Evidence map›Paper›PMID 36342317›Full record

ArticleFEBS open bio2022

Identification of novel meQTLs strongly associated with rheumatoid arthritis by large-scale epigenome-wide analysis.

Guoping Tang, Chen Sun, Hongchao Lv, Mingming Zhang, Yongshuai Jiang, Jing Xu

Open access · goldAbstract read
In one paragraph

Article in FEBS open bio, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 institutions in 1 country.

Guoping TangThe Fourth Affiliated Hospital, Zhejiang University School of Medicine, China.
Chen SunCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Hongchao LvCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Mingming ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Yongshuai JiangCollege of Bioinformatics Science and Technology, Harbin Medical University, China.ORCID 0000-0002-7163-6554
Jing XuCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Harbin Medical University · CNFourth Affiliated Hospital of China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rheumatoid arthritis (RA) is highly heritable, and previous studies have suggested that genetic variation may affect susceptibility to RA by altering epigenetic modifications (e.g. DNA methylation). Here we examined how genetic variation influences DNA methylation (DNAm) in RA by integrating individual genetic variation and DNAm data. Epigenome-wide meQTL (methylation quantitative trait loci) analysis was performed on 354 RA patients and 335 controls, scanning 30,101,744 relationships between 62 SNPs and 485,512 DNA methylation sites. Two regulatory relationship pairs (FDR < 0.05) showed very strong associations with RA risk. One was rs10796216-cg00475509, and the DNAm decreased by 0.0168 per addition of allele rs10796216-A. The other was rs6546473-cg13358873, for which a 0.0365 reduction of DNAm at cg13358873 was observed for each addition of allele rs6546473-A, and lower DNAm was found to be significantly associated with RA risk (P = 2.0407e-28). Moreover, both pairs of meQTL showed a strong regulatory relationship only in RA samples, so they can be subsequently considered as risk markers for RA. In conclusion, our integrated analysis of genetic and epigenetic variation suggests that genetic variation may affect the risk of RA by regulating DNA methylation levels. Alterations of DNAm at cg00475509 and cg13358873 loci conferred by rs10796216-A and rs6546473-A allele may suggest a potential risk for RA. Our results deepen our understanding of the genetic and epigenetic mechanisms of RA and provide novel associations that can be further investigated in future studies.

Indexed as

Arthritis, RheumatoidEpigenomeQuantitative Trait LociDNA MethylationEpigenesis, GeneticHumansbioinformaticsDNA methylationepigeneticsgenetic riskrheumatoid arthritisSNP

Identifiers

PMID36342317
PMCPMC9714356
OpenAlexW4308371207

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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.