Association of Serum miR-99a level and Nonalcoholic Fatty Liver Disease, Serum mTOR levels in Patients with Type 2 Diabetes Mellitus

Association of Serum miR-99a level and Nonalcoholic Fatty Liver Disease, Serum mTOR levels in Patients with Type 2 Diabetes Mellitus | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of Serum miR-99a level and Nonalcoholic Fatty Liver Disease, Serum mTOR levels in Patients with Type 2 Diabetes Mellitus Yangyang Zhang, Yuqiong Zuo, Qian Chen, Yaqiang Cui, Yanxia Bao, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3888039/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose This study was designed with the goal of exploring miR-99a expression in T2DM patients suffering from comorbid NAFLD and clarifying the importance of miR-99a in this pathological context. Methods A total of 137 subjects were included in this study, including 50 T2DM patients with NAFLD (T2DM + NAFLD group),48 T2DM patients without NAFLD (T2DM group), and 39 healthy subjects (Control group). We measured the levels of IL-6, mTOR and SOD in the serum of the subjects by ELISA. The plasma miR-99a levels was detected by RT-PCR. The correlation between serum miR-99a level and other indicators was analyzed. Results Serum miR-99a levels (median 0.79 vs 0.16 vs 0.03, P < 0.001) were significantly lower in the T2DM group than the healthy population and further decreased in the T2DM with NAFLD patients (P < 0.001). After adjusting for age, gender, illness duration and BMI, spearman correlation analysis showed that TG, HBA1c, FPG, HOMA-IR, Hs-CRP, IL-6, HDL-C, mTOR(P < 0.05) remained independently linked with serum miR-99a. And stepwise linear regression analysis showed that HBA1c, IL-6 and mTOR are independent serum miR-99a correlation variables (P < 0.05). Moreover, the ROC results indicated that serum miR-99a has a high diagnostic value for T2DM with NAFLD. In conclusion, serum miR-99a may be utilized as a screening biomarker for T2DM with NAFLD. Conclusions These data highlight a potential role for miR-99a as a regulator of the comorbid incidence of T2DM and NAFLD, suggesting that measuring the levels of miR-99a can effectively predict the risk of NAFLD in those with T2DM. type 2 diabetes mellitus nonalcoholic fatty liver disease miR-99a mTOR Figures Figure 1 Figure 2 Introduction Type 2 diabetes mellitus (T2DM) is among the most common forms of chronic disease, and many T2DM patients suffer from comorbid non-alcoholic fatty liver disease (NAFLD) [ 1 ] , which impacts upwards of 70% of individuals with T2DM [ 2 , 3 ] . The risk of T2DM incidence is also approximately two-fold higher among patients with a NAFLD diagnosis [ 4 ] , and the alleviation of NAFLD severity can modulate the risk of T2DM incidence in patients [ 5 ] . MicroRNAs (miRNAs) are 21–25 nucleotide-long transcripts that exhibit a high degree of evolutionary conservation and function through their ability to bind to target mRNA 3’-untranslated region (UTR) sequences, thereby suppressing translation or promoting degradation [ 6 ] . Liver tissue reportedly exhibits high levels of miR-99a expression, while the downregulation of this miRNA has been reported in a range of cancers such as breast cancer [ 7 ] , acute myeloid leukemia [ 8 ] , and hepatocellular carcinoma [ 9 ] , thereby promoting enhanced proliferative, invasive, and migratory activity in these malignant cells. A significant correlative relationship between miR-99a downregulation in NAFLD patient visceral adipose tissue and hepatic fibrosis [ 10 ] . Insulin can regulate miR-99a, and the miR-99a/mTOR/PKM2 axis can regulate glucose consumption [ 11 ] . As such, miR-99a may influence the incidence of severity of comorbid T2DM and NAFLD, although no studies to date have specifically examined its role in this pathogenic context. This study was thus developed to examine how serum miR-99a levels relate to the incidence of comorbid T2DM and NAFLD through comparisons of samples from controls, T2DM patients, and T2DM with NAFLD patients. Together, these analyses aim to define a novel target for treating and/or preventing T2DM and NAFLD, offering a theoretical foundation for future interventional approaches. Materials and Methods Research participants For this study, 98 T2DM patients were recruited among individuals receiving treatment in the Endocrinology Department of Gansu Provincial Hospital, including 48 without NAFLD and 50 with NAFLD as diagnosed via ultrasonography. In addition, 39 healthy individuals were selected as controls during the same study interval. Subjects were recruited if they exhibited (1) viral hepatitis, hepatic cirrhosis, biliary tract obstruction, or autoimmune liver disease, (2) a history of alcohol use (> 210 g/week or > 140 g/week for over 12 months for males and females, respectively, (3) severe infections, acute diabetic complications, or pregnancy, or (4) were using drugs with the potential to impact lipid metabolism. The Clinical Research Ethics Committee of Gansu Provincial Hospital approved these studies, with all subjects providing written informed consent. Physiological and biochemical analyses General physiological characteristics were recorded for all subjects, including age, sex, weight, height, Hip Circumference (HC), Waist Circumference (WC) and diabetes duration, enabling the calculation of both the waist-hip ratio (WHR; WC/HC) and BMI (weight/height squared (kg/m2)). Biochemical testing of parameters including TC, TG, LDL-C, HDL-C, FPG, DINS, HBA1c, and Hs-CRP was performed by the Laboratory Department of Gansu Provincial Hospital. The homeostatic insulin resistance (HOMA-IR) model was computed as follows: HOMA-IR = FPG×FINS/22.5. NAFLD was detected based on carotid ultrasonography (7.5 MHz frequency color Doppler ultrasound, Siemens Acuson×300, Germany) performed by a trained sonographer. Standard testing procedures were used for all analyses. Analysis of serum miR-99a, mTOR, SOD, and IL-6 levels Patient 5 mL venous blood samples were collected while fasting. These samples were centrifuged (3,000 rpm, 10 min, 4°C), and serum was stored at -80°C. To measure miR-99a levels, 200 µL of serum was combined with 600 µL of Trizol (Shanghai, China) to extract RNA at room temperature for 5 min, and 14 µL of DEPC H 2 O was used for dissolving RNA. Then, cDNA synthesis was performed with an All-in-One™ miRNA First-Strand cDNA Synthesis Kit 2.0 (Guangzhou, China). All qPCR reactions were performed in a 20 µL total volume with Taq Pro Universal SYBR qPCR Master Mix (Nanjing, China) and a LightCycler 480 instrument (Shanghai, China) with the settings: 95°C for 3 min; 40 cycles of 90°C 10 s, and 65°C 30s. The 2 −△△CT method was used to assess relative gene expression [ 12 ] . Plasma IL-6, SOD, and mTOR levels were detected with commercial ELISA kits (Shanghai, China) as directed, with standard curves being generated by plotting the concentrations of standards against absorbance at 450 nm, with logistic regression equations then being used to fit these data, enabling the calculation of sample concentrations. Statistical analysis Data were analyzed with SPSS 27.0 (IBM, USA) and GraphPad Prism 9.4.1. Continuous normally distributed data are reported as means ± SD and analyzed with one-way ANOVAs, whereas non-normally distributed data were given in the form of medians with interquartile range ranges (M (P25, P75)) and compared with Kruskal-Wallis test. Categorical variables were reported as percentages. Relationships among variables were assessed with Spearman correlation test. Following adjustment for age, sex, BMI, and diabetes duration, a partial correlation method was used to assess these relationships. Univariate regression analyses were also employed to assess the interplay among different variables, after which a multiple regression model was established. Diagnostic performance was also evaluated with receiver operating characteristic (ROC) curves. P < 0.05 serves as the cut-off to define statistical significance. Results Physiological and biochemical results from participants in the three subject groups are presented in Table 1 . No differences in age, sex, BMI, LDL-C, or FINS were