 310058, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, 518083, China
- James D. Watson Institute of Genome Sciences, Hangzhou, 310058, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Xin Jin
- BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Tao Zhang
- BGI-Shenzhen, Shenzhen, 518083, China
- Department of Biology, University of Copenhagen, Universitetsparken 13, 2100, Copenhagen, Denmark
| | - Junxia Min
- School of Medicine, The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang University, Hangzhou, China.
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development, Raissun Institute for Advanced Studies, Peking University, Beijing, China.
| | - Huijue Jia
- Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Shanghai, China.
| | - Yong Hou
- BGI-Shenzhen, Shenzhen, 518083, China.
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10
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Expression of Androgen and Estrogen Receptors in the Human Lacrimal Gland. Int J Mol Sci 2023; 24:ijms24065609. [PMID: 36982683 PMCID: PMC10053362 DOI: 10.3390/ijms24065609] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/12/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023] Open
Abstract
Lacrimal gland dysfunction causes dry eye disease (DED) due to decreased tear production. Aqueous-deficient DED is more prevalent in women, suggesting that sexual dimorphism of the human lacrimal gland could be a potential cause. Sex steroid hormones are a key factor in the development of sexual dimorphism. This study aimed to quantify estrogen receptor (ER) and androgen receptor (AR) expression in the human lacrimal gland and compare it between sexes. RNA was isolated from 35 human lacrimal gland tissue samples collected from 19 cornea donors. AR, ERα, and ERβ mRNA was identified in all samples, and their expression was quantified using qPCR. Immunohistochemical staining was performed on selected samples to evaluate protein expression of the receptors. ERα mRNA expression was significantly higher than the expression of AR and ERβ. No difference in sex steroid hormone (SSH) receptor mRNA expression was observed between sexes, and no correlation was observed with age. If ERα protein expression is found to be concordant with mRNA expression, it should be investigated further as a potential target for hormone therapy of DED. Further research is needed to elucidate the role of sex steroid hormone receptors in sex-related differences of lacrimal gland structure and disease.
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11
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Iannuzzi V, Bacalini MG, Franceschi C, Giuliani C. The role of genetics and epigenetics in sex differences in human survival. GENUS 2023. [DOI: 10.1186/s41118-023-00181-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
AbstractSex differences in human survival have been extensively investigated in many studies that have in part uncovered the biological determinants that promote a longer life in females with respect to males. Moreover, researches performed in the past years have prompted increased awareness about the biological effects of environmental factors that can modulate the magnitude of the sex gap in survival. Besides the genetic background, epigenetic modifications like DNA methylation, that can modulate cell function, have been particularly studied in this framework. In this review, we aim to summarize the role of the genetic and epigenetic mechanisms in promoting female advantage from the early in life (“INNATE” features), and in influencing the magnitude of the gap in sex differences in survival and ageing (“VARIABLE” features). After briefly discussing the biological bases of sex determination in humans, we will provide much evidence showing that (i) “innate” mechanisms common to all males and to all females (both genetic and epigenetic) play a major role in sex differences in lifespan; (ii) “variable” genetic and epigenetic patterns, that vary according to context, populations and exposures to different environments, can affect the magnitude of the gap in sex differences in survival. Then we will describe recent findings in the use of epigenetic clocks to uncover sex differences in biological age and thus potentially in mortality. In conclusion, we will discuss how environmental factors cannot be kept apart from the biological factors providing evidence from the field of human ecology.
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12
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Sex differences in the oral microbiome, host traits, and their causal relationships. iScience 2022; 26:105839. [PMID: 36660475 PMCID: PMC9843272 DOI: 10.1016/j.isci.2022.105839] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 08/09/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022] Open
Abstract
The oral microbiome has been implicated in a growing number of diseases; however, determinants of the oral microbiome and their roles remain elusive. Here, we investigated the oral (saliva and tongue dorsum) metagenome, the whole genome, and other omics data in a total of 4,478 individuals and demonstrated that the oral microbiome composition and its major contributing host factors significantly differed between sexes. We thus conducted a sex-stratified metagenome-genome-wide-association study (M-GWAS) and identified 11 differential genetic associations with the oral microbiome (p sex-difference < 5 × 10-8). Furthermore, we performed sex-stratified Mendelian randomization (MR) analyses and identified abundant causalities between the oral microbiome and serum metabolites. Notably, sex-specific microbes-hormonal interactions explained the mostly observed sex hormones differences such as the significant causalities enrichments for aldosterone in females and androstenedione in males. These findings illustrate the necessity of sex stratification and deepen our understanding of the interplay between the oral microbiome and serum metabolites.
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13
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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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14
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Porcu E, Claringbould A, Weihs A, Lepik K, Richardson TG, Völker U, Santoni FA, Teumer A, Franke L, Reymond A, Kutalik Z. Limited evidence for blood eQTLs in human sexual dimorphism. Genome Med 2022; 14:89. [PMID: 35953856 PMCID: PMC9373355 DOI: 10.1186/s13073-022-01088-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 07/14/2022] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND The genetic underpinning of sexual dimorphism is very poorly understood. The prevalence of many diseases differs between men and women, which could be in part caused by sex-specific genetic effects. Nevertheless, only a few published genome-wide association studies (GWAS) were performed separately in each sex. The reported enrichment of expression quantitative trait loci (eQTLs) among GWAS-associated SNPs suggests a potential role of sex-specific eQTLs in the sex-specific genetic mechanism underlying complex traits. METHODS To explore this scenario, we combined sex-specific whole blood RNA-seq eQTL data from 3447 European individuals included in BIOS Consortium and GWAS data from UK Biobank. Next, to test the presence of sex-biased causal effect of gene expression on complex traits, we performed sex-specific transcriptome-wide Mendelian randomization (TWMR) analyses on the two most sexually dimorphic traits, waist-to-hip ratio (WHR) and testosterone levels. Finally, we performed power analysis to calculate the GWAS sample size needed to observe sex-specific trait associations driven by sex-biased eQTLs. RESULTS Among 9 million SNP-gene pairs showing sex-combined associations, we found 18 genes with significant sex-biased cis-eQTLs (FDR 5%). Our phenome-wide association study of the 18 top sex-biased eQTLs on >700 traits unraveled that these eQTLs do not systematically translate into detectable sex-biased trait-associations. In addition, we observed that sex-specific causal effects of gene expression on complex traits are not driven by sex-specific eQTLs. Power analyses using real eQTL- and causal-effect sizes showed that millions of samples would be necessary to observe sex-biased trait associations that are fully driven by sex-biased cis-eQTLs. Compensatory effects may further hamper their detection. CONCLUSIONS Our results suggest that sex-specific eQTLs in whole blood do not translate to detectable sex-specific trait associations of complex diseases, and vice versa that the observed sex-specific trait associations cannot be explained by sex-specific eQTLs.
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Affiliation(s)
- Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland. .,Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,University Center for Primary Care and Public Health, Lausanne, Switzerland.
| | - Annique Claringbould
- University Medical Centre Groningen, Groningen, the Netherlands.,Structural and Computational Biology Unit, European Molecular Biology Laboratories (EMBL), Heidelberg, Germany
| | - Antoine Weihs
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Kaido Lepik
- Institute of Computer Science, University of Tartu, Tartu, Estonia.,Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Tom G Richardson
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, OX3 7DQ, UK
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany.,DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Federico A Santoni
- Endocrine, Diabetes, and Metabolism Service, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland.,Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Alexander Teumer
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.,Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Lude Franke
- University Medical Centre Groningen, Groningen, the Netherlands
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,University Center for Primary Care and Public Health, Lausanne, Switzerland. .,Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
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15
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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: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [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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16
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Genome-Wide Association Study of Fluorescent Oxidation Products Accounting for Tobacco Smoking Status in Adults from the French EGEA Study. Antioxidants (Basel) 2022; 11:antiox11050802. [PMID: 35624665 PMCID: PMC9137810 DOI: 10.3390/antiox11050802] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 04/13/2022] [Accepted: 04/18/2022] [Indexed: 12/14/2022] Open
Abstract
Oxidative stress (OS) is the main pathophysiological mechanism involved in several chronic diseases, including asthma. Fluorescent oxidation products (FlOPs), a global biomarker of damage due to OS, is of growing interest in epidemiological studies. We conducted a genome-wide association study (GWAS) of the FlOPs level in 1216 adults from the case-control and family-based EGEA study (mean age 43 years old, 51% women, and 23% current smokers) to identify genetic variants associated with FlOPs. The GWAS was first conducted in the whole sample and then stratified according to smoking status, the main exogenous source of reactive oxygen species. Among the top genetic variants identified by the three GWAS, those located in BMP6 (p = 3 × 10−6), near BMPER (p = 9 × 10−6), in GABRG3 (p = 4 × 10−7), and near ATG5 (p = 2 × 10−9) are the most relevant because of both their link to biological pathways related to OS and their association with several chronic diseases for which the role of OS in their pathophysiology has been pointed out. BMP6 and BMPER are of particular interest due to their involvement in the same biological pathways related to OS and their functional interaction. To conclude, this study, which is the first GWAS of FlOPs, provides new insights into the pathophysiology of chronic OS-related diseases.
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17
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Ji JS, Liu L, Zeng Y, Yan LL. Effect of FOXO3 and Air Pollution on Cognitive Function: A Longitudinal Cohort Study of Older Adults in China From 2000 to 2014. J Gerontol A Biol Sci Med Sci 2022; 77:1534-1541. [PMID: 35029671 PMCID: PMC9890624 DOI: 10.1093/gerona/glac016] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Indexed: 02/05/2023] Open
Abstract
Forkhead Box O 3 (FOXO3) genotype is strongly associated with human longevity and may be protective against neurodegeneration. Air pollution is a risk factor for cognitive decline and dementia. We aimed to study the individual and combined effects of FOXO3 and air pollution on cognitive function in a large prospective cohort with up to 14 years of follow-up. We measured cognitive function and impairment using the Mini-Mental State Examination (MMSE). We used tagging SNPs rs2253310, rs2802292, and rs4946936 to identify the FOXO3 gene, of which roughly half of the population had the longevity-associated polymorphism. We matched annual average fine particulate matter (PM2.5) concentrations within a 1 km2 grid. We conducted cross-sectional and longitudinal analyses using multivariable linear and logistic regression models and generalized estimating equations. At baseline, carriers of the longevity-associated homozygous minor alleles of FOXO3 SNPs had a higher MMSE score than the carriers of homozygous major alleles. In the longitudinal follow-up, carriers of FOXO3 homozygous minor alleles had lower odds of cognitive impairment compared with noncarriers. Higher PM2.5 was associated with a lower MMSE score and higher odds of cognitive impairment. The positive effects of FOXO3 were the strongest in females, older people, and residents in areas with lower air pollution.
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Affiliation(s)
- John S Ji
- Address correspondence to: John S. Ji, ScD, Vanke School of Public Health, Tsinghua University, 4th Floor, Mingli Building, Haidian District, Beijing 100083, China. E-mail:
| | - Linxin Liu
- Vanke School of Public Health, Tsinghua University, Beijing, 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, Duke Medical School, Durham, North Carolina, USA
| | - Lijing L Yan
- Global Health Research Center, Duke Kunshan University, Kunshan, China
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18
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Cheng JY, Stern AJ, Racimo F, Nielsen R. Detecting Selection in Multiple Populations by Modeling Ancestral Admixture Components. Mol Biol Evol 2022; 39:msab294. [PMID: 34626111 PMCID: PMC8763095 DOI: 10.1093/molbev/msab294] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
One of the most powerful and commonly used approaches for detecting local adaptation in the genome is the identification of extreme allele frequency differences between populations. In this article, we present a new maximum likelihood method for finding regions under positive selection. It is based on a Gaussian approximation to allele frequency changes and it incorporates admixture between populations. The method can analyze multiple populations simultaneously and retains power to detect selection signatures specific to ancestry components that are not representative of any extant populations. Using simulated data, we compare our method to related approaches, and show that it is orders of magnitude faster than the state-of-the-art, while retaining similar or higher power for most simulation scenarios. We also apply it to human genomic data and identify loci with extreme genetic differentiation between major geographic groups. Many of the genes identified are previously known selected loci relating to hair pigmentation and morphology, skin, and eye pigmentation. We also identify new candidate regions, including various selected loci in the Native American component of admixed Mexican-Americans. These involve diverse biological functions, such as immunity, fat distribution, food intake, vision, and hair development.
