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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    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
    rs1042522 TP53 0.57 0.006 100 very old vs 280 old vs 189 young — Italian 91+, 73-91 P — Candidate Region/Gene 23125046
    rs1042522 TP53 0.88 0.005 9219 participants (Copenhagen City Heart Study) — Danish Range: 20-95 G — Candidate Region/Gene 18256523
    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
    rs1042718 ADRB2 1.27 0.014 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 C A Candidate Region/Gene 23020224
    rs1042719 ADRB2 1.29 1.29 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 G C Candidate Region/Gene 23020224
    rs10459953 — — 0.522 321 vs 442 — Italian 89-107 — — Candidate Region/Gene 23572278
    rs1048310 — — 0.87 208 vs 399 — Japanese 95+ — — Candidate Region/Gene 23770741
    rs1059234 CDKN1A 0.47 0.026 184 vs 184 — Italian 100 T C Candidate Region/Gene 20126416
    rs1061170 CFH 1.78 0.005 491 with follow-up during 4 years — Finn >90 — TT Candidate Region/Gene 19000922
    rs1061581 HSPA1B — 0.05 191 vs 53 — Chinese >90 A G Candidate Region/Gene 19840767
    rs1061581 HSPA1B 2.76 0.039 168 cases — Danish Mean age 92.8 +/- 0.4 А — Candidate Region/Gene 20388090
    rs10737170 LMNA — 0.11 873 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
    rs1078892 FOXO1 0.96 0.589 1447 vs 1029 (German) 166 vs 216 (Italian) German — — — Candidate Region/Gene 21388494
    rs10811661 — — 0.13 213 vs 402 — Japanese 95+ — — Candidate Region/Gene 23770741
    rs10947623 CDKN1A 1.37 0.199 184 vs 184 — Italian 100 — — Candidate Region/Gene 20126416
    rs11039149 NR1H3 — 0.015 599 — Dutch 85 years haplotype 1 haplotype 2 Candidate Region/Gene 17452725
    rs11209971 FOXO6 0.94 0.336 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs11217184 CBL — 0.8 212 vs 396 — Japanese 95+ — — Candidate Region/Gene 23770741
    rs1130214 AKT1 0.97 0.544 2996 vs 1840 — Danish, German 92-110 — — Candidate Region/Gene 22929028
    rs1137100 LEPR — 0.026 128 vs 414 — Polish 100+ AA — Candidate Region/Gene 24549597
    rs1143634 IL1B — 0.53 250 vs 400 — Finn >90 — — Candidate Region/Gene 11640949
    rs11555236 SIRT3 — 0.03 357 — Italian 70+ — T Candidate Region/Gene 23839864
    rs11571461 RAD52 2.23 0.0001 1089 vs 736 1613 vs 1104 Danish 92-93 years old A G Candidate Region/Gene 22406557
    rs11571461 RAD52 2.23 0.0001 1089 vs 736 1613 vs 1104 Danish 92.2–93.8 (mean age 93.2) A — Candidate Region/Gene 22406557

    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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