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      Genomics of 1 million parent lifespans implicates novel pathways and common diseases and distinguishes survival chances

      research-article
      1 , 2 , 3 , 4 , 5 , 4 , 5 , 6 , 7 , 8 , 1 , eQTLGen Consortium
      , 1 , 6 , 7 , 4 , 9 , 2 , 3 , 1 , 8 , 1 , 2 ,
      eLife
      eLife Sciences Publications, Ltd
      genomics, longevity, lifespan, complex trait, Human

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and IGF2R. We also validate previous findings near 5q33.3/ EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer – but not other cancers – explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles.

          Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed ( see decision letter).

          eLife digest

          Ageing happens to us all, and as the cabaret singer Maurice Chevalier pointed out, "old age is not that bad when you consider the alternative". Yet, the growing ageing population of most developed countries presents challenges to healthcare systems and government finances. For many older people, long periods of ill health are part of the end of life, and so a better understanding of ageing could offer the opportunity to prolong healthy living into old age.

          Ageing is complex and takes a long time to study – a lifetime in fact. This makes it difficult to discern its causes, among the countless possibilities based on an individual’s genes, behaviour or environment. While thousands of regions in an individual’s genetic makeup are known to influence their risk of different diseases, those that affect how long they will live have proved harder to disentangle. Timmers et al. sought to pinpoint such regions, and then use this information to predict, based on their DNA, whether someone had a better or worse chance of living longer than average.

          The DNA of over 500,000 people was read to reveal the specific ‘genetic fingerprints’ of each participant. Then, after asking each of the participants how long both of their parents had lived, Timmers et al. pinpointed 12 DNA regions that affect lifespan. Five of these regions were new and had not been linked to lifespan before. Across the twelve as a whole several were known to be involved in Alzheimer’s disease, smoking-related cancer or heart disease. Looking at the entire genome, Timmers et al. could then predict a lifespan score for each individual, and when they sorted participants into ten groups based on these scores they found that top group lived five years longer than the bottom, on average.

          Many factors beside genetics influence how long a person will live and our lifespan cannot be read from our DNA alone. Nevertheless, Timmers et al. had hoped to narrow down their search and discover specific genes that directly influence how quickly people age, beyond diseases. If such genes exist, their effects were too small to be detected in this study. The next step will be to expand the study to include more participants, which will hopefully pinpoint further genomic regions and help disentangle the biology of ageing and disease.

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          Most cited references35

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          General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

          Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
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            Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics

            Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.
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              Genetic Signatures of Exceptional Longevity in Humans

              Like most complex phenotypes, exceptional longevity is thought to reflect a combined influence of environmental (e.g., lifestyle choices, where we live) and genetic factors. To explore the genetic contribution, we undertook a genome-wide association study of exceptional longevity in 801 centenarians (median age at death 104 years) and 914 genetically matched healthy controls. Using these data, we built a genetic model that includes 281 single nucleotide polymorphisms (SNPs) and discriminated between cases and controls of the discovery set with 89% sensitivity and specificity, and with 58% specificity and 60% sensitivity in an independent cohort of 341 controls and 253 genetically matched nonagenarians and centenarians (median age 100 years). Consistent with the hypothesis that the genetic contribution is largest with the oldest ages, the sensitivity of the model increased in the independent cohort with older and older ages (71% to classify subjects with an age at death>102 and 85% to classify subjects with an age at death>105). For further validation, we applied the model to an additional, unmatched 60 centenarians (median age 107 years) resulting in 78% sensitivity, and 2863 unmatched controls with 61% specificity. The 281 SNPs include the SNP rs2075650 in TOMM40/APOE that reached irrefutable genome wide significance (posterior probability of association = 1) and replicated in the independent cohort. Removal of this SNP from the model reduced the accuracy by only 1%. Further in-silico analysis suggests that 90% of centenarians can be grouped into clusters characterized by different “genetic signatures” of varying predictive values for exceptional longevity. The correlation between 3 signatures and 3 different life spans was replicated in the combined replication sets. The different signatures may help dissect this complex phenotype into sub-phenotypes of exceptional longevity.
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                Author and article information