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Affiliation(s)
- Jade Yu Cheng
- Lundbeck GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Aaron J Stern
- Graduate Group in Computational Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Fernando Racimo
- Lundbeck GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Rasmus Nielsen
- Lundbeck GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA, USA
- Department of Statistics, University of California, Berkeley, Berkeley, CA, USA
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19
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Chen Q, Li ZH, Song WQ, Yao Y, Zhang YJ, Zhong WF, Zhang PD, Liu D, Zhang XR, Huang QM, Zhao XY, Shi XM, Mao C. Association between single nucleotide polymorphism of rs1937 in TFAM gene and longevity among the elderly Chinese population: based on the CLHLS study. BMC Geriatr 2022; 22:16. [PMID: 34979947 PMCID: PMC8722189 DOI: 10.1186/s12877-021-02655-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 11/22/2021] [Indexed: 12/02/2022] Open
Abstract
Background To investigate whether the mitochondrial transcription factor A (TFAM) rs1937 single nucleotide polymorphism (SNP) is associated with longevity. Methods We conducted a case-control study among Chinese long-lived individuals (≥90 years). Data were obtained on 3294 participants who were able to voluntarily provided a saliva sample during 2008–2009 from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). In this study, 1387 young elderly (65–74 years) were allocated to the control group, and 1907 long-lived individuals were recruited as the case group. SNP rs1937 on TFAM were genotyped. Logistic regression models were applied to evaluate the association between rs1937 SNP and longevity. Results The genotype frequency of the SNP of rs1937 in the two groups had a significant difference (p = 0.003). Binary logistic regression analysis showed that compared to younger elderly, the long-lived individuals with “CC genotype” of rs1937 were more closely related to increased longevity than those with “GG genotype” (OR: 1.989, 95% CI: 1.160–3.411). The positive association between rs1937 SNP and longevity was robust in stratified analyses and sensitivity analyses. Conclusions We found the SNP of rs1937 may be a potential biomarker for longer human life span. Further studies are necessary to elucidate the biological mechanism of rs1937 on TFAM with promoting longevity. Supplementary Information The online version contains supplementary material available at 10.1186/s12877-021-02655-3.
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Affiliation(s)
- Qing Chen
- Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.,Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Zhi-Hao Li
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Wei-Qi Song
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Yao Yao
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China
| | - Yu-Jie Zhang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Wen-Fang Zhong
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Pei-Dong Zhang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Dan Liu
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Xi-Ru Zhang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Qing-Mei Huang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Xiao-Yang Zhao
- State Key Laboratory of Organ Failure Research, Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China. .,Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou, China.
| | - Xiao-Ming Shi
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Chen Mao
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
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20
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Song B, Zhao X, Yao T, Lu W, Zhang H, Liu T, Liu C, Wang K. Triglyceride Glucose-Body Mass Index and Risk of Incident Type 2 Diabetes Mellitus in Japanese People With Normal Glycemic Level: A Population-Based Longitudinal Cohort Study. Front Endocrinol (Lausanne) 2022; 13:907973. [PMID: 35909552 PMCID: PMC9336540 DOI: 10.3389/fendo.2022.907973] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/21/2022] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND It has been proved that triglyceride glucose-body mass index (TyG-BMI) is a readily available and clinically significant indicator of insulin resistance (IR). Nevertheless, the association between TyG-BMI and incident Type 2 diabetes mellitus (T2DM) remains uncertain. This study aimed to study the relationship between TyG-BMI and T2DM and explore the predictive characteristics of TyG-BMI. METHODS Our study was conducted as a longitudinal cohort study. 8,430 men and 7,034 women were enrolled and analyzed. They were both non-diabetic subjects with normal glycemic levels. Follow-up lasted for 13 years, from 1994 to 2016. To make the number of TyG-BMI in each group similar, the subjects were divided into four groups with 3866 subjects in each group. RESULTS During the 13-year follow-up period, 373 subjects were diagnosed with incident T2DM. Our multivariate Cox regression analysis revealed that TyG-BMI was an independent predictor of incident T2DM. In addition, our research identified four specific groups, young people (18-44 years old), women, the non-hypertensive population and non-drinkers were at significantly higher risk of developing TyG-BMI-related diabetes (P-interaction< 0.05). The best threshold TyG-BMI for predicting incident T2DM was 197.2987 (area under the curve 0.7738). CONCLUSIONS Our longitudinal cohort study demonstrated the positive correlation between baseline TyG-BMI and risk of incident T2DM in Japanese with normal glycemic levels, and this risk was significantly higher in the young people, women, the non-hypertensive population and non-drinkers.
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Affiliation(s)
| | | | | | | | | | | | | | - Kun Wang
- *Correspondence: Chengyun Liu, ; Kun Wang,
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21
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Lopez-Lee C, Kodama L, Gan L. Sex Differences in Neurodegeneration: The Role of the Immune System in Humans. Biol Psychiatry 2022; 91:72-80. [PMID: 33715827 PMCID: PMC8263798 DOI: 10.1016/j.biopsych.2021.01.002] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 12/29/2020] [Accepted: 01/04/2021] [Indexed: 01/03/2023]
Abstract
Growing evidence supports significant involvement of immune dysfunction in the etiology of neurodegenerative diseases, several of which also display prominent sex differences across prevalence, pathology, and symptomology. In this review, we summarize evidence from human studies of established and recent findings of sex differences in multiple sclerosis, Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis and discuss how sex-specific central nervous system innate immune activity could contribute to downstream sex differences in these diseases. We examine human genomic and transcriptomics studies in each neurodegenerative disease through the lens of sex differences in the neuroimmune system and highlight the importance of stratifying sex in clinical and translational research studies. Finally, we discuss the limitations of the existing studies and outline recommendations for further advancing sex-based analyses to uncover novel disease mechanisms that could ultimately help treat both sexes.
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Affiliation(s)
- Chloe Lopez-Lee
- Neuroscience Graduate Program, Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York; Helen and Robert Appel Alzheimer's Disease Research Institute, Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York
| | - Lay Kodama
- Helen and Robert Appel Alzheimer's Disease Research Institute, Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York; Medical Scientist Training Program and Neuroscience Graduate Program, University of California San Francisco, San Francisco, California.
| | - Li Gan
- Neuroscience Graduate Program, Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York; Helen and Robert Appel Alzheimer's Disease Research Institute, Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York.
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22
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Ji JS, Liu L, Shu C, Yan LL, Zeng Y. Sex Difference and Interaction of SIRT1 and FOXO3 Candidate Longevity Genes on Life Expectancy: A 10-year Prospective Longitudinal Cohort Study. J Gerontol A Biol Sci Med Sci 2021; 77:1557-1563. [PMID: 34928346 DOI: 10.1093/gerona/glab378] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Indexed: 11/14/2022] Open
Abstract
SIRT1 and FOXO3 are both associated with longevity. Molecular biology research in many organisms (yeast, nematode worm Caenorhabditis elegans, and mice mammalian models) shows SIRT1 acts on the FOXO family of forkhead transcription factors to respond to oxidative stress better, shifting processes away from cell death towards stress resistance. Human population studies need epidemiologic evidence. We used an open cohort of 3,166 community-dwelling participants in China with follow-up from 2008 to 2018. The mean age at baseline was 84.6 years. In 16,375 person-years of follow-up, there were 1,968 mortality events. SIRT1 and FOXO3 exhibited mendelian randomization as there was no correlation with each other and with baseline study population characteristics. Some SIRT1 and FOXO3 SNPs showed protective effects for mortality risk. The FOXO3 protective effect was stronger in females, and the SIRT1 protective effect was stronger in male study participants. We did not see evidence of a synergistic effect of being carriers of both SIRT1 and FOXO3.
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Affiliation(s)
- John S Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China.,Global Health Research Center, Duke Kunshan University, Kunshan, China
| | - Linxin Liu
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Chang Shu
- Department of Pediatrics & Department of System Biology, Columbia University, New York, USA
| | - Lijing L Yan
- Global Health Research Center, Duke Kunshan University, Kunshan, 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, Duke Medical School, Durham, NC, USA
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23
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Bacalini MG, Palombo F, Garagnani P, Giuliani C, Fiorini C, Caporali L, Stanzani Maserati M, Capellari S, Romagnoli M, De Fanti S, Benussi L, Binetti G, Ghidoni R, Galimberti D, Scarpini E, Arcaro M, Bonanni E, Siciliano G, Maestri M, Guarnieri B, Martucci M, Monti D, Carelli V, Franceschi C, La Morgia C, Santoro A. Association of rs3027178 polymorphism in the circadian clock gene PER1 with susceptibility to Alzheimer's disease and longevity in an Italian population. GeroScience 2021; 44:881-896. [PMID: 34921659 PMCID: PMC9135916 DOI: 10.1007/s11357-021-00477-0] [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: 07/26/2021] [Accepted: 10/15/2021] [Indexed: 12/11/2022] Open
Abstract
Many physiological processes in the human body follow a 24-h circadian rhythm controlled by the circadian clock system. Light, sensed by retina, is the predominant “zeitgeber” able to synchronize the circadian rhythms to the light-dark cycles. Circadian rhythm dysfunction and sleep disorders have been associated with aging and neurodegenerative diseases including mild cognitive impairment (MCI) and Alzheimer’s disease (AD). In the present study, we aimed at investigating the genetic variability of clock genes in AD patients compared to healthy controls from Italy. We also included a group of Italian centenarians, considered as super-controls in association studies given their extreme phenotype of successful aging. We analyzed the exon sequences of eighty-four genes related to circadian rhythms, and the most significant variants identified in this first discovery phase were further assessed in a larger independent cohort of AD patients by matrix assisted laser desorption/ionization-time of flight mass spectrometry. The results identified a significant association between the rs3027178 polymorphism in the PER1 circadian gene with AD, the G allele being protective for AD. Interestingly, rs3027178 showed similar genotypic frequencies among AD patients and centenarians. These results collectively underline the relevance of circadian dysfunction in the predisposition to AD and contribute to the discussion on the role of the relationship between the genetics of age-related diseases and of longevity.
