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 (1027)   No Age Effect (543)  
  • Study type: + -
    GWAS (2)   ‑ (27)   Candidate Region/Gene (784)   Meta‑Analysis (38)   Complete Mitochondrial Genome (2)   Whole‑Genome Linkage Scan (1)   Genome‑Wide Association Study (710)   Mitochondrial Haplogroup (36)   Mitochondrial genome (3)  
  • Variant type: + -
    SNP (572)   Locus (5)   Haplotype (87)   Other (1)   STR (11)   Deletion (5)   CNV (1)    (1)   VNTR (1)  
    • 1 2 3 4 5 6 7 8 9 10 11 12
    13 14 15 16 17 18 19 20 21 X Y MT
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    Populations | Study Types | Variant Types


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    polymorphism factor odds ratio pvalue initial number replication number Population age of cases shorter lived allele longer lived allele study type reference
    rs12865518 FOXO1 1.07 0.307 1447 vs 1029 (German) 166 vs 216 (Italian) German — — — Candidate Region/Gene 21388494
    rs2721069 FOXO1 0.93 0.251 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs2755213 FOXO1 0.95 0.626 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs2701880 FOXO1 0.83 0.12 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs2951787 FOXO1 1.03 0.6 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs2984121 FOXO1 1.05 0.178 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs2721044 FOXO1 0.90 0.097 1447 vs 1029 (German) 166 vs 216 (Italian) German — — — Candidate Region/Gene 21388494
    rs4943794 FOXO1 0.93 0.313 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs1986649 FOXO1 0.92 0.229 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs17630266 FOXO1 1.11 0.51 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs12876443 FOXO1 1.00 0.989 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs7981045 FOXO1 1.06 0.349 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs9603776 FOXO1 1.05 0.778 1447 vs 1029 (German) 166 vs 216 (Italian) German Mean age 98.8 — — Candidate Region/Gene 21388494
    rs9530108 NBEA 1.26 0.00112398 801 vs 914 — Caucasian Median age 104 G A Genome-Wide Association Study 22279548
    rs7319813 PIG38 1.39 0.000391694 801 vs 914 — Caucasian Median age 104 G A Genome-Wide Association Study 22279548
    rs7318601 PIG38 1.44 0.000508958 801 vs 914 — Caucasian Median age 104 G A Genome-Wide Association Study 22279548
    rs1805097 IRS2 2.03 0.0003 144 vs 418 — Italian 85-100 years old non-AA AA Candidate Region/Gene 19887537
    rs1207362 KL 0.63 0.0001 1089 vs 736 1613 vs 1104 Danish 92-93 years old A C Candidate Region/Gene 22406557
    rs9517320 STK24 — 0.00204 1173 vs 570 — American 85-100 — C Genome-Wide Association Study 22533364
    rs9557276 CLYBL 1.33 4.6512e-05 801 vs 914 — Caucasian Median age 104 A C Genome-Wide Association Study 22279548
    R353Q F7 — 0.045 224 vs 441 — Ashkenazi Jewish 75 A G Candidate Region/Gene 15621215
    rs17702471 GPC6 1.16 0.000147857 801 vs 914 — Caucasian Median age 104 A G Genome-Wide Association Study 22279548
    rs2755209 FOXO1 0.80 0.0046 761 vs 1056 350 vs 350 Chinese mean age 102.3 C T Candidate Region/Gene 19793722
    rs2755213 FOXO1 0.75 7.4e-05 761 vs 1056 350 vs 350 Chinese mean age 102.3 C T Candidate Region/Gene 19793722
    rs4148544 ABCC4 — 0.00977 1173 vs 570 — American 85-100 — T Genome-Wide Association Study 22533364

    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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