1
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de Kat AC, Roelofs F, Slagboom PE, Broekmans FJM, Beekman M, Berg NVD. Late reproduction is associated with extended female survival but not with familial longevity. Reprod Biomed Online 2024; 49:104073. [PMID: 38964280 DOI: 10.1016/j.rbmo.2024.104073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Revised: 04/03/2024] [Accepted: 04/09/2024] [Indexed: 07/06/2024]
Abstract
RESEARCH QUESTION Are age at last childbirth and number of children, as facets of female reproductive health, related to individual lifespan or familial longevity? DESIGN This observational study included 10,255 female participants from a multigenerational historical cohort, the LINKing System for historical family reconstruction (LINKS), and 1258 female participants from 651 long-lived families in the Leiden Longevity Study (LLS). Age at last childbirth and number of children, as outcomes of reproductive success, were compared with individual and familial longevity using the LINKS dataset. In addition, the genetic predisposition in the form of a polygenic risk score (PRS) for age at menopause was studied in relation to familial longevity using the LLS dataset. RESULTS For each year increase in the age of the birth of the last child, a woman's lifespan increased by 0.06 years (22 days; P = 0.002). The yearly risk for having a last child was 9% lower in women who survived to the oldest 10% of their birth cohort (hazard ratio 0.91, 95% CI 0.86-0.95). Women who came from long-living families did not have a higher mean age of last childbirth. There was no significant association between familial longevity and genetic predisposition to age at menopause. CONCLUSIONS Female reproductive health associates with a longer lifespan. Familial longevity does not associate to extended reproductive health. Other factors in somatic maintenance that support a longer lifespan are likely to have an impact on reproductive health.
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Affiliation(s)
- Annelien C de Kat
- Department of Reproductive Medicine and Gynecology, University Medical Center Utrecht, Utrecht, The Netherlands..
| | - Femke Roelofs
- Department of Reproductive Medicine and Gynecology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - P Eline Slagboom
- Section of Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Frank J M Broekmans
- Department of Reproductive Medicine and Gynecology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Marian Beekman
- Section of Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Niels van den Berg
- Section of Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
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2
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Smulders L, Deelen J. Genetics of human longevity: From variants to genes to pathways. J Intern Med 2024; 295:416-435. [PMID: 37941149 DOI: 10.1111/joim.13740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
The current increase in lifespan without an equivalent increase in healthspan poses a grave challenge to the healthcare system and a severe burden on society. However, some individuals seem to be able to live a long and healthy life without the occurrence of major debilitating chronic diseases, and part of this trait seems to be hidden in their genome. In this review, we discuss the findings from studies on the genetic component of human longevity and the main challenges accompanying these studies. We subsequently focus on results from genetic studies in model organisms and comparative genomic approaches to highlight the most important conserved longevity-associated pathways. By combining the results from studies using these different approaches, we conclude that only five main pathways have been consistently linked to longevity, namely (1) insulin/insulin-like growth factor 1 signalling, (2) DNA-damage response and repair, (3) immune function, (4) cholesterol metabolism and (5) telomere maintenance. As our current approaches to study the relevance of these pathways in humans are limited, we suggest that future studies on the genetics of human longevity should focus on the identification and functional characterization of rare genetic variants in genes involved in these pathways.
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Affiliation(s)
- Larissa Smulders
- Max Planck Institute for Biology of Ageing, Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Ageing-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Joris Deelen
- Max Planck Institute for Biology of Ageing, Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Ageing-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
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3
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van der Spek A, Karamujić-Čomić H, Pool R, Bot M, Beekman M, Garmaeva S, Arp PP, Henkelman S, Liu J, Alves AC, Willemsen G, van Grootheest G, Aubert G, Ikram MA, Jarvelin MR, Lansdorp P, Uitterlinden AG, Zhernakova A, Slagboom PE, Penninx BWJH, Boomsma DI, Amin N, van Duijn CM. Fat metabolism is associated with telomere length in six population-based studies. Hum Mol Genet 2021; 31:1159-1170. [PMID: 34875050 DOI: 10.1093/hmg/ddab281] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 08/13/2021] [Accepted: 09/07/2021] [Indexed: 11/13/2022] Open
Abstract
Telomeres are repetitive DNA sequences located at the end of chromosomes, which are associated to biological aging, cardiovascular disease, cancer, and mortality. Lipid and fatty acid metabolism have been associated with telomere shortening. We have conducted an in-depth study investigating the association of metabolic biomarkers with telomere length (LTL). We performed an association analysis of 226 metabolic biomarkers with LTL using data from 11 775 individuals from six independent population-based cohorts (BBMRI-NL consortium). Metabolic biomarkers include lipoprotein lipids and subclasses, fatty acids, amino acids, glycolysis measures and ketone bodies. LTL was measured by quantitative polymerase chain reaction or FlowFISH. Linear regression analysis was performed adjusting for age, sex, lipid-lowering medication and cohort-specific covariates (model 1) and additionally for body mass index (BMI) and smoking (model 2), followed by inverse variance-weighted meta-analyses (significance threshold pmeta = 6.5x10-4). We identified four metabolic biomarkers positively associated with LTL, including two cholesterol to lipid ratios in small VLDL (S-VLDL-C % and S-VLDL-ce %) and two omega-6 fatty acid ratios (FAw6/FA and LA/FA). After additionally adjusting for BMI and smoking, these metabolic biomarkers remained associated with LTL with similar effect estimates. In addition, cholesterol esters in very small VLDL (XS-VLDL-ce) became significantly associated with LTL (p = 3.6x10-4). We replicated the association of FAw6/FA with LTL in an independent dataset of 7845 individuals (p = 1.9x10-4). To conclude, we identified multiple metabolic biomarkers involved in lipid and fatty acid metabolism that may be involved in LTL biology. Longitudinal studies are needed to exclude reversed causation.
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Affiliation(s)
- Ashley van der Spek
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,SkylineDx B.V., Rotterdam, The Netherlands
| | - Hata Karamujić-Čomić
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit University Amsterdam, Amsterdam, The Netherlands.,Amsterdam Public Health research institute, Amsterdam University Medical Centers, The Netherlands.,BBMRI-NL: Infrastructure for the Application of Metabolomics Technology in Epidemiology (RP4), The Netherlands
| | - Mariska Bot
- Department of Psychiatry and GGZ in Geest, Amsterdam Public Health research institute and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Sanzhima Garmaeva
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Pascal P Arp
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Sandra Henkelman
- European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jun Liu
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Alexessander Couto Alves
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.,School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit University Amsterdam, Amsterdam, The Netherlands.,Amsterdam Public Health research institute, Amsterdam University Medical Centers, The Netherlands
| | - Gerard van Grootheest
- Department of Psychiatry and GGZ in Geest, Amsterdam Public Health research institute and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Geraldine Aubert
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, V5Z 1L3 British Columbia, Canada
| | | | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.,Center for Life Course Epidemiology, Faculty of Medicine, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Peter Lansdorp
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, V5Z 1L3 British Columbia, Canada.,Departments of Medical Genetics and Hematology, University of British Columbia, Vancouver, V6T 1Z4 British Columbia, Canada
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Alexandra Zhernakova
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - P Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry and GGZ in Geest, Amsterdam Public Health research institute and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit University Amsterdam, Amsterdam, The Netherlands.,Amsterdam Public Health research institute, Amsterdam University Medical Centers, The Netherlands.,BBMRI-NL: Infrastructure for the Application of Metabolomics Technology in Epidemiology (RP4), The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, UK
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4
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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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5
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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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6
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Genomic Approach to Understand the Association of DNA Repair with Longevity and Healthy Aging Using Genomic Databases of Oldest-Old Population. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2018; 2018:2984730. [PMID: 29854078 PMCID: PMC5960555 DOI: 10.1155/2018/2984730] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2018] [Accepted: 04/03/2018] [Indexed: 12/16/2022]
Abstract
Aged population is increasing worldwide due to the aging process that is inevitable. Accordingly, longevity and healthy aging have been spotlighted to promote social contribution of aged population. Many studies in the past few decades have reported the process of aging and longevity, emphasizing the importance of maintaining genomic stability in exceptionally long-lived population. Underlying reason of longevity remains unclear due to its complexity involving multiple factors. With advances in sequencing technology and human genome-associated approaches, studies based on population-based genomic studies are increasing. In this review, we summarize recent longevity and healthy aging studies of human population focusing on DNA repair as a major factor in maintaining genome integrity. To keep pace with recent growth in genomic research, aging- and longevity-associated genomic databases are also briefly introduced. To suggest novel approaches to investigate longevity-associated genetic variants related to DNA repair using genomic databases, gene set analysis was conducted, focusing on DNA repair- and longevity-associated genes. Their biological networks were additionally analyzed to grasp major factors containing genetic variants of human longevity and healthy aging in DNA repair mechanisms. In summary, this review emphasizes DNA repair activity in human longevity and suggests approach to conduct DNA repair-associated genomic study on human healthy aging.
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7
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Wahl A, van den Akker E, Klaric L, Štambuk J, Benedetti E, Plomp R, Razdorov G, Trbojević-Akmačić I, Deelen J, van Heemst D, Slagboom PE, Vučković F, Grallert H, Krumsiek J, Strauch K, Peters A, Meitinger T, Hayward C, Wuhrer M, Beekman M, Lauc G, Gieger C. Genome-Wide Association Study on Immunoglobulin G Glycosylation Patterns. Front Immunol 2018. [PMID: 29535710 PMCID: PMC5834439 DOI: 10.3389/fimmu.2018.00277] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Immunoglobulin G (IgG), a glycoprotein secreted by plasma B-cells, plays a major role in the human adaptive immune response and are associated with a wide range of diseases. Glycosylation of the Fc binding region of IgGs, responsible for the antibody’s effector function, is essential for prompting a proper immune response. This study focuses on the general genetic impact on IgG glycosylation as well as corresponding subclass specificities. To identify genetic loci involved in IgG glycosylation, we performed a genome-wide association study (GWAS) on liquid chromatography electrospray mass spectrometry (LC–ESI-MS)—measured IgG glycopeptides of 1,823 individuals in the Cooperative Health Research in the Augsburg Region (KORA F4) study cohort. In addition, we performed GWAS on subclass-specific ratios of IgG glycans to gain power in identifying genetic factors underlying single enzymatic steps in the glycosylation pathways. We replicated our findings in 1,836 individuals from the Leiden Longevity Study (LLS). We were able to show subclass-specific genetic influences on single IgG glycan structures. The replicated results indicate that, in addition to genes encoding for glycosyltransferases (i.e., ST6GAL1, B4GALT1, FUT8, and MGAT3), other genetic loci have strong influences on the IgG glycosylation patterns. A novel locus on chromosome 1, harboring RUNX3, which encodes for a transcription factor of the runt domain-containing family, is associated with decreased galactosylation. Interestingly, members of the RUNX family are cross-regulated, and RUNX3 is involved in both IgA class switching and B-cell maturation as well as T-cell differentiation and apoptosis. Besides the involvement of glycosyltransferases in IgG glycosylation, we suggest that, due to the impact of variants within RUNX3, potentially mechanisms involved in B-cell activation and T-cell differentiation during the immune response as well as cell migration and invasion involve IgG glycosylation.