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Affiliation(s)
- Maria Giulia Bacalini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Laboratorio Brain Aging, Bologna, Italy
| | - Flavia Palombo
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy
| | - Paolo Garagnani
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.,Applied Biomedical Research Center (CRBA), S. Orsola-Malpighi Polyclinic, Bologna, Italy.,CNR Institute of Molecular Genetics "Luigi Luca Cavalli-Sforza", Unit of Bologna, Bologna, Italy.,Department of Laboratory Medicine, Clinical Chemistry, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.,Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), University of Bologna, Bologna, Italy
| | - Cristina Giuliani
- Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), University of Bologna, Bologna, Italy.,Laboratory of Molecular Anthropology and Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Claudio Fiorini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy
| | - Leonardo Caporali
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy
| | | | - Sabina Capellari
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Clinica Neurologica, Bologna, Italy.,Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
| | - Martina Romagnoli
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy
| | - Sara De Fanti
- Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), University of Bologna, Bologna, Italy.,Laboratory of Molecular Anthropology and Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Luisa Benussi
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giuliano Binetti
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Roberta Ghidoni
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda, Ospedale Policlinico, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Elio Scarpini
- Fondazione IRCCS Ca' Granda, Ospedale Policlinico, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Marina Arcaro
- Fondazione IRCCS Ca' Granda, Ospedale Policlinico, Milan, Italy
| | - Enrica Bonanni
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Gabriele Siciliano
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Michelangelo Maestri
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Biancamaria Guarnieri
- Center of Sleep Medicine, Villa Serena Hospital and Villaserena Foundation for the Research, Città S. Angelo, Pescara, Italy
| | | | - Morena Martucci
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Daniela Monti
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Florence, Italy
| | - Valerio Carelli
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy.,Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
| | - Claudio Franceschi
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.,Department of Applied Mathematics, Institute of Information Technology, Mathematics and Mechanics (ITMM), Lobachevsky State University of Nizhny Novgorod-National Research University (UNN), Nizhny Novgorod, Russia
| | - Chiara La Morgia
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Clinica Neurologica, Bologna, Italy
| | - Aurelia Santoro
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy. .,Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), University of Bologna, Bologna, Italy.
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24
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Abstract
Biology of aging is an active and rapidly expanding area of biomedical research. Over the years, focus of work in this field has been gradually shifting from studying the effects and symptoms of aging to searching for mechanisms of the aging process. Progress of this work led to an additional shift from looking for “the mechanism” of aging and formulating the corresponding “theories of aging” to appreciation that aging represents a net result of multiple physiological changes and their intricate interactions. It was also shown that mechanisms of aging include nutrient-dependent signaling pathways which have been remarkably conserved in the course of the evolution. Another important development in this field is increased emphasis on searching for pharmacological and environmental interventions that can extend healthspan or influence other aspects of aging. Progress in understanding the key role of aging as a risk factor for chronic disease provides impetus for these studies. Data from the recent pandemic provided additional evidence for the impact of age on resilience. Progress of work in this area also was influenced by major analytical and technological advances, including greatly improved methods for the study of gene expression, protein, lipids, and metabolites profiles, enhanced ability to produce various genetic modifications and novel approaches to assessment of biological age. Progress in research on the biology of aging provides reasons for optimism about the chances that safe and widely applicable anti-aging interventions with significant benefits for both individual and public health will be developed in the not too distant future.
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Affiliation(s)
- Andrzej Bartke
- Department of Internal Medicine, Southern Illinois University School of Medicine, 801 N. Rutledge St., P. O. Box 19628, Springfield, IL, 62794-9628, USA.
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25
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Secci R, Hartmann A, Walter M, Grabe HJ, Van der Auwera-Palitschka S, Kowald A, Palmer D, Rimbach G, Fuellen G, Barrantes I. Biomarkers of geroprotection and cardiovascular health: An overview of omics studies and established clinical biomarkers in the context of diet. Crit Rev Food Sci Nutr 2021; 63:2426-2446. [PMID: 34648415 DOI: 10.1080/10408398.2021.1975638] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The slowdown, inhibition, or reversal of age-related decline (as a composite of disease, dysfunction, and, ultimately, death) by diet or natural compounds can be defined as dietary geroprotection. While there is no single reliable biomarker to judge the effects of dietary geroprotection, biomarker signatures based on omics (epigenetics, gene expression, microbiome composition) are promising candidates. Recently, omic biomarkers started to supplement established clinical ones such as lipid profiles and inflammatory cytokines. In this review, we focus on human data. We first summarize the current take on genetic biomarkers based on epidemiological studies. However, most of the remaining biomarkers that we describe, whether omics-based or clinical, are related to intervention studies. Then, because of their promising potential in the context of dietary geroprotection, we focus on the effects of berry-based interventions, which up to now have been mostly described employing clinical markers. We provide an aggregation and tabulation of all the recent systematic reviews and meta-analyses that we could find related to this topic. Finally, we present evidence for the importance of the "nutribiography," that is, the influence that an individual's history of diet and natural compound consumption can have on the effects of dietary geroprotection.
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Affiliation(s)
- Riccardo Secci
- Junior Research Group Translational Bioinformatics, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany
| | - Alexander Hartmann
- Institute for Clinical Chemistry and Laboratory Medicine, University Medical Center Rostock, University of Rostock, Rostock, Germany
| | - Michael Walter
- Institute for Clinical Chemistry and Laboratory Medicine, University Medical Center Rostock, University of Rostock, Rostock, Germany.,Institute of Laboratory Medicine, Clinical Chemistry, and Pathobiochemistry, Charite University Medical Center, Berlin, Germany
| | - Hans Jörgen Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.,German Centre for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Sandra Van der Auwera-Palitschka
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.,German Centre for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Axel Kowald
- Institute for Biostatistics and Informatics in Medicine and Aging Research, Rostock University Medical Center, Rostock, Germany
| | - Daniel Palmer
- Institute for Biostatistics and Informatics in Medicine and Aging Research, Rostock University Medical Center, Rostock, Germany
| | - Gerald Rimbach
- Institute of Human Nutrition and Food Science, University of Kiel, Kiel, Germany
| | - Georg Fuellen
- Institute for Biostatistics and Informatics in Medicine and Aging Research, Rostock University Medical Center, Rostock, Germany
| | - Israel Barrantes
- Junior Research Group Translational Bioinformatics, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany
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26
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Meeks KAC, Bentley AR, Gouveia MH, Chen G, Zhou J, Lei L, Adeyemo AA, Doumatey AP, Rotimi CN. Genome-wide analyses of multiple obesity-related cytokines and hormones informs biology of cardiometabolic traits. Genome Med 2021; 13:156. [PMID: 34620218 PMCID: PMC8499470 DOI: 10.1186/s13073-021-00971-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 09/16/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND A complex set of perturbations occur in cytokines and hormones in the etiopathogenesis of obesity and related cardiometabolic conditions such as type 2 diabetes (T2D). Evidence for the genetic regulation of these cytokines and hormones is limited, particularly in African-ancestry populations. In order to improve our understanding of the biology of cardiometabolic traits, we investigated the genetic architecture of a large panel of obesity- related cytokines and hormones among Africans with replication analyses in African Americans. METHODS We performed genome-wide association studies (GWAS) in 4432 continental Africans, enrolled from Ghana, Kenya, and Nigeria as part of the Africa America Diabetes Mellitus (AADM) study, for 13 obesity-related cytokines and hormones, including adipsin, glucose-dependent insulinotropic peptide (GIP), glucagon-like peptide-1 (GLP-1), interleukin-1 receptor antagonist (IL1-RA), interleukin-6 (IL-6), interleukin-10 (IL-10), leptin, plasminogen activator inhibitor-1 (PAI-1), resistin, visfatin, insulin, glucagon, and ghrelin. Exact and local replication analyses were conducted in African Americans (n = 7990). The effects of sex, body mass index (BMI), and T2D on results were investigated through stratified analyses. RESULTS GWAS identified 39 significant (P value < 5 × 10-8) loci across all 13 traits. Notably, 14 loci were African-ancestry specific. In this first GWAS for adipsin and ghrelin, we detected 13 and 4 genome-wide significant loci respectively. Stratified analyses by sex, BMI, and T2D showed a strong effect of these variables on detected loci. Eight novel loci were successfully replicated: adipsin (3), GIP (1), GLP-1 (1), and insulin (3). Annotation of these loci revealed promising links between these adipocytokines and cardiometabolic outcomes as illustrated by rs201751833 for adipsin and blood pressure and locus rs759790 for insulin level and T2D in lean individuals. CONCLUSIONS Our study identified genetic variants underlying variation in multiple adipocytokines, including the first loci for adipsin and ghrelin. We identified population differences in variants associated with adipocytokines and highlight the importance of stratification for discovery of loci. The high number of African-specific loci detected emphasizes the need for GWAS in African-ancestry populations, as these loci could not have been detected in other populations. Overall, our work contributes to the understanding of the biology linking adipocytokines to cardiometabolic traits.
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Affiliation(s)
- Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Mateus H Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Lin Lei
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA.
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA.
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27
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Tan Q, Li S, Sørensen M, Nygaard M, Mengel‐From J, Christensen K. Age patterns of intra-pair DNA methylation discordance in twins: Sex difference in epigenomic instability and implication on survival. Aging Cell 2021; 20:e13460. [PMID: 34427971 PMCID: PMC8441297 DOI: 10.1111/acel.13460] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 07/22/2021] [Accepted: 08/06/2021] [Indexed: 12/19/2022] Open
Abstract
Aging is a biological process linked to specific patterns and changes in the epigenome. We hypothesize that age‐related variation in the DNA methylome could reflect cumulative environmental modulation to the epigenome which could impact epigenomic instability and survival differentially by sex. To test the hypothesis, we performed sex‐stratified epigenome‐wide association studies on age‐related intra‐pair DNA methylation discordance in 492 twins aged 56–80 years. We identified 3084 CpGs showing increased methylation variability with age (FDR < 0.05, 7 CpGs with p < 1e‐07) in male twins but no significant site found in female twins. The results were replicated in an independent cohort of 292 twins aged 30–74 years with 37% of the discovery CpGs successfully replicated in male twins. Functional annotation showed that genes linked to the identified CpGs were significantly enriched in signaling pathways, neurological functions, extracellular matrix assembly, and cancer. We further explored the implication of discovery CpGs on individual survival in an old cohort of 224 twins (220 deceased). In total, 264 CpGs displayed significant association with risk of death in male twins. In female twins, 175 of the male discovery CpGs also showed non‐random correlation with mortality. Intra‐pair comparison showed that majority of the discovery CpGs have higher methylation in the longer‐lived twins suggesting that loss of DNA methylation during aging contributes to increased risk of death which is more pronounced in male twins. In conclusion, age‐related epigenomic instability in the DNA methylome is more evident in males than in females and could impact individual survival and contribute to sex difference in human lifespan.
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Affiliation(s)
- Qihua Tan
- Epidemiology, Biostatistics and Biodemography Department of Public Health University of Southern Denmark Odense Denmark
- Unit of Human Genetics Department of Clinical Research University of Southern Denmark Odense Denmark
| | - Shuxia Li
- Epidemiology, Biostatistics and Biodemography Department of Public Health University of Southern Denmark Odense Denmark
| | - Mette Sørensen
- Epidemiology, Biostatistics and Biodemography Department of Public Health University of Southern Denmark Odense Denmark
| | - Marianne Nygaard
- Epidemiology, Biostatistics and Biodemography Department of Public Health University of Southern Denmark Odense Denmark
| | - Jonas Mengel‐From
- 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
- Unit of Human Genetics Department of Clinical Research University of Southern Denmark Odense Denmark
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28
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Lin WY, Chan CC, Liu YL, Yang AC, Tsai SJ, Kuo PH. Sex-specific autosomal genetic effects across 26 human complex traits. Hum Mol Genet 2021; 29:1218-1228. [PMID: 32160288 DOI: 10.1093/hmg/ddaa040] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 12/26/2019] [Accepted: 03/05/2020] [Indexed: 12/28/2022] Open
Abstract
Previous studies have shown that men and women have different genetic architectures across many traits. However, except waist-to-hip ratio (WHR) and waist circumference (WC), it remains unknown whether the genetic effects of a certain trait are weaker or stronger on men/women. With ~18 000 Taiwan Biobank subjects, we comprehensively investigate sexual heterogeneity in autosomal genetic effects, for traits regarding cardiovascular health, diabetes, kidney, liver, anthropometric profiles, blood, etc. 'Gene-by-sex interactions' (G $\times$ S) were detected in 18 out of 26 traits, each with an interaction P-value (${{P}}_{{INT}}$) less than $0.05/104={0.00048}$, where 104 is the number of tests conducted in this study. The most significant evidence of G $\times$ S was found in WHR (${{P}}_{{INT}}$ = 3.2 $\times{{10}}^{-{55}}$) and WC (${{P}}_{{INT}}$ = 2.3$\times{{10}}^{-{41}}$). As a novel G$\times$S investigation for other traits, we here find that the autosomal genetic effects are weaker on women than on men, for low-density lipoprotein cholesterol (LDL-C), uric acid (UA) and diabetes-related traits such as fasting glucose and glycated hemoglobin. For LDL-C and UA, the evidence of G$\times$S is especially notable in subjects aged less than 50 years, where estrogen can play a role in attenuating the autosomal genetic effects of these two traits. Men and women have systematically distinct environmental contexts caused by hormonal milieu and their specific society roles, which may trigger diverse gene expressions despite the same DNA materials. As many environmental exposures are difficult to collect and quantify, sex can serve as a good surrogate for these factors.
