Identification of a blood-based 12-gene signature that predicts the severity of coronary artery stenosis: An integrative approach based on gene network construction, Support Vector Machine algorithm, and multi-cohort validation

Wang, Xuebin; Cui, Naiqiang; Liu, Xianan; Ming, Liang

doi:10.1016/j.atherosclerosis.2019.10.001

Cited by 7 publications

(5 citation statements)

References 46 publications

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“…Detailed description of clinical variables has been presented in our previous studies [18,27]. Briefly, demographic factors, including age, sex, smoking status (never, former, and current), alcohol drinking status (ever and never), diabetes duration, and type of diabetes management (lifestyle modification, oral agents, insulin, and oral agents plus insulin), were documented by checking participants' medical records and questionnaires.…”

Section: Collection and Definition Of Clinical Variablesmentioning

confidence: 99%

Mitochondrial 8-hydroxy-2′-deoxyguanosine and coronary artery disease in patients with type 2 diabetes mellitus

Wang

Cui

Liu

et al. 2020

Cardiovasc Diabetol

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Background: Little is known about whether mitochondria 8-hydroxy-2′-deoxyguanosine (8-OHdG), a biomarker of mitochondrial DNA (mtDNA) oxidative damage, contributes to the development of coronary artery disease (CAD) in diabetic patients. Here, we explored the associations of mtDNA 8-OHdG in leukocytes with obstructive CAD, coronary stenosis severity, cardiovascular biomarkers, and 1-year adverse outcomes after coronary revascularization in patients with type 2 diabetes mellitus (T2DM). Methods: In a total of 1920 consecutive patients with T2DM who underwent coronary angiography due to symptoms of angina or angina equivalents, the presence of obstructive CAD, the number of diseased vessels with ≥ 50% stenosis, and modified Gensini score were cross-sectionally evaluated; the level of mtDNA 8-OHdG was quantified by quantitative PCR. Then, 701 of 1920 diabetic patients who further received coronary revascularization completed 1-year prospective follow-up to document major adverse cardiovascular and cerebral events (MACCEs). In vitro experiments were also performed to observe the effects of mtDNA oxidative damage in high glucose-cultured human umbilical vein endothelial cells (HUVECs). Results: Cross-sectionally, greater mtDNA 8-OHdG was associated with increased odds of obstructive CAD (odds ratio [OR] 1.38, 95% CI confidence interval 1.24-1.52), higher degree of coronary stenosis (number of diseased vessels: OR 1.29, 95% CI 1.19-1.41; modified Gensini scores: OR 1.28, 95% CI 1.18-1.39), and higher levels of C-reactive protein (β 0.18, 95% CI 0.06-0.31) after adjusting for confounders. Sensitivity analyses using propensity score matching yielded similar results. Stratification by smoking status showed that the association between mtDNA 8-OHdG and obstructive CAD was most evident in current smokers (P interation < 0.01). Prospectively, the adjusted hazards ratio per 1-SD increase in mtDNA 8-OHdG was 1.59 (95% CI 1.33-1.90) for predicting 1-year MACCEs after revascularization. In HUVECs, exposure to antimycin A, an inducer for mtDNA oxidative damage, led to adverse alterations in markers of mitochondrial and endothelia function. Conclusion: Greater mtDNA 8-OHdG in leukocytes may serve as an independent risk factor for CAD in patients with T2DM.

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Section: Collection and Definition Of Clinical Variablesmentioning

confidence: 99%

Mitochondrial 8-hydroxy-2′-deoxyguanosine and coronary artery disease in patients with type 2 diabetes mellitus

Wang

Cui

Liu

et al. 2020

Cardiovasc Diabetol

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“…Indeed, in previous work, we found that plasma levels of acyl carnitines of specific chain lengths may be directly altered by changes in fatty acid quality of the diet [6]. Taken together, these processes may be particularly sensitive to variation in dietary intake; therefore, they could potentially be biomarkers of dietary intake, and also potentially predict future risk [39,40]. However, more prediction research is needed before this can be realized.…”

Section: Dps Associated With Few Gene Expression Clustersmentioning

confidence: 89%

Associations between dietary patterns and gene expression pattern in peripheral blood mononuclear cells: A cross-sectional study

