Frontiers in Genetics (Feb 2020)

Multi-Omics Analysis Reveals MicroRNAs Associated With Cardiometabolic Traits

  • Michelle M. J. Mens,
  • Silvana C. E. Maas,
  • Silvana C. E. Maas,
  • Jaco Klap,
  • Gerrit Jan Weverling,
  • Paul Klatser,
  • Just P. J. Brakenhoff,
  • Joyce B. J. van Meurs,
  • Joyce B. J. van Meurs,
  • André G. Uitterlinden,
  • André G. Uitterlinden,
  • M. Arfan Ikram,
  • Maryam Kavousi,
  • Mohsen Ghanbari

DOI
https://doi.org/10.3389/fgene.2020.00110
Journal volume & issue
Vol. 11

Abstract

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MicroRNAs (miRNAs) are non-coding RNA molecules that regulate gene expression. Extensive research has explored the role of miRNAs in the risk for type 2 diabetes (T2D) and coronary heart disease (CHD) using single-omics data, but much less by leveraging population-based omics data. Here we aimed to conduct a multi-omics analysis to identify miRNAs associated with cardiometabolic risk factors and diseases. First, we used publicly available summary statistics from large-scale genome-wide association studies to find genetic variants in miRNA-related sequences associated with various cardiometabolic traits, including lipid and obesity-related traits, glycemic indices, blood pressure, and disease prevalence of T2D and CHD. Then, we used DNA methylation and miRNA expression data from participants of the Rotterdam Study to further investigate the link between associated miRNAs and cardiometabolic traits. After correcting for multiple testing, 180 genetic variants annotated to 67 independent miRNAs were associated with the studied traits. Alterations in DNA methylation levels of CpG sites annotated to 38 of these miRNAs were associated with the same trait(s). Moreover, we found that plasma expression levels of 8 of the 67 identified miRNAs were also associated with the same trait. Integrating the results of different omics data showed miR-10b-5p, miR-148a-3p, miR-125b-5p, and miR-100-5p to be strongly linked to lipid traits. Collectively, our multi-omics analysis revealed multiple miRNAs that could be considered as potential biomarkers for early diagnosis and progression of cardiometabolic diseases.

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