Analysis of circRNA-mRNA expression profiles and functional enrichment in diabetes mellitus based on high throughput sequencing

RETRACTION: Analysis of circRNA-mRNA Expression Profiles and Functional Enrichment in Diabetes Mellitus Based on High Throughput Sequencing

RETRACTION

W. Zhao, X. Meng, and J. Liang, "Analysis of circRNA-mRNA Expression Profiles and Functional Enrichment in Diabetes Mellitus Based on High Throughput Sequencing," International Wound Journal 20, no. 5 (2023): 1253-1262, https://doi.org/10.1111/iwj.13838. The above article, published online on 03 May 2022, in Wiley Online Library (http://onlinelibrary.wiley.com/), has been retracted by agreement between the journal Editor in Chief, Professor Keith Harding; and John Wiley & Sons Ltd. Following an investigation by the publisher, all parties have concluded that this article was accepted solely on the basis of a compromised peer review process. In addition, further investigation by the publisher found discrepancies between the figures and data and the statements made in the results, contradictions between the methodology and data, and flaws in the research concept and design that fundamentally compromise the validity of the results presented in the article. The editors have therefore decided to retract the article. The authors did not respond to our notice regarding the retraction.

Single-cell RNA sequencing reveals the dysfunctional characteristics of PBMCs in patients with type 2 diabetes mellitus

Introduction

Type 2 diabetes mellitus (T2DM) is a disease that involves autoimmunity. However, how immune cells function in the peripheral blood remains unclear. Exploring T2DM biomarkers via single-cell RNA sequencing (scRNA-seq) could provide new insights into the underlying molecular mechanisms.

Methods

The clinical trial registration number is ChiCTR2100049613. In this study, we included three healthy participants and three T2DM patients. The observed clinical indicators included weight and fasting blood glucose (FBG), glycosylated haemoglobin A1c (HbA1c) and fasting insulin levels. Direct separation and purification of peripheral blood mononuclear cells (PBMCs) were performed via the Ficoll density gradient centrifugation method. Immune cell types were identified via scRNA-seq. The differentially expressed genes, biological functions, cell cycle dynamics, and correlations between blood glucose indicators and genes in different cell types were analysed.

Results

There were differences between the healthy and T2DM groups in terms of FBG and HbA1c (p<0.05 or p<0.01). We profiled 13,591 cells and 3188 marker genes from PBMCs. B cells, T cells, monocytes, and NK cells were grouped into 4 subclusters from PBMCs. CD4+ T cells are mainly in the memory activation stage, and CD8+ T cells are effectors. Monocytes include mainly CD14+ monocytes and FCGR3A+ monocytes. There were 119 differentially expressed genes in T cells and 175 differentially expressed genes in monocytes. Gene set enrichment analysis revealed that the marker genes were enriched in HALLMARK_ INTERFERON_GAMMA_RESPONSE and HALLMARK_TNFA_SIGNALING_VIA_ NFKB. Moreover, TNFRSF1A was identified as the core gene involved in network interactions in T cells.

Discussion

Our study provides a transcriptional map of immune cells from PBMCs and provides a framework for understanding the immune status and potential immune mechanisms of T2DM patients via scRNA-seq.

Clinical trial registration

http://www.chictr.org.cn, identifier ChiCTR2100049613.

Downregulation of Tnf-α and Cat Expression in a Wistar Rat Diabetic Model during Diabetes Onset

INTRODUCTION

Diabetes Mellitus (DM) is a metabolic disorder characterized by persistent hyperglycemia and/or insulin resistance. If left uncontrolled, it can lead to a combination of cardiac and renal alterations known as cardiorenal syndrome. Additionally, oxidative stress and inflammation contribute to tissue damage, thereby reducing the life expectancy of individuals with diabetes.

AIM

The aim of this study was to identify early molecular markers associated with cardiorenal syndrome, oxidative stress, and inflammation, and to investigate their correlation with the duration of exposure to DM.

