Functional connectivity alterations in depression and their associations with gene expression
Poster No:
536
Submission Type:
Abstract Submission
Authors:
Rui Qian1, Huaijin Gao1, Chengjiaao Liao1, Wen Zhu1, Minmin Wang2, Dan Wu1, Zhiyong Zhao1
Institutions:
1Zhejiang University, Hangzhou, China, 2Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China
First Author:
Co-Author(s):
Introduction:
Major Depressive Disorder (MDD) has persisted as one of the predominant psychiatric disorders for over a century, exerting a substantial adverse impact on patients' life. Previous studies have reported aberrant functional connectivity strength (FCS) in MDD, which exhibited distinct patterns in first-episode, drug-naïve (FEDN) and recurrent MDD (RMDD) [1,2]. However, the molecular basis of FCS differences between first-episode and recurrent MDD remains unexplored. Recent studies have demonstrated a close relationship between FCS and gene expression in the brain cortex of healthy populations [3]. Therefore, this study aims to explore the genetic basis underlying the differences of FCS among different MDD subtypes.
Methods:
Resting-state fMRI data from the REST-meta-MDD Consortium were utilized in this study, comprising four paired groups: 848 MDD and 794 normal control (NC), 232 FEDN and 394 NC, 189 RMDD and 427 NC, 119 FEDN and 72 RMDD. The brain was divided into 116 regions of interest (ROI) according to Anatomical Automatic Labeling (AAL) atlas, and then ROI-wise FCS was calculated using Pearson correlation with a threshold of R ≥ 0.25 [4]. Finally, we compared differences between groups using a linear mixed model controlling age, sex, education and head motion as covariates, and site as a random factor [5]. False Discovery Rate (FDR) correction was used to control false positive discoveries.
The ROI-wise gene expression profile was obtained from the AHBA database using abagen toolbox [6] with AAL atlas. Then, partial least squares (PLS) regression analysis [7] was employed to explore the association between transcriptional profiles and FCS differences. Finally, the genes were ranked based on corrected weights reflecting their contribution to the PLS regression component, and further were applied to enrichment analysis to identify enriched Gene Ontology terms using Gorilla [8] (http://cbl-gorilla.cs.technion.ac.il/), considering all three ontology categories: biological process, molecular function, and cellular component.
The ROI-wise gene expression profile was obtained from the AHBA database using abagen toolbox [6] with AAL atlas. Then, partial least squares (PLS) regression analysis [7] was employed to explore the association between transcriptional profiles and FCS differences. Finally, the genes were ranked based on corrected weights reflecting their contribution to the PLS regression component, and further were applied to enrichment analysis to identify enriched Gene Ontology terms using Gorilla [8] (http://cbl-gorilla.cs.technion.ac.il/), considering all three ontology categories: biological process, molecular function, and cellular component.
Results:
Significant increase in FCS was observed in the left angular gyrus in total MDD and in the right posterior cingulate gyrus, left and right thalamus, and cerebellum in RMDD compared to NC (Fig. 1). No significant difference was found between FEDN and NC and between FEDN and RMDD.
The first PLS component (PLS1) showed the highest interpretable variance among all components (25.4% for FEDN vs. NC, 35.9% for RMDD vs. NC). The PLS1 showing positive correlation with FCS alteration in FEDN displayed high expression in the frontal lobe and primary motor cortex but low expression in the occipital and temporal lobes (Fig. 2a), while that in RMDD showed low expression across the entire brain, especially in the frontal and parietal regions (Fig. 2b). Moreover, the PLS1 gene sequence enriched in the biological process of the electron transport chain for FEDN (Fig. 2c), whereas it enriched in the biological process of regulation of nucleic acid-related metabolic processes for RMDD (Fig. 2d).
The first PLS component (PLS1) showed the highest interpretable variance among all components (25.4% for FEDN vs. NC, 35.9% for RMDD vs. NC). The PLS1 showing positive correlation with FCS alteration in FEDN displayed high expression in the frontal lobe and primary motor cortex but low expression in the occipital and temporal lobes (Fig. 2a), while that in RMDD showed low expression across the entire brain, especially in the frontal and parietal regions (Fig. 2b). Moreover, the PLS1 gene sequence enriched in the biological process of the electron transport chain for FEDN (Fig. 2c), whereas it enriched in the biological process of regulation of nucleic acid-related metabolic processes for RMDD (Fig. 2d).
·Fig1. The FCS differences in the total MDD vs. NC and RMDD vs. NC. PCG.L: right posterior cingulate gyrus; THA.L/THA.R left/right thalamus.
·Fig2. Association between FCS alterations and gene expression. PLS1 of FEDN and RMDD was enriched in biological process of electron transportation and regulation of metabolic processes, respectively.
Conclusions:
We found RMDD showed FCS values increase in several brain regions, while FEDN had no significant alterations compared with NC. This supported previous findings that FEDN and RMDD differed in functional connectivity abnormality [2]. Moreover, transcription-neuroimaging association analysis demonstrated that the genes related to FCS alterations of MDD subtypes enriched in distinct biological processes, specifically electron transposition in the mitochondrion for FEDN and nucleic acid metabolism for RMDD, which were related to mitochondrial dysfunction and epigenetic modification role as molecular pathways of MDD [9]. These findings offer new insights into the biological substrates underlying FCS differences between MDD patients and NC.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Genetics:
Transcriptomics 2
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling
Neuroinformatics and Data Sharing:
Brain Atlases
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
FUNCTIONAL MRI
Psychiatric Disorders
Other - Transcriptomics
1|2Indicates the priority used for review
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