Differentially expressed circRNAs
A total of 992 differentially expressed circRNAs were detected in the Group LA vs Group NG:209 circRNAs were significantly upregulated and 783 circRNAs downregulated. These circRNAs were distributed in all chromosomes (Fig. 1). Most differentially expressed circRNAs were derived from exons (Fig. 2).
After screening and comparison, 2 dysregulated circRNAs are listed in Table 1, which were selected according to the following conditions: 1. Basic parameters: the difference multiple is greater than 1.5, and the p value is less than 0.05; 2. Exon source for subsequent functional research; 3. Combined with literature. One of which was recognized as unannotated, new circRNAs in the circBase or Circ2Traits database. According to the txStart genome coordinates of the circRNA, we named it hsa_circ_62540520.
Bioinformatics analysis
Compared to Group NG, 209 circRNAs were significantly upregulated and 783 circRNAs downregulated in the Group LA (Fig. 3a, b, and c). The functions of differentially expressed circRNAs were annotated and hypothesised by gene ontology (GO) analysis of the host genes, including biological process (BP), cell component (CC), and molecular function (MF), as shown in Fig. 4(a-c) and Fig. 5(a-c). We found that the most significantly enriched GO terms in BP were organelle organization, mitotic cell cycle, cell cycle and cellular macromolecule metabolic process. GO terms in CC were intracellular part, intracellular, nucleoplasm and nuclear lumen. GO terms in MF were protein binding, binding, protein binding and protein serine/threonine kinase activity. The results of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis are shown in Fig. 4(d) and Fig. 5(d). Differentially expressed circRNAs were mainly associated with the influenza A, herpes simplex infection, HTLV-I infection and cell cycle.
The source gene CDK1 of hsa_circ_62540520 was significantly enriched in the KEGG pathway, analysis of which was cell cycle (http://www.genome.jp/kegg-bin/show_pathway?hsa04110+996+983+1869+4998+7029, Fig. 6), and the difference was statistically significant (p value<0.05).
Differentially expressed circRNA validation by qRT-PCR
To verify the sequencing results, the top 2 most differentially expressed circRNAs were further confirmed by qRT-PCR (Fig. 7). We used qRT-PCR technology to draw the dissolution curve and amplification curve in real time. All primers (Table 2) were synthesised by Sangon Biotech (Shanghai, China). The results showed that the PCR amplification curve was smooth at baseline, and the exponential amplification period was obvious until the plateau period. The parallelism between the secondary pores was good, indicating that the PCR amplification was good. The dissolution curves were unimodal and no heterozygous peaks, which proved that the products amplified had specificity and no other non-specific products existed.
Prediction of circRNA-miRNA interaction and the circRNA network
We predicted the potential target miRNAs and coding genes of hsa_circ_62540520, hsa_circ_0097425 using MiRanda and TargetScan software (Table 3). The network map (Fig. 8) shows the top five miRNAs that potentially link to the circRNA, and the most likely target genes for each miRNA, clearly identifying the potential targets for the differentially expressed circRNAs.These findings lay the foundation for studying the specific mechanisms of these circRNAs in LADA.
Discussion
According to the Diabetes Atlas of International Diabetes Federation, 10 million people are newly diagnosed with diabetes every year [13]. A Chinese LADA study found that rate of LADA in individuals over 30 years old newly diagnosed with type 2 diabetes mellitus was 5.9% [14]. The development of diabetes has become an urgent public health threat problem, which has a great impact on social economy and needs to be solved. In fact, diabetes has become a global epidemic associated with the leading cause of hospitalization and death in older populations.
