High-Throughput RNA Sequencing Analysis of Plasma Samples Reveals Circulating microRNA Signatures with Biomarker Potential in Dengue Disease Progression

Abstract

The circulating microRNA (miRNA) profile has been widely used for identifying potential biomarkers against viral infections. However, data on circulating microRNA expression patterns in dengue patients are scanty. Considering the impact of severity caused by dengue infection, circulating miRNA profiles in plasma of dengue patients may prove to be valuable for developing early prognostic markers for the disease severity. Here, we described an in-depth analytical study of small RNA sequencing data obtained from the plasma of 39 dengue patients. Integrating bioinformatics and in vitro studies, we identified differentially expressed miRNAs (DEMs) (log2 fold change ≥1.5, P < 0.05) associated with dengue disease progression. In comparing miRNA expression pattern with the follow-up samples, nine miRNAs were found to exhibit an altered expression that could distinguish between severe dengue and the convalescent patients. To understand the abundance and specificity of the DEMs in the context of dengue infection and disease progression, eight top-hit DEMs were further validated in the dengue virus-infected cell lines as well as in the patient’s plasma and peripheral blood mononuclear cells (PBMCs) using the quantitative reverse transcription-PCR (qRT‐PCR) method. Importantly, receiver operating curve analysis further confirmed that the plasma expression pattern of hsa-miR-122-5p could differentiate between different stages of dengue infection (area under the concentration-time curve [AUC] = 0.792), and dengue-negative patients with other febrile illnesses (AUC = 0.984). The in silico analysis of DEM target genes suggested an enrichment of the pathways associated with metabolism and inflammation. Our study gives a global view of miRNA expression in the plasma from dengue patients and provides a precious resource of candidate miRNAs involved in dengue infection and disease progression. IMPORTANCE Dengue virus (DENV) infection usually causes dengue fever (DF) with flu-like illness affecting infants, young children, and adults. The DF occasionally evolves into a potentially lethal complication called dengue severe (DS) leading to a rapid fall in platelet count along with plasma leakage, fluid accumulation, respiratory distress, and severe bleeding. The diverse clinical spectrum of dengue disease, as well as its significant similarity to other febrile viral illnesses, makes early identification more challenging in this high-risk group. microRNAs (miRNAs) are small (∼19 to 21 nucleotides [nt] in length), noncoding RNAs, extremely stable and easily detectable in the plasma; thus, they have potential as biomarkers for diagnosing and monitoring human diseases. This study provides a comprehensive analysis of miRNAs circulating in plasma of dengue virus-infected patients and identifies the miRNA signatures that have biomarker potential for dengue infection and disease progression.

Circulating microRNA sequencing revealed miRNome patterns in hematology and oncology patients aiding the prognosis of invasive aspergillosis

“…An essential component of reliable quantitative reverse transcription PCR (qRT-PCR) analyses is the normalization of gene expression data because it controls for variations and allows comparisons of gene expression levels among different samples. An ideal reference gene must be stably expressed, abundant and without any significant variation in its expression status 20 . Due to high heterogeneity, there is no consensus for the best reference gene to be used to normalize miRNA gene expression data in HO patients.…”

Regulation of Host Innate Immunity by Non-Coding RNAs During Dengue Virus Infection

“…The study could successfully correlate the dysregulation of several miRNAs among mild and severe dengue patients. (Saini et al, 2020). Specifically, the expression profile of hsa-miR-122-5p in plasma specimens was found to be an important differentiator of dengue infection stage.…”

Establishment of a molecular risk model for the prognosis of cervical cancer based on microRNA expression

“…Leveraging the 'edge' R package in R software, we screened the differential expression of miRNAs in 12 miRNA-seq and TCGA database tissues. The screening criterion was log2(fold change) >1.5, and the cut-off for the false discovery rate (FDR) =0.05, there was statistical significance when P<0.05, in order to select the more significant differential miRNAs we referred to the literatures (13)(14)(15) and found that the difference was more significant when log2>1.5. With the help of the 'ggplot2' package in R software, two volcano maps of differentially-expressed miRNAs in the 12 miRNAseq and TCGA database tissues were drawn.…”