bioRxivBioinformaticsPreprint
Hepatic isomiR landscaping reveals new biological insights into metabolic dysfunction in steatotic liver disease
Christian BrioniD, Stephen Aurelien HoangiD, Guangliang WangiD, Faridodin Mirshahi, Jessie Ang, Matthew Long, Zhu ZhengiD, Bhanu Sakhamuri, Molly A. Srour, Mohammad Shadab SiddiquiiD, Amon AsgharpouriD, David J. Hayes, Neal C. Foster, David William SalzmaniD, Arun Jayant SanyaliD
Abstract
Post-transcriptionally modified microRNA (miRNA), called isomiRs, expand the repertoire of transcripts that can leveraged for therapeutic targets and biological insights. However, the expression of isomiRs has not been characterized in metabolic dysfunction-associated steatotic liver disease (MASLD). Therefore, we assessed the isomiR expression profile in liver biopsies from 79 patients with MASLD and modeled their potential role in disease biology. MiRNAs represented 75% of the sequencing reads and over 65% of them were attributed to isomiRs, demonstrating their higher expression and diversity compared to canonically annotated miRNAs. Differential expression and machine-learning analyses were used to identify 173 isomiRs associated to MASLD severity and 58 isomiRs associated to fibrosis score. Candidate target mRNAs were identified for each isomiR based on sequence complementarity. Using matched mRNA sequencing data, and supported by data from an independent study, we proposed key dysregulated mRNA targets involved in a selection of 33 disease-associated pathways. Importantly, isomiRs offered novel and unique mRNA targets compared to the canonical miRNA, e.g. isomiR-122 targeting INSIG1 (insulin and cholesterol metabolism), and isomiR-21 targeting HMGCS2 and PPARA (PARR and TGF-beta signaling). Our work advances knowledge regarding the role of isomiRs in MASLD and lays a foundation for therapeutic targets identification. HighlightsOur results provide a comprehensive analysis of microRNA (isomiRs) in liver tissue. Machine learning identified isomiRs whose expression is associated with MASLD. Multi-omic analysis uncovered novel isomiR regulatory mechanisms involved in MASLD.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: machine learning (classical)
- Citations
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