NDLI: Dysregulation of long non-coding RNA gene expression pathways in monocytes of type 2 diabetes patients with cardiovascular disease

Content Provider	Springer Nature : BioMed Central
Author	Halabi, Najeeb Thomas, Binitha Chidiac, Omar Robay, Amal AbiNahed, Julien Jayyousi, Amin Al Suwaidi, Jassim Bradic, Martina Abi Khalil, Charbel
Abstract	Background Monocytes play a central role in the pathophysiology of cardiovascular complications in type 2 diabetes (T2D) patients through different mechanisms. We investigated diabetes-induced changes in lncRNA genes from T2D patients with cardiovascular disease (CVD), long-duration diabetes, and poor glycemic control. Methods We performed paired-end RNA sequencing of monocytes from 37 non-diabetes controls and 120 patients with T2D, of whom 86 had either macro or microvascular disease or both. Monocytes were sorted from peripheral blood using flow cytometry; their RNA was purified and sequenced. Alignments and gene counts were obtained with STAR to reference GRCh38 using Gencode (v41) annotations followed by batch correction with CombatSeq. Differential expression analysis was performed with EdgeR and pathway analysis with IPA software focusing on differentially expressed genes (DEGs) with a p-value < 0.05. Additionally, differential co-expression analysis was done with csdR to identify lncRNAs highly associated with diabetes-related expression networks with network centrality scores computed with Igraph and network visualization with Cytoscape. Results Comparing T2D vs. non-T2D, we found two significantly upregulated lncRNAs (ENSG00000287255, FDR = 0.017 and ENSG00000289424, FDR = 0.048) and one significantly downregulated lncRNA (ENSG00000276603, FDR = 0.017). Pathway analysis on DEGs revealed networks affecting cellular movement, growth, and development. Co-expression analysis revealed ENSG00000225822 (UBXN7-AS1) as the highest-scoring diabetes network-associated lncRNA. Analysis within T2D patients and CVD revealed one lncRNA upregulated in monocytes from patients with microvascular disease without clinically documented macrovascular disease. (ENSG00000261654, FDR = 0.046). Pathway analysis revealed DEGs involved in networks affecting metabolic and cardiovascular pathologies. Co-expression analysis identified lncRNAs strongly associated with diabetes networks, including ENSG0000028654, ENSG00000261326 (LINC01355), ENSG00000260135 (MMP2-AS1), ENSG00000262097, and ENSG00000241560 (ZBTB20-AS1) when we combined the results from all patients with CVD. Similarly, we identified from co-expression analysis of diabetes patients with a duration ≥ 10 years vs. <10 years two lncRNAs: ENSG00000269019 (HOMER3-AS10) and ENSG00000212719 (LINC02693). The comparison of patients with good vs. poor glycemic control also identified two lncRNAs: ENSG00000245164 (LINC00861) and ENSG00000286313. Conclusion We identified dysregulated diabetes-related genes and pathways in monocytes of diabetes patients with cardiovascular complications, including lncRNA genes of unknown function strongly associated with networks of known diabetes genes.
Related Links	https://cardiab.biomedcentral.com/counter/pdf/10.1186/s12933-024-02292-1.pdf
Ending Page	23
Page Count	23
Starting Page	1
File Format	HTM / HTML
ISSN	14752840
DOI	10.1186/s12933-024-02292-1
Journal	Cardiovascular Diabetology
Issue Number	1
Volume Number	23
Language	English
Publisher	BioMed Central
Publisher Date	2024-06-07
Access Restriction	Open
Subject Keyword	Diabetes Angiology Cardiology Long non-coding RNAs Cardiovascular disease Type 2 diabetes Macrovascular disease Microvascular disease
Content Type	Text
Resource Type	Article
Subject	Cardiology and Cardiovascular Medicine Internal Medicine Endocrinology, Diabetes and Metabolism
Journal Impact Factor	8.5/2023
5-Year Journal Impact Factor	8.9/2023

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