Cited by 373Genetic Associations and EpidemiologyGenetics, Aging, and Longevity in Model OrganismsGenetic and phenotypic traits in livestock

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A meta-analysis of genome-wide association studies identifies multiple longevity genes

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Deelen, Joris, Evans, Daniel S., Arking, Dan E., Tesi, Niccolò, Nygaard, Marianne, Liu, Xiaomin, Wojczynski, Mary K., Biggs, Mary L., van der Spek, Ashley, Atzmon, Gil, Ware, Erin B., Sarnowski, Chloé, Smith, Albert V., Seppälä, Ilkka, Cordell, Heather J., Dose, Janina, Amin, Najaf, Arnold, Alice M., Ayers, Kristin L., Barzilai, Nir, Becker, Elizabeth J., Beekman, Marian, Blanché, Hélène, Christensen, Kaare, Christiansen, Lene, Collerton, Joanna C., Cubaynes, Sarah, Cummings, Steven R., Davies, Karen, Debrabant, Birgit, Deleuze, Jean-François, Duncan, Rachel, Faul, Jessica D., Franceschi, Claudio, Galan, Pilar, Gudnason, Vilmundur, Harris, Tamara B., Huisman, Martijn, Hurme, Mikko A., Jagger, Carol, Jansen, Iris, Jylhä, Marja, Kähönen, Mika, Karasik, David, Kardia, Sharon L. R., Kingston, Andrew, Kirkwood, Thomas B. L., Launer, Lenore J., Lehtimäki, Terho, Lieb, Wolfgang, Lyytikäinen, Leo-Pekka, Martin-Ruiz, Carmen, Min, Junxia, Nebel, Almut, Newman, Anne B., Nie, Chao, Nohr, Ellen A., Orwoll, Eric S., Perls, Thomas T., Province, Michael A., Psaty, Bruce M., Raitakari, Olli T., Reinders, Marcel J. T., Robine, Jean-Marie, Rotter, Jerome I., Sebastiani, Paola, Smith, Jennifer, Sørensen, Thorkild I. A., Taylor, Kent D., Uitterlinden, André G., van der Flier, Wiesje, van der Lee, Sven J., van Duijn, Cornelia M., van Heemst, Diana, Vaupel, James W., Weir, David, Ye, Kenny, Zeng, Yi, Zheng, Wanlin, Holstege, Henne, Kiel, Douglas P., Lunetta, Kathryn L., Slagboom, P. Eline, Murabito, Joanne M.·2019·Nature Communications

DOI 10.1038/s41467-019-11558-2PMC PMC6694136

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Abstract

Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78 , associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.

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Fig. 1 Results of the European genome-wide association meta-analyses. Manhattan plot presenting the –log10 P-values from the European genome-wide association meta-analysis of the 90th percentile cases versus all controls (a) and 99th percentile cases versus all controls (b). The red line indicates the threshold for genome-wide significance (P ≤ 5 × 10−8), while the blue line indicates the threshold for genetic variants that showed a suggestive significant association (P ≤ 1 × 10−6). The variants that are reported in Table 2 are highlighted in green. For representation purposes, the maximum of the y-axis was set to 14. Regional association plot for the APOE (c) and GPR78 (d) loci based on the results from the 90th percentile cases versus all controls meta-analysis. The colour of the variants is based on the linkage disequilibrium with rs429358 (ApoE ε4) (c) or rs7676745 (d)CC BY · PubMed Central

Fig. 2 Study-specific results for the genetic variants in APOE and GPR78. Forest plots for the ApoE ε4 (a) and ε2 (b) variants and rs7676745 (c) based on the results from the 90th percentile versus all controls analysis. The size of the boxes represents the sample size of the cohort. We had no data available for ApoE ε4 in LLFS and for rs7676745 in DKLS, GEHA Italy, GEHA Danish, LLS (combined with GEHA Dutch), Longevity, and Newcastle 85 + . The data for ApoE ε2 in FHS was based on imputation using the Haplotype Reference Consortium reference panel due to the low-imputation quality of this variant when using the 1000 Genomes reference panelCC BY · PubMed Central

Fig. 3 Results of the trans-ethnic genome-wide association meta-analyses. Manhattan plot presenting the –log10 P-values from the trans-ethnic genome-wide association meta-analysis of the 90th percentile cases versus all controls (a) and 99th percentile cases versus all controls (b). The red line indicates the threshold for genome-wide significance (P ≤ 5 × 10−8), while the blue line indicates the threshold for genetic variants that showed a suggestive significant association (P ≤ 1 × 10−6)CC BY · PubMed Central

