| Literature DB >> 33007777 |
Erica B Baller1, Antonia N Kaczkurkin1,2, Aristeidis Sotiras3,4,5, Azeez Adebimpe1, Danielle S Bassett1,6,7,8,9,10,11, Monica E Calkins1,12, Ganesh B Chand3,5, Zaixu Cui1, Raquel E Gur1,3,9,12, Ruben C Gur1,3,12, Kristin A Linn13, Tyler M Moore1,12, David R Roalf1,12, Erdem Varol3,5, Daniel H Wolf1,5,12, Cedric H Xia1, Christos Davatzikos3,5, Theodore D Satterthwaite14,15,16.
Abstract
Depression is a common psychiatric illness that often begins in youth, and is sometimes associated with cognitive deficits. However, there is significant variability in cognitive dysfunction, likely reflecting biological heterogeneity. We sought to identify neurocognitive subtypes and their neurofunctional signatures in a large cross-sectional sample of depressed youth. Participants were drawn from the Philadelphia Neurodevelopmental Cohort, including 712 youth with a lifetime history of a major depressive episode and 712 typically developing (TD) youth matched on age and sex. A subset (MDD n = 368, TD n = 200) also completed neuroimaging. Cognition was assessed with the Penn Computerized Neurocognitive Battery. A recently developed semi-supervised machine learning algorithm was used to delineate neurocognitive subtypes. Subtypes were evaluated for differences in both clinical psychopathology and brain activation during an n-back working memory fMRI task. We identified three neurocognitive subtypes in the depressed group. Subtype 1 was high-performing (high accuracy, moderate speed), Subtype 2 was cognitively impaired (low accuracy, slow speed), and Subtype 3 was impulsive (low accuracy, fast speed). While subtypes did not differ in clinical psychopathology, they diverged in their activation profiles in regions critical for executive function, which mirrored differences in cognition. Taken together, these data suggest disparate mechanisms of cognitive vulnerability and resilience in depressed youth, which may inform the identification of biomarkers for prognosis and treatment response.Entities:
Mesh:
Year: 2020 PMID: 33007777 PMCID: PMC8027806 DOI: 10.1038/s41386-020-00871-w
Source DB: PubMed Journal: Neuropsychopharmacology ISSN: 0893-133X Impact factor: 7.853