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 (153)   No Age Effect (209)  
  • Study type: + -
    Candidate Region/Gene « 
  • Variant type: + -
    SNP « 
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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
    rs440446 APOE 1083.00 0.509 597 vs 1275 — Sichuan 90+ — — Candidate Region/Gene 24924924
    rs2280789 RANTES 8.80 0.03 104 vs 110 — Spaniard Mean age 89.5 C T Candidate Region/Gene 22265023
    rs6166 FSHR 4.21 0.036 114 vs 173 — Italian >/=90 Asn Ser Candidate Region/Gene 22985084
    rs1008438 HSPA1A 3.86 0.016 168 cases — Danish Mean age 92.8 +/- 0.4 А — Candidate Region/Gene 20388090
    rs422858 AGTR1 3.57 0.007 173 vs 376 — Italian 99-106 (mean 100.9±1.7) AG CC Candidate Region/Gene 22569962
    rs275653 AGTR1 3.57 0.007 173 vs 376 598 vs 422 Italian 99-106 (mean 100.9±1.7) A G Candidate Region/Gene 22569962
    rs5882 CETP 3.56 0.001 213 vs 258 — Ashkenazi Jewish 98,2 +/- 5,3 non-GG GG Candidate Region/Gene 14559957
    K153R MSTN 3.48 0.001 156 vs 384 79 vs 316 Italian, Spaniard 100–111 K — Candidate Region/Gene 23354683
    rs2107538 RANTES 3.20 0.029 104 vs 110 — Spaniard Mean age 89.4 A G Candidate Region/Gene 22265023
    rs13320360 MLH1 3.13 0.0036 1089 (see notes - follow-up study) 563 (see notes - follow-up study) Danish 92.2–93.8 (mean age 93.2) w/ 11.4 years follow-up A — Candidate Region/Gene 22406557
    rs1800896 IL10 3.10 0.0003 142 vs 153 — Mean age 67 AA GG Candidate Region/Gene 15466015
    rs1061581 HSPA1B 2.76 0.039 168 cases — Danish Mean age 92.8 +/- 0.4 А — Candidate Region/Gene 20388090
    rs26802 GHRL 2.34 0.032 1089 (see notes - follow-up study) 563 (see notes - follow-up study) Danish 92.2–93.8 (mean age 93.2) w/ 11.4 years follow-up A — Candidate Region/Gene 22406557
    rs11571461 RAD52 2.23 0.0001 1089 vs 736 1613 vs 1104 Danish 92-93 years old A G Candidate Region/Gene 22406557
    rs11571461 RAD52 2.23 0.0001 1089 vs 736 1613 vs 1104 Danish 92.2–93.8 (mean age 93.2) A — Candidate Region/Gene 22406557
    rs8052394 MT1a 2.16 0.0002 151 vs 100 — Italian Mean age 91.4 +/- 4.1 — A Candidate Region/Gene 16955215
    rs4746720 SIRT1 2.10 0.0001 223 vs 277 — Chinese Average age 93 CC, TT CT Candidate Region/Gene 23450480
    rs1805097 IRS2 2.07 0.04 144 vs 418 — Caucasian 85 to 104, mean age = 96 ± 4 C — Candidate Region/Gene 19887537
    rs3211994 NTLH1 1.99 0.0056 1089 vs 736 1613 vs 1104 Danish 92-93 years old G A Candidate Region/Gene 22406557
    rs3211994 NTHL1 1.99 0.0056 1089 vs 736 1613 vs 1104 Danish 92.2–93.8 (mean age 93.2) G — Candidate Region/Gene 22406557
    rs73598374 ADA 1.94 0.036 261 vs 144 — Italian 66-88 G*/G* A*+ Candidate Region/Gene 21865054
    rs4646 CYP19 1.90 0.04 108 vs 85 — Italian 90+ — T Candidate Region/Gene 20819792
    rs189037 ATM 1.85 0.037 67 vs 61 — Italian Centenarians — — Candidate Region/Gene 22960875
    rs13251813 WRN 1.84 0.0002 1089 vs 736 1613 vs 1104 Danish 92-93 years old G A Candidate Region/Gene 22406557
    rs3842755 INS 1.79 0.0001 1089 vs 736 1613 vs 1104 Danish 92-93 years old C A Candidate Region/Gene 22406557
    • Page 1 of 15
    • 25 of 375 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