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“Similarly, in a review of 37 studies with 37,294 participants, cardiometabolic and neurodegenerative diseases, thereby contributing to longevity in these individuals [ 18 , 19 ].”
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A minimal three-arm oral regimen for healthspan: mechanistic alignment with transcriptomic signals from a large parental-lifespan GWAS
Cheung, N. (2026) · Frontiers in Aging · doi:10.3389/fragi.2026.1856979
“Its directional signals are broadly compatible with independent longevity GWAS and trans-omic analyses that implicate metabolic, inflammatory, and age-related disease biology (Deelen et al., 2019; Pilling et al., 2017; Perrot et al., 2021).”
Vector2Variant: Discovery of Genetic Associations from ML Derived Representations without Phenotype EngineeringPreprint
Sooknah, M., Srinivasan, R., Sankarapandian, S., Chen, Z., & Xu, J. (2026) · medRxiv · doi:10.64898/2026.04.10.26350624
Enhancing Drug Discovery and Development Through Artificial Intelligence
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Multimodal single-cell analysis uncovers transcription factor networks underlying T-cell agingPreprint
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“For this, we considered traits related to healthspan [29], parental lifespan [30], exceptional longevity [31], epigenetic age acceleration (EAA) (from the PhenoAge cohort) [33], and frailty (from a meta-analysis of UKB and TwinGene cohort participants) [32].”
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Unraveling ‘F’ factor: towards a genetic-clinical framework for the musculoskeletal-heart crosstalk in metabolic aging
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Self-citation
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Influential
Parental longevity and polygenic longevity scores in relation to ageing-related factors in a population of 70-year-olds followed over six years: The Gothenburg H70 Birth Cohort Study
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Self-citation
Polygenic scores for longevity in relation to brain MRI measures in a cohort of 70-year-olds
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“Usingthisapproach,studies have reported that individuals with high PGLSs are more likely to have a healthy metabolic pro ﬁ le 4 , more often have long-lived parents 2,5 , higher education 6 and better cardiovascular health 2,5 .”
InfluentialSelf-citation

