has_circ_CCNB1 and has_circ_0009024 function as potential biomarkers for the diagnosis of type 2 diabetes mellitus

Abstract Circular RNAs (circRNAs) have been reported to be associated with various diseases, including type 2 diabetes mellitus (T2DM). The aim of present study was to investigate the clinical value of has_circ_CCNB1 and has_circ_0009024 in T2DM. Serum samples from patients with T2DM (n = 166) and healthy volunteers (n = 166) were recruited. Then, real‐time quantitative reverse transcription‐polymerase chain reaction (RT‐qPCR) analysis and enzyme‐linked immunosorbent (ELISA) assays were conducted to detect the expression levels of circRNAs and inflammatory factors. Furthermore, the correlation analysis and receiver operating characteristic (ROC) curve were used to evaluate diagnostic accuracy. From the results, circ_CCNB1 was significantly increased while circ_0009024 was decreased in serum samples from T2DM patients. Moreover, has_circ_CCNB1 was positively correlated with glucose (GLU), glycosylated hemoglobin (GHb), interleukin 6 (IL‐6), and tumor necrosis factor‐α (TNF‐α) while has_circ_0009024 was negatively correlated with them. Importantly, the AUC of has_circ_CCNB1 and has_and circ_0009024 was 0.9255 (95% CI = 0.8909‐0.9601) and 0.9592 (95% CI = 0.9381‐0.9803), while the AUC of combinative curve is 0.8875 (95% CI = 0.8204‐0.8547). In a word, has_circ_CCNB1 and has_circ_0009024 may exhibit as potential biomarkers for the diagnosis of T2DM.

Then, real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR) analysis and enzyme-linked immunosorbent (ELISA) assays were conducted to detect the expression levels of circRNAs and inflammatory factors. Furthermore, the correlation analysis and receiver operating characteristic (ROC) curve were used to evaluate diagnostic accuracy. From the results, circ_CCNB1 was significantly increased while circ_0009024 was decreased in serum samples from T2DM patients.

K E Y W O R D S
biomarker, circular RNAs (circRNAs), diagnosis, type 2 diabetes mellitus (T2DM) has_circRNA_ 063981, has_circRNA_102682, and has_cir-cRNA_103410 were dysregulated in gestational diabetes mellitus. 8 Moreover, 489 circRNAs were found to be dysregulated in T2DM patients and has_circRNA_00054633 presented a significant diagnostic value for pre-diabetes and T2DM. 9 In the present study, we focused on elucidating the clinical values of two circRNAs (has_circRNA_CCNB1 and has_circ_0009024) in detecting T2DM patients.

| RNA E X TR AC TI ON AND RE AL-TIME QUANTITATIVE RE VER S E TR AN SCRIP TI ON -P OLYMER A S E CHAIN RE AC TI ON (RT-Q P CR )
Total RNA was extracted from serum samples using TRIzol reagent (Thermo Fisher Scientific, Inc, USA) and reverse transcribed into cDNA under the manufacturer's instructions. Then, cDNA was amplified using the Reverse Transcription System (Promega Corporation, Madison, WI, USA) in accordance with the protocol of SYBR Green Master Mix (Takara Biotechnology Co., Ltd). The PCR thermal cycles were as follows: 35 cycles of 95℃ for 5 seconds, 62℃ for 15 seconds, and 72℃ for 20 seconds. The levels of circRNAs were normalized to U6 and analyzed using the 2 −△△Ct method.

| ENZ YME-LINKED IMMUNOSORB ENT (ELISA ) A SSAY
All the serum samples were taken from the refrigerator and placed to room temperature prior to usage. The levels of IL-6 and tumor necrosis factor-α (TNF-α) were measured by a Total Antigen Assay ELISA kit (Cloud-Clone Corporation, Wuhan, China) following the manufacturer's instructions. Measurements were carried out at 450 nm.

