Evidence map›Paper›PMID 33230199›Full record

ArticleJournal of human genetics2021

Genome-wide association study of individual differences of human lymphocyte profiles using large-scale cytometry data.

Daigo Okada, Naotoshi Nakamura, Kazuya Setoh, Takahisa Kawaguchi, Koichiro Higasa, Yasuharu Tabara, Fumihiko Matsuda, Ryo Yamada

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Journal of human genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 30% of its field
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

6 citing papers in PubMed, 26 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Daigo OkadaDepartment of Statistical Genetics, Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Naotoshi NakamuraDepartment of Statistical Genetics, Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Kazuya SetohDepartment of Human Disease Genomics, Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Takahisa KawaguchiDepartment of Human Disease Genomics, Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Koichiro HigasaDepartment of Human Disease Genomics, Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Yasuharu TabaraDepartment of Human Disease Genomics, Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Fumihiko MatsudaDepartment of Human Disease Genomics, Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Ryo YamadaDepartment of Statistical Genetics, Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan. ryamada@genome.med.kyoto-u.ac.jp.
Kyoto University · JPKansai Medical University · JP

Funding

MEXT | Japan Science and Technology Agency (JST) AIP ChallengeMEXT | Japan Society for the Promotion of Science (JSPS) JP19J14816MEXT | JST | Core Research for Evolutional Science and Technology (CREST) JPMJCR1502MEXT | JST | Core Research for Evolutional Science and Technology (CREST) JPMJCR15G1
6 · The paper itself

Abstract

Human immune systems are very complex, and the basis for individual differences in immune phenotypes is largely unclear. One reason is that the phenotype of the immune system is so complex that it is very difficult to describe its features and quantify differences between samples. To identify the genetic factors that cause individual differences in whole lymphocyte profiles and their changes after vaccination without having to rely on biological assumptions, we performed a genome-wide association study (GWAS), using cytometry data. Here, we applied computational analysis to the cytometry data of 301 people before receiving an influenza vaccine, and 1, 7, and 90 days after the vaccination to extract the feature statistics of the lymphocyte profiles in a nonparametric and data-driven manner. We analyzed two types of cytometry data: measurements of six markers for B cell classification and seven markers for T cell classification. The coordinate values calculated by this method can be treated as feature statistics of the lymphocyte profile. Next, we examined the genetic basis of individual differences in human immune phenotypes with a GWAS for the feature statistics, and we newly identified seven significant and 36 suggestive single-nucleotide polymorphisms associated with the individual differences in lymphocyte profiles and their change after vaccination. This study provides a new workflow for performing combined analyses of cytometry data and other types of genomics data.

Indexed as

Genome-Wide Association StudyB-LymphocytesData MiningFemaleFlow CytometryHumansImmune SystemInfluenza, HumanInfluenza VaccinesLymphocytesMalePolymorphism, Single NucleotideT-LymphocytesVaccinationInfluenza Vaccines

Identifiers

PMID33230199
PMCPMC8144016
OpenAlexW3108982394

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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.