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Affiliation(s)
- Annika Wahl
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Epidemiology 2, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Erik van den Akker
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center (LUMC), Leiden, Netherlands.,Pattern Recognition and Bioinformatics, Delft University of Technology, Delft, Netherlands
| | - Lucija Klaric
- Genos Glycoscience Research Laboratory, Zagreb, Croatia.,MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom.,Centre for Global Health Research Population Health Sciences, School of Molecular, Genetic and Population Health Sciences, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Jerko Štambuk
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Elisa Benedetti
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Rosina Plomp
- Center for Proteomics and Metabolomics, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | | | | | - Joris Deelen
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center (LUMC), Leiden, Netherlands.,Max Planck Institute for Biology of Ageing, Köln, Germany
| | - Diana van Heemst
- Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - P Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | | | - Harald Grallert
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Epidemiology 2, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Jan Krumsiek
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,IBE, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology 2, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Manfred Wuhrer
- Center for Proteomics and Metabolomics, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia.,Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Epidemiology 2, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
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8
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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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9
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Deelen J, van den Akker EB, Trompet S, van Heemst D, Mooijaart SP, Slagboom PE, Beekman M. Employing biomarkers of healthy ageing for leveraging genetic studies into human longevity. Exp Gerontol 2016; 82:166-74. [PMID: 27374409 DOI: 10.1016/j.exger.2016.06.013] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Revised: 05/27/2016] [Accepted: 06/27/2016] [Indexed: 01/03/2023]
Abstract
Genetic studies have thus far identified a limited number of loci associated with human longevity by applying age at death or survival up to advanced ages as phenotype. As an alternative approach, one could first try to identify biomarkers of healthy ageing and the genetic variants associated with these traits and subsequently determine the association of these variants with human longevity. In the present study, we used this approach by testing whether the 35 baseline serum parameters measured in the Leiden Longevity Study (LLS) meet the proposed criteria for a biomarker of healthy ageing. The LLS consists of 421 families with long-lived siblings of European descent, who were recruited together with their offspring and the spouses of the offspring (controls). To test the four criteria for a biomarker of healthy ageing in the LLS, we determined the association of the serum parameters with chronological age, familial longevity, general practitioner-reported general health, and mortality. Out of the 35 serum parameters, we identified glucose, insulin, and triglycerides as biomarkers of healthy ageing, meeting all four criteria in the LLS. We subsequently showed that the genetic variants previously associated with these parameters are significantly enriched in the largest genome-wide association study for human longevity. In conclusion, we showed that biomarkers of healthy ageing can be used to leverage genetic studies into human longevity. We identified several genetic variants influencing the variation in glucose, insulin and triglycerides that contribute to human longevity.
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Affiliation(s)
- Joris Deelen
- Department of Molecular Epidemiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; Max Planck Institute for Biology of Ageing, P.O. Box 41 06 23, 50866 Cologne, Germany.
| | - Erik B van den Akker
- Department of Molecular Epidemiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; Delft Bioinformatics Lab, Delft University of Technology, P.O. Box 5031, 2600 GA Delft, The Netherlands.
| | - Stella Trompet
- Department of Gerontology and Geriatrics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; Department of Cardiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands.
| | - Diana van Heemst
- Department of Gerontology and Geriatrics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands.
| | - Simon P Mooijaart
- Department of Gerontology and Geriatrics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands.
| | - P Eline Slagboom
- Department of Molecular Epidemiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands.
| | - Marian Beekman
- Department of Molecular Epidemiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands.
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10
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Nygaard M, Debrabant B, Tan Q, Deelen J, Andersen‐Ranberg K, Craen AJ, Beekman M, Jeune B, Slagboom PE, Christensen K, Christiansen L. Copy number variation associates with mortality in long-lived individuals: a genome-wide assessment. Aging Cell 2016; 15:49-55. [PMID: 26446717 PMCID: PMC4717275 DOI: 10.1111/acel.12407] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/09/2015] [Indexed: 11/30/2022] Open
Abstract
Copy number variants (CNVs) represent a significant source of genetic variation in the human genome and have been implicated in numerous diseases and complex traits. To date, only a few studies have investigated the role of CNVs in human lifespan. To investigate the impact of CNVs on prospective mortality at the extreme end of life, where the genetic component of lifespan appears most profound, we analyzed genomewide CNV data in 603 Danish nonagenarians and centenarians (mean age 96.9 years, range 90.0–102.5 years). Replication was performed in 500 long‐lived individuals from the Leiden Longevity Study (mean age 93.2 years, range 88.9–103.4 years). First, we assessed the association between the CNV burden of each individual (the number of CNVs, the average CNV length, and the total CNV length) and mortality and found a significant increase in mortality per 10 kb increase in the average CNV length, both for all CNVs (hazard ratio (HR) = 1.024, P = 0.002) and for duplications (HR = 1.011, P = 0.005), as well as per 100 kb increase in the total length of deletions (HR = 1.009, P = 0.0005). Next, we assessed the relation between specific deletions and duplications and mortality. Although no genome–wide significant associations were discovered, we identified six deletions and one duplication that showed consistent association with mortality in both or either of the sexes across both study populations. These results indicate that the genome–wide CNV burden, specifically the average CNV length and the total CNV length, associates with higher mortality in long‐lived individuals.
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Affiliation(s)
- Marianne Nygaard
- The Danish Aging Research Center Epidemiology, Biostatistics and Biodemography Department of Public Health University of Southern Denmark J.B. Winsloews Vej 9B, 5000, Odense C Denmark
- Department of Clinical Genetics Odense University Hospital Sdr. Boulevard 29, 5000, Odense C Denmark
| | - Birgit Debrabant
- The Danish Aging Research Center Epidemiology, Biostatistics and Biodemography Department of Public Health University of Southern Denmark J.B. Winsloews Vej 9B, 5000, Odense C Denmark
| | - Qihua Tan
- The Danish Aging Research Center Epidemiology, Biostatistics and Biodemography Department of Public Health University of Southern Denmark J.B. Winsloews Vej 9B, 5000, Odense C Denmark
- Department of Clinical Genetics Odense University Hospital Sdr. Boulevard 29, 5000, Odense C Denmark
| | - Joris Deelen
- Department of Molecular Epidemiology Leiden University Medical Center P.O. Box 9600, 2300 RC Leiden The Netherlands
| | - Karen Andersen‐Ranberg
- The Danish Aging Research Center Epidemiology, Biostatistics and Biodemography Department of Public Health University of Southern Denmark J.B. Winsloews Vej 9B, 5000, Odense C Denmark
| | - Anton J.M. Craen
- Department of Gerontology and Geriatrics Leiden University Medical Center P.O. Box 9600, 2300 RC Leiden The Netherlands
| | - Marian Beekman
- Department of Molecular Epidemiology Leiden University Medical Center P.O. Box 9600, 2300 RC Leiden The Netherlands
| | - Bernard Jeune
- The Danish Aging Research Center Epidemiology, Biostatistics and Biodemography Department of Public Health University of Southern Denmark J.B. Winsloews Vej 9B, 5000, Odense C Denmark
| | - Pieternella E. Slagboom
- Department of Molecular Epidemiology Leiden University Medical Center P.O. Box 9600, 2300 RC Leiden The Netherlands
| | - Kaare Christensen
- The Danish Aging Research Center Epidemiology, Biostatistics and Biodemography Department of Public Health University of Southern Denmark J.B. Winsloews Vej 9B, 5000, Odense C Denmark
- Department of Clinical Genetics Odense University Hospital Sdr. Boulevard 29, 5000, Odense C Denmark
- Department of Clinical Biochemistry and Pharmacology Odense University Hospital Sdr. Boulevard 29, 5000 Odense C Denmark
| | - Lene Christiansen
- The Danish Aging Research Center Epidemiology, Biostatistics and Biodemography Department of Public Health University of Southern Denmark J.B. Winsloews Vej 9B, 5000, Odense C Denmark
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11
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Postmus I, Deelen J, Sedaghat S, Trompet S, de Craen AJM, Heijmans BT, Franco OH, Hofman A, Dehghan A, Slagboom PE, Westendorp RGJ, Jukema JW. LDL cholesterol still a problem in old age? A Mendelian randomization study. Int J Epidemiol 2015; 44:604-12. [DOI: 10.1093/ije/dyv031] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/26/2015] [Indexed: 12/31/2022] Open
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12
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Association of adiponectin and leptin with relative telomere length in seven independent cohorts including 11,448 participants. Eur J Epidemiol 2014; 29:629-38. [DOI: 10.1007/s10654-014-9940-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Accepted: 07/15/2014] [Indexed: 01/09/2023]
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13
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Lee JH, Cheng R, Honig LS, Feitosa M, Kammerer CM, Kang MS, Schupf N, Lin SJ, Sanders JL, Bae H, Druley T, Perls T, Christensen K, Province M, Mayeux R. Genome wide association and linkage analyses identified three loci-4q25, 17q23.2, and 10q11.21-associated with variation in leukocyte telomere length: the Long Life Family Study. Front Genet 2014; 4:310. [PMID: 24478790 PMCID: PMC3894567 DOI: 10.3389/fgene.2013.00310] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2013] [Accepted: 12/20/2013] [Indexed: 11/13/2022] Open
Abstract
Leukocyte telomere length is believed to measure cellular aging in humans, and short leukocyte telomere length is associated with increased risks of late onset diseases, including cardiovascular disease, dementia, etc. Many studies have shown that leukocyte telomere length is a heritable trait, and several candidate genes have been identified, including TERT, TERC, OBFC1, and CTC1. Unlike most studies that have focused on genetic causes of chronic diseases such as heart disease and diabetes in relation to leukocyte telomere length, the present study examined the genome to identify variants that may contribute to variation in leukocyte telomere length among families with exceptional longevity. From the genome wide association analysis in 4,289 LLFS participants, we identified a novel intergenic SNP rs7680468 located near PAPSS1 and DKK2 on 4q25 (p = 4.7E-8). From our linkage analysis, we identified two additional novel loci with HLOD scores exceeding three, including 4.77 for 17q23.2, and 4.36 for 10q11.21. These two loci harbor a number of novel candidate genes with SNPs, and our gene-wise association analysis identified multiple genes, including DCAF7, POLG2, CEP95, and SMURF2 at 17q23.2; and RASGEF1A, HNRNPF, ANF487, CSTF2T, and PRKG1 at 10q11.21. Among these genes, multiple SNPs were associated with leukocyte telomere length, but the strongest association was observed with one contiguous haplotype in CEP95 and SMURF2. We also show that three previously reported genes-TERC, MYNN, and OBFC1-were significantly associated with leukocyte telomere length at p empirical < 0.05.