                Contributors
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                15 January 2019
                2019
                : 8
                : e39856
                Affiliations
                Ontario Institute for Cancer Research TorontoCanada
                deptDepartment of Public Health Sciences University of Chicago ChicagoUnited States
                Ontario Institute for Cancer Research TorontoCanada
                deptSingapore Immunology Network Agency for Science, Technology and Research SingaporeSingapore
                Ontario Institute for Cancer Research TorontoCanada
                deptDepartment of Computer Science Johns Hopkins University BaltimoreUnited States
                deptDepartment of Genetics University Medical Centre Groningen GroningenThe Netherlands
                Vrije Universiteit AmsterdamThe Netherlands
                deptCardiovascular Health Research Unit University of Washington SeattleUnited States
                deptDepartment of Genetics University Medical Centre Groningen GroningenThe Netherlands
                deptDepartment of Genetics University Medical Centre Groningen GroningenThe Netherlands
                Vrije Universiteit AmsterdamThe Netherlands
                deptEstonian Genome Center University of Tartu TartuEstonia
                Ontario Institute for Cancer Research TorontoCanada
                deptDepartment of Genetics University Medical Centre Groningen GroningenThe Netherlands
                deptExeter Medical School University of Exeter ExeterUnited Kingdom
                deptDepartment of Medicine University of Washington SeattleUnited States
                deptSchool of Biological Sciences Georgia Institute of Technology AtlantaUnited States
                deptMRC Integrative Epidemiology Unit University of Bristol BristolUnited Kingdom
                Vrije Universiteit AmsterdamThe Netherlands
                deptEstonian Genome Center University of Tartu TartuEstonia
                deptEstonian Genome Center University of Tartu TartuEstonia
                University of Helsinki HelsinkiFinland
                deptDepartment of Computer Science Johns Hopkins University BaltimoreUnited States
                deptInstitut für Medizinische Informatik, Statistik und Epidemiologie, LIFE – Leipzig ResearchCenter for Civilization Diseases Universität Leipzig LeipzigGermany
                deptIFB Adiposity Diseases Universität Leipzig LeipzigGermany
                deptInterdisciplinary Center for Clinical Research, Faculty of Medicine Universität Leipzig LeipzigGermany
                deptEstonian Genome Center University of Tartu TartuEstonia
                deptEstonian Genome Center University of Tartu TartuEstonia
                Lausanne University Hospital LausanneSwitzerland
                deptDepartment of Clinical Physiology and Faculty of Medicine and Life Sciences Tampere University Hospital and University of Tampere TampereFinland
                deptSingapore Immunology Network Agency for Science, Technology and Research SingaporeSingapore
                deptDepartment of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Life Sciences University of Tampere TampereFinland
                deptInstitut für Medizinische Informatik, Statistik und Epidemiologie, LIFE – Leipzig Research Center for Civilization Diseases Universität Leipzig LeipzigGermany
                deptSchool of Biological Sciences Georgia Institute of Technology AtlantaUnited States
                deptEstonian Genome Center University of Tartu TartuEstonia
                deptDepartment of Internal Medicine Erasmus Medical Centre RotterdamThe Netherlands
                deptEstonian Genome Center University of Tartu TartuEstonia
                deptInstitute of Genetic Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health NeuherbergGermany
                deptInstitute of Clinical Chemistry and Laboratory Medicine University Medicine Greifswald GreifswaldGermany
                Vrije Universiteit AmsterdamThe Netherlands
                Vrije Universiteit AmsterdamThe Netherlands
                deptNational Institute for Health and Welfare University of Helsinki HelsinkiFinland
                deptEstonian Genome Center University of Tartu TartuEstonia
                deptDepartment of Public Health Sciences University of Chicago ChicagoUnited States
                deptInstitute for Molecular Bioscience University of Queensland BrisbaneAustralia
                deptInstitute of Human Genetics Helmholtz Zentrum München MünchenGermany
                deptDepartments of Epidemiology, Medicine, and Health Services, Cardiovascular Health Research Unit University of Washington SeattleUnited States
                deptDepartment of Clinical Physiology and Nuclear Medicine Turku University Hospital and University of Turku TurkuFinland
                deptSchool of Social and Community Medicine University of Bristol BristolUnited Kingdom
                University of Helsinki HelsinkiFinland
                deptSingapore Immunology Network Agency for Science, Technology and Research SingaporeSingapore
                Lausanne University Hospital LausanneSwitzerland
                deptDepartment of Computer Science Johns Hopkins University BaltimoreUnited States
                deptInstitut für Medizinische InformatiK, Statistik und Epidemiologie, LIFE – Leipzig Research Center for Civilization Diseases Universität Leipzig LeipzigGermany
                deptInstitute of Genetic Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health NeuherbergGermany
                deptDepartment of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Life Sciences University of Tampere TampereFinland
                deptDepartment of Medicine Universität Leipzig LeipzigGermany
