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


    LVDB_word_cloud.png
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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
    rs7896005 SIRT1 — 0.0056 224 vs 293 170 vs 220 Caucasian Range: 90-103 A — Candidate Region/Gene 21972126
    rs1042522 TP53 0.88 0.005 9219 participants (Copenhagen City Heart Study) — Danish Range: 20-95 G — Candidate Region/Gene 18256523
    rs429358, rs7412 APOE — 0.0212 60 vs 89 — African European Range: 20-59 — — Candidate Region/Gene 20569235
    K153R MSTN 3.48 0.001 156 vs 384 79 vs 316 (unelated Italian cohort) Spaniard Range : 100-111 K R Candidate Region/Gene 23354683
    Arg 213 ->His SULT1A1 — 0.017 Total 165 — Nigerian, Caucasian range 17- 90 SULT1A1*2 — — 9854023
    APOE e2,e3,e4 APOE — 0.05 185 vs 486 — Finn Over 100 E4 e2 Candidate Region/Gene 8018664
    rs662 PON1 — 1.0 579 vs 308 — Italian Over 100 G A Candidate Region/Gene 12082503
    rs854560 PON1 — 1.0 579 vs 308 — Italian Over 100 — — Candidate Region/Gene 12082503
    192/55 loci PON1 — 0.01 579 vs 308 — Italian Over 100 — R+M+ Candidate Region/Gene 12082503
    rs4646994 ACE — 0.04 227 Uighur individuals, 108 Kazakh individuals, and 89 Han individuals — Chinese Old: 59-70, Very old 90-113 I (insertion) — Candidate Region/Gene 11773214
    rs1887922 IDE 2.02 0.0004 829 vs 1033 — Australian, Caucasian Mixed — — Candidate Region/Gene 18448515
    rs2251101 IDE 1.88 0.0011 829 vs 1033 — Australian, Caucasian Mixed — — Candidate Region/Gene 18448515
    AAT M/Z/S AAT 0.21 0.0001 143 vs 255 — Minimum age 99 M, S — Candidate Region/Gene 17048073
    rs28940577 MEFV 3.70 0.004 68 vs 196 vs 121 — Human Minimum age 99 G A Candidate Region/Gene 16387839
    Chromosome 4 at D4S1564 Chromosome 4 at D4S1564 — 0.044 303 — Human Minimum age 98 for one sibling (of sibship) — — Genome-Wide Association Study 11526246
    3p24-22 3p24-22 — 0.037 3953 — American Minimum age 98 — — Genome-Wide Association Study 20824210
    G1691A F5 — 0.004 432 vs 184 — Polish Minimum age 95 A G Candidate Region/Gene 20720309
    rs5882 CETP — 0.05 300 vs 320 vs 258 — Ashkenazi Jewish Minimum age 95 AA, AG GG Candidate Region/Gene 15621216
    ADA genotypes ADA — 0.003 62 vs 64 vs143 vs 272 — Italian Minimum age 90 ADA*2 non-ADA*2 Candidate Region/Gene 20174870
    GH1 "intron SNP" GH1 — 0.019 866 — Dutch Minimum age 85 — — Candidate Region/Gene 15771611
    mtDNA haplogroups mtDNA — 0.027 138 — Spaniard Minimum age 85 non-J J Mitochondrial Haplogroup 18931934
    ACE D/I ACE — 0.02 689 — Danish Minimum age 73 II DI, DD Candidate Region/Gene 12547486
    rs4646994 ACE — 0.05 4000 — Chinese Minimum age 65 DD — Candidate Region/Gene 22456784
    D4a mtDNA haplogroups — 0.05 112 vs 96 — Japanese Minimum age 105 non-D4a D4a Complete Mitochondrial Genome 18545700
    APOE e2/e3/e4 APOE 4.40 0.02 179 — Finn Minimum age 104 e3, e4 e2 Candidate Region/Gene 11213279
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    • 25 of 1635 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