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Affiliation(s)
- Wan-Yu Lin
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.,Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Chang-Chuan Chan
- Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan.,Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Yu-Li Liu
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | - Albert C Yang
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, USA.,Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan.,Division of Psychiatry, National Yang-Ming University, Taipei, Taiwan.,Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Po-Hsiu Kuo
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.,Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
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29
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Lung T, Di Cesare P, Risch L, Nydegger U, Risch M. Elementary Laboratory Assays as Biomarkers of Ageing: Support for Treatment of COVID-19? Gerontology 2021; 67:503-516. [PMID: 34340235 PMCID: PMC8450824 DOI: 10.1159/000517659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 05/19/2021] [Indexed: 11/24/2022] Open
Abstract
Youth, working age and the elderly: On a timeline, chronological age (CA) and biological age (BA) may dissociate; nosological entities manifest themselves at different BAs. In determining which disease corresponds to a given age decade, statistical registries of causes of death are unreliable and this does not change with SARS CoV-2 infection. Beyond adolescence, ageing metrics involve estimations of changes in fitness, including prediction models to estimate the number of remaining years left to live. A substantial disparity in biomarker levels and health status of ageing can be observed: the difference in CA and BA in the large cohorts under consideration is glaring. Here, we focus more closely on ageing and senescence metrics in order to make information available for risk analysis non the least with COVID-19, including the most recent risk factors of ABO blood type and 3p21.31 chromosome cluster impacting on C5a and SC5b-9 plasma levels. From the multitude of routine medical laboratory assays, a potentially meaningful set of assays aimed to best reflect the stage of individual senescence; hence risk factors the observational prospective SENIORLABOR study of 1,467 healthy elderly performed since 2009 and similar approaches since 1958 can be instantiated as a network to combine a set of elementary laboratory assays quantifying senescence.
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Affiliation(s)
- Thomas Lung
- Labormedizinisches Zentrum Dr. Risch, Vaduz, Liechtenstein
| | | | - Lorenz Risch
- Labormedizinisches Zentrum Dr. Risch, Vaduz, Liechtenstein
| | - Urs Nydegger
- Labormedizinisches Zentrum Dr. Risch, Vaduz, Liechtenstein
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30
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Westerman KE, Pham DT, Hong L, Chen Y, Sevilla-González M, Sung YJ, Sun YV, Morrison AC, Chen H, Manning AK. CLUE: Exact maximal reduction of kinetic models by constrained lumping of differential equations. Bioinformatics 2021; 37:btab223. [PMID: 34037712 PMCID: PMC8545347 DOI: 10.1093/bioinformatics/btab223] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 03/09/2021] [Accepted: 04/07/2021] [Indexed: 01/19/2023] Open
Abstract
MOTIVATION Detailed mechanistic models of biological processes can pose significant challenges for analysis and parameter estimations due to the large number of equations used to track the dynamics of all distinct configurations in which each involved biochemical species can be found. Model reduction can help tame such complexity by providing a lower-dimensional model in which each macro-variable can be directly related to the original variables. RESULTS We present CLUE, an algorithm for exact model reduction of systems of polynomial differential equations by constrained linear lumping. It computes the smallest dimensional reduction as a linear mapping of the state space such that the reduced model preserves the dynamics of user-specified linear combinations of the original variables. Even though CLUE works with nonlinear differential equations, it is based on linear algebra tools, which makes it applicable to high-dimensional models. Using case studies from the literature, we show how CLUE can substantially lower model dimensionality and help extract biologically intelligible insights from the reduction. AVAILABILITY An implementation of the algorithm and relevant resources to replicate the experiments herein reported are freely available for download at https://github.com/pogudingleb/CLUE. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Kenneth E Westerman
- Department of Medicine, Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA 02114, USA
- Metabolism Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Duy T Pham
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Liang Hong
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Ye Chen
- Department of Medicine, Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Magdalena Sevilla-González
- Department of Medicine, Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA 02114, USA
- Metabolism Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63130, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63130, USA
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA 30322, USA
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Center for Precision Health, School of Public Health and School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Alisa K Manning
- Department of Medicine, Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA 02114, USA
- Metabolism Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
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31
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The genetic predisposition to longevity acts through behavioral phenotypes in females. Eur Neuropsychopharmacol 2021; 45:1-14. [PMID: 33730682 DOI: 10.1016/j.euroneuro.2021.02.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 02/10/2021] [Accepted: 02/15/2021] [Indexed: 02/08/2023]
Abstract
The discovery of genetic factors for the predisposition of longevity is promising but their functional role and clinical relevance remain largely unclear. Based on results from a large genome-wide association study (GWAS) on human longevity (N ≈ 390,000) we identified six phenotype categories belonging to behavioral and psychiatric traits showing significant genetic correlations using LD Hub. We validated these genetic correlations on the phenotype level in a general population sample using a polygenic risk score (PRS) based on the longevity GWAS as proxy for longevity (N ≈ 8190; Study of Health in Pomerania). The behavioral phenotypes education, smoking and body mass index (BMI) were highly associated with the PRS for longevity especially in females (peducation=0.003, psmoking=0.049, pBMI=2.0E-4) with increased rates for higher education, lower smoking rates and decrease in BMI attributed to a higher PRS for longevity. Moreover, the psychiatric phenotypes depression and subjective health complaints showed significant associations (pDEPR=0.032, pSHC=0.002) in females only. Generally, a higher genetic predisposition for longevity had a stronger association with behavioral phenotypes in females than in males. It is unclear what causes the higher ``behavioral heterogeneity'' in males but different biological mechanisms might be involved. Sensitivity analyses showed that the association for the PRS for longevity with BMI and smoking were robust against adjustment with the PRS for BMI and smoking. In conclusion, our analyses demonstrated that genetic information obtained from highly powered GWAS for longevity revealed a clear behavioral signature on the phenotype level in a smaller population based sample.
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32
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Guerini FR, Cesari M, Arosio B. Hypothetical COVID-19 protection mechanism: hints from centenarians. IMMUNITY & AGEING 2021; 18:15. [PMID: 33785044 PMCID: PMC8008020 DOI: 10.1186/s12979-021-00226-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Accepted: 03/15/2021] [Indexed: 01/06/2023]
Abstract
The risk of serious complications and the fatality rate due to COVID-19 pandemic have proven particularly higher in older persons, putting a further strain in healthcare system as we dramatically observed. COVID-19 is not exclusively gerophile (géro “old” and philia “love”) as young people can be infected, even if older people experience more severe symptoms and mortality due to their greater frailty. Indeed, frailty could complicate the course of COVID-19, much more than the number of years lived. As demonstration, there are centenarians showing remarkable capacity to recover after coronavirus infection. We hypothesize that centenarian’s portfolio could help in identifying protective biological mechanisms underlying the coronavirus infection. The human leukocyte antigen (HLA) is one of the major genetic regions associated with human longevity, due to its central role in the development of adaptive immune response and modulation of the individual’s response to life threatening diseases. The HLA locus seems to be crucial in influencing susceptibility and severity of COVID-19. In this hypothesis, we assume that the biological process in which HLA are involved may explain some aspects of coronavirus infection in centenarians, although we cannot rule out other biological mechanisms that these extraordinary persons are able to adopt to cope with the infection.
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Affiliation(s)
| | - Matteo Cesari
- Geriatric Unit, IRCCS Istituti Clinici Scientifici Maugeri, Milan, Italy.,Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Beatrice Arosio
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy. .,Geriatric Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
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33
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Yao Y, Liu L, Guo G, Zeng Y, Ji JS. Interaction of Sirtuin 1 (SIRT1) candidate longevity gene and particulate matter (PM2.5) on all-cause mortality: a longitudinal cohort study in China. Environ Health 2021; 20:25. [PMID: 33715628 PMCID: PMC7958462 DOI: 10.1186/s12940-021-00718-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 03/10/2021] [Indexed: 05/29/2023]
Abstract
BACKGROUND The SIRT1 gene was associated with the lifespan in several organisms through inflammatory and oxidative stress pathways. Long-term air particulate matter (PM) is detrimental to health through the same pathways. METHODS We used the Chinese Longitudinal Healthy Longevity Survey (CLHLS) to investigate whether there is a gene-environment (G × E) interaction of SIRT1 and air pollution on mortality in an older cohort in China. Among 7083 participants with a mean age of 81.1 years, we genotyped nine SIRT1 alleles for each participant and assessed PM2.5 concentration using 3-year average concentrations around each participant's residence. We used Cox-proportional hazards models to estimate the independent and joint effects of SIRT1 polymorphisms and PM2.5 exposure on all-cause mortality, adjusting for a set of confounders. RESULTS There were 2843 deaths over 42,852 person-years. The mortality hazard ratio (HR) and 95% confidence interval (CI) for each 10 μg/m3 increase in PM2·5 was 1.08 (1.05-1.11); for SIRT1_391 was 0.77 (0.61, 0.98) in the recessive model after adjustment. In stratified analyses, participants carrying two SIRT1_391 minor alleles had a significantly higher HR for each 10 μg/m3 increase in PM2.5 than those carrying zero minor alleles (1.323 (95% CI: 1.088, 1.610) vs. 1.062 (1.028, 1.096) p for interaction = 0.03). Moreover, the interaction of SIRT1 and air pollution on mortality is significant among women but not among men. We did not see significant relationships for SIRT1_366, SIRT1_773, and SIRT1_720. CONCLUSION We found a gene-environment interaction of SIRT1 and air pollution on mortality, future experimental studies are warranted to depict the mechanism observed in this study.
