.png){kind=icon}
.png){kind=icon}
Return
Polygenic risk for depression and resting-state functional connectivity of subgenual anterior cingulate cortex in young adults
.png){kind=icon}
OA
AI
Y
H
X
G
J
C
DOI：10.1503/jpn.240087.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Background: Genetic variants may confer risk for depression by modulating brain structure and function; evidence has underscored the key role of the subgenual anterior cingulate cortex (sgACC) in depression. We sought to examine how the resting-state functional connectivity (rsFC) of the sgACC was associated with polygenic risk for depression in a subclinical population.Methods: Following published protocols, we computed seed-based whole-brain sgACC rsFC and calculated polygenic risk scores (PRS) using data from healthy young adults from the Human Connectome Project. We performed whole-brain regression against PRS and severity of depression symptoms in a single model for all participants and by sex, controlling for age, sex, race or ethnicity, alcohol use severity, and household income. We evaluated the results at a corrected threshold.Results: We included data for 717 healthy young adults. We found lower rsFC between the sgACC and the default mode network and frontal regions in association with PRS and lower sgACC-cerebellar rsFC in association with depression severity. We also noted differences by sex in the connectivity correlates of PRS and depression severity. In an additional set of analyses, we observed a significant correlation between PRS and somatic complaints, as well as altered sgACC-somatosensory cortical connectivity in association with the severity of somatic complaints.Limitations: The current findings should be considered specific to subclinical depression and may not generalize to patients with depressive disorders.Conclusion: Our findings highlight the pivotal role of distinct sgACC-based networks in the genetic predisposition for depression and the manifestation of depression among young adults with subclinical depression. Distinguishing the risk from severity markers of depression may have implications in developing early and effective treatments for people at risk for depression.
Keywords:
SUBCLINICAL DEPRESSION
MAJOR DEPRESSION
SEX-DIFFERENCES
DEFAULT-MODE
METAANALYSIS
DISORDER
BRAIN
CEREBELLUM
SYMPTOMS
ABNORMALITIES
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.3
Papers:
802
Citations:
3.7K
Organization
Cited Papers