| Statistical analysis
All the statistical analysis was performed using the SPSS 19.0 software (IBM Corp, New York, NY) and GraphPad Prism 6.0 (GraphPad Software, Inc, La Jolla, CA, USA). Data were presented as mean ± standard deviation (SD). Significant differences between control and T2DM groups were analyzed using Student's t test followed by Newman-Keuls post hoc test. Pearson's correlation analysis and receiver operating characteristics (ROC) analysis were used, as appropriate. P < .05 was considered to indicate statistically significant differences.

| The expressions of has_circ_CCNB1 and has_ circ_0009024 verified by RT-qPCR
To determine the expressions of has_circ_CCNB1 and has_ circ_0009024 in serum samples from T2DM and healthy controls, RT-qPCR analysis was performed accordingly. From the results ( Figure 1A and B), the expression of has_circ_CCNB1 was significantly up-regulated while has_circ_0009024 was decreased in the T2DM group compared with healthy controls (P < .01).

| THE A SSO CIATI ON B E T WEEN CIRCRNA S E XPRE SS I ON S AND G LU AND G HB
As shown in Table 1 and Figure 2, has_circ_CCNB1 was positively correlated with GLU (r = .3364, P < .0001) and GHb (r = .4485, P < .0001) while has_circ_0009024 was negatively correlated with GLU (r = −.3227, P < .0001) and GHb (r = −.4359, P < .0001).

| THE A SSO CIATI ON B E T WEEN CIRCRNA S E XPRE SS I ON S AND INFL AMMATORY FAC TOR S
The expression levels of inflammatory factors (IL-6, TNF-α) were measured by ELISA. As shown in Table 2, the expression levels of IL-6 and TNF-α were markedly elevated in patients with T2DM as compared with controls (P < .01). Furthermore, Pearson's correlation analysis was conducted to examine the correlation between circRNAs and inflammatory factors. As shown in Figure 3, has_circ_CCNB1 was positively correlated with IL-6 and TNF-α (r = .7419, P < .0001; r = .1964, P = .0112 respectively). However, has_circ_0009024 was negatively correlated with IL-6 and TNF-α (r = −.5628, P < .0001; r = −.1981, P = .0105, respectively).

| D ISCUSS I ON
As elucidated in previous studies, a variety of circRNAs are being identified as potential noninvasive, rapid, sensitive, and specific biomarkers for different diseases providing novel prognostic or diagnostic measures. For instance, circFARSA is abundant in lung cancer cell and may function as a potential noninvasive biomarker in lung cancer. 10 Another study proposed that circRNA Cdr1as was elevated in cholangiocarcinoma tissues serving as a potential vicious molecular biomarker to predict the worse prognosis for cholangiocarcinoma patients. 11 Several circRNAs are reported to be involved in regulating T2DM processes, and however, their diagnostic values remain to be further verified. Moreover, a number of circRNAs participated in regulating metabolic diseases, such as osteoporosis and diabetes mellitus. 12,13 A previous study pointed out that has_ circ_CCNB1 was significantly elevated while has_circ_0009024 was down-regulated in T2DM patients, 13 which was consistent with our results.
The triggering mechanisms of the inflammation in T2DM have been reported recently. As known, inflammatory response may trigger insulin resistance which likely contribute to T2DM occurrence and lead to complex long-term complications. 14 Another study reported that adipose tissues inflammation is associated with insulin resistance and serve as key factor in the development of T2DM. 15 In our study, we examined two typical inflammatory cytokines IL-6 and TNF-α as indicators. IL-6 is a multifunctional cytokines which has been found to be promising biomarker for T2DM. 16 Moreover, elevated expression of IL-6 was considered to be related to development of T2DM and insulin resistance. 17 TNF-α, an adipocytokine, which has been implicated in the development of insulin resistance, was considered to predict T2DM development as well. 18 Another report also proposed that elevated expressions of IL-6 and TNF-α were associated with T2DM, functioning as potential biomarkers for T2DM. 19 The results elucidated that has_circ_ CCNB1 was positively correlated whereas has_circ_0009024 was negatively correlated with IL-6 and TNF-α, which con-