Optimisation of laboratory methods for whole transcriptomic RNA analyses in human left ventricular biopsies and blood samples of clinical relevance

Prospective multiparametric CMR characterization and MicroRNA profiling of anthracycline cardiotoxicity: A pilot translational study

Background

Anthracycline cardiotoxicity is a significant clinical challenge. Biomarkers to improve risk stratification and identify early cardiac injury are required.

Objectives

The purpose of this pilot study was to prospectively characterize anthracycline cardiotoxicity using cardiovascular magnetic resonance (CMR), echocardiography and MicroRNAs (MiRNAs), and identify baseline predictors of LVEF recovery.

Methods

Twenty-four patients (age 56 range 18-75 years; 42 % female) with haematological malignancy scheduled to receive anthracycline chemotherapy (median dose 272 mg/m2 doxorubicin equivalent) were recruited and evaluated at three timepoints (baseline, completion of chemotherapy, and 6 months after completion of chemotherapy) with multiparametric 1.5 T CMR, echocardiography and circulating miRNAs sequencing.

Results

Seventeen complete datasets were obtained. CMR left ventricular ejection fraction (LVEF) fell significantly between baseline and completion of chemotherapy (61 ± 3 vs 53 ± 3 %, p < 0.001), before recovering significantly at 6-month follow-up (55 ± 3 %, p = 0.018). Similar results were observed for 3D echocardiography-derived LVEF and CMR-derived longitudinal, circumferential and radial feature-tracking strain. Patients were divided into tertiles according to LVEF recovery (poor recovery, partial recovery, good recovery). CMR-derived mitral annular plane systolic excursion (MAPSE) was significantly different at baseline in patients exhibiting poor LVEF recovery (11.7 ± 1.5 mm) in comparison to partial recovery (13.7 ± 2.7 mm), and good recovery (15.7 ± 3.1 mm; p = 0.028). Furthermore, baseline miRNA-181-5p and miRNA-221-3p expression were significantly higher in this group. T2 mapping increased significantly on completion of chemotherapy compared to baseline (54.0 ± 4.6 to 57.8 ± 4.9 ms, p = 0.001), but was not predictive of LVEF recovery. No changes to LV mass, extracellular volume fraction, T1 mapping or late gadolinium enhancement were observed.

Conclusions

Baseline CMR-derived MAPSE, circulating miRNA-181-5p, and miRNA-221-3p were associated with poor recovery of LVEF 6 months after completion of anthracycline chemotherapy, suggesting their potential predictive role in this context. T2 mapping increased significantly on completion of chemotherapy but was not predictive of LVEF recovery.

Single-cell RNA sequencing of mouse left ventricle reveals cellular diversity and intercommunication

Previous studies have revealed the diversity of the whole cardiac cellulome but not refined the left ventricle, which was essential for finding therapeutic targets. Here, we characterized single-cell transcriptional profiles of the mouse left ventricular cellular landscape using single-cell RNA sequencing (10× Genomics). Detailed t-distributed stochastic neighbor embedding (tSNE) analysis revealed the cell types of left ventricle with gene markers. Left ventricular cellulome contained cardiomyocytes highly expressed Trdn, endothelial cells highly expressed Pcdh17, fibroblast highly expressed Lama2, and macrophages highly expressed Hpgds, also proved by in situ hybridization. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis (ListHits > 2, P < 0.05) were employed with the DAVID database to investigate subtypes of each cell type with the underlying functions of differentially expressed genes (DEGs). Endothelial cells included 5 subtypes, fibroblasts comprising 7 subtypes, and macrophages contained 11 subtypes. The key representative DEGs (P < 0.001) were Gja4 and Gja5 in cluster 3 of endothelial cells, Aqp2 and Thbs4 in cluster 2 of fibroblasts, and Clec4e and Trem-1 in cluster 3 of macrophages perhaps involved in the occurrence of atherosclerosis, heart failure, and acute myocardial infarction proved by literature review. We also revealed extensive networks of intercellular communication in left ventricle. We suggested possible therapeutic targets for cardiovascular disease and autocrine and paracrine signaling underpins left ventricular homeostasis. This study provided new insights into the structure and function of the mammalian left ventricular cellulome and offers an important resource that will stimulate studies in cardiovascular research.

Chromatin Immunoprecipitation Sequencing (ChIP-seq) Protocol for Small Amounts of Frozen Biobanked Cardiac Tissue

Chromatin immunoprecipitation and sequencing (ChIP-seq) is a well-established method to study the epigenetic profile at the genome-wide scale, including histone modifications and DNA-protein interactions. It provides valuable insights to better understand disease mechanisms. Here we present an optimized ChIP-seq protocol suitable for human cardiac tissues, especially the frozen biobanked small biopsy samples.

