The structure of psychiatric comorbidity without selection and assortative mating

Area of Science:

• Psychiatric Genetics
• Behavioral Genetics
• Population Health

Background:

• Psychiatric disorders frequently co-occur (comorbidity), potentially due to factors like assortative mating or selection bias in studies.
• Between-family genetic analyses can be confounded by these biases, whereas within-family analyses offer a less biased approach.

Purpose of the Study:

• To compare the structure of psychiatric comorbidity using both between-family and within-family genetic analyses.
• To identify the underlying genetic factors contributing to psychiatric comorbidity and assess potential biases in cohort studies.

Main Methods:

• Utilized genetic data from over 25,000 parent-offspring trios in the Norwegian Mother Father and Child Cohort study (MoBa).
• Employed factor models to analyze psychiatric polygenic scores calculated both between-family and within-family (regressing child scores on parental scores).
• Assessed partner genetic correlations to detect assortative mating and examined sex-specific participation bias.

Main Results:

• A consistent best-fitting model emerged for both between- and within-family analyses, revealing a general genetic factor (p-factor) and three subfactors related to neurodevelopment, psychosis, and constraint.
• Assortative mating was not significant for the general p-factor but was substantial for psychosis and constraint subfactors.
• Evidence of sex-specific participation bias was found when comparing parental factor levels to a population mean.

Conclusions:

• The within-family design effectively disentangles genetic influences on psychiatric comorbidity, overcoming biases present in traditional between-family approaches.
• Findings highlight the importance of considering specific genetic architectures for different psychiatric dimensions and potential biases in large cohort studies.
• This research advances understanding of the mechanisms underlying psychiatric comorbidity and its impact on population health.