METHODS

An experimental DM model was employed using Wistar rats. The rats were divided into four groups: diabetic rats at 7 days (DM7), diabetic rats at 30 days (DM30), control sham at 7 days (CS7), and control sham at 30 days (CS30). Blood and brain tissue from the brainstem region were collected at 7 and 30 days after confirming DM induction. Gene expression analysis of Bnp, Anp, Cat, Gpx, Sod, Tnf-α, and Il-6 was performed.

RESULTS

The analysis revealed lower expression values of Cat in the brainstem tissue of the DM7 group compared to the NDS7 group. Moreover, diabetic animals exhibited statistically lower levels of Tnf-α in their peripheral blood compared to the control animals.

CONCLUSION

This study concluded that DM alters the oxidative balance in the brainstem after 7 days of DM induction, resulting in lower Cat expression levels. Although some genes did not show statistical differences after 30 days of DM induction, other genes exhibited no expression values, indicating possible gene silencing. The study identified an imbalance in the studied pathways and concluded that the organism undergoes a compensatory state in response to the initial metabolic alterations caused by DM.

Microbial community composition in subgingival plaques and heterogeneity of tumor tissue TCRβ CDR3 repertoire in patients with moderate-to-severe periodontitis and oral squamous cell carcinoma

BACKGROUND

The human oral cavity contains over 700 types of bacteria that may protect the body against colonization by exogenous pathogens and maintain relative homeostasis. However, alterations in the immune status can disrupt the balance between microorganisms and the host, inducing various diseases such as oral cancer and diabetes mellitus. The mechanism underlying this process is not clearly understood.

OBJECTIVE

The purpose of this study was to investigate the relationships between subgingival bacteria, T-cell receptor β-chain complementarity-determining region 3 (TCRβ CDR3), and the development oforal squamous cell carcinoma (OSCC).

METHODS

We grouped patients as "healthy periodontal" (H), "moderate-to-severe chronic periodontitis" (C), and "moderate-to-severe chronic periodontitis with OSCC" (T). Bacterial groups were "subgingival plaque" (bp) and "gingival/tumor tissue" (g). We also recorded patients' age, gender, attachment level (AL), bleeding on probing (BOP), and probing depth (PD). We extracted and sequenced RNA from plaques, gingival tissues, tumors, and teeth. We performed high-throughput sequencing on TCRβ CDR3 and plaque bacteria.

RESULTS

Synergistetes and Veillonella parvula were more abundant in the H group than in the T group. Granulicatella, Peptostreptococcus, and Streptococcus infantis were enriched in the T-bp group. AL, BOP, and PD were positively correlated with Granulicatella, Peptostreptococcus, and Pseudomonas but negatively correlated with Prevotella nigrescens and V. parvula. TCRβ CDR3 diversity was C > H > T. TCR β-chain Variable gene (TRBV)20-1 usage varied among the H, C, and T groups. TRBV2 and TRBV5-1 usage was greater in the T group than in the C group. TRBJ1-1, TRBJ1-2, TRBJ2-2, TRBJ2-7, and TRBJ2-5 were most frequently used.

CONCLUSIONS

These trends and the reduction of gingival Synergistetes were correlated with OSCC. TCRβ CDR3 diversity was the lowest in patients in the T group, and there were considerable changes in the expression of TRBV2 and TRBJ. Therefore, plaque bacterial composition can influence TCRβ CDR3.

Circular RNA PIP5K1A Promotes Glucose and Lipid Metabolism Disorders and Inflammation in Type 2 Diabetes Mellitus