detected among these three groups, and diabetes duration was comparable in the T2DM and T2DM with NAFLD ( P > 0.05). Comapred with controls, the T2DM and T2DM with NAFLD patients exhibited elevated IL-6, HBA1c, FPG, and HOMA-IR levels ( P < 0.001), as well as reduced HDL-C and mTOR levels ( P 0.05). Serum TG and Hs-CRP in T2DM + NAFLD group were significantly elevated relative to control group and T2DM individuals ( P < 0.001), whereas the opposite trend was observed with respect to SOD levels ( P 0.05). Significantly decreased median serum miR-99a levels were also noted in the T2DM group compared to healthy controls, with further reductions in T2DM + NAFLD patients (0.79 vs 0.16 vs 0.03, P < 0.001) (Fig. 1 ) (Table 1 ). Table 1 Participant physicochemical characteristics Parameters Control Group (n = 39) T2DM group (n = 48) T2DM + NAFLD group(n = 50) P Age(years) 45.74 ± 7.496c 48.27 ± 5.414 47.84 ± 5.947 0.224 Sex 22(56.4%) 27(56.3%) 28(56%) 0.999 Disease duration(years) - 5(2,7) 3(1, 7.25) 0.435 BMI (kg/m2 ) 24.39(23.24,25.95) 23.856(21.78,26.25) 25.40(23.57, 26.40) 0.128 WHR 0.919 ± 0.047 c 0.934 ± 0.040 0.947 ± 0.054 a 0.029 TC (mmol/L) 4.39(3.87,4.78) 4.17(3.20,4.82) c 4.72(4.02, 5.63) b 0.022 TG (mmol/L) 1.23(0.96,1.56) c 1.39(1.03,2.17) c 2.23(1.53,3.30) a,b <0.001 HDL-C(mmol/L) 1.23 ± 0.23 b、c 0.98 ± 0.24 a 0.90 ± 0.17 a <0.001 LDL-C(mmol/L) 2.61 ± 0.48 2.57 ± 1.04 2.89 ± 0.74 0.045 HBA1c (%) 5.5(5.3,5.8) b,c 8.4(7.7, 10.78) a 9.75(8.45,11.46) a <0.001 FPG (mmol/L) 5.13(4.86,5.73) b,c 9.03(7.15, 12.86) a 10(7.35,13.16) a <0.001 FINS (mU/mL) 6.1(5.0,8.7) 7.05(4.02,10.70) 8.2(5.6,12.03) 0.068 HOMA-IR 1.49(1.06,2.12) b、c 2.72(2.06,4.21) a 3.66(2.51,5.81) a <0.001 Hs-CRP (mg/L) 0.60(0.40,0.90) c 0.95(0.50,1.75) c 1.65(0.80,3.33) a,b <0.001 IL-6 (pg/mL) 16.41(13.55,22.24) b、c 32.01(30.02,39.92) a 43.33(31.11,52.59) a <0.001 SOD(pg/mL) 238.14 ± 69.33 c 213.67 ± 53.88 c 187.39 ± 41.50 a、b <0.001 mTOR(pg/mL) 344.03(222.13, 408.80) b、c 199.91(118.18,214.51) a 137.75(86.47,177.79) a <0.001 miR-99a 0.79(0.20,2.01) b, c 0.16(0.11,0.31) a, c 0.03(0.01,0.08) a, b <0.001 Note: a, P < 0.05 vs. Control group; b, P < 0.05 vs. T2DM group; c, P < 0.05 vs. T2DM + NAFLD group. Correlations between serum miR-99a and physicochemical parameters The levels of miR-99a in patient serum were significantly negatively correlated with TG, HBA1c, FPG, HOMA-IR, Hs-CRP, and IL-6 levels, whereas miR-99a levels were positively correlated with mTOR and HDL-C in this patient cohort ( P < 0.01) (Table 2 ). Following adjustment for age, sex, BMI, and T2DM duration, an independent association between serum miR-99a levels and HOMA-IR, Hs-CRP, TG, HBA1c, IL-6, HDL-C, FPG, and mTOR levels remained evident ( P < 0.05) (Table 2 ). The Durbin-Watson (D-W) value for the regression equation was 1.714, indicating the absence of any autocorrelative relationship among variables consistent with good model construction. The mean of the standardized residuals was 0, while the SD was 0.989, consistent with an approximately normal distribution. These results thus revealed that HBA1c, IL-6, and mTOR levels were independently correlated with patient serum miR-99a levels ( P < 0.05) (Table 3 ). Table 2 Correlations between serum miR-99a levels and other parameters. Parameters miR-99a (unadjusted) miR-99a (age, sex, disease course, and BMI adjusted) r value P -value r value P -value Age(years) 0.088 0.309 - - Sex -0.009 0.914 - - Diseaseduration(years) 0.056 0.584 - - BMI (kg/m2 ) 0.046 0.591 - - WHR -0.122 0.192 -0.124 0.155 TC (mmol/L) -0.120 0.164 -0.089 0.309 TG (mmol/L) -0.330 <0.001 -0.183 0.034 HDL-C(mmol/L) 0.333 <0.001 0.223 0.010 LDL-C(mmol/L) -0.166 0.179 -0.056 0.454 HBA1c (%) -0.457 <0.001 -0.392 <0.001 FPG (mmol/L) -0.400 <0.001 -0.299 <0.001 FINS (mU/mL) -0.128 0.135 -0.154 0.076 HOMA-IR -0.358 <0.001 -0.288 <0.001 Hs-CRP (mg/L) -0.282 <0.001 -0.231 0.007 IL-6 (pg/mL) -0.523 <0.001 -0.346 <0.001 SOD(pg/mL) 0.160 0.061 0.109 0.210 mTOR(pg/mL) 0.441 <0.001 0.348 <0.001 Table 3 Stepwise multiple linear regression analyses. Independent variable B Beta SE t P VIF (Constant) 1.262 0.399 3.166 0.002 HBA1c -0.076 -0.188 0.038 -2.024 0.045 1.493 IL-6 -0.014 -0.220 0.006 -2.537 0.011 1.265 mTOR 0.002 0.218 0.001 2.556 0.012 1.253 Correlative relationships among clinicopathological variables in patients with T2DM and NAFLD Univariate analyses revealed TC, TG, HDL-C, LDL-C, HBA1c, FPG, FINS, HOMA-IR, Hs-CRP, IL-6, SOD, mTOR and miR-99a levels to be significantly associated with comorbid T2DM and NAFLD ( P < 0.05) (Table 4 ). With a cut-off value of 0.0678, the AUC was 0.9021 (95%CI: 0.8440–0.9601, P < 0.001), with respective sensitivity and specificity values of 94.3% and 76%, suggesting that serum miR-99a offers a high degree of diagnostic utility for T2DM with NAFLD (Fig. 2 ). Analyzing serum miR-99a may thus be an effective biomarker strategy when screening for comorbid T2DM with NAFLD. Table 4 Univariate logistic regression analyses of correlations between serum miR-99a levels and T2DM with NAFLD. Parameters OR OR 95% CI P -value Age(years) 1.018 0.963–1.076 0.529 Sex 1.013 0.503–2.042 0.971 Disease duration(years) 0.972 0.865–1.092 0.630 BMI (kg/m2 ) 1.134 0.974–1.320 0.106 TC (mmol/L) 1.599 1.117–2.289 0.010 TG (mmol/L) 2.308 1.526–3.490 <0.001 HDL-C(mmol/L) 0.019 0.003–0.136 <0.001 LDL-C(mmol/L) 1.609 1.018–2.542 0.042 HBA1c (%) 1.495 1.265–1.765 <0.001 FPG (mmol/L) 1.313 1.039–1.231 0.004 FINS (mU/mL) 1.106 1.019–1.201 0.016 HOMA-IR 1.575 1.277–1.944 <0.001 Hs-CRP (mg/L) 1.554 1.212–1.991 <0.001 IL-6 (pg/mL) 1.086 1.051–1.121 <0.001 SOD(pg/mL) 0.986 0.978–0.994 <0.001 mTOR(pg/mL) 0.989 0.985–0.994 <0.001 miR-99a 0.000 0.000-0.015 <0.001 Note: All listed variables were considered for one-way logistic regression analyses. OR, odds ratio; CI, confidence interval. Discussion Patients often present with comorbid T2DM and NAFLD owing to the fact that both of these conditions are associated with similar risk factors, contributing to synergistic damage to the liver and other adverse extra-hepatic events [ 13 , 14 ] . In one cross-sectional analysis of patients with T2DM from 20 nations, an estimated 55% of these individuals were also diagnosed with NAFLD [ 15 ] . The risk of T2DM is also approximately two-fold higher among NAFLD patients [ 3 ] , in part because oxidative stress, inflammation, and insulin resistance (IR) drive NAFLD onset [ 16 , 17 ] , with IR also a well-established risk factor for T2DM. However, there remains a pronounced lack of research focused on the pathogenic nature of the association between these two conditions, highlighting a major knowledge gap that warrants further study. In normal human hepatic tissue samples, miR-99a was identified as the 6th most abundant miRNA, whereas it was significantly downregulated in visceral adipose tissue from NAFLD patients and in individuals with HCC, with such downregulation being related to the incidence of hepatic fibrosis [ 18 , 10 ] . Li et al. additionally observed that insulin treatment induced a two-fold decline in miR-99a expression in HL7702 cells, with the ability of insulin to modulate glycolytic activity being dependent on the inhibition of miR-99a expression such that the miR-99a/mTOR/HIF-1 axis plays a key role in shaping glucose consumption and the expression of PKM2 in response to insulin [ 11 ] . Here, T2DM patients were found to exhibit significantly decreased serum miR-99a levels compared to the control group, and these levels were lower still among individuals with comorbid NAFLD (Fig. 1 ). These data thus suggest a potential role for miR-99a downregulation in the incidence of T2DM and NAFLD. The serine/threonine kinase mTOR is a central regulator of cell growth in response to environmental stimuli, with the dysregulation of mTOR signaling having been linked to a range of human diseases including cancer, diabetes, and neurodegenerative conditions [ 19 ] . There is evidence that miR-99a can also directly target mTOR [ 20 ] , and Li et al. recently reported an association between lower miR-99a levels and the insulin-inducible activation of mTOR [ 11 ] . In one meta-analysis, Feng et al. found that mTOR is