Evidence map›Paper›PMID 30152754›Full record

ArticleeLife2018

Human T cell receptor occurrence patterns encode immune history, genetic background, and receptor specificity.

William S DeWitt, Anajane Smith, Gary Schoch, John A Hansen, Frederick A Matsen, Philip Bradley

Open access · goldAbstract read
In one paragraph

Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
109citing papers in PubMed, 1 pooled it
7.5field-weighted citation impact, top 2% 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

109 citing papers in PubMed, 1 synthesis or guideline pooled it, 156 citations in OpenAlex.

  1. Resolving SARS-CoV-2 CD4Cell reports. Medicine · 2022
    Pooled it
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49 more citing papers are in PubMed but not listed here.

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

6 authors at 2 institutions in 1 country.

William S DeWittPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, United States.ORCID http://orcid.org/0000-0002-6802-9139
Anajane SmithClinical Division, Fred Hutchinson Cancer Research Center, Seattle, United States.
Gary SchochClinical Division, Fred Hutchinson Cancer Research Center, Seattle, United States.
John A HansenClinical Division, Fred Hutchinson Cancer Research Center, Seattle, United States.
Frederick A MatsenPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, United States.ORCID http://orcid.org/0000-0003-0607-6025
Philip BradleyPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, United States.ORCID http://orcid.org/0000-0002-0224-6464
University of Washington · USFred Hutch Cancer Center · US

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Marian Esvelt · 1985 to 2026
$296.4M
INTERDISCIPLINARY TRAINING IN GENOMIC SCIENCEST32HG000035 · NHGRI · UNIVERSITY OF WASHINGTON · PI Bruce Colston Trapnell · 1995 to 2026
$24.2M
Whole Genome Association Analysis of Hematopoietic Cell Transplant (HCT) OutcomeR01HL105914 · NHLBI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI MARTIN, PAUL J · 2011 to 2019
$9.8M
Modeling the dynamics and evolution of immune responses to influenza virusesU19AI117891 · NIAID · EMORY UNIVERSITY · PI AHMED, RAFI, ANTIA, RUSTOM NOSHIR · 2015 to 2019
$8.4M
Leveraing deep sequencing data to understand antibody maturationR01GM113246 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI MATSEN, FREDERICK ALBERT · 2014 to 2018
$1.9M
FHCRC High-Performance Computing ClusterS10OD020069 · OD · FRED HUTCHINSON CANCER RESEARCH CENTER · PI KOOPERBERG, CHARLES L · 2015 to 2015
$600k
Fred Hutchinson Cancer Research Center Salary supportHoward Hughes Medical Institute 55108544NCI NIH HHS P30 CA015704NHLBI NIH HHS R01 HL105914NIAID NIH HHS U19 AI117891NIGMS NIH HHS R01 GM113246NIH HHS CA015704NIH HHS R01-GM113246NIH HHS R01-HL105914NIH HHS S10 OD020069NIH HHS U19-AI117891
6 · The paper itself

Abstract

The T cell receptor (TCR) repertoire encodes immune exposure history through the dynamic formation of immunological memory. Statistical analysis of repertoire sequencing data has the potential to decode disease associations from large cohorts with measured phenotypes. However, the repertoire perturbation induced by a given immunological challenge is conditioned on genetic background via major histocompatibility complex (MHC) polymorphism. We explore associations between MHC alleles, immune exposures, and shared TCRs in a large human cohort. Using a previously published repertoire sequencing dataset augmented with high-resolution MHC genotyping, our analysis reveals rich structure: striking imprints of common pathogens, clusters of co-occurring TCRs that may represent markers of shared immune exposures, and substantial variations in TCR-MHC association strength across MHC loci. Guided by atomic contacts in solved TCR:peptide-MHC structures, we identify sequence covariation between TCR and MHC. These insights and our analysis framework lay the groundwork for further explorations into TCR diversity.

Indexed as

ImmunityAllelesAmino Acid SequenceComplementarity Determining RegionsCytomegalovirusGene FrequencyGenetic LociHLA AntigensHumansModels, MolecularProbabilityReceptors, Antigen, T-CellComplementarity Determining RegionsHLA AntigensReceptors, Antigen, T-Celladaptive immunitycomputational biologyhumanimmunologyinflammationsystems biologyT cell receptor sequencingT cell repertoires

Identifiers

PMID30152754
PMCPMC6162092
OpenAlexW2951959160

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.