Comparison and optimisation of microRNA extraction from the plasma of healthy pregnant women

Circulating microRNA (miRNA) biomarkers are implicated in the diagnosis, monitoring and prediction of various disease processes. Before embarking upon biomarker discovery, miRNA extraction techniques must first be optimised in the biofluid and population under study. Using plasma from a healthy pregnant woman, it was attempted to optimise and compare the performance of two commercially available miRNA extraction kits; Qiagen (miRNeasy Serum/Plasma) and Promega (Maxwell^® RSC miRNA from Tissue or Plasma or Serum). Sample miRNA content (concentration and percentage) was assessed using Agilent Bioanalyzer Small RNA chips and reverse transcription-quantitative PCR (RT-qPCR) using four constitutively expressed miRNAs (hsa-miR-222-3p, hsa-let-7i-3p, hsa-miR-148-3p and hsa-miR-30e-5p). Quality control spike-ins monitored RNA extraction (UniSp2, 4 and 5) and cDNA synthesis (UniSp6, cel-miR-39-3p) efficiency. Optimisation approaches included: i) Starting volume of plasma; the addition of ii) Proteinase K; iii) a RNA bacteriophage carrier (MS2); and iv) a glycogen carrier. The two kits exhibited equivalence in terms of miRNA recovery based on Bioanalyzer and RT-qPCR ΔΔCq results. Optimisation attempts for both kits failed to improve upon miRNA content compared with standard methodology. Comparing the standard methodology, the Qiagen kit was more consistent (smaller variance of ΔCq values) compared with the Promega kit. The standard methodology of either kit would be suitable for the investigation of miRNA biomarkers in a healthy pregnant population.

Dysregulation of Circulating miR-24-3p in Children with Obesity and Its Predictive Value for Metabolic Syndrome

INTRODUCTION

Obesity is a major risk factor for metabolic disorders in children. Therefore, it is particularly important to study the abnormal regulation of circulating miR-24-3p in obese children and its predictive value for metabolic syndrome.

METHODS

Serum samples were obtained from children with obesity (n = 45), obese children with metabolic syndrome (n = 52), and healthy controls (n = 50). The expression levels of miR-24-3p were detected by reverse transcription quantitative PCR. The ROC curve was used to evaluate the diagnostic value of miR-24-3p. Pearson's correlation analysis was performed to evaluate the relationship between serum miR-24-3p and different clinical parameters. Logistic regression analysis was used to evaluate the relationship between miR-24-3p and obesity with metabolic syndrome in children.

RESULTS

The expression of miR-24-3p was the highest in obese children with metabolic syndrome. ROC results showed that miR-24-3p had the ability to distinguish healthy individuals from obese children (area under the curve [AUC] = 0.951) and can predict the occurrence of metabolic syndrome for obese children (AUC = 0.890). The expression level of miR-24-3p was positively correlated with body mass index (r = 0.817, p < 0.001), fasting blood glucose (r = 0.798, p < 0.001), triglycerides (r = 0.773, p < 0.001), systolic blood pressure (r = 0.746, p < 0.001), and diastolic blood pressure (r = 0.623, p < 0.001), respectively. Logistic regression analysis showed that miR-24-3p was an independent influence factor for the occurrence of metabolic syndrome in obese children.

DISCUSSION/CONCLUSION

MiR-24-3p is a potential noninvasive marker for children with obesity and has predictive value for the occurrence of metabolic syndrome.

Comparison of methods for miRNA isolation and quantification from ovine plasma

microRNA (miRNA) are promising candidates for disease biomarkers as they are abundant in circulation, highly stable in biological fluids and may yield diagnostic biomarker signatures. The reported issues with miRNA isolation using traditional RNA reagents necessitates the optimisation of miRNA isolation from challenging samples. In this study we compared six commercial RNA extraction kits to evaluate their ability to isolate miRNA from ovine plasma. We also compared three methods for quantification of small RNA extracted from plasma to determine the most reliable. Using minimal sample inputs of fresh and frozen plasma from five sheep, we compared the six kits (Kit A-F) using quantitative PCR. Operational factors were also assessed for each kit. Kits A and B provided the best detection of the miRNA qPCR reference genes across fresh and frozen samples (p < 0.001) followed by Kit C. The Qubit and microRNA assay provided the least variation (% CV 5.47, SEM ± 0.07), followed by the NanoDrop (% CV 7.01, SEM ± 0.92) and Agilent Bioanalyzer (% CV 59.21, SEM ± 1.31). We identify Kit A to be optimal for isolating miRNA from small volumes of fresh and frozen ovine plasma, and Kit B the top performing kit taking into consideration miRNA detection and operational factors. The Qubit fluorometer using a microRNA assay was the most reliable miRNA quantification method.

Advances in Research on Diabetes by Human Nutriomics

The incidence and prevalence of diabetes mellitus (DM) have increased rapidly worldwide over the last two decades. Because the pathogenic factors of DM are heterogeneous, determining clinically effective treatments for DM patients is difficult. Applying various nutrient analyses has yielded new insight and potential treatments for DM patients. In this review, we summarized the omics analysis methods, including nutrigenomics, nutritional-metabolomics, and foodomics. The list of the new targets of SNPs, genes, proteins, and gut microbiota associated with DM has been obtained by the analysis of nutrigenomics and microbiomics within last few years, which provides a reference for the diagnosis of DM. The use of nutrient metabolomics analysis can obtain new targets of amino acids, lipids, and metal elements, which provides a reference for the treatment of DM. Foodomics analysis can provide targeted dietary strategies for DM patients. This review summarizes the DM-associated molecular biomarkers in current applied omics analyses and may provide guidance for diagnosing and treating DM.