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
    rs189037 ATM — 0.004 875 vs 886 — Chinese mean 94.6 — CT Candidate Region/Gene 20816691
    rs189037 ATM 1.45 0.12 128 vs 150 — Italian Mean age 98.7 +/- 5.1 — — Candidate Region/Gene 22960875
    rs189037 ATM 1.85 0.037 67 vs 61 — Italian Centenarians — — Candidate Region/Gene 22960875
    rs189037 ATM 1.85 0.028 128 vs 150 — Italian — — — - 22960875
    rs189037 (genotype) ATM — 0.004 875 (280 m, 595 f) vs 886 (491 m, 395 f) — Chinese Mean age 94,6, healthy — CT (Article); GA (ENSEMBL) Candidate Region/Gene 20816691
    rs3842755 INS 1.79 0.0001 1089 vs 736 1613 vs 1104 Danish 92-93 years old C A Candidate Region/Gene 22406557
    many SNPs INS — 0.05 1321 vs 1140 — Italian Mean age 101.9 (southern Italian), 101.0 (northern-central Italian), 104.41 (German), 103.1 (French) — — Candidate Region/Gene 19367319
    rs3842755 INS 1.79 0.0001 1089 vs 736 1613 vs 1104 Danish 92.2–93.8 (mean age 93.2 C — Candidate Region/Gene 22406557
    DRD4 DRD4 — 1.0 224 vs 441 — Ashkenazi Jewish 75 — — Candidate Region/Gene 15621215
    DRD4 7R allele DRD4 — 3.5e-08 310 vs 2909 — European mean age 95.2 years — — Candidate Region/Gene 23283341
    rs2542052 APOC3 — 0.0001 Centenarians (n = 213) their offspring (n = 216) vs 258 — Ashkenazi Jewish Mean age 98.2 A — — 16602826
    rs2542052 APOC3 — 0.0001 213 old vs 216 offspring vs 258 controls — Ashkenazi Jewish 100+ A — Candidate Region/Gene 16602826
    T-455C APOC3 — 0.005 183 vs 110 — Russian 70-106 T C Candidate Region/Gene 11193221
    APOC3 T455C APOC3 — 0.05 147 elderly individuals (70–106 years old) — Russian mean age: 84.6 years — — Candidate Region/Gene 11193221
    APOC3-SstI-RFLP (3'UTR, 3238 nt) APOC3 — 0.05 229 vs 571 — Calabrian 81–109 (median 101) — — Candidate Region/Gene 12556235
    rs2542052 APOC3 — 0.0001 Centenarians (n = 213) their offspring (n = 216) vs 258 — Ashkenazi Jewish mean age 98.2 A — Candidate Region/Gene 16602826
    rs2542052 APOC3 — 0.001 213 old vs 216 offspring vs 258 controls — Ashkenazi Jewish — A — Candidate Region/Gene 16602826
    rs2542052 APOC3 — 0.0001 213 old vs 216 offspring vs 258 controls — Ashkenazi Jewish — A — Candidate Region/Gene 16602826
    APOA1-MspI-RFLP A/P alleles APOA1 — 0.045 413 vs. 571 — Italian median age 101 A P Candidate Region/Gene 12556235
    APOA1-MspI-RFLP (−75) APOA1 — 0.016 229 vs 571 — Calabrian 81–109 (median 101) A (=Absence) — Candidate Region/Gene 12556235
    apoAIV(360:His) APOA4 — 0.005 119 (see notes) vs 264 — French 74.29 ∓ 8.46 ApoAIV-1_x000D_, by the order of the sentence - I'm assuming it's Glutamine = G — Candidate Region/Gene 9533408
    HinfI347 APOA4 — 0.05 71 vs 100 — Italian mean102.3 years — — Candidate Region/Gene 9622284
    rs147610191 APOA4 — 0.05 229 vs 571 — Calabrian 81–109 (median 101) — — Candidate Region/Gene 12556235
    rs675 APOA4 — 0.05 58 vs 100 — Italian Mean age 102,3 — A (NCBI) Candidate Region/Gene 9622284
    many SNPs IGF2 — 0.05 1321 vs 1140 — Italian Mean age 101.9 (southern Italian), 101.0 (northern-central Italian), 104.41 (German), 103.1 (French) — — Candidate Region/Gene 19367319
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    • 25 of 81 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