Evidence map›Paper›PMID 27851916›Full record

ArticleImmunity2016

Systematic Analysis of Cell-to-Cell Expression Variation of T Lymphocytes in a Human Cohort Identifies Aging and Genetic Associations.

Yong Lu, Angelique Biancotto, Foo Cheung, Elaine Remmers, Naisha Shah, J Philip McCoy, John S Tsang

Abstract read
In one paragraph

Article in Immunity, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
  2. Article
  3. bioRxiv : the preprint server for biology · 2025
    Article
  4. Article
  5. Article
  6. Anti-Aging Tests for Middle Aged Women.Journal of menopausal medicine · 2024
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Bet-hedging in innate and adaptive immune systems.Evolution, medicine, and public health · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Yong LuSystems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA.
Angelique BiancottoTrans-NIH Center for Human Immunology, Autoimmunity, and Inflammation, NIH, Bethesda, MD 20892, USA.
Foo CheungTrans-NIH Center for Human Immunology, Autoimmunity, and Inflammation, NIH, Bethesda, MD 20892, USA.
Elaine RemmersNational Human Genome Research Institute, NIH, Bethesda, MD 20892, USA.
Naisha ShahSystems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA.
J Philip McCoyTrans-NIH Center for Human Immunology, Autoimmunity, and Inflammation, NIH, Bethesda, MD 20892, USA; Hematology Branch, National Heart, Lung and Blood Institute, NIH, Bethesda, MD 20892, USA.
John S TsangSystems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA; Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation, NIH, Bethesda, MD 20892, USA. Electronic address: john.tsang@nih.gov.

Funding

Flow Cytometry Core FacilityZICHL005905 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI DAGUR, PRADEEP · 2009 to 2025
$32.3M
Integrative analysis and modeling of human immune responses and pathologiesZIAAI001152 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI TSANG, JOHN · 2011 to 2022
$14.1M
Intramural NIH HHS ZIC HL005905
6 · The paper itself

Abstract

Cell-to-cell expression variation (CEV) is a prevalent feature of even well-defined cell populations, but its functions, particularly at the organismal level, are not well understood. Using single-cell data obtained via high-dimensional flow cytometry of T cells as a model, we introduce an analysis framework for quantifying CEV in primary cell populations and studying its functional associations in human cohorts. Analyses of 840 CEV phenotypes spanning multiple baseline measurements of 14 proteins in 28 T cell subpopulations suggest that the quantitative extent of CEV can exhibit substantial subject-to-subject differences and yet remain stable within healthy individuals over months. We linked CEV to age and disease-associated genetic polymorphisms, thus implicating CEV as a biomarker of aging and disease susceptibility and suggesting that it might play an important role in health and disease. Our dataset, interactive figures, and software for computing CEV with flow cytometry data provide a resource for exploring CEV functions.

Indexed as

AgingCohort StudiesFemaleFlow CytometryGenetic Predisposition to DiseaseHumansMalePhenotypePolymorphism, Single NucleotideT-Lymphocytes

Identifiers

PMID27851916
PMCPMC6532399

What OpenQuestion holds

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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.