Sex-specific transcriptome similarity networks elucidate comorbidity relationships

Area of Science:

• Genomics
• Sex-based biology
• Computational biology

Background:

• Biological differences between sexes influence disease prevalence and comorbidity.
• Existing research on sex-specific disease patterns is limited, especially at the comorbidity level.
• No prior studies have identified sex-specific biological processes underlying differing comorbidities.

Purpose of the Study:

• To identify sex-specific biological processes that contribute to differing comorbidities in men and women.
• To analyze transcriptomic data for over 100 diseases independently for each sex.
• To investigate sex-specific transcriptomic similarities between comorbid diseases.

Main Methods:

• Analysis of gene expression data from public repositories for over 100 diseases.
• Independent analysis of expression data for male and female subjects.
• Calculation of similarities between differential expression profiles for disease pairs.
• Comparison of transcriptomic findings with epidemiological data on known comorbidities.

Main Results:

• 13-16% of transcriptomically similar disease pairs were found to be sex-specific.
• 53-60% of known sex-distinct comorbidities were recapitulated based on transcriptomic similarities.
• Diseases can co-occur through alternative biological pathways in men and women.
• Different drugs showed sex-specific associations with comorbid diseases.

Conclusions:

• Transcriptomic analysis reveals significant sex-specific patterns in disease comorbidities.
• Biological pathways underlying comorbidities can differ between sexes.
• Patient sex is a critical variable influencing drug efficacy and comorbidity management.