Authors: Deelen, J., Evans, D. S., Arking, D. E., Tesi, N., Nygaard, M., Liu, X., Wojczynski, M. K., Biggs, M. L., van der Spek, A., Atzmon, G., Ware, E. B., Sarnowski, C., Smith, A. V., Seppälä, I., Cordell, H. J., Dose, J., Amin, N., Arnold, A. M., Ayers, K. L., Barzilai, N., Becker, E. J., Beekman, M., Blanché, H., Christensen, K., Christiansen, L., Collerton, J. C., Cubaynes, S., Cummings, S. R., Davies, K., Debrabant, B., Deleuze, J.-F., Duncan, R., Faul, J. D., Franceschi, C., Galan, P., Gudnason, V., Harris, T. B., Huisman, M., Hurme, M. A., Jagger, C., Jansen, I., Jylhä, M., Kähönen, M., Karasik, D., Kardia, S. L. R., Kingston, A., Kirkwood, T. B. L., Launer, L. J., Lehtimäki, T., Lieb, W., Lyytikäinen, L.-P., Martin-Ruiz, C., Min, J., Nebel, A., Newman, A. B., Nie, C., Nohr, E. A., Orwoll, E. S., Perls, T. T., Province, M. A., Psaty, B. M., Raitakari, O. T., Reinders, M. J. T., Robine, J.-M., Rotter, J. I., Sebastiani, P., Smith, J., Sørensen, T. I. A., Taylor, K. D., Uitterlinden, A. G., van der Flier, W., van der Lee, S. J., van Duijn, C. M., van Heemst, D., Vaupel, J. W., Weir, D., Ye, K., Zeng, Y., Zheng, W., Holstege, H., Kiel, D. P., Lunetta, K. L., Slagboom, P. E., & Murabito, J. M.
Affiliations: Leiden University (NL)
California Pacific Medical Center (US)
Johns Hopkins University (US)
University of Southern Denmark (DK)
BGI Group (China) (CN)
Washington University in St. Louis (US)
University of Washington (US)
Albert Einstein College of Medicine (US)
University of Michigan (US)
Boston University (US)
Tampere University (FI)
Centre for Life (GB)
Christian-Albrechts-Universität zu Kiel (DE)
Erasmus MC (NL)
Sema4 (United States) (US)
Fondation Jean Dausset-CEPH (FR)
Royal Victoria Infirmary (GB)
Inserm (FR)
Newcastle University (GB)
Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
Istituto delle Scienze Neurologiche di Bologna (IT)
University of Iceland (IS)
National Institutes of Health (US)
Amsterdam Public Health (NL)
Amsterdam Neuroscience (NL)
Bar-Ilan University (IL)
Zhejiang University (CN)
University of Pittsburgh (US)
Oregon Health & Science University (US)
Kaiser Permanente Washington Health Research Institute (US)
University of Turku (FI)
Delft University of Technology (NL)
Centre National de la Recherche Scientifique (FR)
The Lundquist Institute (US)
University of Copenhagen (DK)
University of California, Los Angeles (US)
Max Planck Institute for Demographic Research (DE)
Duke University (US)
Amsterdam UMC Location University of Amsterdam (NL)
Broad Institute (US)
Corresponding author: Deelen, Joris
Evans, Daniel S.
Slagboom, P. Eline
Murabito, Joanne M.
ORCID: Deelen, Joris
Evans, Daniel S.
Arking, Dan E.
Tesi, Niccolò
Nygaard, Marianne
Liu, Xiaomin
Wojczynski, Mary K.
van der Spek, Ashley
Atzmon, Gil
Ware, Erin B.
Sarnowski, Chloé
Smith, Albert V.
Seppälä, Ilkka
Cordell, Heather J.
Dose, Janina
Amin, Najaf
Arnold, Alice M.
Ayers, Kristin L.
Barzilai, Nir
Beekman, Marian
Blanché, Hélène
Christensen, Kaare
Christiansen, Lene
Cubaynes, Sarah
Cummings, Steven R.
Davies, Karen
Debrabant, Birgit
Deleuze, Jean-François
Duncan, Rachel
Faul, Jessica D.
Franceschi, Claudio
Galan, Pilar
Gudnason, Vilmundur
Harris, Tamara B.
Huisman, Martijn
Hurme, Mikko A.
Jagger, Carol
Jansen, Iris
Jylhä, Marja
Kähönen, Mika
Karasik, David
Kingston, Andrew
Kirkwood, Thomas B. L.
Launer, Lenore J.
Lehtimäki, Terho
Lieb, Wolfgang
Lyytikäinen, Leo-Pekka
Martin-Ruiz, Carmen
Min, Junxia
Newman, Anne B.
Nie, Chao
Nohr, Ellen A.
Orwoll, Eric S.
Perls, Thomas T.
Province, Michael A.
Psaty, Bruce M.
Raitakari, Olli T.
Reinders, Marcel J. T.
Robine, Jean-Marie
Rotter, Jerome I.
Smith, Jennifer
Sørensen, Thorkild I. A.
Taylor, Kent D.
Uitterlinden, André G.
van der Lee, Sven J.
Vaupel, James W.
Weir, David
Ye, Kenny
Zheng, Wanlin
Holstege, Henne
Kiel, Douglas P.
Lunetta, Kathryn L.
Slagboom, P. Eline
Murabito, Joanne M.
Venue: Nature Communications
Publisher: Springer Science and Business Media LLC
Published: 2019-08-14
Volume: 10
Issue: 1
Pages: 3669-3669
ISSN: 2041-1723 (ISSN-L)
DOI: 10.1038/s41467-019-11558-2
PMC: PMC6694136
OpenAlex: W2967338832
Cited by: 370
References: 61
Citations by year: 2026: 38 · 2025: 64 · 2024: 56 · 2023: 60 · 2022: 51 · 2021: 53 · 2020: 44 · 2019: 3
FWCI: 5.07
Type: journal article
Language: en
Update notices: correction (2021-04-23)
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor)
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Funders: Alexander von Humboldt-Stiftung
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
Keywords: human longevity, longevity genes, apolipoprotein E, APOE ε4, APOE ε2, tissue-specific gene expression, genetic correlation, heritability of longevity, genetic overlap
MeSH terms: Endoplasmic Reticulum Chaperone BiP, Heat-Shock Proteins, Humans, Longevity, Apolipoprotein E4, Apolipoprotein E2, Genome-Wide Association Study

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A meta-analysis of genome-wide association studies identifies multiple longevity genes

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