Whole blood microRNA levels associate with glycemic status and correlate with target mRNAs in pathways important to type 2 diabetes

1 Scientific RepoRts | (2019) 9:8887 | https://doi.org/10.1038/s41598-019-43793-4 www.nature.com/scientificreports Whole blood microRNA levels associate with glycemic status and correlate with target mRNAs in pathways important to type 2 diabetes Nina Mononen1, Leo-pekka Lyytikäinen 1, Ilkka seppälä 1, pashupati p. Mishra1, Markus Juonala2, Melanie Waldenberger3, Norman Klopp4,5, thomas Illig3,4,5, Jaana Leiviskä6, Britt-Marie Loo7, Reijo Laaksonen1, Niku oksala1,8, Mika Kähönen9, Nina Hutri-Kähönen10, olli Raitakari11,12, terho Lehtimäki1 & emma Raitoharju1 We analyzed the associations between whole blood microRNA profiles and the indices of glucose metabolism and impaired fasting glucose and examined whether the discovered microRNAs correlate with the expression of their mRNA targets. MicroRNA and gene expression profiling were performed for the Young Finns Study participants (n = 871). Glucose, insulin, and glycated hemoglobin (HbA1c) levels were measured, the insulin resistance index (HOMA2-IR) was calculated, and the glycemic status (normoglycemic [n = 534]/impaired fasting glucose [IFG] [n = 252]/type 2 diabetes [T2D] [n = 24]) determined. Levels of hsa-miR-144-5p, -122-5p, -148a-3p, -589-5p, and hsa-let-7a-5p associated with glycemic status. hsa-miR-144-5p and -148a-3p associated with glucose levels, while hsa-miR-144-5p, -122-5p, -184, and -339-3p associated with insulin levels and HOMA2-IR, and hsa-miR-148a-3p, -15b3p, -93-3p, -146b-5p, -221-3p, -18a-3p, -642a-5p, and -181-2-3p associated with HbA1c levels. The targets of hsa-miR-146b-5p that correlated with its levels were enriched in inflammatory pathways, and the targets of hsa-miR-221-3p were enriched in insulin signaling and T2D pathways. These pathways showed indications of co-regulation by HbA1c-associated miRNAs. There were significant differences in the microRNA profiles associated with glucose, insulin, or HOMA-IR compared to those associated with HbA1c. The HbA1c-associated miRNAs also correlated with the expression of target mRNAs in pathways important to the development of T2D. 1Department of clinical chemistry, Pirkanmaa Hospital District, fimlab Laboratories, and the finnish cardiovascular Research center, tampere, faculty of Medicine and Health technology, tampere University, tampere, finland. 2Division of Medicine, turku University Hospital, and Department of Medicine, University of turku, turku, finland. 3Research Unit of Molecular epidemiology, Helmholtz Zentrum, German Research center for environmental Health, Munich, Germany. 4Hannover Unified Biobank, Hannover Medical School, Hannover, Germany. 5institute for Human Genetics, Hannover Medical School, Hanover, Germany. 6Department of clinical chemistry, University of Helsinki and Helsinki University Hospital HUSLAB, Helsinki, Finland. 7Joint Clinical Biochemistry Laboratory of the University of turku and turku University central Hospital and Department of chronic Disease Prevention, national institute for Health and Welfare, turku, finland. 8centre for Vascular Surgery and interventional Radiology, tampere University Hospital, tampere, finland. 9Department of clinical Physiology, tampere University Hospital, and faculty of Medicine and Health technology, tampere University, tampere, finland. 10Department of Pediatrics, tampere University and tampere University Hospital, tampere, finland. 11Research centre for Applied and Preventive cardiovascular Medicine, University of turku, turku, finland. 12Department of clinical Physiology and nuclear Medicine and centre for Population Health Research, University of turku and turku University Hospital, turku, finland. correspondence and requests for materials should be addressed to e.R. (email: [email protected]) Received: 28 June 2018 Accepted: 29 April 2019 Published: xx xx xxxx opeN 2 Scientific RepoRts | (2019) 9:8887 | https://doi.org/10.1038/s41598-019-43793-4 www.nature.com/scientificreports www.nature.com/scientificreports/ Globally, approximately 422 million adults were living with diabetes in 2014, and the age-standardized prevalence has more than doubled since 19801. The majority of the cases of diabetes in adults are of type 2 (T2D), and in addition to increasing rates in adults, T2D accounts for 8–45% of all new cases of diabetes reported among children and adolescents2. The development of T2D is asymptomatic, and disease that already fulfils the diagnostic criteria of T2D often remains subclinical for a long period. Prior to T2D, individuals can reside in the high-risk state of