Peripheral Blood miRome Identified miR-155 as Potential Biomarker of MetS and Cardiometabolic Risk in Obese Patients
Abstract
:1. Introduction
2. Subjects and Methods
2.1. Patients and Study Design
2.2. Clinical Laboratory Analyses
2.3. RNA Extraction and Analysis
2.4. miRome Analysis by RNA-Seq
2.5. In Silico Analysis for Selection of miRNAs Target Genes
2.6. Expression of Selected miRNAs by Stem Loop RT-qPCR
2.7. Expression of Target mRNAs by qPCR
2.8. Statistical Analysis
3. Results
3.1. Characteristics of the Study Groups
3.2. miRNome in Peripheral Blood (Screening Study)
3.3. Selected miR:mRNA Interactions Study
3.4. Expression of Selected miRNAs by qPCR (Validation Study)
3.5. Expression of Target Genes in Peripheral Blood
3.6. Influence of MetS Criteria and Insulin Resistance on miRNA and mRNA Expression
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
BMI | Body mass index |
CEBP | CCAAT Enhancer binding protein beta gene |
FDR | False discovery rate |
GLP-1 | Glucagon like peptide 1 |
HbA1c | Glycated hemoglobin |
HDL | High-density lipoprotein |
HOMA-IR | Homeostasis model assessment of insulin resistance |
hsCRP | High-sensitivity C-reactive protein |
IL-1β | Interleukin 1β |
IL-6 | Interleukin 6 |
IL-10 | Interleukin 10 |
IPA | Ingenuity Pathway Analysis |
KRAS | KRAS proto-oncogene, GTPase |
LDL | Low-density lipoprotein |
MetS | Metabolic Syndrome |
miRNAs | microRNAs |
NF-kB | Nuclear factor Kappa B |
PBMC | Peripheral blood mononuclear cells |
RIN | RNA integrity number |
RT-qPCR | Reverse transcription quantitative PCR |
SOCS1 | Suppressor of cytokine signaling 1 |
TNF-α | Tumor necrosis factor alpha |
T2D | Type 2 diabetes |
VLDL | Very low-density lipoprotein |
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Variables | Total Group (n = 80) | MetS (n = 48) | non-MetS (n = 32) | p-Value | |
---|---|---|---|---|---|
Demographic and Clinical Data | Age in years | 48.8 ± 8.2 | 49.7 ± 8.0 | 47.4 ± 8.2 | 0.261 |
Gender [woman], % | 67 (54) | 61 (29) | 78 (25) | 0.095 | |
Hypertension, % | 45 (36) | 54 (26) | 31 (10) | 0.043 | |
Dyslipidemia, % | 71 (57) | 85 (41) | 50 (16) | <0.001 | |
Insulin resistance, % | 75 (60) | 83 (40) | 63 (20) | 0.035 | |
Type 2 diabetes, % | 28 (22) | 33 (16) | 19 (6) | 0.146 | |
Additional MetS criteria #, % | |||||
0 | 19 (15) | 0 (0) | 47 (15) | <0.001 | |
1 | 21 (17) | 0 (0) | 53 (17) | ||
2 | 33 (26) | 54 (26) | 0 (0) | ||
3 | 20 (16) | 33 (16) | 0 (0) | ||
4 | 7 (6) | 13 (6) | 0 (0) | ||
Alcohol consumption, % | 7.5 (6) | 6.2 (3) | 9.4 (3) | 0.603 | |
Tobacco smoking, % | 19 (15) | 21 (10) | 15 (5) | 0.559 | |
Anthropometric Measures | BMI, Kg/m2 | 33.8 ± 4.2 | 35.1 ± 3.2 | 32.1 ± 3.8 | 0.002 |
