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Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression
Published on: May 19, 2015
Polygenic risk for depression and resting-state functional connectivity of subgenual anterior cingulate cortex in
Yu Chen1, Huey-Ting Li2, Xingguang Luo2
1From the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn., USA (Chen, Luo, Ide, C.-S. Li); Yale University, New Haven, Conn., USA (H.-T. Li); the Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China (G. Li); the Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China (G. Li); the Department of Neuroscience, Yale University School of Medicine, New Haven, Conn., USA (C.-S Li); the Interdepartment Neuroscience Program, Yale University, New Haven, Conn., USA (C.-S. Li); the Wu Tsai Institute, Yale University, New Haven, Conn., USA (C.-S. Li) yu.chen.yc838@yale.edu.
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.
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