Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profiles.

ABSTRACT: Considering the burden of depression and the lack of efficacy of available treatments, there is a need for biomarkers to predict tailored or personalized treatments. However, identifying reliable biomarkers for depression has been challenging, likely owing to the vast symptom heterogeneity and high rates of comorbidity that exists. Examining biomarkers that map onto dimensions of depression as well as shared symptoms/constructs that cut across disorders could be most effective for informing personalized treatment approaches. With a sample of 539 young adults, we conducted a principal component analysis (PCA) followed by hierarchical cluster analysis to develop transdiagnostic clusters of depression and anxiety symptoms. We collected blood to assess whether neuroendocrine (cortisol) and inf

SUBMITTER: Franklyn SI 

PROVIDER: S-EPMC8971490 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature