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 (153)   No Age Effect (209)  
  • Study type: + -
    Candidate Region/Gene « 
  • Variant type: + -
    SNP « 
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    Populations | Study Types | Variant Types


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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
    −1190G/A VEGFA 1.39 0.014 166 vs 324 — Italian 85-99 (mean 89.8±2.8) G A Candidate Region/Gene 17574707
    XbaI APOB 1.30 0.03 191 (case) vs 53 — Chinese > 90 baseline, Mean age 97 +/- 3 — X+X+ Candidate Region/Gene 17393087
    SNP at chromosome location 36750804 CDKN1A 0.83 0.414 184 vs 184 — Italian 100 — — Candidate Region/Gene 20126416
    rs9861425 ADCY5 — 0.251 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs9844212 ADCY5 — 0.901 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs9603776 FOXO1 1.05 0.778 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs9470367 CDKN1A 1.01 0.949 184 vs 184 — Italian 100 — — Candidate Region/Gene 20126416
    rs9462209 CDKN1A 1.25 0.228 184 vs 184 — Italian 100 — — Candidate Region/Gene 20126416
    rs9456497 IGF2R 1.42 0.005 1089 vs 736 1613 vs 1104 Danish 92-93 years old A G Candidate Region/Gene 22406557
    rs9456497 IGF2R 1.42 0.005 1089 vs 736 1613 vs 1104 Danish 92.2–93.8 (mean age 93.2) A — Candidate Region/Gene 22406557
    rs9400239 FOXO3 1.38 0.0007 388 vs 371 535 vs 553 German mean age 98.4 years — — Candidate Region/Gene 19196970
    rs9340799 ESR1 — 1.0 148 vs 414 — Polish mean age 101.1 — — Candidate Region/Gene 20599431
    rs9340799 ESR1 — 0.22 108 vs 85 — Italian 90+ — — Candidate Region/Gene 20819792
    rs9282861 SULT1A1 — 0.017 68 vs 49 — American, Caucasian 70-99 — GG Candidate Region/Gene 9854023
    rs915179 LMNA — 0.014 873 vs 443 (initial) New England Centenarian Study: 545 vs 193; French: 557 vs 546; Southern Italian Centenarian Study: 455 vs 450; Ashkenazi Jewish: 354 vs 348 (replication) American, Caucasian Mean age 101.5 — — Candidate Region/Gene 22340368
    rs876581 CDKN1A 0.58 0.103 184 vs 184 — Italian 100 — — Candidate Region/Gene 20126416
    rs861539 XRCC3 — 0.97 430 vs 290 — British Mean age 70 — — Candidate Region/Gene 16518718
    rs8192678 PPARGC1A — 0.469 122 vs 122 — Japanese mean age 106.8 — — Candidate Region/Gene 15582274
    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
    rs8192287 SOD3 — 0.955 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs8052394 MT1a 2.16 0.0002 151 vs 100 — Italian Mean age 91.4 +/- 4.1 — A Candidate Region/Gene 16955215
    rs8031 SOD2 — 0.186 1612 vs 1104 — German 90+ — — Candidate Region/Gene 24163049
    rs800140 TSPAN32 — 0.0081 1600 samples (cases and controls combined) — German, Italian — — — Candidate Region/Gene 19367319
    rs7981045 FOXO1 1.06 0.349 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    • Page 1 of 15
    • 25 of 375 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