Lessons Learned From Parsing Genetic Risk for Schizophrenia Into Biological Pathways
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Updated: Aug 11, 2025

A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
Published on: June 15, 2011
Giulio Pergola1, Nora Penzel1, Leonardo Sportelli1
1Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.
Abstract:
The clinically heterogeneous presentation of schizophrenia is compounded by the heterogeneity of risk factors and neurobiological correlates of the disorder. Genome-wide association studies in schizophrenia have uncovered a remarkably high number of genetic variants, but the biological pathways they impact upon remain largely unidentified. Among the diverse methodological approaches employed to provide a more granular understanding of genetic risk for schizophrenia, the use of biological labels, such as gene ontologies, regulome approaches, and gene coexpression have all provided novel perspectives into how genetic risk translates into the neurobiology of schizophrenia. Here, we review the salient aspects of parsing polygenic risk for schizophrenia into biological pathways. We argue that parsed scores, compared to standard polygenic risk scores, may afford a more biologically plausible and accurate physiological modeling of the different dimensions involved in translating genetic risk into brain mechanisms, including multiple brain regions, cell types, and maturation stages. We discuss caveats, opportunities, and pitfalls inherent in the parsed risk approach.
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