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Affiliation(s)
- Joseph H Lee
- Sergievsky Center, College of Physicians and Surgeons, Columbia University New York, NY, USA ; Taub Institute, College of Physicians and Surgeons, Columbia University New York, NY, USA ; Department of Epidemiology, School of Public Health, Columbia University New York, NY, USA
| | - Rong Cheng
- Sergievsky Center, College of Physicians and Surgeons, Columbia University New York, NY, USA ; Taub Institute, College of Physicians and Surgeons, Columbia University New York, NY, USA
| | - Lawrence S Honig
- Sergievsky Center, College of Physicians and Surgeons, Columbia University New York, NY, USA ; Taub Institute, College of Physicians and Surgeons, Columbia University New York, NY, USA ; Department of Neurology, College of Physicians and Surgeons, Columbia University New York, NY, USA
| | - Mary Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine St. Louis, MO, USA
| | - Candace M Kammerer
- Department of Epidemiology, University of Pittsburgh Pittsburgh, PA, USA ; Department of Human Genetics, University of Pittsburgh Pittsburgh, PA, USA ; Center for Aging and Population Health, University of Pittsburgh Pittsburgh, PA, USA
| | - Min S Kang
- Taub Institute, College of Physicians and Surgeons, Columbia University New York, NY, USA
| | - Nicole Schupf
- Sergievsky Center, College of Physicians and Surgeons, Columbia University New York, NY, USA ; Taub Institute, College of Physicians and Surgeons, Columbia University New York, NY, USA ; Department of Epidemiology, School of Public Health, Columbia University New York, NY, USA ; Department of Psychiatry, College of Physicians and Surgeons, Columbia University New York, NY, USA
| | - Shiow J Lin
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine St. Louis, MO, USA
| | - Jason L Sanders
- Department of Epidemiology, University of Pittsburgh Pittsburgh, PA, USA ; Center for Aging and Population Health, University of Pittsburgh Pittsburgh, PA, USA
| | - Harold Bae
- Department of Biostatistics, Boston University Medical Center Boston, MA, USA
| | - Todd Druley
- Department of Pediatrics and Genetics, Washington University School of Medicine St. Louis, MO, USA
| | - Thomas Perls
- Department of Medicine, Boston University Medical Center Boston, MA, USA
| | - Kaare Christensen
- The Danish Aging Research Center, Epidemiology, University of Southern Denmark Odense, Denmark
| | - Michael Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine St. Louis, MO, USA
| | - Richard Mayeux
- Sergievsky Center, College of Physicians and Surgeons, Columbia University New York, NY, USA ; Taub Institute, College of Physicians and Surgeons, Columbia University New York, NY, USA ; Department of Epidemiology, School of Public Health, Columbia University New York, NY, USA ; Department of Neurology, College of Physicians and Surgeons, Columbia University New York, NY, USA ; Department of Psychiatry, College of Physicians and Surgeons, Columbia University New York, NY, USA
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14
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Deelen J, Beekman M, Codd V, Trompet S, Broer L, Hägg S, Fischer K, Thijssen PE, Suchiman HED, Postmus I, Uitterlinden AG, Hofman A, de Craen AJM, Metspalu A, Pedersen NL, van Duijn CM, Jukema JW, Houwing-Duistermaat JJ, Samani NJ, Slagboom PE. Leukocyte telomere length associates with prospective mortality independent of immune-related parameters and known genetic markers. Int J Epidemiol 2014; 43:878-86. [PMID: 24425829 PMCID: PMC4052133 DOI: 10.1093/ije/dyt267] [Citation(s) in RCA: 87] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Background: Human leukocyte telomere length (LTL) decreases with age and shorter LTL has previously been associated with increased prospective mortality. However, it is not clear whether LTL merely marks the health status of an individual by its association with parameters of immune function, for example, or whether telomere shortening also contributes causally to lifespan variation in humans. Methods: We measured LTL in 870 nonagenarian siblings (mean age 93 years), 1580 of their offspring and 725 spouses thereof (mean age 59 years) from the Leiden Longevity Study (LLS). Results: We found that shorter LTL is associated with increased prospective mortality in middle (30–80 years; hazard ratio (HR) = 0.75, P = 0.001) and highly advanced age (≥90 years; HR = 0.92, P = 0.028), and show that this association cannot be explained by the association of LTL with the immune-related markers insulin-like growth factor 1 to insulin-like growth factor binding protein 3 molar ratio, C-reactive protein, interleukin 6, cytomegalovirus serostatus or white blood cell counts. We found no difference in LTL between the middle-aged LLS offspring and their spouses (β = 0.006, P = 0.932). Neither did we observe an association of LTL-associated genetic variants with mortality in a prospective meta-analysis of multiple cohorts (n = 8165). Conclusions: We confirm LTL to be a marker of prospective mortality in middle and highly advanced age and additionally show that this association could not be explained by the association of LTL with various immune-related markers. Furthermore, the approaches performed here do not further support the hypothesis that LTL variation contributes to the genetic propensity for longevity.
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Affiliation(s)
- Joris Deelen
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Marian Beekman
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Veryan Codd
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Stella Trompet
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medica
| | - Linda Broer
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Sara Hägg
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Krista Fischer
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Peter E Thijssen
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - H Eka D Suchiman
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Iris Postmus
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - André G Uitterlinden
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medica
| | - Albert Hofman
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Anton J M de Craen
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Andres Metspalu
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Nancy L Pedersen
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Cornelia M van Duijn
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - J Wouter Jukema
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Jeanine J Houwing-Duistermaat
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Nilesh J Samani
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - P Eline Slagboom
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands, Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, Leiden, The Netherlands, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK, Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands and Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
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15
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Brooks-Wilson AR. Genetics of healthy aging and longevity. Hum Genet 2013; 132:1323-38. [PMID: 23925498 PMCID: PMC3898394 DOI: 10.1007/s00439-013-1342-z] [Citation(s) in RCA: 185] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2012] [Accepted: 07/15/2013] [Indexed: 12/17/2022]
Abstract
Longevity and healthy aging are among the most complex phenotypes studied to date. The heritability of age at death in adulthood is approximately 25 %. Studies of exceptionally long-lived individuals show that heritability is greatest at the oldest ages. Linkage studies of exceptionally long-lived families now support a longevity locus on chromosome 3; other putative longevity loci differ between studies. Candidate gene studies have identified variants at APOE and FOXO3A associated with longevity; other genes show inconsistent results. Genome-wide association scans (GWAS) of centenarians vs. younger controls reveal only APOE as achieving genome-wide significance (GWS); however, analyses of combinations of SNPs or genes represented among associations that do not reach GWS have identified pathways and signatures that converge upon genes and biological processes related to aging. The impact of these SNPs, which may exert joint effects, may be obscured by gene-environment interactions or inter-ethnic differences. GWAS and whole genome sequencing data both show that the risk alleles defined by GWAS of common complex diseases are, perhaps surprisingly, found in long-lived individuals, who may tolerate them by means of protective genetic factors. Such protective factors may ‘buffer’ the effects of specific risk alleles. Rare alleles are also likely to contribute to healthy aging and longevity. Epigenetics is quickly emerging as a critical aspect of aging and longevity. Centenarians delay age-related methylation changes, and they can pass this methylation preservation ability on to their offspring. Non-genetic factors, particularly lifestyle, clearly affect the development of age-related diseases and affect health and lifespan in the general population. To fully understand the desirable phenotypes of healthy aging and longevity, it will be necessary to examine whole genome data from large numbers of healthy long-lived individuals to look simultaneously at both common and rare alleles, with impeccable control for population stratification and consideration of non-genetic factors such as environment.
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Affiliation(s)
- Angela R Brooks-Wilson
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, V5Z 1L3, Canada,
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16
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Beekman M, Blanché H, Perola M, Hervonen A, Bezrukov V, Sikora E, Flachsbart F, Christiansen L, De Craen AJM, Kirkwood TBL, Rea IM, Poulain M, Robine JM, Valensin S, Stazi MA, Passarino G, Deiana L, Gonos ES, Paternoster L, Sørensen TIA, Tan Q, Helmer Q, van den Akker EB, Deelen J, Martella F, Cordell HJ, Ayers KL, Vaupel JW, Törnwall O, Johnson TE, Schreiber S, Lathrop M, Skytthe A, Westendorp RGJ, Christensen K, Gampe J, Nebel A, Houwing-Duistermaat JJ, Slagboom PE, Franceschi C. Genome-wide linkage analysis for human longevity: Genetics of Healthy Aging Study. Aging Cell 2013; 12:184-93. [PMID: 23286790 DOI: 10.1111/acel.12039] [Citation(s) in RCA: 118] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/27/2012] [Indexed: 01/04/2023] Open
Abstract
Clear evidence exists for heritability of human longevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome-wide linkage scan thus far reported. Linkage analyses included 2118 nonagenarian Caucasian sibling pairs that have been enrolled in 15 study centers of 11 European countries as part of the Genetics of Healthy Aging (GEHA) project. In the joint linkage analyses, we observed four regions that show linkage with longevity; chromosome 14q11.2 (LOD = 3.47), chromosome 17q12-q22 (LOD = 2.95), chromosome 19p13.3-p13.11 (LOD = 3.76), and chromosome 19q13.11-q13.32 (LOD = 3.57). To fine map these regions linked to longevity, we performed association analysis using GWAS data in a subgroup of 1228 unrelated nonagenarian and 1907 geographically matched controls. Using a fixed-effect meta-analysis approach, rs4420638 at the TOMM40/APOE/APOC1 gene locus showed significant association with longevity (P-value = 9.6 × 10(-8) ). By combined modeling of linkage and association, we showed that association of longevity with APOEε4 and APOEε2 alleles explain the linkage at 19q13.11-q13.32 with P-value = 0.02 and P-value = 1.0 × 10(-5) , respectively. In the largest linkage scan thus far performed for human familial longevity, we confirm that the APOE locus is a longevity gene and that additional longevity loci may be identified at 14q11.2, 17q12-q22, and 19p13.3-p13.11. As the latter linkage results are not explained by common variants, we suggest that rare variants play an important role in human familial longevity.
