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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    variants.jpg
    polymorphism factor odds ratio pvalue initial number replication number Population age of cases shorter lived allele longer lived allele study type reference
    rs6459623 IBRDC2 — 0.00015 1345 cohort + 1087 offspring — American — — — Genome-Wide Association Study 17903295
    LPA isoform LPA — 0.05 84 (cases) vs 517 — Japanese 80+ Lp(a)F, Lp(a)B — Candidate Region/Gene 11269751
    rs697739 ATXN1 0.59 8.97e-05 410 vs 553 — Italian 90–109 — — Genome-Wide Association Study 21612516
    rs1800629 TNF — 0.019 747 — Italian 19-110 A G Candidate Region/Gene 18511747
    rs1800629 TNF — 1.0 174 vs 224 — Italian >100 — — Candidate Region/Gene 12676903
    HLA-A phenotype HLA-A 1.95 0.002 201 vs 211 — Chinese 22 centenarians + 179 nonagenarians (mean age 93 ±1.04) A9 A30 Candidate Region/Gene 9147371
    HLA-C phenotype HLA-C 0.49 0.02 201 vs 211 — Chinese >93 Cw3, Cw6. Cw7 — Candidate Region/Gene 9147371
    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
    rs1044891 FOXO3A 1.17 0.14 298 vs 603;279 vs 797;383 vs 363 — Caucasian 95.3 ± 2.2_x000D_;+M19994.5 ± 2.1_x000D_;mean 97.7, 95– 113 — — Candidate Region/Gene 19489743
    rs1935949 FOXO3A 1.46 0.019 299 vs 603;279 vs 797;383 vs 363 — Caucasian 95.3 ± 2.2_x000D_;+M19994.5 ± 2.1_x000D_;mean 97.7, 95– 114 T — Candidate Region/Gene 19489743
    rs2153960 FOXO3A 1.16 0.019 300 vs 603;279 vs 797;383 vs 363 — Caucasian 95.3 ± 2.2_x000D_;+M19994.5 ± 2.1_x000D_;mean 97.7, 95– 115 — — Candidate Region/Gene 19489743
    rs3778588 FOXO3A 1.22 0.023 301 vs 603;279 vs 797;383 vs 363 — Caucasian 95.3 ± 2.2_x000D_;+M19994.5 ± 2.1_x000D_;mean 97.7, 95– 116 — — Candidate Region/Gene 19489743
    rs4946935 FOXO3A 1.48 0.018 302 vs 603;279 vs 797;383 vs 363 — Caucasian 95.3 ± 2.2_x000D_;+M19994.5 ± 2.1_x000D_;mean 97.7, 95– 117 A — Candidate Region/Gene 19489743
    rs9486902 FOXO3A 1.18 0.073 303 vs 603;279 vs 797;383 vs 363 — Caucasian 95.3 ± 2.2_x000D_;+M19994.5 ± 2.1_x000D_;mean 97.7, 95– 118 — — Candidate Region/Gene 19489743
    rs9486913 FOXO3A 1.18 0.053 304 vs 603;279 vs 797;383 vs 363 — Caucasian 95.3 ± 2.2_x000D_;+M19994.5 ± 2.1_x000D_;mean 97.7, 95– 119 — — Candidate Region/Gene 19489743
    rs1799945 HFE — 0.008 57 vs 60 — Italian 100-105 — — Candidate Region/Gene 12714263
    rs1800629 TNF — 1.0 93 vs 100 — Irish 80-97 years — — Candidate Region/Gene 12714268
    rs909253 TNF — 1.0 93 vs 100 — Irish 80-97 years — — Candidate Region/Gene 12714268
    rs2253310 FOXO3 1.35 7.9e-05 761 vs 1056 350 vs 350 Chinese mean age 102.3 C G Candidate Region/Gene 19793722
    rs2802292 FOXO3 1.36 2.9e-05 761 vs 1056 350 vs 350 Chinese mean age 102.3 G T Candidate Region/Gene 19793722
    rs4946936 FOXO3 1.40 1.8e-05 761 vs 1056 350 vs 350 Chinese mean age 102.3 T C Candidate Region/Gene 19793722
    rs9340799 ESR1 — 1.0 148 vs 414 — Polish mean age 101.1 — — Candidate Region/Gene 20599431
    -351A/G ESR1 — 0.05 148 vs 414 — Polish 99.6-107.2; mean= 101.1±1.2 — — Candidate Region/Gene 20599431
    -397T/C ESR1 — 0.06 149 vs 414 — Polish 99.6-107.2; mean= 101.1±1.3 — — Candidate Region/Gene 20599431

    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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