Evidence map›Paper›PMID 35383111›Full record

ArticleLife science alliance2022

Intensive single-cell analysis reveals immune-cell diversity among healthy individuals.

Yukie Kashima, Keiya Kaneko, Patrick Reteng, Nina Yoshitake, Lucky Ronald Runtuwene, Satoi Nagasawa, Masaya Onishi, Masahide Seki, Ayako Suzuki, Sumio Sugano and 6 more

Abstract read
In one paragraph

Article in Life science alliance, 2022. 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

16 authors.

Yukie KashimaDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
Keiya KanekoDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
Patrick RetengDivision of Collaboration and Education, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.
Nina YoshitakeDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
Lucky Ronald RuntuweneAIDS Research Center, National Institute of Infectious Disease, Tokyo, Japan.
Satoi NagasawaDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.ORCID 0000-0003-3967-7644
Masaya OnishiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
Masahide SekiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
Ayako SuzukiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
Sumio SuganoInstitute of Kashiwa-no-ha Omics Gate, Kashiwa, Japan.
Mamiko Sakata-YanagimotoDepartment of Hematology, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan.
Yumiko ImaiLaboratory of Regulation for Intractable Infectious Diseases, National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN), Osaka, Japan.
Kaori Nakayama-HosoyaAIDS Research Center, National Institute of Infectious Disease, Tokyo, Japan.
Ai Kawana-TachikawaAIDS Research Center, National Institute of Infectious Disease, Tokyo, Japan.
Taketoshi MizutaniDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
Yutaka SuzukiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan ysuzuki@k.u-tokyo.ac.jp.ORCID 0000-0002-7559-5139

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune responses are different between individuals and personal health histories and unique environmental conditions should collectively determine the present state of immune cells. However, the molecular systems underlying such heterogeneity remain elusive. Here, we conducted a systematic time-lapse single-cell analysis, using 171 single-cell libraries and 30 mass cytometry datasets intensively for seven healthy individuals. We found substantial diversity in immune-cell profiles between different individuals. These patterns showed daily fluctuations even within the same individual. Similar diversities were also observed for the T-cell and B-cell receptor repertoires. Detailed immune-cell profiles at healthy statuses should give essential background information to understand their immune responses, when the individual is exposed to various environmental conditions. To demonstrate this idea, we conducted the similar analysis for the same individuals on the vaccination of influenza and SARS-CoV-2. In fact, we detected distinct responses to vaccines between individuals, although key responses are common. Single-cell immune-cell profile data should make fundamental data resource to understand variable immune responses, which are unique to each individual.

Indexed as

COVID-19Single-Cell AnalysisCOVID-19 VaccinesHumansSARS-CoV-2VaccinationCOVID-19 Vaccines

Identifiers

PMID35383111
PMCPMC8983398

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.