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 « 
  • Study type: + -
    GWAS (2)   ‑ (8)   Candidate Region/Gene (344)   Meta‑Analysis (30)   Complete Mitochondrial Genome (1)   Genome‑Wide Association Study (607)   Mitochondrial Haplogroup (7)   Mitochondrial genome (3)  
  • Variant type: + -
    SNP (243)   Locus (3)   Haplotype (39)   STR (3)   Deletion (1)   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
    rs9397084 SYNE1 1.40 0.000104307 801 vs 914 — Caucasian Median age 104 A G Genome-Wide Association Study 22279548
    rs3804474 FLJ33708 1.22 0.000264519 801 vs 914 — Caucasian Median age 104 A G Genome-Wide Association Study 22279548
    rs2242653 BAT5 1.39 0.000314783 801 vs 914 — Caucasian Median age 104 G A Genome-Wide Association Study 22279548
    rs11153598 NT5DC1 1.06 0.00214039 801 vs 914 — Caucasian Median age 104 C A Genome-Wide Association Study 22279548
    rs2269475 AIF1 1.45 0.000435495 801 vs 914 — Caucasian Median age 104 G A Genome-Wide Association Study 22279548
    rs524533 NFKBIE 1.29 0.000732713 801 vs 914 — Caucasian Median age 104 G A Genome-Wide Association Study 22279548
    rs3019435 PARK2 1.41 0.001006354 801 vs 914 — Caucasian Median age 104 C A Genome-Wide Association Study 22279548
    HFE C282Y HFE — 7.2e-07 35 vs 106 — 91-105 (< 50 versus >90) C Y Candidate Region/Gene 11857056
    rs1799945 HFE — 0.008 57 vs 60 — Italian 100-105 — — Candidate Region/Gene 12714263
    rs4880 SOD2 — 0.009 224 vs 441 — Ashkenazi Jewish 75 C T Candidate Region/Gene 15621215
    rs1801270 CDKN1A 0.44 0.02 184 vs 184 — Italian 100 A C Candidate Region/Gene 20126416
    rs1059234 CDKN1A 0.47 0.026 184 vs 184 — Italian 100 T C Candidate Region/Gene 20126416
    HLA-DRB1 haplotypes HLA-DRB1 — 0.004 120 vs 129 — Okinawan Mean age 102.3 +/- 1.9 years non-DRB1*0401 alleles DRB1*0401 Candidate Region/Gene 9389323
    HLA-DQB1 haplotypes HLA-DQB1 — 0.0002 120 vs 129 — Okinawan Mean age 102.3 +/- 1.9 years non-DQB1*0503 alleles DQB1*0503 Candidate Region/Gene 9389323
    HLA-DQA1 haplotypes HLA-DQA1 — 0.04 120 vs 129 — Okinawan Mean age 102.3 +/- 1.9 years non-HLA-DQA1*0101=0104 alleles HLA-DQA1*0101=0104 Candidate Region/Gene 9389323
    HLA-DQA1 haplotypes HLA-DQA1 — 0.038 120 vs 129 — Okinawan Mean age 102.3 +/- 1.9 years non-HLA-DQA1*05 alleles HLA-DQA1*05 Candidate Region/Gene 9389323
    HLA DRB1*18 HLA-DRB1 — 0.0266 77 vs 299 — 100 — — Candidate Region/Gene 20426625
    rs1008438 HSPA1A — 0.005 157 vs 62 — Danish 92.8 A — Candidate Region/Gene 16804002
    rs1061581 HSPA1L — 0.04 157 vs 62 — Danish 92.8 A — Candidate Region/Gene 16804002
    rs2234693 - rs2234693 ESR1 — 0.12 108 vs 85 — Italian 90+ — — Candidate Region/Gene 20819792
    rs9340799 ESR1 — 0.22 108 vs 85 — Italian 90+ — — Candidate Region/Gene 20819792
    rs1008438 HSPA1A 3.86 0.016 168 cases — Danish Mean age 92.8 +/- 0.4 А — Candidate Region/Gene 20388090
    rs1061581 HSPA1B 2.76 0.039 168 cases — Danish Mean age 92.8 +/- 0.4 А — Candidate Region/Gene 20388090
    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

    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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