Genetics of Human Longevity From Incomplete Data: New Findings From the Long Life Family Study

Abstract

The special design of the Long Life Family Study provides a unique opportunity to investigate the genetics of human longevity by analyzing data on exceptional lifespans in families. In this article, we performed two series of genome wide association studies of human longevity which differed with respect to whether missing lifespan data were predicted or not predicted. We showed that the use of predicted lifespan is most beneficial when the follow-up period is relatively short. In addition to detection of strong associations of SNPs in APOE, TOMM40, NECTIN2, and APOC1 genes with longevity, we also detected a strong new association with longevity of rs1927465, located between the CYP26A1 and MYOF genes on chromosome 10. The association was confirmed using data from the Health and Retirement Study. We discuss the biological relevance of the detected SNPs to human longevity.

Figure 1.

Survival functions (conditional on survival to age 80) for the LLFS participants in comparison with 1900 and 1920 birth cohorts: (a) U.S. females; (b) U.S. males; (c) Danish females; (d) Danish males. The LLFS curves are shown by solid thick line with 95% confidence intervals indicated by solid thin lines. Dashed lines display population survival functions from corresponding cohort life tables: Social Security Administration (SSA) for USA and Human Mortality Database (HMD) for Denmark. The numbers after SSA and HMD show the respective birth cohort.

Figure 2.

(A) QQ-plot and (B) Manhattan plot. The results of GWAS of human longevity using the LLFS data on age at death for deceased individuals and data on predicted lifespan for censored individuals. The logistic regression model for related individuals in the GMMAT software package (11) with sex and country (DK, US) as observed covariates was used. Cases comprised individuals from the proband generation with lifespans (for deceased study subjects) or predicted lifespans (for study subjects with censored lifespans) ≥96 years (877 individuals). Controls comprised individuals from the offspring generation with age at death (for deceased study subjects) or attained age (for study subjects with censored lifespans) <75 years (2,462 individuals).

Figure 3.

(A) QQ-plot; (B) Manhattan plot. The results of GWAS of human longevity using observed LLFS data on lifespan. The logistic regression model for related individuals in the GMMAT software package (11) with sex and country (DK, US) as observed covariates was used. Cases comprised individuals from the proband generation with lifespans (for deceased subjects) or censored lifespans (for living study subjects, or for those who dropped out from the study) ≥96 years (723 individuals). Controls comprised individuals from the offspring generation whose age at death (for deceased study subjects) or attained age (for study subjects with censored lifespans) <75 years (2,462 individuals).

Figure 4.

QQ plots corresponding to analyses of predicted and observed data with different periods of follow-up. The results of the GWAS of human longevity obtained in the GMMAT analyses of unpredicted (left panels) and predicted (right panels) LLFS data on males and females combined for different durations of follow-up. The panels from the top to the bottom represent follow-up periods from baseline to 2010, 2011, 2013, and 2015, respectively.