Genetic vulnerability to mental disorders has been associated with coronavirus disease-19 (COVID-19) outcomes. We explored whether polygenic risk scores (PRSs) for several mental disorders predicted poorer clinical and psychological COVID-19 outcomes in people with pre-existing depression.

Data from three assessments of the Australian Genetics of Depression Study (N = 4405; 52.2 years ± 14.9; 76.2% females) were analyzed. Outcomes included COVID-19 clinical outcomes (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] infection and long COVID, noting the low incidence of COVID-19 cases in Australia at that time) and COVID-19 psychological outcomes (COVID-related stress and COVID-19 burnout). Predictors included PRS for depression, bipolar disorder, schizophrenia, and anxiety. The associations between these PRSs and the outcomes were assessed with adjusted linear/logistic/multinomial regressions. Mediation (N = 4338) and moderation (N = 3326) analyses were performed to explore the potential influence of anxiety symptoms and resilience on the identified associations between the PRSs and COVID-19 psychological outcomes.

None of the selected PRS predicted SARS-CoV-2 infection or long COVID. In contrast, the depression PRS predicted higher levels of COVID-19 burnout. Anxiety symptoms fully mediated the association between the depression PRS and COVID-19 burnout. Resilience did not moderate this association.

A higher genetic risk for depression predicted higher COVID-19 burnout and this association was fully mediated by anxiety symptoms. Interventions targeting anxiety symptoms may be effective in mitigating the psychological effects of a pandemic among people with depression.

The Connor–Davidson Resilience Scale (CD-RISC) and the Brief Resilience Scale (BRS) are two scales widely used to measure resilience. Although both scales seek to assess an individual's ability to recover from and adapt to disruptions or stressful events, they can capture different aspects of resilience. While the CD-RISC focuses on resources that can help individuals to recover from and adapt to disruptions or stressful events, the BRS directly measures one's ability to bounce back or be resilient. The aim of this study is to better understand resilience through empirically examining the differences between the CD-RISC and the BRS.

Samples (a pooled sample N = 448 and two subsamples N = 202 and 246) consisting of undergraduate students from Taiwan were used. Confirmatory factor analysis (CFA) was performed to examine the relationship between the CD-RISC and BRS. Regression analysis was conducted to examine predictive effects of the CD-RISC and BRS on depression and life satisfaction.

The results of CFA using different samples consistently show that the CD-RISC and the BRS are highly correlated but still distinct. The results of regression analyses using different samples also consistently show that the CD-RISC and the BRS have unique predictive effects regarding depression and life satisfaction.

The research findings suggest that the CD-RISC and the BRS capture different aspects of resilience. For future research on resilience, researchers should pay closer attention to the differences between these scales and choose the one that most closely fits their research purpose.