prediabetes, defined as impaired fasting glucose (IFG) or impaired glucose tolerance3. T2D is a complex multi-organ disease with many interrelated dysfunctions. Insulin resistance in the skeletal muscles and in adipose tissue is followed initially by an increase in insulin production in pancreatic β-cells. The failure to respond to the increased insulin demand will eventually lead to progressive β-cell failure, hyperglycemia, and glucose toxicity. The disease is also characterized by the accumulation of fat in the liver, as adipose tissue lipolysis is not sufficiently inhibited by insulin in type 2 diabetes. The pathogenesis of T2D has been shown to be heterogenic, and the progression of the disease, for example, differs according to the age of onset4. The risk of complications also varies according to ethnicity5 as well as the level of control of the glycemic status6. The rise in the prevalence of T2D is tied to the increasing rates of obesity. Positive T2D family history also increases the risk for developing the disease7, even though independent variations in the DNA code have been shown to explain only a small proportion of the heritability of T2D8,9. Recently, it has been hypothesized that the effect could also be conveyed by epigenetic changes and that these changes could be mediated by predisposing individuals to the risk of insulin resistance during gestation, and possibly even by the interand transgenerational transmission of the disorder7. MicroRNAs (miRNAs, miRs) are small non-protein coding RNAs. They are known to regulate gene expression at the post-transcriptional level by binding to target mRNAs and affecting their translation. MicroRNAs can control several genes, and individual mRNAs can be bound by several miRNAs—miRNAs can thus establish wide regulatory networks affecting several metabolic processes. Research on T2D and miRNAs in humans has focused on the identification of possible biomarkers for established T2D. The results have been inconsistent, mainly due to the small populations studied, different starting materials and profiling methods, preselected pools of miRNAs, and the heterogeneity of T2D as a disease10. A meta-analysis by Zhu et al. indicated that miR-29a, -34a, -375, -103, -107, -132, -142-3p, and -144 could be potential circulatory biomarkers (plasma, serum, peripheral blood mononuclear cells, and whole blood as profiling samples) for T2D10, while another meta-analysis reported that levels of miR-320a, -142-3p, -222, -29a, -27a, and -375 increased and levels of miR-197, -20b, -17, and -652 decreased in individuals with T2D11. In contrast to these studies, more long-term solutions for the T2D epidemic could be reached by identifying individuals early in the prediabetic state and by understanding the function of miRNAs in both the normoglycemic (NG) and prediabetic state. However, miRNAs in prediabetes have been studied far less. Villard et al. showed that only circulatory miR-29a, -192, and -126 were consistently dysregulated in individuals with prediabetes11. Although we have seen interesting results—indicating, for example, changes in serum miR-192, -193b12 and -126 in response to glycemic status and intervention—most studies in humans on miRNAs and prediabetes have been small case/control studies (n < 100)12–17 or/and no multiple testing correction has been utilized12–14,18, and/or they were performed with only preselected miRNAs14,17–19. The aims of this study were to (i) analyze the difference in the whole blood miRNA expression in individuals with and without IFG in the large (n = 871; individuals with IFG = 252 and those with T2D = 24) population-based Young Finns Study (YFS) cohort (aged 34–49 years) with individuals currently approaching the age when T2D is most frequently diagnosed; (ii) to study the association of glucose, insulin, and glycated hemoglobin (HbA1c) levels with the HOMA2 insulin resistance (HOMA-IR) index and whole blood miRNA levels; (iii) to look for insight into the cellular origins of the miRNAs of interest by correlating their levels with the blood cell counts; (iv) to investigate whether these miRNAs of interest correlate with their predicted targets and whether the correlated targets are enriched in specific biological pathways; and (v) to see whether the miRNAs of interest together may co-regulate these pathways. Results The levels of five miRNAs are associated with glycemic status. The Kruskal-Wallis test on glycemic status groups (NG, IFG, and T2D) showed a significant association (pc < 0.05) for the levels of hsa-miR-144-5p, -122-5p, -148a-3p, -589-5p, and hsa-let7a-5p. Hsa-miR-144-5p and hsa-let7a-5p were significantly