capable of directly regulating a range of inflammatory mediators including NF-κB and IL-6, protecting against NAFLD development and progression. While the pathogenesis of NAFLD is complex, many of the associated pathways are related to mTOR, as it is capable of indirectly and directly modulating autophagic activity and lipid accumulation within hepatocytes [ 21 ] . Here, significantly lower levels of both miR-99a and mTOR were detected in T2DM with NAFLD patients compared to healthy subjects, and mTOR levels were independently related to miR-99a levels. As such, miR-99a may influence the combined progression of T2DM and NAFLD via the mTOR pathway and related metabolic mechanisms. Inflammation, oxidative stress, and IR all play roles in the onset of NAFLD and T2DM [ 22 , 23 , 24 , 25 ] . IR can contribute to a range of adverse metabolic outcomes such as hyperglycemia, dyslipidemia, prothrombotic state, visceral adiposity, inflammation, and dysregulated endothelial function that can lead to the development of these diseases. In patients with diabetes and prolonged hyperglycemia, abnormal levels of serum biomarkers of inflammation and oxidative stress including NF-κB and IL-6 are evident together with aberrant free fatty acid (FFA) metabolism. These changes contribute to functional alterations in hepatic interstitial cells and the hepatic microcirculatory system, impacting lipid metabolism and exchange between the blood and the liver in a way that promotes the incidence of NAFLD [ 26 ] . Here, T2DM patients diagnosed with NAFLD presented with elevated serum HBAlc, FPG, IR, CRP, and IL-6 levels compared to control subjects, with these correlations between these factors and miR-99a levels remaining evident even after controlling for a range of other factors. HBA1c and IL-6 were both independently correlated with serum miR-99a in this patient cohort. Oxidative stress arises from the production of reactive oxygen species goes beyond the antioxidant system to mitigate associated damage, contributing to decreased peripheral insulin sensitivity and T2DM onset through various pathways. In individuals with NAFLD, lower levels of antioxidant factors including coenzyme Q (CoQ), superoxide dismutase (SOD), and Cu-Zn SOD have been reported [ 27 , 28 ] . Relative to healthy controls, T2DM and T2DM with NAFLD patients exhibited reduced serum SOD levels. In stepwise regression analyses, HBA1c and IL-6 levels were independently associated with miR-99a levels, suggesting that lower levels of this miR-99a may be related to IL-6 and HBA1c status, with all of these variables potentially shaping the onset or progression of T2DM with NAFLD as a consequence of changes in miR-99a expression. Conclusion T2DM patients were herein found to exhibit lower miR-99a levels than those in healthy controls, and these levels were even lower in patients with both T2DM and NAFLD. A strong association between serum miR-99a and mTOR levels was also noted. Lower serum miR-99a levels may be independently associated with NAFLD risk among T2DM patients, suggesting that it may be a valuable diagnostic or prognostic biomarker when screening for these comorbid diseases. Serum miR-99a levels are also functionally related to inflammation, IR, and glucolipid metabolism, underscoring the need for additional research focused on clarifying the pathophysiological role that miR-99a plays in the context of T2DM and NAFLD. Declarations Acknowledgments All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, editors and reviewers. Any product that may be evaluated in this article, or the claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Funding This study was supported by the National Natural Science Foundation of China (grant number 81960160) and the Natural Science Foundation of Gansu Province (grant number 20JR5RA155). Ethics approval This study was approved by the ethics committee of the Second Affiliated Hospital of Gansu Provincial Hospital approved these studies, and conducted in accordance with both the Declarations of Helsinki and Istanbul. Patient consent statement Informed consent was obtained from all individual participants included in the study. Author contribution Y-Y Z, Y-Q Z, P-P J and J-X L designed the research, analyzed the data and wrote the manuscript. J-X L, J-X Q and J L provided the platform and funding for the research and participated in guiding the entire research process. Q C, Y-X B and Y-Q C recruited subjects and collected the data. All authors contributed to the article and approved the submitted version. Data availability Data is available on request to the corresponding authors. Declaration of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. References Rabiee B, Roozafzai F, Hemasi GR, et al. The Prevalence of Non-alcoholic Fatty Liver Disease and Diabetes Mellitus in an Iranian Population. Middle East J Dig Dis . 2017;9(2):86-93. Bellentani S, Marino M. Epidemiology and natural history of non-alcoholic fatty liver disease (NAFLD). Ann Hepatol . 2009;8 Suppl 1:S4-8. Bril F, Cusi K. Management of Nonalcoholic Fatty Liver Disease in Patients With Type 2 Diabetes: A Call to Action. Diabetes Care .2017;40(3):419-430. Ballestri S, Zona S, Targher G, et al. Nonalcoholic fatty liver disease is associated with an almost twofold increased risk of incident type 2 diabetes and metabolic syndrome. Evidence from a systematic review and meta-analysis. J Gastroenterol Hepatol . 2016;31(5):936-44. Yamazaki H, Tsuboya T, Tsuji K, Dohke M, Maguchi H. Independent Association Between Improvement of Nonalcoholic Fatty Liver Disease and Reduced Incidence of Type 2 Diabetes. Diabetes Care .2015;38(9):1673-9. Vidigal JA, Ventura A. The biological functions of miRNAs: lessons from in vivo studies. Trends Cell Biol . 2015;25(3):137-47. Qin H, Liu W. MicroRNA-99a-5p suppresses breast cancer progression and cell-cycle pathway through downregulating CDC25A. J Cell Physiol .2019;234(4):3526-3537. Khalaj M, Woolthuis CM, Hu W, et al. miR-99 regulates normal and malignant hematopoietic stem cell self-renewal. J Exp Med .Aug 7 2017;214(8):2453-2470. Cheng H, Xue J, Yang S, et al. Co-targeting of IGF1R/mTOR pathway by miR-497 and miR-99a impairs hepatocellular carcinoma development. Oncotarget .2017;8(29):47984-47997. Estep M, Armistead D, Hossain N, et al. Differential expression of miRNAs in the visceral adipose tissue of patients with non-alcoholic fatty liver disease. Aliment Pharmacol Ther .2010;32(3):487-97. Li W, Wang J, Chen QD, et al. Insulin promotes glucose consumption via regulation of miR-99a/mTOR/PKM2 pathway. PLoS One . 2013;8(6):e64924. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods .2001;25(4):402-8. Targher G, Lonardo A, Byrne CD. Nonalcoholic fatty liver disease and chronic vascular complications of diabetes mellitus. Nat Rev Endocrinol .2018;14(2):99-114. Mantovani A, Scorletti E, Mosca A, Alisi A, Byrne CD, Targher G. Complications, morbidity and mortality of nonalcoholic fatty liver disease. Metabolism . 2020;111S:154170. Younossi ZM, Golabi P, de Avila L, et al. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: A systematic review and meta-analysis. J Hepatol .2019;71(4):793-801. Videla LA, Rodrigo R, Araya J, Poniachik J. Insulin resistance and oxidative stress interdependency in non-alcoholic fatty liver disease. Trends Mol Med .2006;12(12):555-8. Tilg H, Moschen AR. Insulin resistance, inflammation, and non-alcoholic fatty liver disease. Trends Endocrinol Metab .2008;19(10):371-9. Li D, Liu X, Lin L, et al. MicroRNA-99a inhibits hepatocellular carcinoma growth and correlates with prognosis of patients with hepatocellular carcinoma. J Biol Chem . 2011;286(42):36677-85. Laplante M, Sabatini DM. mTOR signaling in growth control and disease. Cell . 2012;149(2):274-93. Zhang ZW, Guo RW, Lv JL, et al. MicroRNA-99a inhibits insulin-induced proliferation, migration, dedifferentiation, and rapamycin resistance of vascular smooth muscle cells by inhibiting insulin-like growth factor-1 receptor and mammalian target of rapamycin. Biochem Biophys Res Commun . 2017;486(2):414-422. Feng J, Qiu S, Zhou S, et al. mTOR: A Potential New Target in Nonalcoholic Fatty Liver Disease. Int J Mol Sci . 