PLX003723

GSE129534: Frailty in middle age is associated with race-specific changes to the transcriptome.

  • Organsim human
  • Type RNASEQ
  • Target gene
  • Project ARCHS4

Frailty is an aging-associated syndrome resulting from diminished capacity to respond to stressors, disrupted homeostasis. It is a significant risk factor for disability and mortality. Although frailty is usually studied in old age, it is present in mid-life. Given the increases in mortality statistics among middle-aged Americans, understanding molecular drivers of frailty in a younger, diverse cohort may facilitate identifying pathways for early intervention. We analyzed frailty-associated, genome-wide transcriptional changes in middle-aged African Americans (AAs) and whites. Next generation RNA sequencing was completed using total RNA from peripheral blood mononuclear cells. We analyzed differential gene expression patterns and completed a parametric analysis of gene set enrichment (PAGE). Differential gene expression was validated using RT-qPCR. We identified 5,082 genes differentially expressed with frailty. Frailty altered gene expression patterns and biological pathways differently in AAs and whites, including inflammatory and immune response pathways. The validation study showed a significant two-way interaction between frailty, race, and expression of the cytokine IL1B and the transcription factor EGR1. The glucose transporter, SLC2A6, the neutrophil receptor, FCGR3B, and the accessory protein, C17orf56, were decreased with frailty. These results suggest that there may be demographic dependent, divergent biological pathways underlying frailty diagnosis in middle-aged adults. SOURCE: Supriyo DeComputational Biology Core NIA-IRP, NIH

View on GEOView in Pluto

Key Features

Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.

Learn More

14K+ Published Experiments

Access an extensive range of curated bioinformatics data sets, including genomic, transcriptomic, and proteomic data.

Easy Data Import

Request imports from GEO or TCGA directly within Pluto Bio. Seamlessly integrate external data sets into your workflow.

Advanced Search Capabilities

Utilize powerful search tools to quickly find the data sets relevant to your research. Filter by type, disease, gene, and more.

Analyze and visualize data for this experiment

Use Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.

Read about post-pipeline analysis

View QC data and experiment metadata

View quality control data and experiment metadata for this experiment.

Request import of other GEO data

Request imports from GEO or TCGA directly within Pluto Bio.

Chat with our Scientific Insights team