IDENTIFYING THE UNIQUE GENETIC ARCHITECTURE OF SCHIZOPHRENIA DISTINGUISHED FROM BIPOLAR DISORDER USING GENOMIC STRUCTURAL EQUATION MODELING
*Yoonjeong Jang, Sanghyeon Park, Hong-Hee Won, Woojae MyungAbstract
Background
Schizophrenia (SCZ) and bipolar disorder (BIP) exhibit considerable overlap in symptomatology and genetic components. The pharmacological treatments and clinical differential diagnosis between these disorders present significant challenges due to their shared characteristics. Unraveling the specific genetic architecture of SCZ, independent of BIP, could significantly advance the identification of therapeutic targets and the development of biomarkers for SCZ.
Methods
This study aimed to explore the unique genetic architecture of SCZ. We employed Genomic Structural Equation Modeling (Genomic SEM) on genome-wide association study (GWAS) data for SCZ and BIP. It integrates the results of schizophrenia GWAS analysis and bipolar disorder GWAS analysis to construct a genetic structure, including factors, as a multivariate model, enabling the validation of associated genetic variants for each factor. GWAS-by-Subtraction is a technique used with the Genomic SEM method to elucidate the specific genetic composition of a particular trait by removing the genetic influence of other traits. Our approach focused on identifying the unique genetic pathways of SCZ by subtracting the genetic variance attributable to BIP.
Results
From the initial 205 SCZ-associated single nucleotide polymorphisms (SNPs) identified in GWAS, conditioning on BIP resulted in the attenuation of 13 signals, leaving 192 SCZ-specific signals (p <5 x 10- 8, r2 = 0.2). Notably, the SNP-based heritability for SCZ GWAS was 40% (s.e. = 1.8%), but it was estimated to be 9% (s.e. = 0.4%) when SCZ conditioned on BIP.
Conclusion
These findings enhance our understanding of the pathophysiology of SCZ and indicate distinct genetic underpinnings that differentiate it from BIP. This study paves the way for more targeted SCZ treatments and the development of specific biomarkers, contributing to precision medicine in psychiatric disorders.