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Affiliation(s)
- Yao Yao
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China
| | - Linxin Liu
- Environmental Research Center, Duke Kunshan University, 22 Address: No. 8 Duke Avenue, Kunshan, 215316 Jiangsu China
| | - Guang Guo
- Department of Sociology, Carolina Population Center, and Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - 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, Duke Medical School, Durham, NC USA
| | - John S. Ji
- Environmental Research Center, Duke Kunshan University, 22 Address: No. 8 Duke Avenue, Kunshan, 215316 Jiangsu China
- Nicholas School of the Environment, Duke University, Durham, NC USA
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34
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Liu X, Song Z, Li Y, Yao Y, Fang M, Bai C, An P, Chen H, Chen Z, Tang B, Shen J, Gao X, Zhang M, Chen P, Zhang T, Jia H, Liu X, Hou Y, Yang H, Wang J, Wang F, Xu X, Min J, Nie C, Zeng Y. Integrated genetic analyses revealed novel human longevity loci and reduced risks of multiple diseases in a cohort study of 15,651 Chinese individuals. Aging Cell 2021; 20:e13323. [PMID: 33657282 PMCID: PMC7963337 DOI: 10.1111/acel.13323] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 01/16/2021] [Accepted: 01/23/2021] [Indexed: 12/14/2022] Open
Abstract
There is growing interest in studying the genetic contributions to longevity, but limited relevant genes have been identified. In this study, we performed a genetic association study of longevity in a total of 15,651 Chinese individuals. Novel longevity loci, BMPER (rs17169634; p = 7.91 × 10-15 ) and TMEM43/XPC (rs1043943; p = 3.59 × 10-8 ), were identified in a case-control analysis of 11,045 individuals. BRAF (rs1267601; p = 8.33 × 10-15 ) and BMPER (rs17169634; p = 1.45 × 10-10 ) were significantly associated with life expectancy in 12,664 individuals who had survival status records. Additional sex-stratified analyses identified sex-specific longevity genes. Notably, sex-differential associations were identified in two linkage disequilibrium blocks in the TOMM40/APOE region, indicating potential differences during meiosis between males and females. Moreover, polygenic risk scores and Mendelian randomization analyses revealed that longevity was genetically causally correlated with reduced risks of multiple diseases, such as type 2 diabetes, cardiovascular diseases, and arthritis. Finally, we incorporated genetic markers, disease status, and lifestyles to classify longevity or not-longevity groups and predict life span. Our predictive models showed good performance (AUC = 0.86 for longevity classification and explained 19.8% variance of life span) and presented a greater predictive efficiency in females than in males. Taken together, our findings not only shed light on the genetic contributions to longevity but also elucidate correlations between diseases and longevity.
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Affiliation(s)
- Xiaomin Liu
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
- BGI Education Center University of Chinese Academy of Sciences Shenzhen China
| | - Zijun Song
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
| | - Yan Li
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Yao Yao
- Center for the Study of Aging and Human Development Medical School of Duke University Durham USA
- Center for Healthy Aging and Development Studies National School of Development, Raissun Institute for Advanced Studies, Peking University Beijing China
| | - Mingyan Fang
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Chen Bai
- Center for Healthy Aging and Development Studies National School of Development, Raissun Institute for Advanced Studies, Peking University Beijing China
- School of Labor and Human Resources Renmin University Beijing China
| | - Peng An
- Beijing Advanced Innovation Center for Food Nutrition and Human Health China Agricultural University Beijing China
| | - Huashuai Chen
- Business School of Xiangtan University Xiangtan China
| | - Zhihua Chen
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Biyao Tang
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
| | - Juan Shen
- BGI Genomics BGI‐Shenzhen Shenzhen China
| | - Xiaotong Gao
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
| | | | - Pengyu Chen
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
| | - Tao Zhang
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Huijue Jia
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Xiao Liu
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Yong Hou
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Huanming Yang
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Jian Wang
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Fudi Wang
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
- Beijing Advanced Innovation Center for Food Nutrition and Human Health China Agricultural University Beijing China
| | - Xun Xu
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
- Guangdong Provincial Key Laboratory of Genome Read and Write Shenzhen China
| | - Junxia Min
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
| | - Chao Nie
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Yi Zeng
- Center for the Study of Aging and Human Development Medical School of Duke University Durham USA
- Center for Healthy Aging and Development Studies National School of Development, Raissun Institute for Advanced Studies, Peking University Beijing China
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35
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Liu X, Tang S, Zhong H, Tong X, Jie Z, Ding Q, Wang D, Guo R, Xiao L, Xu X, Yang H, Wang J, Zong Y, Liu W, Liu X, Zhang Y, Brix S, Kristiansen K, Hou Y, Jia H, Zhang T. A genome-wide association study for gut metagenome in Chinese adults illuminates complex diseases. Cell Discov 2021; 7:9. [PMID: 33563976 PMCID: PMC7873036 DOI: 10.1038/s41421-020-00239-w] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 12/11/2020] [Indexed: 12/12/2022] Open
Abstract
The gut microbiome has been established as a key environmental factor to health. Genetic influences on the gut microbiome have been reported, yet, doubts remain as to the significance of genetic associations. Here, we provide shotgun data for whole genome and whole metagenome from a Chinese cohort, identifying no <20% genetic contribution to the gut microbiota. Using common variants-, rare variants-, and copy number variations-based association analyses, we identified abundant signals associated with the gut microbiome especially in metabolic, neurological, and immunological functions. The controversial concept of enterotypes may have a genetic attribute, with the top two loci explaining 11% of the Prevotella-Bacteroides variances. Stratification according to gender led to the identification of differential associations in males and females. Our two-stage metagenome genome-wide association studies on a total of 1295 individuals unequivocally illustrates that neither microbiome nor GWAS studies could overlook one another in our quest for a better understanding of human health and diseases.
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Affiliation(s)
- Xiaomin Liu
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- China National Genebank, BGI-Shenzhen, Shenzhen,, Guangdong 518120, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen,, Guangdong 518083, China
| | - Shanmei Tang
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- China National Genebank, BGI-Shenzhen, Shenzhen,, Guangdong 518120, China
| | - Huanzi Zhong
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- Department of Biology, University of Copenhagen, Universitetsparken 13, DK-2100, Copenhagen, Denmark
| | - Xin Tong
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- Shenzhen Key Laboratory of Cognition and Gene Research, BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
| | - Zhuye Jie
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- Shenzhen Key Laboratory of Human Commensal Microorganisms and Health Research, BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
| | - Qiuxia Ding
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
| | - Dan Wang
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- China National Genebank, BGI-Shenzhen, Shenzhen,, Guangdong 518120, China
| | - Ruidong Guo
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
| | - Liang Xiao
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- Shenzhen Engineering Laboratory of Detection and Intervention of Human Intestinal Microbiome, BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- BGI-Qingdao, BGI-Shenzhen, Qingdao,, Shandong 266555, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- China National Genebank, BGI-Shenzhen, Shenzhen,, Guangdong 518120, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- James D. Watson Institute of Genome Sciences, Hangzhou,, Zhejiang 310058, China
| | - Jian Wang
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- James D. Watson Institute of Genome Sciences, Hangzhou,, Zhejiang 310058, China
| | - Yang Zong
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
| | - Weibin Liu
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
| | - Xiao Liu
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
| | - Yong Zhang
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
| | - Susanne Brix
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- Department of Biotechnology and Biomedicine, Technical University of Denmark, 2800 Kgs, Lyngby, Denmark
| | - Karsten Kristiansen
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China
- Department of Biology, University of Copenhagen, Universitetsparken 13, DK-2100, Copenhagen, Denmark
| | - Yong Hou
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China.
| | - Huijue Jia
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China.
- Shenzhen Key Laboratory of Human Commensal Microorganisms and Health Research, BGI-Shenzhen, Shenzhen,, Guangdong 518083, China.
| | - Tao Zhang
- BGI-Shenzhen, Shenzhen,, Guangdong 518083, China.
- China National Genebank, BGI-Shenzhen, Shenzhen,, Guangdong 518120, China.
- Department of Biology, University of Copenhagen, Universitetsparken 13, DK-2100, Copenhagen, Denmark.
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36
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Xiao L, Zan G, Feng X, Bao Y, Huang S, Luo X, Xu X, Zhang Z, Yang X. The associations of multiple metals mixture with accelerated DNA methylation aging. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 269:116230. [PMID: 33316491 DOI: 10.1016/j.envpol.2020.116230] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 10/29/2020] [Accepted: 12/03/2020] [Indexed: 06/12/2023]
Abstract
Aging is a leading cause of mortality for the elderly and DNA methylation age is reported to be predictive of biological aging. However, few studies have investigated the associations between multiple metals exposure and accelerated aging in the elderly. We performed a pilot study of 288 elderly participants aged 50-115 years and measured genome-wide DNA methylation and 22 blood metals concentrations. Measures of DNA methylation age were estimated using CpGs from Illumina HumanMethylation EPIC BeadChip. Linear mixed regression and Bayesian kernel machine regression (BKMR) models were used to estimate the individual and overall associations between multiple metals and accelerated methylation aging. Single metal models revealed that each 1-standard deviance (SD) increase in log-transformed vanadium, cobalt, nickel, zinc, arsenic, and barium was associated with a -2.256, -1.318, 1.004, -1.926, 1.910 and -1.356 changes in ΔAge, respectively; meanwhile, for aging rate, the change was -0.019, -0.013, 0.010, -0.018, 0.023, and -0.012, respectively (all P < 0.05). The BKMR models showed reverse U-shaped associations of the overall metals mixture with ΔAge and aging rate. Downward trends of ΔAge and aging rate were observed for increasing quantiles of essential metals mixture, but upward trends were observed for non-essential metals mixture. Further individual analysis of the BKMR revealed that the 95% confidence interval of ΔAge and aging rate associated with vanadium, zinc, and arsenic did not cross 0, when other metals concentrations set at 25th, 50th, and 75th percentile. Our findings suggest reverse U-shaped associations of the overall metals mixture with accelerated methylation aging for the first time, and vanadium, zinc, and arsenic may be major contributors driving the associations.
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Affiliation(s)
- Lili Xiao
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Gaohui Zan
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Xiuming Feng
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Yu Bao
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Sifang Huang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Xiaoyu Luo
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Xia Xu
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Zhiyong Zhang
- School of Public Health, Guilin Medical University, Guilin, Guangxi, China
| | - Xiaobo Yang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China; Department of Public Health, School of Medicine, Guangxi University of Science and Technology, Liuzhou, Guangxi, China.
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37
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Ye Y, Chen X, Han J, Jiang W, Natarajan P, Zhao H. Interactions Between Enhanced Polygenic Risk Scores and Lifestyle for Cardiovascular Disease, Diabetes, and Lipid Levels. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2021; 14:e003128. [PMID: 33433237 DOI: 10.1161/circgen.120.003128] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
BACKGROUND Both lifestyle and genetic factors confer risk for cardiovascular diseases, type 2 diabetes, and dyslipidemia. However, the interactions between these 2 groups of risk factors were not comprehensively understood due to previous poor estimation of genetic risk. Here we set out to develop enhanced polygenic risk scores (PRS) and systematically investigate multiplicative and additive interactions between PRS and lifestyle for coronary artery disease, atrial fibrillation, type 2 diabetes, total cholesterol, triglyceride, and LDL-cholesterol. METHODS Our study included 276 096 unrelated White British participants from the UK Biobank. We investigated several PRS methods (P+T, LDpred, PRS continuous shrinkage, and AnnoPred) and showed that AnnoPred achieved consistently improved prediction accuracy for all 6 diseases/traits. With enhanced PRS and combined lifestyle status categorized by smoking, body mass index, physical activity, and diet, we investigated both multiplicative and additive interactions between PRS and lifestyle using regression models. RESULTS We observed that healthy lifestyle reduced disease incidence by similar multiplicative magnitude across different PRS groups. The absolute risk reduction from lifestyle adherence was, however, significantly greater in individuals with higher PRS. Specifically, for type 2 diabetes, the absolute risk reduction from lifestyle adherence was 12.4% (95% CI, 10.0%-14.9%) in the top 1% PRS versus 2.8% (95% CI, 2.3%-3.3%) in the bottom PRS decile, leading to a ratio of >4.4. We also observed a significant interaction effect between PRS and lifestyle on triglyceride level. CONCLUSIONS By leveraging functional annotations, AnnoPred outperforms state-of-the-art methods on quantifying genetic risk through PRS. Our analyses based on enhanced PRS suggest that individuals with high genetic risk may derive similar relative but greater absolute benefit from lifestyle adherence.