down-regulated in individuals with IFG (vs. NG) (pc < 0.05, FC = 0.91 and FC = 0.93, respectively) (Fig.1A, Table1, Supplementary TableS1). Both of the miRNAs were significant (p < 0.05) statistical predictors of IFG (vs. NG) also in the fully adjusted model 2. Hsa-miR-148a-3p was also down-regulated in individuals with IFG (FC = 0.92) and up-regulated in those with T2D (vs. NG) (FC = 1.12) (Fig.1A), but the significance did not survive multiple testing correction and this miRNA was thus not included in further regression analysis. When comparing T2D individuals with NG individuals, hsa-miR-122-5p and hsa-miR-589-3p were up-regulated (pc < 0.05, FC = 1.53 and FC = 1.29, respectively) (Fig.1B, Table1, Supplementary TableS1). Both of these miRNAs were also up-regulated (p < 0.05 but pc > 0.05) in T2D, in comparison to individuals with IFG (FC = 1.34 and FC = 1.32). Hsa-miR-589-3p was an independent statistical predictor of T2D when compared to NG or IFG individuals in fully adjusted model 2, and hsa-miR-122-5p was an independent statistical predictor of T2D when compared to NG individuals also in the fully adjusted model, but not when compared to individuals with IFG (Fig.1A, Table1, Supplementary TableS1). Twelve miRNAs significantly associate with glucose and HbA1c levels and/or indicators of insulin resistance. In addition to being down-regulated in individuals with prediabetes, hsa-miR-144-5p also correlated inversely (pc < 0.05) with insulin levels and the HOMA2 index. This miRNA also associated with serum glucose levels in the fully adjusted model 2 (p < 0.05), but adding triglycerides to the model predicting 3 Scientific RepoRts | (2019) 9:8887 | https://doi.org/10.1038/s41598-019-43793-4 www.nature.com/scientificreports www.nature.com/scientificreports/ insulin and HOMA2 index levels abolished the association. Further analysis showed that this miRNA correlated even more significantly with serum triglyceride levels (p = 7.3*10−20, r = −0.304). Only one other miRNA (hsa-miR-148a-3p) correlated with serum glucose levels and also associated with serum glucose levels in the fully adjusted model 2 (Table2, Supplementary TableS2). Hsa-miR-122-5p, -184, and -339-3p correlated with insulin levels and HOMA2 index (pc < 0.05). Hsa-miR122-5p, which was also up-regulated in individuals with T2D, is the only miRNA with a direct correlation with these indicators of insulin resistance. Unlike hsa-miR-144-5p, these three miRNAs have an independent association with insulin levels and HOMA2 index in the fully adjusted model (p < 0.05) (Table2, Supplementary TableS2). Hsa-miR-144-5p, -148a-3p, -15b-3p, -93-3p, -146b-5p, -221-3p, -642a-5p, -181a-2-3p, and -18a-3p correlated with either HbA1c and/or HbA1c% (pc < 0.05). Hsa-miR-148a-3p, -15-3p, -93-5p, and -18-3p had an inverse Figure 1. Blood levels of hsa-miR-1445p, -let-7a-5p (A), -122-5p, -589-3p, and -148a-3p (B) in normoglycemic individuals (NG), individuals with impaired fasting glucose (IFG) and individuals with type 2 diabetes (T2D). The trend over groups is analyzed using the Kruskal-Wallis test (dash line) and the differences between groups by the Mann-Whitney U test (solid line). Hsa-miR-144-5p and Let-7a-5p are significantly (Bonferroni corrected p < 0.05) down-regulated in IFG vs. NG (A), while hsa-miR-122-5p and 589-3p were significantly up-regulated in T2D vs. NG (B). 4 Scientific RepoRts | (2019) 9:8887 | https://doi.org/10.1038/s41598-019-43793-4 www.nature.com/scientificreports www.nature.com/scientificreports/ correlation with HbA1c/HbA1c%, while the other miRNAs had a positive correlation with their levels. All except hsa-miR-144-5p associated significantly with the levels of HbA1c/HbA1c% in the fully adjusted model (Table2, Supplementary TableS3). Distinct miRNAs are associated with indicators of glucose levels and insulin resistance in NG and IFG individuals. In NG individuals, significant (pc < 0.05) correlations were seen only between miRNA levels and levels of HbA1c or HbA1c%. Hsa-miR-221-3p and -642a-5p, which were associated with HbA1c and HbA1c% in the whole population, had a positive correlation with these variables, and these miRNAs had an independent association with HbA1c levels and percentages in the fully adjusted model as well. In addition, hsa-miR589-3p, which was up-regulated in individuals with T2D, correlated negatively with HbA1c and HbA1c% and also associated with these values in the fully adjusted model. In individuals with IFG, hsa-miR-589-3p was not associated with HbA1c and HbA1c% levels, and in individuals with T2D (n = 24), the correlation was positive (p = 0.032, r = 0.438 and p = 0.034, r = 0.435 respectively), but