Coronary heart disease (CHD) is a prevalent global cause of death. Research suggests that circular RNAs (circRNAs) play a role in the development of CHD. In this study, we investigated the expression of hsa_circRNA_0000284 in peripheral blood leukocytes (PBLs) obtained from a cohort of 94 CHD patients aged over 50 years, as well as 126 age-matched healthy controls (HC). An in vitro inflammatory and oxidative injury cell model that simulates CHD was used to evaluate changes in hsa_ circRNA _0000284 under stress. CRISPR/Cas9 technology was used to evaluate changes in hsa_circRNA_0000284 expression. An hsa_ circRNA_0000284 overexpression and silencing cell model was used to analyze the biological functions of hsa_circRNA_0000284. Bioinformatics, qRT-PCR, viral transfection technology, and luciferase assays were used to evaluate the potential hsa_circRNA_0000284/miRNA-338-3p/ETS1 axis. Western blotting analysis was performed to detect protein expression. Herein, PBLs from CHD patients exhibited downregulation of hsa_circRNA_0000284 expression. Exposure to oxidative stress and inflammation can induce damage to human umbilical endothelial cells, resulting in the downregulation of hsa_circRNA_0000284 expression. The expression of hsa_circRNA_0000284 in EA-hy926 cells was significantly reduced after the AluSq2 element of hsa_circRNA_0000284 had been knocked out. The expression of hsa_circRNA_0000284 affected proliferation, cycle distribution, aging, and apoptosis in EA-hy926 cells. Consistent with the results of cell transfection experiments and luciferase assays, Western blotting showed that hsa_circRNA_0000284 plays a role in the regulation of hsa-miRNA-338-3p expression. Subsequently, hsa-miRNA-338-3p was found to be involved in the regulation of ETS1 expression.Communicated by Ramaswamy H. Sarma.

BACKGROUND: CircRNAs are essential for the regulation of post-transcriptional gene expression, including as miRNA sponges, and play an important role in disease development. Some computational tools have been proposed recently to predict circRNA, since only one classifier is used, there is still much that can be done to improve the performance.
RESULTS: StackCirRNAPred was proposed, the computational classification of long circRNA from other lncRNA based on stacking strategy. In order to cope with the potential problem that a single feature might not be able to distinguish circRNA well from other lncRNA, we first extracted features from different sources, including nucleic acid composition, sequence spatial features and physicochemical properties, Alu and tandem repeats. We innovatively apply the stacking strategy to integrate the more advantageous classifiers of RF, LightGBM, XGBoost. This allows the model to incorporate these features more flexibly. StackCirRNAPred was found to be significantly better than other tools, with precision, accuracy, F1, recall and MCC of 0.843, 0.833, 0.831, 0.819 and 0.666 respectively. We tested it directly on the mouse dataset. StackCirRNAPred was still significantly better than other methods, with precision, accuracy, F1, recall and MCC of 0.837, 0.839, 0.839, 0.841, 0.677.
CONCLUSIONS: We proposed StackCirRNAPred based on stacking strategy to distinguish long circRNAs from other lncRNAs. With the test results demonstrating the validity and robustness of StackCirRNAPred, we hope StackCirRNAPred will complement existing circRNA prediction methods and is helpful in down-stream research.

BACKGROUND: Cell-free DNA (cfDNA) primers have been designed to screen for cancer diagnosis, but the results have been inconsistent. The study aimed to compare different primers for diagnosing cfDNA of colorectal cancer (CRC).
METHODS: Peripheral blood specimens were collected from 71 patients with CRC and 20 patients with proliferative intestinal polyps. Quantitative polymerase chain reaction (q-PCR) was used to detect the concentration of cfDNA of these primers, including ALU elements (ALU), Beta-actin (ACTB), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). The receiver operator characteristic curve (ROC) was performed to analyze the diagnostic value.
RESULTS: The concentration of cfDNA in plasma of the CRC group determined by primers ALU and GAPDH was significantly higher than that of the intestinal polyp group (P<0.05). There was no significant difference in cfDNA level determined by primer ACTB between the CRC group and the intestinal polyp group (P>0.05). The area under curves (AUCs) of ALU, GAPDH, and ACTB were 0.734, 0.800, and 0.503, respectively.
CONCLUSIONS: The GAPDH and ALU in plasma are expected to be sensitive indicators for the diagnosis of CRC.

Enhancers modulate gene expression by interacting with promoters. Models of enhancer-promoter interactions (EPIs) in the literature involve the activity of many components, including transcription factors and nucleic acid. However, the role that sequence similarity plays in EPIs remains largely unexplored. Herein, we report that Alu-derived sequences dominate sequence similarity between enhancers and promoters. After rejecting alternative DNA:DNA and DNA:RNA triplex models, we propose that enhancer-associated RNAs (eRNAs) may directly contact their targeted promoters by forming trans-acting R-loops at those Alu sequences. We show how the characteristic distribution of functional genomic data, such as RNA-DNA proximate ligation reads, binding of transcription factors, and RNA-binding proteins, all align with the Alu sequences of EPIs. We also show that these aligned Alu sequences may be subject to the constraint of coevolution, further implying the functional significance of these R-loop hybrids. Finally, our results imply that eRNA and Alu elements associate in a manner previously unrecognized in EPIs and the evolution of gene regulation networks in mammals.

