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ORIGINAL RESEARCH article
Front. Immunol.
Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders
Volume 15 - 2024 |
doi: 10.3389/fimmu.2024.1381445
Integrating Genomics and AI to Uncover Molecular Targets for mRNA Vaccine Development in Lupus Nephritis
Provisionally accepted- 1 Shenzhen Second People’s Hospital, Shenzhen, China
- 2 Shenzhen Second People's Hospital, Shenzhen, Guangdong Province, China
Lupus nephritis (LN), a complex complication of systemic lupus erythematosus, requires in-depth cellular and molecular analysis for advanced treatment strategies, including mRNA vaccine development. In this study, we analyzed single-cell RNA sequencing data from 24 LN patients and 10 healthy controls, supplemented by bulk RNA-seq data from additional LN patients and controls. By applying nonnegative matrix factorization (NMF), we identified four distinct leukocyte metaprograms in LN, highlighting diverse immune functions and potential mRNA vaccine targets. Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. These models were instrumental in identifying potential targets for mRNA vaccine development. Our functional network analysis further revealed intricate gene interactions, providing novel insights into the molecular basis of LN.Additionally, we validated the mRNA expression levels of potential vaccine targets across multiple cohorts and correlated them with clinical parameters such as the glomerular filtration rate (GFR) and pathological stage. This study represents a significant advance in LN research by merging single-cell genomics with the precision of NMF and machine learning, broadening our understanding of LN at the cellular and molecular levels. More importantly, our findings shed light on the development of targeted mRNA vaccines, offering new possibilities for diagnostics and therapeutics for this complex autoimmune disease.
Keywords: systemic lupus erythematosus, Lupus Nephritis, Genomics, single cell, single-cell RNA sequencing, non-negative matrix factorization (NMF), machine learning, Functional Network Analysis
Received: 03 Feb 2024; Accepted: 02 Sep 2024.
Copyright: © 2024 Mou, Lu, Wu and Pu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Zuhui Pu, Shenzhen Second People's Hospital, Shenzhen, Guangdong Province, China
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