this did not survive multiple testing correction (pc > 0.05). Hsa-miR-454-5p had a correlation (pc < 0.05) only with HbA1c%, even though it was associated with both HbA1c and HbA1c% (pc < 0.05) in the fully adjusted model (Table3 and Supplementary TablesS4 and S5). In individuals with IFG, hsa-miR-122-5p and -146b-5p showed association patterns similar to their patterns in the whole population, with hsa-miR-122-5p levels having an independent association with insulin levels and HOMA2 index, while hsa-miR-146b-5p associated with the levels of HbA1c and HbA1c%. Furthermore, hsa-miR-885-5p and -106b-5p correlated positively with serum glucose levels and also had an independent association with glucose levels in the fully adjusted model in individuals with IFG (Table3, Supplementary TablesS4 and S5). Expression patterns and technical validation of data. No clear expression clusters were identified when analyzing the miRNAs of interest. We could see an increased amount of significant positive correlations between miRNAs that associated with insulin levels/HOMA2-IR index and, similarly, between those that associated with HbA1c and HbA1c% levels, but the most significant correlations were the negative associations between hsa-miR-221-3p, and hsa-miR-589-3p and hsa-miR-18a-3p (Supplementary Fig.S3). The functionality of the miRNA profiling arrays has been previously validated in a smaller sample population (n = 72) by correlating the results obtained by this method with those achieved with Human MiRNA Microarray Release 14.0, 8 × 15 K (Agilent). The correlation between the methods was good, and the association between hsa-miR-144-5p and serum glucose levels, for example, was also seen in the results obtained with the Agilent array20. To further validate the results, we detected a similar pattern in the expressions of hsa-miR-144-5p and -let-7a between the glycemic status groups (Supplementary Fig.S1) and even succeeded in replicating the IFG vs. NG T2D vs. NG T2D vs. IFG p-value FC/ OR p-value FC/ OR p-value FC/ OR hsa-miR-144-5p U-test 2.35*10−60.91 0.033 0.90 Model 1 7.42*10−50.71 0.043 0.63 Model 2 3.64*10−40.73 hsa-let-7a-5p U-test 6.39*10−60.93 Model 1 3.00*10−40.74 Model 2 4.50*10−40.73 hsa-miR-122-5p U-test 0.006 1.14 4.80*10−51.53 0.009 1.34 Model 1 0.002 2.68 0.042 1.64 Model 2 0.010 2.48 hsa-miR-589-3p U-test 1.82*10−41.29 6.60*10−51.32 Model 1 2.34*10−42.53 2.27*10−42.51 Model 2 3.70*10−42.80 1.65*10−42.83 Table 1. Significant (pc < 0.05) associations between miRNAs and individuals’ glycemic status (normoglycemic [NG/impaired fasting glucose [IFG]/type 2 diabetes [T2D]). Associations are evaluated with the MannWhitney U test and stepwise logistic regression models. Only p-values smaller than 0.05 are shown here and those with a pc < 0.05 are indicated by bold font. *Multiply sign. Fold changes (FC) describe the magnitude of the difference with the Mann-Whitney U test, while odds ratios (OR) were calculated with regression models. All p-values, numbers of samples, and 95% CIs are shown in Supplementary Table1. Statistical model: U-test = Mann-Whitney U test; Model 1 = stepwise logistic regression model including miRNA of interest (one by one), age, sex, and BMI; Model 2 = Model 1 + leukocyte, erythrocyte, and thrombocyte count, in addition to total cholesterol, LDL, HDL, and triglyceride levels, as well as alcohol consumption, and history of smoking or hypertension. 5 Scientific RepoRts | (2019) 9:8887 | https://doi.org/10.1038/s41598-019-43793-4 www.nature.com/scientificreports www.nature.com/scientificreports/ Glucose Insulin HOMA2-IR HbA1c HbA1c % p-value r/βp-value r/βp-value r/βp-value r/βp-value r/β hsa-miR-144-5p Correlation 7.67*10−7−0.167 1.35*10−8−0.192 1.81*10−8−0.190 8.05*10−5−0.134 5.80*10−5−0.137 Model 1 1.57*10−7−0.163 8.19*10−5−0.113 9.99*10−5−0.111 0.009 −0.086 0.009 −0.084 Model 2 1.22*10−5−0.14 hsa-miR-148a-3p Correlation 1.71*10−4−0.136 0.033 −0.078 0.023 −0.083 1.39*10−5−0.158 9.39*10−6−0.161 Model 1 0.002 −0.103 7.72*10−5−0.135 6.00*10−5−0.137 Model 2 0.015 −0.082 5.05*10−5−0.14 3.74*10−5−0.143 hsa-miR-122-5p Correlation 3.17*10−40.135 1.49*10−11 0.251 7.37*10−12 0.255 3.58*10−40.134 2.23*10−40.139 Model 1 1.52*10−40.119 6.41*10−50.124 0.004 0.105 0.004 0.107 Model 2 2.48*10−40.109 2.09*10−40.110 0.005 0.104 0.005 0.104 hsa-miR-184 Correlation 0.002 −0.108 2.86*10−5−0.145 1.03*10−5−0.153 Model 1 0.001 −0.099 1.76*10−4−0.109 Model 2 0.007 −0.088 0.004 −0.08 0.003 −0.084 hsa-miR-339-3p Correlation 4.44*10−5−0.140 4.66*10−5−0.139 Model 1 0.001 −0.094 0.001 −0.095 Model 2 0.006 −0.077 0.003 −0.083 hsa-miR-15b-3p Correlation 0.006 −0.099 0.008 −0.096 0.001 −0.121 