Evidence map›Paper›PMID 36280495›Full record

ReviewTrends in biochemical sciences2023

Mechanistic perspectives on anti-aminoacyl-tRNA synthetase syndrome.

Sachiko Kanaji, Wenqian Chen, Yosuke Morodomi, Ryan Shapiro, Taisuke Kanaji, Xiang-Lei Yang

Open access · greenAbstract readReview
In one paragraph

Review in Trends in biochemical sciences, 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
1.0field-weighted citation impact, top 26% 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, 12 citations in OpenAlex.

  1. Review
  2. Article
  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

6 authors at 1 institution in 1 country.

Sachiko KanajiDepartment of Molecular Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.
Wenqian ChenDepartment of Molecular Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.
Yosuke MorodomiDepartment of Molecular Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.
Ryan ShapiroDepartment of Molecular Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.
Taisuke KanajiDepartment of Molecular Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.
Xiang-Lei YangDepartment of Molecular Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA. Electronic address: xlyang@scripps.edu.
Scripps Research Institute · US

Funding

Link extracellular function of tRNA synthetase with pathological mechanism of diseaseR35GM139627 · NIGMS · SCRIPPS RESEARCH INSTITUTE, THE · PI YANG, XIANG-LEI · 2021 to 2025
$2.3M
NIGMS NIH HHS R35 GM139627
6 · The paper itself

Abstract

Antisynthetase syndrome (ASSD) is an autoimmune disease characterized by circulating autoantibodies against one of eight aminoacyl-tRNA synthetases (aaRSs). Although these autoantibodies are believed to play critical roles in ASSD pathogenesis, the nature of their roles remains unclear. Here we describe ASSD pathogenesis and discuss ASSD-linked aaRSs - from the WHEP domain that may impart immunogenicity to the role of tRNA in eliciting the innate immune response and the secretion of aaRSs from cells. Through these explorations, we propose that ASSD pathogenesis involves the tissue-specific secretion of aaRSs and that extracellular tRNAs or tRNA fragments and their ability to engage Toll-like receptor signaling may be important disease factors.

Indexed as

Amino Acyl-tRNA SynthetasesMyositisAutoantibodiesHumansRNA, TransferAmino Acyl-tRNA SynthetasesAutoantibodiesRNA, Transferautoantigenextracellular vesicleHisRSimmune complextRNAWHEP domain

Identifiers

PMID36280495
PMCPMC9974581
OpenAlexW4307170576

What OpenQuestion holds

Textmetadata
LicenceTDM
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.