Genetic Risk for Psychiatric Disorders and Telomere Length

Abstract

Background: Previous studies have revealed associations between psychiatric disorder diagnosis and shorter telomere length. Here, we attempt to discern whether genetic risk for psychiatric disorders, or use of pharmacological treatments (i.e., antidepressants), predict shorter telomere length and risk for aging-related disease in a United Kingdom population sample. Methods: DNA samples from blood were available from 351 participants who were recruited as part of the South East London Community Health (SELCoH) Study, and for which whole-genome genotype data was available. Leukocyte telomere length was characterized using quantitative polymerase chain reactions. Individualized polygenic risk scores for major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) were calculated using Psychiatric Genomics Consortium summary statistics. We subsequently performed linear models, to discern the impact polygenic risk for psychiatric disorders (an etiological risk factor) and antidepressant use (common pharmacological treatment) have on telomere length, whilst accounting for other lifestyle/health factors (e.g., BMI, smoking). Results: There were no significant associations between polygenic risk for any of the psychiatric disorders tested and telomere length (p > 0.05). Antidepressant use was significantly associated with shorter telomere length and this was independent from a depression diagnosis or current depression severity (p ≤ 0.01). Antidepressant use was also associated with a significantly higher risk of aging-related disease, which was independent from depression diagnosis (p ≤ 0.05). Conclusion: Genetic risk for psychiatric disorders is not associated with shorter telomere length. Further studies are now needed to prospectively characterize if antidepressant use increases risk for aging-related disease and telomere shortening, or whether people who age faster and have aging-related diseases are just more likely to be prescribed antidepressants.

Keywords: aging; antidepressants; polygenic risk score; psychiatry; telomeres.

FIGURE 1

Correlation between telomere length and chronological age. A scatterplot showing a significant negative correlation between chronological age (x-axis) and adjusted RTL (y-axis). The blue line represents a line of best fit.

FIGURE 2

The association between polygenic risk for psychiatric disorders and telomere length. A scatter plot showing PRSs for SCZ (A, top left), BD (B, top right) and MDD (C, bottom) adjusted for PCs 1–7 (x-axis), and log(RTL) adjusted for age, sex, ethnicity, BMI, smoking status and telomere plate batch (y-axis). The blue line represents the line of best fit.

FIGURE 3

The association between antidepressant use and RTL. A plot showing adjusted RTL in participants: (i) without depression and who are not currently taking antidepressants (Dep-/Anti-), (ii) with a depression diagnosis and who are not currently taking antidepressants (Dep+/Anti-), (iii) without depression who are currently taking antidepressants, (iv) with depression who are currently taking antidepressants. Participants currently taking antidepressants had significantly shorter RTL compared to those not taking antidepressants, irrespective of depression diagnosis. The symbol ‘^∗∗’ indicates a difference of p ≤ 0.01.

FIGURE 4

Antidepressant use and aging-related disease. A bar chart showing the frequency of participants with 0, 1 or 2(+) aging-related diseases, split by those who are not currently taking antidepressants and those who are. Actual sample size within each group is shown on top of each bar. There is a significant difference in the frequency of aging-related disease between the two groups (p < 0.05). Aging-related diseases included: type-2 diabetes, arthritis, cardiovascular disease, stroke, high blood pressure, and cancer.