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: + -
    No Age Effect « 
  • Study type: + -
    Candidate Region/Gene « 
  • Variant type: + -
    SNP (209)   Haplotype (17)   Other (1)   STR (7)   Deletion (1)  
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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
    rs2275075 LMNA — 0.54 873 vs 443 New England Centenarian Study: 545 vs 193; French: 557 vs 546; Southern Italian Centenarian Study: 455 vs 450; Ashkenazi Jewish: 354 vs 348 American, Caucasian Mean age 101.5 — — Candidate Region/Gene 22340368
    rs740746 ADRB1 — 0.556 384 vs 384 579 vs 644 Chinese Mean age 102.1±0.20 — — 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
    rs2877709 ADCY5 — 0.767 384 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
    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
    rs5749998 MAPK1 — 0.152 384 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
    length (STR polymorphism) TH — 1.0 196 vs 358 471 vs 462 German (in replication) 96-110 years — — Candidate Region/Gene 21407269
    rs17630266 FOXO1 — 1.0 761 vs 1056 350 vs 350 Chinese mean age 102.3 — — Candidate Region/Gene 19793722
    rs2721047 FOXO1A 0.98 0.177 1447 vs 1029 (initial) 166 vs 216 (Italian) (replication) German Mean age 98.8 — — Candidate Region/Gene 21388494
    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
    • Page 1 of 16
    • 25 of 382 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