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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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Torres GG, Dose J, Hasenbein TP, Nygaard M, Krause-Kyora B, Mengel-From J, Christensen K, Andersen-Ranberg K, Kolbe D, Lieb W, Laudes M, Görg S, Schreiber S, Franke A, Caliebe A, Kuhlenbäumer G, Nebel A. Long-Lived Individuals Show a Lower Burden of Variants Predisposing to Age-Related Diseases and a Higher Polygenic Longevity Score. Int J Mol Sci 2022; 23:10949. [PMID: 36142858 PMCID: PMC9504529 DOI: 10.3390/ijms231810949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/05/2022] [Accepted: 09/07/2022] [Indexed: 11/22/2022] Open
Abstract
Longevity is a complex phenotype influenced by both environmental and genetic factors. The genetic contribution is estimated at about 25%. Despite extensive research efforts, only a few longevity genes have been validated across populations. Long-lived individuals (LLI) reach extreme ages with a relative low prevalence of chronic disability and major age-related diseases (ARDs). We tested whether the protection from ARDs in LLI can partly be attributed to genetic factors by calculating polygenic risk scores (PRSs) for seven common late-life diseases (Alzheimer's disease (AD), atrial fibrillation (AF), coronary artery disease (CAD), colorectal cancer (CRC), ischemic stroke (ISS), Parkinson's disease (PD) and type 2 diabetes (T2D)). The examined sample comprised 1351 German LLI (≥94 years, including 643 centenarians) and 4680 German younger controls. For all ARD-PRSs tested, the LLI had significantly lower scores than the younger control individuals (areas under the curve (AUCs): ISS = 0.59, p = 2.84 × 10-35; AD = 0.59, p = 3.16 × 10-25; AF = 0.57, p = 1.07 × 10-16; CAD = 0.56, p = 1.88 × 10-12; CRC = 0.52, p = 5.85 × 10-3; PD = 0.52, p = 1.91 × 10-3; T2D = 0.51, p = 2.61 × 10-3). We combined the individual ARD-PRSs into a meta-PRS (AUC = 0.64, p = 6.45 × 10-15). We also generated two genome-wide polygenic scores for longevity, one with and one without the TOMM40/APOE/APOC1 gene region (AUC (incl. TOMM40/APOE/APOC1) = 0.56, p = 1.45 × 10-5, seven variants; AUC (excl. TOMM40/APOE/APOC1) = 0.55, p = 9.85 × 10-3, 10,361 variants). Furthermore, the inclusion of nine markers from the excluded region (not in LD with each other) plus the APOE haplotype into the model raised the AUC from 0.55 to 0.61. Thus, our results highlight the importance of TOMM40/APOE/APOC1 as a longevity hub.
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Affiliation(s)
- Guillermo G. Torres
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Janina Dose
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Tim P. Hasenbein
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
- Department of Neurology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Str. 3, 24105 Kiel, Germany
- Institute of Pharmacology and Toxicology, Technical University Munich, Biedersteiner Str. 29, 80802 Munich, Germany
| | - Marianne Nygaard
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, J.B. Winsloews Vej 4, 5000 Odense, Denmark
| | - Ben Krause-Kyora
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Jonas Mengel-From
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, J.B. Winsloews Vej 4, 5000 Odense, Denmark
| | - Kaare Christensen
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, J.B. Winsloews Vej 4, 5000 Odense, Denmark
- Department of Clinical Biochemistry, Odense University Hospital, Kløvervænget 47, 5000 Odense, Denmark
| | - Karen Andersen-Ranberg
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Geriatric Medicine, Odense University Hospital, Kløvervænget 23, 5000 Odense, Denmark
| | - Daniel Kolbe
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Wolfgang Lieb
- Institute of Epidemiology and Biobank Popgen, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Niemannsweg 11, 24105 Kiel, Germany
| | - Matthias Laudes
- Clinic for Internal Medicine I, Division of Endocrinology, Diabetes and Clinical Nutrition, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Straße 3, 24105 Kiel, Germany
| | - Siegfried Görg
- Institute of Transfusion Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Amke Caliebe
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Brunswiker Str. 10, 24105 Kiel, Germany
| | - Gregor Kuhlenbäumer
- Department of Neurology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Str. 3, 24105 Kiel, Germany
| | - Almut Nebel
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
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Duara R, Barker W. Heterogeneity in Alzheimer's Disease Diagnosis and Progression Rates: Implications for Therapeutic Trials. Neurotherapeutics 2022; 19:8-25. [PMID: 35084721 PMCID: PMC9130395 DOI: 10.1007/s13311-022-01185-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/05/2022] [Indexed: 01/03/2023] Open
Abstract
The clinical presentation and the pathological processes underlying Alzheimer's disease (AD) can be very heterogeneous in severity, location, and composition including the amount and distribution of AB deposition and spread of neurofibrillary tangles in different brain regions resulting in atypical clinical patterns and the existence of distinct AD variants. Heterogeneity in AD may be related to demographic factors (such as age, sex, educational and socioeconomic level) and genetic factors, which influence underlying pathology, the cognitive and behavioral phenotype, rate of progression, the occurrence of neuropsychiatric features, and the presence of comorbidities (e.g., vascular disease, neuroinflammation). Heterogeneity is also manifest in the individual resilience to the development of neuropathology (brain reserve) and the ability to compensate for its cognitive and functional impact (cognitive and functional reserve). The variability in specific cognitive profiles and types of functional impairment may be associated with different progression rates, and standard measures assessing progression may not be equivalent for individual cognitive and functional profiles. Other factors, which may govern the presence, rate, and type of progression of AD, include the individuals' general medical health, the presence of specific systemic conditions, and lifestyle factors, including physical exercise, cognitive and social stimulation, amount of leisure activities, environmental stressors, such as toxins and pollution, and the effects of medications used to treat medical and behavioral conditions. These factors that affect progression are important to consider while designing a clinical trial to ensure, as far as possible, well-balanced treatment and control groups.
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Affiliation(s)
- Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA
- Departments of Neurology, University of Florida College of Medicine, Gainesville, FL, USA
- Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA
| | - Warren Barker
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA.
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4
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Olivieri F, Prattichizzo F, Giuliani A, Matacchione G, Rippo MR, Sabbatinelli J, Bonafè M. miR-21 and miR-146a: The microRNAs of inflammaging and age-related diseases. Ageing Res Rev 2021; 70:101374. [PMID: 34082077 DOI: 10.1016/j.arr.2021.101374] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 05/14/2021] [Accepted: 05/20/2021] [Indexed: 02/06/2023]
Abstract
The first paper on "inflammaging" published in 2001 paved the way for a unifying theory on how and why aging turns out to be the main risk factor for the development of the most common age-related diseases (ARDs). The most exciting challenge on this topic was explaining how systemic inflammation steeps up with age and why it shows different rates among individuals of the same chronological age. The "epigenetic revolution" in the past twenty years conveyed that the assessment of the individual genetic make-up is not enough to depict the trajectories of age-related inflammation. Accordingly, others and we have been focusing on the role of non-coding RNA, i.e. microRNAs (miRNAs), in inflammaging. The results obtained in the latest 10 years underpinned the key role of a miRNA subset that we have called inflammamiRs, owing to their ability to master (NF-κB)-driven inflammatory pathways. In this review, we will focus on two inflammamiRs, i.e. miR-21-5p and miR-146a-5p, which target a variety of molecules belonging to the NF-κB/NLRP3 pathways. The interplay between miR-146a-5p and IL-6 in the context of aging and ARDs will also be highlighted. We will also provide the most relevant evidence suggesting that circulating inflammamiRs, along with IL-6, can measure the degree of inflammaging.
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5
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The Jackson Laboratory Nathan Shock Center: impact of genetic diversity on aging. GeroScience 2021; 43:2129-2137. [PMID: 34297313 DOI: 10.1007/s11357-021-00421-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 07/11/2021] [Indexed: 12/25/2022] Open
Abstract
Healthspan is a complex trait, influenced by many genes and environmental factors that accelerate or delay aging, reduce or increase disease risk, and extend or reduce lifespan. Thus, assessing the role of genetic variation in aging requires an experimental strategy capable of modeling the genetic and biological complexity of human populations. The goal of the The Jackson Laboratory Nathan Shock Center (JAX NSC) is to provide research resources and training for geroscience investigators that seek to understand the role of genetics and genetic diversity on the fundamental process of aging and diseases of human aging using the laboratory mouse as a model system. The JAX NSC has available novel, deeply characterized populations of aged mice, performs state-of-the-art phenotyping of age-relevant traits, provides systems genetics analysis of complex data sets, and provides all of these resources to the geroscience community. The aged animal resources, phenotyping capacity, and genetic expertise available through the JAX NSC benefit the geroscience community by fostering cutting-edge, novel lines of research that otherwise would not be possible. Over the past 15 years, the JAX NSC has transformed aging research across the geroscience community, providing aging mouse resources and tissues to researchers. All JAX NSC data and tools are publicly disseminated on the Mouse Phenome Database and the JAX NSC website, thus ensuring that the resources generated and expertise acquired through the Center are readily available to the aging research community. The JAX NSC will continue to enhance its ability to perform innovative research using a mammalian model to illuminate novel genotype-phenotype relationships and provide a rational basis for designing effective risk assessments and therapeutic interventions to boost longevity and disease-free healthspan.
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6
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Torres GG, Nygaard M, Caliebe A, Blanché H, Chantalat S, Galan P, Lieb W, Christiansen L, Deleuze JF, Christensen K, Strauch K, Müller-Nurasyid M, Peters A, Nöthen MM, Hoffmann P, Flachsbart F, Schreiber S, Ellinghaus D, Franke A, Dose J, Nebel A. Exome-Wide Association Study Identifies FN3KRP and PGP as New Candidate Longevity Genes. J Gerontol A Biol Sci Med Sci 2021; 76:786-795. [PMID: 33491046 PMCID: PMC8087267 DOI: 10.1093/gerona/glab023] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Indexed: 12/19/2022] Open
Abstract
Despite enormous research efforts, the genetic component of longevity has remained largely elusive. The investigation of common variants, mainly located in intronic or regulatory regions, has yielded only little new information on the heritability of the phenotype. Here, we performed a chip-based exome-wide association study investigating 62 488 common and rare coding variants in 1248 German long-lived individuals, including 599 centenarians and 6941 younger controls (age < 60 years). In a single-variant analysis, we observed an exome-wide significant association between rs1046896 in the gene fructosamine-3-kinase-related-protein (FN3KRP) and longevity. Noteworthy, we found the longevity allele C of rs1046896 to be associated with an increased FN3KRP expression in whole blood; a database look-up confirmed this effect for various other human tissues. A gene-based analysis, in which potential cumulative effects of common and rare variants were considered, yielded the gene phosphoglycolate phosphatase (PGP) as another potential longevity gene, though no single variant in PGP reached the discovery p-value (1 × 10E−04). Furthermore, we validated the previously reported longevity locus cyclin-dependent kinase inhibitor 2B antisense RNA 1 (CDKN2B-AS1). Replication of our results in a French longevity cohort was only successful for rs1063192 in CDKN2B-AS1. In conclusion, we identified 2 new potential candidate longevity genes, FN3KRP and PGP which may influence the phenotype through their role in metabolic processes, that is, the reverse glycation of proteins (FN3KRP) and the control of glycerol-3-phosphate levels (PGP).
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Affiliation(s)
- Guillermo G Torres
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Germany
| | - Marianne Nygaard
- The Danish Twin Registry and The Danish Aging Research Center, Department of Public Health, University of Southern Denmark, Odense C.,Department of Clinical Genetics, Odense University Hospital, Denmark
| | - Amke Caliebe
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein, Germany
| | - Hélène Blanché
- Fondation Jean Dausset-Centre d'Etude du Polymorphisme Humain (CEPH), Paris, France
| | - Sophie Chantalat
- Centre National de Recherche en Génomique Humaine CNRGH-CEA, Evry, France
| | - Pilar Galan
- Université Sorbonne Paris Cité-UREN, Unité de Recherche en Epidémiologie Nutritionelle, U557 Inserm, U1125 Inra, Bobigny, France
| | - Wolfgang Lieb
- Institute of Epidemiology and Biobank Popgen, Kiel University, University Hospital Schleswig-Holstein, Germany
| | - Lene Christiansen
- The Danish Twin Registry and The Danish Aging Research Center, Department of Public Health, University of Southern Denmark, Odense C.,Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Denmark
| | - Jean-François Deleuze
- Fondation Jean Dausset-Centre d'Etude du Polymorphisme Humain (CEPH), Paris, France.,Centre National de Recherche en Génomique Humaine CNRGH-CEA, Evry, France
| | - Kaare Christensen
- The Danish Twin Registry and The Danish Aging Research Center, Department of Public Health, University of Southern Denmark, Odense C.,Department of Clinical Genetics, Odense University Hospital, Denmark.,Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Denmark
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Chair of Genetic Epidemiology, IBE, Faculty of Medicine, Ludwig-Maximilians-University (LMU) Munich, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Chair of Genetic Epidemiology, IBE, Faculty of Medicine, Ludwig-Maximilians-University (LMU) Munich, Germany.,Department of Internal Medicine I (Cardiology), Hospital of the LMU Munich, Germany
| | - Annette Peters
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | | | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, Germany
| | - Friederike Flachsbart
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Germany
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Germany
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Germany
| | - Janina Dose
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Germany
| | - Almut Nebel
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Germany
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7
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Identification of cardiovascular health gene variants related to longevity in a Chinese population. Aging (Albany NY) 2020; 12:16775-16802. [PMID: 32897244 PMCID: PMC7521493 DOI: 10.18632/aging.103396] [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: 01/11/2020] [Accepted: 05/25/2020] [Indexed: 01/24/2023]
Abstract
Cardiovascular disease (CVD) is one of the most important causes of human death, but no attention has been paid to cardiovascular health genes related to healthy longevity. Therefore, we developed a cohort study to explore such genes in healthy, long-lived Chinese subjects. A total of 13275 healthy elderly people were enrolled, including 5107 healthy long-lived individuals and 8168 age-matched control individuals with low CVD risk. Using a combination of whole-exome sequencing (WES) and genome-wide association studies (GWAS), we identified 2 genetic variants (TFPI rs7586970 T, p=0.013, OR=1.100. ADAMTS7 rs3825807 A, p=0.017, OR=1.198) associated with healthy lipid metabolism and longevity. Furthermore, we showed that an interaction among TFPI rs7586970, ADAMTS7 rs3825807 and APOE ɛ3 maintained normal blood lipid levels in centenarians by stratified analysis of CVD risk factors. Finally, through biological function analysis, we revealed clues regarding the mechanism of factor related to cardiovascular health (FCH) such as lipids and longevity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the two variants above may be associated with longevity via FCH lipid metabolism pathways. From a meta-analysis of venous thrombosis patients, we unexpectedly found that rs7586970 T is associated with both longevity and protection against vascular disease.
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8
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Breitbach ME, Greenspan S, Resnick NM, Perera S, Gurkar AU, Absher D, Levine AS. Exonic Variants in Aging-Related Genes Are Predictive of Phenotypic Aging Status. Front Genet 2019; 10:1277. [PMID: 31921313 PMCID: PMC6931058 DOI: 10.3389/fgene.2019.01277] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Accepted: 11/19/2019] [Indexed: 01/31/2023] Open
Abstract
Background: Recent studies investigating longevity have revealed very few convincing genetic associations with increased lifespan. This is, in part, due to the complexity of biological aging, as well as the limited power of genome-wide association studies, which assay common single nucleotide polymorphisms (SNPs) and require several thousand subjects to achieve statistical significance. To overcome such barriers, we performed comprehensive DNA sequencing of a panel of 20 genes previously associated with phenotypic aging in a cohort of 200 individuals, half of whom were clinically defined by an "early aging" phenotype, and half of whom were clinically defined by a "late aging" phenotype based on age (65-75 years) and the ability to walk up a flight of stairs or walk for 15 min without resting. A validation cohort of 511 late agers was used to verify our results. Results: We found early agers were not enriched for more total variants in these 20 aging-related genes than late agers. Using machine learning methods, we identified the most predictive model of aging status, both in our discovery and validation cohorts, to be a random forest model incorporating damaging exon variants [Combined Annotation-Dependent Depletion (CADD) > 15]. The most heavily weighted variants in the model were within poly(ADP-ribose) polymerase 1 (PARP1) and excision repair cross complementation group 5 (ERCC5), both of which are involved in a canonical aging pathway, DNA damage repair. Conclusion: Overall, this study implemented a framework to apply machine learning to identify sequencing variants associated with complex phenotypes such as aging. While the small sample size making up our cohort inhibits our ability to make definitive conclusions about the ability of these genes to accurately predict aging, this study offers a unique method for exploring polygenic associations with complex phenotypes.
