Identification of potential diagnostic biomarkers for hypertension via integrated analysis of gene expression and DNA methylation
Year: 2024
Type: article
Abstract: OBJECTIVE: Hypertension refers to the elevated blood pressure (BP) in arteries, with a BP reading of 140/90 mm Hg or higher in adults. Over 40% of >25-year-old population have suffered from hypertension. Thus, this study aimed to find novel diagnostic biomarkers for hypertension. METHODS: All hypertension-related mRNA and methylation datasets were downloaded from the GEO database. Liner model method was used to identify differentially expressed genes (DEGs) between hypertension and control groups. Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes enrichment analysis was employed to obtain functional information. CpG sites and the corresponding genes associated with hypertension were screened using epigenome-wide association study (EWAS) analysis. RESULTS: There were 37 DEGs between the hypertension group and control group, which were significantly enriched in 84 Biological Process terms, 31 Cellular Component terms, 18 Molecular Function terms and 9 signalling pathways. EWAS results indicated that 1072 CpG sites were associated with hypertension occurrence, corresponding to 1029 genes. After cross-analysis, complement factor D (CFD) and OTU deubiquitinase, ubiquitin aldehyde binding 2 (OTUB2) with methylation modification were identified as diagnostic markers for hypertension. CONCLUSION: In conclusion, CFD and OTUB2 were potential biomarkers of hypertension occurrence. Our results will provide more information for hypertension diagnosis and would be more reliable combined with multiple biomarkers.
Source: Blood Pressure
Authors: Xiujiang Han, Jing Xue, Sheng Gao, Yongjian Li, Yuehe Duo, Feifei Gao
Institutions: Tianjin Nankai Hospital, Tianjin Medical University
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,650
Award: G4823513139
OpenAlex ID: W4402081784
