Ageing-related genetic variants have been identified mostly in GWAS, which test statistical associations between millions of germline variants and a phenotype, often in several hundred thousand people5. Smaller-scale candidate studies test a subset of variants, yet both approaches include multiple statistical tests. As more variants are compared, it becomes increasingly likely that some will be statistically significant merely by chance5. To guard against false-positive findings, stringent statistical significance thresholds are used, and ‘significant’ associations need to be replicated in independent samples. In reviewing ageing studies, we therefore prioritize the strongest available associations (preferably at a genome-wide statistical significance24 of P < 5 × 10–8), especially those with independent replication.

Parental lifespan

The most robust identifications of lifespan-related variants currently come from recent, very large cohorts such as the UK Biobank25, which includes 500,000 community volunteers. These studies have focused on parental age at death, as offspring health status and survival are associated with parental lifespan. For example, analysis of data from the University of Michigan Health and Retirement Study, a longitudinal study of approximately 20,000 participants aged 51–61 years at baseline who were followed up for 18 years, found that all-cause mortality consistently declined by 19% for each decade that participants’ mothers had survived beyond 65 years of age (14% per decade for fathers)26. Additionally, study participants had progressively lower incidences of cardiovascular disease and cancers26 as well as reduced rates of cognitive decline27, with increasing parental survival. A study of 186,151 non-adopted UK Biobank participants followed up for up to 6 years produced similar results, with declines in all-cause mortality of 16% per decade of mothers’ survival ≥70 years of age (HR 0.84, 95% CI 0.79–0.89) and 17% for fathers’ survival (HR 0.83, 95% CI 0.78–0.89). Cause-specific mortality declined with advancing parental ages, especially for coronary heart disease (20% per decade with decades of mothers’ age ≥70 years: HR 0.80, 95% CI 0.68–0.95; and 21% for fathers’ age: HR 0.79, 95% CI 0.63–0.98), but declines in cancer mortality (HR 0.92, 95% CI 0.90–0.95) were also present28.

Several GWAS have been reported for parental age at death (or attained age thus far) either in the UK Biobank cohort alone21,29,30 or in meta-analyses combining UK Biobank data with data from other cohorts; the LifeGen consortium included data on approximately 160,000 study participants from 25 cohorts in addition to UK Biobank data31, and a separate analysis included pedigree data from AncestryDNA32 on 300,000 individuals for a meta-analyses with UK Biobank data. The ages at death of the parents (or current age if still alive) studied in the LifeGen analysis31 varied from 40 to 107 years, whereas the AncestryDNA32 lifespans ranged from 40 to 120 years. Six genetic loci were identified in both studies for longer parental lifespan (Table 1), with 12 additional loci identified only in one or the other study. Many of the implicated variants have been linked previously to cardiometabolic conditions (mostly myocardial infarction and T2DM), with some linked to Alzheimer disease, autoimmunity and cancer risk31, thus reflecting the more common causes of death in older people.

Table 1 Genetic variants associated with parental lifespan Full size table

Gene–environment interactions were evident for some variants. For example, the variant rs1051730 lies in an exon of CHRNA3, which encodes a nicotinic acetylcholine receptor subunit, and the lifespan-reducing allele was correlated with rs8042849, which increases susceptibility to nicotine dependence33 and likely reduces lifespan by increasing smoking exposure. Interestingly, this association was stronger for fathers’ age at death than mothers’ age at death, possibly owing to gender differences in smoking in the parental generation21. Effect sizes for all lifespan-associated variants were modest, with the largest per allele effect for the APOE ɛ4 variant accounting for 1.06 years of parental lifespan31. The smallest-effect variant identified by LifeGen was intronic in the HTT gene (also known as Huntingtin), although the relationship of this variant to Huntington disease mutations is unclear. Of the 18 variants identified, only one (in APOE) was exonic and affected the coding sequence, suggesting mainly regulatory effects, as is common for polygenic traits34.

In a UK Biobank GWAS, sub-analysis of the participants’ genotypes in the top 10% of parental survival (with survival to ≥90 years in mothers and ≥87 years in fathers) produced results similar to overall lifespan analyses29: four loci remained associated at genome-wide significance (APOE, CHRNA3, LPA and CDKN2B-AS1), with the others remaining nominally significant (all with P values <0.002). Two additional loci (MC2R and USP2-AS1) were significant for the top 10% survival in the analysis of parental lifespan. These results were consistent with an analysis of centenarian parents, with similar genotype–lifespan effect sizes29, although numbers here were small, with only 1,181 participants having at least one centenarian parent, meaning that only the APOE locus reached genome-wide significance29. Thus, lifespan-associated variants can also be important for longevity, with some variants likely being specific to longevity.

Genetic associations with longevity

GWAS have also directly compared long-lived individuals (aged ≥90 years) to younger control individuals (aged <65 years, although definitions vary35,36,37,38, as recently reviewed elsewhere3). The most recent meta-analysis included 11,262 participants who lived beyond the 90th percentile38. The most robust findings have been for the APOE haplotypes, with ɛ4 being less common in long-lived participants and APOE ɛ2 more common (versus the ɛ3 haplotype). The two APOE haplotypes have similarly inverse associations with Alzheimer disease22 and cardiovascular disease39. Apolipoprotein E (APOE) is involved in the transport of cholesterol and other lipids to cells; in the brain, this function is important in neural cell membrane and synapse maintenance and repair40, although the full mechanisms causing Alzheimer disease remain elusive. A recent study showed that the APOE ɛ4 haplotype was associated with excess mortality even within the longest-lived 1% of survivors, whereas the ɛ2/ɛ2 or ɛ2/ɛ3 haplotypes were associated with modestly decreased mortality within the longest-lived 1% of survivors41. The recent meta-analysis of longevity GWAS38 identified a new locus, GPR78; variants in this locus associated with longevity were not previously linked in GWAS with other traits, but the gene, which encodes G protein-coupled receptor 78, has been implicated in traits such as lung function42 in the GWAS Catalog43.

