Prediction of Angiographic Extent of Coronary Artery Disease on the Basis of Clinical Risk Scores in Patients of Unstable Angina

Association of Angio-LncRNAs MIAT rs1061540/MALAT1 rs3200401 Molecular Variants with Gensini Score in Coronary Artery Disease Patients Undergoing Angiography

Long non-coding RNAs (lncRNAs) have emerged as essential biomolecules with variable diagnostic and/or prognostic utility in several diseases, including coronary artery disease (CAD). We aimed for the first time to investigate the potential association of five angiogenesis-related lncRNAs (PUNISHER, SENCR, MIAT, MALAT1, and GATA6-AS) variants with CAD susceptibility and/or severity. TaqMan Real-Time genotyping for PUNISHER rs12318065A/C, SENCR rs12420823C/T, MIAT rs1061540C/T, MALAT1 rs3200401T/C, and GATA6-AS1 rs73390820A/G were run on the extracted genomic DNA from 100 unrelated patients with stable CAD undergoing diagnostic coronary angiography and from 100 controls. After adjusting covariates, the studied variants showed no association with disease susceptibility; however, MIAT*T/T genotype was associated with a more severe Gensini score. In contrast, MALAT1*T/C heterozygosity was associated with a lower score. The lipid profile, and to a lesser extent smoking status, male sex, weight, hypertension, and MALAT1 (T > C) (negative correlation), explained the variance between patients/control groups via a principal component analysis. Incorporating the principal components into a logistic regression model to predict CAD yielded a 0.92 AUC. In conclusion: MIAT rs1061540 and MALAT1 rs3200401 variants were associated with CAD severity and Gensini score in the present sample of the Egyptian population. Further large multi-center and functional analyses are needed to confirm the results and identify the underlying molecular mechanisms.

Evaluation of hs-CRP and sLOX-1 Levels in Moderate-to-High Risk Acute Coronary Syndromes

OBJECTIVE

Risk stratification and prompt treatment are essential for the management of acute coronary syndromes (ACS) and prediction of future prognosis. Subclinical vascular inflammation and novel biomarkers play an important role in the clinical evaluation of ACS patients.

METHODS

We enrolled patients who were admitted to emergency service with unstable angina or non- ST segment elevated ACS (NSTE-ACS) in the study population. Coronary artery disease (CAD) complexity was determined via evaluation of angiographical views and peripheral venous blood samples were collected to measure highly sensitive C-reactive protein (hs-CRP) and soluble form of Lectin-like OxLDL receptor-1 (sLOX-1) levels.

RESULTS

A total of 40 patients were enrolled in the study population, mean age was 65.1±13.8 years and male gender percentage was 52.5%. Twenty-nine of patients had NSTE-ACS and 11 patients had unstable angina presentation. The modified Gensini scores were higher for patients with elevated hs- CRP and sLOX-1 levels.

CONCLUSION

Vascular inflammation displays the onset of ACS and it is related to more complex CAD in these patients. An increase in sLOX-1 expression is closely related to anatomical complexity of CAD in ACS.

Atherosclerotic and thrombotic genetic and environmental determinants in Egyptian coronary artery disease patients: a pilot study

BACKGROUND

Coronary artery disease (CAD) is the leading cause of morbidity and mortality worldwide. Multiple genetic variants in combination with various environmental risk factors have been implicated. This study aimed to investigate the association of twelve thrombotic and atherosclerotic gene variants in combination with other environmental risk factors with CAD risk in a preliminary sample of Egyptian CAD patients.

METHODS

Twenty three consecutive CAD patients undergoing diagnostic coronary angiography and 34 unrelated controls, have been enrolled in the study. Genotyping was based on polymerase chain reaction and reverse multiplex hybridization. Five genetic association models were tested. Data distribution and variance homogeneity have been checked by Shapiro-Wilk test and Levene test, respectively; then the appropriate comparison test was applied. Spearman's rank correlation coefficient was used for correlation analysis and logistic regression has been performed to adjust for significant risk factors. Clustering the study participants according to gene-gene and gene-environment interaction has been done by Detrended Correspondence Analysis (DCA).

RESULTS

The univariate analysis indicated that the five variants; rs1800595 (FVR2; factor 5), rs1801133 (MTHFR; 5,10-methylenetetrahydrofolate reductase), rs5918 (HPA-1; human platelet antigen 1), rs1799752 (ACE; angiotensin-converting enzyme), and rs7412 and rs429358 (ApoE; apolipoprotein E) were significantly associated with CAD susceptibility under different genetic models. Multivariate analysis revealed clustering of the study population into three patient groups (P) and one control group. FVR2 was the most variant associated with CAD patients, combined with the factor V Leiden (FVL) variant in P1 cluster and with both ACE and MTHFR 667C > T in P2. Whereas, P3 was mostly affected by both MTHFR 667C > T and FXIII (factor 13) V89L mutations. When combined with traditional risk factors, P1 was mostly affected by dyslipidemia, smoking and hypertension, while P2 was mostly affected by their fasting blood sugar levels and ApoE variant.

CONCLUSIONS

Taken together, these preliminary results could have predictive value to be applied in refining a risk profile for our CAD patients, in order to implement early preventive interventions including specific antithrombotic therapy. Further large scale and follow-up studies are highly recommended to confirm the study findings.