The genetics of human ageing

Abstract

The past two centuries have witnessed an unprecedented rise in human life expectancy. Sustaining longer lives with reduced periods of disability will require an understanding of the underlying mechanisms of ageing, and genetics is a powerful tool for identifying these mechanisms. Large-scale genome-wide association studies have recently identified many loci that influence key human ageing traits, including lifespan. Multi-trait loci have been linked with several age-related diseases, suggesting shared ageing influences. Mutations that drive accelerated ageing in prototypical progeria syndromes in humans point to an important role for genome maintenance and stability. Together, these different strands of genetic research are highlighting pathways for the discovery of anti-ageing interventions that may be applicable in humans.

Fig. 1 |. Genetic overlap between age-related chronic diseases and parental longevity , based on correlations between whole-genome association results.

Genetic correlations are from linkage disequilibrium score regression methods using available genome-wide association study summary statistics^,,,,,,,,,. Statistically significant correlations are indicated with an asterisk (single for nominal P < 0.05 significance, double indicates significant after Bonferroni correction for 36 tests in this analysis). The diseases and parental lifespans are ordered by similarity in patterns of genetic correlations using hierarchical clustering (see Supplementary Table 3 for details).

Fig. 2 |. Selected loci with correlated variants associated with three or more age-related diseases or lifespan.

Nine loci were identified as hot spots for at least three major age-related diseases or lifespan in genome-wide association studies (GWAS) that included multiple correlated (R² > 0.6) genetic variants^,,,,,,,,, (see Supplementary Tables 4 and 5 for details). The lipid-related variants LPA, LDLR and APOE were excluded for simplicity. Genes are shown on the left, with each ‘link’ to a disease on the right indicating a GWAS-identified signal. Lifespan refers to parental lifespan. Circos Table Viewer was used for visualization. AD, Alzheimer disease; CAD, coronary artery disease; CKD, chronic kidney disease; OA , osteoarthritis; T2DM, type 2 diabetes mellitus.

Fig. 3 |. Disease-associated genetic variants in the 9p21.3 locus by effect size of association with parental lifespan.

LocusZoom plot of known disease-associated variants in the 9p21.3 locus, which harbours the genes CDKN2A (encodes p16^ink4a), CDKN2B (encodes p15^ink4b) and CDKN2B-AS1 (encodes the long non-coding RNA ANRIL). Genetic variants are labelled with the traits they are reported to be associated with in published genome-wide association studies (GWAS) (see Supplementary Table 6 for details). The y-axis shows the association (−log₁₀ P value) with parental lifespan from the 2019 UK Biobank and LifeGen cohort GWAS meta-analysis. The variant in purple (rs1556516) is the lead signal at this locus from the parental lifespan analysis. The other variants are coloured according to their correlation with rs1556516 in 1000 Genomes European ancestry data (v. Nov 2014). CHD, coronary heart disease; T2DM, type 2 diabetes mellitus.

Fig. 4 |. Diagram of the major influences and mechanisms of human ageing.

The emerging picture from genetic studies of human ageing supports the hypothesis that ageing is driven by the balance of damage and repair processes. There is genetic evidence for the importance of several damage pathways in humans. Damage can be intrinsic, for example, through somatic mutations arising during cell division. Also important are health behavioural risk factors such as smoking and obesity , which are also influenced by gene–environment interactions. The net impact of damage depends on the activity of repair and response mechanisms. At the cellular level, complete repair can yield undamaged cells (not shown). By contrast, unrepaired damage can lead to cell death (apoptosis), preventing cancers but leading to the depletion of stem cells and loss of regenerative capacity. Cells with somatic oncogene mutations can survive and replicate, sometimes leading to tumour development. Alternatively , damaged cells can enter senescent states and produce a secretory senescence phenotype (SASP), resulting in inflammation and reduced repair that contributes to degenerative diseases5. These mechanisms can result in reduced repair and increasing incidence of chronic diseases of ageing but with decreased cancer risks, or vice versa. This ageing versus cancer trade-off is evident for several of the loci described, notably in the 9p21 cell cycle and senescence-related locus, telomere variation and in the SH2B3 locus.