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Affiliation(s)
| | | | - Markus Perola
- The National Institute for Health and Welfare; THL; Helsinki; FI-00271; Finland
| | - Anti Hervonen
- Tampere School of Public Health; Tampere; FI-33014; Finland
| | | | - Ewa Sikora
- Nencki Istitute for Experimental Biology; NENCKI; Warszawa; 02-093; Poland
| | - Friederike Flachsbart
- Institute of Clinical Molecular Biology; Christian-Albrechts-University Kiel (CAU); Kiel; 24118; Germany
| | - Lene Christiansen
- Danish Aging Research Center; Institute of Public Health; University of Southern Denmark; Odense; DK-5230; Denmark
| | | | - Tom B. L. Kirkwood
- Institute for Ageing and Health; Newcastle University; UNEW; Newcastle; NE1 7RU; UK
| | - Irene Maeve Rea
- Queens University of Belfast; QUB; Belfast; Northern Ireland; BT7 1NN; UK
| | | | | | - Silvana Valensin
- Interdepartmental Centre “Luigi Galvani” CIG; University of Bologna UNIBO; Bologna; 40126; Italy
| | | | | | - Luca Deiana
- UNISS; University of Sassari; 07100; Sassari; Italy
| | | | | | | | | | - Quinta Helmer
- Medical Statistics and Bioinformatics; Leiden University Medical Centre; Leiden; ZC; 2333; The Netherlands
| | | | - Joris Deelen
- Molecular Epidemiology; Leiden University Medical Centre; Leiden; ZC; 2333; The Netherlands
| | | | - Heather J. Cordell
- Institute for Ageing and Health; Newcastle University; UNEW; Newcastle; NE1 7RU; UK
| | - Kristin L. Ayers
- Institute for Ageing and Health; Newcastle University; UNEW; Newcastle; NE1 7RU; UK
| | - James W. Vaupel
- Max Planck Institute for Demographic Research; MPIDR; 18057; Rostock; Germany
| | - Outi Törnwall
- The National Institute for Health and Welfare; THL; Helsinki; FI-00271; Finland
| | - Thomas E. Johnson
- Institute for Behavioral Genetics; University of Colorado at Boulder; Boulder; CO 80309-0447; USA
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology; Christian-Albrechts-University Kiel (CAU); Kiel; 24118; Germany
| | - Mark Lathrop
- Foundation Jean Dausset; CEPH; 75010; Paris; France
| | - Axel Skytthe
- Danish Aging Research Center; Institute of Public Health; University of Southern Denmark; Odense; DK-5230; Denmark
| | - Rudi G. J. Westendorp
- Gerontology and Geriatrics; Leiden University Medical Centre; Leiden; ZA; 2333; The Netherlands
| | | | - Jutta Gampe
- Max Planck Institute for Demographic Research; MPIDR; 18057; Rostock; Germany
| | - Almut Nebel
- Institute of Clinical Molecular Biology; Christian-Albrechts-University Kiel (CAU); Kiel; 24118; Germany
| | | | | | - Claudio Franceschi
- Interdepartmental Centre “Luigi Galvani” CIG; University of Bologna UNIBO; Bologna; 40126; Italy
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17
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Deelen J, Beekman M, Capri M, Franceschi C, Slagboom PE. Identifying the genomic determinants of aging and longevity in human population studies: progress and challenges. Bioessays 2013; 35:386-96. [PMID: 23423909 PMCID: PMC3633240 DOI: 10.1002/bies.201200148] [Citation(s) in RCA: 75] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Human lifespan variation is mainly determined by environmental factors, whereas the genetic contribution is 25–30% and expected to be polygenic. Two complementary fields go hand in hand in order to unravel the mechanisms of biological aging: genomic and biomarker research. Explorative and candidate gene studies of the human genome by genetic, transcriptomic, and epigenomic approaches have resulted in the identification of a limited number of interesting positive linkage regions, genes, and pathways that contribute to lifespan variation. The possibilities to further exploit these findings are rapidly increasing through the use of novel technologies, such as next-generation sequencing. Genomic research is progressively being integrated with biomarker studies on aging, including the application of (noninvasive) deep phenotyping and omics data – generated using novel technologies – in a wealth of studies in human populations. Hence, these studies may assist in obtaining a more holistic perspective on the role of the genome in aging and lifespan regulation.
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Affiliation(s)
- Joris Deelen
- Section of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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18
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Deelen J, Uh HW, Monajemi R, van Heemst D, Thijssen PE, Böhringer S, van den Akker EB, de Craen AJM, Rivadeneira F, Uitterlinden AG, Westendorp RGJ, Goeman JJ, Slagboom PE, Houwing-Duistermaat JJ, Beekman M. Gene set analysis of GWAS data for human longevity highlights the relevance of the insulin/IGF-1 signaling and telomere maintenance pathways. AGE (DORDRECHT, NETHERLANDS) 2013; 35:235-49. [PMID: 22113349 PMCID: PMC3543749 DOI: 10.1007/s11357-011-9340-3] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2011] [Accepted: 10/28/2011] [Indexed: 05/22/2023]
Abstract
In genome-wide association studies (GWAS) of complex traits, single SNP analysis is still the most applied approach. However, the identified SNPs have small effects and provide limited biological insight. A more appropriate approach to interpret GWAS data of complex traits is to analyze the combined effect of a SNP set grouped per pathway or gene region. We used this approach to study the joint effect on human longevity of genetic variation in two candidate pathways, the insulin/insulin-like growth factor (IGF-1) signaling (IIS) pathway and the telomere maintenance (TM) pathway. For the analyses, we used genotyped GWAS data of 403 unrelated nonagenarians from long-lived sibships collected in the Leiden Longevity Study and 1,670 younger population controls. We analyzed 1,021 SNPs in 68 IIS pathway genes and 88 SNPs in 13 TM pathway genes using four self-contained pathway tests (PLINK set-based test, Global test, GRASS and SNP ratio test). Although we observed small differences between the results of the different pathway tests, they showed consistent significant association of the IIS and TM pathway SNP sets with longevity. Analysis of gene SNP sets from these pathways indicates that the association of the IIS pathway is scattered over several genes (AKT1, AKT3, FOXO4, IGF2, INS, PIK3CA, SGK, SGK2, and YWHAG), while the association of the TM pathway seems to be mainly determined by one gene (POT1). In conclusion, this study shows that genetic variation in genes involved in the IIS and TM pathways is associated with human longevity.
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Affiliation(s)
- Joris Deelen
- Section of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
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19
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Microsomal triglyceride transfer protein gene -493G/T polymorphism and its association with serum lipid levels in Bama Zhuang long-living families in China. Lipids Health Dis 2012; 11:177. [PMID: 23273182 PMCID: PMC3554484 DOI: 10.1186/1476-511x-11-177] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2012] [Accepted: 12/26/2012] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The -493G/T polymorphism in the microsomal triglyceride transfer protein (MTP) gene is associated with lower serum low-density lipoprotein cholesterol (LDL-C) and triglyceride (TG) levels and longevity in several populations, but the results are inconsistent in different racial/ethnic groups. The current study was to investigate the plausible association of MTP -493G/T polymorphism with serum lipid levels and longevity in Zhuang long-lived families residing in Bama area, a famous home of longevity in Guangxi, China. METHODS The MTP -493G/T was genotyped by PCR-restriction fragment length polymorphism in 391 Bama Zhuang long-lived families (BLF, n = 1467, age 56.60 ± 29.43 years) and four control groups recruited from Bama and out-of-Bama area with or without a familial history of exceptional longevity: Bama non-long-lived families (BNLF, n = 586, age 44.81 ± 26.83 years), Bama non-Zhuang long-lived families (BNZLF, n = 444, age 52.09 ± 31.91 years), Pingguo long-lived families (PLF, n = 658, age 50.83 ± 30.30 years), and Pingguo non-long-lived families (PNLF, n = 539, age 38.74 ± 24.69 years). Correlation analyses between genotypes and serum lipid levels and longevity were then performed. RESULTS No particularly favorable lipoprotein and clinical phenotypes were seen in BLF as compared to general families in the same area. Instead, the levels of total cholesterol (TC), TG, LDL-C, and the prevalence of dyslipidemia were significantly higher in the three Bama families as compared to the two non-Bama families (P < 0.01 for all). There were no differences in the allelic and genotypic frequencies among the tested cohorts (P > 0.05 for all), but the TT genotype tended to enrich in the three long-lived cohorts from both areas. In addition, the individuals harboring TT genotype exhibited lower LDL-C and TC levels in the overall populations and Bama populations with a region- and sex-specific pattern. Multiple linear regression analyses unraveled that LDL-C levels were correlated with genotypes in Bama combined population, BNLF, and the total population (P < 0.05 for each) but not in Pingguo populations; TC and HDL-C levels were correlated with genotypes in Bama combined population and BLF, respectively (P < 0.05 for each). CONCLUSIONS MTP -493G/T polymorphism may play an important role in fashioning the serum lipid profiles of Bama populations, despite no direct association between MTP -493G/T and longevity was detected.
