| Literature DB >> 28540143 |
Rehan Malik1, Raja S Mushtaque2, Usman A Siddiqui2, Adnan Younus2, Muhammad A Aziz2, Choudhry Humayun2, Kanaan Mansoor2, Muhammad A Latif3, Salman Waheed4, Salman Assad5, Idrees Khan2, Syed M Bukhari6, Daniel DelCampo2, Ali Adus2, Swetha Gannarapu2.
Abstract
BACKGROUND: Until recently, circulating micro-RNAs (miRNAs) have attracted major interest as novel biomarkers for the early diagnosis of coronary artery disease (CAD). This review article summarizes the available evidence on the correlation of micro-RNAs with both the clinical and subclinical coronary artery disease and highlights the necessity for exploring miRNAs as a potential diagnostic and prognostic biomarker of early CAD in an adult population.Entities:
Keywords: association; coronary artery disease; mirna
Year: 2017 PMID: 28540143 PMCID: PMC5441689 DOI: 10.7759/cureus.1188
Source DB: PubMed Journal: Cureus ISSN: 2168-8184
Figure 1Detailed literature analysis- CAD and miRNA association
Demographics table
A :Age, M: Male, CAD: Coronary Artery Disease, AP: Atherosclerotic Plaque, Pre: Premature, UA: Unstable Angina, HLD: Hyperlipidemia, ACS: Acute Coronary Syndrome, ASCL: Atherosclerosis, VC: Validation Cohort, UAP: Unstable Angina Pectoris, SAP: Stable Angina Pectoris, AO : Arteriosclerosis Obliterans
| Serial# | Author, Year, Study Population | Study Population Characteristics | Country | Type of Study | Outcome |
| 1 |
Diehl, et al.,2011 [ | CAD: A: 76±2; M: 3 (60%) ACS: A: 66±4; M 5 (100%) | China | Case Control | CAD |
| 2 |
Sayed, et al., 2015 [ | CAD: A: 53 (49–57); M: 38 (58.4%) Non-CAD: A: 53 (49–57); M: 16(50%) | China | Case Control | CAD |
| 3 |
Sayed, et al., 2015 [ | CAD: A: 72.97 ± 4.28; M: 18 (67.5%) Non-CAD: A: 71.7 ± 5.2, M: 10(50%) | China | Case Control | CAD |
| 4 |
Zhou, et al., 2015 [ | CAD: A 64.70± 6.79 M: 43 (64.2%) Non-CAD: A: 63.69± 5.96 M: 32 (47.8%) | China | Case Control | CAD |
| 5 |
Liu, et al., 2015 [ | Not Given | China | Case Control | CAD |
| 6 |
Han, et al., 2015 [ | CAD A: 67±11; M: 32 (100%) Non-CAD: A 62±8; M: 20 (100%) | China | Case Control | CAD |
| 7 |
Zhu, et al., 2014 [ | Not Given | China | Case Control | CAD |
| 8 |
Li, et al., 2013 [ | Age/Sex matched in pre CAD and Non CAD. | China | Case Control | CAD |
| 9 |
Ren, et al., 2013 [ | CAD (UA): A: 63±12; M: 25 (55.5%) Non-CAD: 59±6, M: 22 (59.4%) | China | Case Control | CAD |
| 10 |
Guo, et al., 2012 [ | HLD+CAD: A: 65.3 ± 11.0; M: 105 (67.7%) Non-CAD: A 63.0 ± 10.7; M: 35 (70%) | China | Case Control | CAD |
| 11 |
Weber, et al., 2011 [ | Age and sex matched | USA | Case Control | CAD |
| 12 |
Sondermeijer, et al., 2011 [ | Age matched and males only; controls > 20 yr younger, sex unknown | Netherlands | Case Control | CAD |
| 13 |
Fichtlscherer, et al., 2011 [ | Cohort; CAD: A: 67.69 ± 11.07; M: 25 (69.4%) Non-CAD: A: 32.18 ± 8.78Male: 6 (35.3%); VC; CAD: A: 68.06 ± 9.66; M: 21 (68%) Non-CAD: A: 39.28 ± 17.52; M: 5: (36%) | Germany | Case Control | CAD |
| 14 |
Taurino, et al., 2010 [ | CAD: A: 66±11; M: 12 (100%) Non-CAD: A: 597; M: 12 (100%) | UK | Case Control | CAD |
| 15 |
Hoesktra, et al., 2010 [ | Age, sex, ethnically, smoking matched | Norway | Case Control | CAD |
| 16 |
Takahashi, et al., 2010 [ | CAD: A: 66.2±9.5, M: 52 (79%) Non-CAD: A: 64.2±10.3, M: 26 (79%) | Japan | Case Control | CAD |
| 17 |
Li, et al., 2010 [ | Age Matched | China | Case Control | CAD |
