Comprehensive Identification of Key Genes Involved in Development of Diabetes Mellitus-Related Atherogenesis Using Weighted Gene Correlation Network Analysis

The role of Phafin proteins in cell signaling pathways and diseases

Membrane-associated proteins are important membrane readers that mediate and facilitate the signaling and trafficking pathways in eukaryotic membrane-bound compartments. The protein members in the Phafin family are membrane readers containing two phosphoinositide recognition domains: the Pleckstrin Homology domain and the FYVE (Fab1, YOTB, Vac1, and early endosome antigen 1) domain. Phafin proteins, categorized into two subfamilies, Phafin1 and Phafin2, associate with cellular membranes through interactions involving membrane-embedded phosphoinositides and phosphoinositide-binding domains. These membrane-associated Phafin proteins play pivotal roles by recruiting binding partners and forming complexes, which contribute significantly to apoptotic, autophagic, and macropinocytotic pathways. Elevated expression levels of Phafin1 and Phafin2 are observed in various cancers. A recent study highlights a significant increase in Phafin1 protein levels in the lungs of idiopathic pulmonary fibrosis patients compared to normal subjects, suggesting a crucial role for Phafin1 in the pathogenesis of pulmonary fibrosis. Additionally, phosphatidylinositol-3-phosphate-binding 2 (Pib2), a close relative of the Phafin1 protein, functions as an amino acid sensor activating the TOCR1 pathway in yeasts. This review focuses on delineating the involvement of Phafin proteins in cellular signaling and their implications in diseases and briefly discusses the latest research findings concerning Pib2.

Causal network perturbation analysis identifies known and novel type-2 diabetes driver genes

The molecular pathogenesis of diabetes is multifactorial, involving genetic predisposition and environmental factors that are not yet fully understood. However, pancreatic β-cell failure remains among the primary reasons underlying the progression of type-2 diabetes (T2D) making targeting β-cell dysfunction an attractive pathway for diabetes treatment. To identify genetic contributors to β-cell dysfunction, we investigated single-cell gene expression changes in β-cells from healthy (C57BL/6J) and diabetic (NZO/HlLtJ) mice fed with normal or high-fat, high-sugar diet (HFHS). Our study presents an innovative integration of the causal network perturbation assessment (ssNPA) framework with meta-cell transcriptome analysis to explore the genetic underpinnings of type-2 diabetes (T2D). By generating a reference causal network and in silico perturbation, we identified novel genes implicated in T2D and validated our candidates using the Knockout Mouse Phenotyping (KOMP) Project database.

Local administration of liposomal-based Plekhf1 gene therapy attenuates pulmonary fibrosis by modulating macrophage polarization

Idiopathic pulmonary fibrosis (IPF) is a fatal interstitial lung disease with limited therapeutic options. Macrophages, particularly alternatively activated macrophages (M2), have been recognized to contribute to the pathogenesis of pulmonary fibrosis. Therefore, targeting macrophages might be a viable therapeutic strategy for IPF. Herein, we report a potential nanomedicine-based gene therapy for IPF by modulating macrophage M2 activation. In this study, we illustrated that the levels of pleckstrin homology and FYVE domain containing 1 (Plekhf1) were increased in the lungs originating from IPF patients and PF mice. Further functionality studies identified the pivotal role of Plekhf1 in macrophage M2 activation. Mechanistically, Plekhf1 was upregulated by IL-4/IL-13 stimulation, after which Plekhf1 enhanced PI3K/Akt signaling to promote the macrophage M2 program and exacerbate pulmonary fibrosis. Therefore, intratracheal administration of Plekhf1 siRNA-loaded liposomes could effectively suppress the expression of Plekhf1 in the lungs and notably protect mice against BLM-induced lung injury and fibrosis, concomitant with a significant reduction in M2 macrophage accumulation in the lungs. In conclusion, Plekhf1 may play a crucial role in the pathogenesis of pulmonary fibrosis, and Plekhf1 siRNA-loaded liposomes might be a promising therapeutic approach against pulmonary fibrosis.

