Biological Psychiatry Global Open ScienceNeurosciencePeer-reviewed journal article
Schizophrenia polygenic risk during typical development reflects multiscale cortical organization
Matthias KirschneriD, Casey PaquolaiD, Budhachandra S. KhundrakpamiD, Uku VainikiD, Neha BhutaniiD, Benazir H. Hodzic-Santor, Foivos GeorgiadisiD, Noor Al‐SharifiD, Bratislav MišićiD, Boris C. BernhardtiD, Alan Charles EvansiD, Alain DagheriD
Abstract
Schizophrenia is widely recognized as a neurodevelopmental disorder. Abnormal cortical development may by revealed using polygenic risk scoring for schizophrenia (PRS-SCZ). We assessed PRS-SCZ and cortical morphometry in typically developing children (3-21 years) using whole genome genotyping and T1-weighted MRI (n=390) from the Pediatric Imaging, Neurocognition and Genetics (PING) cohort. We contextualise the findings using (i) age-matched transcriptomics, (ii) histologically-defined cytoarchitectural types and functionally-defined networks, (iii) case-control differences of schizophrenia and other major psychiatric disorders. Higher PRS-SCZ was associated with greater cortical thickness, which was most prominent in areas with heightened gene expression of dendrites and synapses. PRS-SCZ related increases in vertex-wise cortical thickness were especially focused in the ventral attention network, while koniocortical type cortex (i.e. primary sensory areas) was relatively conserved from PRS-SCZ related differences. The large-scale pattern of cortical thickness increases related to PRS-SCZ mirrored the pattern of cortical thinning in schizophrenia and mood-related psychiatric disorders. Age group models illustrate a possible trajectory from PRS-SCZ associated cortical thickness increases in early childhood towards thinning in late adolescence, which resembles the adult brain phenotype of schizophrenia. Collectively, combining imaging-genetics with multi-scale mapping, our work provides novel insight into how genetic risk for schizophrenia impacts the cortex early in life.
- organism: human
- assay: bulk RNA-seq
- assay: multiome
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- Citations
- 10
- FWCI
- 1.30
- Field percentile
- top 21%
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