In a recent study published in the journal BMJ Evidence-Based Medicine, researchers assessed how lifestyle and genetic factors are linked to lifespan using a longitudinal cohort dataset.
Their results indicate that there are independent associations of lifestyle and genetic factors with lifespan and that following a healthy lifestyle can mitigate the risk of premature death or a shorter lifespan due to genetic factors.
Study: Genetic predisposition, modifiable lifestyles, and their joint effects on human lifespan: evidence from multiple cohort studies. Image Credit: lusia83 / Shutterstock
Background
Human lifespans are known to be affected by genetic factors, with heritability estimated to be approximately 16% by some studies, as well as non-genetic attributes such as lifestyle.
Researchers have identified a 'longevity gene' apolipoprotein E and other genetic loci significantly correlated with lifespans.
However, even if certain people are genetically predisposed toward shorter lifespans, certain modifiable lifestyle behaviors may mitigate their risk, but to what extent a high genetic risk of premature death can be offset by lifestyle is not well understood.
About the study
Researchers combined cohort data from multiple sources, including the United Kingdom Biobank study, to calculate a polygenic risk score (PRS) that assessed the genetic susceptibility of individuals linked to their lifespan.
Using this score, participants were categorized based on their genetically predicted human lifespan as long, intermediate, and short. Individuals in the lowest PRS quintile were classified as being genetically predisposed to long lifespans.
Researchers then used the PRS to examine the relationship between lifespans and specific common lifestyle indicators such as sleep duration, body shape, physical activity, diet, alcohol consumption, and smoking, as well as how lifestyle and genetic factors interacted to influence lifespan.
These lifestyle indicators were used to construct a healthy lifestyle score (HLS). Based on the HLS, the participants were classified as having unfavorable, intermediate, and favorable lifestyles.
The researchers calculated lifespan as the death date minus birth date or as the summed age at baseline with time of follow-up. They excluded deaths resulting from COVID-19, injuries, or accidents. Covariates in the analysis included sex, age, comorbidity, socioeconomic status, and educational attainment, which were collected through baseline questionnaires.
The dataset was analyzed using multivariable logistics regression models and Cox proportional hazard regression models; these were adjusted with the covariates and ancestral principal components.
Flexible parametric survival models were used to calculate life expectancy for participants of different lifestyle and genetic risk classes. Multiplicative interaction models were run to examine interactions between lifestyle factors and PRS. Multiple sensitivity tests were conducted to assess the robustness of the findings.
Findings
The study analyzed data from 353,742 European participants, excluding those who did not have genetic data, failed quality control, or died from specific causes.
The median follow-up was 12.9 years, during which 24,239 deaths occurred. A PRS based on 19 independent single nucleotide polymorphisms was created, showing a linear increase in the risk of death across genetic risk categories.
Participants with a high genetic risk had a 21% higher risk of dying compared to those with a low genetic risk, even after adjusting for lifestyle factors.
Additionally, the HLS demonstrated a dose-response relationship with the risk of death. Individuals with an unfavorable lifestyle had a 78% higher risk of death compared to those with a favorable lifestyle. This association persisted even after accounting for genetic risk.
The combined analysis of lifestyle and genetic factors revealed that individuals with a high genetic risk and unfavorable lifestyle had a 104% higher risk of death compared to those with low genetic risk and a favorable lifestyle.
Conversely, those with high genetic risk but a favorable lifestyle had a 54% lower risk of death compared to their counterparts with an unfavorable lifestyle.
The stratified analysis was confirmatory, suggesting that an unfavorable lifestyle increased the risk of dying for all genetic risk groups. No significant interaction was found between genetic risk and lifestyle factors. Sensitivity analyses supported the robustness of the findings.
The combined impact of lifestyle and genetic risk on life expectancy was assessed in a secondary analysis.
Participants with a favorable lifestyle and low genetic risk had a significantly longer life expectancy than those with an unfavorable lifestyle and high genetic risk, with an average lifespan difference of 6.7 years.
The study emphasized the importance of lifestyle factors, particularly smoking cessation, physical activity, sleep, and diet, in prolonging lifespan.
Conclusions
The discussion underscores the study's investigation into the interplay of genetic and lifestyle factors on lifespan among 353,742 individuals.
Findings reveal that higher genetic risk correlates with an increased death risk of 21%, while an unfavorable lifestyle poses a 78% higher risk, independent of genetic factors. However, a favorable lifestyle can offset genetic predispositions by as much as 62%, with specific combinations yielding better outcomes.
Strengths include large, prospective cohorts and comprehensive sensitivity analyses. Limitations include incomplete genetic understanding, short follow-up, reliance on self-reported data, and cohort representativeness.
Nonetheless, promoting healthy lifestyle behaviors could extend lifespan and mitigate genetic risk, suggesting significant public health implications.
Journal reference:
- Genetic predisposition, modifiable lifestyles, and their joint effects on human lifespan: evidence from multiple cohort studies. Bian, Z., Wang, L., Fan, R., Sun, J., Yu, L., Xu, M., Timmers, P.R.H.J., Shen, X., Wilson, J.F., Theodoratou, E., Wu, X., Li, X. BMJ Evidence-Based Medicine (2024). DOI: 10.1136/bmjebm-2023-112583, https://ebm.bmj.com/content/early/2024/04/16/bmjebm-2023-112583