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
    G477T SIRT3 — 0.0272 801 — Italian 120 subject aged 100 or older GT TT Candidate Region/Gene 14580859
    APOA1-MspI-RFLP A/P alleles APOA1 — 0.045 413 vs. 571 — Italian median age 101 A P Candidate Region/Gene 12556235
    HRAS1 3'VNTR HRAS 1.13 0.551 234 vs 467 — Italian Minimum age 100 a3 non-a3 Candidate Region/Gene 11943467
    rs11039149 NR1H3 — 0.015 599 — Dutch 85 years haplotype 1 haplotype 2 Candidate Region/Gene 17452725
    rs651922 DCPS 1.19 4.75e-05 801 vs 914 — Caucasian Median age 104 A G Genome-Wide Association Study 22279548
    rs1470196 KIAA1377 1.33 0.000498694 801 vs 914 — Caucasian Median age 104 A G Genome-Wide Association Study 22279548
    rs216493 PLEKHA7 1.10 0.001543457 801 vs 914 — Caucasian Median age 104 A G Genome-Wide Association Study 22279548
    rs7127390 IGSF4 1.13 0.001091248 801 vs 914 — Caucasian Median age 104 A G Genome-Wide Association Study 22279548
    rs4237774 OR56A1 1.18 0.000637699 801 vs 914 — Caucasian Median age 104 A G Genome-Wide Association Study 22279548
    rs7103504 CNTN5 — 4.39e-05 1364 — American, British Age range 50-108; mean age at death 80.2 A G Genome-Wide Association Study 22445811
    rs7952321 OR5AS1 — 4.68e-05 1364 — American, British Age range 50-108; mean age at death 80.2 T G Genome-Wide Association Study 22445811
    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
    rs189037 ATM — 0.004 875 vs 886 — Chinese mean 94.6 — CT Candidate Region/Gene 20816691
    T-455C APOC3 — 0.005 183 vs 110 — Russian 70-106 T C Candidate Region/Gene 11193221
    rs739401 CARS — 0.00154 1173 vs 570 — American 85-100 — C Genome-Wide Association Study 22533364
    rs507879 CASP5 — 1.4e-05 510 vs 549 — Russian 75–103 AG AA, GG Candidate Region/Gene 20434535
    A/G IGF2 — 0.063 (150 m, 74 f) vs (121 m, 320 f) — Ashkenazi Jewish Mean age 75 — A, AA Candidate Region/Gene 15621215
    rs675 APOA4 — 0.05 58 vs 100 — Italian Mean age 102,3 — A (NCBI) Candidate Region/Gene 9622284
    rs3842755 INS 1.79 0.0001 1089 vs 736 1613 vs 1104 Danish 92-93 years old C A Candidate Region/Gene 22406557
    rs10502005 MMP20 1.48 2.42e-05 403 vs 1670 3746 vs 5912 Dutch Mean age 94 — A Genome-Wide Association Study 21418511
    rs894558 NAV2 1.13 0.004524209 801 vs 914 — Caucasian Median age 104 G A Genome-Wide Association Study 22279548
    rs4755936 SYT13 1.19 0.003578524 801 vs 914 — Caucasian Median age 104 G A Genome-Wide Association Study 22279548
    rs610932 MS4A6A — 0.176 1364 — American, British Age range 50-108; mean age at death 80.2 C A Candidate Region/Gene 22445811
    rs3851179 PICALM — 0.227 1364 — American, British Age range 50-108; mean age at death 80.2 G A Candidate Region/Gene 22445811
    rs680109 GRIA4 — 2.52e-05 1364 — American, British Age range 50-108; mean age at death 80.2 C A Genome-Wide Association Study 22445811
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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