A Complex Network of Obesity‐Risk Genes Revealed by Systematic Bioinformatics and Single‐Cell Transcriptomic Analyses
The development of obesity is closely linked to genetic factors. Despite the identification of numerous genes associated with an increased risk of obesity in humans, a comprehensive understanding of their biological roles has not been achieved. In our extensive bioinformatics study, we identified 802 core genes implicated in obesity. Our protein-protein interaction (PPI) network analysis revealed that these genes form a tightly connected functional network primarily involved in neurological and metabolic regulatory processes. Moreover, our in-depth analysis of single-cell transcriptomic datasets from the human hypothalamus, pancreatic islets, adipose tissue, and liver has shed light on the distinct expression profiles of these obesity-linked genes across various tissue and cell types. This analysis also highlighted the biological processes they influence and the upstream transcriptional regulatory networks involved. Our study not only uncovers the complicated regulatory role of genetic factors in the pathogenesis and progression of obesity but also establishes a close link between the expression patterns and functional roles of these obesity-associated genes. This study provides crucial insights for advancing our understanding of the genetic mechanisms underlying obesity.
Authors
- Y. Liu (ORCID: https://orcid.org/0009-0008-9946-9912)
- Shankai Yin (ORCID: https://orcid.org/0000-0003-3689-8599)
- Yiming Hu (ORCID: https://orcid.org/0000-0002-5143-2239)
- Feng Liu (ORCID: https://orcid.org/0000-0002-4442-7028)
- Junhui Hu (ORCID: https://orcid.org/0000-0001-9260-2858)
- Xu Xu (ORCID: https://orcid.org/0000-0001-9005-1466)
- Honglei Yuan (ORCID: https://orcid.org/0009-0006-1711-1542)
Institutions
- Shanghai Sixth People's Hospital (CN)
Publication Details
- Journal
- Journal of Obesity
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1155/jobe/7821115
- Citations
- 1
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- National Natural Science Foundation of China
- Ministry of Science and Technology of the People's Republic of China
- Science and Technology Commission of Shanghai Municipality