Identify depressive phenotypes by applying RDOC domains to the PHQ-9

Area of Science:

• Psychiatry and Mental Health
• Neuroscience
• Public Health

Background:

• Major depression is a heterogeneous disorder with various phenotypic expressions.
• Understanding these phenotypes is crucial for effective diagnosis and treatment.
• The Patient Health Questionnaire (PHQ)-9 is a widely used depression screening tool.

Purpose of the Study:

• To characterize depressive phenotypes within the PHQ-9 using the Research Domain Criteria (RDoC) framework.
• To identify distinct symptom clusters associated with major depression.
• To explore demographic and clinical factors influencing these phenotypes.

Main Methods:

• Utilized cross-sectional data from the National Health and Nutrition Examination Survey (N=10,561).
• Employed factor analysis and qualitative analysis to map PHQ-9 items onto RDoC domains.
• Conducted multiple indicator multiple cause analysis to examine group differences.

Main Results:

• A four-factor model demonstrated excellent fit for the PHQ-9, aligning with RDoC domains.
• Identified phenotypes related to Negative Valence (Externalizing/Internalizing), Arousal/Regulatory Systems, and Cognitive/Sensorimotor Systems.
• Phenotypic trait expressions varied significantly by age, race/ethnicity, sex, and comorbidity count.

Conclusions:

• The PHQ-9 can be effectively mapped to RDoC domains, yielding distinct phenotypic clusters.
• While a single depression score is often useful, understanding specific phenotypes may refine assessment.
• Future research should investigate personalized care strategies based on identified depression phenotypes.