Title: Cognition, Diabetes and Functional Outcomes in Schizophrenia: A 6-year Follow-up Study
Summary: Schizophrenia (SCZ) is a heterogeneous, complex, most common psychotic disorder that has been associated with several genetic and environmental risk factors. Poor cognitive and functional outcomes in patients with SCZ and their unaffected siblings are common that can be attributed to genetic susceptibility, medical comorbidities including diabetes, and other environmental factors, such as antipsychotic drugs and long-term cannabis use. Given the limited use of genetic data, rareness of longitudinal studies and small sample size, controversy persists regarding illness trajectory, and cognitive and functional outcomes in patients with SCZ and their unaffected siblings. Thus, further investigation is required. The aim of this PhD project is to unravel diabetes and determinants of cognitive and functional outcomes in SCZ using the Genetic Risk and Outcome of Psychosis (GROUP) cohort data. Study I, pilot work, is a cross-sectional study in 820 patients with SCZ and used multiple linear regression analysis to study associated factors of diabetes. Study II is a systematic review and meta-analysis to synthesize contemporary evidence on the association between cardiometabolic dysregulation and cognitive impairment. Study III to VI are a 6-year longitudinal study in 1,119 patients with SCZ and 1,059 unaffected siblings: study III and IV will use clustered ordinal logistic regression analysis to investigate the risk factors of cognitive impairments; study V and VI will use linear mixed effects regression analyses to examine negative symptoms, and quality of life and functioning, respectively. This PhD project will advance the existing knowledge and yield a more accurate picture of determinants of comorbid diabetes, cognitive and functions outcomes, and the course of SCZ. Therefore, to ensure healthy aging, the outputs will aid clinicians to perform personalizing assessment, initiate early intervention strategies and selection of treatment for subgroups of patients and their unaffected siblings with similar characteristics which optimize the overall efficiency of evidence-based personalized interventions. Furthermore, the outputs can be utilized by researchers and policymakers.