Integrated Bioinformatics Analysis Reveals Marker Genes and Potential Therapeutic Targets for Pulmonary Arterial Hypertension

Abstract

Pulmonary arterial hypertension (PAH) is a rare cardiovascular disease with very high mortality rate. The currently available therapeutic strategies, which improve symptoms, cannot fundamentally reverse the condition. Thus, new therapeutic strategies need to be established. Our research analyzed three microarray datasets of lung tissues from human PAH samples retrieved from the Gene Expression Omnibus (GEO) database. We combined two datasets for subsequent analyses, with the batch effects removed. In the merged dataset, 542 DEGs were identified and the key module relevant to PAH was selected using WGCNA. GO and KEGG analyses of DEGs and the key module indicated that the pre-ribosome, ribosome biogenesis, centriole, ATPase activity, helicase activity, hypertrophic cardiomyopathy, melanoma, and dilated cardiomyopathy pathways are involved in PAH. With the filtering standard (|MM| > 0.95 and |GS| > 0.90), 70 hub genes were identified. Subsequently, five candidate marker genes (CDC5L, AP3B1, ZFYVE16, DDX46, and PHAX) in the key module were found through overlapping with the top thirty genes calculated by two different methods in CytoHubb. Two of them (CDC5L and DDX46) were found to be significantly upregulated both in the merged dataset and the validating dataset in PAH patients. Meanwhile, expression of the selected genes in lung from PAH chicken measured by qRT-PCR and the ROC curve analyses further verified the potential marker genes’ predictive value for PAH. In conclusion, CDC5L and DDX46 may be marker genes and potential therapeutic targets for PAH.

Integrated genomic analysis defines molecular subgroups in dilated cardiomyopathy and identifies novel biomarkers based on machine learning methods

“…Compared to previous studies, the functional modules and pathways identi ed by WGCNA method were also connected with speci c molecular subgroup of DCM [30][31][32]. We found that the speci c differential expression genes in subgroup 2 were mostly in the black, blue, green and grey WGCNA module.…”

FAM171B as a Novel Biomarker Mediates Tissue Immune Microenvironment in Pulmonary Arterial Hypertension

“…Most of these studies apply machine learning methods to simulate the progression of malignancy and find significant characteristics that are then used in a categorization scheme. According to the results of our study and those of other researchers [50][51][52][53][54][55][56], this was the first study in which analytical methods for identifying PAH biomarkers use many machine learning approaches, including RF, Lasso, SVM-RFE, and WGCNA. Akter et al [57] suggest that merging different machine learning algorithms may boost prediction performance and construct highly accurate diagnostic models.…”

Integrated genomic analysis defines molecular subgroups in dilated cardiomyopathy and identifies novel biomarkers based on machine learning methods

“…Compared to previous studies, the functional modules and pathways identified by WGCNA method were also connected with specific molecular subgroup of DCM ( Zhou et al, 2020 ; Huang et al, 2021 ; Li et al, 2021 ). We found that the specific differential expression genes in subgroup 2 were mostly in the black, blue, green and grey WGCNA module.…”