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Affiliation(s)
- Megan E Breitbach
- HudsonAlpha Institute for Biotechnology, Hunstville, AL, United States.,Department of Biotechnology Science and Engineering, University of Alabama in Huntsville, Hunstville, AL, United States
| | - Susan Greenspan
- Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | - Neil M Resnick
- Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.,Institute on Aging of UPMC, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | - Subashan Perera
- Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.,Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, United States
| | - Aditi U Gurkar
- Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.,Institute on Aging of UPMC, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Hunstville, AL, United States
| | - Arthur S Levine
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.,UPMC Hillman Cancer Center, Pittsburgh, PA, United States
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9
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Identification of novel genes associated with longevity in Drosophila melanogaster - a computational approach. Aging (Albany NY) 2019; 11:11244-11267. [PMID: 31794428 PMCID: PMC6932890 DOI: 10.18632/aging.102527] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Accepted: 11/18/2019] [Indexed: 12/13/2022]
Abstract
Despite a growing number of studies on longevity in Drosophila, genetic factors influencing lifespan are still poorly understood. In this paper we propose a conceptually new approach for the identification of novel longevity-associated genes and potential target genes for SNPs in non-coding regions by utilizing the knowledge of co-location of various loci, governed by the three-dimensional architecture of the Drosophila genome. Firstly, we created networks between genes/genomic regions harboring SNPs deemed to be significant in two longevity GWAS summary statistics datasets using intra- and inter-chromosomal interaction frequencies (Hi-C data) as a measure of co-location. These networks were further extended to include regions strongly interacting with previously selected regions. Using various network measures, literature search and additional bioinformatics resources, we investigated the plausibility of genes found to have genuine association with longevity. Several of the newly identified genes were common between the two GWAS datasets and these possessed human orthologs. We also found that the proportion of non-coding SNPs in borders between topologically associated domains is significantly higher than expected by chance. Assuming co-location, we investigated potential target genes for non-coding SNPs. This approach therefore offers a stepping stone to identification of novel genes and SNP targets linked to human longevity.
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10
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Giuliani C, Sazzini M, Pirazzini C, Bacalini MG, Marasco E, Ruscone GAG, Fang F, Sarno S, Gentilini D, Di Blasio AM, Crocco P, Passarino G, Mari D, Monti D, Nacmias B, Sorbi S, Salvarani C, Catanoso M, Pettener D, Luiselli D, Ukraintseva S, Yashin A, Franceschi C, Garagnani P. Impact of demography and population dynamics on the genetic architecture of human longevity. Aging (Albany NY) 2019; 10:1947-1963. [PMID: 30089705 PMCID: PMC6128422 DOI: 10.18632/aging.101515] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Accepted: 07/26/2018] [Indexed: 02/07/2023]
Abstract
The study of the genetics of longevity has been mainly addressed by GWASs that considered subjects from different populations to reach higher statistical power. The "price to pay" is that population-specific evolutionary histories and trade-offs were neglected in the investigation of gene-environment interactions. We propose a new “diachronic” approach that considers processes occurred at both evolutionary and lifespan timescales. We focused on a well-characterized population in terms of evolutionary history (i.e. Italians) and we generated genome-wide data for 333 centenarians from the peninsula and 773 geographically-matched healthy individuals. Obtained results showed that: (i) centenarian genomes are enriched for an ancestral component likely shaped by pre-Neolithic migrations; (ii) centenarians born in Northern Italy unexpectedly clustered with controls from Central/Southern Italy suggesting that Neolithic and Bronze Age gene flow did not favor longevity in this population; (iii) local past adaptive events in response to pathogens and targeting arachidonic acid metabolism became favorable for longevity; (iv) lifelong changes in the frequency of several alleles revealed pleiotropy and trade-off mechanisms crucial for longevity. Therefore, we propose that demographic history and ancient/recent population dynamics need to be properly considered to identify genes involved in longevity, which can differ in different temporal/spatial settings.
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Affiliation(s)
- 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.,Interdepartmental Center "L. Galvani," (CIG), University of Bologna, Bologna, Italy
| | - Marco Sazzini
- Department of Biological, Geological, and Environmental Sciences (BiGeA), Laboratory of Molecular Anthropology and Centre for Genome Biology, University of Bologna, Bologna, Italy
| | - Chiara Pirazzini
- IRCCS, Institute of Neurological Sciences of Bologna, Bologna, Italy
| | | | - Elena Marasco
- Interdepartmental Center "L. Galvani," (CIG), University of Bologna, Bologna, Italy.,Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy.,Applied Biomedical Research Center (CRBA), S. Orsola-Malpighi Polyclinic, Bologna, Italy
| | - Guido Alberto Gnecchi Ruscone
- Department of Biological, Geological, and Environmental Sciences (BiGeA), Laboratory of Molecular Anthropology and Centre for Genome Biology, University of Bologna, Bologna, Italy
| | - Fang Fang
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA
| | - Stefania Sarno
- Department of Biological, Geological, and Environmental Sciences (BiGeA), Laboratory of Molecular Anthropology and Centre for Genome Biology, University of Bologna, Bologna, Italy
| | - Davide Gentilini
- Istituto Auxologico Italiano IRCCS, Cusano Milanino, Milan, Italy
| | | | - Paolina Crocco
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende, Italy
| | - Giuseppe Passarino
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende, Italy
| | - Daniela Mari
- Geriatric Unit, Department of Medical Sciences and Community Health, Milan, Italy.,Fondazione Ca' Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy
| | - Daniela Monti
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Florence, Italy
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.,IRCCS Don Gnocchi, Florence, Italy
| | - Carlo Salvarani
- Azienda Ospedaliera-IRCCS, Reggio Emilia, Italy.,Department of Surgical, Medical, Dental and Morphological Sciences with Interest Transplant, Oncological and Regenerative Medicine, , Italy
| | | | - Davide Pettener
- Department of Biological, Geological, and Environmental Sciences (BiGeA), Laboratory of Molecular Anthropology and Centre for Genome Biology, University of Bologna, Bologna, Italy
| | - Donata Luiselli
- Department for the Cultural Heritage (DBC), University of Bologna, Ravenna, Italy
| | - Svetlana Ukraintseva
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA
| | - Anatoliy Yashin
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA
| | - Claudio Franceschi
- IRCCS, Institute of Neurological Sciences of Bologna, Bologna, Italy.,Co-senior authors
| | - Paolo Garagnani
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy.,Clinical Chemistry, Department of Laboratory Medicine, Karolinska Institutet at Huddinge University Hospital, S-141 86 Stockholm, Sweden.,CNR Institute of Molecular Genetics, Unit of Bologna, Bologna, Italy.,Rizzoli Orthopaedic Institute, Laboratory of Cell Biology, Bologna, Italy.,Co-senior authors
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11
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Giuliani C, Garagnani P, Franceschi C. Genetics of Human Longevity Within an Eco-Evolutionary Nature-Nurture Framework. Circ Res 2019; 123:745-772. [PMID: 30355083 DOI: 10.1161/circresaha.118.312562] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Human longevity is a complex trait, and to disentangle its basis has a great theoretical and practical consequences for biomedicine. The genetics of human longevity is still poorly understood despite several investigations that used different strategies and protocols. Here, we argue that such rather disappointing harvest is largely because of the extraordinary complexity of the longevity phenotype in humans. The capability to reach the extreme decades of human lifespan seems to be the result of an intriguing mixture of gene-environment interactions. Accordingly, the genetics of human longevity is here described as a highly context-dependent phenomenon, within a new integrated, ecological, and evolutionary perspective, and is presented as a dynamic process, both historically and individually. The available literature has been scrutinized within this perspective, paying particular attention to factors (sex, individual biography, family, population ancestry, social structure, economic status, and education, among others) that have been relatively neglected. The strength and limitations of the most powerful and used tools, such as genome-wide association study and whole-genome sequencing, have been discussed, focusing on prominently emerged genes and regions, such as apolipoprotein E, Forkhead box O3, interleukin 6, insulin-like growth factor-1, chromosome 9p21, 5q33.3, and somatic mutations among others. The major results of this approach suggest that (1) the genetics of longevity is highly population specific; (2) small-effect alleles, pleiotropy, and the complex allele timing likely play a major role; (3) genetic risk factors are age specific and need to be integrated in the light of the geroscience perspective; (4) a close relationship between genetics of longevity and genetics of age-related diseases (especially cardiovascular diseases) do exist. Finally, the urgent need of a global approach to the largely unexplored interactions between the 3 genetics of human body, that is, nuclear, mitochondrial, and microbiomes, is stressed. We surmise that the comprehensive approach here presented will help in increasing the above-mentioned harvest.
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Affiliation(s)
- Cristina Giuliani
- From the Department of Biological, Geological, and Environmental Sciences (BiGeA), Laboratory of Molecular Anthropology and Centre for Genome Biology (C.G.), University of Bologna, Italy.,School of Anthropology and Museum Ethnography, University of Oxford, United Kingdom (C.G.).,Interdepartmental Centre 'L. Galvani' (CIG), University of Bologna, Italy (C.G.)
| | - Paolo Garagnani
- Department of Experimental, Diagnostic, and Specialty Medicine (DIMES) (P.G.), University of Bologna, Italy.,Clinical Chemistry, Department of Laboratory Medicine, Karolinska Institutet at Huddinge University Hospital, Stockholm, Sweden (P.G.)
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12
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A Prospective Analysis of Genetic Variants Associated with Human Lifespan. G3-GENES GENOMES GENETICS 2019; 9:2863-2878. [PMID: 31484785 PMCID: PMC6723124 DOI: 10.1534/g3.119.400448] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
We present a massive investigation into the genetic basis of human lifespan. Beginning with a genome-wide association (GWA) study using a de-identified snapshot of the unique AncestryDNA database – more than 300,000 genotyped individuals linked to pedigrees of over 400,000,000 people – we mapped six genome-wide significant loci associated with parental lifespan. We compared these results to a GWA analysis of the traditional lifespan proxy trait, age, and found only one locus, APOE, to be associated with both age and lifespan. By combining the AncestryDNA results with those of an independent UK Biobank dataset, we conducted a meta-analysis of more than 650,000 individuals and identified fifteen parental lifespan-associated loci. Beyond just those significant loci, our genome-wide set of polymorphisms accounts for up to 8% of the variance in human lifespan; this value represents a large fraction of the heritability estimated from phenotypic correlations between relatives.
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13
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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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14
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Wolters FJ, Yang Q, Biggs ML, Jakobsdottir J, Li S, Evans DS, Bis JC, Harris TB, Vasan RS, Zilhao NR, Ghanbari M, Ikram MA, Launer L, Psaty BM, Tranah GJ, Kulminski AM, Gudnason V, Seshadri S. The impact of APOE genotype on survival: Results of 38,537 participants from six population-based cohorts (E2-CHARGE). PLoS One 2019; 14:e0219668. [PMID: 31356640 PMCID: PMC6663005 DOI: 10.1371/journal.pone.0219668] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 06/28/2019] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Apolipoprotein E is a glycoprotein best known as a mediator and regulator of lipid transport and uptake. The APOE-ε4 allele has long been associated with increased risks of Alzheimer's disease and mortality, but the effect of the less prevalent APOE-ε2 allele on diseases in the elderly and survival remains elusive. METHODS We aggregated data of 38,537 individuals of European ancestry (mean age 65.5 years; 55.6% women) from six population-based cohort studies (Rotterdam Study, AGES-Reykjavik Study, Cardiovascular Health Study, Health-ABC Study, and the family-based Framingham Heart Study and Long Life Family Study) to determine the association of APOE, and in particular APOE-ε2, with survival in the population. RESULTS During a mean follow-up of 11.7 years, 17,021 individuals died. Compared with homozygous APOE-ε3 carriers, APOE-ε2 carriers were at lower risk of death (hazard ratio,95% confidence interval: 0.94,0.90-0.99; P = 1.1*10-2), whereas APOE-ε4 carriers were at increased risk of death (HR 1.17,1.12-1.21; P = 2.8*10-16). APOE was associated with mortality risk in a dose-dependent manner, with risk estimates lowest for homozygous APOE-ε2 (HR 0.89,0.74-1.08), and highest for homozygous APOE-ε4 (HR 1.52,1.37-1.70). After censoring for dementia, effect estimates remained similar for APOE-ε2 (HR 0.95,0.90-1.01), but attenuated for APOE-ε4 (HR 1.07,1.01-1.12). Results were broadly similar across cohorts, and did not differ by age or sex. APOE genotype was associated with baseline lipid fractions (e.g. mean difference(95%CI) in LDL(mg/dL) for ε2 versus ε33: -17.1(-18.1-16.0), and ε4 versus ε33: +5.7(4.8;6.5)), but the association between APOE and mortality was unaltered after adjustment for baseline LDL or cardiovascular disease. Given the European ancestry of the study population, results may not apply to other ethnicities. CONCLUSION Compared with APOE-ε3, APOE-ε2 is associated with prolonged survival, whereas mortality risk is increased for APOE-ε4 carriers. Further collaborative efforts are needed to unravel the role of APOE and in particular APOE-ε2 in health and disease.
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Affiliation(s)
- Frank J. Wolters
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Mary L. Biggs
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | | | - Shuo Li
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, California, United States of America
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Tamara B. Harris
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, Maryland, United States of America
| | - Ramachandran S. Vasan
- Sections of Preventive Medicine and Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, United States of America
| | | | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Lenore Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, Maryland, United States of America
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
- Departments of Epidemiology and Health Services, University of Washington, Seattle, Washington, United States of America
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, United States of America
| | - Gregory J. Tranah
- California Pacific Medical Center Research Institute, San Francisco, California, United States of America
| | - Alexander M. Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina, United States of America
| | - Vilmundur Gudnason
- Faculty of Medicine, University of Iceland, Reykavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | - Sudha Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, United States of America
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15
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Morris BJ, Willcox BJ, Donlon TA. Genetic and epigenetic regulation of human aging and longevity. Biochim Biophys Acta Mol Basis Dis 2019; 1865:1718-1744. [PMID: 31109447 PMCID: PMC7295568 DOI: 10.1016/j.bbadis.2018.08.039] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 08/02/2018] [Accepted: 08/28/2018] [Indexed: 02/06/2023]
Abstract
Here we summarize the latest data on genetic and epigenetic contributions to human aging and longevity. Whereas environmental and lifestyle factors are important at younger ages, the contribution of genetics appears more important in reaching extreme old age. Genome-wide studies have implicated ~57 gene loci in lifespan. Epigenomic changes during aging profoundly affect cellular function and stress resistance. Dysregulation of transcriptional and chromatin networks is likely a crucial component of aging. Large-scale bioinformatic analyses have revealed involvement of numerous interaction networks. As the young well-differentiated cell replicates into eventual senescence there is drift in the highly regulated chromatin marks towards an entropic middle-ground between repressed and active, such that genes that were previously inactive "leak". There is a breakdown in chromatin connectivity such that topologically associated domains and their insulators weaken, and well-defined blocks of constitutive heterochromatin give way to generalized, senescence-associated heterochromatin, foci. Together, these phenomena contribute to aging.
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Affiliation(s)
- Brian J Morris
- Basic & Clinical Genomics Laboratory, School of Medical Sciences and Bosch Institute, University of Sydney, New South Wales 2006, Australia; Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, HI 96817, United States; Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Kuakini Medical Center Campus, Honolulu, HI 96813, United States.
| | - Bradley J Willcox
- Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, HI 96817, United States; Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Kuakini Medical Center Campus, Honolulu, HI 96813, United States.
| | - Timothy A Donlon
- Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, HI 96817, United States; Departments of Cell & Molecular Biology and Pathology, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI 96813, United States.
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16
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The Genetic Variability of APOE in Different Human Populations and Its Implications for Longevity. Genes (Basel) 2019; 10:genes10030222. [PMID: 30884759 PMCID: PMC6471373 DOI: 10.3390/genes10030222] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 03/01/2019] [Accepted: 03/12/2019] [Indexed: 12/11/2022] Open
Abstract
Human longevity is a complex phenotype resulting from the combinations of context-dependent gene-environment interactions that require analysis as a dynamic process in a cohesive ecological and evolutionary framework. Genome-wide association (GWAS) and whole-genome sequencing (WGS) studies on centenarians pointed toward the inclusion of the apolipoprotein E (APOE) polymorphisms ε2 and ε4, as implicated in the attainment of extreme longevity, which refers to their effect in age-related Alzheimer's disease (AD) and cardiovascular disease (CVD). In this case, the available literature on APOE and its involvement in longevity is described according to an anthropological and population genetics perspective. This aims to highlight the evolutionary history of this gene, how its participation in several biological pathways relates to human longevity, and which evolutionary dynamics may have shaped the distribution of APOE haplotypes across the globe. Its potential adaptive role will be described along with implications for the study of longevity in different human groups. This review also presents an updated overview of the worldwide distribution of APOE alleles based on modern day data from public databases and ancient DNA samples retrieved from literature in the attempt to understand the spatial and temporal frame in which present-day patterns of APOE variation evolved.