1.27*10−4−0.139 Model 1 0.003 −0.089 0.007 −0.082 1.80*10−4−0.128 5.55*10−5−0.138 Model 2 0.031 −0.075 hsa-miR-93-3p Correlation 0.045 −0.068 3.29*10−6−0.157 5.78*10−6−0.153 Model 1 0.036 −0.060 0.019 −0.066 8.73*10−7−0.157 1.11*10−6−0.155 Model 2 8.21*10−6−0.145 1.06*10−5−0.143 hsa-miR-146b-5p Correlation 0.011 0.086 0.014 0.084 3.32*10−60.157 2.39*10−60.159 Model 1 9.57*10−50.126 9.39*10−50.126 Model 2 8.05*10−50.123 2.58*10−40.122 hsa-miR-221-3p Correlation 0.013 0.085 0.015 0.082 9.62*10−50.132 2.74*10−40.123 Model 1 1.82*10−40.120 0.001 0.109 Model 2 0.006 0.095 0.014 0.085 hsa-miR-642a-5p Correlation 4.51*10−70.170 7.95*10−70.167 Model 1 8.46*10−80.171 1.73*10−70.167 Model 2 8.70*10−80.176 1.54*10−70.173 hsa-miR-181a-2-3p Correlation 2.50*10−50.143 2.92*10−50.142 Model 1 1.62*10−40.121 2.10*10−40.119 Model 2 0.001 0.110 0.001 0.106 hsa-miR-18a-3p Correlation 1.30*10−4−0.130 1.18*10−4−0.131 Model 1 0.001 −0.109 0.001 −0.106 Model 2 0.002 −0.104 0.002 −0.102 Table 2. Significant (pc < 0.05) associations between miRNAs and serum glucose and insulin levels, the HOMA2 insulin resistance index, and glycated hemoglobin (HbA1c) levels and percentage. Associations are evaluated with Spearman’s correlation and stepwise linear regression models. *Multiply sign. Only p-values smaller than 0.05 are shown here, and those with a pc < 0.05 are indicated by bold font. All p-values, numbers of samples, and 95% CIs are shown in Supplementary Tables2 and 3. Statistical model: Correlation = Spearman correlation; Model 1 = Stepwise regression model including miRNA of interest (one by one), age, sex, and BMI; Model = Model 1 + leukocyte, erythrocyte, and thrombocyte count, in addition to total cholesterol, LDL, HDL, and triglyceride levels, as well as glycemic status, alcohol consumption, and history of smoking or hypertension. 6 Scientific RepoRts | (2019) 9:8887 | https://doi.org/10.1038/s41598-019-43793-4 www.nature.com/scientificreports www.nature.com/scientificreports/ nominally significant difference between NG and IFG groups in has-let-7a levels (p = 0.003, FC = 0.97) and the borderline significant result in hsa-miR-144-5p levels (p = 0.061, FC = 0.91) in the same setting. MicroRNAs hsa-miR-146b-5p, -221-3p and -589-3p associated with blood cell counts, while only hsa-miR-122-5p levels are originated solely from serum. To analyze the possibility that the miRNAs that were associated with the individuals’ glycemic status, glucose levels, or indicators of insulin resistance are expressed particularly in certain circulatory blood cells, we correlated the levels of these miRNAs with the leukocyte, erythrocyte, and thrombocyte counts. Out of the 16 miRNAs, hsa-miR-146b-5p and -589-3p correlated significantly with the leukocyte count (p = 1.01*10−4, r = 0.132 and p = 7.20*10−5, r = −0.135), and hsa-miR-589-3p hd an even stronger negative correlation with the erythrocyte count (p = 4.85*10−6, r = −0.155). Also, hsa-miR-106b-5p levels correlated with the leukocyte count in the whole population (p = 2.60*10−5, r = −0.143), but no association was seen in the subpopulation of individuals with IFG, where hsa-miR-106b-5p associated with glucose levels. Only levels of hsa-miR-221-3p correlated significantly with the thrombocyte count (p = 1.58*10−18, r = 0.293). Serum glucose Insulin HOMA2-IR HbA1c HbA1c % p-value r/βp-value r/βp-value r/βp-value r/βp-value r/β In normoglycemic individuals hsa-miR-589-3p Correlation 0.007 −0.117 0.007 −0.117 1.80*10−5−0.185 4.80*10−5−0.175 Model 1 0.045 −0.077 0.049 −0.075 4.61*10−5−0.167 1.37*10−4−0.154 Model 2 1.03*10−4−0.158 2.68*10−4−0.147 hsa-miR-221-3p Correlation 4.50*10−50.176 1.29*10−40.165 Model 1 4.05*10−60.189 7.57*10−60.181 Model 2 7.47*10−50.170 1.15*10−40.163 hsa-miR-642a-5p Correlation 7.80*10−50.170 2.63*10−40.157 Model 1 7.20*10−60.184 1.91*10−50.173 Model 2 2.49*10−60.192 5.58*10−60.183 hsa-miR-454-5p Correlation 2.42*10−4−0.174 1.34*10−4−0.181 Model 1 1.54*10−4−0.170 9.94*10−5−0.171 Model 2 2.23*10−4−0.165 1.40*10−4−0.167 In individuals with IFG hsa-miR-885-5p Correlation 9.00*10−50.244 0.038 0.131 0.029 0.138 Model 1 0.007 0.169 0.010 0.135 0.007 0.142 Model 2 0.008 0.167 0.007 0.141 0.005 0.146 hsa-miR-106b-5p Correlation 9.20*10−50.244 0.048 0.124 0.036 0.132 Model 1 2.82*10−40.223 0.041 −0.127 0.043 −0.125 Model 2 2.09*10−40.230 hsa-miR-122-5p Correlation 8.42*10−70.334 9.31*10−70.333 Model 1 2.81*10−40.206 3.00*10−40.206 Model 2 1.76*10−40.207 2.05*10−40.206 hsa-miR-146b-5p Correlation 4.90*10−50.254 6.30*10−50.250 Model 1 2.56*10−50.260 4.41*10−50.252 Model 2 6.05*10−50.251 5.25*10−50.252 Table 3. Significant (pc < 0.05) associations between miRNAs and serum