Differentially Expressed Genes and Biological Pathways in Moyamoya Disease: A Systematic Review and Meta-analysis of

Yunru Chen1, Hao Xing Lai1, Eda Liew1

  • 1Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.

PubMed

Insights

This study analyzed gene expression in Moyamoya disease (MMD) patients, identifying key biological pathways and potential drug targets. Findings may improve risk stratification and treatment for this rare cerebrovascular disorder.

Area of Science:

  • Genomics
  • Molecular Biology
  • Neuroscience

Background:

  • Moyamoya disease (MMD) is a progressive cerebrovascular disorder causing internal carotid artery stenosis, primarily in East Asian populations.
  • Understanding the molecular basis of MMD is crucial for developing effective treatments.

Purpose of the Study:

  • To identify differentially expressed genes (DEGs) and associated biological pathways in MMD by aggregating transcriptomic data from multiple studies.
  • To explore potential therapeutic targets through gene-drug interaction analysis.

Main Methods:

  • Systematic literature search of PubMed and Embase for transcriptomic studies on MMD.
  • Meta-analysis of RNA sequencing data from 177 MMD patients and controls.
  • Pathway enrichment, gene-transcription factor, and gene-drug interaction analyses.

Main Results:

  • Identified 98 upregulated and 37 downregulated DEGs in MMD patients.
  • Upregulated pathways in peripheral blood cells (PBCs) involved mitotic kinetochore assembly and axon injury response.
  • Downregulated pathways in PBCs related to BDNF signaling and extracellular matrix organization; vascular tissues showed similar mitotic pathway upregulation and suppressed proliferation/circulation pathways.
  • MI-773 and MLN 8237 identified as potential therapeutic agents.

Conclusions:

  • Distinct biological pathways are dysregulated in MMD patients' peripheral blood and vascular tissues.
  • Findings provide potential biomarkers for MMD risk stratification and novel therapeutic targets for improved disease management.

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