Can genetic variants underlying subjective well-being predict age-related health problems

In a time where population aging is one of the most important demographic phenomena, the idea of predicting future health has received great attention with the hope of developing intervention strategies. Interestingly, simple... [ view full abstract ]

In a time where population aging is one of the most important demographic phenomena, the idea of predicting future health has received great attention with the hope of developing intervention strategies. Interestingly, simple measures of subjective well-being (SWB) based on a single item, are often superior to more objective clinical assessment for predicting an individuals’ morbidity and mortality, suggesting that SWB is a powerful predictor of future health (Idler & Benyamini, 1997). However, still little is known about the genetic architecture underlying this link between self-perceived measures of well-being and healthy aging.

Recently, we identified genetic polymorphisms underlying SWB (rs3756290, rs2075677, and rs4958581) using genome-wide data of more than 298,000 individuals (Okbay et al., 2016). Here we derived polygenic risk-scores based on the genome-wide association results of SWB to predict age-related health problems as measured by the Cumulative Illness Rating Scale (CIRS). CIRS is a cumulative score based on medical problems in 13 different organ systems which reflects common problems of the elderly. One or more existing diseases per organ system will result in a score of one for that particular system, with a final score between zero (disease free) to thirteen. CIRS scores as well as genetic information were available for 8,000 individuals from the IGEMS consortium. The polygenic risk-score was regressed on the observed CIRS scores to assess the degree to which variability in CIRS is explained by variability in genes underlying SWB. Findings and implications will be discussed.

Idler, E.L., & Benyamini, Y. (1997). Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav, 38(1), 21-37.

Okbay, A., Baselmans, B.M., De Neve, J.E., Turley, P., Nivard, M.G., Fontana, M.A., . . . Cesarini, D. (2016). Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat Genet, 48(6), 624-633.