ArticleJournal of biochemistry2024
Whole blood transcriptome analysis for age- and gender-specific gene expression profiling in Japanese individuals.
Article in Journal of biochemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- ibSLS as a biobank for democratizing access to multi-omics data and biospecimens from spaceflight research.Nature communications · 2026Article
- Integrated analysis of sex differences in human dendritic cell, monocyte, and natural killer cell subsets.Frontiers in immunology · 2026Article
- Systemic activation of NRF2 contributes to the therapeutic efficacy of clinically-approved KRAS-G12C anti-cancer drugs.British journal of cancer · 2025Article
- Article
- Bulk RNA sequencing for analysis of post COVID-19 condition in adolescents and young adults.Journal of translational medicine · 2024Article
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Authors and funding
15 authors.
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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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