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20
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Ferrario A, Villa F, Malovini A, Araniti F, Puca AA. The application of genetics approaches to the study of exceptional longevity in humans: potential and limitations. IMMUNITY & AGEING 2012; 9:7. [PMID: 22524405 PMCID: PMC3407776 DOI: 10.1186/1742-4933-9-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2012] [Accepted: 04/23/2012] [Indexed: 01/08/2023]
Abstract
The average life-span of the population of industrialized countries has improved enormously over the last decades. Despite evidence pointing to the role of food intake in modulating life-span, exceptional longevity is still considered primarily an inheritable trait, as pointed out by the description of families with centenarian clusters and by the elevated relative probability of siblings of centenarians to become centenarians themselves. However, rather than being two separate concepts, the genetic origin of exceptional longevity and the more recently observed environment-driven increase in the average age of the population could possibly be explained by the same genetic variants and environmentally modulated mechanisms (caloric restriction, specific nutrients). In support of this hypothesis, polymorphisms selected for in the centenarian population as a consequence of demographic pressure have been found to modulate cellular signals controlled also by caloric restriction. Here, we give an overview of the recent findings in the field of the genetics of human exceptional longevity, of how some of the identified polymorphisms modulate signals also influenced by food intake and caloric restriction, of what in our view have been the limitations of the approaches used over the past years to study genetics (sib-pair-, candidate gene association-, and genome-wide association-studies), and briefly of the limitations and the potential of the new, high-throughput, next-generation sequencing techniques applied to exceptional longevity.
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Affiliation(s)
- Anna Ferrario
- IRCCS Multimedica, Via Fantoli 16/15, 20138, Milan, Italy.
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21
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Huffman DM, Deelen J, Ye K, Bergman A, Slagboom EP, Barzilai N, Atzmon G. Distinguishing between longevity and buffered-deleterious genotypes for exceptional human longevity: the case of the MTP gene. J Gerontol A Biol Sci Med Sci 2012; 67:1153-60. [PMID: 22496539 DOI: 10.1093/gerona/gls103] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The single nucleotide polymorphism, rs2866164, in the MTP gene, has been associated with human longevity but has not been validated by subsequent longevity studies. Using our population of Ashkenazi Jews, we find that the MTP CC genotype is significantly overrepresented in centenarians and their offspring, as compared with controls (p < .05). However, when we examined MTP CC genotype frequency pattern with aging, we observed a monotonic decline between ages 55-85 years followed by a dramatic enrichment after age 90 years, forming a U-shape pattern (p < .05). Furthermore, the MTP CC genotype was buffered by three validated longevity genotypes (p < .05). This buffering effect was found to confer an enrichment of the MTP CC genotype in centenarians, whereas their absence in CC controls resulted in poorer survivorship (p < .05). Thus, we conclude that MTP CC is a buffered-deleterious genotype and that assessing genotype frequency across aging is essential for discerning longevity from buffered-deleterious genotypes.
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Affiliation(s)
- Derek M Huffman
- Department of Medicine, The Albert Einstein College of Medicine of Yeshiva University, New York, NY, USA
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22
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Design, recruitment, logistics, and data management of the GEHA (Genetics of Healthy Ageing) project. Exp Gerontol 2011; 46:934-45. [PMID: 21871552 DOI: 10.1016/j.exger.2011.08.005] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2010] [Revised: 07/09/2011] [Accepted: 08/10/2011] [Indexed: 11/21/2022]
Abstract
In 2004, the integrated European project GEHA (Genetics of Healthy Ageing) was initiated with the aim of identifying genes involved in healthy ageing and longevity. The first step in the project was the recruitment of more than 2500 pairs of siblings aged 90 years or more together with one younger control person from 15 areas in 11 European countries through a coordinated and standardised effort. A biological sample, preferably a blood sample, was collected from each participant, and basic physical and cognitive measures were obtained together with information about health, life style, and family composition. From 2004 to 2008 a total of 2535 families comprising 5319 nonagenarian siblings were identified and included in the project. In addition, 2548 younger control persons aged 50-75 years were recruited. A total of 2249 complete trios with blood samples from at least two old siblings and the younger control were formed and are available for genetic analyses (e.g. linkage studies and genome-wide association studies). Mortality follow-up improves the possibility of identifying families with the most extreme longevity phenotypes. With a mean follow-up time of 3.7 years the number of families with all participating siblings aged 95 years or more has increased by a factor of 5 to 750 families compared to when interviews were conducted. Thus, the GEHA project represents a unique source in the search for genes related to healthy ageing and longevity.
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23
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Deelen J, Beekman M, Uh HW, Helmer Q, Kuningas M, Christiansen L, Kremer D, van der Breggen R, Suchiman HED, Lakenberg N, van den Akker EB, Passtoors WM, Tiemeier H, van Heemst D, de Craen AJ, Rivadeneira F, de Geus EJ, Perola M, van der Ouderaa FJ, Gunn DA, Boomsma DI, Uitterlinden AG, Christensen K, van Duijn CM, Heijmans BT, Houwing-Duistermaat JJ, Westendorp RGJ, Slagboom PE. Genome-wide association study identifies a single major locus contributing to survival into old age; the APOE locus revisited. Aging Cell 2011; 10:686-98. [PMID: 21418511 PMCID: PMC3193372 DOI: 10.1111/j.1474-9726.2011.00705.x] [Citation(s) in RCA: 208] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
By studying the loci that contribute to human longevity, we aim to identify mechanisms that contribute to healthy aging. To identify such loci, we performed a genome-wide association study (GWAS) comparing 403 unrelated nonagenarians from long-living families included in the Leiden Longevity Study (LLS) and 1670 younger population controls. The strongest candidate SNPs from this GWAS have been analyzed in a meta-analysis of nonagenarian cases from the Rotterdam Study, Leiden 85-plus study, and Danish 1905 cohort. Only one of the 62 prioritized SNPs from the GWAS analysis (P < 1 × 10−4) showed genome-wide significance with survival into old age in the meta-analysis of 4149 nonagenarian cases and 7582 younger controls [OR = 0.71 (95% CI 0.65–0.77), P = 3.39 × 10−17]. This SNP, rs2075650, is located in TOMM40 at chromosome 19q13.32 close to the apolipoprotein E (APOE) gene. Although there was only moderate linkage disequilibrium between rs2075650 and the ApoE ε4 defining SNP rs429358, we could not find an APOE-independent effect of rs2075650 on longevity, either in cross-sectional or in longitudinal analyses. As expected, rs429358 associated with metabolic phenotypes in the offspring of the nonagenarian cases from the LLS and their partners. In addition, we observed a novel association between this locus and serum levels of IGF-1 in women (P = 0.005). In conclusion, the major locus determining familial longevity up to high age as detected by GWAS was marked by rs2075650, which tags the deleterious effects of the ApoE ε4 allele. No other major longevity locus was found.
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Affiliation(s)
- Joris Deelen
- Section of Molecular Epidemiology, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - Marian Beekman
- Section of Molecular Epidemiology, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - Hae-Won Uh
- Section of Medical Statistics, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - Quinta Helmer
- Section of Medical Statistics, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - Maris Kuningas
- Department of Epidemiology, Erasmus Medical CenterPO Box 2040, 3015 CE Rotterdam, The Netherlands
| | - Lene Christiansen
- Department of Epidemiology, University of Southern DenmarkJ.B. Winsløws Vej 9, DK-5000 Odense C, Denmark
- The Danish Aging Research Center, Institute of Public Health-EpidemiologyJ.B. Winsløws Vej 9 B, st. tv, DK-5000 Odense C, Denmark
- Department of Clinical Genetics and Department of Clinical Biochemistry and Pharmacology, Odense University HospitalDK-5000 Odense C, Denmark
| | - Dennis Kremer
- Section of Molecular Epidemiology, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - Ruud van der Breggen
- Section of Molecular Epidemiology, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - H Eka D Suchiman
- Section of Molecular Epidemiology, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - Nico Lakenberg
- Section of Molecular Epidemiology, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - Erik B van den Akker
- Section of Molecular Epidemiology, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
- Department of Mediamatics, Delft Bioinformatics Lab, Delft University of TechnologyPO Box 5031, 2600 GA Delft, The Netherlands
| | - Willemijn M Passtoors
- Section of Molecular Epidemiology, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus Medical CenterPO Box 2040, 3015 CE Rotterdam, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center and Sophia Children's HospitalPO Box 2040, 3015 CE Rotterdam, The Netherlands
| | - Diana van Heemst
- Department of Gerontology and Geriatrics, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - Anton J de Craen
- Department of Gerontology and Geriatrics, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical CenterPO Box 2040, 3015 CE Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical CenterPO Box 2040, 3015 CE Rotterdam, The Netherlands
| | - Eco J de Geus
- Department of Biological Psychology, VU University AmsterdamVan der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
| | - Markus Perola
- National Institute for Health and WelfarePO Box 30, 00271 Helsinki, Finland
| | - Frans J van der Ouderaa
- Netherlands Consortium for Healthy Ageing, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
- Department of Gerontology and Geriatrics, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - David A Gunn
- Unilever DiscoverColworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University AmsterdamVan der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
| | - André G Uitterlinden
- Netherlands Consortium for Healthy Ageing, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
- Department of Epidemiology, Erasmus Medical CenterPO Box 2040, 3015 CE Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical CenterPO Box 2040, 3015 CE Rotterdam, The Netherlands
| | - Kaare Christensen
- The Danish Aging Research Center, Institute of Public Health-EpidemiologyJ.B. Winsløws Vej 9 B, st. tv, DK-5000 Odense C, Denmark
- Department of Clinical Genetics and Department of Clinical Biochemistry and Pharmacology, Odense University HospitalDK-5000 Odense C, Denmark
| | - Cornelia M van Duijn
- Netherlands Consortium for Healthy Ageing, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
- Department of Epidemiology, Erasmus Medical CenterPO Box 2040, 3015 CE Rotterdam, The Netherlands
| | - Bastiaan T Heijmans
- Section of Molecular Epidemiology, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | | | - Rudi G J Westendorp
- Netherlands Consortium for Healthy Ageing, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
- Department of Gerontology and Geriatrics, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
| | - P Eline Slagboom
- Section of Molecular Epidemiology, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden University Medical CenterPO Box 9600, 2300 RC Leiden, The Netherlands
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Slagboom PE, Beekman M, Passtoors WM, Deelen J, Vaarhorst AAM, Boer JM, van den Akker EB, van Heemst D, de Craen AJM, Maier AB, Rozing M, Mooijaart SP, Heijmans BT, Westendorp RGJ. Genomics of human longevity. Philos Trans R Soc Lond B Biol Sci 2011; 366:35-42. [PMID: 21115528 PMCID: PMC3001312 DOI: 10.1098/rstb.2010.0284] [Citation(s) in RCA: 60] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
In animal models, single-gene mutations in genes involved in insulin/IGF and target of rapamycin signalling pathways extend lifespan to a considerable extent. The genetic, genomic and epigenetic influences on human longevity are expected to be much more complex. Strikingly however, beneficial metabolic and cellular features of long-lived families resemble those in animals for whom the lifespan is extended by applying genetic manipulation and, especially, dietary restriction. Candidate gene studies in humans support the notion that human orthologues from longevity genes identified in lower species do contribute to longevity but that the influence of the genetic variants involved is small. Here we discuss how an integration of novel study designs, labour-intensive biobanking, deep phenotyping and genomic research may provide insights into the mechanisms that drive human longevity and healthy ageing, beyond the associations usually provided by molecular and genetic epidemiology. Although prospective studies of humans from the cradle to the grave have never been performed, it is feasible to extract life histories from different cohorts jointly covering the molecular changes that occur with age from early development all the way up to the age at death. By the integration of research in different study cohorts, and with research in animal models, biological research into human longevity is thus making considerable progress.