                deptDepartment of Medical Epidemiology and Biostatistics Karolinska Institutet StockholmSweden
                deptInstitute for Community Medicine University Medicine Greifswald GreifswaldGermany
                deptInstitute for Laboratory Medicine, LIFE – Leipzig Research Center for Civilization Diseases Universität Leipzig LeipzigGermany
                deptDepartment of Public Health Sciences University of Chicago ChicagoUnited States
                deptDepartment of Medicine Universität Leipzig LeipzigGermany
                deptDepartment of Internal Medicine Erasmus Medical Centre RotterdamThe Netherlands
                deptInstitute for Molecular Bioscience University of Queensland BrisbaneAustralia
                deptDepartment of Genetics University Medical Centre Groningen GroningenThe Netherlands
                deptInterfaculty Institute for Genetics and Functional Genomics University Medicine Greifswald GreifswaldGermany
                deptExeter Medical School University of Exeter ExeterUnited Kingdom
                deptInstitute for Molecular Bioscience University of Queensland BrisbaneAustralia
                deptSchool of Biological Sciences Georgia Institute of Technology AtlantaUnited States
                deptInstitute for Molecular Bioscience University of Queensland BrisbaneAustralia
                Ontario Institute for Cancer Research TorontoCanada
                deptDepartment of Public Health Sciences University of Chicago ChicagoUnited States
                Ontario Institute for Cancer Research TorontoCanada
                deptSingapore Immunology Network Agency for Science, Technology and Research SingaporeSingapore
                Ontario Institute for Cancer Research TorontoCanada
                deptDepartment of Computer Science Johns Hopkins University BaltimoreUnited States
                deptDepartment of Genetics University Medical Centre Groningen GroningenThe Netherlands
                Vrije Universiteit AmsterdamThe Netherlands
                deptCardiovascular Health Research Unit University of Washington SeattleUnited States
                deptDepartment of Genetics University Medical Centre Groningen GroningenThe Netherlands
                deptDepartment of Genetics University Medical Centre Groningen GroningenThe Netherlands
                Vrije Universiteit AmsterdamThe Netherlands
                deptEstonian Genome Center University of Tartu TartuEstonia
                Ontario Institute for Cancer Research TorontoCanada
                deptDepartment of Genetics University Medical Centre Groningen GroningenThe Netherlands
                deptExeter Medical School University of Exeter ExeterUnited Kingdom
                deptDepartment of Medicine University of Washington SeattleUnited States
                deptSchool of Biological Sciences Georgia Institute of Technology AtlantaUnited States
                deptMRC Integrative Epidemiology Unit University of Bristol BristolUnited Kingdom
                Vrije Universiteit AmsterdamThe Netherlands
                deptEstonian Genome Center University of Tartu TartuEstonia
                deptEstonian Genome Center University of Tartu TartuEstonia
                University of Helsinki HelsinkiFinland
                deptDepartment of Computer Science Johns Hopkins University BaltimoreUnited States
                deptInstitut für Medizinische Informatik, Statistik und Epidemiologie, LIFE – Leipzig ResearchCenter for Civilization Diseases Universität Leipzig LeipzigGermany
                deptIFB Adiposity Diseases Universität Leipzig LeipzigGermany
                deptInterdisciplinary Center for Clinical Research, Faculty of Medicine Universität Leipzig LeipzigGermany
                deptEstonian Genome Center University of Tartu TartuEstonia
                deptEstonian Genome Center University of Tartu TartuEstonia
                Lausanne University Hospital LausanneSwitzerland
                deptDepartment of Clinical Physiology and Faculty of Medicine and Life Sciences Tampere University Hospital and University of Tampere TampereFinland
                deptSingapore Immunology Network Agency for Science, Technology and Research SingaporeSingapore
                deptDepartment of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Life Sciences University of Tampere TampereFinland
                deptInstitut für Medizinische Informatik, Statistik und Epidemiologie, LIFE – Leipzig Research Center for Civilization Diseases Universität Leipzig LeipzigGermany
                deptSchool of Biological Sciences Georgia Institute of Technology AtlantaUnited States
                deptEstonian Genome Center University of Tartu TartuEstonia
                deptDepartment of Internal Medicine Erasmus Medical Centre RotterdamThe Netherlands
                deptEstonian Genome Center University of Tartu TartuEstonia
                deptInstitute of Genetic Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health NeuherbergGermany
                deptInstitute of Clinical Chemistry and Laboratory Medicine University Medicine Greifswald GreifswaldGermany
                Vrije Universiteit AmsterdamThe Netherlands
                Vrije Universiteit AmsterdamThe Netherlands
                deptNational Institute for Health and Welfare University of Helsinki HelsinkiFinland
                deptEstonian Genome Center University of Tartu TartuEstonia
                deptDepartment of Public Health Sciences University of Chicago ChicagoUnited States
                deptInstitute for Molecular Bioscience University of Queensland BrisbaneAustralia
                deptInstitute of Human Genetics Helmholtz Zentrum München MünchenGermany
                deptDepartments of Epidemiology, Medicine, and Health Services, Cardiovascular Health Research Unit University of Washington SeattleUnited States
