Stress-related disorders stem from a complex interplay of genetic and environmental factors. While the impact of adverse experiences is well-established, individual responses to these experiences vary significantly, resulting in diverse mental health trajectories. This study focuses on understanding the interplay between genetic predisposition (measured by polygenic risk scores, PRSs) and long-term cortisol secretion (measured by hair cortisol concentration, HCC) in predicting these varying mental health trajectories. Previous research has linked both high PRSs and elevated HCC to negative mental health outcomes. However, the combined predictive power of these two factors remains largely unexplored, particularly in the context of a major, widespread stressor such as the COVID-19 pandemic. Our earlier work identified three distinct mental health trajectory groups (acute dysfunction, delayed dysfunction, resilient) among participants during Germany's first COVID-19 lockdown. These groups differed in their response to the pandemic's stressors despite equal exposure, highlighting the need to understand underlying individual differences. This study aims to investigate whether pre-pandemic HCC and PRSs for various psychiatric phenotypes can predict group membership within these trajectories. We hypothesize that elevated pre-pandemic HCC and increased genetic risk for psychiatric disorders (as measured by a general pleiotropic PRS factor) will be associated with a greater likelihood of falling into the ‘acute dysfunction’ and ‘delayed dysfunction’ groups compared to the ‘resilient’ group. We further explore the association of disorder-specific PRSs and investigate potential interaction effects between HCC and genetic risk.

The literature supports a multifactorial etiology for stress-related disorders, with both genetic and environmental influences playing crucial roles. Studies examining the combined effect of PRSs and HCC are limited. While HCC, reflecting long-term cortisol secretion, serves as a potential biomarker for chronic stress, the consistency of its association with stress-related disorders is debated in meta-analyses. Most prospective studies on HCC sampled hair immediately post-trauma, potentially confounding acute cortisol secretion with long-term levels. Research using PRSs has demonstrated the additive genetic contributions to psychiatric disorders, allowing for individual genetic risk quantification. However, the high genetic correlation between different psychiatric disorders, and the presence of pleiotropic effects, complicates analysis. Studies employing exploratory factor analysis have identified general factors of psychopathology, suggesting a common underlying genetic architecture across various disorders. This study builds upon previous research by incorporating both HCC and a comprehensive set of PRSs to predict mental health trajectories during the COVID-19 pandemic.

This study utilized data from the Longitudinal Resilience Assessment (LORA) study. 523 participants from the LORA study participated in weekly mental health assessments (GHQ-28) during the initial 8 weeks of the COVID-19 lockdown in Germany. These participants were previously classified into three mental health trajectory groups (acute dysfunction, delayed dysfunction, and resilient) using latent growth mixture models. The current study focused on a subset of these participants (n=192) with available hair cortisol data and (n=364) with available genetic data. Hair samples collected quarterly prior to the pandemic were used to determine HCC (averaged over three measurements for a baseline level). DNA from blood samples obtained at the baseline of the LORA study was used to calculate PRSs for 12 different psychiatric phenotypes (ADHD, ALC, ANO, ANX, AUT, BPD, MDD, OCD, OPI, PTSD, SCZ, NEU). An exploratory bifactor model with Schmid-Leiman transformation was used to identify a general genetic factor and sub-factors for psychiatric disorders. Bivariate logistic regressions were conducted to test the associations of HCC and PRS factors with each mental health trajectory group, using the ‘resilient’ group as the reference category. Covariates considered in the analysis included age, sex, pre-lockdown mental health status, hormonal contraceptive use, hair treatment, and the time interval between hair sample collection and the lockdown.

The bifactor model successfully extracted one general factor (g-factor) representing a general pleiotropic risk for psychiatric disorders, and four sub-factors: internalizing disorders (INT), psychotic disorders (PSY), childhood-onset neurodevelopmental disorders (ND), and dysfunctional coping disorders (DYS). Logistic regression analyses revealed that higher values of the general pleiotropic pPRS factor significantly predicted membership in the acute dysfunction class compared to the resilient class (b = 0.44, p = 0.025; odds ratio = 1.55). Similarly, elevated HCC significantly predicted acute dysfunction (b = 0.45, p = 0.045; odds ratio = 1.56). The exploratory analysis additionally showed an association between the ND factor and acute dysfunction (b = 0.43, p = 0.031; odds ratio = 1.53). Notably, neither HCC nor the genetic risk factors showed a significant association with the delayed dysfunction class compared to the resilient class. No significant interaction effects between HCC and the genetic risk factors were detected. However, the main effects of HCC and the general pleiotropic pPRS factor remained significant even after controlling for relevant covariates.

This study provides evidence that both long-term elevated cortisol levels and increased genetic predisposition towards psychiatric disorders are associated with an acute, rather than delayed, negative mental health response to the COVID-19 lockdown. The significant association of both HCC and the general pleiotropic pPRS factor with acute dysfunction suggests additive effects of biological (physiological) and genetic vulnerability in predicting heightened susceptibility to stress. The finding that the neurodevelopmental disorder subfactor (ND) was associated with acute dysfunction suggests that difficulties with emotion regulation and other aspects of neurodevelopmental functioning may increase vulnerability to immediate stress responses. The lack of significant findings for the delayed dysfunction group may reflect the need for larger samples or a different methodological approach to identify predictors for this group. The absence of significant interaction effects between HCC and PRSs suggests that these factors have additive, rather than synergistic, effects on mental health trajectories. The results highlight the potential clinical utility of combining biological and genetic risk factors in the early identification of individuals at higher risk for mental health difficulties following major stressful events.

This study demonstrates the potential value of using both long-term cortisol levels (HCC) and polygenic risk scores (summarized in a bifactor model) in identifying individuals at risk for acute mental health deterioration following significant stressors. The findings emphasize the importance of considering both physiological and genetic predispositions for early identification and intervention. Future research should focus on replication studies with larger samples and explore the long-term mental health outcomes for the different trajectory groups, along with investigating the genetic basis of HCC variation and refining the PRS methodology to increase predictive power. Further investigations are needed to fully clarify the predictive value of these biomarkers for different mental health trajectory patterns.

The study's limitations include the limited sample size, particularly within the ‘acute’ and ‘delayed dysfunction’ groups, potentially affecting statistical power and the generalizability of findings. The exploratory bifactor model, while well-fitting, exhibited some anomalies that require further investigation before generalizing the results. The overrepresentation of women, a known risk factor for mental health deterioration during the pandemic, may also limit the generalizability of the findings to men. The study's reliance on GWAS data predominantly from individuals of European ancestry limits the generalizability of the results to other ethnic groups. The main effects reported are only marginally significant and may not be particularly robust, demanding replication in larger studies.