Dataset Information

Obsessive-Compulsive Disorder Interactome Profile Analysis: A Perspective From Molecular Mechanism.

ABSTRACT:

Introduction

Obsessive-Compulsive Disorder (OCD) is one of the complex neuropsychiatric conditions. This disorder disables individuals in many different aspects of their personal and social life. Interactome analysis may provide a better understanding of this disorder's molecular origin and its underlying mechanisms.

Methods

In this study, the OCD-associated genes were extracted from the literature. The criterion for gene selection was to choose genes with at least one significant report. Furthermore, by applying Cytoscape and its plugins, protein-protein interaction network, and gene ontology of the 31 candidate genes related to OCD from genetic association studies is examined. The cross-validation method was used for network centrality assessment.

Results

A scale-free network, including 1940 nodes and 3269 edges for 31 genes, was constructed. According to the network centrality evaluation, ESR1, TNFα, DRD2, DRD4, HTR1B, HTR2A, and CDH2 showed the highest values and can be considered hub-bottlenecks elements. It is also confirmed by the number of 123 cross-validation tests that the frequency of these essential genes remains unaltered against the initial seed genes' changes with the accuracy of 0.962. Besides, enrichment analysis identified four highlighted biological processes related to the 31 candidate genes. The top biological processes are determined as dopamine transport, learning, memory, and monoamine transport.

Conclusion

Among 31 initial genes, 7 were introduced as crucial elements for onset and development in OCD and can be suggested for further investigations. Furthermore, the complex molecular origin of OCD requires high-throughput screening for diagnosis and treatment goals. The findings are a possible valuable source to establish molecular-based diagnostic tools for OCD.

SUBMITTER: Zamanian-Azodi M

PROVIDER: S-EPMC8672674 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:We investigated whether obsessive-compulsive (OC) symptoms from a population-based sample could be analyzed to detect genetic variants influencing obsessive-compulsive disorder (OCD). We performed a genome-wide association studies (GWAS) on the obsession (rumination and impulsions) and compulsion (checking, washing, and ordering/precision) subscales of an abbreviated version of the Padua Inventory (N = 8,267 with genome-wide genotyping and phenotyping). The compulsion subscale showed a substantial and significant positive genetic correlation with an OCD case-control GWAS (r G = 0.61, p = .017) previously published by the Psychiatric Genomics Consortium (PGC-OCD). The obsession subscale and the total Padua score showed no significant genetic correlations (r G = -0.02 and r G = 0.42, respectively). A meta-analysis of the compulsive symptoms GWAS with the PGC-OCD revealed no genome-wide significant Single-Nucleotide Polymorphisms (SNPs combined N = 17,992, indicating that the power is still low for individual SNP effects). A gene-based association analysis, however, yielded two novel genes (WDR7 and ADCK1). The top 250 genes in the gene-based test also showed a significant increase in enrichment for psychiatric and brain-expressed genes. S-Predixcan testing showed that for genes expressed in hippocampus, amygdala, and caudate nucleus significance increased in the meta-analysis with compulsive symptoms compared to the original PGC-OCD GWAS. Thus, the inclusion of dimensional symptom data in genome-wide association on clinical case-control GWAS of OCD may be useful to find genes for OCD if the data are based on quantitative indices of compulsive behavior. SNP-level power increases were limited, but aggregate, gene-level analyses showed increased enrichment for brain-expressed genes related to psychiatric disorders, and increased association with gene expression in brain tissues with known emotional, reward processing, memory, and fear-formation functions.