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Cognitive impairment constitutes a prevailing issue in the schizophrenia spectrum, severely impacting patients' functional outcomes. A global cognitive score, sensitive to the stages of the spectrum, would benefit the exploration of potential factors involved in the cognitive decline.
Methods
First, we performed principal component analysis on cognitive scores from 768 individuals across the schizophrenia spectrum, including first-degree relatives of patients, individuals at ultra-high risk, who had a first-episode psychosis, and chronic schizophrenia patients, alongside 124 healthy controls. The analysis provided 10 g-factors as global cognitive scores, validated through correlations with intelligence quotient and assessed for their sensitivity to the stages on the spectrum using analyses of variance. Second, using the g-factors, we explored potential mechanisms underlying cognitive impairment in the schizophrenia spectrum using correlations with sociodemographic, clinical, and developmental data, and linear regressions with genotypic data, pooled through meta-analyses.
Results
The g-factors were highly correlated with intelligence quotient and with each other, confirming their validity. They presented significant differences between subgroups along the schizophrenia spectrum. They were positively correlated with educational attainment and the polygenic risk score (PRS) for cognitive performance, and negatively correlated with general psychopathology of schizophrenia, neurodevelopmental load, and the PRS for schizophrenia.
Conclusions
The g-factors appeared as valid estimators of global cognition, enabling discerning cognitive states within the schizophrenia spectrum. Educational attainment and genetics related to cognitive performance may have a positive influence on cognitive functioning, while general psychopathology of schizophrenia, neurodevelopmental load, and genetic liability to schizophrenia may have an adverse impact.
Multiple factors contribute to high levels of cardiovascular (CV) risk in schizophrenia patients including lifestyle habits. The additive CV effects of cigarette smoking, hypertension, total cholesterol, and high density lipoprotein (HDL) cholesterol have been found to predict the risk of major cardiac events over a 10 year period. These effects can be calculated with empirically derived CV risk algorithms. By the time the initial Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) analysis of metabolic syndrome prevalence was performed in 2005, there was already a signal that schizophrenia patients had 2-4 times higher prevalence than that expected from general population estimates. The CATIE schizophrenia trial data illustrate the possibility for improving metabolic health by switching patients from more offending medications, and for avoiding long-term CV consequences by preferential use of agents with metabolically benign profiles. Management of schizophrenia requires acknowledgment that CV disease remains a primary cause of excess mortality.
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