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Updated: Aug 13, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
Identification of LRRK2 gene related to sarcopenia and neuroticism using weighted gene co-expression network analysis
Shu Ran1, Min-Fei Zhao1, Ling-Li Huang1
1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, PR China.
Background:
Sarcopenia is reported to be associated with neuroticism, but the mechanisms are not fully understood. Thus, it's of vital importance to elucidate the molecular mechanism of sarcopenia and neuroticism and to explore the potential molecular target of medical therapies for sarcopenia and neuroticism.
Methods:
The expression datasets (sarcopenia: GSE111006 and neuroticism: GSE60491) were downloaded from the Gene Expression Omnibus. Weighted gene co-expression network analysis (WGCNA) was used to build the gene co-expression network, screen important modules, and filter the hub genes. Genes with significance over 0.2 and a module membership over 0.8 were hub genes. The overlapped hub genes between sarcopenia and neuroticism were defined as key genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed for the genes in modules with clinical interest.
Results:
In this study, we identified 28 gene modules for sarcopenia and 7 for neuroticism by WGCNA. The key modules of sarcopenia and neuroticism were the tan and turquoise modules, respectively. Hub genes of sarcopenia and neuroticism were 20 genes and 107 genes, respectively. The function enrichment found that apoptosis was the common pathway for sarcopenia and neuroticism. Finally, LRRK2 was identified as key genes.
Limitations:
The sarcopenia dataset contained fewer samples.
Conclusion:
Based on WGCNA, our study identified apoptosis pathway and LRRK2 that acted as essential components in the etiology of sarcopenia and neuroticism, which may enhance our fundamental knowledge of the molecular mechanisms underlying the disease.
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