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 (344)   No Age Effect (382)  
  • Study type: + -
    Candidate Region/Gene « 
  • Variant type: + -
    SNP (375)   Locus (3)   Haplotype (53)   Other (1)   STR (11)   Deletion (5)   CNV (1)    (1)   VNTR (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
    rs1042718-rs1042719 ADRB2 0.63 1.86e-05 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 G-C A-C Candidate Region/Gene 23020224
    rs2053044 ADRB2 — 0.138 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs1042713 ADRB2 — 0.149 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs1042714 ADRB2 — 0.558 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs2877709 ADCY5 — 0.767 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    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
    rs4677882 ADCY5 — 0.999 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs4482616 ADCY5 — 0.398 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs2291727 ADCY6 — 0.003 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs5749998 MAPK1 — 0.152 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs2266968 MAPK1 — 0.048 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs1892848 MAPK1 — 0.218 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs5999521 MAPK1 — 0.218 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — Candidate Region/Gene 23020224
    rs10047589 TXNRD1 1.46 0.043 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 G — Candidate Region/Gene 22406557
    rs207444 XDH — 0.046 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 G - Unsure — 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
    rs2509049 H2AFX 0.63 0.017 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
    rs705649 XRCC5 — 0.029 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 - Unsure — Candidate Region/Gene 22406557
    Met410Val SHC1 — 0.192 730 563 Human 85+ Met — Candidate Region/Gene 15036421
    rs770087 DUSP6 1.53 0.002 386 vs 410 541 vs 469 German 100 to 110, mean age = 101.3 C — Candidate Region/Gene 20800603
    rs2301582 NALP1 1.30 0.011 386 vs 410 541 vs 469 German 100 to 110, mean age = 101.3 C — Candidate Region/Gene 20800603
    rs648802 PERP 1.29 0.012 386 vs 410 541 vs 469 German 100 to 110, mean age = 101.3 C — Candidate Region/Gene 20800603
    rs662 PON1 — 0.04 1265 vs 582 541 total Danish 93 R Q Candidate Region/Gene 15241482

    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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