Genome-Wide Identification of lncRNA and mRNA for Diagnosing Type 2 Diabetes in Saudi Arabia

Purpose

According to the World Health Organization, Saudi Arabia ranks seventh worldwide in the number of patients with diabetes mellitus. To our knowledge, no research has addressed the potential of noncoding RNA as a diagnostic and/or management biomarker for patients with type 2 diabetes mellitus (T2DM) living in high-altitude areas. This study aimed to identify molecular biomarkers influencing patients with T2DM living in high-altitude areas by analyzing lncRNA and mRNA.

Patients and Methods

RNA sequencing and bioinformatics analyses were used to identify significantly expressed lncRNAs and mRNAs in T2DM and healthy control groups. Coding potential was analyzed using coding-noncoding indices, the coding potential calculator, and PFAM, and the lncRNA function was predicted using Pearson's correlation. Differentially expressed transcripts between the groups were identified, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to identify the biological functions of both lncRNAs and mRNAs.

Results

We assembled 1766 lncRNAs in the T2DM group, of which 582 were novel. This study identified three lncRNA target genes (KLF2, CREBBP, and REL) and seven mRNAs (PIK3CD, PIK3R5, IL6R, TYK2, ZAP70, LAMTOR4, and SSH2) significantly enriched in important pathways, playing a role in the progression of T2DM.

Conclusion

To the best of our knowledge, this comprehensive study is the first to explore the applicability of certain lncRNAs as diagnostic or management biomarkers for T2DM in females in Taif City, Saudi Arabia through the genome-wide identification of lncRNA and mRNA profiling using RNA seq and bioinformatics analysis. Our findings could help in the early diagnosis of T2DM and in designing effective therapeutic targets.

WDR54 exerts oncogenic roles in T-cell acute lymphoblastic leukemia

WDR54 has been recently identified as a novel oncogene in colorectal and bladder cancers. However, the expression and function of WDR54 in T-cell acute lymphoblastic leukemia (T-ALL) were not reported. In this study, we investigated the expression of WDR54 in T-ALL, as well as its function in T-ALL pathogenesis using cell lines and T-ALL xenograft. Bioinformatics analysis indicated high mRNA expression of WDR54 in T-ALL. We further confirmed that the expression of WDR54 was significantly elevated in T-ALL. Depletion of WDR54 dramatically inhibited cell viability and induced apoptosis and cell cycle arrest at S phase in T-ALL cells in vitro. Moreover, knockdown of WDR54 impeded the process of leukemogenesis in a Jurkat xenograft model in vivo. Mechanistically, the expression of PDPK1, phospho-AKT (p-AKT), total AKT, phospho-ERK (p-ERK), Bcl-2 and Bcl-xL were downregulated, while cleaved caspase-3 and cleaved caspase-9 were upregulated in T-ALL cells with WDR54 knockdown. Additionally, RNA-seq analysis indicated that WDR54 might regulate the expression of some oncogenic genes involved in multiple signaling pathways. Taken together, these findings suggest that WDR54 may be involved in the pathogenesis of T-ALL and serve as a potential therapeutic target for the treatment of T-ALL.

Single-cell RNA sequencing highlights the roles of C1QB and NKG7 in the pancreatic islet immune microenvironment in type 1 diabetes mellitus

Single-cell RNA sequencing (scRNA-seq) technology is a powerful tool for characterizing individual cells and elucidating biological mechanisms at the cellular level. Using this technology, this study focuses on the mechanism of C1QB and NKG7 in pancreatic islet immune microenvironment in type 1 diabetes mellitus (T1DM). T1DM-related scRNA-seq data were downloaded from GEO database, followed by batch effect removal, cluster analysis, cell annotation and enrichment analysis. Thereafter, T1DM-related Bulk RNA-seq data were downloaded from GEO database. The infiltrating immune cell abundance was estimated and its correlation with the expression of immune cell marker genes was determined. Functional assays were performed in a constructed rat model of T1DM and cultured monocytes and lymphocytes for further validation. A large number of highly variable genes were found in pancreatic islet samples in T1DM. T1DM islet-derived cells may consist of 14 cell types. Macrophages and T lymphocytes were the major cells in pancreatic islet immune microenvironment. C1QB and NKG7 may be the key genes affecting macrophages and T lymphocytes, respectively. Silencing C1QB inhibited the differentiation of monocytes into macrophages and reduced the number of macrophages. Silencing NKG7 prevented T lymphocyte activation and proliferation. In vivo data confirmed that silencing C1QB and NKG7 reduced the number of macrophages and T lymphocytes in the pancreatic islet of T1DM rats, respectively, and alleviated pancreatic islet β-cell damage. Overall, C1QB and NKG7 can increase the number of macrophages and T lymphocytes, respectively, causing pancreatic islet β-cell damage and promoting T1DM in rats.

