Age-dependent patterns of schizophrenia genetic risk affect cognition

Kuo, Susan S.; Musket, Christie; Rupert, Petra; Almasy, Laura; Gur, Ruben C.; Prasad, Konasale; Roalf, David R.; Gur, Raquel E.; Nimgaonkar, Vishwajit L.; Pogue-Geile, Michael F.

doi:10.1016/j.schres.2022.05.012

Cited by 1 publication

(1 citation statement)

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“… 54 We also observed that the genetic effects shared between deficits in general cognition and schizophrenia were nonsignificant in the early phases of the illness than during the later stages. 55 These data suggest that gene expression differences may impact CT changes in patients with longer duration of illness than those with short duration of illness. Since hundreds of gene expressions of small effects correlated with CT, multiple pathways may underlie such correlations.…”

Section: Discussionmentioning

confidence: 91%

Gene Expressions Preferentially Influence Cortical Thickness of Human Connectome Project Atlas Parcellated Regions in First-Episode Antipsychotic-Naïve Psychoses

McGuigan,

Santini,

Keshavan

et al. 2023

Schizophrenia Bulletin Open

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Altered gene expressions may mechanistically link genetic factors with brain morphometric alterations. Existing gene expression studies have examined selected morphometric features using low-resolution atlases in medicated schizophrenia. We examined the relationship of gene expression with cortical thickness (CT), surface area (SA), and gray matter volume (GMV) of first-episode antipsychotic-naïve psychosis patients (FEAP=85) and 81 controls, hypothesizing that gene expressions often associated with psychosis, will differentially associate with different morphometric features. We explored such associations among schizophrenia and non-schizophrenia subgroups within FEAP group compared to controls. We mapped 360 Human Connectome Project atlas-based parcellations on brain MRI on to the publicly available brain gene expression data from the Allen Brain Institute collection. Significantly correlated genes were investigated using Ingenuity Pathway Analysis to elucidate molecular pathways. CT but not SA or GMV correlated with expression of 1,137 out of 15,633 genes examined controlling for age, sex, and average CT. Among these ≈19%, ≈39%, and 8% of genes were unique to FEAP, schizophrenia, and non-schizophrenia, respectively. Variants of 10 among these 1,137 correlated genes, previously showed genomewide-association with schizophrenia. Molecular pathways associated with CT were axonal guidance and sphingosine pathways (common to FEAP and controls), selected inflammation pathways (unique to FEAP), synaptic modulation (unique to schizophrenia) and telomere extension (common to NSZ and HC). We demonstrate that different sets of genes and molecular pathways may preferentially influence CT in different diagnostic groups. Genes with altered expressions correlating with CT and associated pathways may be targets for pathophysiological investigations and novel treatment designs.

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Section: Discussionmentioning

confidence: 91%