Polygenic risk for depression and resting-state functional connectivity of subgenual anterior cingulate cortex in young adults.

Yu Chen, Huey-Ting Li, Xingguang Luo, Guangfei Li, Jaime S Ide, Chiang-Shan R Li
Author Information
  1. Yu Chen: From 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.
  2. Huey-Ting Li: From 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).
  3. Xingguang Luo: From 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).
  4. Guangfei Li: From 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).
  5. Jaime S Ide: From 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).
  6. Chiang-Shan R Li: From 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).

Abstract

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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Grants

  1. R01 DA051922/NIDA NIH HHS
  2. UL1 TR001863/NCATS NIH HHS

MeSH Term

Humans
Gyrus Cinguli
Male
Female
Young Adult
Magnetic Resonance Imaging
Connectome
Adult
Multifactorial Inheritance
Depression
Genetic Predisposition to Disease
Default Mode Network
Adolescent
Nerve Net

Word Cloud

Created with Highcharts 10.0.0depressionriskseverityPRSsgACCconnectivityrsFCyoungadultsmaysubclinicalsexassociationrolesubgenualanteriorcingulatecortexresting-statefunctionalpolygenicwhole-braindatahealthylowersomaticcomplaintsfindingsBACKGROUND:GeneticvariantsconfermodulatingbrainstructurefunctionevidenceunderscoredkeysoughtexamineassociatedpopulationMETHODS:Followingpublishedprotocolscomputedseed-basedcalculatedscoresusingHumanConnectomeProjectperformedregressionsymptomssinglemodelparticipantscontrollingageraceethnicityalcoholusehouseholdincomeevaluatedresultscorrectedthresholdRESULTS:included717founddefaultmodenetworkfrontalregionssgACC-cerebellaralsonoteddifferencescorrelatesadditionalsetanalysesobservedsignificantcorrelationwellalteredsgACC-somatosensorycorticalLIMITATIONS:currentconsideredspecificgeneralizepatientsdepressivedisordersCONCLUSION:highlightpivotaldistinctsgACC-basednetworksgeneticpredispositionmanifestationamongDistinguishingmarkersimplicationsdevelopingearlyeffectivetreatmentspeoplePolygenic

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