Title: The Biopsychosocial Liability for Late-Life Depression
Late-life depression is a common, complex, and highly heterogeneous disorder in the elderly.1 It has different biopsychosocial risk factors that interact among themselves to determine the emergence of depressive symptoms in one individual (Fig. 1). However, to what extent each risk factor contributes to the emergence of depressive symptoms is largely unknown. A better understanding of the individual contributions of biological, psychological, and social risk factors can have a significant impact on the implementation of preventive measures to reduce the risk of depression in the population.
FIGURE 1. Venn diagram showing the intersection of biopsychosocial risk factors for late-life depression.
The polygenic risk score (PRS) is an integrated measure of the genetic liability to a given complex disorder.2 The PRS is most commonly calculated as a weighted sum of the number of risk alleles carried by an individual as detected by genome-wide association studies and can include hundreds to thousands of risk alleles. PRS has been applied in different psychiatric disorders to gain a better understanding of the disease genetic architecture, risk stratification, prediction of disease onset, and treatment response.3 Stringa et al.4 developed a PRS-Depression (PRS-D) score to evaluate the impact of genetic liability and social characteristics in the risk of depressive symptoms in older adults. They analyzed 2,279 participants from the Longitudinal Aging Study Amsterdam with genotyping data.5 They showed that a higher PRS-D was associated with higher depressive symptoms and that the PRS-D explained 0.5%–1.8% of the variance in depressive symptoms in this cohort. Social factors like having a partner and having a bigger network size were protective against depressive symptoms in this population. Interestingly, there was no significant interaction between PRS-D and social factors. Also, the effect size of the protective effect of having a partner or bigger network size was higher than for the detrimental effect of PRS-D on the depressive symptoms.
The results from Stinga et al.4 raise many important questions. First, the genetic liability to depression, measured by the PRS-D, explains a very small amount of the variance in depressive symptoms in older adults. Although in line with the literature,6
this result demonstrates the complexity and heterogeneity of the mechanisms of depression, even in a relatively homogeneous sample of older adults. An alternative explanation is that the development of the PRS-D was based on a sample of mostly young and middle-aged adults, and the genetic architecture of depression in older adults is different from younger populations. Finally, the development of PRS is an ever-evolving field, and as additional data are available in the literature, improved PRS-D scores will be able to explain a greater variance in depressive symptoms in older adults.
The lack of gene-by-environment interaction and the larger protective effect of having a partner and a bigger support network highlight the relevance of social determinants of depression in older adults.7 Improvements in the social environment from a population-based or individual perspective are feasible can have a significant impact on preventing depression in this highly vulnerable population.8 Also, we can envision that a strong social network can protect against depression in older adults, even in those with high genetic liability, demonstrating the positive impact of a nurturing environment on mental health and well-being.9
Despite its relevance, the study from Stringa et al.4 has important limitations. It did not evaluate other important biological and psychological risk factors for late-life depression (e.g., medical comorbidities, perceived stress, loneliness, personality traits). Therefore, we have a limited view of the determinants of depression in older adults, their contribution to depressive symptoms, and if they interact with one another to increase or reduce the risk of depressive symptoms in older adults. Future studies, preferably including multiple and diverse cohorts, should address these issues to provide a comprehensive view of the biopsychosocial liability to depression in older adults.
