2025-12-16

105_ Associations Between Polygenic Risk Scores for the p-Factor and Demographic, Somatic, and Psychosocial Variables in Neurotypical Individuals of the PsyCourse Study

Research Question and Aims

The p-factor, also known as the "general psychopathology factor," is a concept suggesting that a common underlying factor contributes to the development of various mental disorders (Caspi et al., 2018). While several studies have estimated the phenotypic p-factor using factor analysis of various psychopathology indicators (e.g., DeLisi et al., 2022), our project focuses on the genetic p-factor, operationalized through polygenic risk scores (PRS) based on joint analysis of genome-wide association summary statistics (Grotzinger et al., 2019). Our goal is to investigate associations between p-factor PRS and various psychosocial and health-related variables at baseline (visit 1) in the healthy control group (n = 466) of the PsyCourse Study. This approach could offer insights into subclinical manifestations of psychiatric risk in a non-clinical population. We plan to specifically explore associations between the genetic p-factor and
• Demographic variables,
• Somatic diseases,
• Observer-rated symptoms of depression (IDS-C30), mania (ASRM) and schizophrenia (PANSS) (total scores or subscale scores of each test)
• Self-rated symptoms of depression (BDI_II), mania (MSS, ASRM) and psychotic-like symptoms (CAPE-42) (total scores on each test)
• Substance use,
• Religious activities,
• Life events (LEQ),
• The Verbal Learning and Memory Test (VLMT, Visit 2)
• Global functioning (GAF) and
• Quality of life (WHOQOL-BREF Domain Scores),
• Short Form Health Survey (SF-12),
• Sleep and daytime sleepiness. To assess the latter, we will extract sleep-related items from available symptom measurements.
This study may help uncover subclinical phenotypic footprints of genetic risk for psychiatric disorders. By examining associations in healthy controls, we aim to identify potential protective factors or early indicators of vulnerability, with implications for early intervention and personalized prevention.

Analytic Plan

This is an exploratory study without hypotheses. For each variable we will set up an appropriate linear model (according to the scale level of the data), regressing the phenotype of interest on sex, age, the first four ancestry principal components and PRS for the p-factor. Polygenic scores for the p-Factor have already been calculated for earlier PsyCourse proposals (#55, #68a and #78) using PRS-CS and will be re-used.
To estimate the statistical power of our project, we re-examined the results of a power analysis of an earlier PsyCourse proposal (078_ Association of Big-5 Personality Traits with a phenotypic Common Executive Function Factor and Polygenic Risk Scores for a Common Executive Function Factor and the P-Factor). As an example, for the SF-12 Item0, available for n=365 participants, a power of 0.8 has been calculated, assuming an effect size of 0.04 and a Bonferroni correction for 20 simultaneous tests. As we plan to assess about 100 interrelated variables, we will use the more powerful FDR correction to account for multiple testing, instead of Bonferroni correction, to retain an acceptable level of statistical power. Additionally, statistically significant results may be re-assessed in a different cohort.

Resources needed

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