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Progeria and Aging-Omics Based Comparative Analysis.

Aylin Caliskan1, Samantha A W Crouch1, Sara Giddins1

  • 1Department of Bioinformatics, Biocenter, University of Würzburg, 97074 Würzburg, Germany.

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|October 27, 2022
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Summary
This summary is machine-generated.

Researchers analyzed gene expression data to identify common markers in natural aging and Hutchinson-Gilford progeria syndrome. This study highlights potential therapeutic targets by examining differentially expressed genes and their pathways.

Keywords:
ACKR4HGPSIGFBP2RNA sequencingWNTagingbioinformaticsomicsprogeriasun exposure

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Area of Science:

  • Genomics and Bioinformatics
  • Molecular Biology
  • Aging Research

Background:

  • Aging is a complex process with ancient roots, often viewed as a disease state.
  • Understanding the genetic underpinnings of aging and premature aging syndromes like Hutchinson-Gilford progeria syndrome (HGPS) is crucial for identifying disease markers and therapeutic targets.
  • Omics technologies, particularly RNA-Seq, offer powerful tools for dissecting the molecular mechanisms of aging.

Purpose of the Study:

  • To perform an in silico analysis of differentially expressed genes (DEGs) in progeria and normal aging using a public RNA-Seq dataset.
  • To identify genes and pathways common to both natural aging and progeria.
  • To predict microRNAs (miRNAs) and interactomes for key identified genes and validate findings with proteomic data.

Main Methods:

  • Utilized bioinformatics tools for in silico analysis of RNA-Seq data (GEO dataset GSE113957).
  • Conducted comparative analysis of gene expression between healthy children, nonagenarians, and HGPS patients.
  • Predicted miRNA targets and protein-protein interactions for selected genes (WNT16, UCP2, IGFBP2).
  • Performed comparative proteomic analysis to correlate with RNA-Seq findings.

Main Results:

  • Identified several genes (KRT8, KRT18, ACKR4, CCL2, UCP2, ADAMTS15, ACTN4P1, WNT16, IGFBP2) involved in both natural aging and progeria.
  • Reported IGFBP2 as a gene potentially involved in progeria for the first time.
  • Predicted specific miRNAs (e.g., hsa-mir-181a-5p, hsa-mir-26a-5p, hsa-mir-124-3p) interacting with WNT16, UCP2, and IGFBP2.
  • Demonstrated concordance between RNA-Seq data and proteomic analyses.

Conclusions:

  • The identified genes and pathways represent potential novel biomarkers and therapeutic targets for aging and progeria.
  • Further in vitro and in vivo research is warranted to elucidate the functional roles of these genes in aging processes.
  • The study showcases the utility of public RNA-Seq datasets and bioinformatics tools for aging research.