2022;23(16)doi:10.3390/ijms23169196 Tanase DM, Gosav EM, Costea CF, et al. The Intricate Relationship between Type 2 Diabetes Mellitus (T2DM), Insulin Resistance (IR), and Nonalcoholic Fatty Liver Disease (NAFLD). J Diabetes Res . 2020;2020:3920196. Klisic A, Isakovic A, Kocic G, et al. Relationship between Oxidative Stress, Inflammation and Dyslipidemia with Fatty Liver Index in Patients with Type 2 Diabetes Mellitus. Exp Clin Endocrinol Diabetes .2018;126(6):371-378. Asrih M, Jornayvaz FR. Inflammation as a potential link between nonalcoholic fatty liver disease and insulin resistance. J Endocrinol . 2013;218(3):R25-36. Donath MY, Shoelson SE. Type 2 diabetes as an inflammatory disease. Nat Rev Immunol .2011;11(2):98-107. Zhang H, Dellsperger KC, Zhang C. The link between metabolic abnormalities and endothelial dysfunction in type 2 diabetes: an update. Basic Res Cardiol . 2012;107(1):237. Erhardt A, Stahl W, Sies H, Lirussi F, Donner A, Haussinger D. Plasma levels of vitamin E and carotenoids are decreased in patients with Nonalcoholic Steatohepatitis (NASH). Eur J Med Res . 2011;16(2):76-8. Videla LA, Rodrigo R, Orellana M, et al. Oxidative stress-related parameters in the liver of non-alcoholic fatty liver disease patients. Clin Sci (Lond) . 2004;106(3):261-8. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3888039","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268720824,"identity":"2e5e0f95-c089-45fc-8fa2-b948bcbbd675","order_by":0,"name":"Yangyang Zhang","email":"","orcid":"","institution":"Affiliations 1Clinical Medical College, Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yangyang","middleName":"","lastName":"Zhang","suffix":""},{"id":268720825,"identity":"c3f82315-94ff-4e63-9e2a-98a8e985ceb5","order_by":1,"name":"Yuqiong Zuo","email":"","orcid":"","institution":"Medical Record Management Department, Gansu Provincial hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuqiong","middleName":"","lastName":"Zuo","suffix":""},{"id":268720826,"identity":"31ea49b2-1041-4556-9d21-a49053720bfc","order_by":2,"name":"Qian Chen","email":"","orcid":"","institution":"Affiliations 1Clinical Medical College, Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Chen","suffix":""},{"id":268720827,"identity":"1713d81e-341d-4434-bcb0-8f339d6cd43a","order_by":3,"name":"Yaqiang Cui","email":"","orcid":"","institution":"Gansu Provincial hospital","correspondingAuthor":false,"prefix":"","firstName":"Yaqiang","middleName":"","lastName":"Cui","suffix":""},{"id":268720828,"identity":"033c43df-0070-45a0-a68f-0ee3d95d1932","order_by":4,"name":"Yanxia Bao","email":"","orcid":"","institution":"Gansu Provincial hospital","correspondingAuthor":false,"prefix":"","firstName":"Yanxia","middleName":"","lastName":"Bao","suffix":""},{"id":268720829,"identity":"d0116099-32c9-4191-a66d-57fc555dc099","order_by":5,"name":"Panpan Jiang","email":"","orcid":"","institution":"First Clinical Medical College of Lanzhou University","correspondingAuthor":false,"prefix":"","firstName":"Panpan","middleName":"","lastName":"Jiang","suffix":""},{"id":268720830,"identity":"12b1c244-abde-42b8-b8c1-e3005e9df4a1","order_by":6,"name":"Jing Liu","email":"","orcid":"","institution":"Gansu Provincial hospital","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Liu","suffix":""},{"id":268720831,"identity":"0f76ea9d-4819-44d1-bd1a-6ed724699427","order_by":7,"name":"Jinxing Quan","email":"","orcid":"","institution":"Gansu Provincial hospital","correspondingAuthor":false,"prefix":"","firstName":"Jinxing","middleName":"","lastName":"Quan","suffix":""},{"id":268720832,"identity":"a14925d2-4b9a-4a50-96b2-a97c1d2cfae4","order_by":8,"name":"Juxiang Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYDAC5gMMBz78YGBsYG9sfPiBKC1sCYwHZ/YAtfAcbjaWIFIL82EeNqAWifQ2AR5idJizcScc4OGxkd1w82EbgwSDnZxuAwEtlm28Gw5IWKQZb7id2PaggCHZ2OwAAS0G93s3HDDgOZwI1NJuIMFwIHEbQS3HgLYksP1P3HDzYJsED9FaDrAdSNxwg5EELQcbe5KNZ55JBAayATF+Oca7+fOfH3ayfcePP3z4ocJOjqAWdBNIUz4KRsEoGAWjAAcAACRnTTxRSVz0AAAAAElFTkSuQmCC","orcid":"","institution":"Gansu Provincial hospital","correspondingAuthor":true,"prefix":"","firstName":"Juxiang","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-01-22 13:25:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3888039/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3888039/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50172871,"identity":"f0429af8-2e7d-4991-b27e-ba9c83b612f1","added_by":"auto","created_at":"2024-01-25 15:58:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":20734,"visible":true,"origin":"","legend":"\u003cp\u003eSerum miR-99a expression in the indicated participant groups. ****P\u0026lt;0.001; **P\u0026lt;0.01.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3888039/v1/39d6ac3ee3656c06d1d5a0cc.png"},{"id":50172870,"identity":"940bf906-86ea-47e0-bc86-9cb40058ca50","added_by":"auto","created_at":"2024-01-25 15:58:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":15272,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3888039/v1/0420df12c245372014d911ad.png"},{"id":50317102,"identity":"14f63d7a-dcf1-409e-a118-beeae4c80f99","added_by":"auto","created_at":"2024-01-29 16:13:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":390483,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3888039/v1/1de0e998-4b3d-4a6e-9365-8c92d9084585.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of Serum miR-99a level and Nonalcoholic Fatty Liver Disease, Serum mTOR levels in Patients with Type 2 Diabetes Mellitus","fulltext":[{"header":"Introduction","content":"\u003cp\u003eType 2 diabetes mellitus (T2DM) is among the most common forms of chronic disease, and many T2DM patients suffer from comorbid non-alcoholic fatty liver disease (NAFLD)\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e, which impacts upwards of 70% of individuals with T2DM\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. The risk of T2DM incidence is also approximately two-fold higher among patients with a NAFLD diagnosis\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e, and the alleviation of NAFLD severity can modulate the risk of T2DM incidence in patients\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMicroRNAs (miRNAs) are 21\u0026ndash;25 nucleotide-long transcripts that exhibit a high degree of evolutionary conservation and function through their ability to bind to target mRNA 3\u0026rsquo;-untranslated region (UTR) sequences, thereby suppressing translation or promoting degradation\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Liver tissue reportedly exhibits high levels of miR-99a expression, while the downregulation of this miRNA has been reported in a range of cancers such as breast cancer\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e, acute myeloid leukemia\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e, and hepatocellular carcinoma\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e, thereby promoting enhanced proliferative, invasive, and migratory activity in these malignant cells. A significant correlative relationship between miR-99a downregulation in NAFLD patient visceral adipose tissue and hepatic fibrosis\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Insulin can regulate miR-99a, and the miR-99a/mTOR/PKM2 axis can regulate glucose consumption\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. As such, miR-99a may influence the incidence of severity of comorbid T2DM and NAFLD, although no studies to date have specifically examined its role in this pathogenic context.\u003c/p\u003e \u003cp\u003eThis study was thus developed to examine how serum miR-99a levels relate to the incidence of comorbid T2DM and NAFLD through comparisons of samples from controls, T2DM patients, and T2DM with NAFLD patients. Together, these analyses aim to define a novel target for treating and/or preventing T2DM and NAFLD, offering a theoretical foundation for future interventional approaches.