Evidence map›Paper›PMID 34804070›Full record

ReviewFrontiers in immunology2021

High Throughput Human T Cell Receptor Sequencing: A New Window Into Repertoire Establishment and Alloreactivity.

Jianing Fu, Mohsen Khosravi-Maharlooei, Megan Sykes

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

11 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Recent progress and future challenges in structure-based protein-protein interaction prediction.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Review
  5. Review
  6. Alloreactive memory CD4 T cells promote transplant rejection by engaging DCs to induce innate inflammation and CD8 T cell priming.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
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

3 authors at 1 institution in 1 country.

Jianing FuColumbia Center for Translational Immunology, Department of Medicine, Columbia University, New York, NY, United States.
Mohsen Khosravi-MaharlooeiColumbia Center for Translational Immunology, Department of Medicine, Columbia University, New York, NY, United States.
Megan SykesColumbia Center for Translational Immunology, Department of Medicine, Columbia University, New York, NY, United States.
Columbia University · US

Funding

Immune Tolerance Network UM1 2023 SupplementUM1AI109565 · NIAID · BENAROYA RESEARCH INST AT VIRGINIA MASON · PI Mark S Anderson, Jane Hoyt Buckner · 2014 to 2026
$451.6M
Transcriptomics and Repertoire ProfilingP01AI106697 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Donna L. Farber · 2013 to 2026
$31.3M
Modeling autoimmune pathogenesis and beta cell destruction by T1D immune systemsU01DK123559 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI ANDERSON, MARK S, PARENT, AUDREY · 2019 to 2023
$4.3M
Mice with autologous human T1D-derived immune systems and iPSC-derived beta cellsUC4DK104207 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SYKES, MEGAN · 2014 to 2014
$3.8M
Immune Response to iPSC-Derived Beta Cells in Type 1 DiabetesR01DK103585 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SYKES, MEGAN · 2015 to 2018
$1.8M
TCR and BCR deep sequencing to distinguish autoimmune recurrence from allograft rejectionR21TR002279 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SYKES, MEGAN · 2018 to 2019
$461k
Immune profiling of γδ T cells after human intestinal transplantationR21AI166069 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FU, JIANING · 2021 to 2022
$446k
NCATS NIH HHS R21 TR002279NIAID NIH HHS P01 AI106697NIAID NIH HHS R21 AI166069NIAID NIH HHS UM1 AI109565NIDDK NIH HHS R01 DK103585NIDDK NIH HHS U01 DK123559NIDDK NIH HHS UC4 DK104207
6 · The paper itself

Abstract

Recent advances in high throughput sequencing (HTS) of T cell receptors (TCRs) and in transcriptomic analysis, particularly at the single cell level, have opened the door to a new level of understanding of human immunology and immune-related diseases. In this article, we discuss the use of HTS of TCRs to discern the factors controlling human T cell repertoire development and how this approach can be used in combination with human immune system (HIS) mouse models to understand human repertoire selection in an unprecedented manner. An exceptionally high proportion of human T cells has alloreactive potential, which can best be understood as a consequence of the processes governing thymic selection. High throughput TCR sequencing has allowed assessment of the development, magnitude and nature of the human alloresponse at a new level and has provided a tool for tracking the fate of pre-transplant-defined donor- and host-reactive TCRs following transplantation. New insights into human allograft rejection and tolerance obtained with this method in combination with single cell transcriptional analyses are reviewed here.

Indexed as

High-Throughput Nucleotide SequencingAnimalsAutoimmunityCell DifferentiationClonal Selection, Antigen-MediatedDisease SusceptibilityGene Expression RegulationGenetic Predisposition to DiseaseGraft RejectionGraft SurvivalHumansImmune ToleranceImmunityModels, AnimalReceptors, Antigen, T-CellT-LymphocytesReceptors, Antigen, T-Cellhigh throughput TCR sequencinghuman alloresponsehuman immune system mouse modelsimmune toleranceorgan transplantationpublic T cell receptorsthymic selection

Identifiers

PMID34804070
PMCPMC8604183
OpenAlexW3213766185

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.