Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Adolescent depression shows high clinical heterogeneity. Brain functional networks serve as a powerful tool for investigating neural mechanisms underlying depression profiles. A key challenge is to characterize how variation in brain functional organization links to behavioral features and psychosocial environmental influences.
Methods: We recruited 80 adolescents with major depressive disorder (MDD) and 42 healthy controls (HCs). First, we estimated the differences in functional connectivity of resting-state networks (RSN) between the two groups. Then, we used sparse canonical correlation analysis to characterize patterns of associations between RSN connectivity and symptoms, cognition, and psychosocial environmental factors in MDD adolescents. Clustering analysis was applied to stratify patients into homogenous subtypes according to these brain-behavior-environment associations.
Results: MDD adolescents showed significantly hyperconnectivity between the ventral attention and cingulo-opercular networks compared with HCs. We identified one reliable pattern of covariation between RSN connectivity and clinical/environmental features in MDD adolescents. In this pattern, psychosocial factors, especially the interpersonal and family relationships, were major contributors to variation in connectivity of salience, cingulo-opercular, ventral attention, subcortical and somatosensory-motor networks. Based on this association, we categorized patients into two subgroups which showed different environment and symptoms characteristics, and distinct connectivity alterations. These differences were covered up when the patients were taken as a whole group.
Conclusion: This study identified the environmental exposures associated with specific functional networks in MDD youths. Our findings emphasize the importance of the psychosocial context in assessing brain function alterations in adolescent depression and have the potential to promote targeted treatment and precise prevention.
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http://dx.doi.org/10.1016/j.ajp.2024.104009 | DOI Listing |
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