Complex Relationship Between Gene Expression and Diseases: A Transcriptomics Approach

The understanding of how gene expression changes in healthy and diseased tissues is crucial for elucidating the molecular mechanisms underlying human diseases. Differential gene expression (DE) studies have been instrumental in identifying genes that exhibit altered expression levels between diseased and healthy states. However, a large group of genes appears to be differentially expressed across various studies regardless of the biological context. This article delves into the relationships between genes, their differential expression, and diseases by analyzing transcriptomic data from healthy tissues and exploring how these genes are implicated in various pathological conditions.

A set of 9,972 disease genes was generated from five gene-phenotype databases (OMIM, ORPHANET, DDG2P, DisGeNet, and MalaCards) and the International Union of Immunological Societies (IUIS) report by Kolobkov et al. (2022). Transcriptomic profiles of disease and non-disease genes in healthy tissues were obtained from the Human Protein Atlas (HPA) website. The dependency between expression in healthy tissues and gene occurrence in Gene Expression Omnibus (GEO) series was analyzed using tools within the Enrichr libraries. Additionally, Gene Ontology (GO) and Human Phenotype Ontology (HPO) terms were used to annotate the results of expression studies.

Kolobkov et al. (2022) is validated previous findings that disease genes tend to be expressed at higher levels in tissues where alterations of these genes cause pathology compared to other tissues. Preferentially differentially expressed genes were generally highly expressed in one or multiple tissues and were enriched for disease genes. GO enrichment analyses revealed that both down- and up-regulated DE genes most often participated in immune response, translation, and tissue-specific processes. A connection between DE-related pathology and the diversity of HPO terms was also found, indicating that investigating the link between expression and phenotype can enhance the understanding of the development and progression of human diseases.

Kolobkov et al. (2022) highlight the importance of considering gene expression profiles in healthy tissues to understand the impact of gene expression changes in disease conditions. Their findings support the notion that a specific fraction of genes, which are generally highly expressed and enriched for disease genes, show predictable differential expression across various pathological conditions. The frequent overlaps between down- and up-regulated biological processes suggest compensatory involvement in the same biological processes, which may be crucial for maintaining tissue homeostasis in response to disease stimuli. rewrite it

Conclusions: The study provides insights into the relationships between gene expression in healthy tissues, differential expression in disease studies, and the diversity of phenotypic manifestations. The findings underscore the value of integrating transcriptomic data with gene-phenotype associations to deepen the understanding of the molecular mechanisms underlying human diseases. This approach can contribute to the identification of potential biomarkers and therapeutic targets for various diseases.

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