| 18 |
Minami, et al., 2009 [ | CAD: A 66.1±12.8; M: 36 (82%). Non-CAD: A: 64.5 ± 8.5, M: 17 (77%) | Japan | Case Control | CAD |
MicroRNA up-regulated studies
QRT-PCR: Quantitative Reverse Transcription Polymerase Chain Reaction, CAD: Coronary Artery Disease, DM: Diabetes Mellitus, HTN: Hypertension, TC: Total Cholesterol, TAG Triacylglycerols, HDL-c: High Density Lipoprotein Cholesterol, LDL-c: Low Density Lipoprotein Cholesterol, AST: Aspartate Aminotransferase, ALT: Alanine Transaminase, LVEF: Left Ventricle Ejection Fraction, CK-MB: Creatine Kinase Myocardial B fraction, LDH: Lactate Dehydrogenase, BMI: Body Mass Index, HLD : Hyperlipidemia, ACS: Acute Coronary Syndrome, KEGG: Kyoto Engenomes, SMCS: Smooth Muscle Cells, HBA1C: Hemoglobin A1C, CRP: C-Reactive Protein, TLR: Toll Like Receptor, AO: Arteriosclerosis Obliterans. EP: Endothetial Progenitor Cells, MP- Microparticles
| Serial # | Name of Author; Year of Study | MicroRNA (miR or miRNA) | MicroRNA: Regulation | MicroRNA Analysis | Source | Strength of Association (Odds ratio, Relative Risk or Regression Analysis) | Comments |
| 1 |
Diehl, et al. 2012 [ | miR 19 miR 21 miR 146 miR 155 miR 223 | Up-regulated: miR 19 miR 21 miR 146 miR 155 miR 223 | QRT-PCR | MP from plasma | ACS vs CAD miR 21 P=0.042 miR 146a P=0.003 | Univariate Analysis |
| 2 |
Sayed, et al., 2015 [ | miR149 miR 424 miR 765 | Up-regulated: miR 765 | QRT-PCR | Serum/ Plasma | Non-CAD vs. CAD (Adjusted) miR 149 95% CI 0.894 to 0.983 p= <0.0001 miR 424 95% CI 0.863 to 0.975 p = <0.0001 miR 765 95% CI 0.939 to 0.996 p=0.0001 | Adjusted for age, gender, TC, TAG, HDL-C, LDL-C, systolic blood pressure, diastolic blood pressure, AST, ALT, creatinine, LVEF, DM, smoking, HTN and medications |
| 3 |
Sayed, et al., 2015 [ | miR 149 miR 765 | Up-regulated: miR 765 | QRT-PCR | Serum/ Plasma | Stable/unstable CAD vs Non-CAD (Adjusted) miR 765 p=< 0.001 | Adjusted for subjects with similar age, gender, total cholesterol, total glyceride, HDL, LDL, systolic blood pressure, diastolic blood pressure, AST, ALT, creatinine, cardiac troponinI, CK-MB, LDH, LVEF, DM, smoking, HTN, and medications |
| 4 |
Zhou, et al., 2015 [ | miR206 miR574/5p | Up-regulated: miR 206 miR 574/5p | QRT-PCR | Plasma | CAD vs Non-CAD (Adjusted) miR 206 –95% CI: (0.508-0.706) miR 574/5p – 95% CI: (0.609- 0.787) | Multivariate analysis (no significant differences between two groups including HTN, DM, smoking history, age, gender, HDL-C, TAG, LDL-C and TC) |
| 5 |
Liu, et al., 2015 [ | miR 2861 miR 3135b miR191/3p miR133a/3p miR1229/5p miR134 miR3679/5p miR223 | Up-regulated: miR 133a/3p miR 134 miR 191/3p miR 223 miR 1229/5p miR 2861 miR 3135b miR 3679/5p | QRT-PCR | Serum/ Plasma | Unadjusted miR 133a/3p 95% CI 0.55-0.82 p = 0.0096 miR 134 95% CI 0.54-0.82 p= 0.015 miR 191/3p 95% CI 0.58-0.83p= 0.0046 miR 223 95% CI 0.47-0.74p= 0.13 miR 1229-5p 95% CI 0.54-0.83 p= 0.015 miR 286195% CI 0.61-0.87 p= <0.001 miR 3135b95% CI 0.61-0.86 p= <0.001 miR 3679/5p95% CI 0.49-0.79 p = 0.06 | Univariate Analysis Matched for sex, DM, and age. A key feature in vasculature calcification is the osteogenic transition of SMCs miR 2861 might function as an enhancer of osteogenic differentiation of SMCs. The increased circulating miR 2861 level may reflect CAC progression. |
| 6 |
Han, et al.,
