Genetic and clinical determinants of telomere length

Abstract

Many epidemiologic studies have identified important relationships between leukocyte telomere length (LTL) with genetics and health. Most of these studies have been significantly limited in scope by focusing predominantly on individual diseases or restricted to GWAS analysis. Using two large patient populations derived from Vanderbilt University and Marshfield Clinic biobanks linked to genomic and phenomic data from medical records, we investigated the inter-relationship between LTL, genomics, and human health. Our GWAS confirmed 11 genetic loci previously associated with LTL and two novel loci in SCNN1D and PITPNM1. PheWAS of LTL identified 67 distinct clinical phenotypes associated with both short and long LTL. We demonstrated that several diseases associated with LTL were related to one another but were largely independent from LTL genetics. Age of death was correlated with LTL independent of age. Those with very short LTL (<-1.5 standard deviation [SD]) died 10.4 years (p < 0.0001) younger than those with average LTL (±0.5 SD; mean age of death = 74.2 years). Likewise, those with very long LTL (>1.5 SD) died 1.9 years (p = 0.0175) younger than those with average LTL. This is consistent with the PheWAS results showing diseases associating with both short and long LTL. Finally, we estimated that the genome (12.8%) and age (8.5%) explain the largest proportion of LTL variance, whereas the phenome (1.5%) and sex (0.9%) explained a smaller fraction. In total, 23.7% of LTL variance was explained. These observations provide the rationale for expanded research to understand the multifaceted correlations between TL biology and human health over time, leading to effective LTL usage in medical applications.

Keywords: GWAS; PheWAS; aging; telomere.

Figure 1

Visual summary of GWAS and PheWAS results Manhattan plot of (A) GWAS and (B) PheWAS results. Red lines show genome-wide (p = 1E−08) and phenome-wide (p = 3.9E−05) significance. Blue line designates suggestive significance (p = 1E−06). We refer to p as the probability (p) value.

Figure 2

Analysis of sentinel phenotypes (A) Forest plot showing effect size and 95% confidence intervals of the 67 identified sentinel phenotypes. (B) Dependency network among sentinel phenotypes. First row phenotypes are associated with LTL independently from other phenotypes. Second and third row phenotypes are associated with LTL dependent on above phenotypes.

Figure 3

Age of death is associated with telomere length Mean age of death with 95% confidence intervals for baseline age-adjusted LTL (blue) and phenome-adjusted age-adjusted LTL (orange). LTL values were binned according to SD (very short: SD < −1.5, short: −1.5 < SD < −0.5, average: −0.5 < SD < 0.5, long: 0.5 < SD < 1.5, very long: SD > 1.5). Significance between baseline bins is shown (N/S, not significant; ∗ p < 0.05, ∗∗∗ p < 0.0001). We refer to p as the probability (p) value.

Figure 4

LTL variance explained by age, sex, phenome, and genome Shown is the variance explained by GWAS and PheWAS results.