LADA is currently classified as T1DM, but its clinical manifestations are similar to T2DM. The autoantibodies of the patients with LADA indicate the pathogenesis of autoimmune diseases. However, the autoimmune process of LADA seems to be milder, and the procession of islet β cell failure is slower and consistently shows a higher level of C-peptide as an indicator of insulin secretion, indicating that other mechanisms also play an important role in the pathogenesis of LADA [15]. Studies have shown that the number of natural killer cells in individuals who were newly diagnosed with LADA is similar to that in individuals with type 1 diabetes, but lower than that in individuals with type 2 diabetes [16]. The degree of insulin resistance in individuals with LADA is similar to that in individuals with T2DM [17]. Another Chinese LADA study found that the prevalence of metabolic syndrome in individuals with LADA is slightly lower in those with type 2 diabetes mellitus, but higher in those with type 1 diabetes and healthy individuals [18]. To summarise, while some of the relationships and differences among individuals with type 1 diabetes, type 2 diabetes, and LADA have been explored, the nature of these connections has not yet been fully elucidated.
Circular RNA was first discovered by scientists using electron microscopy to observe the virus in the 1970s. However, due to technical limitations, circRNAs were initially considered as by-products of mal-splicing of mRNA, with extremely low levels in cells.With the development of scientific and technological advances, especially high-throughput sequencing and bioinformatics, we gradually uncover the mystery of circRNAs. Most of the circRNAs currently studied are produced by antisplicing of the messenger RNA precursor (pre-messenger RNA, pre-mRNA) of the exon, where the downstream 5' splicing site is connected to the upstream 3' splicing site, and the 3'-5' phosphodiester bond is connected to produce a circular structure. The characteristics of circRNAs are also worthy of mention due to their circular structure, which is different from other linear non-coding RNAs:1. Universality: circRNA has been found in a variety of eukaryotic cells, including human, fruit fly and yeast [19]. 2. Stability: circRNA has a covalent closed-loop structure, unlike linear non-coding RNA, which has a polar terminal of 3'/5' or a polynucleotide tail. Therefore, it is not affected by ribonuclease R and RNA nucleic acid exonuclease, and has strong stability.3. High abundance: due to its strong stability, its abundance can be more than 10 times that of corresponding linear RNA, and it can exist not only in cells but also in extracellular fluids [20]. Therefore, real-time fluorescence quantitative PCR can be used to detect the expression level of circRNA in tissues.4. Specificity: specific expression of circRNA in tissue or developmental stage can be observed in multiple times in the same organism, and such specificity also exists in different species [21]. Because of this specificity, we can compare the circRNA in the normal dynamic equilibrium state with the disease state and use it as a target for disease diagnosis and treatment.
Metabolic syndrome refers to the pathological status of metabolic disorders of proteins, fats, carbohydrates and other substances in the human body. It is a group of complex metabolic disorders, which is a risk factor for dyslipidaemia, hyperglycaemia, and cerebrovascular diseases [22]. Individuals with metabolic syndrome often show a state of pro-inflammation. The change in cytokine expression may be one of the mechanisms of low inflammation accompanying disorder of lipid and glucose metabolism [23]. The hsa_circ_0097425 gene, HECTD4, has been reported to be a pleiotropic gene that regulates metabolic syndrome and inflammation [24]. In our results, hsa_circ_0097425 was obviously downregulated in participants with T2DM and LADA relative to the control group, especially in the LADA group. We speculate that hsa_circ_0097425 regulates metabolic syndrome and inflammation via HECTD4, and acts as a protective circRNA; this is consistent with the results of GO and KEGG analysis.
Recent studies have shown that circRNAs are derived from the exons or introns of their host genes, and may regulate the expression of these host genes [25]. The GO analysis results of our study showed that the circRNA host genes were related to diabetes development. Moreover, the results of KEGG analysis revealed that the host genes of significantly dysregulated circRNAs were involved in many important pathways, among which, the source gene CDK1 of hsa_circ_62540520 was significantly enriched in the KEGG pathway. The analysis of its KEGG pathway was cell cycle, which is highly consistent with the results of GO analysis, further validates that circRNA may be involved in the development of diabetes by regulating the cell cycle, and also provides ideas for us to select signaling pathways in further cell and animal experiments. Therefore, GO and KEGG analyses showed that the dysfunctional circRNAs might be involved in the pathogenesis of different types of diabetes. Nevertheless, we need further studies to confirm these findings.