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17
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Yashin AI, Arbeev KG, Wu D, Arbeeva LS, Bagley O, Stallard E, Kulminski AM, Akushevich I, Fang F, Wojczynski MK, Christensen K, Newman AB, Boudreau RM, Province MA, Thielke S, Perls TT, An P, Elo I, Ukraintseva SV. Genetics of Human Longevity From Incomplete Data: New Findings From the Long Life Family Study. J Gerontol A Biol Sci Med Sci 2018; 73:1472-1481. [PMID: 30299504 PMCID: PMC6175028 DOI: 10.1093/gerona/gly057] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Indexed: 02/04/2023] Open
Abstract
The special design of the Long Life Family Study provides a unique opportunity to investigate the genetics of human longevity by analyzing data on exceptional lifespans in families. In this article, we performed two series of genome wide association studies of human longevity which differed with respect to whether missing lifespan data were predicted or not predicted. We showed that the use of predicted lifespan is most beneficial when the follow-up period is relatively short. In addition to detection of strong associations of SNPs in APOE, TOMM40, NECTIN2, and APOC1 genes with longevity, we also detected a strong new association with longevity of rs1927465, located between the CYP26A1 and MYOF genes on chromosome 10. The association was confirmed using data from the Health and Retirement Study. We discuss the biological relevance of the detected SNPs to human longevity.
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Affiliation(s)
- Anatoliy I Yashin
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina,Address correspondence to: Anatoliy I. Yashin, PhD, Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina. E-mail:
| | - Konstantin G Arbeev
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
| | - Deqing Wu
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
| | - Liubov S Arbeeva
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Olivia Bagley
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
| | - Eric Stallard
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
| | - Alexander M Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
| | - Igor Akushevich
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
| | - Fang Fang
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
| | - Mary K Wojczynski
- Department of Genetics, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Kaare Christensen
- Department of Epidemiology, University of Southern Denmark, Odense, Denmark
| | - Anne B Newman
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Robert M Boudreau
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Michael A Province
- Department of Genetics, Washington University in St Louis, St Louis, Missouri
| | | | - Thomas T Perls
- Medical Center, Boston University, Boston, Massachusetts
| | - Ping An
- Department of Genetics, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Irma Elo
- Department of Sociology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Svetlana V Ukraintseva
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
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18
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Hook M, Roy S, Williams EG, Bou Sleiman M, Mozhui K, Nelson JF, Lu L, Auwerx J, Williams RW. Genetic cartography of longevity in humans and mice: Current landscape and horizons. Biochim Biophys Acta Mol Basis Dis 2018; 1864:2718-2732. [PMID: 29410319 PMCID: PMC6066442 DOI: 10.1016/j.bbadis.2018.01.026] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 01/24/2018] [Accepted: 01/28/2018] [Indexed: 12/14/2022]
Abstract
Aging is a complex and highly variable process. Heritability of longevity among humans and other species is low, and this finding has given rise to the idea that it may be futile to search for DNA variants that modulate aging. We argue that the problem in mapping longevity genes is mainly one of low power and the genetic and environmental complexity of aging. In this review we highlight progress made in mapping genes and molecular networks associated with longevity, paying special attention to work in mice and humans. We summarize 40 years of linkage studies using murine cohorts and 15 years of studies in human populations that have exploited candidate gene and genome-wide association methods. A small but growing number of gene variants contribute to known longevity mechanisms, but a much larger set have unknown functions. We outline these and other challenges and suggest some possible solutions, including more intense collaboration between research communities that use model organisms and human cohorts. Once hundreds of gene variants have been linked to differences in longevity in mammals, it will become feasible to systematically explore gene-by-environmental interactions, dissect mechanisms with more assurance, and evaluate the roles of epistasis and epigenetics in aging. A deeper understanding of complex networks-genetic, cellular, physiological, and social-should position us well to improve healthspan.
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Affiliation(s)
- Michael Hook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Suheeta Roy
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Evan G Williams
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland
| | - Maroun Bou Sleiman
- Interfaculty Institute of Bioengineering, Laboratory of Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - James F Nelson
- Department of Cellular and Integrative Physiology and Barshop Institute for Longevity and Aging Studies, The University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Lu Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Johan Auwerx
- Interfaculty Institute of Bioengineering, Laboratory of Integrative and Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
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19
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Zeng Y, Nie C, Min J, Chen H, Liu X, Ye R, Chen Z, Bai C, Xie E, Yin Z, Lv Y, Lu J, Li J, Ni T, Bolund L, Land KC, Yashin A, O’Rand AM, Sun L, Yang Z, Tao W, Gurinovich A, Franceschi C, Xie J, Gu J, Hou Y, Liu X, Xu X, Robine JM, Deelen J, Sebastiani P, Slagboom E, Perls T, Hauser E, Gottschalk W, Tan Q, Christensen K, Shi X, Lutz M, Tian XL, Yang H, Vaupel J. Sex Differences in Genetic Associations With Longevity. JAMA Netw Open 2018; 1:e181670. [PMID: 30294719 PMCID: PMC6173523 DOI: 10.1001/jamanetworkopen.2018.1670] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Accepted: 05/15/2018] [Indexed: 01/09/2023] Open
Abstract
IMPORTANCE Sex differences in genetic associations with human longevity remain largely unknown; investigations on this topic are important for individualized health care. OBJECTIVE To explore sex differences in genetic associations with longevity. DESIGN SETTING AND PARTICIPANTS This population-based case-control study used sex-specific genome-wide association study and polygenic risk score (PRS) analyses to examine sex differences in genetic associations with longevity. Five hundred sixty-four male and 1614 female participants older than 100 years were compared with a control group of 773 male and 1526 female individuals aged 40 to 64 years. All were Chinese Longitudinal Healthy Longevity Study participants with Han ethnicity who were recruited in 1998 and 2008 to 2014. MAIN OUTCOMES AND MEASURES Sex-specific loci and pathways associated with longevity and PRS measures of joint effects of sex-specific loci. RESULTS Eleven male-specific and 11 female-specific longevity loci (P < 10-5) and 35 male-specific and 25 female-specific longevity loci (10-5 ≤ P < 10-4) were identified. Each of these loci's associations with longevity were replicated in north and south regions of China in one sex but were not significant in the other sex (P = .13-.97), and loci-sex interaction effects were significant (P < .05). The associations of loci rs60210535 of the LINC00871 gene with longevity were replicated in Chinese women (P = 9.0 × 10-5) and US women (P = 4.6 × 10-5) but not significant in Chinese and US men. The associations of the loci rs2622624 of the ABCG2 gene were replicated in Chinese women (P = 6.8 × 10-5) and European women (P = .003) but not significant in both Chinese and European men. Eleven male-specific pathways (inflammation and immunity genes) and 34 female-specific pathways (tryptophan metabolism and PGC-1α induced) were significantly associated with longevity (P < .005; false discovery rate < 0.05). The PRS analyses demonstrated that sex-specific associations with longevity of the 4 exclusive groups of 11 male-specific and 11 female-specific loci (P < 10-5) and 35 male-specific and 25 female-specific loci (10-5 ≤P < 10-4) were jointly replicated across north and south discovery and target samples. Analyses using the combined data set of north and south showed that these 4 groups of sex-specific loci were jointly and significantly associated with longevity in one sex (P = 2.9 × 10-70 to 1.3 × 10-39) but not jointly significant in the other sex (P = .11 to .70), while interaction effects between PRS and sex were significant (P = 4.8 × 10-50 to 1.2 × 10-16). CONCLUSION AND RELEVANCE The sex differences in genetic associations with longevity are remarkable, but have been overlooked by previously published genome-wide association studies on longevity. This study contributes to filling this research gap and provides a scientific basis for further investigating effects of sex-specific genetic variants and their interactions with environment on healthy aging, which may substantially contribute to more effective and targeted individualized health care for male and female elderly individuals.
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Affiliation(s)
- Yi Zeng
- Center for the Study of Aging and Human Development, Medical School of Duke University, Durham, North Carolina
- Center for Healthy Aging and Development Studies, National School of Development, Raissun Institute for Advanced Studies, Peking University, Beijing, China
| | - Chao Nie
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China
- BGI–Shenzhen, Shenzhen, China
| | - Junxia Min
- The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China
| | - Huashuai Chen
- Center for the Study of Aging and Human Development, Medical School of Duke University, Durham, North Carolina
- Business School of Xiangtan University, Xiangtan, China
| | | | - Rui Ye
- BGI–Shenzhen, Shenzhen, China
| | | | - Chen Bai
- Center for Healthy Aging and Development Studies, National School of Development, Raissun Institute for Advanced Studies, Peking University, Beijing, China
| | - Enjun Xie
- The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China
| | - Zhaoxue Yin
- Division of Non-Communicable Disease Control and Community Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuebin Lv
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jiehua Lu
- Department of Sociology, Peking University, Beijing, China
| | - Jianxin Li
- Department of Sociology, Peking University, Beijing, China
| | - Ting Ni
- School of Life Sciences, Fudan University, Shanghai, China
| | - Lars Bolund
- BGI–Shenzhen, Shenzhen, China
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Kenneth C. Land
- Duke Population Research Institute, Duke University, Durham, North Carolina
| | - Anatoliy Yashin
- Duke Population Research Institute, Duke University, Durham, North Carolina
| | - Angela M. O’Rand
- Duke Population Research Institute, Duke University, Durham, North Carolina
| | - Liang Sun
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Ze Yang
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Wei Tao
- School of Life Sciences, Peking University, Beijing, China
| | | | | | - Jichun Xie
- Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina
| | - Jun Gu
- School of Life Sciences, Peking University, Beijing, China
| | | | | | - Xun Xu
- BGI–Shenzhen, Shenzhen, China
| | - Jean-Marie Robine
- French National Institute on Health and Medical Research and Ecole Pratique des Hautes Etudes, University of Montpellier, Montpellier, France
| | - Joris Deelen
- Max Planck Institute for Biology of Ageing, Cologne, Germany
| | | | - Eline Slagboom
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Elizabeth Hauser
- Molecular Physiology Institute, Medical Center, Duke University, Durham, North Carolina
| | - William Gottschalk
- Department of Neurology, Medical Center, Duke University, Durham, North Carolina
| | - Qihua Tan
- University of Southern Denmark, Odense, Denmark
| | | | - Xiaoming Shi
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mike Lutz
- Department of Neurology, Medical Center, Duke University, Durham, North Carolina
| | - Xiao-Li Tian
- Human Aging Research Institute and School of Life Science, Nanchang University, Jiangxi, China
| | - Huanming Yang
- BGI–Shenzhen, Shenzhen, China
- James D. Watson Institute of Genome Sciences, Hangzhou, China
| | - James Vaupel
- Max Planck Institute for Demographic Research, Rostock, Germany
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20
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Dato S, Soerensen M, De Rango F, Rose G, Christensen K, Christiansen L, Passarino G. The genetic component of human longevity: New insights from the analysis of pathway-based SNP-SNP interactions. Aging Cell 2018; 17:e12755. [PMID: 29577582 PMCID: PMC5946073 DOI: 10.1111/acel.12755] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/13/2018] [Indexed: 01/24/2023] Open
Abstract
In human longevity studies, single nucleotide polymorphism (SNP) analysis identified a large number of genetic variants with small effects, yet not easily replicable in different populations. New insights may come from the combined analysis of different SNPs, especially when grouped by metabolic pathway. We applied this approach to study the joint effect on longevity of SNPs belonging to three candidate pathways, the insulin/insulin‐like growth factor signalling (IIS), DNA repair and pro/antioxidant. We analysed data from 1,058 tagging SNPs in 140 genes, collected in 1825 subjects (1,089 unrelated nonagenarians from the Danish 1905 Birth Cohort Study and 736 Danish controls aged 46–55 years) for evaluating synergic interactions by SNPsyn. Synergies were further tested by the multidimensional reduction (MDR) approach, both intra‐ and interpathways. The best combinations (FDR<0.0001) resulted those encompassing IGF1R‐rs12437963 and PTPN1‐rs6067484, TP53‐rs2078486 and ERCC2‐rs50871, TXNRD1‐rs17202060 and TP53‐rs2078486, the latter two supporting a central role of TP53 in mediating the concerted activation of the DNA repair and pro‐antioxidant pathways in human longevity. Results were consistently replicated with both approaches, as well as a significant effect on longevity was found for the GHSR gene, which also interacts with partners belonging to both IIS and DNA repair pathways (PAPPA,PTPN1,PARK7, MRE11A). The combination GHSR‐MREA11, positively associated with longevity by MDR, was further found influencing longitudinal survival in nonagenarian females (p = .026). Results here presented highlight the validity of SNP‐SNP interactions analyses for investigating the genetics of human longevity, confirming previously identified markers but also pointing to novel genes as central nodes of additional networks involved in human longevity.
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Affiliation(s)
- Serena Dato
- Department of Biology, Ecology and Earth Sciences; University of Calabria; Rende Italy
| | - Mette Soerensen
- The Danish Aging Research Center, Epidemiology, Biostatistics and Biodemography; Institute of Public Health; University of Southern Denmark; Odense C Denmark
- Department of Clinical Genetics; Odense University Hospital; Odense C Denmark
| | - Francesco De Rango
- 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
| | - Kaare Christensen
- The Danish Aging Research Center, Epidemiology, Biostatistics and Biodemography; Institute of Public Health; University of Southern Denmark; Odense C Denmark
- Department of Clinical Genetics; Odense University Hospital; Odense C Denmark
| | - Lene Christiansen
- The Danish Aging Research Center, Epidemiology, Biostatistics and Biodemography; Institute of Public Health; University of Southern Denmark; Odense C Denmark
| | - Giuseppe Passarino
- Department of Biology, Ecology and Earth Sciences; University of Calabria; Rende Italy
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21
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Yang F, Sun L, Zhu X, Han J, Zeng Y, Nie C, Yuan H, Li X, Shi X, Yang Y, Hu C, Lv Z, Huang Z, Zheng C, Liang S, Huang J, Wan G, Qi K, Qin B, Cao S, Zhao X, Zhang Y, Yang Z. Identification of new genetic variants of HLA-DQB1 associated with human longevity and lipid homeostasis-a cross-sectional study in a Chinese population. Aging (Albany NY) 2018; 9:2316-2333. [PMID: 29129831 PMCID: PMC5723689 DOI: 10.18632/aging.101323] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Accepted: 11/02/2017] [Indexed: 01/09/2023]
Abstract
Healthy longevity has been an unremitting pursuit of human, but its genetic and the environment causes are still unclear. As longevity population is a good healthy aging model for understanding how the body begin aging and the process of aging, and plasma lipids metabolism and balance is a very important to life maintain and physiologic functional turnover. It is important to explore how the effect of genetic variants associated long-life individuals on lipids metabolism and balance. Therefore, we developed a comparative study based population which contains 2816 longevity and 2819 control. Through whole-exome sequencing and sanger sequencing genotypes, we identified four new single nucleotide polymorphisms of HLA-DQB1(major histocompatibility complex, class II, DQ beta 1), rs41542812 rs1049107 rs1049100 rs3891176(Prange=0.048-2.811×10−8 for allele frequencies), associated with longevity in Chinese Longevity Cohort. Further, by analysis of the longevity-variants linked to blood lipids, we identified HLA-DQB1 rs1049107, T-carriers (PHDL=0.006, OR: 11.277; PTG=9.095×10−7, OR: 0.025; PLDL/HDL=0.047, OR: 1.901) and HLA-DQB1 rs1049100, T-carriers (PTG=1.799×10-6, OR: 0.028) associated with lipid homeostasis in long lived individuals. Our finding showed that longevity and lipid homeostasis were associated with HLA-DQB1 and suggested that immune gene variants could act on both new function of maintaining the homeostasis and anti-aging in longevity.
