Evidence map›Paper›PMID 37582060›Full record

ArticleRMD open2022

Novel insight into the aetiology of rheumatoid arthritis gained by a cross-tissue transcriptome-wide association study.

Jing Ni, Peng Wang, Kang-Jia Yin, Xiao-Ke Yang, Han Cen, Cong Sui, Guo-Cui Wu, Hai-Feng Pan

Open access · goldAbstract read
In one paragraph

Article in RMD open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 2 pooled it
12.1field-weighted citation impact, top 1% 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

32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 50 citations in OpenAlex.

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  4. Integrative Multi-omics Analysis for Prioritization of Candidate Genes in Polycystic Ovary Syndrome.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
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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

8 authors at 2 institutions in 1 country.

Jing NiDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China panhaifeng1982@sina.com nijing@ahmu.edu.cn.
Peng WangTeaching Center for Preventive Medicine, School of Public Health, Anhui Medical University, Hefei, China.
Kang-Jia YinDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China.
Xiao-Ke YangDepartment of Rheumatology and Immunology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Han CenDepartment of Preventive Medicine, Ningbo University Medical School, Ningbo, Zhejiang, China.ORCID 0000-0002-9251-2331
Cong SuiDepartment of Orthopedics Trauma, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Guo-Cui WuDepartment of Obstetrics and Gynecological Nursing, School of Nursing, Anhui Medical University, Hefei, Anhui, China.
Hai-Feng PanDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China panhaifeng1982@sina.com nijing@ahmu.edu.cn.ORCID 0000-0001-8218-5747
Anhui Medical University · CNNingbo University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough genome-wide association studies (GWASs) have identified more than 100 loci associated with rheumatoid arthritis (RA) susceptibility, the causal genes and biological mechanisms remain largely unknown.

methodsA cross-tissue transcriptome-wide association study (TWAS) using the unified test for molecular signaturestool was performed to integrate GWAS summary statistics from 58 284 individuals (14 361 RA cases and 43 923 controls) with gene-expression matrix in the Genotype-Tissue Expression project. Subsequently, a single tissue by using FUSION software was conducted to validate the significant associations. We also compared the TWAS with different gene-based methodologies, including Summary Data Based Mendelian Randomization (SMR) and Multimarker Analysis of Genomic Annotation (MAGMA). Further in silico analyses (conditional and joint analysis, differential expression analysis and gene-set enrichment analysis) were used to deepen our understanding of genetic architecture and comorbidity aetiology of RA.

resultsWe identified a total of 47 significant candidate genes for RA in both cross-tissue and single-tissue test after multiple testing correction, of which 40 TWAS-identified genes were verified by SMR or MAGMA. Among them, 13 genes were situated outside of previously reported significant loci by RA GWAS. Both TWAS-based and MAGMA-based enrichment analyses illustrated the shared genetic determinants among autoimmune thyroid disease, asthma, type I diabetes mellitus and RA.

conclusionOur study unveils 13 new candidate genes whose predicted expression is associated with risk of RA, providing new insights into the underlying genetic architecture of RA.

Indexed as

Arthritis, RheumatoidTranscriptomeCausalityGenome-Wide Association StudyHumansPolymorphism, Single NucleotideEpidemiologyPolymorphism, GeneticRheumatoid Arthritis

Identifiers

PMID37582060
PMCPMC9462377
OpenAlexW4294958729

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.