Citation

Gunzler D, Sehgal AR, Kauffman K, Davey CH, Dolata J, Figueroa M, Huml A, Pencak J, Sajatovic M. Psychiatry Res. 2020; 286: e112872.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.psychres.2020.112872

PMID

32151848

PMCID

PMC7434666

Abstract

Major depression consists of multiple phenotypic traits. Our objective was to characterize depressive phenotypes in the patient health questionnaire (PHQ)-9 using the Research Domain Criteria (RDoC) research framework. Cross-sectional data were examined from the 2013-2014 (N = 5397) and 2015-2016 (N = 5164) National Health and Nutrition Examination Survey, a large, nationally representative U.S. sample. Using both factor analysis and qualitative analysis in mapping scale items along RDoC domains, a four factor model was found to be theoretically appropriate and had an excellent model fit for the PHQ-9. The factor structure consisted of phenotypes describing Negative Valence Systems and Externalizing (anhedonia and depression), Negative Valence Systems and Internalizing (depression, guilt and self-harm), Arousal and Regulatory Systems (sleep, fatigue and appetite) and Cognitive and Sensorimotor Systems (concentration and psychomotor). High correlation between these phenotypes did indicate screening and monitoring for depression study population using a single depression score is likely useful in most circumstances. In multiple indicator multiple cause analysis, differences in the means of the phenotypic traits were found by age, race/ethnicity, sex, and number of comorbidities. Future research should explore whether phenotype expression derived from readily available self-rated depression scales can help to inform more personalized care.

Language: en

Keywords

Factor analysis; Major depression; Research domain criteria; Patient health questionnaire-9; Multiple indicator multiple cause modeling; National health and nutrition examination survey