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eResearch participants\u003c/h2\u003e \u003cp\u003eFor this study, 98 T2DM patients were recruited among individuals receiving treatment in the Endocrinology Department of Gansu Provincial Hospital, including 48 without NAFLD and 50 with NAFLD as diagnosed via ultrasonography. In addition, 39 healthy individuals were selected as controls during the same study interval. Subjects were recruited if they exhibited (1) viral hepatitis, hepatic cirrhosis, biliary tract obstruction, or autoimmune liver disease, (2) a history of alcohol use (\u0026gt;\u0026thinsp;210 g/week or \u0026gt;\u0026thinsp;140 g/week for over 12 months for males and females, respectively, (3) severe infections, acute diabetic complications, or pregnancy, or (4) were using drugs with the potential to impact lipid metabolism. The Clinical Research Ethics Committee of Gansu Provincial Hospital approved these studies, with all subjects providing written informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePhysiological and biochemical analyses\u003c/h2\u003e \u003cp\u003eGeneral physiological characteristics were recorded for all subjects, including age, sex, weight, height, Hip Circumference (HC), Waist Circumference (WC) and diabetes duration, enabling the calculation of both the waist-hip ratio (WHR; WC/HC) and BMI (weight/height squared (kg/m2)). Biochemical testing of parameters including TC, TG, LDL-C, HDL-C, FPG, DINS, HBA1c, and Hs-CRP was performed by the Laboratory Department of Gansu Provincial Hospital. The homeostatic insulin resistance (HOMA-IR) model was computed as follows: HOMA-IR\u0026thinsp;=\u0026thinsp;FPG\u0026times;FINS/22.5. NAFLD was detected based on carotid ultrasonography (7.5 MHz frequency color Doppler ultrasound, Siemens Acuson\u0026times;300, Germany) performed by a trained sonographer. Standard testing procedures were used for all analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of serum miR-99a, mTOR, SOD, and IL-6 levels\u003c/h2\u003e \u003cp\u003ePatient 5 mL venous blood samples were collected while fasting. These samples were centrifuged (3,000 rpm, 10 min, 4\u0026deg;C), and serum was stored at -80\u0026deg;C. To measure miR-99a levels, 200 \u0026micro;L of serum was combined with 600 \u0026micro;L of Trizol (Shanghai, China) to extract RNA at room temperature for 5 min, and 14 \u0026micro;L of DEPC H\u003csub\u003e2\u003c/sub\u003eO was used for dissolving RNA. Then, cDNA synthesis was performed with an All-in-One\u0026trade; miRNA First-Strand cDNA Synthesis Kit 2.0 (Guangzhou, China). All qPCR reactions were performed in a 20 \u0026micro;L total volume with Taq Pro Universal SYBR qPCR Master Mix (Nanjing, China) and a LightCycler 480 instrument (Shanghai, China) with the settings: 95\u0026deg;C for 3 min; 40 cycles of 90\u0026deg;C 10 s, and 65\u0026deg;C 30s. The 2\u003csup\u003e\u0026minus;△△CT\u003c/sup\u003e method was used to assess relative gene expression \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Plasma IL-6, SOD, and mTOR levels were detected with commercial ELISA kits (Shanghai, China) as directed, with standard curves being generated by plotting the concentrations of standards against absorbance at 450 nm, with logistic regression equations then being used to fit these data, enabling the calculation of sample concentrations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were analyzed with SPSS 27.0 (IBM, USA) and GraphPad Prism 9.4.1. Continuous normally distributed data are reported as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and analyzed with one-way ANOVAs, whereas non-normally distributed data were given in the form of medians with interquartile range ranges (M (P25, P75)) and compared with Kruskal-Wallis test. Categorical variables were reported as percentages. Relationships among variables were assessed with Spearman correlation test. Following adjustment for age, sex, BMI, and diabetes duration, a partial correlation method was used to assess these relationships. Univariate regression analyses were also employed to assess the interplay among different variables, after which a multiple regression model was established. Diagnostic performance was also evaluated with receiver operating characteristic (ROC) curves. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 serves as the cut-off to define statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003ePhysiological and biochemical results from participants in the three subject groups are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. No differences in age, sex, BMI, LDL-C, or FINS were detected among these three groups, and diabetes duration was comparable in the T2DM and T2DM with NAFLD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Comapred with controls, the T2DM and T2DM with NAFLD patients exhibited elevated IL-6, HBA1c, FPG, and HOMA-IR levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as well as reduced HDL-C and mTOR levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while these values did not differ when comparing T2DM patients with and without NAFLD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Serum TG and Hs-CRP in T2DM\u0026thinsp;+\u0026thinsp;NAFLD group were significantly elevated relative to control group and T2DM individuals (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas the opposite trend was observed with respect to SOD levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while in the control and T2DM groups were comparable (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Significantly decreased median serum miR-99a levels were also noted in the T2DM group compared to healthy controls, with further reductions in T2DM\u0026thinsp;+\u0026thinsp;NAFLD patients (0.79 vs 0.16 vs 0.03, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant physicochemical characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl Group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;39)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT2DM group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;48)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT2DM\u0026thinsp;+\u0026thinsp;NAFLD group(n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.74\u0026thinsp;\u0026plusmn;\u0026thinsp;7.496c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.27\u0026thinsp;\u0026plusmn;\u0026thinsp;5.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.84\u0026thinsp;\u0026plusmn;\u0026thinsp;5.947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22(56.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(56.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28(56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(2,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(1, 7.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m2 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.39(23.24,25.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.856(21.78,26.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.40(23.57, 26.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.919\u0026thinsp;\u0026plusmn;\u0026thinsp;0.047\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.934\u0026thinsp;\u0026plusmn;\u0026thinsp;0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.947\u0026thinsp;\u0026plusmn;\u0026thinsp;0.054\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.39(3.87,4.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.17(3.20,4.82)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.72(4.02, 5.63)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23(0.96,1.56)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.39(1.03,2.17)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.23(1.53,3.30)\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003eb、c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBA1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.5(5.3,5.8)\u003csup\u003eb,c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.4(7.7, 10.78)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.75(8.45,11.46)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.13(4.86,5.73)\u003csup\u003eb,c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.03(7.15, 12.86)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(7.35,13.16)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFINS (mU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.1(5.0,8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.05(4.02,10.