2015 [ | miR 21a miR 23a miR 34a | Up-regulated: miR 21 miR 23a miR 34a | QRT-PCR | Serum/ Plasma | CAD vs Non-CAD miR-34a, miR-21, and miR-23a that are differentially expressed in CAD plasma p=<0.01 | Univariate Analysis |
| 7 |
Li, et al., 2013 [ | miR 526b | Up-regulated: miR 526b | MiRNA by KEGG | Serum/ Plasma | Pre CAD vs Non-CAD (Adjusted) miR 526b p=0.00072, p=0.003215 | Univariate Analysis |
| 8 |
Ren, et al.,
2013 [ | miR 21 miR 25 miR 92a miR 106b miR 126 miR 451 miR 590/5p | Up-regulated: miR 21 miR 25 miR 92a miR 106b miR 126 miR 451 miR 590/5p | QRT-PCR | Serum/ Plasma | CAD (UA) vs Non-CAD (Adjusted) miR 21OR 2.488 95% CI (1.173, 5.277) p=<0.017 miR 25 OR 2.036 95% CI (1.048, 3.955) p =<0.036 miR 92a OR 2.611 95% CI (1.110, 6.144) p =< 0.028 miR 106b OR 2.389 95% CI (1.158, 4.927) p= <0.018 miR 126 OR 1.882 95% CI (1.140, 3.108) p =<0.013 miR 126 OR 1.882 95% CI (1.140, 3.108) p =<0.013 miR 451 OR 4.609 95% CI (2.171, 9.782) p =<0.001 miR 5905p OR 2.67895% CI (1.226, 5.849) p =<0.013 | Adjusted for age, sex, HTN, dyslipidemia, DM, smoking status, and the use of statins and anti-platelet drugs) |
| 9 |
Guo, et al., 2012 [ | miR 122 miR 370 | Up-regulated: miR 122 miR 370 | QRT-PCR | Serum/ Plasma | HLD+CAD vs Non-CAD miR 122 OR 1.08 95 % CI 1.01–1.16 p = 0.034 miR 370 OR 1.05 95 % CI 1.01–1.12 p = 0.022 | Adjustment for age, gender, BMI, smoking, HTN, DM, and blood lipid profiles |
| 10 |
Sondermeijer, et al.,2011 [ | miR 340 miR 624 | Up-regulated: miR 340 miR 624 | QRT-PCR | Platelets | Pre CAD vs Non-CAD miR-340/ miR624 95% CI: 0.59–0.83, p=<0.002 | Univariate Analysis |
| 11 |
Fichtlscherer, et al., 2010 [ | miR 17 miR 92a miR 126 miR 133a miR 145 miR 155 miR 208a | Up-regulated: miR 133a miR 208a | QRT-PCR | Plasma/ Serum | CAD vs Non-CAD miR133a95% CI (5.22-6.35,3.94-6.10) p=0.16 miR208a 95% CI(5.72-6.74, 4.91-6.61) p=0.29 | Univariate Analysis In patients with stable CAD, vascular-derivedMiRNAs were significantly down-regulated, whereas musclederivedMiRNAs tended to be higher. |
| 12 |
Hokestra, et al., 2010 [ | miR 135 miR 147 | Up-regulated: miR 135 | QRT-PCR | PBMCs | CAD vs Non-CAD miR 135a p=<0.001 | Univariate Analysis |
| 13 |
Takahashi, et al., 2010 [ | miR146a/b | Up-regulated: miR146a/b | QRT-PCR | PMBC | CAD vs Non-CAD miR 146a/b p=<0.01 | Adjusted for age, sex, culprit lesion, fasting glucose, HbA1C, LDL cholesterol, high-sensitive CRP, and history of HTN, DM, and corrected CAD. Marked TLR4 expression in atherosclerotic plaques, oxidative stress upregulates macrophage TLR4 expression, perhaps an association between TLR4, inflammation and coronary atherosclerosis. Activation of TLR4 signal may induce miR-146a/b expression as a negative regulator and induce progression of coronary atherosclerosis. |
| 14 |
Li, et al.,
2010 [ | miR 21 miR 27b miR 130, miR 210 | Up-regulated: miR 21 miR 27b miR 130 miR 210 | QRT-PCR | Vessel Intima and Serum | AO vs Non-AO miR 21/27b/130/210 p=<0.05 | Univariate Analysis |
| 15 |
Minami, et al.,
2009 [ | miR 221 miR 222 | Up-regulated: miR 221 miR 222 | QRT-PCR | EP | Levels of miR 221 and miR 222 were higher in CAD group than in non-CAD group (p<0.01) | Univariate Analysis |
Down-Regulated microRNA studies
Reg: Regulated, QRT-PCR: Quantitative Reverse Transcription Polymerase Chain Reaction, CAD: Coronary Artery Disease, DM: Diabetes Mellitus, HTN: Hypertension, TC: Total Cholesterol, TAG: Triacylglycerols, HDL-c: High Density Lipoprotein Cholesterol, LDL-c: Low Density Lipoprotein Cholesterol, AST: Aspartate Aminotransferase, ALT: Alanine Transaminase, LVEF: Left Ventricle Ejection Fraction, CK-MB: Creatine Kinase for Myocardial B fraction, AP: Atherosclerotic Plaque, PBMC: Peripheral Blood Mononuclear Cells, RF: Risk Factor, CRP: C-Reactive Protein, ACEI: Angiotensin Converting Enzyme Inhibitor
