Fetal Gene Regulatory Gene Deletions are Associated with Poor Cognition in Schizophrenia and Community-Based Samples
Objective:
Schizophrenia is a neurodevelopmental disorder involving clinical and genetic heterogeneity. Multiple recurrent copy number variants (CNVs) increase risk for schizophrenia spectrum disorders (SSD). However, how known risk CNVs and broader genome-wide CNVs influence clinical variability is unclear. Furthermore, whether biological annotation of CNV scores can improve power for patient stratification is unknown.
Methods:
This study examined associations between severe phenotypes in 617 SSD individuals, namely, child-onset psychosis or borderline intellectual functioning (IQ), and: 1) known risk CNVs; 2) genome-wide deletion burden scores; and 3) novel scores capturing deletion burden in 18 previously validated and mutually exclusive gene-sets, representing distinct aspects of neurodevelopment. Associations with borderline IQ were assessed for replicability in 233 SSD-relatives and 581 controls, and 9,930 youth from the Adolescent Brain Cognitive Development (ABCD) Study.
Results:
Known SSD- (odds ratios (OR)=7.07, 95%CI[1.60,31.32]) and neurodevelopmental disorder (NDD)-risk CNVs (OR=4.56, 95%CI[1.48,14.10]) were associated with borderline IQ in SSD. Furthermore, beyond effects of known NDD-risk CNVs, deletion of genes involved in regulating gene expression during fetal brain development was associated with borderline IQ across SSD cases and non-cases (OR=2.57, 95%CI[1.44,4.60]), and in the ABCD cohort (OR=1.33, 95%CI[1.00,1.76]). Exploratory structural MRI-based analyses showed associations between fetal gene regulatory gene deletions and altered gray matter volume ( b =0.09, 95%CI[0.004,0.17]) and cortical thickness ( b =0.14, 95%CI[0.05,0.24]) across SSD cases and non-cases.
Conclusions:
Results confirm contributions of known risk CNVs to severe phenotypes in SSD, implicate disrupted fetal brain development in poor cognition, and demonstrate the utility of a neurodevelopmental framework for identifying mechanisms underlying severe SSD-relevant phenotypes.
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