Polygenic risk of depression and resting state connectivity of subgenual ACC in young adults
Poster No:
515
Submission Type:
Abstract Submission
Authors:
Huey-Ting Li1, Yu Chen2, Xingguang Luo2, Jaime Ide2, Chiang-Shan Li2
Institutions:
1Yale University, Hamden, CT, 2Yale University School of Medicine, New Haven, CT
First Author:
Co-Author(s):
Introduction:
Genetic variants may confer risks for depression by modulating brain structure and function. Converging evidence has associated depression with brain network dysfunction and highlighted the role of frontolimbic circuits in the pathophysiology of depression. In particular, prior evidence has underscored a key role of the subgenual anterior cingulate cortex (sgACC) in depression. However, the great majority of previous studies were conducted in clinical samples, where the effects of the duration, outcome, and comorbidities of depression could not be readily distinguished from those conferred by genetic risks. Here, we built on the literature and examined how the resting state functional connectivity (rsFC) of the sgACC was associated with polygenic risks (PRS) for depression in a neurotypical sample curated from the Human Connectome Project (HCP).
Methods:
We followed published routines and computed seed-based whole-brain sgACC rsFC and PRS of 717 young adults curated from the HCP (a total of 489 subjects were excluded because of missing or questionable imaging or clinical data). The PRS was computed for individuals of the initial cohort of 1,206 young adults using a base sample of 170,756 unrelated cases with major depressive disorder and 329,443 unrelated healthy controls from the meta-analysis of GWAS of 33 UK Biobank cohorts of the Psychiatric Genomics Consortium (Howard et al., 2018). Participants completed the Achenbach Adult Self Report (Achenbach et al., 2003), including the DSM-oriented subscale of depression (14 items). The age- and sex- adjusted depression T score was used in the analyses, with higher T scores indicating higher severity of depressive symptoms. Participants were also evaluated with the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA). As in our previous studies (Li et al., 2022), we performed a principal component analysis on the 15 interrelated drinking metrics and identified one principal component (PC1) with an eigenvalue > 1 that accounted for 50.54% of the variance. SSAGA also collected household income data, which could serve as a surrogate of socioeconomic factors that may influence the development of depression. We performed whole-brain regression against PRS and severity of depression symptoms in a single model for all subjects and for men and women alone, controlling for age, sex (for all), race, drinking PC1, and household income, and evaluated the results at a corrected threshold. For findings obtained in men or women alone, we followed up with slope tests to confirm sex differences.
Results:
In whole-brain regressions, higher PRS were correlated with weaker sgACC rsFC with bilateral superior frontal gyri (SFG) and bilateral precuneus/posterior cingulate cortex, and higher depression T scores were correlated with weaker rsFC between sgACC and right cerebellum (CBL) across all subjects (Fig. 1A). In men alone, higher PRS were correlated with stronger sgACC-left CBL and weaker sgACC-left SFG rsFC, and higher depression T scores were correlated with weaker sgACC rsFC with bilateral CBL and insula (Fig. 1B). In women alone, higher PRS were correlated with stronger sgACC rsFC with bilateral lingual and calcarine gyri (Fig. 1C). For those clusters identified in men and women alone, we confirmed sex differences in the correlations (with slope t's ≥ 2.40 and p's ≤ 0.017; Fig. 2).
Conclusions:
Our findings collectively highlighted the pivotal role of distinct sgACC-based networks in the genetic predisposition to depression and the clinical manifestation of depression. The findings also suggest sex differences in the neural markers of the genetic risks of depression. Distinguishing the risk from severity markers of depression may have implications in developing early diagnostics and effective treatments for individuals at risk for depression.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Genetics:
Genetic Association Studies
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
ADULTS
Affective Disorders
Anxiety
Emotions
FUNCTIONAL MRI
Limbic Systems
Phenotype-Genotype
Psychiatric Disorders
Sexual Dimorphism
Systems
1|2Indicates the priority used for review
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Howard, D.M., Adams, M.J., Shirali, M., Clarke, T.-K., Marioni, R.E., Davies, G., Coleman, J.R., Alloza, C., Shen, X., Barbu, M.C., 2018. Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways. Nature communications 9, 1470.
Li, G., Chen, Y., Chaudhary, S., Tang, X., Li, C.R., 2022. Loss and frontal striatal reactivities characterize alcohol use severity and rule-breaking behavior in young adult drinkers. Biol Psychiatry Cogn Neurosci Neuroimaging. 7(10):1007-1016.