Joint Modeling Study Identifies Blood-Based Transcripts Link to Cognitive Decline in Parkinson's Disease

Area of Science:

• Neuroscience
• Genomics
• Biomarker Discovery

Background:

• Cognitive decline is a common and burdensome symptom in Parkinson's disease (PD).
• Early identification of cognitive impairment in PD is crucial for timely intervention.

Purpose of the Study:

• To identify blood-based transcriptome-wide biomarkers for predicting cognitive decline in PD.
• To develop models for identifying PD patients at high risk of cognitive impairment.

Main Methods:

• Utilized joint modeling analysis to assess longitudinal gene expression and its association with mild cognitive impairment (MCI) progression in PD patients.
• Validated predictive models using discovery (n=272) and replication (n=177) cohorts.
• Employed time-dependent area under the curves (AUCs) to evaluate model accuracy.

Main Results:

• Identified five transcripts significantly associated with MCI progression in PD.
• The IGLC1 transcript model accurately predicted MCI progression (average time-dependent AUCs >0.82) in both cohorts.
• A cognitive survival score (CogSs) derived from the IGLC1 model demonstrated high early-stage prediction accuracy (AUC ≥0.91).

Conclusions:

• Uncovered five blood-based transcripts associated with cognitive decline in PD.
• Developed predictive models for early screening of cognitive impairment risk in PD patients.
• These findings support personalized medicine approaches for Parkinson's disease.