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Affiliation(s)
- Yixuan Ye
- Program of Computational Biology and Bioinformatics (Y.Y., H.Z.), Yale University
| | - Xi Chen
- Department of Statistics and Data Science (X.C., J.H.), Yale University.,Department of Molecular Biophysics and Biochemistry (X.C., J.H.), Yale University
| | - James Han
- Department of Statistics and Data Science (X.C., J.H.), Yale University.,Department of Molecular Biophysics and Biochemistry (X.C., J.H.), Yale University
| | - Wei Jiang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT (W.J., H.Z.)
| | - Pradeep Natarajan
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston (P.N.).,Program in Medical and Population Genetics, Broad Institute of Harvard & Massachusetts Institute of Technology, Cambridge, MA (P.N.)
| | - Hongyu Zhao
- Program of Computational Biology and Bioinformatics (Y.Y., H.Z.), Yale University.,Department of Biostatistics, Yale School of Public Health, New Haven, CT (W.J., H.Z.)
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Zhao X, Liang S, Wang N, Hong T, Sambou M, Fan J, Zhu M, Wang C, Hang D, Jiang Y, Dai J. Sex-Specific Associations of Testosterone and Genetic Factors With Health Span. Front Endocrinol (Lausanne) 2021; 12:773464. [PMID: 34899607 PMCID: PMC8655098 DOI: 10.3389/fendo.2021.773464] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 10/26/2021] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Previous studies have suggested associations between testosterone, genetic factors, and a series of complex diseases, but the associations with the lifespan phenotype, such as health span, remain unclear. METHODS In this prospective cohort study, we analyzed 145,481 men and 147,733 women aged 38-73 years old from UK Biobank (UKB) to investigate the sex-specific associations of total testosterone (TT), free testosterone (FT), or polygenic risk score (PRS) with health span termination (HST) risk. At baseline, serum testosterone levels were measured. HST was defined by eight events strongly associated with longevity. PRS, an efficient tool combining the effect of common genetic variants to discriminate genetic risk of complex phenotypes, was constructed by 12 single-nucleotide polymorphisms related to health span from UKB (P ≤ 5.0 × 10-8). We used multivariable Cox regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS With a median follow-up time of 7.70 years, 26,748 (18.39%) men and 18,963 (12.84%) women had HST. TT was negatively associated with HST in men [HR per standard deviation (SD) increment of log-TT: 0.92, 95% CI: 0.88-0.97]. Inversely, both TT (HR per SD increment of log-TT: 1.05, 95% CI: 1.02-1.08) and FT (HR per SD increment of log-FT: 1.08, 95% CI: 1.05-1.11) presented an increased risk of HST in women. PRS was positively associated with HST risk (quintile 5 versus quintile 1, men, HR: 1.19, 95% CI: 1.15-1.24; women, HR: 1.21, 95% CI: 1.16-1.27). Moreover, men with high TT and low genetic risk showed the lowest HST risk (HR: 0.80, 95% CI: 0.73-0.88), whereas HST risk for women with both high TT and genetic risk increased obviously (HR: 1.32, 95% CI: 1.19-1.46). Similar joint effects were observed for FT in both genders. CONCLUSIONS We observed sex-specific associations that testosterone was negatively associated with HST risk in men and positively associated with HST risk in women. Genetic factors increased the HST risk, suggesting that participants with both high genetic risk and abnormal testosterone levels (high level in women or low level in men) should be the target for early intervention. Although our findings highlight the associations between testosterone and health span, further mechanistic studies and prospective trials are warranted to explore the causation behind.
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Affiliation(s)
- Xiaoyu Zhao
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Shuang Liang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Nanxi Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Tongtong Hong
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Muhammed Lamin Sambou
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jingyi Fan
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Cheng Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Dong Hang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Yue Jiang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
- *Correspondence: Juncheng Dai,
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Yashin AI, Wu D, Arbeev K, Yashkin AP, Akushevich I, Bagley O, Duan M, Ukraintseva S. Roles of interacting stress-related genes in lifespan regulation: insights for translating experimental findings to humans. JOURNAL OF TRANSLATIONAL GENETICS AND GENOMICS 2021; 5:357-379. [PMID: 34825130 PMCID: PMC8612394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
AIM Experimental studies provided numerous evidence that caloric/dietary restriction may improve health and increase the lifespan of laboratory animals, and that the interplay among molecules that sense cellular stress signals and those regulating cell survival can play a crucial role in cell response to nutritional stressors. However, it is unclear whether the interplay among corresponding genes also plays a role in human health and lifespan. METHODS Literature about roles of cellular stressors have been reviewed, such as amino acid deprivation, and the integrated stress response (ISR) pathway in health and aging. Single nucleotide polymorphisms (SNPs) in two candidate genes (GCN2/EIF2AK4 and CHOP/DDIT3) that are closely involved in the cellular stress response to amino acid starvation, have been selected using information from experimental studies. Associations of these SNPs and their interactions with human survival in the Health and Retirement Study data have been estimated. The impact of collective associations of multiple interacting SNP pairs on survival has been evaluated, using a recently developed composite index: the SNP-specific Interaction Polygenic Risk Score (SIPRS). RESULTS Significant interactions have been found between SNPs from GCN2/EIF2AK4 and CHOP/DDI3T genes that were associated with survival 85+ compared to survival between ages 75 and 85 in the total sample (males and females combined) and in females only. This may reflect sex differences in genetic regulation of the human lifespan. Highly statistically significant associations of SIPRS [constructed for the rs16970024 (GCN2/EIF2AK4) and rs697221 (CHOP/DDIT3)] with survival in both sexes also been found in this study. CONCLUSION Identifying associations of the genetic interactions with human survival is an important step in translating the knowledge from experimental to human aging research. Significant associations of multiple SNPxSNP interactions in ISR genes with survival to the oldest old age that have been found in this study, can help uncover mechanisms of multifactorial regulation of human lifespan and its heterogeneity.
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Franceschi C, Garagnani P, Olivieri F, Salvioli S, Giuliani C. The Contextualized Genetics of Human Longevity: JACC Focus Seminar. J Am Coll Cardiol 2020; 75:968-979. [PMID: 32130932 DOI: 10.1016/j.jacc.2019.12.032] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 12/13/2019] [Accepted: 12/17/2019] [Indexed: 12/17/2022]
Abstract
The genetics of human longevity has long been studied, and in this regard, centenarians represent a very informative model. Centenarians are characterized by 2 main features: 1) the capability to avoid or postpone the major age-related diseases; and 2) a high level of heterogeneity of their phenotype. The first suggests that longevity and resistance to diseases are mediated by shared mechanisms, the latter that many strategies can be used to become long lived, likely as a result of variable genome-environment interactions. The authors suggest that the complexity of genome-environment interactions must be considered within an evolutionary and ecological perspective and that the concept of "risk allele" is highly context dependent, changing with age, time, and geography. Genes involved in both longevity and cardiovascular diseases, taken as a paradigmatic example of age-related diseases, as well as other emerging topics in genetics of longevity, such as micro-ribonucleic acid (miRNA) genetics, polygenic risk scores, environmental pollutants, and somatic mutations are discussed.
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Affiliation(s)
- Claudio Franceschi
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy; Department of Applied Mathematics, Institute of Information Technology, Mathematics and Mechanics, Lobachevsky State University of Nizhny Novgorod-National Research University, Nizhny Novgorod, Russia.
| | - Paolo Garagnani
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Fabiola Olivieri
- Laboratory of Experimental Pathology, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy; Center of Clinical Pathology and Regenerative Therapy, IRCCS INRCA, Ancona, Italy
| | - Stefano Salvioli
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Cristina Giuliani
- Laboratory of Molecular Anthropology and Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy.
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Yusipov I, Bacalini MG, Kalyakulina A, Krivonosov M, Pirazzini C, Gensous N, Ravaioli F, Milazzo M, Giuliani C, Vedunova M, Fiorito G, Gagliardi A, Polidoro S, Garagnani P, Ivanchenko M, Franceschi C. Age-related DNA methylation changes are sex-specific: a comprehensive assessment. Aging (Albany NY) 2020; 12:24057-24080. [PMID: 33276343 PMCID: PMC7762479 DOI: 10.18632/aging.202251] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 10/19/2020] [Indexed: 12/18/2022]
Abstract
The existence of a sex gap in human health and longevity has been widely documented. Autosomal DNA methylation differences between males and females have been reported, but so far few studies have investigated if DNA methylation is differently affected by aging in males and females. We performed a meta-analysis of 4 large whole blood datasets, comparing 4 aspects of epigenetic age-dependent remodeling between the two sexes: differential methylation, variability, epimutations and entropy. We reported that a large fraction (43%) of sex-associated probes undergoes age-associated DNA methylation changes, and that a limited number of probes show age-by-sex interaction. We experimentally validated 2 regions mapping in FIGN and PRR4 genes and showed sex-specific deviations of their methylation patterns in models of decelerated (centenarians) and accelerated (Down syndrome) aging. While we did not find sex differences in the age-associated increase in epimutations and entropy, we showed that the number of probes having an age-related increase in methylation variability is 15 times higher in males compared to females. Our results can offer new epigenetic tools to study the interaction between aging and sex and can pave the way to the identification of molecular triggers of sex differences in longevity and age-related diseases prevalence.
