Evidence map›Paper›PMID 36550178›Full record

ArticleScientific reports2022

Single-cell RNA sequencing of immune cells in patients with acute gout.

Jan-Gowth Chang, Siang-Jyun Tu, Chung-Ming Huang, Yu-Chia Chen, Hui-Shan Chiang, Ya-Ting Lee, Ju-Chen Yen, Chia-Li Lin, Chin-Chun Chung, Ta-Chih Liu and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

20 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Peripheral CD4Frontiers in immunology · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Senescent CD4Clinical rheumatology · 2023
    Article
  19. Article
  20. 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

11 authors at 3 institutions in 1 country.

Jan-Gowth ChangCenter for Precision Medicine, China Medical University Hospital, 2 Yuh-Der Road, Taichung, 404, Taiwan.
Siang-Jyun TuCenter for Precision Medicine, China Medical University Hospital, 2 Yuh-Der Road, Taichung, 404, Taiwan.
Chung-Ming HuangDivision of Immunology and Rheumatology, Department of Internal Medicine, China Medical University Hospital, Taichung, Taiwan.
Yu-Chia ChenCenter for Precision Medicine, China Medical University Hospital, 2 Yuh-Der Road, Taichung, 404, Taiwan.
Hui-Shan ChiangCenter for Precision Medicine, China Medical University Hospital, 2 Yuh-Der Road, Taichung, 404, Taiwan.
Ya-Ting LeeCenter for Precision Medicine, China Medical University Hospital, 2 Yuh-Der Road, Taichung, 404, Taiwan.
Ju-Chen YenCenter for Precision Medicine, China Medical University Hospital, 2 Yuh-Der Road, Taichung, 404, Taiwan.
Chia-Li LinCenter for Precision Medicine, China Medical University Hospital, 2 Yuh-Der Road, Taichung, 404, Taiwan.
Chin-Chun ChungCenter for Precision Medicine, China Medical University Hospital, 2 Yuh-Der Road, Taichung, 404, Taiwan.
Ta-Chih LiuDepartment of Hematology-Oncology, Chang Bing Show Chwan Memorial Hospital, 6 Lugong Road, Changhua, 505, Taiwan. touchyou3636@gmail.com.
Ya-Sian ChangCenter for Precision Medicine, China Medical University Hospital, 2 Yuh-Der Road, Taichung, 404, Taiwan. t25074@mail.cmuh.org.tw.
China Medical University · TWChina Medical University Hospital · TWChang Bing Show Chwan Memorial Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell subpopulations in the blood and joint fluid of patients with gout are poorly understood. Single-cell RNA sequencing and bioinformatic tools were used to identify cell subsets and their gene signatures in blood and synovial fluid (SF) cells, determine their relationships, characterize the diversity, and evaluate interactions among specific cell types. We identified 34 subpopulations (5 types of B cells, 16 types of T and natural killer cells, 9 types of monocytes, and 4 other cell types) in the blood of five healthy subjects and seven patients with acute gouty, and the SF of three patients with acute gout. We found that naïve CD4 T cells and classical monocytes cell populations were enriched in patients with gout, whereas plasmacytoid dendritic cells and intermediate monocytes were more abundant in healthy subjects. SF was enriched in Th1/Th17 cells, effector memory CD8 T cells, mucosal-associated invariant T cells, and macrophages. Subclusters of these cell subpopulations showed different compositions between healthy subjects and those with acute gout, according to blood and SF samples. At the cellular level, the inflammation score of a subpopulation or subcluster was highest in SF, following by the blood of acute gout patients and healthy person, whereas energy score showed the opposite trend. We also detected specific cell-cell interactions for interleukin-1, tumor necrosis factor-α, and transforming growth factor-β1 expression in the cells of patients with acute gout. Our study reveals cellular and molecular insights on inflammatory responses to hyperuricemia or uric crystal and may provide therapeutic guidance to improve treatments for gout.

Indexed as

Arthritis, GoutyGoutHyperuricemiaHumansMacrophagesSequence Analysis, RNA

Identifiers

PMID36550178
PMCPMC9772586
OpenAlexW4312192769

What Socratic 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 Socratic graph.