Jeong · The Journal of frailty & aging 2017 · observational transcriptomic / bioinformatics study · n=?

Determination of the Mechanisms that Cause Sarcopenia through cDNA Microarray.

Cited 5 times in the scientific literature.

Level 4 - case-series / case-control

Cross-sectional transcriptomic and bioinformatics analysis in clinical patient data

PubMed 28555711 · doi:10.14283/jfa.2017.13 · record verified 2026-08-31

What was done

Researchers performed cDNA microarray gene expression profiling combined with protein-protein interaction network prediction in sarcopenia patients aged over 60 years to detect differentially expressed genes and identify potential therapeutic targets.

What was found

The authors identified 673 significantly differentially expressed genes, including 128 upregulated and 545 downregulated genes in sarcopenic patients. Upregulated genes were enriched in metabolic processes such as the PPAR signaling pathway and fatty acid/lipid metabolism (notably FABP4, PLIN1, and ADIPOQ). Downregulated genes included components localized to the mitochondrial matrix. Protein interaction network modeling highlighted two key autophagy-related hubs: MAP1LC3B and HSP90AB1. Exact fold-changes and p-values were not reported in the abstract.

Why it matters

This study points to altered lipid metabolism, mitochondrial dysfunction, and autophagy disruption as major molecular features of age-related sarcopenia, offering potential candidate pathways for therapeutic investigation.

Limits

The abstract does not provide sample size (n), participant demographics, control group specifications, tissue source (e.g., muscle biopsy), or quantitative effect sizes. The findings represent bioinformatic associations without reported experimental or functional validation.

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