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Affiliation(s)
- Fan Yang
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China.,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Liang Sun
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Xiaoquan Zhu
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Jing Han
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China.,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Yi Zeng
- Center for the Study of Aging and Human Development and Geriatrics Division, Medical School of Duke University, Durham, NC 27708, USA.,Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China
| | - Chao Nie
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Huiping Yuan
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Xiaoling Li
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China.,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaohong Shi
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Yige Yang
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Caiyou Hu
- Jiangbing Hospital, Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Zeping Lv
- Jiangbing Hospital, Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Zezhi Huang
- Office of Longevity Cultural, People's Government of Yongfu County, Yongfu, Guangxi, China
| | - Chenguang Zheng
- Birth Defects Prevention and Control Research Institute, Guangxi Zhuang Autonomous Region Women and Children Health Care Hospital, Nanning, Guangxi, China
| | - Siying Liang
- Genetic Testing Center Qingdao Women and Children's Hospital, Qingdao University, Qingdao, China
| | - Jin Huang
- Department of Obstetrics and Gynecology, Aviation General Hospital of China Medical University, Beijing, China
| | - Gang Wan
- Capital Medical University Affiliated Beijing Ditan Hospital, Beijing, China
| | - Keyan Qi
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Bin Qin
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Suyan Cao
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Xin Zhao
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Yongqiang Zhang
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Ze Yang
- The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China.,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
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22
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Davy PMC, Allsopp RC, Donlon TA, Morris BJ, Willcox DC, Willcox BJ. FOXO3 and Exceptional Longevity: Insights From Hydra to Humans. Curr Top Dev Biol 2018; 127:193-212. [PMID: 29433738 DOI: 10.1016/bs.ctdb.2017.10.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Aging is a complex, multifactorial process with significant plasticity. While several biological pathways appear to influence aging, few genes have been identified that are both evolutionarily conserved and have a strong impact on aging and age-related phenotypes. The FoxO3 gene (FOXO3), and its homologs in model organisms, appears especially important, forming a key gene in the insulin/insulin-like growth factor-signaling pathway, and influencing life span across diverse species. We highlight some of the key findings that are associated with FoxO3 protein, its gene and homologs in relation to lifespan in different species, and the insights these findings might provide about the molecular, cellular, and physiological processes that modulate aging and longevity in humans.
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Affiliation(s)
- Philip M C Davy
- Institute for Biogenesis Research, University of Hawaii, Honolulu, HI, United States
| | - Richard C Allsopp
- Institute for Biogenesis Research, University of Hawaii, Honolulu, HI, United States
| | - Timothy A Donlon
- Honolulu Heart Program/Honolulu-Asia Aging Study, Kuakini Medical Center, Honolulu, HI, United States; Ohana Genetics, Honolulu, HI, United States
| | - Brian J Morris
- Honolulu Heart Program/Honolulu-Asia Aging Study, Kuakini Medical Center, Honolulu, HI, United States; John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States; School of Medical Sciences and Bosch Institute, University of Sydney, Sydney, NSW, Australia
| | - Donald Craig Willcox
- Honolulu Heart Program/Honolulu-Asia Aging Study, Kuakini Medical Center, Honolulu, HI, United States; John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States; Okinawa International University, Ginowan, Okinawa, Japan
| | - Bradley J Willcox
- Honolulu Heart Program/Honolulu-Asia Aging Study, Kuakini Medical Center, Honolulu, HI, United States; John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States.
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23
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Dougherty M, Lazar J, Klein JC, Diaz K, Gobillot T, Grunblatt E, Hasle N, Lawrence D, Maurano M, Nelson M, Olson G, Srivatsan S, Shendure J, Keene CD, Bird T, Horwitz MS, Marshall DA. Genome sequencing in a case of Niemann-Pick type C. Cold Spring Harb Mol Case Stud 2017; 2:a001222. [PMID: 27900365 PMCID: PMC5111003 DOI: 10.1101/mcs.a001222] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Adult-onset Niemann–Pick disease type C (NPC) is an infrequent presentation of a rare neurovisceral lysosomal lipid storage disorder caused by autosomal recessive mutations in NPC1 (∼95%) or NPC2 (∼5%). Our patient was diagnosed at age 33 when he presented with a 10-yr history of difficulties in judgment, concentration, speech, and coordination. A history of transient neonatal jaundice and splenomegaly with bone marrow biopsy suggesting a lipid storage disorder pointed to NPC; biochemical (“variant” level cholesterol esterification) and ultrastructural studies in adulthood confirmed the diagnosis. Genetic testing revealed two different missense mutations in the NPC1 gene—V950M and N1156S. Symptoms progressed over >20 yr to severe ataxia and spasticity, dementia, and dysphagia with aspiration leading to death. Brain autopsy revealed mild atrophy of the cerebrum and cerebellum. Microscopic examination showed diffuse gray matter deposition of balloon neurons, mild white matter loss, extensive cerebellar Purkinje cell loss with numerous “empty baskets,” and neurofibrillary tangles predominantly in the hippocampal formation and transentorhinal cortex. We performed whole-genome sequencing to examine whether the patient harbored variants outside of the NPC1 locus that could have contributed to his late-onset phenotype. We focused analysis on genetic modifiers in pathways related to lipid metabolism, longevity, and neurodegenerative disease. We identified no rare coding variants in any of the pathways examined nor was the patient enriched for genome-wide association study (GWAS) single-nucleotide polymorphisms (SNPs) associated with longevity or altered lipid metabolism. In light of these findings, this case provides support for the V950M variant being sufficient for adult-onset NPC disease.
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Affiliation(s)
- Max Dougherty
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA;; Department of Genome Sciences, University of Washington, Seattle, Washington 98105, USA
| | - John Lazar
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA;; Department of Genome Sciences, University of Washington, Seattle, Washington 98105, USA
| | - Jason C Klein
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA;; Department of Genome Sciences, University of Washington, Seattle, Washington 98105, USA
| | - Karina Diaz
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA
| | - Theodore Gobillot
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA
| | - Eli Grunblatt
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA
| | - Nicholas Hasle
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA
| | - Daniel Lawrence
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA
| | - Megan Maurano
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA
| | - Maria Nelson
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA
| | - Gregory Olson
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA
| | - Sanjay Srivatsan
- University of Washington School of Medicine, Seattle, Washington 98195, USA;; Medical Scientist Training Program (MSTP), University of Washington, Seattle, Washington 98195, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, USA;; Howard Hughes Medical Institute, Seattle, Washington 98195, USA
| | - C Dirk Keene
- Department of Pathology, University of Washington, Seattle, Washington 98195, USA
| | - Thomas Bird
- Department of Neurology, University of Washington, Seattle, Washington 98105, USA;; Department of Medicine, University of Washington, Seattle, Washington 98195, USA
| | - Marshall S Horwitz
- Department of Pathology, University of Washington, Seattle, Washington 98195, USA
| | - Desiree A Marshall
- Department of Pathology, University of Washington, Seattle, Washington 98195, USA
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24
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Joshi PK, Pirastu N, Kentistou KA, Fischer K, Hofer E, Schraut KE, Clark DW, Nutile T, Barnes CLK, Timmers PRHJ, Shen X, Gandin I, McDaid AF, Hansen TF, Gordon SD, Giulianini F, Boutin TS, Abdellaoui A, Zhao W, Medina-Gomez C, Bartz TM, Trompet S, Lange LA, Raffield L, van der Spek A, Galesloot TE, Proitsi P, Yanek LR, Bielak LF, Payton A, Murgia F, Concas MP, Biino G, Tajuddin SM, Seppälä I, Amin N, Boerwinkle E, Børglum AD, Campbell A, Demerath EW, Demuth I, Faul JD, Ford I, Gialluisi A, Gögele M, Graff M, Hingorani A, Hottenga JJ, Hougaard DM, Hurme MA, Ikram MA, Jylhä M, Kuh D, Ligthart L, Lill CM, Lindenberger U, Lumley T, Mägi R, Marques-Vidal P, Medland SE, Milani L, Nagy R, Ollier WER, Peyser PA, Pramstaller PP, Ridker PM, Rivadeneira F, Ruggiero D, Saba Y, Schmidt R, Schmidt H, Slagboom PE, Smith BH, Smith JA, Sotoodehnia N, Steinhagen-Thiessen E, van Rooij FJA, Verbeek AL, Vermeulen SH, Vollenweider P, Wang Y, Werge T, Whitfield JB, Zonderman AB, Lehtimäki T, Evans MK, Pirastu M, Fuchsberger C, Bertram L, Pendleton N, Kardia SLR, Ciullo M, Becker DM, Wong A, Psaty BM, van Duijn CM, Wilson JG, Jukema JW, Kiemeney L, Uitterlinden AG, Franceschini N, North KE, Weir DR, Metspalu A, Boomsma DI, Hayward C, Chasman D, Martin NG, Sattar N, Campbell H, Esko T, Kutalik Z, Wilson JF. Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity. Nat Commun 2017; 8:910. [PMID: 29030599 PMCID: PMC5715013 DOI: 10.1038/s41467-017-00934-5] [Citation(s) in RCA: 86] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Accepted: 08/08/2017] [Indexed: 01/03/2023] Open
Abstract
Genomic analysis of longevity offers the potential to illuminate the biology of human aging. Here, using genome-wide association meta-analysis of 606,059 parents’ survival, we discover two regions associated with longevity (HLA-DQA1/DRB1 and LPA). We also validate previous suggestions that APOE, CHRNA3/5, CDKN2A/B, SH2B3 and FOXO3A influence longevity. Next we show that giving up smoking, educational attainment, openness to new experience and high-density lipoprotein (HDL) cholesterol levels are most positively genetically correlated with lifespan while susceptibility to coronary artery disease (CAD), cigarettes smoked per day, lung cancer, insulin resistance and body fat are most negatively correlated. We suggest that the effect of education on lifespan is principally mediated through smoking while the effect of obesity appears to act via CAD. Using instrumental variables, we suggest that an increase of one body mass index unit reduces lifespan by 7 months while 1 year of education adds 11 months to expected lifespan. Variability in human longevity is genetically influenced. Using genetic data of parental lifespan, the authors identify associations at HLA-DQA/DRB1 and LPA and find that genetic variants that increase educational attainment have a positive effect on lifespan whereas increasing BMI negatively affects lifespan.
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Affiliation(s)
- Peter K Joshi
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK.
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Katherine A Kentistou
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK.,Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, Scotland
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, University of Tartu, Tartu, 51010, Estonia
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, 8036, Austria.,Institute of Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, 8036, Austria
| | - Katharina E Schraut
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK.,Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, Scotland
| | - David W Clark
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Teresa Nutile
- Institute of Genetics and Biophysics "A. Buzzati-Traverso" - CNR, Naples, 80131, Italy
| | - Catriona L K Barnes
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Paul R H J Timmers
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Xia Shen
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, SE-171 77, Stockholm, Sweden
| | - Ilaria Gandin
- Department of Medical Sciences, University of Trieste, Trieste, 34100, Italy.,Institute for Maternal and Child Health, IRCCS "Burlo Garofolo", Trieste, 34137, Italy
| | - Aaron F McDaid
- Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, 1010, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - Thomas Folkmann Hansen
- Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Mental Health Services Copenhagen, Roskilde, DK-4000, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, DK-8000, Denmark
| | - Scott D Gordon
- QIMR Berghofer Institute of Medical Research, Brisbane, QLD, 4006, Australia
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
| | - Thibaud S Boutin
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Abdel Abdellaoui
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, Amsterdam Public Health Institute (APH), Amsterdam, 1081BT, Netherlands
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands.,Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Biostatistics and Medicine, University of Washington, Seattle, WA, 98101, USA
| | - Stella Trompet
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, 2300RC, The Netherlands.,Department of Cardiology, Leiden University Medical Center, Leiden, 2300RC, The Netherlands
| | - Leslie A Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Laura Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Ashley van der Spek
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - Tessel E Galesloot
- Department for Health Evidence, Radboud Institute for Health Sciences, Radboud university medical center, Nijmegen, 6500 HB, The Netherlands
| | - Petroula Proitsi
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, London, WC1B 5JU, UK
| | - Lisa R Yanek
- Department of Medicine, GeneSTAR Research Program, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Antony Payton
- Centre for Epidemiology, Division of Population Health, Health Services Research & Primary Care, The University of Manchester, Manchester, Greater, Manchester, M13 9PL, UK
| | - Federico Murgia
- Center for Biomedicine, European Academy of Bozen/Bolzano (EURAC), (Affiliated Institute of the University of Lübeck, Lübeck, Germany), Bolzano, 39100, Italy
| | - Maria Pina Concas
- Institute of Genetic and Biomedical Research - Support Unity, National Research Council of Italy, Sassari, 07100, Italy
| | - Ginevra Biino
- Institute of Molecular Genetics, National Research Council of Italy, Pavia, 27100, Italy
| | - Salman M Tajuddin
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore City, MD, 21224, USA
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, 33014, Finland
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - Eric Boerwinkle
- Health Science Center at Houston, UTHealth School of Public Health, University of Texas, Houston, TX, 77030, USA
| | - Anders D Børglum
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, DK-8000, Denmark.,Department of Biomedicine-Human Genetics, Aarhus University, DK-8000, Aarhus C, Denmark.,Centre for Integrative Sequencing, iSEQ, Aarhus University, DK-8000, Aarhus C, Denmark
| | - Archie Campbell
- Centre for Genomic & Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Ellen W Demerath
- Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 55454, USA
| | - Ilja Demuth
- Charité Research Group on Geriatrics, Charité, Universitätsmedizin Berlin, Berlin, 13347, Germany.,Lipid Clinic at the Interdisciplinary Metabolism Center, Charité, Universitätsmedizin Berlin, Berlin, 13353, Germany.,Institute for Medical and Human Genetics, Charité, Universitätsmedizin Berlin, Berlin, 13353, Germany
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48014, USA
| | - Ian Ford
- Robertson Center for biostatistics, University of Glasgow, Glasgow, G12 8QQ, UK
| | | | - Martin Gögele
- Center for Biomedicine, European Academy of Bozen/Bolzano (EURAC), (Affiliated Institute of the University of Lübeck, Lübeck, Germany), Bolzano, 39100, Italy
| | - MariaElisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Aroon Hingorani
- Institute of Cardiovascular Science, University College London, London, WC1E 6BT, UK
| | - Jouke-Jan Hottenga
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, Amsterdam Public Health Institute (APH), Amsterdam, 1081BT, Netherlands
| | - David M Hougaard
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, DK-8000, Denmark.,Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, 2300, Denmark
| | - Mikko A Hurme
- Department of Microbiology and Immunology, Fimlab Laboratories and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, 33014, Finland
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - Marja Jylhä
- Gerontology Research Center, Tampere, Finland, Faculty of Social Sciences, University of Tampere, Tampere, 33104, Finland
| | - Diana Kuh
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, London, WC1B 5JU, UK
| | - Lannie Ligthart
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, Amsterdam Public Health Institute (APH), Amsterdam, 1081BT, Netherlands
| | - Christina M Lill
- Genetic and Molecular Epidemiology Group, Institute of Neurogenetics, University of Lübeck, 23562, Lübeck, Germany
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, 14195, Germany.,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, 14195, Germany
| | - Thomas Lumley
- Department of Statistics, University of Auckland, Auckland, 1010, New Zealand
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, University of Tartu, Tartu, 51010, Estonia
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, 1011, Switzerland
| | - Sarah E Medland
- QIMR Berghofer Institute of Medical Research, Brisbane, QLD, 4006, Australia
| | - Lili Milani
- Estonian Genome Center, University of Tartu, University of Tartu, Tartu, 51010, Estonia
| | - Reka Nagy
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - William E R Ollier
- Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, Manchester Academic Health Science Centre, University of Manchester, Manchester, Greater Manchester, M13 9PL, UK
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Peter P Pramstaller
- Center for Biomedicine, European Academy of Bozen/Bolzano (EURAC), (Affiliated Institute of the University of Lübeck, Lübeck, Germany), Bolzano, 39100, Italy
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA.,TH Chan School of Public Health, Harvard Medical School, Boston, MA, 02115, USA
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands.,Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics "A. Buzzati-Traverso" - CNR, Naples, 80131, Italy
| | - Yasaman Saba
- Austrian Stroke Prevention Study, Institute of Molecular Biology and Biochemistry, Centre for Molecular Medicine, Medical University of Graz, Graz, 8010, Austria
| | - Reinhold Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, 8036, Austria
| | - Helena Schmidt
- Austrian Stroke Prevention Study, Institute of Molecular Biology and Biochemistry, Centre for Molecular Medicine, Medical University of Graz, Graz, 8010, Austria
| | - P Eline Slagboom
- Section of Molecular Epidemiology, Department of medical statistics, Leiden University Medical Center, Leiden, 2300RC, The Netherlands
| | - Blair H Smith
- Division of Population Health Sciences, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA.,Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48014, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, 98101, USA
| | | | - Frank J A van Rooij
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - André L Verbeek
- Department for Health Evidence, Radboud Institute for Health Sciences, Radboud university medical center, Nijmegen, 6500 HB, The Netherlands
| | - Sita H Vermeulen
- Department for Health Evidence, Radboud Institute for Health Sciences, Radboud university medical center, Nijmegen, 6500 HB, The Netherlands
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, 1011, Switzerland
| | - Yunpeng Wang
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, DK-8000, Denmark.,NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, 0450, Norway
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Mental Health Services Copenhagen, Roskilde, DK-4000, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, DK-8000, Denmark
| | - John B Whitfield
- QIMR Berghofer Institute of Medical Research, Brisbane, QLD, 4006, Australia
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore City, MD, 21224, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, 33014, Finland
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore City, MD, 21224, USA
| | - Mario Pirastu
- Institute of Genetic and Biomedical Research - Support Unity, National Research Council of Italy, Sassari, 07100, Italy
| | - Christian Fuchsberger
- Center for Biomedicine, European Academy of Bozen/Bolzano (EURAC), (Affiliated Institute of the University of Lübeck, Lübeck, Germany), Bolzano, 39100, Italy
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, 23562, Germany.,Neuroepidemiology and Ageing Research Group, School of Public Health, Imperial College, London, W6 8RP, UK
| | - Neil Pendleton
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Manchester Academic Health Science Centre, University of Manchester, Manchester, Greater Manchester, M13 9PL, UK
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Marina Ciullo
- Institute of Genetics and Biophysics "A. Buzzati-Traverso" - CNR, Naples, 80131, Italy.,IRCCS Neuromed, Pozzilli (IS), 86077, Italy
| | - Diane M Becker
- Department of Medicine, GeneSTAR Research Program, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Andrew Wong
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, London, WC1B 5JU, UK
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Epidemiology, Medicine and Health Services, University of Washington, Seattle, WA, 98101, USA.,Kaiser Permanente Washington Health Research Institute, Seattle, WA, 98101, USA
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, 39216, USA
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, 2300RC, The Netherlands
| | - Lambertus Kiemeney
- Department for Health Evidence, Radboud Institute for Health Sciences, Radboud university medical center, Nijmegen, 6500 HB, The Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands.,Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48014, USA
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, University of Tartu, Tartu, 51010, Estonia
| | - Dorret I Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, Amsterdam Public Health Institute (APH), Amsterdam, 1081BT, Netherlands
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Daniel Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA.,TH Chan School of Public Health, Harvard Medical School, Boston, MA, 02115, USA
| | - Nicholas G Martin
- QIMR Berghofer Institute of Medical Research, Brisbane, QLD, 4006, Australia
| | - Naveed Sattar
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, G12 8TD, UK
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Tōnu Esko
- Estonian Genome Center, University of Tartu, University of Tartu, Tartu, 51010, Estonia.,Program in Medical and Population Genetics, Broad Institute, Broad Institute, Cambridge, MA, 02142, USA
| | - Zoltán Kutalik
- Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, 1010, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - James F Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK.,MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
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25
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The system capacity view of aging and longevity. QUANTITATIVE BIOLOGY 2017. [DOI: 10.1007/s40484-017-0115-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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26
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Tanisawa K, Arai Y, Hirose N, Shimokata H, Yamada Y, Kawai H, Kojima M, Obuchi S, Hirano H, Yoshida H, Suzuki H, Fujiwara Y, Ihara K, Sugaya M, Arai T, Mori S, Sawabe M, Sato N, Muramatsu M, Higuchi M, Liu YW, Kong QP, Tanaka M. Exome-wide Association Study Identifies CLEC3B Missense Variant p.S106G as Being Associated With Extreme Longevity in East Asian Populations. J Gerontol A Biol Sci Med Sci 2017; 72:309-318. [PMID: 27154906 PMCID: PMC5861862 DOI: 10.1093/gerona/glw074] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Accepted: 04/06/2016] [Indexed: 02/05/2023] Open
Abstract
Life span is a complex trait regulated by multiple genetic and environmental factors; however, the genetic determinants of extreme longevity have been largely unknown. To identify the functional coding variants associated with extreme longevity, we performed an exome-wide association study (EWAS) on a Japanese population by using an Illumina HumanExome Beadchip and a focused replication study on a Chinese population. The EWAS on two independent Japanese cohorts consisting of 530 nonagenarians/centenarians demonstrated that the G allele of CLEC3B missense variant p.S106G was associated with extreme longevity at the exome-wide level of significance (p = 2.33×10–7, odds ratio [OR] = 1.50). The CLEC3B gene encodes tetranectin, a protein implicated in the mineralization process in osteogenesis as well as in the prognosis and metastasis of cancer. The replication study consisting of 448 Chinese nonagenarians/centenarians showed that the G allele of CLEC3B p.S106G was also associated with extreme longevity (p = .027, OR = 1.51), and the p value of this variant reached 1.87×10–8 in the meta-analysis of Japanese and Chinese populations. In conclusion, the present study identified the CLEC3B p.S106G as a novel longevity-associated variant, raising the novel hypothesis that tetranectin, encoded by CLEC3B, plays a role in human longevity and aging.