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Affiliation(s)
- P E Slagboom
- Section of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
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Soerensen M, Dato S, Christensen K, McGue M, Stevnsner T, Bohr VA, Christiansen L. Replication of an association of variation in the FOXO3A gene with human longevity using both case-control and longitudinal data. Aging Cell 2010; 9:1010-7. [PMID: 20849522 DOI: 10.1111/j.1474-9726.2010.00627.x] [Citation(s) in RCA: 139] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Genetic variation in FOXO3A has previously been associated with human longevity. Studies published so far have been case-control studies and hence vulnerable to bias introduced by cohort effects. In this study we extended the previous findings in the cohorts of oldest old Danes (the Danish 1905 cohort, N=1089) and middle-aged Danes (N=736), applying a longitudinal study design as well as the case-control study design. Fifteen SNPs were chosen in order to cover the known common variation in FOXO3A. Comparing SNP frequencies in the oldest old with middle-aged individuals, we found association (after correction for multiple testing) of eight SNPs; 4 (rs13217795, rs2764264, rs479744, and rs9400239) previously reported to be associated with longevity and four novel SNPs (rs12206094, rs13220810, rs7762395, and rs9486902 (corrected P-values 0.001-0.044). Moreover, we found association of the haplotypes TAC and CAC of rs9486902, rs10499051, and rs12206094 (corrected P-values: 0.01-0.03) with longevity. Finally, we here present data applying a longitudinal study design; when using follow-up survival data on the oldest old in a longitudinal analysis, we found no SNPs to remain significant after the correction for multiple testing (Bonferroni correction). Hence, our results support and extent the proposed role of FOXO3A as a candidate longevity gene for survival from younger ages to old age, yet not during old age.
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Affiliation(s)
- Mette Soerensen
- The Danish Aging Research Center, Epidemiology, Institute of Public Health, University of Southern Denmark, Odense C, Denmark.
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Boyden SE, Kunkel LM. High-density genomewide linkage analysis of exceptional human longevity identifies multiple novel loci. PLoS One 2010; 5:e12432. [PMID: 20824210 PMCID: PMC2930849 DOI: 10.1371/journal.pone.0012432] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2010] [Accepted: 08/04/2010] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Human lifespan is approximately 25% heritable, and genetic factors may be particularly important for achieving exceptional longevity. Accordingly, siblings of centenarians have a dramatically higher probability of reaching extreme old age than the general population. METHODOLOGY/PRINCIPAL FINDINGS To map the loci conferring a survival advantage, we performed the second genomewide linkage scan on human longevity and the first using a high-density marker panel of single nucleotide polymorphisms. By systematically testing a range of minimum age cutoffs in 279 families with multiple long-lived siblings, we identified a locus on chromosome 3p24-22 with a genomewide significant allele-sharing LOD score of 4.02 (empirical P = 0.037) and a locus on chromosome 9q31-34 with a highly suggestive LOD score of 3.89 (empirical P = 0.054). The empirical P value for the combined result was 0.002. A third novel locus with a LOD score of 4.05 on chromosome 12q24 was detected in a subset of the data, and we also obtained modest evidence for a previously reported interval on chromosome 4q22-25. CONCLUSIONS/SIGNIFICANCE Our linkage data should facilitate the discovery of both common and rare variants that determine genetic variability in lifespan.
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Affiliation(s)
- Steven E. Boyden
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
- Program in Genomics, Division of Genetics, and The Manton Center for Orphan Disease Research, Children's Hospital Boston, Boston, Massachusetts, United States of America
| | - Louis M. Kunkel
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
- Program in Genomics, Division of Genetics, and The Manton Center for Orphan Disease Research, Children's Hospital Boston, Boston, Massachusetts, United States of America
- Howard Hughes Medical Institute, Children's Hospital Boston, Boston, Massachusetts, United States of America
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Callegaro A, van Houwelingen JC, Houwing-Duistermaat JJ. Robust age at onset linkage analysis in nuclear families. Hum Hered 2009; 69:80-90. [PMID: 19996606 DOI: 10.1159/000264446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2009] [Accepted: 07/13/2009] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE Standard methods for linkage analysis ignore the phenotype of the parents when they are not genotyped. However, this information can be useful for gene mapping. In this paper we propose methods for age at onset genetic linkage analysis in sibling pairs, taking into account parental age at onset. METHODS Two new score statistics are derived, one from an additive gamma frailty model and one from a log-normal frailty model. The score statistics are classical non-parametric linkage (NPL) statistics weighted by a function of the age at onset of the four family members. The weight depends on information from registries (age-specific incidences) and family studies (sib-sib and father-mother correlation). RESULTS In order to investigate how age at onset of sibs and their parents affect the information for linkage analysis the weight functions were studied for rare and common disease models, realistic models for breast cancer and human lifespan. We studied the performance of the weighted NPL methods by simulations. As illustration, the score statistics were applied to the GAW12 data. The results show that it is useful to include parental age at onset information in genetic linkage analysis.
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Affiliation(s)
- Andrea Callegaro
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, University of Leiden, Leiden, The Netherlands.
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Li Y, Wang WJ, Cao H, Lu J, Wu C, Hu FY, Guo J, Zhao L, Yang F, Zhang YX, Li W, Zheng GY, Cui H, Chen X, Zhu Z, He H, Dong B, Mo X, Zeng Y, Tian XL. Genetic association of FOXO1A and FOXO3A with longevity trait in Han Chinese populations. Hum Mol Genet 2009; 18:4897-904. [PMID: 19793722 DOI: 10.1093/hmg/ddp459] [Citation(s) in RCA: 222] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
FOXO1A and FOXO3A are two members of the FoxO family. FOXO3A has recently been linked to human longevity in Japanese, German and Italian populations. Here we tested the genetic contribution of FOXO1A and FOXO3A to the longevity phenotype in Han Chinese population. Six tagging SNPs from FOXO1A and FOXO3A were selected and genotyped in 1817 centenarians and younger individuals. Two SNPs of FOXO1A were found to be associated with longevity in women (P = 0.01-0.005), whereas all three SNPs of FOXO3A were associated with longevity in both genders (P = 0.005-0.001). One SNP from FOXO1A was found not to be associated with longevity. In haplotype association tests, the OR (95% CI) for haplotypes TTG and CCG of FOXO1A in association with female longevity were 0.72 (0.58-0.90) and 1.38 (1.08-1.76), P = 0.0033 and 0.0063, respectively. The haplotypes of FOXO3A were associated with longevity in men [GTC: OR (95% CI) = 0.67 (0.51-0.86), P = 0.0014; CGT: OR (95% CI) = 1.48 (1.12-1.94), P = 0.0035] and in women [GTC: OR (95% CI) = 0.75 (0.60-0.94), P = 0.0094; CGT: OR (95% CI) = 1.47 (1.16-1.86), P = 0.0009]. The haplotype association tests were validated by permutation analysis. The association of FOXO1A with female longevity was replicated in 700 centenarians and younger individuals that were sampled geographically different from the original population. Thus, we demonstrate that, unlike FOXO3A, FOXO1A is more closely associated with human female longevity, suggesting that the genetic contribution to longevity trait may be affected by genders.
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Affiliation(s)
- Yang Li
- Department of Human Population Genetics, Institute of Molecular Medicine, Peking University, Beijing, China
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Gene variants as determinants of longevity: focus on the inflammatory factors. Pflugers Arch 2009; 459:239-46. [DOI: 10.1007/s00424-009-0726-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2009] [Accepted: 08/26/2009] [Indexed: 01/01/2023]
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Fraga MF. Genetic and epigenetic regulation of aging. Curr Opin Immunol 2009; 21:446-53. [PMID: 19500963 DOI: 10.1016/j.coi.2009.04.003] [Citation(s) in RCA: 78] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2009] [Revised: 04/24/2009] [Accepted: 04/28/2009] [Indexed: 10/20/2022]
Abstract
Many age-associated conditions, such as the decrease in regenerative capacity of tissues, appear to be determined by a decline in the function of specific somatic stem cells. Although it is obvious that the genotype determines the average lifespan of different species, the variation in lifespan of individuals within a species seems to be more affected by the accumulation over time of molecular errors that compromise adult stem cell function. These molecular alterations can occur at both the genetic and epigenetic levels and depend on hereditary, environmental, and stochastic factors. This complex multifactorial mixture determines characteristics, such as longevity and a healthy life, that are central concerns of human existence.
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Affiliation(s)
- Mario F Fraga
- Department of Immunology and Oncology, National Center for Biotechnology, CNB-CSIC, Cantoblanco, Madrid, Spain.
