High-throughput dissection of inter-organ genetic networks: A multi-omic systems biology approach
The existing multi-omic analyses are frequently confined to individual tissues, and the regulatory picture of the systemic regulator of complex physiology and disease is hidden. To fill this gap, we have created a unified systems biology model of the high-throughput dissection of inter-organ genetic networks. Our model incorporates transcriptomic, epigenomic and proteomic analysis of five major organs (liver, kidney, heart, lung, brain) using the Multi-Omics Factor Analysis (MOFA+) tool, specifically, cross-tissue coordination. We characterized 27 evidence-heavy cross-tissue modules (FDR < 0.05) that are major hubs such as *HNF4Aenda NRF2cheng8loadmasterregulatingconstitutionembryonicstemcellularinfoncogenes recognize them. One notable observation was liver-kidney metabolic axis, significant cross-talks in hepatocyte organoids are confirmed with CRISPR knockdown, which suppresses the expression of transporters expressed by the kidney. Our work offers a scalable validated framework that goes beyond organ-centric perspectives, which can be used as a potent tool of systemic disease modelling and precision medicine.
Authors
- Asma A. Alhashmi (ORCID: https://orcid.org/0000-0001-7871-7069)
- Rana Alabdan (ORCID: https://orcid.org/0000-0003-2410-486X)
- Najla Al-Harbi (ORCID: https://orcid.org/0009-0004-8009-9502)
- Eman M Alanazi (ORCID: https://orcid.org/0000-0001-9558-2602)
- Mukhtar Ghaleb (ORCID: https://orcid.org/0000-0002-6461-1818)
- Rowida Mohammed Alharbi
- Ghada Moh. Samir Elhessewi (ORCID: https://orcid.org/0000-0003-3158-6924)
- Hechmi Shili
Institutions
- Princess Nourah bint Abdulrahman University (SA)
- Northern Border University (SA)
- Saudi Electronic University (SA)
- King Abdulaziz City for Science and Technology (SA)
- Majmaah University (SA)
- Taibah University (SA)
- University of Bisha (SA)
- University of Tabuk (SA)
Publication Details
- Journal
- SLAS TECHNOLOGY
- Published
- 2025-12-11
- DOI
- https://doi.org/10.1016/j.slast.2025.100376
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00