Machine learning and bioinformatics to identify 8 autophagy-related biomarkers and construct gene regulatory networks in dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a condition of impaired ventricular remodeling and systolic diastole that is often complicated by arrhythmias and heart failure with a poor prognosis. This study attempted to identify autophagy-related genes (ARGs) with diagnostic biomarkers of DCM using machine learning and bioinformatics approaches. Differential analysis of whole gene microarray data of DCM from the Gene Expression Omnibus (GEO) database was performed using the NetworkAnalyst 3.0 platform. Differentially expressed genes (DEGs) matching (|log2FoldChange ≥ 0.8, p value < 0.05|) were obtained in the GSE4172 dataset by merging ARGs from the autophagy gene libraries, HADb and HAMdb, to obtain autophagy-related differentially expressed genes (AR-DEGs) in DCM. The correlation analysis of AR-DEGs and their visualization were performed using R language. Gene Ontology (GO) enrichment analysis and combined multi-database pathway analysis were served by the Enrichr online enrichment analysis platform. We used machine learning to screen the diagnostic biomarkers of DCM. The transcription factors gene regulatory network was constructed by the JASPAR database of the NetworkAnalyst 3.0 platform. We also used the drug Signatures database (DSigDB) drug database of the Enrichr platform to screen the gene target drugs for DCM. Finally, we used the DisGeNET database to analyze the comorbidities associated with DCM. In the present study, we identified 23 AR-DEGs of DCM. Eight (PLEKHF1, HSPG2, HSF1, TRIM65, DICER1, VDAC1, BAD, TFEB) molecular markers of DCM were obtained by two machine learning algorithms. Transcription factors gene regulatory network was established. Finally, 10 gene-targeted drugs and complications for DCM were identified.

Susceptibility Loci for Type 2 Diabetes in the Ethnically Endogamous Indian Sindhi Population: A Pooled Blood Genome-Wide Association Study

Type 2 diabetes (T2D) is a complex metabolic derangement that has a strong genetic basis. There is substantial population-specificity in the association of genetic variants with T2D. The Indian urban Sindhi population is at a high risk of T2D. The genetic basis of T2D in this population is unknown. We interrogated 28 pooled whole blood genomes of 1402 participants from the Diabetes In Sindhi Families In Nagpur (DISFIN) study using Illumina's Global Screening Array. From a total of 608,550 biallelic variants, 140 were significantly associated with T2D after adjusting for comorbidities, batch effects, pooling error, kinship status and pooling variation in a random effects multivariable logistic regression framework. Of the 102 well-characterized genes that these variants mapped onto, 70 genes have been previously reported to be associated with T2D to varying degrees with known functional relevance. Excluding open reading frames, intergenic non-coding elements and pseudogenes, our study identified 22 novel candidate genes in the Sindhi population studied. Our study thus points to the potential, interesting candidate genes associated with T2D in an ethnically endogamous population. These candidate genes need to be fully investigated in future studies.

RUNX1 and CCL3 in Diabetes Mellitus-Related Coronary Artery Disease: A Bioinformatics Analysis

BACKGROUND

Cardiovascular complications are a major cause of death and disability in patients with diabetes mellitus, but how such complications arise is unclear.

