Evidence map›Paper›PMID 35860586›Full record

ArticleFrontiers in oncology2022

Exome Sequencing Reveals Genetic Variability and Identifies Chronic Prognostic Loci in Chinese Sarcoidosis Patients.

Qian Zhang, Hui Huang, Meijun Zhang, Chuling Fang, Na Wang, Xiaoyan Jing, Jian Guo, Wei Sun, Xiaoyu Yang, Zuojun Xu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. 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
0.4field-weighted citation impact, top 42% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

10 authors at 2 institutions in 1 country.

Qian ZhangDepartment of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Hui HuangDepartment of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Meijun ZhangANNOROAD Co., Beijing, China.
Chuling FangDepartment of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Na WangDepartment of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Xiaoyan JingDepartment of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Jian GuoDepartment of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Wei SunDepartment of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Xiaoyu YangDepartment of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Zuojun XuDepartment of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Peking Union Medical College Hospital · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sarcoidosis is an inflammatory disease characterized by non-caseating granuloma formation in various organs, with several recognized genetic and environmental risk factors. Despite substantial progress, the genetic determinants associated with its prognosis remain largely unknown. Objectives: This study aimed to identify the genetic changes involved in sarcoidosis and evaluate their clinical relevance. Methods: We performed whole-exome sequencing (WES) in 116 sporadic sarcoidosis patients (acute sarcoidosis patients, n=58; chronic sarcoidosis patients, n=58). In addition, 208 healthy controls were selected from 1000 G East Asian population data. To identify genes enriched in sarcoidosis, Fisher exact tests were performed. The identified genes were included for further pathway analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Additionally, we used the STRING database to construct a protein network of rare variants and Cytoscape to identify hub genes of signaling pathways. Results: WES and Fisher's exact test identified 1,311 variants in 439 protein-coding genes. A total of 135 single nucleotide polymorphisms (SNPs) on 30 protein-coding genes involved in the immunological process based on the GO and KEGG enrichment analysis. Pathway enrichment analysis showed osteoclast differentiation and cytokine-cytokine receptor interactions. Three missense mutations (rs76740888, rs149664918, and rs78251590) in two genes (PRSS3 and CNN2) of immune-related genes showed significantly different mutation frequencies between the disease group and healthy controls. The correlation of genetic abnormalities with clinical outcomes using multivariate analysis of the clinical features and mutation loci showed that the missense variant (rs76740888, Chr9:33796673 G>A) of PRSS3 [ Conclusion: Our study provides new insights into the molecular pathogenesis of sarcoidosis and identifies novel genetic alterations in this disease, especially PRSS3, which may be promising targets for future therapeutic strategies for chronic sarcoidosis.

Indexed as

adaptive immune responsechronic sarcoidosis prognosisnon-synonymous mutationssarcoidosiswhole-exome sequencing

Identifiers

PMID35860586
PMCPMC9289133
OpenAlexW4283790555

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.