In the current study, we sought to test the hypothesis that higher optimism would be associated with metrics suggestive of less cellular aging, as indicated by two DNA methylation age algorithms, intrinsic (IEAA) and extrinsic epigenetic age acceleration (EEAA); these algorithms represent accelerated biologic aging that exceeds chronological age. Intrinsic epigenetic age acceleration captures properties of aging that are independent of cell type and organ whereas extrinsic epigenetic acceleration likely reflects both epigenetic variation and age-related changes in cell distributions in blood [ 27 ]. We used data from two ongoing epidemiologic cohorts that include women or men, the Women’s Health Initiative (WHI) and the VA Normative Aging Study (NAS). Based on prior work we identified relevant covariates for consideration including sociodemographic factors, health status, and health behaviors, which might confound or lie on the pathway between optimism and DNA methylation, as well as depression, which is correlated with both optimism and DNA methylation profiles [ 28 ].

Prior work has suggested epigenetic aging might explain observed relationships between negative psychological factors and health. For example, stress-related epigenetic aging has been proposed as a possible explanatory factor linking psychological stress and higher risk of developing age-related diseases, with several studies demonstrating higher levels of lifetime stress are associated with accelerated DNA methylation age (DNAm) [ 19 , 20 ]. While less work has examined positive psychological factors in relation to epigenetic aging, to assess potential protective effects on aging processes, given prior findings of protective effects in relation to chronic disease outcomes, such relations are plausible. Optimism may be associated with a slower rate of epigenetic aging if it either reduces stress exposure or buffers its effects – although it is important to note that optimism does not simply reflect the absence of stress and in fact may have independent effects on biological processes [ 6 ]. Optimism has been characterized as an asset or resource that people can utilize throughout life and across multiple domains [ 11 , 21 , 22 ]. Generally, psychological health assets like optimism, tend to be stable across time, although they can be responsive to life changes such as unemployment or divorce [ 23 ], or to interventions, such as activities that promote psychological well-being [ 24 – 26 ].

Recent work has identified DNA methylation (DNAm) as a strong component of biologic aging, and developed “epigenetic clocks” designed to capture methylation-based markers of aging. Horvath et al. proposed an “epigenetic clock” derived from age-associated methylation changes in 353 Cytosine-phosphate-Guanosine sites (CpGs) across the genome that are involved in important biological processes (e.g., DNA replication and repair, lipid metabolism, oxidative stress, and other chronic disease related processes) [ 15 , 16 ]. This clock score is well-validated across multiple cell types and tissues, and in epidemiologic studies it predicts cognitive function, lung function, grip strength, and premature mortality, among other outcomes [ 16 – 18 ]. Hannum et al. also derived an epigenetic clock score in a slightly different way, leveraging DNA methylation in blood at 71 CpG sites [ 15 ]. A measure of methylation age acceleration can be derived using either of these scores to capture a positive difference between DNA methylation and chronologic age.

Optimism, which has been defined either as the generalized expectation that good things will happen or according to the ways in which people explain the causes of good and bad events, may therefore be a powerful, positive health asset. Biologic mechanisms underlying the optimism-health associations are not yet well-established, but understanding biologic pathways could point to novel means of improving health in aging. Given the broad associations between optimism and health across disease endpoints, it is possible that optimism is related to systemic processes that affect multiple outcomes. Given consistent findings with age-related diseases, one candidate process is slower cellular aging, whereby optimism could reduce or delay age-related deterioration in health.

Aging and age-related health conditions have become critical public health issues. According to recent projections, the percentage of people aged >65 years in the United States is expected to increase by more than 60% over the next 15 years [ 1 ]. Growing evidence suggests that higher levels of optimism are associated with reduced risk of a wide range of age-related conditions such as cardiovascular events, lung function decline, cognitive impairment, and premature mortality (including both overall mortality and deaths due to heart disease, stroke, or cancer) [ 2 – 11 ]. For example, in a prospective study of 70,021 older women followed over 8 years, women in the highest (versus lowest quartile of optimism had a 38% reduced risk (95% confidence interval [CI]: 0.50, 0.76) of heart disease mortality and a 39% reduced risk (95% CI: 0.43, 0.85) of stroke mortality after adjusting for sociodemographic factors [ 2 ]. Prospective studies in other cohorts have reported similar findings [ 5 , 12 – 14 ].

In both the WHI and NAS, after excluding individuals with depression, associations for optimism with either IEAA and EEAA remained consistently null (Appendix A 1, Table S3 and Table S4 ). Further, no statistically significant associations with IEAA and EEAA were evident for either the pessimism or the optimism subscales. Associations between the explanatory style optimism and both IEAA and EEAA were also uniformly null in all models ( Table 4 ). In analyses stratified by race in WHI (Black and White women), associations remained consistently null across strata (data not shown). Findings from analyses that included the 736 WHI women who did not have the full set of covariates, were similarly null (data not shown). Finally, in WHI, after additionally adjusting for case-control status, WHI observational study membership, as well as clinical trial membership findings were uniformly null across all models (data not shown).

We also evaluated quartiles of optimism in relation to both EEAA and IEAA, in the WHI and NAS. Findings were null in both cohorts for IEAA. In the WHI women, in the unadjusted model, individuals in the lowest (versus highest) quartile of optimism had a lower mean EEAA score (β=-0.73; 95% CI: -1.32,-0.15; Table 3 ). However, this association was no longer statistically significant after adjusting for additional covariates, and all findings with EEAA were null in the NAS.