glucose and insulin levels, the HOMA2 insulin resistance index, and glycated hemoglobin (HbA1c) levels and percentage in normoglycemic individuals and prediabetics separately. Associations are evaluated with Spearman’s correlation and stepwise regression models. *Multiply sign. Only p-values smaller than 0.05 are shown here, and those with a pc < 0.05 are indicated by bold font. All p-values, numbers of samples, and 95%CIs are shown in Supplementary Tables4 and 5. Statistical model: Correlation = Spearman’s correlation; Model 1 = Stepwise regression model including miRNA of interest (one by one), age, sex, and BMI; Model 2 = Model 1 + leukocyte, erythrocyte, and thrombocyte count, in addition to total cholesterol, LDL, HDL, and triglyceride levels, as well as glycemic status, alcohol consumption, and history of smoking or hypertension. 7 Scientific RepoRts | (2019) 9:8887 | https://doi.org/10.1038/s41598-019-43793-4 www.nature.com/scientificreports www.nature.com/scientificreports/ When repeating the non-parametric tests and correlation in the serum samples (n = 146) of YFS, only results regarding hsa-miR-122-5p were replicated, indicating that the levels of this miRNA originate solely from serum. Hsa-miR-184, -589-3p, and 18-a-3p were not sufficiently expressed in serum samples to be included in the analysis, and the rest of the miRNAs of interest did not show an association with glycemic status groups or indicators of glucose metabolism in serum. With hsa-miR-122-5p, the FC between the IFG and NG groups is substantially greater in serum samples (FC = 1.75, p = 0.025) (Supplementary Fig.S2) in comparison to whole blood (FC = 1.14, p = 0.006), indicating that the presence of various other blood components in varying amounts does contribute noise to the measurements. In line with these results, also the correlation coefficients between hsa-miR-122-5p and glucose, insulin, and HOMA2-IR were greater in serum samples (r = 0.353, p = 2.36*10−5; r = 0.412, p = 5.54*10−7 and r = 0.419, p = 3.56*10−7, respectively) in comparison to blood samples (Supplementary TableS8). Targets of hsa-miR-221-3p are enriched in pathways important to the development of T2D, while targets of hsa-miR-146b-5p are enriched in inflammatory pathways. The number of predicted targets with a correlation with a miRNA of interest varied greatly between the miRNAs (Supplementary File II, Correlation Tables1–13). A correlation with a pc < 0.05 were only seen with miRNAs whose levels differed significantly between the glycemic status groups (let-7a-5p and hsa-miR-589-3p) or those with a significant association with HbA1c and HbA1c% (hsa-miR-93-3p, -146b-5p, -148a-3p, -221-3p and -642a-5p). The greatest number of associations were found between hsa-miR-221-3p (111 correlations with pc < 0.05) and hsa-miR146b-5p (42 correlations with pc < 0.05) and their targets. These were also the only miRNAs whose predicted targets were enriched in KEGG pathways (FDR q-value < 0.05) (Table4). The insulin signaling pathway and Type 2 diabetes mellitus pathways were most significantly enriched by the targets of hsa-miR-221-3p and were selected for closer investigation. In addition, we could see enrichment of hsa-miR-146b-3p targets in inflammatory pathways and a pathway related to the cytoskeleton. MicroRNAs that associate with HbA1c levels are associated with the levels of genes in the insulin signaling and T2D pathway. To assess the possible co-regulation of the miRNAs of interest in the insulin signaling pathway and Type 2 diabetes signaling pathway we correlated the genes in these pathways with the miRNAs that were predicted to target them. Our results show that the HbA1c-associated miR-181a-2-3p, -146b5p, -148a-3p, and -221-3p, and hsa-let-7a and miR-589-3p, were also independently and significantly (p < 0.05) associated with mRNA levels of the insulin signaling pathway and type 2 diabetes pathway genes (Fig.2A,B, Supplementary TablesS6 and S7). Most interestingly, hsa-miR-146b-5p correlated highly significantly and negatively with 5′-AMP-activated protein kinase subunit gamma-2 (PRKAG2) mRNA levels, indicating the possible repression of mRNA target. We could also see a similar association between hsa-miR-221-3p and protein phosphatase 1 catalytic subunit beta (PPP1CB) and ribosomal protein S6 kinase B1 (RPS6KB1). Description Genes in pathway Genes in overlap p-value FDR q-value Hsa-miR-221-3p Insulin signaling pathway 137 8 6.60*10−50.006 Type II diabetes mellitus 47 5 9.63*10−50.006 Glycosylphosphatidylinositol(GPI)-anchor biosynthesis 25 4 9.75*10−50.006 Alzheimer’s disease 169 8 2.81*10–4 0.012 Cysteine and methionine metabolism 34 4 