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Affiliation(s)
- Igor Yusipov
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky University, Nizhniy Novgorod, Russia.,Mathematics of Future Technologies Center, Lobachevsky University, Nizhniy Novgorod, Russia
| | | | - Alena Kalyakulina
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky University, Nizhniy Novgorod, Russia
| | - Mikhail Krivonosov
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky University, Nizhniy Novgorod, Russia
| | - Chiara Pirazzini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Noémie Gensous
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), Alma Mater Studiorum – University of Bologna, Bologna, Italy
| | - Francesco Ravaioli
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), Alma Mater Studiorum – University of Bologna, Bologna, Italy
| | - Maddalena Milazzo
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), Alma Mater Studiorum – University of Bologna, Bologna, Italy
| | - Cristina Giuliani
- Department of Biological, Geological, and Environmental Sciences (BiGeA), Laboratory of Molecular Anthropology and Centre for Genome Biology, University of Bologna, Bologna, Italy.,School of Anthropology and Museum Ethnography, University of Oxford, Oxford, UK
| | - Maria Vedunova
- Institute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhni Novgorod, Nizhni Novgorod, Russia
| | - Giovanni Fiorito
- Department of Biomedical Sciences, University of Sassari, Italy.,Department of Epidemiology and Public Health, MRC/HPA Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London W2 1PG, UK
| | - Amedeo Gagliardi
- Italian Institute for Genomic Medicine (IIGM), Candiolo 10060, Italy.,Candiolo Cancer Institute, FPO-IRCCS, Candiolo 10060, Italy
| | - Silvia Polidoro
- Department of Epidemiology and Public Health, MRC/HPA Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London W2 1PG, UK.,Italian Institute for Genomic Medicine (IIGM), Candiolo 10060, Italy.,Candiolo Cancer Institute, FPO-IRCCS, Candiolo 10060, Italy
| | - Paolo Garagnani
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), Alma Mater Studiorum – University of Bologna, Bologna, Italy.,Department of Laboratory Medicine, Clinical Chemistry, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.,Applied Biomedical Research Center (CRBA), Policlinico S.Orsola-Malpighi Polyclinic, Bologna, Italy.,CNR Institute of Molecular Genetics “Luigi Luca Cavalli-Sforza", Unit of Bologna, Bologna, Italy
| | - Mikhail Ivanchenko
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky University, Nizhniy Novgorod, Russia.,Mathematics of Future Technologies Center, Lobachevsky University, Nizhniy Novgorod, Russia
| | - Claudio Franceschi
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky University, Nizhniy Novgorod, Russia
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Dong J, Maj C, Tsavachidis S, Ostrom QT, Gharahkhani P, Anderson LA, Wu AH, Ye W, Bernstein L, Borisov O, Schröder J, Chow WH, Gammon MD, Liu G, Caldas C, Pharoah PD, Risch HA, May A, Gerges C, Anders M, Venerito M, Schmidt T, Izbicki JR, Hölscher AH, Schumacher B, Vashist Y, Neuhaus H, Rösch T, Knapp M, Krawitz P, Böhmer A, Iyer PG, Reid BJ, Lagergren J, Shaheen NJ, Corley DA, Gockel I, Fitzgerald RC, Cook MB, Whiteman DC, Vaughan TL, Schumacher J, Thrift AP. Sex-Specific Genetic Associations for Barrett's Esophagus and Esophageal Adenocarcinoma. Gastroenterology 2020; 159:2065-2076.e1. [PMID: 32918910 PMCID: PMC9057456 DOI: 10.1053/j.gastro.2020.08.052] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 08/04/2020] [Accepted: 08/24/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND & AIMS Esophageal adenocarcinoma (EA) and its premalignant lesion, Barrett's esophagus (BE), are characterized by a strong and yet unexplained male predominance (with a male-to-female ratio in EA incidence of up to 6:1). Genome-wide association studies (GWAS) have identified more than 20 susceptibility loci for these conditions. However, potential sex differences in genetic associations with BE/EA remain largely unexplored. METHODS Given strong genetic overlap, BE and EA cases were combined into a single case group for analysis. These were compared with population-based controls. We performed sex-specific GWAS of BE/EA in 3 separate studies and then used fixed-effects meta-analysis to provide summary estimates for >9 million variants for male and female individuals. A series of downstream analyses were conducted separately in male and female individuals to identify genes associated with BE/EA and the genetic correlations between BE/EA and other traits. RESULTS We included 6758 male BE/EA cases, 7489 male controls, 1670 female BE/EA cases, and 6174 female controls. After Bonferroni correction, our meta-analysis of sex-specific GWAS identified 1 variant at chromosome 6q11.1 (rs112894788, KHDRBS2-MTRNR2L9, PBONF = .039) that was statistically significantly associated with BE/EA risk in male individuals only, and 1 variant at chromosome 8p23.1 (rs13259457, PRSS55-RP1L1, PBONF = 0.057) associated, at borderline significance, with BE/EA risk in female individuals only. We also observed strong genetic correlations of BE/EA with gastroesophageal reflux disease in male individuals and obesity in female individuals. CONCLUSIONS The identified novel sex-specific variants associated with BE/EA could improve the understanding of the genetic architecture of the disease and the reasons for the male predominance.
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Affiliation(s)
- Jing Dong
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas; Division of Hematology and Oncology, Department of Medicine, Cancer Center, and Genomic Sciences & Precision Medicine Center, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Carlo Maj
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University of Bonn, Germany
| | - Spiridon Tsavachidis
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Quinn T Ostrom
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Puya Gharahkhani
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Lesley A Anderson
- Centre for Public Health, Queen's University Belfast, Belfast, Northern Ireland & Aberdeen Center for Health Data Science, University of Aberdeen, Scotland
| | - Anna H Wu
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Weimin Ye
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Leslie Bernstein
- Department of Population Sciences, Beckman Research Institute and City of Hope Comprehensive Cancer Center, Duarte, California
| | - Oleg Borisov
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University of Bonn, Germany
| | - Julia Schröder
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Wong-Ho Chow
- Department of Epidemiology, MD Anderson Cancer Center, Houston, Texas
| | - Marilie D Gammon
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina
| | - Geoffrey Liu
- Pharmacogenomic Epidemiology, Ontario Cancer Institute, Toronto, Ontario, Canada
| | - Carlos Caldas
- Cancer Research UK, Cambridge Institute, Cambridge, UK
| | - Paul D Pharoah
- Department of Oncology, University of Cambridge, Cambridge, UK; Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Harvey A Risch
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut
| | - Andrea May
- Department of Medicine II, Sana Klinikum, Offenbach, Germany
| | - Christian Gerges
- Department of Internal Medicine II, Evangelisches Krankenhaus, Düsseldorf, Germany
| | - Mario Anders
- Department of Gastroenterology and Interdisciplinary Endoscopy, Vivantes Wenckebach-Klinikum, Berlin, Germany
| | - Marino Venerito
- Department of Gastroenterology, Hepatology and Infectious Diseases, Otto-von-Guericke University Hospital, Magdeburg, Germany
| | - Thomas Schmidt
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Jakob R Izbicki
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
| | - Arnulf H Hölscher
- Department of General, Visceral and Cancer Surgery, University of Cologne, Cologne, Germany
| | - Brigitte Schumacher
- Department of Internal Medicine and Gastroenterology, Elisabeth Hospital, Essen, Germany
| | - Yogesh Vashist
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
| | - Horst Neuhaus
- Department of Internal Medicine II, Evangelisches Krankenhaus, Düsseldorf, Germany
| | - Thomas Rösch
- Department of Interdisciplinary Endoscopy, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Michael Knapp
- Institute of Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany
| | - Peter Krawitz
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University of Bonn, Germany
| | - Anne Böhmer
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Prasad G Iyer
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota
| | - Brian J Reid
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Jesper Lagergren
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; School of Cancer and Pharmaceutical Sciences, King's College London, London, UK
| | - Nicholas J Shaheen
- Division of Gastroenterology and Hepatology, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Douglas A Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, California; San Francisco Medical Center, Kaiser Permanente Northern California, San Francisco, California
| | - Ines Gockel
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany
| | - Rebecca C Fitzgerald
- Medical Research Council (MRC) Cancer Unit, Hutchison-MRC Research Centre, University of Cambridge, Cambridge, UK
| | - Michael B Cook
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - David C Whiteman
- Cancer Control, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Thomas L Vaughan
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | | | - Aaron P Thrift
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas.
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Tidière M, Badruna A, Fouchet D, Gaillard JM, Lemaître JF, Pontier D. Pathogens Shape Sex Differences in Mammalian Aging. Trends Parasitol 2020; 36:668-676. [PMID: 32540194 PMCID: PMC7203054 DOI: 10.1016/j.pt.2020.05.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 05/01/2020] [Accepted: 05/01/2020] [Indexed: 11/28/2022]
Abstract
Understanding the origin of sex differences in lifespan and aging patterns remains a salient challenge in both biogerontology and evolutionary biology. Different factors have been studied but the potential influence of pathogens has never been investigated. Sex differences, especially in hormones and resource allocation, generate a differential response to pathogens and thereby shape sex differences in lifespan or aging. We provide an integrative framework linking host pathogenic environment with both sex-specific selections on immune performance and mortality trajectories. We propose future directions to fill existing knowledge gaps about mechanisms that link sex differences, not only to exposition and sensitivity to pathogens, but also to mortality patterns, whilst emphasizing the urgent need to consider the role of sex in medicine. Years of research in biomedical sciences have revealed that sex-specific immune responses to pathogens can be associated with sex-specific consequences on health. These effects partly account for the observed sex gap in lifespan, leading women to be longer-lived than males in human populations. Sexual selection exerted on males and the pathogenic environment may explain, at least partly, the sex-difference in lifespan generally observed across mammalian populations.
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Affiliation(s)
- Morgane Tidière
- Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, UMR5558, F-69622, Villeurbanne, France; LabEx ECOFECT, Université de Lyon, F-69000, Lyon, France.
| | - Adèle Badruna
- Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, UMR5558, F-69622, Villeurbanne, France; LabEx ECOFECT, Université de Lyon, F-69000, Lyon, France
| | - David Fouchet
- Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, UMR5558, F-69622, Villeurbanne, France; LabEx ECOFECT, Université de Lyon, F-69000, Lyon, France
| | - Jean-Michel Gaillard
- Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, UMR5558, F-69622, Villeurbanne, France; LabEx ECOFECT, Université de Lyon, F-69000, Lyon, France
| | - Jean-François Lemaître
- Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, UMR5558, F-69622, Villeurbanne, France; LabEx ECOFECT, Université de Lyon, F-69000, Lyon, France
| | - Dominique Pontier
- Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, UMR5558, F-69622, Villeurbanne, France; LabEx ECOFECT, Université de Lyon, F-69000, Lyon, France
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44
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Deelen J, Evans DS, Arking DE, Tesi N, Nygaard M, Liu X, Wojczynski MK, Biggs ML, van der Spek A, Atzmon G, Ware EB, Sarnowski C, Smith AV, Seppälä I, Cordell HJ, Dose J, Amin N, Arnold AM, Ayers KL, Barzilai N, Becker EJ, Beekman M, Blanché H, Christensen K, Christiansen L, Collerton JC, Cubaynes S, Cummings SR, Davies K, Debrabant B, Deleuze JF, Duncan R, Faul JD, Franceschi C, Galan P, Gudnason V, Harris TB, Huisman M, Hurme MA, Jagger C, Jansen I, Jylhä M, Kähönen M, Karasik D, Kardia SLR, Kingston A, Kirkwood TBL, Launer LJ, Lehtimäki T, Lieb W, Lyytikäinen LP, Martin-Ruiz C, Min J, Nebel A, Newman AB, Nie C, Nohr EA, Orwoll ES, Perls TT, Province MA, Psaty BM, Raitakari OT, Reinders MJT, Robine JM, Rotter JI, Sebastiani P, Smith J, Sørensen TIA, Taylor KD, Uitterlinden AG, van der Flier W, van der Lee SJ, van Duijn CM, van Heemst D, Vaupel JW, Weir D, Ye K, Zeng Y, Zheng W, Holstege H, Kiel DP, Lunetta KL, Slagboom PE, Murabito JM. A meta-analysis of genome-wide association studies identifies multiple longevity genes. Nat Commun 2019; 10:3669. [PMID: 31413261 PMCID: PMC6694136 DOI: 10.1038/s41467-019-11558-2] [Citation(s) in RCA: 168] [Impact Index Per Article: 33.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2018] [Accepted: 07/17/2019] [Indexed: 12/16/2022] Open
Abstract
Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.
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Affiliation(s)
- Joris Deelen
- Max Planck Institute for Biology of Ageing, 50866, Cologne, Germany.
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands.
| | - Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, 94158, USA.
