Exonic Variants in Aging-Related Genes Are Predictive of Phenotypic Aging Status

Abstract

Background: Recent studies investigating longevity have revealed very few convincing genetic associations with increased lifespan. This is, in part, due to the complexity of biological aging, as well as the limited power of genome-wide association studies, which assay common single nucleotide polymorphisms (SNPs) and require several thousand subjects to achieve statistical significance. To overcome such barriers, we performed comprehensive DNA sequencing of a panel of 20 genes previously associated with phenotypic aging in a cohort of 200 individuals, half of whom were clinically defined by an "early aging" phenotype, and half of whom were clinically defined by a "late aging" phenotype based on age (65-75 years) and the ability to walk up a flight of stairs or walk for 15 min without resting. A validation cohort of 511 late agers was used to verify our results. Results: We found early agers were not enriched for more total variants in these 20 agingrelated genes than late agers. Using machine learning methods, we identified the most predictive model of aging status, both in our discovery and validation cohorts, to be a random forest model incorporating damaging exon variants [Combined Annotation-Dependent Depletion (CADD) > 15]. The most heavily weighted variants in the model were within poly(ADP-ribose) polymerase 1 (PARP1) and excision repair cross complementation group 5 (ERCC5), both of which are involved in a canonical aging pathway, DNA damage repair. Conclusion: Overall, this study implemented a framework to apply machine learning to identify sequencing variants associated with complex phenotypes such as aging. While the small sample size making up our cohort inhibits our ability to make definitive conclusions about the ability of these genes to accurately predict aging, this study offers a unique method for exploring polygenic associations with complex phenotypes.

A molecular index for biological age identified from the metabolome and senescence‐associated secretome in humans

“…The individuals that were physically active were classified as “healthy” agers. The remaining 98 were classified as “rapid” agers as they displayed poor walking ability despite being chronologically younger than the healthy agers (Breitbach et al., 2019; Figure 1a). Body bone mineral density and percentage lean body mass did not change significantly between these two groups suggesting the walking differences are not solely due to motor function (Figure S1).…”

Footprints in the Sand: Deep Taxonomic Comparisons in Vertebrate Genomics to Unveil the Genetic Programs of Human Longevity

“…While genetic studies have functionally shown an inverse effect of multiple age-related, disease-associated variants on lifespan regulation, the number of well-replicated longevity-conferring variants remains limited to variants in APOE ( ApoE ε2), and more recently, CDKN2A/B and IL6 (see Table 1 ). To date, studies in humans have been hampered by the specific phenotype definitions used, sample sizes of the extreme phenotypes, and modest heritability of the longevity-related traits ( Breitbach et al, 2019 ). This is due to the complex interplay of biological and social factors involved in human aging, as well as the limited power of GWAS, which require sampling thousands of subjects to achieve statistical significance ( Breitbach et al, 2019 ).…”

“…To date, studies in humans have been hampered by the specific phenotype definitions used, sample sizes of the extreme phenotypes, and modest heritability of the longevity-related traits ( Breitbach et al, 2019 ). This is due to the complex interplay of biological and social factors involved in human aging, as well as the limited power of GWAS, which require sampling thousands of subjects to achieve statistical significance ( Breitbach et al, 2019 ). Genetic studies of aging have also been hindered by an inconsistent use of definitions of aging (reviewed in Baghdadi et al, 2020 ).…”

“…Similarly, Gierman et al (2014) reported of an individual that despite having a pathogenic variant lived to an age 110 suggesting again a protective mechanism. More recently, Breitbach et al (2019) sequenced the coding regions of 20 “aging” genes in a cohort of 200 individuals. Based on their physical abilities, these individuals were grouped into “early aging” and “late aging” subsets.…”

TOMM40 genetic variants associated with healthy aging and longevity: a systematic review

“…In the recent past, longevity studies have shifted to the study of phenotypic age. These studies proposed methods to identify reliable genetic biomarkers such as DNA methylation and leukocyte telomere length [ 3 , 4 ] or exonic and non-coding single nucleotide polymorphism (SNP) variants [ 5 ] as surrogate measures to assess an individual’s healthy life expectancy. Many of these genetic factors were tested on mouse models; and the results suggested a close interconnection between genome maintenance and the underlying biological mechanisms of aging [ 6 ].…”