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Affiliation(s)
- Kumpei Tanisawa
- Department of Genomics for Longevity and Health, Tokyo Metropolitan Institute of Gerontology, Japan.,Faculty of Sport Sciences, Waseda University, Tokorozawa, Japan.,Japan Society for the Promotion of Science, Tokyo, Japan
| | - Yasumichi Arai
- Center for Supercentenarian Research, Keio University School of Medicine, Tokyo, Japan
| | - Nobuyoshi Hirose
- Center for Supercentenarian Research, Keio University School of Medicine, Tokyo, Japan
| | - Hiroshi Shimokata
- Section of Longitudinal Study of Aging, National Institute for Longevity Sciences (NILS-LSA), National Center for Geriatrics and Gerontology, Obu, Japan.,Graduate School of Nutritional Sciences, Nagoya University of Arts and Sciences, Nisshin, Japan
| | - Yoshiji Yamada
- Department of Human Functional Genomics, Life Science Research Center, Mie University, Tsu, Japan
| | - Hisashi Kawai
- Human Care Research Team, Tokyo Metropolitan Institute of Gerontology, Japan
| | - Motonaga Kojima
- Human Care Research Team, Tokyo Metropolitan Institute of Gerontology, Japan
| | - Shuichi Obuchi
- Human Care Research Team, Tokyo Metropolitan Institute of Gerontology, Japan
| | - Hirohiko Hirano
- Research Team for Promoting Independence of the Elderly, Tokyo Metropolitan Institute of Gerontology, Japan
| | - Hideyo Yoshida
- Research Team for Promoting Independence of the Elderly, Tokyo Metropolitan Institute of Gerontology, Japan
| | - Hiroyuki Suzuki
- Research Team for Social Participation and Community Health, Tokyo Metropolitan Institute of Gerontology, Japan
| | - Yoshinori Fujiwara
- Research Team for Social Participation and Community Health, Tokyo Metropolitan Institute of Gerontology, Japan
| | - Kazushige Ihara
- Department of Public Health, Toho University School of Medicine, Tokyo, Japan
| | - Maki Sugaya
- Department of Genomics for Longevity and Health, Tokyo Metropolitan Institute of Gerontology, Japan
| | - Tomio Arai
- Department of Pathology, Tokyo Metropolitan Geriatric Hospital, Japan
| | - Seijiro Mori
- Center for Promotion of Clinical Investigation, Tokyo Metropolitan Geriatric Hospital, Japan
| | - Motoji Sawabe
- Section of Molecular Pathology, Graduate School of Health Care Sciences, Tokyo Medical and Dental University, Japan
| | - Noriko Sato
- Department of Molecular Epidemiology, Medical Research Institute, Tokyo Medical and Dental University, Japan
| | - Masaaki Muramatsu
- Department of Molecular Epidemiology, Medical Research Institute, Tokyo Medical and Dental University, Japan
| | - Mitsuru Higuchi
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Japan.,Institute of Advanced Active Aging Research, Waseda University, Tokorozawa, Japan
| | - Yao-Wen Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, China
| | - Qing-Peng Kong
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, China
| | - Masashi Tanaka
- Department of Clinical Laboratory, Tokyo Metropolitan Geriatric Hospital, Japan
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27
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McDaid AF, Joshi PK, Porcu E, Komljenovic A, Li H, Sorrentino V, Litovchenko M, Bevers RPJ, Rüeger S, Reymond A, Bochud M, Deplancke B, Williams RW, Robinson-Rechavi M, Paccaud F, Rousson V, Auwerx J, Wilson JF, Kutalik Z. Bayesian association scan reveals loci associated with human lifespan and linked biomarkers. Nat Commun 2017; 8:15842. [PMID: 28748955 PMCID: PMC5537485 DOI: 10.1038/ncomms15842] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Accepted: 05/08/2017] [Indexed: 02/07/2023] Open
Abstract
The enormous variation in human lifespan is in part due to a myriad of sequence variants, only a few of which have been revealed to date. Since many life-shortening events are related to diseases, we developed a Mendelian randomization-based method combining 58 disease-related GWA studies to derive longevity priors for all HapMap SNPs. A Bayesian association scan, informed by these priors, for parental age of death in the UK Biobank study (n=116,279) revealed 16 independent SNPs with significant Bayes factor at a 5% false discovery rate (FDR). Eleven of them replicate (5% FDR) in five independent longevity studies combined; all but three are depleted of the life-shortening alleles in older Biobank participants. Further analysis revealed that brain expression levels of nearby genes (RBM6, SULT1A1 and CHRNA5) might be causally implicated in longevity. Gene expression and caloric restriction experiments in model organisms confirm the conserved role for RBM6 and SULT1A1 in modulating lifespan.
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Affiliation(s)
- Aaron F McDaid
- Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne 1010, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland
| | - Eleonora Porcu
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.,Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland
| | - Andrea Komljenovic
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.,Department of Ecology and Evolution, University of Lausanne, Lausanne 1015, Switzerland
| | - Hao Li
- Laboratory of Integrative and Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Vincenzo Sorrentino
- Laboratory of Integrative and Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Maria Litovchenko
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.,Laboratory of Systems Biology and Genetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne and Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Roel P J Bevers
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.,Laboratory of Systems Biology and Genetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne and Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Sina Rüeger
- Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne 1010, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland
| | - Murielle Bochud
- Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne 1010, Switzerland
| | - Bart Deplancke
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.,Laboratory of Systems Biology and Genetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne and Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA
| | - Marc Robinson-Rechavi
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.,Department of Ecology and Evolution, University of Lausanne, Lausanne 1015, Switzerland
| | - Fred Paccaud
- Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne 1010, Switzerland
| | - Valentin Rousson
- Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne 1010, Switzerland
| | - Johan Auwerx
- Laboratory of Integrative and Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - James F Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland.,MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, Scotland
| | - Zoltán Kutalik
- Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne 1010, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
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28
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Sebastiani P, Bae H, Gurinovich A, Soerensen M, Puca A, Perls TT. Limitations and risks of meta-analyses of longevity studies. Mech Ageing Dev 2017; 165:139-146. [PMID: 28143747 PMCID: PMC5533653 DOI: 10.1016/j.mad.2017.01.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Revised: 01/21/2017] [Accepted: 01/23/2017] [Indexed: 11/22/2022]
Abstract
Searching for genetic determinants of human longevity has been challenged by the rarity of data sets with large numbers of individuals who have reached extreme old age, inconsistent definitions of the phenotype, and the difficulty of defining appropriate controls. Meta-analysis - a statistical method to summarize results from different studies - has become a common tool in genetic epidemiology to accrue large sample sizes for powerful genetic association studies. In conducting a meta-analysis of studies of human longevity however, particular attention must be made to the definition of cases and controls (including their health status) and on the effect of possible confounders such as sex and ethnicity upon the genetic effect to be estimated. We will show examples of how a meta-analysis can inflate the false negative rates of genetic association studies or it can bias estimates of the association between a genetic variant and extreme longevity.
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Affiliation(s)
- Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, United States.
| | - Harold Bae
- College of Public Health and Human Sciences, Oregon State University, 151 Milam Hall, Corvallis, OR, United States.
| | - Anastasia Gurinovich
- Bioinformatics Program, Boston University, 44 Cummington Mall, Boston, MA 02215, United States.
| | - Mette Soerensen
- The Danish Aging Research Center, Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, J.B. Winsloews Vej 9 B, St., 5000 Odense C, Denmark.
| | - Annibale Puca
- IRCCS MultiMedica, 20138 Milan (Mi), Italy; University of Salerno, Department of Medicine and Surgery, 84081 Baronissi, SA, Italy.
| | - Thomas T Perls
- Geriatrics Section, Department of Medicine, Boston University School of Medicine & Boston Medical Center, 88 E Newton St., Boston, MA 02118, United States.
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29
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Dato S, Rose G, Crocco P, Monti D, Garagnani P, Franceschi C, Passarino G. The genetics of human longevity: an intricacy of genes, environment, culture and microbiome. Mech Ageing Dev 2017; 165:147-155. [DOI: 10.1016/j.mad.2017.03.011] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Revised: 03/04/2017] [Accepted: 03/30/2017] [Indexed: 12/13/2022]
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30
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Abstract
: The increased prevalence of age-related comorbidities and mortality is worrisome in ageing HIV-infected patients. Here, we aim to analyse the different ageing mechanisms with regard to HIV infection. Ageing results from the time-dependent accumulation of random cellular damage. Epigenetic modifications and mitochondrial DNA haplogroups modulate ageing. In antiretroviral treatment-controlled patients, epigenetic clock appears to be advanced, and some haplogroups are associated with HIV infection severity. Telomere shortening is enhanced in HIV-infected patients because of HIV and some nucleoside analogue reverse transcriptase inhibitors. Mitochondria-related oxidative stress and mitochondrial DNA mutations are increased during ageing and also by some nucleoside analogue reverse transcriptase inhibitors. Overall, increased inflammation or 'inflammageing' is a major driver of ageing and could result from cell senescence with secreted proinflammatory mediators, altered gut microbiota, and coinfections. In HIV-infected patients, the level of inflammation and innate immunity activation is enhanced and related to most comorbidities and to mortality. This status could result, in addition to age, from the virus itself or viral protein released from reservoirs, from HIV-enhanced gut permeability and dysbiosis, from antiretroviral treatment, from frequent cytomegalovirus and hepatitis C virus coinfections, and also from personal and environmental factors, as central fat accumulation or smoking. Adaptive immune activation and immunosenescence are associated with comorbidities and mortality in the general population but are less predictive in HIV-infected patients. Biomarkers to evaluate ageing in HIV-infected patients are required. Numerous systemic or cellular inflammatory, immune activation, oxidative stress, or senescence markers can be tested in serum or peripheral blood mononuclear cells. The novel European Study to Establish Biomarkers of Human Ageing MARK-AGE algorithm, evaluating the biological age, is currently assessed in HIV-infected patients and reveals an advanced biological age. Some enhanced inflammatory or innate immune activation markers are interesting but still not validated for the patient's follow-up. To be able to assess patients' biological age is an important objective to improve their healthspan.
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31
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Pardo LM, Li WQ, Hwang SJ, Verkouteren JAC, Hofman A, Uitterlinden AG, Kraft P, Turman C, Han J, Cho E, Murabito JM, Levy D, Qureshi AA, Nijsten T. Genome-Wide Association Studies of Multiple Keratinocyte Cancers. PLoS One 2017; 12:e0169873. [PMID: 28081215 PMCID: PMC5231365 DOI: 10.1371/journal.pone.0169873] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Accepted: 12/22/2016] [Indexed: 11/18/2022] Open
Abstract
There is strong evidence for a role of environmental risk factors involved in susceptibility to develop multiple keratinocyte cancers (mKCs), but whether genes are also involved in mKCs susceptibility has not been thoroughly investigated. We investigated whether single nucleotide polymorphisms (SNPs) are associated with susceptibility for mKCs. A genome-wide association study (GWAS) of 1,666 cases with mKCs and 1,950 cases with single KC (sKCs; controls) from Harvard cohorts (the Nurses' Health Study [NHS], NHS II, and the Health Professionals Follow-Up Study) and the Framingham Heart Study was carried-out using over 8 million SNPs (stage-1). We sought to replicate the most significant statistical associations (p-value≤ 5.5x10-6) in an independent cohort of 574 mKCs and 872 sKCs from the Rotterdam Study. In the discovery stage, 40 SNPs with suggestive associations (p-value ≤5.5x10-6) were identified, with eight independent SNPs tagging all 40 SNPs. The most significant SNP was located at chromosome 9 (rs7468390; p-value = 3.92x10-7). In stage-2, none of these SNPs replicated and only two of them were associated with mKCs in the same direction in the combined meta-analysis. We tested the associations for 19 previously reported basal cell carcinoma-related SNPs (candidate gene association analysis), and found that rs1805007 (MC1R locus) was significantly associated with risk of mKCs (p-value = 2.80x10-4). Although the suggestive SNPs with susceptibility for mKCs were not replicated, we found that previously identified BCC variants may also be associated with mKC, which the most significant association (rs1805007) located at the MC1R gene.