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Niccolò Tesi
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, 2600 GA, Delft, The Netherlands
| | - Marianne Nygaard
- The Danish Aging Research Center, Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark
| | - Xiaomin Liu
- BGI-Shenzhen, Shenzhen, 518083, China
- China National Genebank, BGI-Shenzhen, Shenzhen, 518120, China
| | - Mary K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, Saint Louis, MO, 63110, USA
| | - Mary L Biggs
- Department of Biostatistics, University of Washington, Seattle, WA, 98115, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA
| | | | - Gil Atzmon
- Department of Biology, Faculty of Natural Science, University of Haifa, Haifa, 3498838, Israel
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Erin B Ware
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Chloé Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Albert V Smith
- School of Public Health, Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
- Icelandic Heart Association, 201, Kópavogur, Iceland
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland
| | - Heather J Cordell
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, NE1 3BZ, UK
| | - Janina Dose
- Institute of Clinical Molecular Biology, Kiel University, 24105, Kiel, Germany
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC, 3000 CA, Rotterdam, The Netherlands
| | - Alice M Arnold
- Department of Biostatistics, University of Washington, Seattle, WA, 98115, USA
| | | | - Nir Barzilai
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | | | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands
| | | | - Kaare Christensen
- The Danish Aging Research Center, Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark
- Clinical Biochemistry and Pharmacology, Odense University Hospital, 5000, Odense C, Denmark
- Department of Clinical Genetics, Odense University Hospital, 5000, Odense C, Denmark
| | - Lene Christiansen
- The Danish Aging Research Center, Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, 2100, Copenhagen, Denmark
| | - Joanna C Collerton
- Institute of Health & Society, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Sarah Cubaynes
- MMDN, Univ. Montpellier, EPHE, Unité Inserm 1198, PSL Research University, 34095, Montpellier, France
| | - Steven R Cummings
- California Pacific Medical Center Research Institute, San Francisco, CA, 94158, USA
| | - Karen Davies
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Birgit Debrabant
- Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark
| | - Jean-François Deleuze
- Fondation Jean Dausset-CEPH, 75010, Paris, France
- Centre National de Recherche en Génomique Humaine, CEA-Institut de Biologie François Jacob, 91000, Evry, France
| | - Rachel Duncan
- Institute of Health & Society, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
- Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Jessica D Faul
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Claudio Franceschi
- Department of Applied Mathematics and Centre of Bioinformatics, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, 603022, Russia
- IRCCS Institute of Neurological Sciences of Bologna (ISNB), 40124, Bologna, Italy
| | - Pilar Galan
- EREN, UMR U1153 Inserm/U1125 Inra/Cnam/Paris 13, Université Paris 13, CRESS, 93017, Bobigny, France
| | - Vilmundur Gudnason
- Icelandic Heart Association, 201, Kópavogur, Iceland
- Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Bethesda, MD, 20892, USA
| | - Martijn Huisman
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, 1007 MB, Amsterdam, The Netherlands
| | - Mikko A Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
| | - Carol Jagger
- Institute of Health & Society, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
- Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Iris Jansen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Marja Jylhä
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), Tampere University, 33104, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, 33521, Tampere, Finland
| | - David Karasik
- Azrieli Faculty of Medicine, Bar Ilan University, Safed, 13010, Israel
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, 02131, USA
| | - Sharon L R Kardia
- School of Public Health, Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Andrew Kingston
- Institute of Health & Society, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
- Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Thomas B L Kirkwood
- Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Bethesda, MD, 20892, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland
| | - Wolfgang Lieb
- Institute of Epidemiology and Biobank PopGen, Kiel University, 24105, Kiel, Germany
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland
| | - Carmen Martin-Ruiz
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Junxia Min
- Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, 311058, China
| | - Almut Nebel
- Institute of Clinical Molecular Biology, Kiel University, 24105, Kiel, Germany
| | - Anne B Newman
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Chao Nie
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Ellen A Nohr
- Research Unit of Gynecology and Obstetrics, Department of Clinical Research, University of Southern Denmark, 5000, Odense C, Denmark
| | - Eric S Orwoll
- Bone and Mineral Unit, Oregon Health Sciences University, Portland, OR, 97239, USA
| | - Thomas T Perls
- Department of Medicine, Geriatrics Section, Boston Medical Center, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, Saint Louis, MO, 63110, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA
- Department of Epidemiology, University of Washington, Seattle, WA, 98101, USA
- Department of Health Services, University of Washington, Seattle, WA, 98101, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, 98101, USA
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, 20521, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, 20014, Turku, Finland
| | - Marcel J T Reinders
- Delft Bioinformatics Lab, Delft University of Technology, 2600 GA, Delft, The Netherlands
| | - Jean-Marie Robine
- MMDN, Univ. Montpellier, EPHE, Unité Inserm 1198, PSL Research University, 34095, Montpellier, France
- CERMES3, UMR CNRS 8211-Unité Inserm 988-EHESS-Université Paris Descartes, 94801, Paris, France
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
- Division of Genetic Outcomes, Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Jennifer Smith
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, 48104, USA
- School of Public Health, Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, and Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen N, Denmark
- MRC Integrative Epidemiology Unit, Bristol University, BS8 2BN, Bristol, UK
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC, 3000 CA, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, 3000 CA, Rotterdam, The Netherlands
| | - Wiesje van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
| | - Sven J van der Lee
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC, 3000 CA, Rotterdam, The Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Diana van Heemst
- Department of Gerontology and Geriatrics, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands
| | - James W Vaupel
- Max Planck Institute for Demographic Research, 18057, Rostock, Germany
| | - David Weir
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Kenny Ye
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development and Raissun Institute for Advanced Studies, Peking University, 100871, Beijing, China
- Center for the Study of Aging and Human Development and Geriatrics Division, Medical School of Duke University, Durham, NC, 27710, USA
| | - Wanlin Zheng
- California Pacific Medical Center Research Institute, San Francisco, CA, 94158, USA
| | - Henne Holstege
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, 2600 GA, Delft, The Netherlands
| | - Douglas P Kiel
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, 02131, USA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, 02215, USA
- Broad Institute of MIT & Harvard, Cambridge, MA, 02142, USA
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - P Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands.
| | - Joanne M Murabito
- NHLBI's and Boston University's Framingham Heart Study, Framingham, MA, 01702, USA.
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, 02118, USA.
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45
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De Rango F, Crocco P, Iannone F, Saiardi A, Passarino G, Dato S, Rose G. Inositol Polyphosphate Multikinase ( IPMK), a Gene Coding for a Potential Moonlighting Protein, Contributes to Human Female Longevity. Genes (Basel) 2019; 10:genes10020125. [PMID: 30744060 PMCID: PMC6410091 DOI: 10.3390/genes10020125] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 02/04/2019] [Accepted: 02/04/2019] [Indexed: 01/03/2023] Open
Abstract
Biogerontological research highlighted a complex and dynamic connection between aging, health and longevity, partially determined by genetic factors. Multifunctional proteins with moonlighting features, by integrating different cellular activities in the space and time, may explain part of this complexity. Inositol Polyphosphate Multikinase (IPMK) is a potential moonlighting protein performing multiple unrelated functions. Initially identified as a key enzyme for inositol phosphates synthesis, small messengers regulating many aspects of cell physiology, IPMK is now implicated in a number of metabolic pathways affecting the aging process. IPMK regulates basic transcription, telomere homeostasis, nutrient-sensing, metabolism and oxidative stress. Here, we tested the hypothesis that the genetic variability of IPMK may affect human longevity. Single-SNP (single nuclear polymorphism), haplotype-based association tests as well as survival analysis pointed to the relevance of six out of fourteen genotyped SNPs for female longevity. In particular, haplotype analysis refined the association highlighting two SNPs, rs2790234 and rs6481383, as major contributing variants for longevity in women. Our work, the first to investigate the association between variants of IPMK and longevity, supports IPMK as a novel gender-specific genetic determinant of human longevity, playing a role in the complex network of genetic factors involved in human survival.
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Affiliation(s)
- Francesco De Rango
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende, Italy.
| | - Paolina Crocco
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende, Italy.
| | - Francesca Iannone
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende, Italy.
| | - Adolfo Saiardi
- MRC Laboratory for Molecular Cell Biology, University College London, London, UK.
| | - Giuseppe Passarino
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende, Italy.
| | - Serena Dato
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende, Italy.
| | - Giuseppina Rose
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende, Italy.
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46
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Coltell O, Asensio EM, Sorlí JV, Barragán R, Fernández-Carrión R, Portolés O, Ortega-Azorín C, Martínez-LaCruz R, González JI, Zanón-Moreno V, Gimenez-Alba I, Fitó M, Ros E, Ordovas JM, Corella D. Genome-Wide Association Study (GWAS) on Bilirubin Concentrations in Subjects with Metabolic Syndrome: Sex-Specific GWAS Analysis and Gene-Diet Interactions in a Mediterranean Population. Nutrients 2019; 11:nu11010090. [PMID: 30621171 PMCID: PMC6356696 DOI: 10.3390/nu11010090] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 12/27/2018] [Accepted: 12/27/2018] [Indexed: 01/30/2023] Open
Abstract
Although, for decades, increased serum bilirubin concentrations were considered a threatening sign of underlying liver disease and had been associated with neonatal jaundice, data from recent years show that bilirubin is a powerful antioxidant and suggest that slightly increased serum bilirubin concentrations are protective against oxidative stress-related diseases, such as cardiovascular diseases. Therefore, a better understanding of the gene-diet interactions in determining serum bilirubin concentrations is needed. None of the previous genome-wide association studies (GWAS) on bilirubin concentrations has been stratified by sex. Therefore, considering the increasing interest in incorporating the gender perspective into nutritional genomics, our main aim was to carry out a GWAS on total serum bilirubin concentrations in a Mediterranean population with metabolic syndrome, stratified by sex. Our secondary aim was to explore, as a pilot study, the presence of gene-diet interactions at the GWAS level. We included 430 participants (188 men and 242 women, aged 55–75 years, and with metabolic syndrome) in the PREDIMED Plus-Valencia study. Global and sex-specific GWAS were undertaken to analyze associations and gene-diet interaction on total serum bilirubin. Adherence (low and high) to the Mediterranean diet (MedDiet) was analyzed as the dietary modulator. In the GWAS, we detected more than 55 SNPs associated with serum bilirubin at p < 5 × 10−8 (GWAS level). The top-ranked were four SNPs (rs4148325 (p = 9.25 × 10−24), rs4148324 (p = 9.48 × 10−24), rs6742078 (p = 1.29 × 10−23), rs887829 (p = 1.39 × 10−23), and the rs4148324 (p = 9.48 × 10−24)) in the UGT1A1 (UDP glucuronosyltransferase family 1 member A1) gene, which replicated previous findings revealing the UGT1A1 as the major locus. In the sex-specific GWAS, the top-ranked SNPs at the GWAS level were similar in men and women (the lead SNP was the rs4148324-UGT1A1 in both men (p = 4.77 × 10−11) and women (p = 2.15 × 10−14), which shows homogeneous genetic results for the major locus. There was more sex-specific heterogeneity for other minor genes associated at the suggestive level of GWAS significance (p < 1 × 10−5). We did not detect any gene-MedDiet interaction at p < 1 × 10−5 for the major genetic locus, but we detected some gene-MedDiet interactions with other genes at p < 1 × 10−5, and even at the GWAS level for the IL17B gene (p = 3.14 × 10−8). These interaction results, however, should be interpreted with caution due to our small sample size. In conclusion, our study provides new data, with a gender perspective, on genes associated with total serum bilirubin concentrations in men and women, and suggests possible additional modulations by adherence to MedDiet.
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Affiliation(s)
- Oscar Coltell
- Department of Computer Languages and Systems, Universitat Jaume I, 12071 Castellón, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - Eva M Asensio
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - José V Sorlí
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Rocio Barragán
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Rebeca Fernández-Carrión
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Olga Portolés
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Carolina Ortega-Azorín
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Raul Martínez-LaCruz
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - José I González
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Vicente Zanón-Moreno
- Area of Health Sciences, Valencian International University, 46002 Valencia, Spain.
- Red Temática de Investigación Cooperativa OftaRed, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Ophthalmology Research Unit "Santiago Grisolia", Dr. Peset University Hospital, 46017 Valencia, Spain.
| | - Ignacio Gimenez-Alba
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Montserrat Fitó
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Instituto Hospital del Mar de Investigaciones Médicas, 08003 Barcelona, Spain.
| | - Emilio Ros
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Lipid Clinic, Endocrinology and Nutrition Service, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, University of Barcelona, 08036 Barcelona, Spain.
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111, USA.
- Department of Cardiovascular Epidemiology and Population Genetics, Centro Nacional de Investigaciones Cardiovasculares (CNIC), 28029 Madrid, Spain.
- IMDEA Alimentación, 28049 Madrid, Spain.
| | - Dolores Corella
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
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