Abstract Background Schizophrenia is often a persistent mental illness characterized by cognitive deficits and altered brain network dynamics especially affecting the cortico-subcortical salience processing system. Childhood trauma has been implicated in mechanisms contributing to schizophrenia, but the role of genetic vulnerability remains unclear. Methods A total of 164 schizophrenia patients and 114 healthy controls were included. First, a matched subsample of 117 patients (76 with and 41 without childhood trauma), and 59 healthy controls were compared on polygenic risk scores for schizophrenia (SczPRS). SczPRS was then correlated with neurocognitive performance using a comprehensive cognitive battery (n = 147 patients) and brain-wide static and dynamic functional connectivity (sFC and dFC) using resting-state fMRI (n = 117 patients). Patients were also stratified into high-SczPRS and low-SczPRS (n = 25 each) subgroups. Results Patients with childhood trauma had significantly lower SczPRS than those without. Higher Childhood Trauma Questionnaire (CTQ) scores related to lower cognitive PC score (r = −0.282, p < 0.001), but CTQ did not affect brain-wide dysconnectivity or subcortical/salience system among patients. Patients with the highest SczPRS showed lower dFC between the cingulo-opercular network and subcortical networks (F = 7.949, p = 0.007), but SczPRS did not affect cognitive performance. Conclusions Our findings reveal distinct effects of childhood trauma and polygenic risk in the neural and cognitive substrates of schizophrenia. Childhood trauma relates to poor cognitive function, while polygenic risk primarily affects salience/subcortical network dynamics. These patterns indicate that in genetically predisposed individuals who experience childhood trauma, a “double mechanistic hit” may influence the schizophrenia phenotype.
Danqing Huang, Yicheng Long, Zhening Liu et al.· European psychiatry· 0 citations
Schizophrenia and related psychoses are characterized by reductions in hippocampal volume and morphometric hippocampal-cortical covariance. No study to date has inferred the temporal relationship between deviations in subfield and adjacent white matter volume and connectivity across psychosis. To explore this relationship, we sampled cross-sectional neuroimaging data from 174 patients and 120 non-clinical controls from two studies on first- and multi-episode psychosis. We applied Subtype and Stage Inference (SuStaIn), a machine learning algorithm combining clustering and disease progression modeling, to eight measures of hippocampal volume and morphometric hippocampal-cortical covariance (subfields and white matter regions per hemisphere) combined. We then performed in-depth SuStaIn analyses for 18 volumes (five subfields and four white matter regions per hemisphere) and 18 connectivity measures (graph-theory-based participation coefficient) separately. Some patients and controls showed no deviations (no increase or decrease) from control means in volume and covariance. For individuals who did show deviations, we inferred data-driven stages from deviations in volume toward covariance. In-depth SuStaIn analyses inferred three distinct volume patterns (intact volume, subfield-dominant, whiter matter-dominant) followed by one of four possible connectivity patterns (intact connectivity, whiter matter-dominant, subfield-dominant, subiculum-dominant). These subtypes showed significant differences in age, patient-control ratio and associations between data-driven stages and memory. In previous work, altered hippocampal volume and morphometric covariance distinctively precede cognitive and clinical symptoms of psychosis. While not all patients were assigned a staging pattern for hippocampal volume or connectivity, our findings might thus contribute to elucidating distinct hippocampal patterns underlying heterogeneous manifestations of psychosis for a subgroup of patients.
Jana F. Totzek, Stephan Heckers, L. Palaniyappan et al.· Cortex; a journal devoted to...· 0 citations
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