Waist circumference, cm | 105.1 ± 13.0 | 111.3 ± 10.2 | 95.9 ± 11.2 | <0.001 | |
Waist-hip ratio | 0.90 ± 0.09 | 0.94 ± 0.09 | 0.84 ± 0.07 | <0.001 | |
Fat mass, % | 36.8 ± 6.1 | 37.6 ± 5.6 | 35.7 ± 6.5 | 0.185 | |
Metabolic Profile | Glucose, mg/dL | 105 ± 27 | 112 ± 33 | 95 ± 9 | <0.001 |
Insulin, mU/L | 23.2 ± 22.9 | 27.8 ± 17.7 | 16.6 ± 10.7 | 0.018 | |
HOMA-IR | 6.62 ± 9.22 | 8.5 ± 11.5 | 3.97 ± 2.78 | 0.016 | |
HbA1c, % | 6.22 ± 1.64 | 6.65 ± 1.97 | 5.57 ± 0.47 | 0.001 | |
Total cholesterol, mg/dL | 210 ± 39 | 214 ± 43 | 206 ± 33 | 0.356 | |
LDL cholesterol, mg/dL | 128 ± 32 | 129 ± 35 | 126 ± 27 | 0.710 | |
HDL cholesterol, mg/dL | 51 ± 14 | 49 ± 16 | 56 ± 13 | 0.028 | |
VLDL cholesterol, mg/dL | 30 ± 15 | 34 ± 16 | 23 ± 12 | 0.001 | |
Triglycerides, mg/dL | 149 ± 77 | 172 ± 80 | 116 ± 59 | 0.001 |
miRNA | Fold Change | p-Value | FDR |
---|---|---|---|
let-7a-1 | −2.22433 | 9.00 × 10−6 | 0.000531 |
let-7f-1 | −2.9723 | 0.000123 | 0.004344 |
let-7g | −2.03151 | 0.000827 | 0.020901 |
let-7i | −2.48811 | 7.25 × 10−7 | 0.000128 |
mir-28 | −1.59773 | 0.002377 | 0.04208 |
mir-30d | −1.57958 | 0.001446 | 0.02843 |
mir-155 | −1.96078 | 2.07 × 10−5 | 0.000916 |
mir-181a | −2.08434 | 8.60 × 10−6 | 0.000531 |
mir-363 | −1.6846 | 0.000663 | 0.019573 |
mir-1839 | −1.81056 | 0.001164 | 0.025752 |
Variables | r | p-Value |
---|---|---|
CEBPB mRNA | −0.431 | <0.001 |
HOMA-IR | −0.256 | 0.036 |
Adiponectin | 0.292 | 0.017 |
Fibrinogen | −0.252 | 0.029 |
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Cerda, A.; Amaral, A.A.; de Oliveira, R.; Moraes, T.I.; Braga, A.A.; Graciano-Saldarriaga, M.E.; Fajardo, C.M.; Hirata, T.D.C.; Bonezi, V.; Campos-Salazar, A.B.; et al. Peripheral Blood miRome Identified miR-155 as Potential Biomarker of MetS and Cardiometabolic Risk in Obese Patients. Int. J. Mol. Sci. 2021, 22, 1468. https://doi.org/10.3390/ijms22031468
Cerda A, Amaral AA, de Oliveira R, Moraes TI, Braga AA, Graciano-Saldarriaga ME, Fajardo CM, Hirata TDC, Bonezi V, Campos-Salazar AB, et al. Peripheral Blood miRome Identified miR-155 as Potential Biomarker of MetS and Cardiometabolic Risk in Obese Patients. International Journal of Molecular Sciences. 2021; 22(3):1468. https://doi.org/10.3390/ijms22031468
Chicago/Turabian StyleCerda, Alvaro, Adonai Aralim Amaral, Raquel de Oliveira, Tamiris Invencioni Moraes, Aécio Assunção Braga, Magda Elizabeth Graciano-Saldarriaga, Cristina Moreno Fajardo, Thiago Dominguez Crespo Hirata, Vivian Bonezi, Antony Brayan Campos-Salazar, and et al. 2021. "Peripheral Blood miRome Identified miR-155 as Potential Biomarker of MetS and Cardiometabolic Risk in Obese Patients" International Journal of Molecular Sciences 22, no. 3: 1468. https://doi.org/10.3390/ijms22031468