Background: Schizophrenia is a severe mental disorder, which has a major impact on the quality of life and imposes a huge burden on the family. However, the pathogenesis of schizophrenia remains unclear and there are no specific biomarkers. Therefore, we intend to explore whether cf-DNA levels are related to the occurrence and development of schizophrenia. Methods: We analyzed and compared the concentration of cf-DNA in 174 SZ patients and 100 matched healthy controls by using quantitative real-time PCR by amplifying the Alu repeats. Results: We found that cf-DNA levels in peripheral blood reliably distinguished SZ patients from healthy controls (P < 0.05). The ROC analysis also supports the above conclusion. By tracking the absolute concentration of serum cf-DNA in primary cases, we found a distinct increase before treatment with antipsychotics, which decreased progressively after treatment. Conclusions: The present work indicates that cf-DNA may improve the efficiency of disease diagnosis, and the level of cf-DNA plays a predictive role in the development of schizophrenia. By evaluating the level of cf-DNA, we might play a certain role in a more reasonable and standardized clinical treatment of schizophrenia.

Short interspersed nuclear elements (SINEs) are nonautonomous retrotransposons that occupy approximately 13% of the human genome. They are transcribed by RNA polymerase III and can be retrotranscribed and inserted back into the genome with the help of other autonomous retroelements. Because they are preferentially located close to or within gene-rich regions, they can regulate gene expression by various mechanisms that act at both the DNA and the RNA levels. In this review, we summarize recent findings on the involvement of SINEs in different types of gene regulation and discuss the potential regulatory functions of SINEs that are in close proximity to genes, Pol III-transcribed SINE RNAs, and embedded SINE sequences within Pol II-transcribed genes in the human genome. These discoveries illustrate how the human genome has exapted some SINEs into functional regulatory elements.

Psychiatric disorders impose a huge burden on individuals, families, and society. The Alu repeat sequence is a member of the short interspersed nuclear element (SINE) family of mammalian genomes, however, its expression pattern and role in psychiatric disorders is unclear. The current paper aimed at determining the concentrations of Alu in patients with schizophrenia (SZ), major depressive disorder (MDD), and alcohol-induced psychotic disorder (AIPD), and to further define the role and value of Alu as a potential biomarker in psychiatric disorders. In this work, we found that the concentration of Alu was considerably incremented in patients with SZ, and a significant difference existed between patients diagnosed with SZ and MDD or AIPD. ROC analysis also indicated that Alu was effective in the complementary diagnosis of SZ, and differentially diagnosed between SZ patients and patients with MDD or AIPD. In addition, we found a positive relationship between the Alu concentrations and interleukin-1β (IL-1β) in patients with SZ, MDD, and AIPD, and between the concentrations of Alu and interleukin-18 (IL-18) in patients with SZ. Overall, the present work indicates that Alu might be an innovative biomarker for diagnosing psychiatric disorders, and provides the basis for hypotheses about the pathophysiology of psychiatric disorders.

N6-methyladenosine (m6A) and adenosine-to-inosine (A-to-I) editing are two of the most abundant RNA modifications, both at adenosines. Yet, the interaction of these two types of adenosine modifications is largely unknown. Here we show a global A-to-I difference between m6A-positive and m6A-negative RNA populations. Both the presence and extent of A-to-I sites in m6A-negative RNA transcripts suggest a negative correlation between m6A and A-to-I. Suppression of m6A-catalyzing enzymes results in global A-to-I RNA editing changes. Further depletion of m6A modification increases the association of m6A-depleted transcripts with adenosine deaminase acting on RNA (ADAR) enzymes, resulting in upregulated A-to-I editing on the same m6A-depleted transcripts. Collectively, the effect of m6A on A-to-I suggests a previously underappreciated interplay between two distinct and abundant RNA modifications, highlighting a complex epitranscriptomic landscape.

Epigenetic studies have identified DNA methylation in coronary artery disease (CAD). How the critical genes interact at the cellular level to cause CAD is still unknown. The discovery of DNA methylation inspired researchers to explore relationships in genomic coding and disease phenotype. In the past two decades, there have been many findings regarding the relationship between DNA methylation and CAD development, and the DNA methylation of critical genes have been found to be significantly changed during CAD, including DNA methylation at homocysteine, Alu and long Interspersed Element 1 (LINE-1) repetitive elements. Here, we provide a brief overview of the biology and mechanisms of DNA methylation and its roles in CAD. We also discuss recent findings regarding DNA methylation of homocysteine, Alu and LINE-1 and some genes on CAD in vitro and in vivo. Finally, we provide some perspectives on DNA methylation in CAD.

In order to improve prognosis of glioma patients, better tools are required for early diagnosis and treatment. Serum cell-free DNA methylation levels of Alu, MGMT, P16, RASSF1A from 124 glioma patients and 58 healthy controls were detected by the bisulfite sequencing. The median methylation level of Alu was 46.15% (IQR, 36.57%-54.00%) and 60.85% (IQR, 57.23%-65.68%) in glioma patients and healthy controls respectively. The median methylation level of MGMT in glioma samples was 64.65% (IQR, 54.87%-74.37%) compared to 38.30% (IQR, 34.13%-45.45%) in healthy controls, and all revealed significant differences including P16. However, the median methylation level of RASSF1A was not significantly altered in glioma patients. Furthermore, the methylation levels of Alu and MGMT in serum had a good diagnostic value, and was higher than P16. Interestingly, combination of Alu and MGMT identified additional patients, which were missed by either diagnosis alone. In the Alu group, the patients with high levels were associated with an increased survival rate compared to those who with low levels, with similar results observed in the MGMT group. In the present study, we demonstrated that the methylation level of Alu and MGMT in serum had a better diagnostic value than P16. Moreover, combined analysis of Alu and MGMT showed higher sensitivity for glioma diagnosis. Therefore, both serum Alu and MGMT methylation levels may represent a novel prognostic factor for glioma patients.