A polygenic score for schizophrenia predicts glycemic control.

Area of Science:

• Neuroscience
• Endocrinology
• Genetics

Background:

• Schizophrenia and type 2 diabetes (T2D) frequently occur together, but the underlying molecular mechanisms are not fully understood.
• Identifying shared biological pathways could lead to novel therapeutic targets for both conditions.

Purpose of the Study:

• To investigate the molecular commonalities between schizophrenia and type 2 diabetes (T2D).
• To determine if gene expression patterns in the brain can predict glycemic control in individuals with schizophrenia.

Main Methods:

• Machine learning was used to identify a gene expression signature in the cortex of 212 schizophrenia patients and controls.
• This signature was then applied to gene expression data from pancreatic islet cells to predict glycemic control (HbA1c).
• The predictive model's ability to differentiate T2D patients from controls was assessed.

Main Results:

• A cortical gene expression signature explained approximately 25% of the variance associated with schizophrenia.
• This signature predicted up to 26.3% of the variance in HbA1c levels and could distinguish T2D patients from controls.
• Key genes involved in the electron transport chain, kidney development, and oxidative stress were identified as drivers of this cross-tissue prediction.

Conclusions:

• The study suggests a molecular link between schizophrenia and type 2 diabetes (T2D), driven by shared biological processes.
• Oxidative stress and mitochondrial dysfunction may play a role in the comorbidity of these conditions.
• These findings open avenues for understanding and potentially treating the dual diagnosis of schizophrenia and T2D.