The study of extreme longevity has been refined recently by the finding that heritability is higher in those who are part of long-lived families and that environmental factors seem to be more important in sporadic longevity44. A GWAS in 583 families of the Long Life Family Study cohort (covering long-lived individuals and offspring, which unusually also included predicted longevities) confirmed associations at the APOE locus and also identified a variant (rs1927465) between the genes MYOF (which encodes myoferlin) and CYP26A1 (which encodes cytochrome P450 family 26 subfamily A member 1) at genome-wide significance45. At the time of writing, rs1927465 has not been reported in the GWAS Catalog for other phenotypes.

A much studied set of extreme longevity-associated variants has been reported in the FOXO3A gene, which encodes a transcription factor that influences energy metabolism, cell cycle regulation and inflammation, and is important in modulating the effect of calorie restriction on longevity in model organisms46. In the longest-lived 1% of survivors, 17 FOXO3A variants were more common than in controls (n = 2,072 aged ≥96 years versus <96 years); the strongest association was found for the variant rs4946935 (OR 1.20 for extreme longevity, P = 3.2 × 10−5)47. However, none of these 17 variants affected death rates for the younger 99% of lifespans, which is consistent with no FOXO3A variants reaching genome-wide significance in the large parental lifespan GWAS discussed above29,31.

The evidence on mostly candidate gene variants has also been reviewed, comparing groups aged ≥85 years, including centenarians, versus those aged <85 years, with most aged <60 years48. Overall, seven variants claimed to be associated with longevity were found to be weakly or not associated with survival to age ≥85 years. It has been argued that different populations may have different exceptional longevity variants due to particular environmental exposures and ancestry-specific genetic differences49, providing a possible explanation for the limited replication of variants linked to exceptional longevity. Another explanation might be the fairly modest sample sizes (often fewer than 10,000 long-lived individuals) or potential false-positive findings of some associations.

None of the variants identified thus far as being associated with (extreme) longevity seems essential (that is, not all long-lived people harbour them) and none seems sufficient to achieve longevity (all are fairly common in groups who die earlier). This finding is consistent with the notion that the heritable component in the longest 10% for survival is a quantitative trait44 likely affected by large numbers of small effect variants.

Reproductive lifespan in women

Women are unusual compared with other female mammals in having a total lifespan that is substantially longer than their reproductive lifespan. In a GWAS of age at menopause50, 56 variants were identified, with approximately two-thirds of loci implicated in the DNA damage response (DDR)51. As discussed below, unrepaired DNA damage might be a major driver of overall ageing. Moreover, some of the menopause-associated variants have effects on the hypothalamic–pituitary axis, which controls many hormone levels. A polygenic risk score for each individual in a study population can be calculated by summing the number of risk-increasing alleles (weighted by published effect size) that each participants carries. However, a genetic risk score for age at menopause was not associated with parental lifespan in the UK Biobank21. Menopause-associated variants may therefore have limited effects on human ageing more generally.

Muscle strength

Decreasing muscle strength is a common feature of ageing and is associated with increased risks of cardiovascular disease and mortality, even in those aged <60 years52. A GWAS of the full range of strength (measured as grip strength) identified several lead variants in or near genes implicated in the structure and function of skeletal muscle fibres, neuronal maintenance and signal transduction in the central and peripheral nervous systems53. A targeted study of the human leukocyte antigen (HLA)-mediated autoimmunity-associated region reported associations with low muscle strength in those aged 60–70 years54 without autoimmune disease, but whether low muscle strength in older people is driven by the same variants is unclear.

Cognitive impairment

Normal ageing is often associated with impairment in some cognitive tests, even in the absence of dementia. Cognitive impairment has a number of risk factors, such as hypertension, some of which are treatable if caught early55. The largest recent genetic study of general cognitive function in >300,000 people identified >100 loci, implicating genes expressed in the brain but also including loci associated with traits such as hypertension, suggesting systemic effects on cognition56. A recent genetic analysis of decline in cognitive ability in 1,091 people found that the APOE ɛ4 allele alone was the strongest predictor compared with polygenic risk scores for CAD, educational attainment and other traits57. Another study in 1,176 men aged in their 50s58 found that genetic risk of Alzheimer disease was associated with mild cognitive impairments. Although these studies were limited by small sample sizes, cognitive impairment is evidently a complex multifactorial process in which inherited variation has a role in addition to lifestyle and other health-related factors59.

Age-related disease variants

Many GWAS of age-related diseases have been reported, with thousands of variants now identified5. One of the earliest successful GWAS identified variants that influence age-related macular degeneration60, the most common cause of blindness in the western world. Two large-effect loci were found: one mapped to CFH, which encodes complement factor H in the complement inflammation cascade, and one to ARMS2 (also known as HTRA1), which is involved in extracellular matrix turnover. Both variants were associated with more than 2.5-fold differences in age-related macular degeneration risk in a recent large study61. The effect sizes of these variants contrast with many other common disease-associated variants for which effect sizes are typically small, often with <10% differences in risk5.