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Affiliation(s)
- Luba M. Pardo
- Department of Dermatology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Wen-Qing Li
- Department of Dermatology, Warren Alpert Medical School, Brown University, Providence Rhode Island, United State of America
- Department of Epidemiology, School of Public Health, Brown University, Rhode Island, United State of America
| | - Shih-Jen Hwang
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts, United State of America
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institute of Health, Bethesda Maryland MD United State of America
| | | | - Albert Hofman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United State of America
| | - André G. Uitterlinden
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, MA, United State of America
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United State of America
| | - Constance Turman
- Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, MA, United State of America
| | - Jiali Han
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United State of America
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, United State of America
- Melvin and Bren Simon Cancer Center, Indiana University, Indianapolis, IN, United State of America
| | - Eunyoung Cho
- Department of Dermatology, Warren Alpert Medical School, Brown University, Providence Rhode Island, United State of America
- Department of Epidemiology, School of Public Health, Brown University, Rhode Island, United State of America
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United State of America
| | - Joanne M. Murabito
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts, United State of America
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, United State of America
| | - Daniel Levy
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts, United State of America
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institute of Health, Bethesda Maryland MD United State of America
| | - Abrar A. Qureshi
- Department of Dermatology, Warren Alpert Medical School, Brown University, Providence Rhode Island, United State of America
- Department of Epidemiology, School of Public Health, Brown University, Rhode Island, United State of America
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United State of America
- * E-mail: (TN); (AAQ)
| | - Tamar Nijsten
- Department of Dermatology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
- * E-mail: (TN); (AAQ)
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32
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Ben-Avraham D, Karasik D, Verghese J, Lunetta KL, Smith JA, Eicher JD, Vered R, Deelen J, Arnold AM, Buchman AS, Tanaka T, Faul JD, Nethander M, Fornage M, Adams HH, Matteini AM, Callisaya ML, Smith AV, Yu L, De Jager PL, Evans DA, Gudnason V, Hofman A, Pattie A, Corley J, Launer LJ, Knopman DS, Parimi N, Turner ST, Bandinelli S, Beekman M, Gutman D, Sharvit L, Mooijaart SP, Liewald DC, Houwing-Duistermaat JJ, Ohlsson C, Moed M, Verlinden VJ, Mellström D, van der Geest JN, Karlsson M, Hernandez D, McWhirter R, Liu Y, Thomson R, Tranah GJ, Uitterlinden AG, Weir DR, Zhao W, Starr JM, Johnson AD, Ikram MA, Bennett DA, Cummings SR, Deary IJ, Harris TB, Kardia SLR, Mosley TH, Srikanth VK, Windham BG, Newman AB, Walston JD, Davies G, Evans DS, Slagboom EP, Ferrucci L, Kiel DP, Murabito JM, Atzmon G. The complex genetics of gait speed: genome-wide meta-analysis approach. Aging (Albany NY) 2017; 9:209-246. [PMID: 28077804 PMCID: PMC5310665 DOI: 10.18632/aging.101151] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2016] [Accepted: 12/26/2016] [Indexed: 01/08/2023]
Abstract
Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging.
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Affiliation(s)
- Dan Ben-Avraham
- Department of Medicine and Genetics Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - David Karasik
- Institute for Aging Research, Hebrew SeniorLife, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02131, USA
- Faculty of Medicine in the Galilee, Bar-Ilan University, Safed, Israel
| | - Joe Verghese
- Integrated Divisions of Cognitive & Motor Aging (Neurology) and Geriatrics (Medicine), Montefiore-Einstein Center for the Aging Brain, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Kathryn L. Lunetta
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA 01702, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - John D. Eicher
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA 01702, USA
- Population Sciences Branch, National Heart Lung and Blood Institute, Framingham, MA 01702, USA
| | - Rotem Vered
- Psychology Department, University of Haifa, Haifa, Israel
| | - Joris Deelen
- Molecular Epidemiology, Leiden University Medical Center, Leiden, Netherlands
- Max Planck Institute for Biology of Ageing, Köln, Germany
| | - Alice M. Arnold
- Department of Biostatistics, University of Washington, Seattle, WA 98115, USA
| | - Aron S. Buchman
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60614, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore MD 21224, USA
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Maria Nethander
- Bioinformatics Core Facility, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Myriam Fornage
- The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Hieab H. Adams
- Department of Epidemiology, Erasmus MC, Rotterdam, Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands
| | - Amy M. Matteini
- Division of Geriatric Medicine, Johns Hopkins Medical Institutes, Baltimore, MD 21224, USA
| | - Michele L. Callisaya
- Medicine, Peninsula Health, Peninsula Clinical School, Central Clinical School, Frankston, Melbourne, Victoria, Australia
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Albert V. Smith
- Icelandic Heart Association, Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60614, USA
| | - Philip L. De Jager
- Broad Institute of Harvard and MIT, Cambridge, Harvard Medical School, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Denis A. Evans
- Rush Institute for Healthy Aging and Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Alison Pattie
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Janie Corley
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Lenore J. Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - Neeta Parimi
- California Pacific Medical Center Research Institute, San Francisco, CA 94107, USA
| | - Stephen T. Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Marian Beekman
- Molecular Epidemiology, Leiden University Medical Center, Leiden, Netherlands
| | - Danielle Gutman
- Department of Human Biology, Faculty of Natural Science, University of Haifa, Haifa, Israel
| | - Lital Sharvit
- Department of Human Biology, Faculty of Natural Science, University of Haifa, Haifa, Israel
| | - Simon P. Mooijaart
- Gerontology and Geriatrics, Leiden University Medical Center, Leiden, Netherland
| | - David C. Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Jeanine J. Houwing-Duistermaat
- Genetical Statistics, Leiden University Medical Center, Leiden, Netherland. Department of Statistics, University of Leeds, Leeds, UK
| | - Claes Ohlsson
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska, Academy, University of Gothenburg, Gothenburg, Sweden
| | - Matthijs Moed
- Molecular Epidemiology, Leiden University Medical Center, Leiden, Netherlands
| | | | - Dan Mellström
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska, Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Magnus Karlsson
- Clinical and Molecular Osteoporosis Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Dena Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD 20892, USA
| | - Rebekah McWhirter
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University, Winston-Salem, NC 27109, USA
| | - Russell Thomson
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
- School of Computing, Engineering and Mathematics, University of Western Sydney, Sydney, Australia
| | - Gregory J. Tranah
- California Pacific Medical Center Research Institute, San Francisco, CA 94107, USA
| | - Andre G. Uitterlinden
- Department of Internal Medicine, Erasmus MC, and Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Rotterdam, The Netherlands
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Andrew D. Johnson
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA 01702, USA
- Population Sciences Branch, National Heart Lung and Blood Institute, Framingham, MA 01702, USA
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC, Rotterdam, Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands
| | - David A. Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60614, USA
| | - Steven R. Cummings
- California Pacific Medical Center Research Institute, San Francisco, CA 94107, USA
| | - Ian J. Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Tamara B. Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Thomas H. Mosley
- University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Velandai K. Srikanth
- Medicine, Peninsula Health, Peninsula Clinical School, Central Clinical School, Frankston, Melbourne, Victoria, Australia
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | | | - Ann B. Newman
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Jeremy D. Walston
- Division of Geriatric Medicine, Johns Hopkins Medical Institutes, Baltimore, MD 21224, USA
| | - Gail Davies
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, CA 94107, USA
| | - Eline P. Slagboom
- Molecular Epidemiology, Leiden University Medical Center, Leiden, Netherlands
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, Baltimore MD 21224, USA
| | - Douglas P. Kiel
- Institute for Aging Research, Hebrew SeniorLife, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02131, USA
- Broad Institute of Harvard and MIT, Boston, MA 02131, USA
| | - Joanne M. Murabito
- The National Heart Lung and Blood Institute'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
| | - Gil Atzmon
- Department of Medicine and Genetics Albert Einstein College of Medicine, Bronx, NY 10461, USA
- Department of Human Biology, Faculty of Natural Science, University of Haifa, Haifa, Israel
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Zeng Y, Feng Q, Gu D, Vaupel JW. Demographics, phenotypic health characteristics and genetic analysis of centenarians in China. Mech Ageing Dev 2016; 165:86-97. [PMID: 28040447 DOI: 10.1016/j.mad.2016.12.010] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2016] [Revised: 12/16/2016] [Accepted: 12/22/2016] [Indexed: 12/11/2022]
Abstract
After a brief introduction to the background, significance and unique features of the centenarian population in China, we describe the Chinese Longitudinal Healthy Longevity Study (CLHLS), which is the world's largest study of centenarians, nonagenarians, octogenarians, and compatible young-old aged 65-79. Based on the CLHLS data and other relevant studies, we summarize demographic and socioeconomic characteristics as well as self-reported and objectively-tested health indicators of centenarians in China, with an emphasis on gender differences and rural/urban disparities. We then compare five-year-age-specific trajectories of physical and cognitive functions, self-reported health, and life satisfactions from ages 65-69 to 100+, concluding that good psychological resilience and optimism are keys to the exceptional longevity enjoyed by centenarians. We discuss recent findings of novel loci and pathways that are significantly associated with longevity based on the genome-wide association study (GWAS) of the CLHLS centenarian sample, which is 2.7 times as large as prior GWAS of longevity. We also highlight colleagues' and our own studies on longevity candidate genes and gene-environment interaction analyses. Finally, we discuss limitations inherent in our studies of centenarians in China and further research perspectives.
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Affiliation(s)
- Yi Zeng
- Center for the Study of Aging and Human Development, Medical School of Duke University, United States; Center for Healthy Aging and Development Studies, National School of Development, Raissun Institute for Advanced Studies, Peking University, China.
| | - Qiushi Feng
- Department of Sociology & Centre for Family and Population Research, National University of Singapore, Singapore
| | - Danan Gu
- United Nations Population Division, United States
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Smita S, Lange F, Wolkenhauer O, Köhling R. Deciphering hallmark processes of aging from interaction networks. Biochim Biophys Acta Gen Subj 2016; 1860:2706-15. [PMID: 27456767 DOI: 10.1016/j.bbagen.2016.07.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 07/18/2016] [Accepted: 07/20/2016] [Indexed: 12/18/2022]
Abstract
BACKGROUND Aging is broadly considered to be a dynamic process that accumulates unfavourable structural and functional changes in a time dependent fashion, leading to a progressive loss of physiological integrity of an organism, which eventually leads to age-related diseases and finally to death. SCOPE OF REVIEW The majority of aging-related studies are based on reductionist approaches, focusing on single genes/proteins or on individual pathways without considering possible interactions between them. Over the last few decades, several such genes/proteins were independently analysed and linked to a role that is affecting the longevity of an organism. However, an isolated analysis on genes and proteins largely fails to explain the mechanistic insight of a complex phenotype due to the involvement and integration of multiple factors. MAJOR CONCLUSIONS Technological advance makes it possible to generate high-throughput temporal and spatial data that provide an opportunity to use computer-based methods. These techniques allow us to go beyond reductionist approaches to analyse large-scale networks that provide deeper understanding of the processes that drive aging. GENERAL SIGNIFICANCE In this review, we focus on systems biology approaches, based on network inference methods to understand the dynamics of hallmark processes leading to aging phenotypes. We also describe computational methods for the interpretation and identification of important molecular hubs involved in the mechanistic linkage between aging related processes. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.
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Affiliation(s)
- Suchi Smita
- Department of Systems Biology & Bioinformatics, University of Rostock, Rostock, Germany; Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany.
| | - Falko Lange
- Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany.
| | - Olaf Wolkenhauer
- Department of Systems Biology & Bioinformatics, University of Rostock, Rostock, Germany; Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, South Africa.
| | - Rüdiger Köhling
- Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany.
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Yashin AI, Arbeev KG, Wu D, Arbeeva L, Kulminski A, Kulminskaya I, Akushevich I, Ukraintseva SV. How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data. NORTH AMERICAN ACTUARIAL JOURNAL : NAAJ 2016; 20:201-232. [PMID: 27773987 PMCID: PMC5070546 DOI: 10.1080/10920277.2016.1178588] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
BACKGROUND AND OBJECTIVE To clarify mechanisms of genetic regulation of human aging and longevity traits, a number of genome-wide association studies (GWAS) of these traits have been performed. However, the results of these analyses did not meet expectations of the researchers. Most detected genetic associations have not reached a genome-wide level of statistical significance, and suffered from the lack of replication in the studies of independent populations. The reasons for slow progress in this research area include low efficiency of statistical methods used in data analyses, genetic heterogeneity of aging and longevity related traits, possibility of pleiotropic (e.g., age dependent) effects of genetic variants on such traits, underestimation of the effects of (i) mortality selection in genetically heterogeneous cohorts, (ii) external factors and differences in genetic backgrounds of individuals in the populations under study, the weakness of conceptual biological framework that does not fully account for above mentioned factors. One more limitation of conducted studies is that they did not fully realize the potential of longitudinal data that allow for evaluating how genetic influences on life span are mediated by physiological variables and other biomarkers during the life course. The objective of this paper is to address these issues. DATA AND METHODS We performed GWAS of human life span using different subsets of data from the original Framingham Heart Study cohort corresponding to different quality control (QC) procedures and used one subset of selected genetic variants for further analyses. We used simulation study to show that approach to combining data improves the quality of GWAS. We used FHS longitudinal data to compare average age trajectories of physiological variables in carriers and non-carriers of selected genetic variants. We used stochastic process model of human mortality and aging to investigate genetic influence on hidden biomarkers of aging and on dynamic interaction between aging and longevity. We investigated properties of genes related to selected variants and their roles in signaling and metabolic pathways. RESULTS We showed that the use of different QC procedures results in different sets of genetic variants associated with life span. We selected 24 genetic variants negatively associated with life span. We showed that the joint analyses of genetic data at the time of bio-specimen collection and follow up data substantially improved significance of associations of selected 24 SNPs with life span. We also showed that aging related changes in physiological variables and in hidden biomarkers of aging differ for the groups of carriers and non-carriers of selected variants. CONCLUSIONS . The results of these analyses demonstrated benefits of using biodemographic models and methods in genetic association studies of these traits. Our findings showed that the absence of a large number of genetic variants with deleterious effects may make substantial contribution to exceptional longevity. These effects are dynamically mediated by a number of physiological variables and hidden biomarkers of aging. The results of these research demonstrated benefits of using integrative statistical models of mortality risks in genetic studies of human aging and longevity.
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Affiliation(s)
- Anatoliy I. Yashin
- Professor, Center for Population Health and Aging, Duke University, 2024 W. Main Street, Room A102E, Durham, NC 27705, USA. Tel.: (+1) 919-668-2713; Fax: (+1) 919-684-3861
| | - Konstantin G. Arbeev
- Sr. Research Scientist, Center for Population Health and Aging, Duke University, 2024 W. Main Street, Room A102F, Durham, NC 27705, USA. Tel.: (+1) 919-668-2707; Fax: (+1) 919-684-3861
| | - Deqing Wu
- Sr. Research Scientist, Center for Population Health and Aging, Duke University, 2024 W. Main Street, Room A104, Durham, NC 27705, USA. Tel.: (+1) 919-684-6126; Fax: (+1) 919-684-3861
| | - Liubov Arbeeva
- Statistician, Center for Population Health and Aging, Duke University, 2024 W. Main Street, Room A102G, Durham, NC 27705, USA. Tel.: (+1) 919-613-0715; Fax: (+1) 919-684-3861
| | - Alexander Kulminski
- Sr. Research Scientist, Center for Population Health and Aging, Duke University, 2024 W. Main Street, Room A106, Durham, NC 27705, USA. Tel.: (+1) 919-684-4962; Fax: (+1) 919-684-3861
| | - Irina Kulminskaya
- Research Scientist, Center for Population Health and Aging, Duke University, 2024 W. Main Street, Room A102D, Durham, NC 27705, USA. Tel.: (+1) 919-681-8232; Fax: (+1) 919-684-3861
| | - Igor Akushevich
- Sr. Research Scientist, Center for Population Health and Aging, Duke University, 2024 W. Main Street, Room A107, Durham, NC 27705, USA. Tel.: (+1) 919-668-2715; Fax: (+1) 919-684-3861
| | - Svetlana V. Ukraintseva
- Sr. Research Scientist, Center for Population Health and Aging, Duke University, 2024 W. Main Street, Room A105, Durham, NC 27705, USA. Tel.: (+1) 919-668-2712; Fax: (+1) 919-684-3861
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Mcilhatton MA, Boivin GP, Groden J. Manipulation of DNA Repair Proficiency in Mouse Models of Colorectal Cancer. BIOMED RESEARCH INTERNATIONAL 2016; 2016:1414383. [PMID: 27413734 PMCID: PMC4931062 DOI: 10.1155/2016/1414383] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2016] [Accepted: 05/09/2016] [Indexed: 12/20/2022]
Abstract
Technical and biological innovations have enabled the development of more sophisticated and focused murine models that increasingly recapitulate the complex pathologies of human diseases, in particular cancer. Mouse models provide excellent in vivo systems for deciphering the intricacies of cancer biology within the context of precise experimental settings. They present biologically relevant, adaptable platforms that are amenable to continual improvement and refinement. We discuss how recent advances in our understanding of tumorigenesis and the underlying deficiencies of DNA repair mechanisms that drive it have been informed by using genetically engineered mice to create defined, well-characterized models of human colorectal cancer. In particular, we focus on how mechanisms of DNA repair can be manipulated precisely to create in vivo models whereby the underlying processes of tumorigenesis are accelerated or attenuated, dependent on the composite alleles carried by the mouse model. Such models have evolved to the stage where they now reflect the initiation and progression of sporadic cancers. The review is focused on mouse models of colorectal cancer and how insights from these models have been instrumental in shaping our understanding of the processes and potential therapies for this disease.