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.2(5.6,12.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMA-IR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.49(1.06,2.12)\u003csup\u003eb、c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.72(2.06,4.21)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.66(2.51,5.81)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHs-CRP (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60(0.40,0.90)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95(0.50,1.75)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.65(0.80,3.33)\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.41(13.55,22.24)\u003csup\u003eb、c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.01(30.02,39.92)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.33(31.11,52.59)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOD(pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e238.14\u0026thinsp;\u0026plusmn;\u0026thinsp;69.33\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213.67\u0026thinsp;\u0026plusmn;\u0026thinsp;53.88\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e187.39\u0026thinsp;\u0026plusmn;\u0026thinsp;41.50\u003csup\u003ea、b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emTOR(pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e344.03(222.13, 408.80)\u003csup\u003eb、c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199.91(118.18,214.51)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137.75(86.47,177.79)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiR-99a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.79(0.20,2.01)\u003csup\u003eb, c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16(0.11,0.31)\u003csup\u003ea, c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03(0.01,0.08)\u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: a, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 vs. Control group; b, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 vs. T2DM group; c, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 vs. T2DM\u0026thinsp;+\u0026thinsp;NAFLD group.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCorrelations between serum miR-99a and physicochemical parameters\u003c/h2\u003e \u003cp\u003eThe levels of miR-99a in patient serum were significantly negatively correlated with TG, HBA1c, FPG, HOMA-IR, Hs-CRP, and IL-6 levels, whereas miR-99a levels were positively correlated with mTOR and HDL-C in this patient cohort (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Following adjustment for age, sex, BMI, and T2DM duration, an independent association between serum miR-99a levels and HOMA-IR, Hs-CRP, TG, HBA1c, IL-6, HDL-C, FPG, and mTOR levels remained evident (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The Durbin-Watson (D-W) value for the regression equation was 1.714, indicating the absence of any autocorrelative relationship among variables consistent with good model construction. The mean of the standardized residuals was 0, while the SD was 0.989, consistent with an approximately normal distribution. These results thus revealed that HBA1c, IL-6, and mTOR levels were independently correlated with patient serum miR-99a levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelations between serum miR-99a levels and other parameters.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003emiR-99a\u003c/p\u003e \u003cp\u003e(unadjusted)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003emiR-99a\u003c/p\u003e \u003cp\u003e(age, sex, disease course, and BMI adjusted)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiseaseduration(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m2 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBA1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFINS (mU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMA-IR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHs-CRP (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOD(pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emTOR(pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStepwise multiple linear regression analyses.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBA1c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.493\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.265\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emTOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.253\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCorrelative relationships among clinicopathological variables in patients with T2DM and NAFLD\u003c/h2\u003e \u003cp\u003eUnivariate analyses revealed TC, TG, HDL-C, LDL-C, HBA1c, FPG, FINS, HOMA-IR, Hs-CRP, IL-6, SOD, mTOR and miR-99a levels to be significantly associated with comorbid T2DM and NAFLD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). With a cut-off value of 0.0678, the AUC was 0.9021 (95%CI: 0.8440\u0026ndash;0.9601, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with respective sensitivity and specificity values of 94.3% and 76%, suggesting that serum miR-99a offers a high degree of diagnostic utility for T2DM with NAFLD (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Analyzing serum miR-99a may thus be an effective biomarker strategy when screening for comorbid T2DM with NAFLD.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate logistic regression analyses of correlations between serum miR-99a levels and T2DM with NAFLD.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR 95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.963\u0026ndash;1.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.529\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.503\u0026ndash;2.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.971\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.865\u0026ndash;1.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.630\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m2 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.974\u0026ndash;1.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.117\u0026ndash;2.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.526\u0026ndash;3.490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.003\u0026ndash;0.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.018\u0026ndash;2.542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBA1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.265\u0026ndash;1.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.039\u0026ndash;1.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFINS (mU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.019\u0026ndash;1.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMA-IR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.277\u0026ndash;1.944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHs-CRP (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.212\u0026ndash;1.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.051\u0026ndash;1.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOD(pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.978\u0026ndash;0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emTOR(pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.985\u0026ndash;0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiR-99a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000-0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: All listed variables were considered for one-way logistic regression analyses. OR, odds ratio; CI, confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003ePatients often present with comorbid T2DM and NAFLD owing to the fact that both of these conditions are associated with similar risk factors, contributing to synergistic damage to the liver and other adverse extra-hepatic events\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. In one cross-sectional analysis of patients with T2DM from 20 nations, an estimated 55% of these individuals were also diagnosed with NAFLD\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. The risk of T2DM is also approximately two-fold higher among NAFLD patients\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e, in part because oxidative stress, inflammation, and insulin resistance (IR) drive NAFLD onset\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e, with IR also a well-established risk factor for T2DM. However, there remains a pronounced lack of research focused on the pathogenic nature of the association between these two conditions, highlighting a major knowledge gap that warrants further study.