Analysis of Gender Differences in Transcriptomes of Postmortem Brain Tissues from Psychiatric Patients

Background

Gender differences in psychiatric patients are a well-documented phenomenon. Disorders such as Schizophrenia (SCZ), Bipolar Disorder (BD), and Autism Spectrum Disorder (ASD) all exhibit significant gender differences. However, the specific mechanisms underlying these differences remain unclear. This paper aims to explore the transcriptomic characteristics of gender differences in psychiatric patients by analyzing transcriptome data from postmortem prefrontal cortex brain samples, with the goal of uncovering the potential pathological mechanisms of these three psychiatric disorders in different genders.

Source of the Paper

This study, titled “Transcriptomic sex differences in postmortem brain samples from patients with psychiatric disorders,” is authored by Yan Xia et al. from several internationally renowned research institutions, including the Broad Institute of MIT and Harvard, Massachusetts General Hospital, and Central South University. The paper was published in the journal “Science Translational Medicine” on May 23, 2024.

Research Process and Methods

Study Subjects and Data Sources

The study utilized data from 2160 adult postmortem prefrontal cortex brain samples from the PsychENCODE project, including 928 patients and 1232 controls without known psychiatric disorders. Specifically, there were 593 patients with schizophrenia, 253 with bipolar disorder, and 82 with autism spectrum disorder. The transcriptome data of these samples were analyzed using RNA sequencing, with separate studies for males and females to explore the functional transcriptomic characteristics in different genders.

Differential Gene Expression Analysis

First, the study conducted gender-stratified differential gene expression analysis between cases and controls. This part of the analysis compared the number of differentially expressed genes (DEGs), effect sizes, and characteristics of transcriptomic dysfunction burdens between genders. Then, direct expression comparisons were carried out to comprehensively evaluate the molecular characteristics in different genders.

Gene Co-expression Network Analysis

The study also conducted Weighted Gene Co-expression Network Analysis (WGCNA) on gender-stratified samples to construct co-expression networks. Changes in network structures were examined through module preservation tests and connectivity difference analyses. Subsequently, through Module Differential Connectivity (MDC) analysis, modules with significant connectivity changes were identified, and enrichment analyses were performed to determine their functions.

Results

Differential Gene Expression Burden

The study showed that female patients exhibited higher transcriptomic burdens in schizophrenia, bipolar disorder, and autism spectrum disorder compared to male patients. Female brain samples displayed more DEGs and greater gene expression changes. Additionally, the samples from female patients demonstrated higher overall connectivity dysfunctions, indicated by a higher proportion of connectivity changes in gene co-expression modules and a higher connectivity burden.

Gene Co-expression Network Burden

In the co-expression network analysis, female patients displayed significant gender differences in module connectivity changes. Specifically, female patients, compared to male patients, showed more connectivity change modules in their gene co-expression networks. Furthermore, these modules were enriched with genes related to immune and synaptic functions, suggesting that these functional pathways may be associated with gender differences in psychiatric disorders.

Gender-specific Functional Modules

Certain gene co-expression modules exhibited significant gender differences across the three psychiatric disorders. The M1 module was related to synaptic function, while the M13 module was associated with immune function. Some hub genes within these modules, such as SCN2A, FGF14, and C3, may play important roles in the gender-specific pathological mechanisms of psychiatric disorders.

Conclusion

This study is the first to reveal the transcriptomic functional dysfunction characteristics of schizophrenia, bipolar disorder, and autism spectrum disorder patients across different genders, indicating that female patients bear a higher transcriptomic burden in these diseases. Additionally, the study emphasizes the potential role of immune and synaptic-related pathways in the gender differences of psychiatric disorders. These findings not only help to understand the mechanisms underlying gender differences in psychiatric disorders but also provide a scientific basis for developing more targeted diagnostic and therapeutic methods considering gender-specific factors.

Significance and Value of the Study

This study reveals the complexity of gender differences in psychiatric patients from a transcriptomic perspective. By deeply understanding the gender-specific changes in gene expression and network connectivity, the research provides new insights into explaining the epidemiological and clinical features of these disorders. This transcriptomic burden-based model may offer important guidance for future research and clinical practice, especially in developing more effective gender-specific treatment plans.

The importance of this study lies in highlighting the significance of considering gender factors when researching psychiatric disorders. Future research can build on these findings to further explore the roles of gender in other complex diseases and how this knowledge can be leveraged to improve clinical treatment strategies.