When evaluating the association between dispositional optimism and DNAm age in NAS, we observed a pattern of null findings in unadjusted as well in all the other models. For example, in our basic adjusted models, optimism was not associated with IEAA (β=-0.06; 95% CI: -0.55,0.42; Table 3 ) or EEAA (β=-0.23; 95% CI: -0.83,0.38).

In WHI, when considering both dispositional optimism and DNAm age as continuous variables, we observed no association of optimism with IEAA (mean difference, β=0.07; 95% CI: -0.10,0.24; Table 2 ); however, we did observe an association with EEAA (mean difference, β=-0.35; 95% CI: -0.55,-0.13) in unadjusted models such that higher optimism was associated with lower DNAm age. In models that adjusted for basic confounders, we observed no relation of optimism to IEAA (β=0.02; 95% CI: -0.16,0.19; Table 2 ) and associations with EEAA were attenuated and no longer statistically significant (β=-0.06; 95% CI: -0.28,0.16). After further adjusting for the full set of covariates, associations were not meaningfully different ( Table 2 ).

The WHI sample consisted of 3,298 women including 1,665 Whites, 961 Blacks, and 561 Hispanics, and 111 in the “Other” race/ethnicity category. Chronological age in the WHI sample ranged from 50-79 years (mean=64). Most women were married (or in marriage-like relationships: 56%), and most had education after high school (some college or an associate degree: 26%, or a college or graduate degree: 30%). The NAS sample consisted of 514 men (99% White) ranging in chronological age from 56-91 years (mean=73). Most men were married (76%), and had either a high school degree (20%) or college or graduate degrees (35%). Table 1 , Table S1 , and Table S2 [see Appendix A 1 for Table S1 and Table S2 ] provide additional details about participants.

Discussion

We examined the association between optimism and epigenetic age acceleration measured by DNA methylation in two well characterized cohorts. We were able to examine two forms of optimism, dispositional and explanatory style. Regardless of which measure we considered and across cohorts, we found consistently null associations between optimism and both measures of DNA methylation aging, the intrinsic and extrinsic epigenetic age acceleration measure. While we did find one statistically significant association between the highest versus lowest quartile of dispositional optimism and lower EEAA score in an unadjusted model, it was evident only among the women. Thus, we remain cautious about interpreting this finding as occurring for reasons other than chance. Findings were unchanged in secondary analyses where we excluded those with depression, separately examined the optimism and pessimism subscales of the LOT, or considered another validated measure of optimism (PSM-R) available in the men.

There may be several explanations for these null associations. Our specific measures of epigenetic age acceleration may not be as relevant for optimism as other formulations might be. The DNA methylation age measures considered here reflect underlying aging processes that are at least partially under genetic control, and are more weakly associated with several lifestyle factors [27]. Pathway analysis suggests the components of the DNA methylation age [16,18] are enriched for immune cell trafficking and development, and these processes may not be strongly influenced by optimism. Further work is needed to evaluate other potential biologic mechanisms of optimism, both epigenetic and others, that may underlie the association of optimism with health. For example, one recently developed metric, DNA methylation PhenoAge, has a stronger association with lifestyle and wellness factors than the IEAA or EEAA measures [29], and as a result, may be more strongly linked to optimism. It is possible that other age acceleration scores that capture processes more tightly linked to optimism will also be developed. Further, although we did not observe evidence of a direct effect between optimism and DNAm age, future research should evaluate if optimism might moderate (or “dampen”) the effects of various stressors on DNAm age.

With increasing availability of epigenetic information, we will have additional opportunities to assess if the biologic correlates of optimism will be better captured by additional epigenetic metrics of aging [29,30], or if specific scores are less effective than broader agnostic analyses of the epigenome. Future studies that have repeated measures of DNA methylation aging could also provide a stronger test of the hypothesis that optimism influences epigenetic aging by evaluating if optimism is associated with changes in the rate of DNA methylation aging over time. However, another plausible explanation for our null findings could be that the biological pathways by which optimism works to reduce risk of age-related chronic diseases simply do not include changes in DNAm aging. Assessing these possibilities and alternative biological pathways for the observed association between optimism and chronic diseases of aging will be important next steps for this research.

The current study has some limitations. Both optimism and DNA methylation were assessed at a single point in time. Measurement error can be particularly problematic in studies such as ours, that rely on a single biomarker measurement [31], which likely has some random variability. Associations were cross-sectional and given the composition of each sample, findings may not be broadly generalizable, particularly to younger individuals. Nonetheless, this study has important strengths. We used two large and richly characterized cohorts and were able to assess associations in both men and women as well as adjust for potential confounders. Further, two forms of optimism, dispositional and explanatory style were assessed, with a commonly used validated measure dispositional optimism in both cohorts and a validated measure of explanatory style optimism in the NAS. Findings were remarkably similar across measures and cohorts. In conclusion, we examined associations between optimism and epigenetic aging in older men and women from two long-running cohorts with large sample sizes and found no statistically significant associations between optimism and intrinsic or extrinsic epigenetic age acceleration. Our findings may indicate that optimism is not specifically associated with biological mechanisms underlying these metrics of epigenetic age and age acceleration. It may also be that the combination of genes included in these epigenetic aging scores do not well-reflect the biological effects of optimism, and analyses of other clock scores, or broader agnostic or pathway analyses of DNA methylation could yield greater insight into biological processes underlying optimism.

Given robust and consistent findings that optimism is associated with reduced risk of developing a range of age-related diseases as well as overall mortality, and that the relationships are not fully explained by health behaviors [32], identifying novel pathways to improving health in aging remains an important goal. Our findings assess only one metric of epigenetic aging, but new methods and measures for assessing these processes are in active development (or recently available), suggesting continued effort to understand the range of epigenetic and other underlying biological mechanisms is warranted.