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 (1027)   No Age Effect (543)  
  • Study type: + -
    GWAS (2)   ‑ (27)   Candidate Region/Gene (784)   Meta‑Analysis (38)   Complete Mitochondrial Genome (2)   Whole‑Genome Linkage Scan (1)   Genome‑Wide Association Study (710)   Mitochondrial Haplogroup (36)   Mitochondrial genome (3)  
  • Variant type: + -
    SNP (572)   Locus (5)   Haplotype (87)   Other (1)   STR (11)   Deletion (5)   CNV (1)    (1)   VNTR (1)  
    • 1 2 3 4 5 6 7 8 9 10 11 12
    13 14 15 16 17 18 19 20 21 X Y MT
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    Populations | Study Types | Variant Types


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    polymorphism factor odds ratio pvalue initial number replication number Population age of cases shorter lived allele longer lived allele study type reference
    ApaI IGF2 — 0.063 224 vs 441 — Ashkenazi Jewish 75 G A Candidate Region/Gene 15621215
    rs12629971 EIF4E3 1.61 1.9e-06 801 vs 914 — Caucasian Median age 104 A G Genome-Wide Association Study 22279548
    rs6801173 EIF4E3 1.52 8.16e-06 801 vs 914 — Caucasian Median age 104 A G Genome-Wide Association Study 22279548
    rs6443429 TBL1XR1 1.13 0.000251569 801 vs 914 — Caucasian Median age 104 A C Genome-Wide Association Study 22279548
    rs2243115 IL12A 1.11 0.001736813 801 vs 914 — Caucasian Median age 104 A C Genome-Wide Association Study 22279548
    rs12634249 SUMF1 1.18 0.000686245 801 vs 914 — Caucasian Median age 104 A C Genome-Wide Association Study 22279548
    rs10510828 FHIT 1.24 0.000311601 801 vs 914 — Caucasian Median age 104 G A Genome-Wide Association Study 22279548
    rs10511330 ZBTB20 1.15 0.002831841 801 vs 914 — Caucasian Median age 104 A G Genome-Wide Association Study 22279548
    rs1377843 DZIP3 1.36 0.000414112 801 vs 914 — Caucasian Median age 104 G A Genome-Wide Association Study 22279548
    rs361072 PIK3CB — 0.829 122 vs 122 — Japanese mean age 106.8 — — Candidate Region/Gene 15582274
    rs2305268 PIK3CB — 0.363 122 vs 122 — Japanese mean age 106.8 — — Candidate Region/Gene 15582274
    rs1801282 PPARG — 0.035 222 vs 250 — Caucasian 86 to 109; median age 99 G — Candidate Region/Gene 15236769
    V465A GABRR3 — 0.04 390 vs 410 — Ashkenazi Jewish Centenarians — — Candidate Region/Gene 23376243
    rs9868286 CCDC50 1.48 7.4e-06 403 vs 1670 3746 vs 5912 Dutch Mean age 94 — C Genome-Wide Association Study 21418511
    rs4681554 C3orf16 0.64 9.82e-05 403 vs 1670 3746 vs 5912 Dutch Mean age 94 A — Genome-Wide Association Study 21418511
    (+)2019 del ADIPOQ10 — 0.05 118 centenarians vs 78 unrelated young — Ashkenazi Jewish 95-105 A Del/Del Candidate Region/Gene 18511746
    rs964403 SUMF1 2.07 4.91e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs3864051 SUMF1 2.07 5.49e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs712773 GRM7 0.66 9.99e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs513154 IMPG2 0.52 4.65e-06 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs571391 IMPG2 0.55 2.67e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs572169 GHSR 0.72 0.0045 1089 vs 736 1613 vs 1104 Danish 92-93 years old A G Candidate Region/Gene 22406557
    rs572169 GHSR 0.72 0.0045 1089 vs 736 1613 vs 1104 Danish 92.2–93.8 (mean age 93.2 A — Candidate Region/Gene 22406557
    rs26802 GHRL 2.34 0.032 1089 (see notes - follow-up study) 563 (see notes - follow-up study) Danish 92.2–93.8 (mean age 93.2) w/ 11.4 years follow-up A — Candidate Region/Gene 22406557
    rs13320360 MLH1 3.13 0.0036 1089 (see notes - follow-up study) 563 (see notes - follow-up study) Danish 92.2–93.8 (mean age 93.2) w/ 11.4 years follow-up A — Candidate Region/Gene 22406557
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    • 25 of 53 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