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Abstract
We investigated the hypothesis that gene expression profiles in cultured cell lines from adults, aged 57–97 years, contain information about the biological age and potential longevity of the donors. We studied 104 unrelated grandparents from 31 Utah CEU (Centre d’Etude du Polymorphisme Humain – Utah) families, for whom lymphoblastoid cell lines were established in the 1980s. Combining publicly available gene expression data from these cell lines, and survival data from the Utah Population Database, we tested the relationship between expression of 2151 always-expressed genes, age, and survival of the donors. Approximately 16% of 2151 expression levels were associated with donor age: 10% decreased in expression with age, and 6% increased with age. Cell division cycle 42 (CDC42) and CORO1A exhibited strong associations both with age at draw and survival after draw (multiple comparisons-adjusted Monte Carlo P-value < 0.05). In general, gene expressions that increased with age were associated with increased mortality. Gene expressions that decreased with age were generally associated with reduced mortality. A multivariate estimate of biological age modeled from expression data was dominated by CDC42 expression, and was a significant predictor of survival after blood draw. A multivariate model of survival as a function of gene expression was dominated by CORO1A expression. This model accounted for approximately 23% of the variation in survival among the CEU grandparents. Some expression levels were negligibly associated with age in this cross-sectional dataset, but strongly associated with inter-individual differences in survival. These observations may lead to new insights regarding the genetic contribution to exceptional longevity.
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Affiliation(s)
- Richard A Kerber
- Department of Oncological Sciences, 2000 Circle of Hope, Salt Lake City, UT 84112-5550, USA.
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Houwing-Duistermaat JJ, Callegaro A, Beekman M, Westendorp RG, Slagboom PE, van Houwelingen JC. Weighted statistics for aggregation and linkage analysis of human longevity in selected families: the Leiden Longevity Study. Stat Med 2009; 28:140-51. [PMID: 18759372 DOI: 10.1002/sim.3421] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Typically long-lived sibling pairs have been collected for linkage analysis of human longevity and information on life span of first-degree relatives is available to assess familial aggregation of life span. We propose a new weighted statistic for aggregation analysis, which tests for a relationship between a family history of excessive survival of the sibships of the long-lived pairs and the survival of their parents and their offspring. For linkage analysis, we derive a new weighted score statistic from a simple gamma frailty model, which assigns more weight to excessive long-lived pairs. We apply the methods to data from the Leiden Longevity Study, which consists of sibling pairs of age 90 years or above and their first-degree relatives. The pairs have been genotyped for microsatellite markers in a candidate region. Association was present between survival within the sibships and survival of the offspring, but not with the parental generation. For linkage analysis, weighting increased the value of the test statistic, but the result was not statistically significant. About the methods we conclude that the statistic for aggregation provides insight into clustering of life span and the statistic for linkage provides a new tool to include demographic information into the analysis.
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Affiliation(s)
- J J Houwing-Duistermaat
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Postzone S-5-P, P.O. Box 9600, Leiden, The Netherlands.
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Abstract
Over the last two decades, aging research has expanded to include not only age-related disease models, and conversely, longevity and disease-free models, but also focuses on biological mechanisms related to the aging process. By viewing aging on multiple research frontiers, we are rapidly expanding knowledge as a whole and mapping connections between biological processes and particular age-related diseases that emerge. This is perhaps most true in the field of genetics, where variation across individuals has improved our understanding of aging mechanisms, etiology of age-related disease, and prediction of therapeutic responses. A close partnership between gerontologists, epidemiologists, and geneticists is needed to take full advantage of emerging genome information and technology and bring about a new age for biological aging research. Here we review current genetic findings for aging across both disease-specific and aging process domains. We then highlight the limitations of most work to date in terms of study design, genomic information, and trait modeling and focus on emerging technology and future directions that can partner genetic epidemiology and aging research fields to best take advantage of the rapid discoveries in each.
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Affiliation(s)
- M Daniele Fallin
- Department of Epidemiology, Bloomberg School of Public Health, Baltimore, MD 21205, USA.
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Cevenini E, Invidia L, Lescai F, Salvioli S, Tieri P, Castellani G, Franceschi C. Human models of aging and longevity. Expert Opin Biol Ther 2008; 8:1393-405. [PMID: 18694357 DOI: 10.1517/14712598.8.9.1393] [Citation(s) in RCA: 101] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
BACKGROUND The aging phenotype in humans is very heterogeneous and can be described as a complex mosaic resulting from the interaction of a variety of environmental, stochastic and genetic-epigenetic variables. Therefore, each old person must be considered as a singleton, and consequently the definition of 'aging phenotype' is very difficult. OBJECTIVE We discuss the phenotype of centenarians, the best example of successful aging, as well as other models exploited to study human aging and longevity, such as families enriched in long-living subjects, twins and cohorts of unrelated subjects. METHODS A critical review of literature available until March 2008. CONCLUSIONS No single model can be considered the gold standard for the study of aging and longevity, instead the combination of results obtained from different models must be considered in order to better understand these complex phenomena. We propose that a systems biology concept such as that of 'bow-tie' architecture, useful for managing information flow, could help in this demanding task.
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Affiliation(s)
- E Cevenini
- University of Bologna, Department of Experimental Pathology, Via S. Giacomo 12, 40126 Bologna, Italy
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Molecular epidemiology, candidate genes versus genome-wide scans. GENES AND NUTRITION 2008; 2:27-9. [PMID: 18850134 DOI: 10.1007/s12263-007-0002-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Abstract
Recent discoveries in the science of ageing indicate that lifespan in model organisms such as yeast, nematodes, flies and mice is plastic and can be manipulated by genetic, nutritional or pharmacological intervention. A better understanding of the targets of such interventions, as well as the proximate causes of ageing-related degeneration and disease, is essential before we can evaluate if abrogation of human senescence is a realistic prospect.
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Schgoer W, Eller P, Mueller T, Tancevski I, Wehinger A, Ulmer H, Sandhofer A, Ritsch A, Haltmayer M, Patsch JR. The MTP -493TT genotype is associated with peripheral arterial disease: results from the Linz Peripheral Arterial Disease (LIPAD) Study. Clin Biochem 2008; 41:712-6. [PMID: 18325332 DOI: 10.1016/j.clinbiochem.2008.02.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2007] [Revised: 02/12/2008] [Accepted: 02/13/2008] [Indexed: 11/16/2022]
Abstract
OBJECTIVES Microsomal triglyceride transfer protein (MTP) transfers lipids into apoprotein B-containing lipoproteins for secretion from liver, intestine, and heart. We hypothesized the -493T single nucleotide polymorphism in the MTP promoter region to be associated with altered lipoprotein levels and with presence of peripheral arterial disease (PAD). DESIGN AND METHODS 433 patients with symptomatic PAD and 433 controls matched for sex and age from the Linz Peripheral Arterial Disease (LIPAD) study were genotyped cross-sectionally for the -493T single nucleotide polymorphism in the promoter region of the MTP gene. RESULTS The frequency of the -493T allele in patients with PAD was 0.320, whereas it was 0.255 in controls (p<0.001). The MTP -493TT genotype was independently associated with PAD, even after adjustment for LDL cholesterol. The odds ratio of the -493TT MTP genotype for PAD was 3.18 (95% CI, 1.76-5.71) when adjusted for current smoking, arterial hypertension, LDL cholesterol, triglycerides, glycohemoglobin, C-reactive protein, and homocysteine. Furthermore, we found an association between the MTP promoter polymorphism and the apolipoprotein B-containing lipoproteins total-cholesterol (p=0.011), LDL cholesterol (p=0.002) and apolipoprotein B (p=0.034). CONCLUSIONS Our results provide preliminary evidence for a potential role of the MTP -493TT genotype in the pathogenesis of PAD.
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Affiliation(s)
- Wilfried Schgoer
- Department of Internal Medicine, Medical University Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria.
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Novelli V, Viviani Anselmi C, Roncarati R, Guffanti G, Malovini A, Piluso G, Puca AA. Lack of replication of genetic associations with human longevity. Biogerontology 2007; 9:85-92. [DOI: 10.1007/s10522-007-9116-4] [Citation(s) in RCA: 52] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2007] [Accepted: 11/04/2007] [Indexed: 10/22/2022]
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Lunetta KL, D'Agostino RB, Karasik D, Benjamin EJ, Guo CY, Govindaraju R, Kiel DP, Kelly-Hayes M, Massaro JM, Pencina MJ, Seshadri S, Murabito JM. Genetic correlates of longevity and selected age-related phenotypes: a genome-wide association study in the Framingham Study. BMC MEDICAL GENETICS 2007; 8 Suppl 1:S13. [PMID: 17903295 PMCID: PMC1995604 DOI: 10.1186/1471-2350-8-s1-s13] [Citation(s) in RCA: 159] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
BACKGROUND Family studies and heritability estimates provide evidence for a genetic contribution to variation in the human life span. METHODS We conducted a genome wide association study (Affymetrix 100K SNP GeneChip) for longevity-related traits in a community-based sample. We report on 5 longevity and aging traits in up to 1345 Framingham Study participants from 330 families. Multivariable-adjusted residuals were computed using appropriate models (Cox proportional hazards, logistic, or linear regression) and the residuals from these models were used to test for association with qualifying SNPs (70, 987 autosomal SNPs with genotypic call rate > or =80%, minor allele frequency > or =10%, Hardy-Weinberg test p > or = 0.001). RESULTS In family-based association test (FBAT) models, 8 SNPs in two regions approximately 500 kb apart on chromosome 1 (physical positions 73,091,610 and 73, 527,652) were associated with age at death (p-value < 10(-5)). The two sets of SNPs were in high linkage disequilibrium (minimum r2 = 0.58). The top 30 SNPs for generalized estimating equation (GEE) tests of association with age at death included rs10507486 (p = 0.0001) and rs4943794 (p = 0.0002), SNPs intronic to FOXO1A, a gene implicated in lifespan extension in animal models. FBAT models identified 7 SNPs and GEE models identified 9 SNPs associated with both age at death and morbidity-free survival at age 65 including rs2374983 near PON1. In the analysis of selected candidate genes, SNP associations (FBAT or GEE p-value < 0.01) were identified for age at death in or near the following genes: FOXO1A, GAPDH, KL, LEPR, PON1, PSEN1, SOD2, and WRN. Top ranked SNP associations in the GEE model for age at natural menopause included rs6910534 (p = 0.00003) near FOXO3a and rs3751591 (p = 0.00006) in CYP19A1. Results of all longevity phenotype-genotype associations for all autosomal SNPs are web posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite. CONCLUSION Longevity and aging traits are associated with SNPs on the Affymetrix 100K GeneChip. None of the associations achieved genome-wide significance. These data generate hypotheses and serve as a resource for replication as more genes and biologic pathways are proposed as contributing to longevity and healthy aging.
