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Whole blood transcriptome analysis for age- and gender-specific gene expression profiling in Japanese individuals. | LitMetric

AI Article Synopsis

  • Whole blood transcriptome analysis offers valuable insights for medical research, primarily due to easy sample collection and the detailed information it provides about gene expression influenced by factors like age and gender.
  • A study was conducted on 576 participants from the Tohoku Medical Megabank, stratifying by age (20-30s and 60-70s) and gender, including pregnant women, to analyze RNA sequencing data and investigate gene expression differences.
  • Findings revealed associations between gene expression and age/gender differences, as well as the impact of immune response status (neutrophil-to-lymphocyte ratio) on gene diversity, resulting in a significant data set for future research in the Japanese population.

Article Abstract

Whole blood transcriptome analysis is a valuable approachin medical research, primarily due to the ease of sample collection and the richness of the information obtained. Since the expression profile of individual genes in the analysis is influenced by medical traits and demographic attributes such as age and gender, there has been a growing demand for a comprehensive database for blood transcriptome analysis. Here, we performed whole blood RNA sequencing (RNA-seq) analysis on 576 participants stratified by age (20-30s and 60-70s) and gender from cohorts of the Tohoku Medical Megabank (TMM). A part of female segment included pregnant women. We did not exclude the globin gene family in our RNA-seq study, which enabled us to identify instances of hereditary persistence of fetal hemoglobin based on the HBG1 and HBG2 expression information. Comparing stratified populations allowed us to identify groups of genes associated with age-related changes and gender differences. We also found that the immune response status, particularly measured by neutrophil-to-lymphocyte ratio (NLR), strongly influences the diversity of individual gene expression profiles in whole blood transcriptome analysis. This stratification has resulted in a data set that will be highly beneficial for future whole blood transcriptome analysis in the Japanese population.

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Source
http://dx.doi.org/10.1093/jb/mvae008DOI Listing

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