Comprehensive Polygenic Score Profiling Reveals Autism Spectrum Disorder Subgroups with Different Genetic Predisposition Related to High-Density Lipoprotein Cholesterol, Urea, and Body Mass Index

Background: Autism spectrum disorder (ASD) is a complex and heterogeneous neurodevelopmental disorder. This study aims to demonstrate the potential of comprehensive polygenic scores (PGSs) as clinical biomarkers for stratifying individuals with ASD and for advancing the understanding of ASD’s heterogeneous etiology. Methods: We calculated 2602 PGSs—representing all publicly available, license-cleared PGSs in the PGS Catalog—for 75 individuals with ASD by utilizing the database of the Tohoku Medical Megabank Birth and Three-generation cohort study. Results: Unsupervised clustering revealed three ASD subgroups. We identified twenty PGSs with the most significant differences among these subgroups as distinctive PGSs for each subgroup. PGS set enrichment analysis associated these distinctive PGSs with different traits in each subgroup: high-density lipoprotein cholesterol measurements, urea measurement, and body mass index. Furthermore, distinctive PGSs indicated consistent genetic predisposition directions: lower high-density lipoprotein cholesterol levels in subgroup 1, higher urea levels in subgroup 2, and lower body mass index in subgroup 3. Conclusions: Comprehensive PGSs extending beyond psychiatry-related traits represent promising clinical biomarkers for identifying ASD subgroups with different genetic predispositions. Such stratification may enhance understanding of heterogenous genetic backgrounds and targeted drug development.