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Background and Hypothesis
Given the available findings confirming accelerated brain aging in schizophrenia (SZ), we conducted a study aimed at verifying whether quantitative retinal morphological data enable age prediction and whether schizophrenia patients present with a positive retinal age gap (RAG).
Study Design
Two samples of patients and controls were enrolled: one included 59 SZ patients and 60 controls, all of whom underwent optical coherence tomography (OCT) enabling the measurement of 72 variables. A second sample of 65 SZ patients and 70 controls was then combined with the first sample, to generate a database where each subject was represented by 28 morphological variables. Four different machine learning (ML) algorithms were used for age prediction based on z-standardized OCT data. The associations between RAG, demographic, and clinical data were also analyzed.
Study Results
Patients from both samples had significantly higher retinal age and positive RAG ranging between 5.88 and 7.44 years depending on the specific sample. Predictions based on the larger group but with fewer OCT variables exhibited higher prediction relative error. All ML algorithms generated similar outcomes regarding retinal age. RAG correlated with the dose of antipsychotic medication and the severity of symptoms. Correlations with chronological age showed that RAG was the highest in younger patients, and from the age of about 45 years, it decreased.
Conclusions
ML-based results corroborated accelerated retinal aging in schizophrenia and showed its associations with pharmacological treatment and syndrome severity. The finding of a larger RAG in younger patients is novel and requires replication.