Denigma

Longevity Variant Database

Narrow results by variant, study, or associated fields (e.g. gene symbol ADRB2):

Use ontology terms to further narrow results (e.g. aging, insulin, etc.):

  • Variant effect: + -
    Longevity‑Associated (607)   No Age Effect (103)  
  • Study type: + -
    Genome‑Wide Association Study « 
  • Variant type: + -
    SNP (147)   Locus (1)  
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    13 14 15 16 17 18 19 20 21 X Y MT
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    Populations | Study Types | Variant Types


    LVDB_word_cloud.png
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    variants.jpg
    polymorphism factor odds ratio pvalue initial number replication number Population age of cases shorter lived allele longer lived allele study type reference
    rs4420638 APOC1 0.53 1.8e-10 763 vs 1085 754 vs 850 German Mean age 99.7 G — Genome-Wide Association Study 21740922
    rs2338013 — 0.67 2.07e-06 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs350450 — 0.69 6.34e-06 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs29228 — 0.68 9.12e-06 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs3129063 — 0.67 4.33e-06 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs3129046 — 0.66 2.21e-07 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs1610742 — 0.66 3.02e-07 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs1610601 — 0.68 1.98e-06 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs1633063 — 0.68 3.82e-06 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs11790055 — 1.38 1.49e-05 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs10959258 — 1.36 1.86e-05 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs9595687 — 0.49 2.09e-05 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs1575892 — 0.45 9.32e-06 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs16947526 — 0.56 1.23e-05 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs158869 — 1.37 4.98e-06 763 vs 1085 754 vs 850 German Mean age 99.7 — — Genome-Wide Association Study 21740922
    rs2495513 TMEM61 0.60 8.13e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs4291539 — 1.81 4.41e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs10923806 — 2.30 7.24e-06 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs1538287 KCNH1 0.55 4.87e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs6540664 — 1.46 9e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs6701445 TAF5L 1.84 4.19e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs12088486 — 0.56 1.75e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs10514626 — 0.38 1.12e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs7583529 CFLAR 3.15 6.45e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs4505466 SH3BP4 2.06 8.31e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
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    • 25 of 710 variants

    The Longevity Variant Database (LVDB) is a collaborative effort to catalogue all published genetic variants relevant to human longevity.

    The project is directed by the Health Extension Research Foundation [http://www.healthextension.co/about/], and the online content is managed by the members of the Global Computing Initiative.

    LVDB is driven by an international collaboration of scientists, programmers, and volunteers, including Joe Betts-LaCroix, Kristen Fortney, Daniel Wuttke, Eric K. Morgen, Nick Schaum, John M. Adams, Jessica Choi, Barry Goldberg, Amir Levine, Maria Litovchenko, Aiste Narkeviciute, Emily Quist, Navneet Ramesh, Justin Rebo, Dmitri Shytikov, and Jimi Vyas. o

    Suggest a new study Report a database issue