\u003c/p\u003e \u003cp\u003eIn normal human hepatic tissue samples, miR-99a was identified as the 6th most abundant miRNA, whereas it was significantly downregulated in visceral adipose tissue from NAFLD patients and in individuals with HCC, with such downregulation being related to the incidence of hepatic fibrosis\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Li et al. additionally observed that insulin treatment induced a two-fold decline in miR-99a expression in HL7702 cells, with the ability of insulin to modulate glycolytic activity being dependent on the inhibition of miR-99a expression such that the miR-99a/mTOR/HIF-1 axis plays a key role in shaping glucose consumption and the expression of PKM2 in response to insulin\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Here, T2DM patients were found to exhibit significantly decreased serum miR-99a levels compared to the control group, and these levels were lower still among individuals with comorbid NAFLD (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These data thus suggest a potential role for miR-99a downregulation in the incidence of T2DM and NAFLD.\u003c/p\u003e \u003cp\u003eThe serine/threonine kinase mTOR is a central regulator of cell growth in response to environmental stimuli, with the dysregulation of mTOR signaling having been linked to a range of human diseases including cancer, diabetes, and neurodegenerative conditions\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. There is evidence that miR-99a can also directly target mTOR\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e, and Li et al. recently reported an association between lower miR-99a levels and the insulin-inducible activation of mTOR\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. In one meta-analysis, Feng et al. found that mTOR is capable of directly regulating a range of inflammatory mediators including NF-κB and IL-6, protecting against NAFLD development and progression. While the pathogenesis of NAFLD is complex, many of the associated pathways are related to mTOR, as it is capable of indirectly and directly modulating autophagic activity and lipid accumulation within hepatocytes\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Here, significantly lower levels of both miR-99a and mTOR were detected in T2DM with NAFLD patients compared to healthy subjects, and mTOR levels were independently related to miR-99a levels. As such, miR-99a may influence the combined progression of T2DM and NAFLD via the mTOR pathway and related metabolic mechanisms.\u003c/p\u003e \u003cp\u003eInflammation, oxidative stress, and IR all play roles in the onset of NAFLD and T2DM\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. IR can contribute to a range of adverse metabolic outcomes such as hyperglycemia, dyslipidemia, prothrombotic state, visceral adiposity, inflammation, and dysregulated endothelial function that can lead to the development of these diseases. In patients with diabetes and prolonged hyperglycemia, abnormal levels of serum biomarkers of inflammation and oxidative stress including NF-κB and IL-6 are evident together with aberrant free fatty acid (FFA) metabolism. These changes contribute to functional alterations in hepatic interstitial cells and the hepatic microcirculatory system, impacting lipid metabolism and exchange between the blood and the liver in a way that promotes the incidence of NAFLD\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Here, T2DM patients diagnosed with NAFLD presented with elevated serum HBAlc, FPG, IR, CRP, and IL-6 levels compared to control subjects, with these correlations between these factors and miR-99a levels remaining evident even after controlling for a range of other factors. HBA1c and IL-6 were both independently correlated with serum miR-99a in this patient cohort. Oxidative stress arises from the production of reactive oxygen species goes beyond the antioxidant system to mitigate associated damage, contributing to decreased peripheral insulin sensitivity and T2DM onset through various pathways. In individuals with NAFLD, lower levels of antioxidant factors including coenzyme Q (CoQ), superoxide dismutase (SOD), and Cu-Zn SOD have been reported\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Relative to healthy controls, T2DM and T2DM with NAFLD patients exhibited reduced serum SOD levels. In stepwise regression analyses, HBA1c and IL-6 levels were independently associated with miR-99a levels, suggesting that lower levels of this miR-99a may be related to IL-6 and HBA1c status, with all of these variables potentially shaping the onset or progression of T2DM with NAFLD as a consequence of changes in miR-99a expression.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eT2DM patients were herein found to exhibit lower miR-99a levels than those in healthy controls, and these levels were even lower in patients with both T2DM and NAFLD. A strong association between serum miR-99a and mTOR levels was also noted. Lower serum miR-99a levels may be independently associated with NAFLD risk among T2DM patients, suggesting that it may be a valuable diagnostic or prognostic biomarker when screening for these comorbid diseases. Serum miR-99a levels are also functionally related to inflammation, IR, and glucolipid metabolism, underscoring the need for additional research focused on clarifying the pathophysiological role that miR-99a plays in the context of T2DM and NAFLD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, editors and reviewers. Any product that may be evaluated in this article, or the claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the National Natural Science Foundation of China (grant number 81960160) and the Natural Science Foundation of Gansu Province (grant number 20JR5RA155).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the ethics committee of the Second Affiliated Hospital of Gansu Provincial Hospital approved these studies, and conducted in accordance with both the Declarations of Helsinki and Istanbul.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY-Y Z, Y-Q Z, P-P J and J-X L designed the research, analyzed the data and wrote the manuscript. J-X L, J-X Q and J L provided the platform and funding for the research and participated in guiding the entire research process. Q C, Y-X B and Y-Q C recruited subjects and collected the data. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is available on request to the corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRabiee B, Roozafzai F, Hemasi GR, et al. The Prevalence of Non-alcoholic Fatty Liver Disease and Diabetes Mellitus in an Iranian Population. \u003cem\u003eMiddle East J Dig Dis\u003c/em\u003e. 2017;9(2):86-93.\u003c/li\u003e\n\u003cli\u003eBellentani S, Marino M. Epidemiology and natural history of non-alcoholic fatty liver disease (NAFLD). \u003cem\u003eAnn Hepatol\u003c/em\u003e. 2009;8 Suppl 1:S4-8.\u003c/li\u003e\n\u003cli\u003eBril F, Cusi K. Management of Nonalcoholic Fatty Liver Disease in Patients With Type 2 Diabetes: A Call to Action. \u003cem\u003eDiabetes Care\u003c/em\u003e.2017;40(3):419-430.\u003c/li\u003e\n\u003cli\u003eBallestri S, Zona S, Targher G, et al. Nonalcoholic fatty liver disease is associated with an almost twofold increased risk of incident type 2 diabetes and metabolic syndrome. Evidence from a systematic review and meta-analysis. \u003cem\u003eJ Gastroenterol Hepatol\u003c/em\u003e. 2016;31(5):936-44.\u003c/li\u003e\n\u003cli\u003eYamazaki H, Tsuboya T, Tsuji K, Dohke M, Maguchi H. Independent Association Between Improvement of Nonalcoholic Fatty Liver Disease and Reduced Incidence of Type 2 Diabetes. \u003cem\u003eDiabetes Care\u003c/em\u003e.2015;38(9):1673-9.