                deptDepartment of Clinical Physiology and Nuclear Medicine Turku University Hospital and University of Turku TurkuFinland
                deptSchool of Social and Community Medicine University of Bristol BristolUnited Kingdom
                University of Helsinki HelsinkiFinland
                deptSingapore Immunology Network Agency for Science, Technology and Research SingaporeSingapore
                Lausanne University Hospital LausanneSwitzerland
                deptDepartment of Computer Science Johns Hopkins University BaltimoreUnited States
                deptInstitut für Medizinische InformatiK, Statistik und Epidemiologie, LIFE – Leipzig Research Center for Civilization Diseases Universität Leipzig LeipzigGermany
                deptInstitute of Genetic Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health NeuherbergGermany
                deptDepartment of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Life Sciences University of Tampere TampereFinland
                deptDepartment of Medicine Universität Leipzig LeipzigGermany
                deptDepartment of Medical Epidemiology and Biostatistics Karolinska Institutet StockholmSweden
                deptInstitute for Community Medicine University Medicine Greifswald GreifswaldGermany
                deptInstitute for Laboratory Medicine, LIFE – Leipzig Research Center for Civilization Diseases Universität Leipzig LeipzigGermany
                deptDepartment of Public Health Sciences University of Chicago ChicagoUnited States
                deptDepartment of Medicine Universität Leipzig LeipzigGermany
                deptDepartment of Internal Medicine Erasmus Medical Centre RotterdamThe Netherlands
                deptInstitute for Molecular Bioscience University of Queensland BrisbaneAustralia
                deptDepartment of Genetics University Medical Centre Groningen GroningenThe Netherlands
                deptInterfaculty Institute for Genetics and Functional Genomics University Medicine Greifswald GreifswaldGermany
                deptExeter Medical School University of Exeter ExeterUnited Kingdom
                deptInstitute for Molecular Bioscience University of Queensland BrisbaneAustralia
                deptSchool of Biological Sciences Georgia Institute of Technology AtlantaUnited States
                deptInstitute for Molecular Bioscience University of Queensland BrisbaneAustralia
                [1 ]deptCentre for Global Health Research, Usher Institute of Population Health Sciences and Informatics University of Edinburgh EdinburghUnited Kingdom
                [2 ]deptInstitute of Social and Preventive Medicine University Hospital of Lausanne LausanneSwitzerland
                [3 ]Swiss Institute of Bioinformatics LausanneSwitzerland
                [4 ]deptEstonian Genome Center, Institute of Genomics University of Tartu TartuEstonia
                [5 ]deptInstitute of Mathematics and Statistics University of Tartu TartuEstonia
                [6 ]deptDepartment of Medical Epidemiology and Biostatistics Karolinska Institutet StockholmSweden
                [7 ]deptState Key Laboratory of Biocontrol, School of Life Sciences Sun Yat-sen University GuangzhouChina
                [8 ]deptMRC Human Genetics Unit, Institute of Genetics and Molecular Medicine University of Edinburgh EdinburghUnited Kingdom
                [9 ]Broad Institute of Harvard and MIT CambridgeUnited States
                Author information
                http://orcid.org/0000-0002-5197-1267
                http://orcid.org/0000-0003-4390-1979
                http://orcid.org/0000-0003-1982-6569
                http://orcid.org/0000-0001-5751-9178
                http://orcid.org/0000-0002-6361-5059
                Article
                39856
                10.7554/eLife.39856
                6333444
                30642433
                3fb46bd6-5975-4977-8c6e-9e9a166cb497
                © 2019, Timmers et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 05 July 2018
                : 20 November 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: DTP in Precision Medicine MR/N013166/1,HGU QTL in health and disease
                Award Recipient : eQTLGen Consortium
                Funded by: FundRef http://dx.doi.org/10.13039/501100005189, Estonian Research Competency Council;
                Award ID: PUT 1665
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Award ID: PhD Training Fellowship for Clinicians
                Award Recipient :
                Funded by: Edinburgh Clinical Academic Track;
                Award ID: 204979/Z/16/Z
                Award Recipient :
                Funded by: Svenska Forskningsrådet Formas;
                Award ID: 2014-00371
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001862, Svenska Forskningsrådet Formas;
                Award ID: 2017-02543
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: 31003A_169929
                Award Recipient :
                Funded by: SystemsX.ch;
                Award ID: 51RTP0_151019
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001961, AXA Research Fund;
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Communication
                Genetics and Genomics
                Custom metadata
                Genomic associations with lifespan principally reflect heart disease/smoking/dementia but not other cancers, and distinguish lifespan differences of five years between top/bottom deciles of a score derived from DNA alone.

                Life sciences
                genomics,longevity,lifespan,complex trait,human
                Life sciences
                genomics, longevity, lifespan, complex trait, human

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