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Affiliation(s)
- Kathryn L Lunetta
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Ralph B D'Agostino
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Statistics and Consulting Unit, Department of Mathematics, Boston University, Boston, MA, USA
| | - David Karasik
- Hebrew Senior Life Institute for Aging Research and Harvard Medical School, Boston, MA, USA
| | - Emelia J Benjamin
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine and the Departments of Neurology, Cardiology, and Preventive Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Chao-Yu Guo
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine and the Departments of Neurology, Cardiology, and Preventive Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Raju Govindaraju
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine and the Departments of Neurology, Cardiology, and Preventive Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Douglas P Kiel
- Hebrew Senior Life Institute for Aging Research and Harvard Medical School, Boston, MA, USA
| | - Margaret Kelly-Hayes
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine and the Departments of Neurology, Cardiology, and Preventive Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Joseph M Massaro
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Statistics and Consulting Unit, Department of Mathematics, Boston University, Boston, MA, USA
| | - Michael J Pencina
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Statistics and Consulting Unit, Department of Mathematics, Boston University, Boston, MA, USA
| | - Sudha Seshadri
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine and the Departments of Neurology, Cardiology, and Preventive Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Joanne M Murabito
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine and the Departments of Neurology, Cardiology, and Preventive Medicine, Boston University School of Medicine, Boston, MA, USA
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Martin GM, Bergman A, Barzilai N. Genetic determinants of human health span and life span: progress and new opportunities. PLoS Genet 2007; 3:e125. [PMID: 17677003 PMCID: PMC1934400 DOI: 10.1371/journal.pgen.0030125] [Citation(s) in RCA: 87] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
We review three approaches to the genetic analysis of the biology and pathobiology of human aging. The first and so far the best-developed is the search for the biochemical genetic basis of varying susceptibilities to major geriatric disorders. These include a range of progeroid syndromes. Collectively, they tell us much about the genetics of health span. Given that the major risk factor for virtually all geriatric disorders is biological aging, they may also serve as markers for the study of intrinsic biological aging. The second approach seeks to identify allelic contributions to exceptionally long life spans. While linkage to a locus on Chromosome 4 has not been confirmed, association studies have revealed a number of significant polymorphisms that impact upon late-life diseases and life span. The third approach remains theoretical. It would require longitudinal studies of large numbers of middle-aged sib-pairs who are extremely discordant or concordant for their rates of decline in various physiological functions. We can conclude that there are great opportunities for research on the genetics of human aging, particularly given the huge fund of information on human biology and pathobiology, and the rapidly developing knowledge of the human genome.
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Affiliation(s)
- George M Martin
- Department of Pathology, University of Washington, Seattle, Washington, United States of America.
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Franceschi C, Bezrukov V, Blanché H, Bolund L, Christensen K, de Benedictis G, Deiana L, Gonos E, Hervonen A, Yang H, Jeune B, Kirkwood TBL, Kristensen P, Leon A, Pelicci PG, Peltonen L, Poulain M, Rea IM, Remacle J, Robine JM, Schreiber S, Sikora E, Slagboom PE, Spazzafumo L, Stazi MA, Toussaint O, Vaupel JW. Genetics of healthy aging in Europe: the EU-integrated project GEHA (GEnetics of Healthy Aging). Ann N Y Acad Sci 2007; 1100:21-45. [PMID: 17460163 DOI: 10.1196/annals.1395.003] [Citation(s) in RCA: 77] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The aim of the 5-year European Union (EU)-Integrated Project GEnetics of Healthy Aging (GEHA), constituted by 25 partners (24 from Europe plus the Beijing Genomics Institute from China), is to identify genes involved in healthy aging and longevity, which allow individuals to survive to advanced old age in good cognitive and physical function and in the absence of major age-related diseases. To achieve this aim a coherent, tightly integrated program of research that unites demographers, geriatricians, geneticists, genetic epidemiologists, molecular biologists, bioinfomaticians, and statisticians has been set up. The working plan is to: (a) collect DNA and information on the health status from an unprecedented number of long-lived 90+ sibpairs (n = 2650) and of younger ethnically matched controls (n = 2650) from 11 European countries; (b) perform a genome-wide linkage scannning in all the sibpairs (a total of 5300 individuals); this investigation will be followed by linkage disequilibrium mapping (LD mapping) of the candidate chromosomal regions; (c) study in cases (i.e., the 2650 probands of the sibpairs) and controls (2650 younger people), genomic regions (chromosome 4, D4S1564, chromosome 11, 11.p15.5) which were identified in previous studies as possible candidates to harbor longevity genes; (d) genotype all recruited subjects for apoE polymorphisms; and (e) genotype all recruited subjects for inherited as well as epigenetic variability of the mitochondrial DNA (mtDNA). The genetic analysis will be performed by 9 high-throughput platforms, within the framework of centralized databases for phenotypic, genetic, and mtDNA data. Additional advanced approaches (bioinformatics, advanced statistics, mathematical modeling, functional genomics and proteomics, molecular biology, molecular genetics) are envisaged to identify the gene variant(s) of interest. The experimental design will also allow (a) to identify gender-specific genes involved in healthy aging and longevity in women and men stratified for ethnic and geographic origin and apoE genotype; (b) to perform a longitudinal survival study to assess the impact of the identified genetic loci on 90+ people mortality; and (c) to develop mathematical and statistical models capable of combining genetic data with demographic characteristics, health status, socioeconomic factors, lifestyle habits.
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Affiliation(s)
- Claudio Franceschi
- C.I.G.-Interdepartmental Centre "L.Galvani," University of Bologna, Via S. Giacomo 12, 40126 Bologna, Italy.
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Salvioli S, Olivieri F, Marchegiani F, Cardelli M, Santoro A, Bellavista E, Mishto M, Invidia L, Capri M, Valensin S, Sevini F, Cevenini E, Celani L, Lescai F, Gonos E, Caruso C, Paolisso G, De Benedictis G, Monti D, Franceschi C. Genes, ageing and longevity in humans: problems, advantages and perspectives. Free Radic Res 2007; 40:1303-23. [PMID: 17090420 DOI: 10.1080/10715760600917136] [Citation(s) in RCA: 44] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Many epidemiological data indicate the presence of a strong familial component of longevity that is largely determined by genetics, and a number of possible associations between longevity and allelic variants of genes have been described. A breakthrough strategy to get insight into the genetics of longevity is the study of centenarians, the best example of successful ageing. We review the main results regarding nuclear genes as well as the mitochondrial genome, focusing on the investigations performed on Italian centenarians, compared to those from other countries. These studies produced interesting results on many putative "longevity genes". Nevertheless, many discrepancies are reported, likely due to the population-specific interactions between gene pools and environment. New approaches, including large-scale studies using high-throughput techniques, are urgently needed to overcome the limits of traditional association studies performed on a limited number of polymorphisms in order to make substantial progress to disentangle the genetics of a trait as complex as human longevity.
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Affiliation(s)
- S Salvioli
- Department of Experimental Pathology, University of Bologna, Bologna, Italy
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Willcox DC, Willcox BJ, Hsueh WC, Suzuki M. Genetic determinants of exceptional human longevity: insights from the Okinawa Centenarian Study. AGE (DORDRECHT, NETHERLANDS) 2006; 28:313-32. [PMID: 22253498 PMCID: PMC3259160 DOI: 10.1007/s11357-006-9020-x] [Citation(s) in RCA: 52] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2006] [Revised: 09/30/2006] [Accepted: 10/01/2006] [Indexed: 05/31/2023]
Abstract
Centenarians represent a rare phenotype appearing in roughly 10-20 per 100,000 persons in most industrialized countries but as high as 40-50 per 100,000 persons in Okinawa, Japan. Siblings of centenarians in Okinawa have been found to have cumulative survival advantages such that female centenarian siblings have a 2.58-fold likelihood and male siblings a 5.43-fold likelihood (versus their birth cohorts) of reaching the age of 90 years. This is indicative of a strong familial component to longevity. Centenarians may live such extraordinarily long lives in large part due to genetic variations that either affect the rate of aging and/or have genes that result in decreased susceptibility to age-associated diseases. Some of the most promising candidate genes appear to be those involved in regulatory pathways such as insulin signaling, immunoinflammatory response, stress resistance or cardiovascular function. Although gene variants with large beneficial effects have been suggested to exist, only APOE, an important regulator of lipoproteins has been consistently associated with a longer human lifespan across numerous populations. As longevity is a very complex trait, several issues challenge our ability to identify its genetic influences, such as control for environmental confounders across time, the lack of precise phenotypes of aging and longevity, statistical power, study design and availability of appropriate study populations. Genetic studies on the Okinawan population suggest that Okinawans are a genetically distinct group that has several characteristics of a founder population, including less genetic diversity, and clustering of specific gene variants, some of which may be related to longevity. Further work on this population and other genetic isolates would be of significant interest to the genetics of human longevity.
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Affiliation(s)
- D. Craig Willcox
- College of Nursing, Okinawa Prefectural University, 1-24-1 Yogi, Naha City, Okinawa Japan 902-0076
- Pacific Health Research Institute, 846 South Hotel Street, Suite 301, Honolulu, HI 96813 USA
| | - Bradley J. Willcox
- Pacific Health Research Institute, 846 South Hotel Street, Suite 301, Honolulu, HI 96813 USA
- Departments of Geriatric Medicine and Medicine, John A. Burns School of Medicine, University of Hawaii, 1356 Lusitana Street, 7F, Honolulu, HI 96813 USA
| | - Wen-Chi Hsueh
- School of Medicine, University of California San Francisco, 74 New Montgomery Street, Suite 600, San Francisco, CA 94105 USA
- 2200 Post Street, C433, San Francisco, CA 94143-1640 USA
| | - Makoto Suzuki
- Faculty of Medicine, University of the Ryukyus, 207 Uehara, Nishihara, Okinawa, Japan
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