\u003c/li\u003e\n\u003cli\u003eVidigal JA, Ventura A. The biological functions of miRNAs: lessons from in vivo studies. \u003cem\u003eTrends Cell Biol\u003c/em\u003e. 2015;25(3):137-47.\u003c/li\u003e\n\u003cli\u003eQin H, Liu W. MicroRNA-99a-5p suppresses breast cancer progression and cell-cycle pathway through downregulating CDC25A. \u003cem\u003eJ Cell Physiol\u003c/em\u003e.2019;234(4):3526-3537.\u003c/li\u003e\n\u003cli\u003eKhalaj M, Woolthuis CM, Hu W, et al. miR-99 regulates normal and malignant hematopoietic stem cell self-renewal. \u003cem\u003eJ Exp Med\u003c/em\u003e.Aug 7 2017;214(8):2453-2470.\u003c/li\u003e\n\u003cli\u003eCheng H, Xue J, Yang S, et al. Co-targeting of IGF1R/mTOR pathway by miR-497 and miR-99a impairs hepatocellular carcinoma development. \u003cem\u003eOncotarget\u003c/em\u003e.2017;8(29):47984-47997.\u003c/li\u003e\n\u003cli\u003eEstep M, Armistead D, Hossain N, et al. Differential expression of miRNAs in the visceral adipose tissue of patients with non-alcoholic fatty liver disease. \u003cem\u003eAliment Pharmacol Ther\u003c/em\u003e.2010;32(3):487-97.\u003c/li\u003e\n\u003cli\u003eLi W, Wang J, Chen QD, et al. Insulin promotes glucose consumption via regulation of miR-99a/mTOR/PKM2 pathway. \u003cem\u003ePLoS One\u003c/em\u003e. 2013;8(6):e64924.\u003c/li\u003e\n\u003cli\u003eLivak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. \u003cem\u003eMethods\u003c/em\u003e.2001;25(4):402-8.\u003c/li\u003e\n\u003cli\u003eTargher G, Lonardo A, Byrne CD. Nonalcoholic fatty liver disease and chronic vascular complications of diabetes mellitus. \u003cem\u003eNat Rev Endocrinol\u003c/em\u003e.2018;14(2):99-114.\u003c/li\u003e\n\u003cli\u003eMantovani A, Scorletti E, Mosca A, Alisi A, Byrne CD, Targher G. Complications, morbidity and mortality of nonalcoholic fatty liver disease. \u003cem\u003eMetabolism\u003c/em\u003e. 2020;111S:154170.\u003c/li\u003e\n\u003cli\u003eYounossi ZM, Golabi P, de Avila L, et al. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: A systematic review and meta-analysis. \u003cem\u003eJ Hepatol\u003c/em\u003e.2019;71(4):793-801.\u003c/li\u003e\n\u003cli\u003eVidela LA, Rodrigo R, Araya J, Poniachik J. Insulin resistance and oxidative stress interdependency in non-alcoholic fatty liver disease. \u003cem\u003eTrends Mol Med\u003c/em\u003e.2006;12(12):555-8.\u003c/li\u003e\n\u003cli\u003eTilg H, Moschen AR. Insulin resistance, inflammation, and non-alcoholic fatty liver disease. \u003cem\u003eTrends Endocrinol Metab\u003c/em\u003e.2008;19(10):371-9.\u003c/li\u003e\n\u003cli\u003eLi D, Liu X, Lin L, et al. MicroRNA-99a inhibits hepatocellular carcinoma growth and correlates with prognosis of patients with hepatocellular carcinoma. \u003cem\u003eJ Biol Chem\u003c/em\u003e. 2011;286(42):36677-85.\u003c/li\u003e\n\u003cli\u003eLaplante M, Sabatini DM. mTOR signaling in growth control and disease. \u003cem\u003eCell\u003c/em\u003e. 2012;149(2):274-93.\u003c/li\u003e\n\u003cli\u003eZhang ZW, Guo RW, Lv JL, et al. MicroRNA-99a inhibits insulin-induced proliferation, migration, dedifferentiation, and rapamycin resistance of vascular smooth muscle cells by inhibiting insulin-like growth factor-1 receptor and mammalian target of rapamycin. \u003cem\u003eBiochem Biophys Res Commun\u003c/em\u003e. 2017;486(2):414-422.\u003c/li\u003e\n\u003cli\u003eFeng J, Qiu S, Zhou S, et al. mTOR: A Potential New Target in Nonalcoholic Fatty Liver Disease. \u003cem\u003eInt J Mol Sci\u003c/em\u003e. 2022;23(16)doi:10.3390/ijms23169196\u003c/li\u003e\n\u003cli\u003eTanase DM, Gosav EM, Costea CF, et al. The Intricate Relationship between Type 2 Diabetes Mellitus (T2DM), Insulin Resistance (IR), and Nonalcoholic Fatty Liver Disease (NAFLD). \u003cem\u003eJ Diabetes Res\u003c/em\u003e. 2020;2020:3920196.\u003c/li\u003e\n\u003cli\u003eKlisic A, Isakovic A, Kocic G, et al. Relationship between Oxidative Stress, Inflammation and Dyslipidemia with Fatty Liver Index in Patients with Type 2 Diabetes Mellitus. \u003cem\u003eExp Clin Endocrinol Diabetes\u003c/em\u003e.2018;126(6):371-378.\u003c/li\u003e\n\u003cli\u003eAsrih M, Jornayvaz FR. Inflammation as a potential link between nonalcoholic fatty liver disease and insulin resistance. \u003cem\u003eJ Endocrinol\u003c/em\u003e. 2013;218(3):R25-36.\u003c/li\u003e\n\u003cli\u003eDonath MY, Shoelson SE. Type 2 diabetes as an inflammatory disease. \u003cem\u003eNat Rev Immunol\u003c/em\u003e.2011;11(2):98-107.\u003c/li\u003e\n\u003cli\u003eZhang H, Dellsperger KC, Zhang C. The link between metabolic abnormalities and endothelial dysfunction in type 2 diabetes: an update. \u003cem\u003eBasic Res Cardiol\u003c/em\u003e. 2012;107(1):237.\u003c/li\u003e\n\u003cli\u003eErhardt A, Stahl W, Sies H, Lirussi F, Donner A, Haussinger D. Plasma levels of vitamin E and carotenoids are decreased in patients with Nonalcoholic Steatohepatitis (NASH). \u003cem\u003eEur J Med Res\u003c/em\u003e. 2011;16(2):76-8.\u003c/li\u003e\n\u003cli\u003eVidela LA, Rodrigo R, Orellana M, et al. Oxidative stress-related parameters in the liver of non-alcoholic fatty liver disease patients. \u003cem\u003eClin Sci (Lond)\u003c/em\u003e. 2004;106(3):261-8.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"type 2 diabetes mellitus, nonalcoholic fatty liver disease, miR-99a, mTOR","lastPublishedDoi":"10.21203/rs.3.rs-3888039/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3888039/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis study was designed with the goal of exploring miR-99a expression in T2DM patients suffering from comorbid NAFLD and clarifying the importance of miR-99a in this pathological context.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 137 subjects were included in this study, including 50 T2DM patients with NAFLD (T2DM\u0026thinsp;+\u0026thinsp;NAFLD group),48 T2DM patients without NAFLD (T2DM group), and 39 healthy subjects (Control group). We measured the levels of IL-6, mTOR and SOD in the serum of the subjects by ELISA. The plasma miR-99a levels was detected by RT-PCR. The correlation between serum miR-99a level and other indicators was analyzed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSerum miR-99a levels (median 0.79 vs 0.16 vs 0.03, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly lower in the T2DM group than the healthy population and further decreased in the T2DM with NAFLD patients (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). After adjusting for age, gender, illness duration and BMI, spearman correlation analysis showed that TG, HBA1c, FPG, HOMA-IR, Hs-CRP, IL-6, HDL-C, mTOR(P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) remained independently linked with serum miR-99a. And stepwise linear regression analysis showed that HBA1c, IL-6 and mTOR are independent serum miR-99a correlation variables (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Moreover, the ROC results indicated that serum miR-99a has a high diagnostic value for T2DM with NAFLD. In conclusion, serum miR-99a may be utilized as a screening biomarker for T2DM with NAFLD.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThese data highlight a potential role for miR-99a as a regulator of the comorbid incidence of T2DM and NAFLD, suggesting that measuring the levels of miR-99a can effectively predict the risk of NAFLD in those with T2DM.\u003c/p\u003e","manuscriptTitle":"Association of Serum miR-99a level and Nonalcoholic Fatty Liver Disease, Serum mTOR levels in Patients with Type 2 Diabetes Mellitus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-25 15:58:45","doi":"10.21203/rs.3.rs-3888039/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1907f917-7cdf-4187-b6d4-8cb1be90dbb8","owner":[],"postedDate":"January 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-29T16:05:40+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-25 15:58:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3888039","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3888039","identity":"rs-3888039","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}