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Affiliation(s)
- Michael A. Mcilhatton
- Department of Cancer Biology and Genetics, The Ohio State University, 460 West 12th Avenue, Columbus, OH 43210, USA
| | - Gregory P. Boivin
- Department of Pathology, Boonshoft School of Medicine, Wright State University, Health Sciences Building 053, 3640 Colonel Glenn Highway, Dayton, OH 45435, USA
| | - Joanna Groden
- Department of Cancer Biology and Genetics, The Ohio State University, 460 West 12th Avenue, Columbus, OH 43210, USA
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Lin R, Yan D, Zhang Y, Liao X, Gong G, Hu J, Fu Y, Cai W. Common variants in SIRT1 and human longevity in a Chinese population. BMC MEDICAL GENETICS 2016; 17:31. [PMID: 27089876 PMCID: PMC4836161 DOI: 10.1186/s12881-016-0293-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2015] [Accepted: 04/14/2016] [Indexed: 01/24/2023]
Abstract
Background The silent information regulator SIR2/SIRT1gene has been demonstrated as regulating lifespan in many model organisms, including yeast, worms, fruit flies and rodents. SIRT1, the human homolog of SIR2, is considered a candidate gene as a modifier of human life expectancy. Methods In the current study we included 616 long-lived individuals and 846 matched younger controls to investigate associations between 8 common single nucleotide polymorphisms (SNPs) (i.e., rs12778366, rs3758391, rs3740051, rs33957861, rs7896005, rs12413112, rs11599176 and rs4746720) in the SIRT1 gene and human longevity. Results The 8 SNPs had strong linkage disequilibrium (LD) and were in an LD block, which was characterized by 4 common haplotypes that capture 99.3 % of the genetic variation present within it. We found no evidence for statistically significant associations between the tested SIRT1 SNPs and longevity at the allele, genotype or haplotype levels. Conclusions Current findings show that several common variants in SIRT1 are not associated with human longevity. Electronic supplementary material The online version of this article (doi:10.1186/s12881-016-0293-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Rong Lin
- Department of Biology, Hainan Medical College, Haikou, 571199, Hainan, China
| | - Dongjing Yan
- Department of Biochemistry and Molecular Biology, Hainan Medical College, Haikou, 571199, Hainan, China
| | - Yunxia Zhang
- Department of Biochemistry and Molecular Biology, Hainan Medical College, Haikou, 571199, Hainan, China
| | - Xiaoping Liao
- Department of Neurology, the Affiliated Hospital of Hainan Medical College, Haikou, 571199, Hainan, China
| | - Gu Gong
- Department of Biology, Hainan Medical College, Haikou, 571199, Hainan, China
| | - Junjie Hu
- Department of Biology, Hainan Medical College, Haikou, 571199, Hainan, China.,College of Agriculture, Hainan University, Haikou, 570228, Hainan, China
| | - Yunxin Fu
- Division of Biostatistics and Human Genetics Center, The University of Texas Health Science Center at Houston, 1200 Herman Pressler, Houston, TX, 77025, USA. .,Laboratory for Conservation and Utilization of Bio-Resources, Yunnan University, Kunming, 650091, Yunnan, China.
| | - Wangwei Cai
- Department of Biochemistry and Molecular Biology, Hainan Medical College, Haikou, 571199, Hainan, China.
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Lin R, Zhang Y, Yan D, Liao X, Gong G, Hu J, Fu Y, Cai W. Lack of association between polymorphisms in the SIRT6 gene and longevity in a Chinese population. Mol Cell Probes 2016; 30:79-82. [DOI: 10.1016/j.mcp.2016.01.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2015] [Revised: 01/19/2016] [Accepted: 01/19/2016] [Indexed: 12/11/2022]
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Novel loci and pathways significantly associated with longevity. Sci Rep 2016; 6:21243. [PMID: 26912274 PMCID: PMC4766491 DOI: 10.1038/srep21243] [Citation(s) in RCA: 121] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Accepted: 01/20/2016] [Indexed: 12/19/2022] Open
Abstract
Only two genome-wide significant loci associated with longevity have been identified so far, probably because of insufficient sample sizes of centenarians, whose genomes may harbor genetic variants associated with health and longevity. Here we report a genome-wide association study (GWAS) of Han Chinese with a sample size 2.7 times the largest previously published GWAS on centenarians. We identified 11 independent loci associated with longevity replicated in Southern-Northern regions of China, including two novel loci (rs2069837-IL6; rs2440012-ANKRD20A9P) with genome-wide significance and the rest with suggestive significance (P < 3.65 × 10(-5)). Eight independent SNPs overlapped across Han Chinese, European and U.S. populations, and APOE and 5q33.3 were replicated as longevity loci. Integrated analysis indicates four pathways (starch, sucrose and xenobiotic metabolism; immune response and inflammation; MAPK; calcium signaling) highly associated with longevity (P ≤ 0.006) in Han Chinese. The association with longevity of three of these four pathways (MAPK; immunity; calcium signaling) is supported by findings in other human cohorts. Our novel finding on the association of starch, sucrose and xenobiotic metabolism pathway with longevity is consistent with the previous results from Drosophilia. This study suggests protective mechanisms including immunity and nutrient metabolism and their interactions with environmental stress play key roles in human longevity.
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Yerges-Armstrong LM, Chai S, O'Connell JR, Curran JE, Blangero J, Mitchell BD, Shuldiner AR, Damcott CM. Gene Expression Differences Between Offspring of Long-Lived Individuals and Controls in Candidate Longevity Regions: Evidence for PAPSS2 as a Longevity Gene. J Gerontol A Biol Sci Med Sci 2016; 71:1295-9. [PMID: 26896383 DOI: 10.1093/gerona/glv212] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2015] [Accepted: 11/04/2015] [Indexed: 11/13/2022] Open
Abstract
Although there is compelling evidence for a genetic contribution to longevity, identification of specific genes that robustly associate with longevity has been a challenge. In order to identify longevity-enhancing genes, we measured differential gene expression between offspring of long-lived Amish (older than 90 years; cases, n = 128) and spouses of these offspring (controls, n = 121) and correlated differentially expressed transcripts with locations of longevity-associated variants detected in a prior genome-wide association study (GWAS) of survival to age 90. Expression of one of these transcripts, 3'-phosphoadenosine 5'-phosphosulfate synthase 2 (PAPSS2), was significantly higher in offspring versus controls (4×10(-4)) and this association was replicated using quantitative real-time polymerase chain reaction. PAPSS2, a sulfation enzyme located on chromosome 10, is ~80kb upstream of the PAPSS2 transcription start site. We found evidence of cis-expression for the originally reported GWAS SNP and PAPSS2 Monogenic conditions linked to PAPSS2 include andrenocortical androgen excess resulting in premature pubarche and skeletal dysplasias, both of which have premature aging features. In summary, these findings provide novel evidence for PAPSS2 as a longevity locus and illustrate the value of harnessing multiple "-omic" approaches to identify longevity candidates.
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Affiliation(s)
- Laura M Yerges-Armstrong
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore
| | - Sumbul Chai
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore
| | - Jeffery R O'Connell
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore
| | - Joanne E Curran
- SouthTexas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville
| | - John Blangero
- SouthTexas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville
| | - Braxton D Mitchell
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore. Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Maryland
| | - Alan R Shuldiner
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore. Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Maryland
| | - Coleen M Damcott
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore.
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Bahado-Singh RO, Zaffra R, Albayarak S, Chelliah A, Bolinjkar R, Turkoglu O, Radhakrishna U. Epigenetic markers for newborn congenital heart defect (CHD). J Matern Fetal Neonatal Med 2015; 29:1881-7. [PMID: 26429603 DOI: 10.3109/14767058.2015.1069811] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
OBJECTIVE Our objective was to determine whether there were significant differences in genome-wide DNA methylation in newborns with major congenital heart defect (CHD) compared to controls. We also evaluated methylation of cytosines in CpG motifs for the detection of these CHDs. METHODS Genome-wide DNA methylation analysis was performed on DNA from 60 newborns with various CHDs, including hypoplastic left heart syndrome, ventricular septal deficit, atrial septal defect, pulmonary stenosis, coarctation of the aorta and Tetralogy of Fallot, and 32 controls. RESULTS Highly significant differences in cytosine methylation were seen in a large number of genes throughout the genome for all CHD categories. Gene ontology analysis of CHD overall indicated over-represented biological processes involving cell development and differentiation, and anatomical structure morphogenesis. Methylation of individual cytosines in CpG motifs had high diagnostic accuracy for the detection of CHD. For example, for coarctation one predictive model based on levels of particular cytosine nucleotides achieved a sensitivity of 100% and specificity of 93.8% (AUC = 0.974, p < 0.00001). CONCLUSION Profound differences in cytosine methylation were observed in hundreds of genes in newborns with different types of CHD. There appears to be the potential for development of accurate genetic biomarkers for CHD detection in newborns.
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Affiliation(s)
- Ray O Bahado-Singh
- a Department of Obstetrics and Gynecology , William Beaumont School of Medicine, Oakland University , Royal Oak , MI , USA and
| | - Rita Zaffra
- b Department of Obstetrics and Gynecology , Wayne State University School of Medicine , Detroit , MI , USA
| | - Samet Albayarak
- b Department of Obstetrics and Gynecology , Wayne State University School of Medicine , Detroit , MI , USA
| | - Anushka Chelliah
- b Department of Obstetrics and Gynecology , Wayne State University School of Medicine , Detroit , MI , USA
| | - Rashmi Bolinjkar
- b Department of Obstetrics and Gynecology , Wayne State University School of Medicine , Detroit , MI , USA
| | - Onur Turkoglu
- a Department of Obstetrics and Gynecology , William Beaumont School of Medicine, Oakland University , Royal Oak , MI , USA and
| | - Uppala Radhakrishna
- a Department of Obstetrics and Gynecology , William Beaumont School of Medicine, Oakland University , Royal Oak , MI , USA and
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Johnson SC, Dong X, Vijg J, Suh Y. Genetic evidence for common pathways in human age-related diseases. Aging Cell 2015; 14:809-17. [PMID: 26077337 PMCID: PMC4568968 DOI: 10.1111/acel.12362] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/11/2015] [Indexed: 12/23/2022] Open
Abstract
Aging is the single largest risk factor for chronic disease. Studies in model organisms have identified conserved pathways that modulate aging rate and the onset and progression of multiple age-related diseases, suggesting that common pathways of aging may influence age-related diseases in humans as well. To determine whether there is genetic evidence supporting the notion of common pathways underlying age-related diseases, we analyzed the genes and pathways found to be associated with five major categories of age-related disease using a total of 410 genomewide association studies (GWAS). While only a small number of genes are shared among all five disease categories, those found in at least three of the five major age-related disease categories are highly enriched for apoliprotein metabolism genes. We found that a more substantial number of gene ontology (GO) terms are shared among the 5 age-related disease categories and shared GO terms include canonical aging pathways identified in model organisms, such as nutrient-sensing signaling, translation, proteostasis, stress responses, and genome maintenance. Taking advantage of the vast amount of genetic data from the GWAS, our findings provide the first direct evidence that conserved pathways of aging simultaneously influence multiple age-related diseases in humans as has been demonstrated in model organisms.
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Affiliation(s)
- Simon C. Johnson
- Department of Genetics Albert Einstein College of Medicine Bronx NY USA
| | - Xiao Dong
- Department of Genetics Albert Einstein College of Medicine Bronx NY USA
| | - Jan Vijg
- Department of Genetics Albert Einstein College of Medicine Bronx NY USA
- Department of Ophthalmology and Visual Sciences Albert Einstein College of Medicine Bronx NY USA
| | - Yousin Suh
- Department of Genetics Albert Einstein College of Medicine Bronx NY USA
- Department of Medicine Endocrinology Albert Einstein College of Medicine Bronx NY USA
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Yashin AI, Arbeev KG, Arbeeva LS, Wu D, Akushevich I, Kovtun M, Yashkin A, Kulminski A, Culminskaya I, Stallard E, Li M, Ukraintseva SV. How the effects of aging and stresses of life are integrated in mortality rates: insights for genetic studies of human health and longevity. Biogerontology 2015; 17:89-107. [PMID: 26280653 DOI: 10.1007/s10522-015-9594-8] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2015] [Accepted: 07/25/2015] [Indexed: 12/21/2022]
Abstract
Increasing proportions of elderly individuals in developed countries combined with substantial increases in related medical expenditures make the improvement of the health of the elderly a high priority today. If the process of aging by individuals is a major cause of age related health declines then postponing aging could be an efficient strategy for improving the health of the elderly. Implementing this strategy requires a better understanding of genetic and non-genetic connections among aging, health, and longevity. We review progress and problems in research areas whose development may contribute to analyses of such connections. These include genetic studies of human aging and longevity, the heterogeneity of populations with respect to their susceptibility to disease and death, forces that shape age patterns of human mortality, secular trends in mortality decline, and integrative mortality modeling using longitudinal data. The dynamic involvement of genetic factors in (i) morbidity/mortality risks, (ii) responses to stresses of life, (iii) multi-morbidities of many elderly individuals, (iv) trade-offs for diseases, (v) genetic heterogeneity, and (vi) other relevant aging-related health declines, underscores the need for a comprehensive, integrated approach to analyze the genetic connections for all of the above aspects of aging-related changes. The dynamic relationships among aging, health, and longevity traits would be better understood if one linked several research fields within one conceptual framework that allowed for efficient analyses of available longitudinal data using the wealth of available knowledge about aging, health, and longevity already accumulated in the research field.
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Affiliation(s)
- Anatoliy I Yashin
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA. .,The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, 2024 W. Main Street, Room A102E, Durham, NC, 27705, USA.
| | - Konstantin G Arbeev
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Liubov S Arbeeva
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Deqing Wu
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Igor Akushevich
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Mikhail Kovtun
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Arseniy Yashkin
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Alexander Kulminski
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Irina Culminskaya
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Eric Stallard
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Miaozhu Li
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Svetlana V Ukraintseva
- The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA.,The Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, 2024 W. Main Street, Room A105, Durham, NC, 27705, USA
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Yashin AI, Wu D, Arbeeva LS, Arbeev KG, Kulminski AM, Akushevich I, Kovtun M, Culminskaya I, Stallard E, Li M, Ukraintseva SV. Genetics of aging, health, and survival: dynamic regulation of human longevity related traits. Front Genet 2015; 6:122. [PMID: 25918517 PMCID: PMC4394697 DOI: 10.3389/fgene.2015.00122] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2014] [Accepted: 03/16/2015] [Indexed: 11/13/2022] Open
Abstract
Background: The roles of genetic factors in human longevity would be better understood if one can use more efficient methods in genetic analyses and investigate pleiotropic effects of genetic variants on aging and health related traits. Data and methods: We used EMMAX software with modified correction for population stratification to perform genome wide association studies (GWAS) of female lifespan from the original FHS cohort. The male data from the original FHS cohort and male and female data combined from the offspring FHS cohort were used to confirm findings. We evaluated pleiotropic effects of selected genetic variants as well as gene-smoking interactions on health and aging related traits. Then we reviewed current knowledge on functional properties of genes related to detected variants. Results: The eight SNPs with genome-wide significant variants were negatively associated with lifespan in both males and females. After additional QC, two of these variants were selected for further analyses of their associations with major diseases (cancer and CHD) and physiological aging changes. Gene-smoking interactions contributed to these effects. Genes closest to detected variants appear to be involved in similar biological processes and health disorders, as those found in other studies of aging and longevity e.g., in cancer and neurodegeneration. Conclusions: The impact of genes on longevity may involve trade-off-like effects on different health traits. Genes that influence lifespan represent various molecular functions but may be involved in similar biological processes and health disorders, which could contribute to genetic heterogeneity of longevity and the lack of replication in genetic association studies.
