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 (22)   No Age Effect (77)  
  • Study type: + -
    Candidate Region/Gene (85)   Genome‑Wide Association Study (14)  
  • Variant type: + -
    SNP « 
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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
    rs5746136 SOD2 — 0.354 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs5746133 SOD2 — 0.466 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs4880 SOD2 — 0.552 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs8192287 SOD3 — 0.955 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs699473 SOD3 — 0.613 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs17881426 SOD3 — 0.425 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs1007991 SOD3 — 0.679 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs2536512 SOD3 — 0.942 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs8192291 SOD3 — 0.144 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs8192290 SOD3 — 0.428 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs13306703 — — 0.764 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs769449 APOE 0.70 0.018 1,089 vs 736 1,613 vs 1,104 Danish, German 92-93 Danish, 95–110 German G — — 22234866
    rs1801274 FCGR2A — 0.05 408 vs 446 vs 454 — German 100–110/ mean101.3 (SNP is His/Arg) — Candidate Region/Gene 16893392
    rs7539614 FOXO6 1.02 0.739 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs7547654 FOXO6 1.08 0.2 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs11581271 FOXO6 0.91 0.131 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs1317558 FOXO6 1.11 0.257 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs1317557 FOXO6 1.04 0.824 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs6693260 FOXO6 0.98 0.824 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs4660532 FOXO6 0.93 0.224 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs6690527 FOXO6 1.01 0.867 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs11209971 FOXO6 0.94 0.336 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs4660192 FOXO6 0.97 0.663 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs2721047 FOXO1A 0.98 0.177 1447 vs 1029 (initial) 166 vs 216 (Italian) (replication) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs2755209 FOXO1 0.98 0.77 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494

    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

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