TY - JOUR
T1 - Neurocognitive and functional heterogeneity in depressed youth
AU - Baller, Erica B.
AU - Kaczkurkin, Antonia N.
AU - Sotiras, Aristeidis
AU - Adebimpe, Azeez
AU - Bassett, Danielle S.
AU - Calkins, Monica E.
AU - Chand, Ganesh B.
AU - Cui, Zaixu
AU - Gur, Raquel E.
AU - Gur, Ruben C.
AU - Linn, Kristin A.
AU - Moore, Tyler M.
AU - Roalf, David R.
AU - Varol, Erdem
AU - Wolf, Daniel H.
AU - Xia, Cedric H.
AU - Davatzikos, Christos
AU - Satterthwaite, Theodore D.
N1 - Funding Information:
This work was supported by grants from the National Institute of Mental Health (NIMH; Grant Numbers: R01MH120482, R01MH107703, R01MH112847, and R01MH113550 to TDS; 2T32MH019112-29A1 to EBB; K99MH117274 to ANK; R01MH107235 to RCG; R01MH13565 to DHW; and R01MH11207 to CD). Additional support was provided by the Lifespan Brain Institute at the Children’s Hospital of Philadelphia and Penn Medicine. The PNC was funded by RC2 Grants MH089983 and MH089924 to REG from the NIMH. Support for developing multivariate pattern analysis software (AS & TDS) was provided by a seed grant by the Center for Biomedical Computing and Image Analysis (CBICA) at Penn. Support was also provided by a NARSAD Young Investigator Award (ANK) as well as a Penn PROMOTES Research on Sex and Gender in Health grant (ANK) awarded as part of the Building Interdisciplinary Research Careers in Women’s Health (BIRCWH) Grant (K12 HD085848) at the University of Pennsylvania. The authors declare no competing interests.
Publisher Copyright:
© 2020, The Author(s), under exclusive licence to American College of Neuropsychopharmacology.
PY - 2021/3
Y1 - 2021/3
N2 - 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.
AB - 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.
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U2 - 10.1038/s41386-020-00871-w
DO - 10.1038/s41386-020-00871-w
M3 - Article
C2 - 33007777
AN - SCOPUS:85091772446
SN - 0893-133X
VL - 46
SP - 783
EP - 790
JO - Neuropsychopharmacology
JF - Neuropsychopharmacology
IS - 4
ER -