| Name of Author; Year of Study | MicroRNA (miR or miRNA) | MicroRNA: Regulation | MicroRNA Analysis | Source | Strength of Association (Odds ratio, Relative Risk or Regression Analysis) | Comments | |
| 1. |
Sayed, et al., 2015
[ | miR149 miR 424 miR 765 | Down Reg: miR 149 miR 424 | QRT-PCR | Serum/ Plasma | Non-CAD vs. CAD (Adjusted) miR149 95% CI ( 0.894-0.983) p=0.0001 miR 424 95% CI (0.863-0.975) p=0.0001 miR 765 95% CI (0.939-0.996) p=0.0001 | Adjusted for age, gender, TC, TG, HDL-C, LDL-C, systolic blood pressure, diastolic blood pressure, AST, ALT, creatinine, LVEF, DM, smoking, HTN and medications. |
| 2. |
Sayed, et al., 2015
[ | miR149 miR 765 | Down Reg: miR 149 | QRT-PCR | Serum/ Plasma | CAD vs Non CAD (Adjusted) miR 149 p=0.001 | Adjusted for subjects with similar age, gender, total cholesterol, total glyceride, HDL, LDL, systolic blood pressure, diastolic blood pressure, AST, ALT, creatinine, cardiac troponinI, CK-MB, LDH, LVEF, DM, smoking, HTN, and medications. |
| 3. |
Zhu, et al., 2014
[ | miRNA 155 | Down Reg: miR 155 | QRT-PCR | PBMC | Correlation of miR-155 levels in PBMCs to Gensini scores in all patients (n=110). Spearman correlation analysis showed a negative correlation between miR-155 expression and the Gensini score in all patients; r = –0.663, p=0.001. | Adjusted ( miR-155 was correlated to multiple metabolic and CAD RF, including age, HTN, TC, HDL-C, LDL-C, Smoking, ACEI, statins, and CRP, but not sex, hereditary and DM or Impaired Glucose Tolerance. |
| 4. |
Weber, et al., 2011
[ | miR 19a miR 29a miR 30e/5p miR 145 miR 150 miR 155 miR 181d miR 222 miR 342 miR 378 miR 584 | Down Reg : miR 19a miR 29a miR 30e/5p miR 145 miR 150 miR 155 miR 181d miR 222 miR 342 miR 378 miR 584 | QRT-PCR | Whole blood | CAD vs Non-CAD miR 19a p= 0.012 miR 29a p=0.012 miR 30e/5p p= 0.02 miR 145 p= 0.008 miR 150 p= 0.006 miR 155 p= 0.002 miR 222 p= 0.001 miR 342 p=0.001 miR 378 p= 0.001 miR 584 p= 0.036 | Univariate Analysis As whole blood samples were studied, thus miRNA profile likely reflects intracellular and extracellular miRNAs levels, in contrast to exclusively extracellular miRNAs that would be detected in plasma. |
| 5 |
Fichtlscherer, et al., 2010
[ | miR 17 miR 92a miR 126 miR 133a miR 145 miR 155 miR 208a | Down Reg: miR 17 miR 92a miR 126 miR 145 miR 155 | QRT-PCR | Plasma/ Serum | CAD vs Non-CAD miR 17 95% CI(9.06-10.97,5.42-8.29) p=0.001 miR 92a 95% CI (9.48-11.30,7.07-9.75) p= 0.01 miR 126 95% CI (9.86-12.02, 6.21-9.03) p=0.001 miR 145 95% CI (3.87-5.57, 4.81-5.90) p= 0.16 | Univariate Analysis In patients with stable coronary artery disease, vascular-derived miRNAs were significantly down-regulated, whereas muscle derived miRNAs tended to be higher. |
| 6 |
Taurino, et al., 2010
[ | miR140/3p miR182 | Down Reg : miR 140/3p miR 182 miR 92a/b | QRT-PCR | Whole blood | CAD vs Non-CAD miR-140-3p control vs. CAD p=0.002 miR-182 control vs. CAD p= 0.001 miR-92a/b control vs. CAD p=0.01 | Univariate Analysis |
| 7 |
Hoesktra, et al., 2010 [ | miR 135 miR 147 | Down Reg: miR 147 | QRT-PCR | PBMC | CAD vs Non-CAD miR 147 p=<0.01 | Univariate Analysis |