METHODS

Weighted gene correlation network analysis (WGCNA) was performed on gene expression profiles from healthy controls, individuals with diabetes mellitus, and individuals with diabetes mellitus-associated coronary artery disease (DMCAD). Phenotypically related module genes were analyzed for enrichment in Gene Ontology (GO) terms and Kyoto Gene and Genome Encyclopedia (KEGG) pathways. Predicted biological functions were validated using gene set enrichment analysis (GSEA) and ClueGo analysis. Based on the TRRUST v2 database and hypergeometric tests, a global network was built to identify transcription factors (TFs) and downstream target genes potentially involved in DMCAD.

RESULTS

WGCNA identified three modules associated with progression from diabetes mellitus to DMCAD. The module genes were significantly involved in biological processes related to interferon and viral infection, while GSEA of DMCAD samples suggested involvement in viral myocarditis, chemokine signaling and phagosomes. RUNX1 was identified as a potential TF regulating these module genes. Analysis of the global regulatory network of TFs and their targets suggested that CCL3 may be a key regulator in DMCAD.

CONCLUSION

We found bioinformatic evidence that CCL3 may be a key regulator and RUNX1 a key TF in DMCAD.

Mutations in Hsp90 Cochaperones Result in a Wide Variety of Human Disorders

The Hsp90 molecular chaperone, along with a set of approximately 50 cochaperones, mediates the folding and activation of hundreds of cellular proteins in an ATP-dependent cycle. Cochaperones differ in how they interact with Hsp90 and their ability to modulate ATPase activity of Hsp90. Cochaperones often compete for the same binding site on Hsp90, and changes in levels of cochaperone expression that occur during neurodegeneration, cancer, or aging may result in altered Hsp90-cochaperone complexes and client activity. This review summarizes information about loss-of-function mutations of individual cochaperones and discusses the overall association of cochaperone alterations with a broad range of diseases. Cochaperone mutations result in ciliary or muscle defects, neurological development or degeneration disorders, and other disorders. In many cases, diseases were linked to defects in established cochaperone-client interactions. A better understanding of the functional consequences of defective cochaperones will provide new insights into their functions and may lead to specialized approaches to modulate Hsp90 functions and treat some of these human disorders.

Identification of an miRNA Regulatory Network and Candidate Markers for Ischemic Stroke Related to Diabetes

Purpose

Type 2 diabetes mellitus (T2DM) increases the risk of ischemic stroke and poor prognosis. This study aimed to identify molecular mechanisms that are dysregulated in T2DM-associated ischemic stroke and candidate genes that might serve as biomarkers.

Methods

The top 25% variance genes in the GSE21321 and GSE22255 datasets were analyzed for coexpression. The differentially expressed mRNAs (DEmRs) between patients with T2DM or ischemic stroke and controls were analyzed. Then, the union of overlapping coexpressed genes and overlapping DEmRs was analyzed. The miRNAs differentially expressed in T2DM-associated ischemic stroke were also analyzed. CIBERSORT was used to evaluate the levels of infiltration by immune cells in T2DM-associated stroke.

Results

Thirteen coexpression modules were identified in T2DM and 10 in ischemic stroke, and 594 module genes were shared between the two conditions. A total of 4452 mRNAs differentially expressed between T2DM patients and controls were identified, as were 2390 mRNAs differentially expressed between ischemic stroke and controls. The 771 union genes were enriched mainly in immune-related biological functions and signaling pathways. UBE2N, TGFB3, EXOSC1, and VIM were identified as candidate markers. In addition, we identified miR-576-3p as having the most regulatory roles in both T2DM and ischemic stroke. Mast cell activation was significantly down-regulated in T2DM but up-regulated in ischemic stroke.

Conclusion

These findings provide numerous testable hypotheses about the pathways underlying T2DM-associated ischemic stroke, which may help identify therapeutic targets.

