Evidence map›Paper›PMID 38268329›Full record

ArticleJournal of biochemistry2024

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

Yu-Ichi Aoki, Keiko Taguchi, Hayato Anzawa, Junko Kawashima, Noriko Ishida, Akihito Otsuki, Atsushi Hasegawa, Liam Baird, Takafumi Suzuki, Ikuko N Motoike and 5 more

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Yu-Ichi AokiTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Keiko TaguchiTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.ORCID 0000-0002-5798-0076
Hayato AnzawaTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.ORCID 0000-0002-9446-1291
Junko KawashimaTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Noriko IshidaTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Akihito OtsukiTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Atsushi HasegawaTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Liam BairdTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Takafumi SuzukiTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Ikuko N MotoikeTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Kinuko OhnedaTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Kazuki KumadaTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Fumiki KatsuokaTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Kengo KinoshitaTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.
Masayuki YamamotoTohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.

Funding

Japan Agency for Medical Research and Development JP21tm0424601
6 · The paper itself

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.

Indexed as

Gene Expression ProfilingTranscriptomeAdultAgedAge FactorsEast Asian PeopleFemaleHumansJapanJapanese peopleMaleMiddle AgedSex FactorsYoung Adultage and gender differenceglobinHPFHRNA-seqwhole blood transcriptome

Identifiers

PMID38268329
PMCPMC11756699

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.