Identify depressive phenotypes by applying RDOC domains to the PHQ-9. (April 2020) - Gunzler, Douglas; Sehgal, Ashwini R.; Kauffman, Kelley; Davey, Christine Horvat; Dolata, Jacqueline; Figueroa, Maria; Huml, Anne; Pencak, Julie; Sajatovic, Martha
Highlights: Four depressive phenotypes found in the patient health questionnaire (PHQ)−9 in a large, nationally representative U.S sample (Negative Valence Systems and Externalizing, Negative Valence Systems and Internalizing, Arousal and Regulatory Systems and Cognitive and Sensorimotor Systems). Research Domain Criteria (RDoC) research framework was useful in evaluating the phenotypic traits of depression. Differences in the means of the phenotypic traits were found by age, race/ethnicity, sex and number of comorbidities. High correlation between the four depressive phenotypes indicates screening and monitoring for depression study population using a single depression score is likely useful in most circumstances. Describing these phenotypes has potential to provide a step towards developing personalized medicine approaches for varying patterns of depressive symptoms. 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.