Disorders of glucose and lipid metabolism are an important cause of type 2 diabetes mellitus (T2DM). Identifying the molecular mechanism of metabolic disorders is key to the treatment of T2DM. The study was to investigate the effect of circRNA PIP5K1A (circPIP5K1A) on glucose and lipid metabolism and inflammation in T2DM rats. A T2DM rat model was established, and then the T2DM rats were injected with lentiviral vectors that interfere with circPIP5K1A, miR-552-3p, or ENO1 expression. Fasting blood glucose (FBG) and fasting insulin (FINS) levels of rats were detected by an automatic analyzer and insulin detection kit, and HOMA-IR was calculated. Lipid metabolism was assessed by measuring serum levels of TG, TC, LDL-C, leptin, and resistin. Serum levels of inflammatory factors (TNF-α and IL-6) were detected by ELISA. The pathological conditions of pancreatic tissue were observed by HE staining. circPIP5K1A, miR-552-3p and ENO1 levels were recorded. The experimental results showed that circPIP5K1A and ENO1 were up-regulated, and miR-552-3p was down-regulated in T2DM rats. Down-regulating circPIP5K1A or up-regulating miR-552-3p reduced blood glucose and lipid levels, inhibited inflammation, and improved pancreatic histopathological changes in T2DM rats. In addition, up-regulating ENO1 rescued the ameliorating effects of down-regulated circPIP5K1A on T2DM rats. In general, downregulating circPIP5K1A improves insulin resistance and lipid metabolism disorders and inhibits inflammation by targeting miR-552-3p to mediate ENO1 expression.

Bioinformatics analysis of ferroptosis-related genes and immune cell infiltration in non-alcoholic fatty liver disease

BACKGROUND

The morbidity and mortality rates of patients with non-alcoholic fatty liver disease (NAFLD) have been steadily increasing in recent years. Previous studies have confirmed the important role of ferroptosis in NAFLD development; however, the precise mechanism through which ferroptosis influences NAFLD occurrence remains unclear. The present study aimed to identify and validate ferroptosis-related genes involved in NAFLD pathogenesis and to investigate the underlying molecular mechanisms of NAFLD.

METHODS

We downloaded microarray datasets GSE72756 and GSE24807 to identify differentially expressed genes (DEGs) between samples from healthy individuals and patients with NAFLD. From these DEGs, we extracted ferroptosis-related DEGs. GSE89632, another microarray dataset, was used to validate the expression of ferroptosis-related genes. A protein-protein interaction (PPI) network of ferroptosis-related genes was then constructed. The target genes were also subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Finally, competing endogenous RNA networks were constructed. We used the CIBERSORT package to evaluate the infiltration of immune cells infiltration in NAFLD.

RESULTS

Five ferroptosis-related genes (SCP2, MUC1, DPP4, SLC1A4, and TF) were identified as promising diagnostic biomarkers for NAFLD. Enrichment analyses revealed that these genes are mainly involved in metabolic processes. NEAT1-miR-1224-5p-SCP2, NEAT1-miR-485-5p-MUC1, MALAT1-miR-485-5p-MUC1, and CNOT6-miR-145-5p-SLC1A4 are likely to be the potential RNA regulatory pathways that affect NAFLD development. Principal component analysis indicated significant differences in immune cell infiltration between the two groups.

CONCLUSIONS

This study identified five ferroptosis-related genes as potential biomarkers for diagnosing NAFLD. The correlations between the expression of ferroptosis-related genes and immune cell infiltration might shed light on the study of the molecular mechanism underlying NAFLD development.

The progress and challenges of circRNA for diabetic foot ulcers: A mini-review

Since the Human Genome Project was successfully completed, humanity has entered a post-genome era, and the second-generation sequencing technology has gradually progressed and become more accurate. Meanwhile, circRNAs plays a crucial role in the regulation of diseases and potential clinical applications has gradually attracted the attention of physicians. However, the mechanisms of circRNAs regulation at the cellular and molecular level of diabetic foot ulcer (DFU) is still not well-understood. With the deepening of research, there have been many recent studies conducted to explore the effect of circRNAs on DFU. In this mini-review, we discuss the potential role of circRNAs as therapeutic targets and diagnostic markers for DFU in order to gain a better understanding of the molecular mechanisms that underlie the development of DFU and to establish a theoretical basis for accurate treatment and effective prevention.

