Evidence map›Paper›PMID 32511339›Full record

ArticlebioRxiv : the preprint server for biology2020

Predicting the Immunogenicity of T cell epitopes: From HIV to SARS-CoV-2.

Ang Gao, Zhilin Chen, Florencia Pereyra Segal, Mary Carrington, Hendrik Streeck, Arup K Chakraborty, Boris Julg

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 22 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 2 countries.

Ang GaoInstitute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Zhilin ChenRagon Insitute of Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard, Cambridge, MA 02139, USA.
Florencia Pereyra SegalBrigham and Women's Hospital, Boston, MA 02115, USA.
Mary CarringtonRagon Insitute of Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard, Cambridge, MA 02139, USA.
Hendrik StreeckInstitut für Virologie, Universitätsklinikum Bonn, 53127 Bonn, Germany.
Arup K ChakrabortyInstitute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Boris JulgRagon Insitute of Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard, Cambridge, MA 02139, USA.
Ragon Institute of MGH, MIT and Harvard · USBrigham and Women's Hospital · USMassachusetts Institute of Technology · USUniversity Hospital Bonn · DE

Funding

Molecular genetics and population studies of the KIR and HLA gene complexesZIABC010792 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI CARRINGTON, MARY N. · 2009 to 2025
$7.8M
Optimizing HIV-specific T-cell responses by therapeutic vaccinationR01AI138790 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI JUELG, BORIS DOMINIK · 2019 to 2024
$2.8M
Host genetic resistance to COVID-19ZIABC011949 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI CARRINGTON, MARY N. · 2020 to 2025
$997k
CCR NIH HHS HHSN261200800001CNCI NIH HHS HHSN261200800001ENIAID NIH HHS R01 AI138790
6 · The paper itself

Abstract

We describe a physics-based learning model for predicting the immunogenicity of Cytotoxic T Lymphocyte (CTL) epitopes derived from diverse pathogens, given a Human Leukocyte Antigen (HLA) genotype. The model was trained and tested on experimental data on the relative immunodominance of CTL epitopes in Human Immunodeficiency Virus infection. The method is more accurate than publicly available models. Our model predicts that only a fraction of SARS-CoV-2 epitopes that have been predicted to bind to HLA molecules is immunogenic. The immunogenic CTL epitopes across all SARS-CoV-2 proteins are predicted to provide broad population coverage, but the immunogenic epitopes in the SARS-CoV-2 spike protein alone are unlikely to do so. Our model predicts that several immunogenic SARS-CoV-2 CTL epitopes are identical to those contained in low-pathogenicity coronaviruses circulating in the population. Thus, we suggest that some level of CTL immunity against COVID-19 may be present in some individuals prior to SARS-CoV-2 infection.

Identifiers

PMID32511339
PMCPMC7241102
OpenAlexW3025244313

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.