Genome-wide Integration Study of Circulating miRNAs and Peripheral Whole-Blood mRNAs of Male Acute Ischemic Stroke Patients

LDLR and PCSK9 3´UTR variants and their putative effects on microRNA molecular interactions in familial hypercholesterolemia: a computational approach

BACKGROUND

Familial hypercholesterolemia (FH) is caused by pathogenic variants in low-density lipoprotein (LDL) receptor (LDLR) or its associated genes, including apolipoprotein B (APOB), proprotein convertase subtilisin/kexin type 9 (PCSK9), and LDLR adaptor protein 1 (LDLRAP1). However, approximately 40% of the FH patients clinically diagnosed (based on FH phenotypes) may not carry a causal variant in a FH-related gene. Variants located at 3' untranslated region (UTR) of FH-related genes could elucidate mechanisms involved in FH pathogenesis. This study used a computational approach to assess the effects of 3'UTR variants in FH-related genes on miRNAs molecular interactions and to explore the association of these variants with molecular diagnosis of FH.

METHODS AND RESULTS

Exons and regulatory regions of FH-related genes were sequenced in 83 FH patients using an exon-target gene sequencing strategy. In silico prediction tools were used to study the effects of 3´UTR variants on interactions between miRNAs and target mRNAs. Pathogenic variants in FH-related genes (molecular diagnosis) were detected in 44.6% FH patients. Among 59 3'UTR variants identified, LDLR rs5742911 and PCSK9 rs17111557 were associated with molecular diagnosis of FH, whereas LDLR rs7258146 and rs7254521 and LDLRAP1 rs397860393 had an opposite effect (p < 0.05). 3´UTR variants in LDLR (rs5742911, rs7258146, rs7254521) and PCSK9 (rs17111557) disrupt interactions with several miRNAs, and more stable bindings were found with LDLR (miR-4435, miR-509-3 and miR-502) and PCSK9 (miR-4796).

CONCLUSION

LDLR and PCSK9 3´UTR variants disturb miRNA:mRNA interactions that could affect gene expression and are potentially associated with molecular diagnosis of FH.

Knockdown of lncRNA TTTY15 alleviates ischemia/reperfusion-induced inflammation and apoptosis of PC12 cells by targeting miR-766-5p

The pathogenesis of ischemic stroke is extremely complex and has a significant impact on the quality of life of the patients. Accumulating studies have reported that long non-coding RNAs (lncRNAs) may be associated with the progression of ischemic stroke. However, the role and underlying mechanism of action of the lncRNA testis-specific transcript Y-linked 15 (TTTY15) in ischemic stroke remains unknown. The present study analyzed the expression levels of TTTY15 in PC12 cells injured by oxygen-glucose deprivation/reperfusion (OGD/R). The effects of the knockdown of TTTY15 expression on the levels of the inflammatory cytokines TNF-α, IL-1β, IL-18 and IL-10, cell apoptosis and the expression levels of the apoptosis-associated proteins Bcl-2, Bax, cleaved caspase-3, caspase-3, cleaved caspase-9 and caspase-9, were subsequently analyzed in OGD/R-treated PC12 cells using ELISA, flow cytometry and western blotting, respectively. In addition, the downstream target gene of TTTY15 was verified using a dual luciferase reporter assay. The effects of TTTY15 on the inflammation and apoptosis of PC12 cells treated with OGD/R were determined by targeting miR-766-5p. The results of the present study revealed that TTTY15 expression was upregulated in OGD/R-treated PC12 cells. The knockdown of TTTY15 significantly decreased the concentrations of the proinflammatory factors TNF-α, IL-1β and IL-18, while it increased the concentration of the anti-inflammatory cytokine IL-10 in OGD/R-treated PC12 cells. Apoptosis was also suppressed following gene silencing of TTTY15. Subsequently, miR-766-5p was identified as a target gene of TTTY15 using a dual luciferase reporter assay and the expression levels of TTTY15 and miR-766-5p were found to be negatively correlated. The overexpression of miR-766-5p alleviated the stimulatory effect of TTTY15 overexpression on the inflammation and apoptosis of PC12 cells treated with OGD/R. Therefore, the present study revealed that TTTY15 knockdown improved the OGD/R-induced injury of PC12 cells by upregulating miR-766-5p expression.