CircRNAs: Roles in regulating head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC), the most common head and neck malignant tumor, with only monotherapy, is characterized by poor prognosis, and low 5-year survival rate. Due to the lack of therapeutic targets, the targeted drugs for HNSCC are rare. Therefore, exploring the regulation mechanism of HNSCC and identifying effective therapeutic targets will be beneficial to its treatment of. Circular RNA (CircRNA) is a class of RNA molecules with a circular structure, which is widely expressed in human body. CircRNAs regulate gene expression by exerting the function as a miRNA sponge, thereby mediating the occurrence and development of HNSCC cell proliferation, apoptosis, migration, invasion, and other processes. In addition, circRNAs are also involved in the regulation of tumor sensitivity to chemical drugs and other biological functions. In this review, we systematically listed the functions of circRNAs and explored the regulatory mechanisms of circRNAs in HNSCC from the aspects of tumor growth, cell death, angiogenesis, tumor invasion and metastasis, tumor stem cell regulation, tumor drug resistance, immune escape, and tumor microenvironment. It will assist us in discovering new diagnostic markers and therapeutic targets, while encourage new ideas for the diagnosis and treatment of HNSCC.

Identification of potential biomarkers and pathways associated with carotid atherosclerotic plaques in type 2 diabetes mellitus: A transcriptomics study

Type 2 diabetes mellitus (T2DM) affects the formation of carotid atherosclerotic plaques (CAPs) and patients are prone to plaque instability. It is crucial to clarify transcriptomics profiles and identify biomarkers related to the progression of T2DM complicated by CAPs. Ten human CAP samples were obtained, and whole transcriptome sequencing (RNA-seq) was performed. Samples were divided into two groups: diabetes mellitus (DM) versus non-DM groups and unstable versus stable groups. The Limma package in R was used to identify lncRNAs, circRNAs, and mRNAs. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, protein-protein interaction (PPI) network creation, and module generation were performed for differentially expressed mRNAs. Cytoscape was used to create a transcription factor (TF)-mRNA regulatory network, lncRNA/circRNA-mRNA co-expression network, and a competitive endogenous RNA (ceRNA) network. The GSE118481 dataset and RT-qPCR were used to verify potential mRNAs.The regulatory network was constructed based on the verified core genes and the relationships were extracted from the above network. In total, 180 differentially expressed lncRNAs, 343 circRNAs, and 1092 mRNAs were identified in the DM versus non-DM group; 240 differentially expressed lncRNAs, 390 circRNAs, and 677 mRNAs were identified in the unstable versus stable group. Five circRNAs, 14 lncRNAs, and 171 mRNAs that were common among all four groups changed in the same direction. GO/KEGG functional enrichment analysis showed that 171 mRNAs were mainly related to biological processes, such as immune responses, inflammatory responses, and cell adhesion. Five circRNAs, 14 lncRNAs, 46 miRNAs, and 54 mRNAs in the ceRNA network formed a regulatory relationship. C22orf34-hsa-miR-6785-5p-RAB37, hsacirc_013887-hsa-miR-6785-5p/hsa-miR-4763-5p/hsa-miR-30b-3p-RAB37, MIR4435-1HG-hsa-miR-30b-3p-RAB37, and GAS5-hsa-miR-30b-3p-RAB37 may be potential RNA regulatory pathways. Seven upregulated mRNAs were verified using the GSE118481 dataset and RT-qPCR. The regulatory network included seven mRNAs, five circRNAs, six lncRNAs, and 14 TFs. We propose five circRNAs (hsacirc_028744, hsacirc_037219, hsacirc_006308, hsacirc_013887, and hsacirc_045622), six lncRNAs (EPB41L4A-AS1, LINC00969, GAS5, MIR4435-1HG, MIR503HG, and SNHG16), and seven mRNAs (RAB37, CCR7, CD3D, TRAT1, VWF, ICAM2, and TMEM244) as potential biomarkers related to the progression of T2DM complicated with CAP. The constructed ceRNA network has important implications for potential RNA regulatory pathways.