microRNAs associated with
Clinical Traits and Diseases
The association of miRNAs with clinical traits and diseases can be investigated through various approaches. In our population-based studies, we have endeavored to identify miRNAs that are associated with various clinical outcomes by linking plasma circulating miRNAs to the specific trait or disease of interest following various downstream analyses. We have examined the association of miRNA-related single nucleotide polymorphisms (SNPs), including miRNA expression quantitative trait loci (miRNA-eQTLs), SNPs in miRNA-encoding sequences, and SNPs in miRNA-binding sites, with different clinical outcomes. Upon discovering an association between a miRNA and a disease, we have established a pipeline for further confirmation. This includes conducting additional in-silico and in-vitro experiments, identifying potential target genes and pathways, and assessing the biomarker potential of the miRNA within a population-based setting. Our studies have yielded significant findings, revealing numerous miRNAs that are associated with clinical traits and diseases. These findings are compiled and accessible by clicking on the name of the specific trait or disease below.
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We have released the results of our project showing distinct plasma miRNA-aging signatures and four miRNA-based aging biomarkers with the potential to identify accelerated aging and age-related decline. You can access our miRNA expression data on https://ega-archive.org (with the EGA accession number EGAS00001008117). For this please cite our paper: Kuiper L.M, …, Ghanbari M. Plasma microRNA signatures of aging and their links to health outcomes and mortality: findings from a population-based cohort study. Genome Medicine 2025 June 25;17(1):70. doi: 10.1186/s13073-025-01437-5.
Moreover, you can access the results of our analyses linking miRNA-eQTLs to various clinical outcomes in the following paper: Mustafa R., (…), Ghanbari M. A comprehensive study of genetic regulation and disease associations of plasma circulatory microRNAs using population-level data. Genome Biology 2024 Oct 21;25(1):276. doi: 10.1186/s13059-024-03420-6.
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