3.33*10−40.012 Tight junction 134 7 3.72*10−40.012 Purine metabolism 159 7 0.001 0.027 Spliceosome 128 6 0.002 0.039 Hsa-miR-146b-5p Toll-like receptor signaling pathway 102 6 1.04*10−40.017 Adherens junction 75 5 2.21*10−40.017 Peroxisome 78 5 2.65*10−40.017 Regulation of actin cytoskeleton 216 7 0.001 0.045 Epithelial cell signaling in Helicobacter pylori infection 68 4 0.002 0.045 Pancreatic cancer 70 4 0.002 0.045 Leishmania infection 72 4 0.002 0.045 Lysosome 121 5 0.002 0.045 Endocytosis 183 6 0.002 0.046 Spliceosome 128 5 0.002 0.046 Table 4. Pathways enriched with the predicted targets of the miRNAs of interest. Only targets that were predicted by two algorithms and whose expression levels correlated with miRNA levels (p < 0.05) were included in the enrichment analysis. Significant results (FDR q-value < 0.05) were found only with hsa-miR-221-2p and -146b-5p. Abbreviations: FDR = false discovery rate. *Multiply sign. 8 Scientific RepoRts | (2019) 9:8887 | https://doi.org/10.1038/s41598-019-43793-4 www.nature.com/scientificreports www.nature.com/scientificreports/ Figure 2. Association between miRNAs of interest and their predicted targets in the insulin signaling pathway (A) and Type II diabetes mellitus pathway (B)52. Transcripts whose expression correlated significantly (p < 0.05) with the miRNAs of interest and whose levels were independently and significantly associated with the targeting miRNA in the fully adjusted regression model* are marked with grey boxes. MicroRNAs whose expression correlated positively with glucose/insulin/HbA1c are indicated in red, while those with a negative correlation or down-regulation in individuals with IFG in comparison to NG are indicated in blue. Positive correlation between miRNA and its target mRNA is marked with and negative correlation with . *Statistical model: Stepwise AIC linear regression model including the miRNA of interest, age, sex, BMI, leukocyte count, erythrocyte count, thrombocyte count, glycemic status, glucose insulin, as well as HbA1c levels, HbA1c%, and HOMA2 IR index statistically predicting the mRNA target. 9 Scientific RepoRts | (2019) 9:8887 | https://doi.org/10.1038/s41598-019-43793-4 www.nature.com/scientificreports www.nature.com/scientificreports/ Discussion T2D is a complex and heterogenic multi-organ disease, which is preceded by a state of increased blood glucose and the development of insulin resistance. We show here, in a general-population-based cohort, that IFG changes are associated with the miRNA expression in whole blood and that elevated levels of serum glucose, insulin, and glycated hemoglobin are strongly associated with the miRNA levels. Gene expression data from the same individuals indicates that miRNAs whose expression is associated with HbA1c may also regulate the expression of their targets in the insulin signaling and type 2 diabetes mellitus pathway. In YFS, the blood levels of hsa-miR-144-5p and hsa-let-7a-5p were down-regulated in individuals with prediabetes. We have previously reported a negative correlation between whole blood hsa-miR-144-5p and serum glucose levels in a pilot population of YFS20 and now show herein that this miRNA is associated with (with negative β value) serum glucose, insulin, and HOMA2 index levels in the fully adjusted model. In contrast to our results, miR-144-5p has been previously reported to be up-regulated in the blood and blood fractions of diabetics21–23. In the regulation of glucose homeostasis, hsa-miR-144-5p has been shown to directly target Insulin receptor substrate 1 (IRS1)23 and Glucose transporter GLUT124 and thus regulate glucose metabolism on many levels. In our whole blood samples, we saw a strong association between hsa-miR-144-5p and serum triglyceride levels, possibly indicating that this miRNA may be connected to the development of T2D also through a role in fatty acid homeostasis, but no significant correlation with target mRNAs was observed. Hsa-let-7a-5p has also been associated with T2D. Its levels in exosomes have been shown to be decreased in individuals with T2D, and, interestingly, the levels increased after 12 months of diabetic medication25. In our transcriptomic analysis, hsa-let-7a-5p levels were associated with the levels of its predicted targets in pathways leading to glycolysis and mitochondrial dysfunction. Hsa-miR-122-5p was significantly up-regulated in individuals with T2D, and the levels of this miRNA also correlated positively with insulin levels and the HOMA2-IR index in both the whole population and individuals with IFG. We and others have shown that the circulatory levels of this miRNA are up-regulated in whole blood and