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Affiliation(s)
- Anatoliy I Yashin
- Biodemography of Aging Research Unit, Center for Population Health and Aging, Social Science Research Institute, Duke University Durham, NC, USA
| | - Deqing Wu
- Biodemography of Aging Research Unit, Center for Population Health and Aging, Social Science Research Institute, Duke University Durham, NC, USA
| | - Liubov S Arbeeva
- Biodemography of Aging Research Unit, Center for Population Health and Aging, Social Science Research Institute, Duke University Durham, NC, USA
| | - Konstantin G Arbeev
- Biodemography of Aging Research Unit, Center for Population Health and Aging, Social Science Research Institute, Duke University Durham, NC, USA
| | - Alexander M Kulminski
- Biodemography of Aging Research Unit, Center for Population Health and Aging, Social Science Research Institute, Duke University Durham, NC, USA
| | - Igor Akushevich
- Biodemography of Aging Research Unit, Center for Population Health and Aging, Social Science Research Institute, Duke University Durham, NC, USA
| | - Mikhail Kovtun
- Biodemography of Aging Research Unit, Center for Population Health and Aging, Social Science Research Institute, Duke University Durham, NC, USA ; Integrative Genomic Analysis Shared Resource, Duke Center for Genomic and Computational Biology, Duke University Durham, NC, USA
| | - Irina Culminskaya
- Biodemography of Aging Research Unit, Center for Population Health and Aging, Social Science Research Institute, Duke University Durham, NC, USA
| | - Eric Stallard
- Biodemography of Aging Research Unit, Center for Population Health and Aging, Social Science Research Institute, Duke University Durham, NC, USA
| | - Miaozhu Li
- Biodemography of Aging Research Unit, Center for Population Health and Aging, Social Science Research Institute, Duke University Durham, NC, USA
| | - Svetlana V Ukraintseva
- Biodemography of Aging Research Unit, Center for Population Health and Aging, Social Science Research Institute, Duke University Durham, NC, USA
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Minster RL, Sanders JL, Singh J, Kammerer CM, Barmada MM, Matteini AM, Zhang Q, Wojczynski MK, Daw EW, Brody JA, Arnold AM, Lunetta KL, Murabito JM, Christensen K, Perls TT, Province MA, Newman AB. Genome-Wide Association Study and Linkage Analysis of the Healthy Aging Index. J Gerontol A Biol Sci Med Sci 2015; 70:1003-8. [PMID: 25758594 DOI: 10.1093/gerona/glv006] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2014] [Accepted: 01/19/2015] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The Healthy Aging Index (HAI) is a tool for measuring the extent of health and disease across multiple systems. METHODS We conducted a genome-wide association study and a genome-wide linkage analysis to map quantitative trait loci associated with the HAI and a modified HAI weighted for mortality risk in 3,140 individuals selected for familial longevity from the Long Life Family Study. The genome-wide association study used the Long Life Family Study as the discovery cohort and individuals from the Cardiovascular Health Study and the Framingham Heart Study as replication cohorts. RESULTS There were no genome-wide significant findings from the genome-wide association study; however, several single-nucleotide polymorphisms near ZNF704 on chromosome 8q21.13 were suggestively associated with the HAI in the Long Life Family Study (p < 10(-) (6)) and nominally replicated in the Cardiovascular Health Study and Framingham Heart Study. Linkage results revealed significant evidence (log-odds score = 3.36) for a quantitative trait locus for mortality-optimized HAI in women on chromosome 9p24-p23. However, results of fine-mapping studies did not implicate any specific candidate genes within this region of interest. CONCLUSIONS ZNF704 may be a potential candidate gene for studies of the genetic underpinnings of longevity.
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Affiliation(s)
| | - Jason L Sanders
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pennsylvania
| | | | | | | | - Amy M Matteini
- Division of Geriatric Medicine and Gerontology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Qunyuan Zhang
- Division of Statistical Genomics, School of Medicine, Washington University in St. Louis, Missouri
| | - Mary K Wojczynski
- Division of Statistical Genomics, School of Medicine, Washington University in St. Louis, Missouri
| | - E Warwick Daw
- Division of Statistical Genomics, School of Medicine, Washington University in St. Louis, Missouri
| | | | - Alice M Arnold
- Department of Biostatistics, University of Washington, Seattle
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Massachusetts
| | - Joanne M Murabito
- National Heart, Lung and Blood Institute Framingham Heart Study, Massachusetts. Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Massachusetts
| | - Kaare Christensen
- Department of Epidemiology, Institute of Public Health, University of Southern Denmark, Odense
| | - Thomas T Perls
- Section of Geriatrics, Department of Medicine, Boston University, Boston School of Medicine and Boston Medical Center, Massachusetts
| | - Michael A Province
- Division of Statistical Genomics, School of Medicine, Washington University in St. Louis, Missouri
| | - Anne B Newman
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pennsylvania.
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Arbeev KG, Akushevich I, Kulminski AM, Ukraintseva SV, Yashin AI. Biodemographic Analyses of Longitudinal Data on Aging, Health, and Longevity: Recent Advances and Future Perspectives. ADVANCES IN GERIATRICS 2015; 2014:957073. [PMID: 25590047 PMCID: PMC4290867 DOI: 10.1155/2014/957073] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Biodemography became one of the most innovative and fastest growing areas in demography. This progress is fueled by the growing variability and amount of relevant data available for analyses as well as by methodological developments allowing for addressing new research questions using new approaches that can better utilize the potential of these data. In this review paper, we summarize recent methodological advances in biodemography and their diverse practical applications. Three major topics are covered: (1) computational approaches to reconstruction of age patterns of incidence of geriatric diseases and other characteristics such as recovery rates at the population level using Medicare claims data; (2) methodological advances in genetic and genomic biodemography and applications to research on genetic determinants of longevity and health; and (3) biodemographic models for joint analyses of time-to-event data and longitudinal measurements of biomarkers collected in longitudinal studies on aging. We discuss how such data and methodology can be used in a comprehensive prediction model for joint analyses of incomplete datasets that take into account the wide spectrum of factors affecting health and mortality transitions including genetic factors and hidden mechanisms of aging-related changes in physiological variables in their dynamic connection with health and survival.
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Affiliation(s)
- Konstantin G Arbeev
- Center for Population Health and Aging, Duke University, Erwin Mill Building, 2024 W. Main Street, P.O. Box 90420, Durham, NC 27705, USA
| | - Igor Akushevich
- Center for Population Health and Aging, Duke University, Erwin Mill Building, 2024 W. Main Street, P.O. Box 90420, Durham, NC 27705, USA
| | - Alexander M Kulminski
- Center for Population Health and Aging, Duke University, Erwin Mill Building, 2024 W. Main Street, P.O. Box 90420, Durham, NC 27705, USA
| | - Svetlana V Ukraintseva
- Center for Population Health and Aging, Duke University, Erwin Mill Building, 2024 W. Main Street, P.O. Box 90420, Durham, NC 27705, USA
| | - Anatoliy I Yashin
- Center for Population Health and Aging, Duke University, Erwin Mill Building, 2024 W. Main Street, P.O. Box 90420, Durham, NC 27705, USA
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Broer L, van Duijn CM. GWAS and Meta-Analysis in Aging/Longevity. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2015; 847:107-25. [PMID: 25916588 DOI: 10.1007/978-1-4939-2404-2_5] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Longevity is an extremely complex phenotype that is determined by environment, life style and genetics. Genome wide association studies (GWAS) have been a powerful tool to identify the genetic origin of other complex outcome with a similar heritability. In this chapter we discuss the findings all GWAS of longevity conducted to date. Various cut-off to define longevity have been used varying from 85+, 90+ and 100+ years and the impact of these difference are addressed in this chapter. The only consistent association emerging from GWAS to data is the APOE gene that has been already identified as a candidate gene. Although (GWAS) have identified biologically plausible genes and pathways, no new loci for longevity have been conclusively proven. A reason for not finding any replicated associations for longevity could be the complexity of the phenotype, although heterogeneity also underlies many other traits for which GWAS has been successful. One may argue that rare variants explain the high heritability of longevity and the segregation of the trait in families. Yet, whole genome analyses of GWAS data still suggest that over 80 % of the heritability is explained by common variants. Although findings of GWAS to date have been disappointing, there is ample opportunity to improve the statistical power of studies to find common variants with small effects. In the near future, joining of the published studies and new ones emerging may bring to surface new loci.
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Affiliation(s)
- Linda Broer
- Department of Epidemiology, Erasmus University Medical Center, Dr. Molewaterplein 50, PO-Box 2040, 3000 CA, Rotterdam, Netherlands,
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48
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Broer L, Buchman AS, Deelen J, Evans DS, Faul JD, Lunetta KL, Sebastiani P, Smith JA, Smith AV, Tanaka T, Yu L, Arnold AM, Aspelund T, Benjamin EJ, De Jager PL, Eirkisdottir G, Evans DA, Garcia ME, Hofman A, Kaplan RC, Kardia SLR, Kiel DP, Oostra BA, Orwoll ES, Parimi N, Psaty BM, Rivadeneira F, Rotter JI, Seshadri S, Singleton A, Tiemeier H, Uitterlinden AG, Zhao W, Bandinelli S, Bennett DA, Ferrucci L, Gudnason V, Harris TB, Karasik D, Launer LJ, Perls TT, Slagboom PE, Tranah GJ, Weir DR, Newman AB, van Duijn CM, Murabito JM. GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy. J Gerontol A Biol Sci Med Sci 2015; 70:110-8. [PMID: 25199915 PMCID: PMC4296168 DOI: 10.1093/gerona/glu166] [Citation(s) in RCA: 218] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2014] [Accepted: 08/07/2014] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND The genetic contribution to longevity in humans has been estimated to range from 15% to 25%. Only two genes, APOE and FOXO3, have shown association with longevity in multiple independent studies. METHODS We conducted a meta-analysis of genome-wide association studies including 6,036 longevity cases, age ≥90 years, and 3,757 controls that died between ages 55 and 80 years. We additionally attempted to replicate earlier identified single nucleotide polymorphism (SNP) associations with longevity. RESULTS In our meta-analysis, we found suggestive evidence for the association of SNPs near CADM2 (odds ratio [OR] = 0.81; p value = 9.66 × 10(-7)) and GRIK2 (odds ratio = 1.24; p value = 5.09 × 10(-8)) with longevity. When attempting to replicate findings earlier identified in genome-wide association studies, only the APOE locus consistently replicated. In an additional look-up of the candidate gene FOXO3, we found that an earlier identified variant shows a highly significant association with longevity when including published data with our meta-analysis (odds ratio = 1.17; p value = 1.85×10(-10)). CONCLUSIONS We did not identify new genome-wide significant associations with longevity and did not replicate earlier findings except for APOE and FOXO3. Our inability to find new associations with survival to ages ≥90 years because longevity represents multiple complex traits with heterogeneous genetic underpinnings, or alternatively, that longevity may be regulated by rare variants that are not captured by standard genome-wide genotyping and imputation of common variants.
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Affiliation(s)
- Linda Broer
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, The Netherlands. Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Aron S Buchman
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Joris Deelen
- Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, The Netherlands. Department of Molecular Epidemiology, Leiden University Medical Center, The Netherlands
| | - Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Massachusetts. NHLBI's and Boston Univesity's Framingham Heart Study, Massachusetts
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Massachusetts
| | | | - Albert V Smith
- Icelandic Heart Association, Kopavogur, Iceland. Department of Medicine, University of Iceland, Reykjavik
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, Maryland
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Alice M Arnold
- Department of Biostatistics, University of Washington, Seattle
| | - Thor Aspelund
- Icelandic Heart Association, Kopavogur, Iceland. Department of Medicine, University of Iceland, Reykjavik
| | - Emelia J Benjamin
- NHLBI's and Boston Univesity's Framingham Heart Study, Massachusetts. Department of Medicine, Sections of Preventive Medicine and Cardiology, Boston University School of Medicine, Massachusetts. Department of Epidemiology, Boston University School of Public Health, Massachusetts
| | - Philip L De Jager
- Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts. Harvard Medical School, Boston, Massachusetts. Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | | | - Denis A Evans
- Rush Institute for Healthy Aging and Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois
| | - Melissa E Garcia
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, Maryland
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, The Netherlands
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College, Bronx, New York
| | | | - Douglas P Kiel
- Harvard Medical School, Boston, Massachusetts. Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School Department of Medicine, Boston, Massachusetts. Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Ben A Oostra
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, The Netherlands
| | - Eric S Orwoll
- School of Medicine, Oregon Health and Science University, Portland
| | - Neeta Parimi
- California Pacific Medical Center Research Institute, San Francisco
| | - Bruce M Psaty
- Department of Medicine, University of Washington, Seattle. Deparment of Epidemiology, University of Washington, Seattle. Department of Health Services, University of Washington, Seattle. Group Health Research Institute, Group Health Cooperative, Seattle, Washington
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School Department of Medicine, Boston, Massachusetts
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California
| | - Sudha Seshadri
- Department of Biostatistics, Boston University School of Public Health, Massachusetts. Department of Neurology, Boston University School of Medicine, Massachusetts
| | - Andrew Singleton
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, Maryland
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, The Netherlands. Department of Child and Adolescent Psychiatry, Erasmus MC and Sophia Children's Hospital, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, The Netherlands. Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor
| | | | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, Baltimore, Maryland
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland. Department of Medicine, University of Iceland, Reykjavik
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, Maryland
| | - David Karasik
- Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School Department of Medicine, Boston, Massachusetts. Faculty of Medicine in The Galilee, Bar-Ilan University, Safed, Israel
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, Maryland
| | - Thomas T Perls
- Section of Geriatrics, Boston University School of Medicine and Boston Medical Center, Massachusetts
| | - P Eline Slagboom
- Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, The Netherlands. Department of Molecular Epidemiology, Leiden University Medical Center, The Netherlands
| | - Gregory J Tranah
- California Pacific Medical Center Research Institute, San Francisco. Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor
| | - Anne B Newman
- Department of Epidemiology, University of Pittsburgh, Pennsylvania. *These authors contributed equally to this work
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, The Netherlands. *These authors contributed equally to this work
| | - Joanne M Murabito
- NHLBI's and Boston Univesity's Framingham Heart Study, Massachusetts. Department of Medicine, Section of General Internal Medicine, Boston University School of Medicine, Massachusetts. *These authors contributed equally to this work.
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Shadyab AH, LaCroix AZ. Genetic factors associated with longevity: a review of recent findings. Ageing Res Rev 2015; 19:1-7. [PMID: 25446805 DOI: 10.1016/j.arr.2014.10.005] [Citation(s) in RCA: 72] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2014] [Revised: 10/20/2014] [Accepted: 10/27/2014] [Indexed: 12/21/2022]
Abstract
Given the rising rate of survival into advanced old age in the United States, achieving longevity and healthy aging is becoming increasingly important. Besides maintaining healthy lifestyle behaviors, positive aging outcomes may also be heritable, with estimates ranging from 20% to 35%. In this qualitative review, we summarize recent findings on genetic factors linked to longevity across different populations and study designs. Recent studies not only confirm the association of APOE with longevity in different populations, but also implicate several other pathways that may influence longevity including nitric oxide production, inflammation, immunity, and DNA damage response and repair. Recent evidence also suggests that mitochondrial DNA may play an important role in attaining longevity. Despite these implicated pathways, longevity may be a polygenic trait influenced by a complex interplay of multiple genes. Future genetic studies on aging would benefit from larger samples of long-lived individuals, birth-cohort matched controls, inclusion of different aging phenotypes (e.g., aging free of morbidities), and analysis of gender differences.
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Affiliation(s)
- Aladdin H Shadyab
- San Diego State University/University of California, San Diego Joint-Doctoral Program in Public Health (Epidemiology), USA; Graduate School of Public Health, San Diego State University, Hardy Tower Room 119, 5500 Campanile Drive, San Diego, CA, 92182-4162, USA.
| | - Andrea Z LaCroix
- Department of Family and Preventive Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA.
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Corella D, Ordovás JM. Aging and cardiovascular diseases: the role of gene-diet interactions. Ageing Res Rev 2014; 18:53-73. [PMID: 25159268 DOI: 10.1016/j.arr.2014.08.002] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2014] [Revised: 08/15/2014] [Accepted: 08/18/2014] [Indexed: 12/21/2022]
Abstract
In the study of longevity, increasing importance is being placed on the concept of healthy aging rather than considering the total number of years lived. Although the concept of healthy lifespan needs to be defined better, we know that cardiovascular diseases (CVDs) are the main age-related diseases. Thus, controlling risk factors will contribute to reducing their incidence, leading to healthy lifespan. CVDs are complex diseases influenced by numerous genetic and environmental factors. Numerous gene variants that are associated with a greater or lesser risk of the different types of CVD and of intermediate phenotypes (i.e., hypercholesterolemia, hypertension, diabetes) have been successfully identified. However, despite the close link between aging and CVD, studies analyzing the genes related to human longevity have not obtained consistent results and there has been little coincidence in the genes identified in both fields. The APOE gene stands out as an exception, given that it has been identified as being relevant in CVD and longevity. This review analyzes the genomic and epigenomic factors that may contribute to this, ranging from identifying longevity genes in model organisms to the importance of gene-diet interactions (outstanding among which is the case of the TCF7L2 gene).
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