miRNA profile in HeFH and non-FH patients treated with PCSK9 inhibitor
Description
Our study aimed to characterize changes in the circulating miRNome during one year of treatment with the monoclonal antibodies alirocumab or evolocumab and to compare these changes between HeFH patients and non-FH patients. We hypothesized that PCSK9i therapy would induce distinct alterations in circulating miRNA profiles reflecting differences in lipid metabolism, inflammatory signaling, and cardiovascular risk-related pathways between HeFH and non-FH patients.
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Steps to reproduce
Total RNA was extracted from plasma and cDNA Libraries were prepared including the ligation of adapters containing unique molecular identifiers. Based on the quality of the inserts and the concentration measurements, the libraries of 75 samples (baseline = 23; 3rd month = 21; 6th month = 13; 12th month = 18) were pooled in equimolar ratios. The library pools were then sequenced using NextSeq500 Illumina and standard settings: 10 million reads/per sample, read length: 75 bp single-end. Raw data were de-multiplexed, and FASTQ files were generated using the bcl2fastq software. Validation of miRNA profile was performed using SYBR green-based real-time quantitative PCR. Spike-in controls were included in each analysis to ensure the quality of RNA isolation, and cDNA synthesis. Inter-plate calibrators were used for calibration between PCR plate runs. In total 23 of candidate miRNAs were measured. As endogenous miRNA controls, miR-103-3p, miR-191-5p, and let-7a-5p were selected. MiR-3184-5p with more than 40% missing values across samples was excluded from the analysis. Ct values greater than 35, which indicate low miRNA plasma concentrations, were replaced with the value 35. MiRNAs expression values are presented in log2(FoldChange). Reads normalization and identification of differentially expressed miRNAs, was conducted using DESeq2 with Benjamini and Hochberg correction for multiple testing and 0.05 significance level. To evaluate the effects of FH status and PCSK9i treatment, both multivariate and univariate approaches were applied. To formally assess group-level differences in overall miRNA expression profiles, PERMANOVA was applied, accounting for the multivariate structure of the data. For univariate analysis linear mixed-effects models were fitted separately for each miRNA using the nlme package (v3.1-164), with patient ID as a random effect to account for repeated measures. Estimated marginal means and pairwise contrasts were computed using the emmeans package (v1.10.4), and Benjamini–Hochberg correction was applied to adjust p-values for multiple testing. A padj value <0.05 was considered statistically significant.
Institutions
- Institute of Clinical and Experimental MedicinePrague, Prague