Christensen

Ulven

Thoresen

et al. 2020

Nutrition, Metabolism and Cardiovascular Diseases

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Background and aims: Diet may alter gene expression in immune cells involved in atherosclerotic cardiovascular disease susceptibility. However, we still lack a robust understanding of the association between diet and immune cell-related gene expression in humans. Therefore, we examined associations between dietary patterns (DPs) and gene expression profiles in peripheral blood mononuclear cells (PBMCs) in a population of healthy, Norwegian adults (n Z 130 women and 105 men). Methods and results: We used factor analysis to define a posteriori DPs from food frequency questionnaire-based dietary assessment data. In addition, we derived interpretable features from microarray-based gene expression data (13 967 transcripts) using two algorithms: CIBERSORT for estimation of cell subtype proportions, and weighted gene co-expression network analysis (WGCNA) for cluster discovery. Finally, we associated DPs with either CIBERSORT-predicted PBMC leukocyte distribution or WGCNA gene clusters using linear regression models. We detected three DPs that broadly reflected Western, Vegetarian, and Low carbohydrate diets. CIBERSORT-predicted percentage of monocytes associated negatively with the Vegetarian DP. For women, the Vegetarian DP associated with a large gene cluster consisting of 600 genes mainly involved in regulation of DNA transcription, whereas for men, the Western DP inversely associated with a smaller cluster of 36 genes mainly involved in regulation of metabolic and inflammatory processes. A subsequent proteineprotein interaction network analysis suggested that genes within these clusters might physically interact in biological networks. Conclusions: Although the present findings are exploratory, our analysis pipeline serves as a useful framework for studying the association between diet and gene expression.

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“…However, unlike usual, coronary computed tomographic angiography was taken as a diagnostic reference rather than ICA in James’ study. More recently, some new indicators (such as coronary artery calcium score, gene expression score, and epicardial fat volume) have been proposed to improve CAD predictions ( 12 , 21 , 22 ), but they are not yet broadly applicable, as the key predictors are not routinely available. In addition, the existing coronary-related predictive model shared the limitation that they are not dedicated to identifying SCAS in suspected NSTE-ACS patients with low-to-intermediate risk.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a nomogram for predicting significant coronary artery stenosis in suspected non-ST-segment elevation acute coronary artery syndrome with low-to-intermediate risk stratification

Chen

Huang

et al. 2022

Front. Cardiovasc. Med.

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BackgroundPatients with non-ST-segment coronary artery syndrome (NSTE-ACS) have significant heterogeneity in their coronary arteries. A better assessment of significant coronary artery stenosis (SCAS) in low-to-intermediate risk NSTE-ACS patients would help identify who might benefit from invasive coronary angiography (ICA). Our study aimed to develop a multivariable-based model for pretesting SCAS in suspected NSTE-ACS with low-to-intermediate risk.MethodsThis prediction nomogram was constructed retrospectively in 469 suspected NSTE-ACS patients with low-to-intermediate risk. Patients were divided into a development group (n = 331, patients admitted to hospital before 1 May 2021) and a temporal validation group (n = 138, patients admitted to hospital since 1 May 2021). The outcome was existing SCAS, including left main artery stenosis ≥50% or any subepicardial coronary artery stenosis ≥70%, all confirmed by invasive coronary angiography. Pretest predictors were selected using Least Absolute Shrinkage and Selection Operator (LASSO) and stepwise logistic regression.ResultsDerivation analyses from the development group (n = 331, admitted before 1 May 2021) generated the 7 strongest predictors out of 25 candidate variables comprising smoker, diabetes, heart rate, cardiac troponin T, N-terminal pro-B-type natriuretic peptide, high-density lipoprotein cholesterol, and left atrial diameter. This nomogram model showed excellent discrimination ability with an area under the receiver operating characteristic curve (AUC) of 0.83 in the development set and 0.79 in the validation dataset. Good calibration was generally displayed, although it slightly overestimated patients’ SCAS risk in the validation group. Decision curve analysis demonstrated the clinical benefit of this model, indicating its value in clinical practice. Furthermore, an optimal cut-off of prediction probability was assigned as 0.61 according to the Youden index.ConclusionA prediction nomogram consisting of seven readily available clinical parameters was established to pretest the probability of SCAS in suspected NSTE-ACS patients with low-to-intermediate risk, which may serve as a cost-effective risk stratification tool and thus assist in initial decision making.

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Identification of a blood-based 12-gene signature that predicts the severity of coronary artery stenosis: An integrative approach based on gene network construction, Support Vector Machine algorithm, and multi-cohort validation

Cited by 7 publications

References 46 publications

Mitochondrial 8-hydroxy-2′-deoxyguanosine and coronary artery disease in patients with type 2 diabetes mellitus

Mitochondrial 8-hydroxy-2′-deoxyguanosine and coronary artery disease in patients with type 2 diabetes mellitus

Associations between dietary patterns and gene expression pattern in peripheral blood mononuclear cells: A cross-sectional study

Development and validation of a nomogram for predicting significant coronary artery stenosis in suspected non-ST-segment elevation acute coronary artery syndrome with low-to-intermediate risk stratification

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