Alteration of miRNA Biogenesis Regulating Proteins in the Human Microglial Cell Line HMC-3 After Ischemic Stress

MicroRNAs (miRNA) are small noncoding sequences that control apoptosis, proliferation, and neuroinflammatory pathways in microglia cells. The expression of distinct miRNAs is altered after ischemia in the brain. Only minor information is available about the biogenesis and maturation of miRNAs after ischemia. We aimed at examining the impact of oxygen-glucose deprivation (OGD) and hydrogen peroxide (H₂O₂)-induced stress on the expression of miRNA regulating proteins such as DROSHA, DGCR8, XPO5, DICER, TARBP2, and AGO2 in the cultured human microglial cell line HMC-3 (human microglial cell line clone 3). OGD duration of 2.5 h or H₂O₂ stimulation at a concentration of 100 μM for 24 h resulted in a marked increase of the hypoxia sensor hypoxia-inducible factor1-α in HMC-3 cells. These treatments also led to an upregulation of DROSHA, DICER1, and AGO2 detected by semiquantitative real-time PCR (qrtPCR). XPO5 and TARBP2 were only upregulated after stimulation with H₂O₂, while DGCR8 responded only to OGD. We found elevated DICER1, DROSHA, and AGO2 protein levels by western blot and immunohistochemistry staining. Interestingly, the latter also exposed a colocalization of AGO2 with stress granules (G3BP1) after OGD. Our data indicate that DICER, DROSHA, and AGO2 are induced in microglial cells under hypoxia-like conditions. It might be speculated that their inductions might increase the miRNA synthesis rate. Future studies should investigate this correlation to determine which miRNAs are preferably expressed by microglia cells after ischemia and which functions they could exert.

Can miRNAs Be Considered as Diagnostic and Therapeutic Molecules in Ischemic Stroke Pathogenesis?-Current Status

Ischemic stroke is one of the leading causes of death worldwide. Clinical manifestations of stroke are long-lasting and causing economic burden on the patients and society. Current therapeutic modalities to treat ischemic stroke (IS) are unsatisfactory due to the intricate pathophysiology and poor functional recovery of brain cellular compartment. MicroRNAs (miRNA) are endogenously expressed small non-coding RNA molecules, which can act as translation inhibitors and play a pivotal role in the pathophysiology associated with IS. Moreover, miRNAs may be used as potential diagnostic and therapeutic tools in clinical practice; yet, the complete role of miRNAs is enigmatic during IS. In this review, we explored the role of miRNAs in the regulation of stroke risk factors viz., arterial hypertension, metabolic disorders, and atherosclerosis. Furthermore, the role of miRNAs were reviewed during IS pathogenesis accompanied by excitotoxicity, oxidative stress, inflammation, apoptosis, angiogenesis, neurogenesis, and Alzheimer's disease. The functional role of miRNAs is a double-edged sword effect in cerebral ischemia as they could modulate pathological mechanisms associated with risk factors of IS. miRNAs pertaining to IS pathogenesis could be potential biomarkers for stroke; they could help researchers to identify a particular stroke type and enable medical professionals to evaluate the severity of brain injury. Thus, ascertaining the role of miRNAs may be useful in deciphering their diagnostic role consequently it is plausible to envisage a suitable therapeutic modality against IS.

Discovery of stroke-related blood biomarkers from gene expression network models

Background

Identifying molecular biomarkers characteristic of ischemic stroke has the potential to aid in distinguishing stroke cases from stroke mimicking symptoms, as well as advancing the understanding of the physiological changes that underlie the body’s response to stroke. This study uses machine learning-based analysis of gene co-expression to identify transcription patterns characteristic of patients with acute ischemic stroke.

Methods

Mutual information values for the expression levels among 13,243 quantified transcripts were computed for blood samples from 82 stroke patients and 68 controls to construct a co-expression network of genes (separately) for stroke and control samples. Page rank centrality scores were computed for every gene; a gene’s significance in the network was assessed according to the differences in their network’s pagerank centrality between stroke and control expression patterns. A hybrid genetic algorithm – support vector machine learning tool was used to classify samples based on gene centrality in order to identify an optimal set of predictor genes for stroke while minimizing the number of genes in the model.

Results

A predictive model with 89.6% accuracy was identified using 6 network-central and differentially expressed genes (ID3, MBTPS1, NOG, SFXN2, BMX, SLC22A1), characterized by large differences in association network connectivity between stroke and control samples. In contrast, classification models based solely on individual genes identified by significant fold-changes in expression level provided lower predictive accuracies: < 71% for any single gene, and even models with larger (10–25) numbers of gene transcript biomarkers gave lower predictive accuracies (≤ 82%) than the 6 network-based gene signature classification. miRNA:mRNA target prediction computational analysis revealed 8 differentially expressed micro-RNAs (miRNAs) that are significantly associated with at least 2 of the 6 network-central genes.

Conclusions

Network-based models have the potential to identify a more statistically robust pattern of gene expression typical of acute ischemic stroke and to generate hypotheses about possible interactions among functionally relevant genes, leading to the identification of more informative biomarkers.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0566-8) contains supplementary material, which is available to authorized users.