scholarly journals Nourin-Dependent miR-137 and miR-106b: Novel Biomarkers for Early Diagnosis of Myocardial Ischemia in Coronary Artery Disease Patients

Diagnostics ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 703
Author(s):  
Salwa A. Elgebaly ◽  
Robert H. Christenson ◽  
Hossam Kandil ◽  
Mohsen Ibrahim ◽  
Hussien Rizk ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chest Pain ◽  
Myocardial Ischemia ◽  
Stress Test ◽  
Expression Levels ◽  
Artery Disease ◽  
Pain Patients ◽  
Treadmill Stress Test ◽  
Post Stress ◽  
Gene Expression Levels

Background: Although cardiovascular imaging techniques are widely used to diagnose myocardial ischemia in patients with suspected stable coronary artery disease (CAD), they have limitations related to lack of specificity, sensitivity and “late” diagnosis. Additionally, the absence of a simple laboratory test that can detect myocardial ischemia in CAD patients, has led to many patients being first diagnosed at the time of the development of myocardial infarction. Nourin is an early blood-based biomarker rapidly released within five minutes by “reversible” ischemic myocardium before progressing to necrosis. Recently, we demonstrated that the Nourin-dependent miR-137 (marker of cell damage) and miR-106b-5p (marker of inflammation) can diagnose myocardial ischemia in patients with unstable angina (UA) and also stratify severity of ischemia, with higher expression in acute ST-segment elevation myocardial infarction (STEMI) patients compared to UA patients. Minimal baseline-gene expression levels of Nourin miRNAs were detected in healthy subjects. Objectives: To determine: (1) whether Nourin miRNAs are elevated in chest pain patients with myocardial ischemia suspected of CAD, who also underwent dobutamine stress echocardiography (DSE) or ECG/Treadmill stress test, and (2) whether the elevated levels of serum Nourin miRNAs correlate with results of ECHO/ECG stress test in diagnosing CAD patients. Methods: Serum gene expression levels of miR-137, miR-106b-5p and their corresponding molecular pathway network were measured blindly in 70 enrolled subjects using quantitative real time PCR (qPCR). Blood samples were collected from: (1) patients with chest pain suspected of myocardial ischemia (n = 38) both immediately “pre-stress test” and “post-stress test” 30 min. after test termination; (2) patients with acute STEMI (n = 16) functioned as our positive control; and (3) healthy volunteers (n = 16) who, also, exercised on ECG/Treadmill stress test for Nourin baseline-gene expression levels. Results: (1) strong correlation was observed between Nourin miRNAs serum expression levels and results obtained from ECHO/ECG stress test in diagnosing myocardial ischemia in CAD patients; (2) positive “post-stress test” patients with CAD diagnosis showed upregulation of miR-137 by 572-fold and miR-106b-5p by 122-fold, when compared to negative “post-stress test” patients (p < 0.001); (3) similarly, positive “pre-stress test” CAD patients showed upregulation of miR-137 by 1198-fold and miR-106b-5p by 114-fold, when compared to negative “pre-stress test” patients (p < 0.001); and (4) healthy subjects had minimal baseline-gene expressions of Nourin miRNAs. Conclusions: Nourin-dependent miR-137 and miR-106b-5p are promising novel blood-based biomarkers for early diagnosis of myocardial ischemia in chest pain patients suspected of CAD in outpatient clinics. Early identification of CAD patients, while patients are in the stable state before progressing to infarction, is key to providing crucial diagnostic steps and therapy to limit adverse cardiac events, improve patients’ health outcome and save lives.

scholarly journals A Sparse and Low-Rank Regression Model for Identifying the Relationships Between DNA Methylation and Gene Expression Levels in Gastric Cancer and the Prediction of Prognosis

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 854
Author(s):  
Yishu Wang ◽  
Lingyun Xu ◽  
Dongmei Ai
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Dna Methylation ◽  
Regression Model ◽  
The Cancer Genome Atlas ◽  
Low Rank ◽  
Expression Levels ◽  
Rank Regression ◽  
Prediction Of Prognosis ◽  
Gene Expression Levels

DNA methylation is an important regulator of gene expression that can influence tumor heterogeneity and shows weak and varying expression levels among different genes. Gastric cancer (GC) is a highly heterogeneous cancer of the digestive system with a high mortality rate worldwide. The heterogeneous subtypes of GC lead to different prognoses. In this study, we explored the relationships between DNA methylation and gene expression levels by introducing a sparse low-rank regression model based on a GC dataset with 375 tumor samples and 32 normal samples from The Cancer Genome Atlas database. Differences in the DNA methylation levels and sites were found to be associated with differences in the expressed genes related to GC development. Overall, 29 methylation-driven genes were found to be related to the GC subtypes, and in the prognostic model, we explored five prognoses related to the methylation sites. Finally, based on a low-rank matrix, seven subgroups were identified with different methylation statuses. These specific classifications based on DNA methylation levels may help to account for heterogeneity and aid in personalized treatments.

scholarly journals High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Weitong Cui ◽  
Huaru Xue ◽  
Lei Wei ◽  
Jinghua Jin ◽  
Xuewen Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Small Sample ◽  
Differentially Expressed ◽  
Cancer Type ◽  
Rna Seq ◽  
Sample Sizes ◽  
Large Sample ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract Background RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible. Results Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis. Conclusions High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

scholarly journals Genome-Wide Expression and Alternative Splicing in Domesticated Sunflowers (Helianthus annuus L.) under Flooding Stress

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 92
Author(s):  
Joon Seon Lee ◽  
Lexuan Gao ◽  
Laura Melissa Guzman ◽  
Loren H. Rieseberg
Keyword(s):  
Gene Expression ◽  
Alternative Splicing ◽  
Mixed Model ◽  
Agricultural Land ◽  
Alcohol Fermentation ◽  
Expression Levels ◽  
Flooding Stress ◽  
Genome Wide ◽  
And Control ◽  
Gene Expression Levels

Approximately 10% of agricultural land is subject to periodic flooding, which reduces the growth, survivorship, and yield of most crops, reinforcing the need to understand and enhance flooding resistance in our crops. Here, we generated RNA-Seq data from leaf and root tissue of domesticated sunflower to explore differences in gene expression and alternative splicing (AS) between a resistant and susceptible cultivar under both flooding and control conditions and at three time points. Using a combination of mixed model and gene co-expression analyses, we were able to separate general responses of sunflower to flooding stress from those that contribute to the greater tolerance of the resistant line. Both cultivars responded to flooding stress by upregulating expression levels of known submergence responsive genes, such as alcohol dehydrogenases, and slowing metabolism-related activities. Differential AS reinforced expression differences, with reduced AS frequencies typically observed for genes with upregulated expression. Significant differences were found between the genotypes, including earlier and stronger upregulation of the alcohol fermentation pathway and a more rapid return to pre-flooding gene expression levels in the resistant genotype. Our results show how changes in the timing of gene expression following both the induction of flooding and release from flooding stress contribute to increased flooding tolerance.

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