Coiled-Coil Domain-Containing (CCDC) Proteins: Functional Roles in General and Male Reproductive Physiology

The coiled-coil domain-containing (CCDC) proteins have been implicated in a variety of physiological and pathological processes. Their functional roles vary from their interaction with molecular components of signaling pathways to determining the physiological functions at the cellular and organ level. Thus, they govern important functions like gametogenesis, embryonic development, hematopoiesis, angiogenesis, and ciliary development. Further, they are implicated in the pathogenesis of a large number of cancers. Polymorphisms in CCDC genes are associated with the risk of lifetime diseases. Because of their role in many biological processes, they have been extensively studied. This review concisely presents the functional role of CCDC proteins that have been studied in the last decade. Studies on CCDC proteins continue to be an active area of investigation because of their indispensable functions. However, there is ample opportunity to further understand the involvement of CCDC proteins in many more functions. It is anticipated that basing on the available literature, the functional role of CCDC proteins will be explored much further.

Integrative Identification of Hub Genes Associated With Immune Cells in Atrial Fibrillation Using Weighted Gene Correlation Network Analysis

Background: Atrial fibrillation (AF) is the most common tachyarrhythmia in the clinic, leading to high morbidity and mortality. Although many studies on AF have been conducted, the molecular mechanism of AF has not been fully elucidated. This study was designed to explore the molecular mechanism of AF using integrative bioinformatics analysis and provide new insights into the pathophysiology of AF. Methods: The GSE115574 dataset was downloaded, and Cibersort was applied to estimate the relative expression of 22 kinds of immune cells. Differentially expressed genes (DEGs) were identified through the limma package in R language. Weighted gene correlation network analysis (WGCNA) was performed to cluster DEGs into different modules and explore relationships between modules and immune cell types. Functional enrichment analysis was performed on DEGs in the significant module, and hub genes were identified based on the protein-protein interaction (PPI) network. Hub genes were then verified using quantitative real-time polymerase chain reaction (qRT-PCR). Results: A total of 2,350 DEGs were identified and clustered into eleven modules using WGCNA. The magenta module with 246 genes was identified as the key module associated with M1 macrophages with the highest correlation coefficient. Three hub genes (CTSS, CSF2RB, and NCF2) were identified. The results verified using three other datasets and qRT-PCR demonstrated that the expression levels of these three genes in patients with AF were significantly higher than those in patients with SR, which were consistent with the bioinformatic analysis. Conclusion: Three novel genes identified using comprehensive bioinformatics analysis may play crucial roles in the pathophysiological mechanism in AF, which provide potential therapeutic targets and new insights into the treatment and early detection of AF.

Understanding Competitive Endogenous RNA Network Mechanism in Type 1 Diabetes Mellitus Using Computational and Bioinformatics Approaches

BACKGROUND

Type 1 diabetes mellitus (T1DM), an autoimmune disease with a genetic tendency, has an increasing prevalence. Long non-coding RNA (lncRNA) and circular RNA (circRNA) are receiving increasing attention in disease pathogenesis. However, their roles in T1DM are poorly understood. The present study aimed at identifying signature lncRNAs and circRNAs and investigating their roles in T1DM using the competing endogenous RNA (ceRNA) network analysis.

METHODS

The T1DM expression profile was downloaded from Gene Expression Omnibus (GEO) database to identify the differentially expressed circRNAs, lncRNAs, and mRNAs. The biological functions of these differentially expressed circRNAs, lncRNAs, and mRNAs were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Targeting relationships of circRNA-miRNA, lncRNA-miRNA, and miRNA-mRNA were predicted, and the circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network was established. Finally, qRT-PCR was applied to identify the effect of hsa_circ_0002202 inhibition on the IFN-I induced macrophage inflammation.

RESULTS

A total of 178 circRNAs, 404 lncRNAs, and 73 mRNAs were identified to be abnormally expressed in T1DM samples. Functional enrichment analysis results indicated that the differentially expressed genes were mainly enriched in extracellular matrix components and macrophage activation. CeRNA regulatory network showed that circRNAs and lncRNAs regulate mRNAs through integrate multiple miRNAs. In addition, in vitro experiments showed that hsa_circ_0002202 inhibition suppressed the type I interferon (IFN-I)-induced macrophage inflammation.

CONCLUSION

In the present study, the circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network in T1DM was established for the first time. We also found that hsa_circ_0002202 inhibition suppressed the IFN-I-induced macrophage inflammation. Our study may lay a foundation for future studies on the ceRNA regulatory network in T1DM.