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@ARTICLE{Janiri:866113,
author = {Janiri, Delfina and Moser, Dominik A. and Doucet, Gaelle E.
and Luber, Maxwell J. and Rasgon, Alexander and Lee, Won Hee
and Murrough, James W. and Sani, Gabriele and Eickhoff,
Simon B. and Frangou, Sophia},
title = {{S}hared {N}eural {P}henotypes for {M}ood and {A}nxiety
{D}isorders},
journal = {JAMA psychiatry},
volume = {77},
number = {2},
issn = {2168-622X},
address = {Chicago, Ill.},
publisher = {JAMA},
reportid = {FZJ-2019-05332},
pages = {172-179},
year = {2020},
note = {This work was supported in part through the computational
resources and staff expertise provided by Scientific
Computing at the Icahn School of Medicine at Mount Sinai.
Drs Frangou and Doucet received support from the National
Institute of Mental Health (R01-MH104284 and R01-MH116147).
Dr Eickhoff received support by the Deutsche
Forschungsgemeinschaft (DFG, EI 816/11-1), the National
Institute of Mental Health (R01-MH074457), and the European
Union’s Horizon 2020 Research and Innovation Programme
under Grant Agreements 720270 (HBP SGA1) and 785907 (HBP
SGA2).},
abstract = {Importance:Major depressive disorder, bipolar disorder,
posttraumatic stress disorder, and anxiety disorders are
highly comorbid and have shared clinical features. It is not
yet known whether their clinical overlap is reflected at the
neurobiological level.Objective:To detect transdiagnostic
convergence in abnormalities in task-related brain
activation.Data Source:Task-related functional magnetic
resonance imaging articles published in PubMed, Web of
Science, and Google Scholar during the last decade comparing
control individuals with patients with mood, posttraumatic
stress, and anxiety disorders were examined.Study
Selection:Following Preferred Reporting Items for Systematic
Reviews and Meta-analyses reporting guidelines, articles
were selected if they reported stereotactic coordinates of
whole-brain-based activation differences between adult
patients and control individuals.Data Extraction and
Synthesis:Coordinates of case-control differences coded by
diagnosis and by cognitive domain based on the research
domain criteria were analyzed using activation likelihood
estimation.Main Outcomes and Measures:Identification of
transdiagnostic clusters of aberrant activation and
quantification of the contribution of diagnosis and
cognitive domain to each cluster.Results:A total of 367
experiments (major depressive disorder, 149; bipolar
disorder, 103; posttraumatic stress disorder, 55; and
anxiety disorders, 60) were included comprising observations
from 4507 patients and 4755 control individuals. Three
right-sided clusters of hypoactivation were identified
centered in the inferior prefrontal cortex/insula (volume,
2120 mm3), the inferior parietal lobule (volume, 1224 mm3),
and the putamen (volume, 888 mm3); diagnostic differences
were noted only in the putamen (χ23 = 8.66;
P = .03), where hypoactivation was more likely in
bipolar disorder (percentage $contribution = 72.17\%).$
Tasks associated with cognitive systems made the largest
contribution to each cluster (percentage contributions
$>29\%).$ Clusters of hyperactivation could only be detected
using a less stringent threshold. These were centered in the
perigenual/dorsal anterior cingulate cortex (volume, 2208
mm3), the left amygdala/parahippocampal gyrus (volume, 2008
mm3), and the left thalamus (volume, 1904 mm3). No
diagnostic differences were observed (χ23 < 3.06;
P > .38), while tasks associated with negative valence
systems made the largest contribution to each cluster
(percentage contributions $>49\%).$ All findings were robust
to the moderator effects of age, sex, and magnetic field
strength of the scanner and medication.Conclusions and
Relevance:In mood disorders, posttraumatic stress disorder,
and anxiety disorders, the most consistent transdiagnostic
abnormalities in task-related brain activity converge in
regions that are primarily associated with inhibitory
control and salience processing. Targeting these shared
neural phenotypes could potentially mitigate the risk of
affective morbidity in the general population and improve
outcomes in clinical populations.},
cin = {INM-7},
ddc = {610},
cid = {I:(DE-Juel1)INM-7-20090406},
pnm = {574 - Theory, modelling and simulation (POF3-574) / HBP
SGA2 - Human Brain Project Specific Grant Agreement 2
(785907)},
pid = {G:(DE-HGF)POF3-574 / G:(EU-Grant)785907},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:31664439},
UT = {WOS:000512049000012},
doi = {10.1001/jamapsychiatry.2019.3351},
url = {https://juser.fz-juelich.de/record/866113},
}