Research overview
The text below is the source article’s original abstract under a verified reuse license. cc by
Abstract The temporal onset of polygenic brain disorders has been closely linked to the developmental dynamics of genome-wide risk gene expression. In this study, we systematically characterized the spatiotemporal expression patterns of these risk genes and their relevance in differentiating major neuropsychiatric disorders. We analyzed genome-wide risk gene sets for Intelligence Quotient (IQ), Autism Spectrum Disorders (ASD), Attention Deficit Hyperactive Disorder (ADHD), Tourette's Syndrome (TS), Obsessive Compulsive Disorder (OCD), Anorexia Nervosa (ANO), Neuroticism, Panic disorder, Major Depressive Disorder (MDD), Bipolar Disorder (BIP), Schizophrenia (SZ), Epilepsy, Alzheimer's Disease (AD), and Parkinson's Disease (PD). Our results reveal distinct patterns of spatiotemporal enrichment across these traits, allowing their classification into three clusters. To validate the biological significance of these enrichment patterns, we integrated clinical MRI datasets and confirmed structural alterations within the identified spatiotemporal “hot-spots”. Furthermore, by combining gene co-expression network analysis and single-cell transcriptomic data, we delineated the cell-type specificity and functional pathways underlying risk gene enrichment. In situ hybridization data from the marmoset brain further provided a comprehensive map of risk gene related module expression. This work reinforces the link between dynamic gene expression and disease mechanisms, while highlighting potential biomarkers and therapeutic targets arising from these identified “hot-spots” and pathways.
Scientific assessment
Research question
Assess the question within the original study’s scope.
Methods & sample
Check the source article for study design and sample details.
Key findings
An editorially approved findings summary is not yet published for this record.
Limitations
Generalizability, bias and clinical meaning require separate assessment.
Methods, samples and clinical conclusions are not inferred from bibliographic metadata.