Evidence map›Paper›PMID 37520578›Full record

ArticleFrontiers in immunology2023

Application of single-cell RNA sequencing methods to develop B cell targeted treatments for autoimmunity.

Catherine A Nicholas, Mia J Smith

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
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

2 authors at 1 institution in 1 country.

Catherine A NicholasBarbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, United States.
Mia J SmithBarbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, United States.
University of Colorado Denver · US

Funding

Decoding the B cell endotype in early onset type 1 diabetesR03DK129925 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI SMITH, MIA · 2021 to 2022
$294k
Characterizing molecular phenotypes of pancreatic islet reactive B cells in T1D through single cell sequencingF31DK134095 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI NICHOLAS, CATHERINE A · 2023 to 2024
$67k
NIDDK NIH HHS F31 DK134095NIDDK NIH HHS R03 DK129925
6 · The paper itself

Abstract

The COVID-19 pandemic coincided with several transformative advances in single-cell analysis. These new methods along with decades of research and trials with antibody therapeutics and RNA based technologies allowed for highly effective vaccines and treatments to be produced at astonishing speeds. While these tools were initially focused on models of infection, they also show promise in an autoimmune setting. Self-reactive B cells play important roles as antigen-presenting cells and cytokine and autoantibody producers for many autoimmune diseases. Yet, current therapies to target autoreactive B cells deplete all B cells irrespective of their pathogenicity. Development of self-reactive B cell targeting therapies that would spare non-pathogenic B cells are needed to treat disease while allowing effective immune responses to other ailments. Single-cell RNA sequencing (scRNA-seq) approaches will aid in identification of the pathogenic self-reactive B cells operative in autoimmunity and help with development of more favorable precision targeted therapies.

Indexed as

Autoimmune DiseasesCOVID-19AutoantibodiesAutoimmunityHumansPandemicsSequence Analysis, RNAAutoantibodiesantigen-specificautoimmunityautoreactiveB cellsscRNA-seq

Identifiers

PMID37520578
PMCPMC10382068
OpenAlexW4384406945

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.