the blood fractions when fatty liver develops26,27. As up to 90% of diabetic individuals have some degree of fatty liver, it is reasonable to assume that the increase in this miRNA in our population reflects the development of fatty liver concomitantly with the dysregulation of glucose homeostasis. Although the levels of hsa-miR-122-5p have been measured from the whole blood samples of the larger YFS population, our results from the serum of the subpopulation of YFS participants indicates that the signal mainly comes from the serum. Hsa-miR-885-5p levels were also shown to be up-regulated in individuals with fatty liver in the YFS26, and in the IFG subpopulation we can see that this miRNA also positively correlates with glucose levels, indicating a similar expression pattern to that of hsa-miR-122-5p. Levels of hsa-miR-589-3p, a miRNA up-regulated in the whole blood of individuals with T2D, also correlated negatively with HbA1c levels in NG individuals. In the T2D populations, the correlation was positive, although it was not significant enough to survive the multiple testing correction and no correlation was seen in the IFG population. In our transcriptomics analysis, hsa-miR-589-3p levels correlated positively with transcripts inhibiting glycogenesis in the type 2 diabetes pathway. This may partly explain the complicated expression pattern of hsa-miR-589-3p in our population, as high blood glucose activates glycogenesis in individuals with a functional regulation of glucose levels, while defective glycogenesis is involved in the worsening of glucose level regulation in T2D28. Hsa-miR-184 blood levels correlated negatively with insulin and HOMA2-IR index. This miRNA has been previously shown to be pancreas-enriched, and its expression has been shown to correlate negatively with glucose-stimulated insulin secretion29. It has been shown to regulate insulin secretion in a cell culture model30 and in the compensatory β-cell proliferation and secretion during insulin resistance in mice31. The expression of hsa-miR-184 has been shown to be increased in the pancreatic islets of mice after fasting and to be down-regulated after the administration of a sucrose rich diet in drosophila31. No previous report exists on the correlation between circulatory levels of hsa-miR-184 and serum insulin levels, but our results indicate that the pancreatic down-regulation of this miRNA in the development of peripheral insulin resistance and the requirement of increased levels of insulin can also be seen in whole blood. In addition to hsa-miR-184, hsa-miR-339-3p levels correlated with insulin levels and the HOMA2-IR index. This miRNA has also been associated with the development of pancreatic islets32 and it has been reported to regulate the expression of glucose-6-phospahatse, the enzyme catalyzing the final steps of gluconeogenesis and glycogenolysis33, suggesting potential participation in the development of insulin resistance. A total of eight miRNAs correlated with HbA1c levels/percentages and had an independent association in the fully adjusted model in the whole population. In addition, hsa-miR-454-5p had an association with HbA1c% in the NG subpopulation. Out of the combined nine miRNAs, miR-148a16 and -181a34 have been shown to be up-regulated in plasma and serum miR-15b35 and -18a36 to be down-regulated in T2D, while plasma miR-9315 and -148a16 have been shown to be down-regulated in prediabetics in comparison to healthy controls (Supplementary TableS9). Similar patterns of up-regulation of serum miR-148a and -181a37 and down-regulation of miR-9338 in PBMCs have been reported in type 1 diabetes. The associations between these miRNAs and HbA1c levels/percentages are well in line with their previously reported directions of regulation in T2D and prediabetes. Several of these miRNAs (miR-14839, -9340 and -14641) have been associated with obesity or/and the differentiation or phenotype of the adipocytes. In addition, miR-221 and -146 are known to be associated with inflammation42, and we were able to show that hsa-miR-146b-5p levels correlated with the leucocyte count, indicating that, in our samples, this miRNA may originate from inflammatory cells. In addition, in our data the predicted target mRNAs of hsa-miR-146b-5p were enriched in several inflammatory pathways—for example, the Toll-like receptor signaling pathway. Interestingly, miR-15b has been shown to be down-regulated in the skeletal muscles of twins with T2D in comparison to those without T2D43, to suppress pancreatic β-cell proliferation and insulin secretion, and to possibly convey the effects of intrauterine conditions into later life in mice44.