Association between rheumatoid arthritis and chronic respiratory diseases in a Japanese population: A Mendelian randomization study

Past observational studies have documented an association between rheumatoid arthritis (RA) and chronic respiratory diseases. Undertaking the approach of Mendelian randomization (MR) analysis, this research aims to delve deeper into the probability of a causal connection between RA and chronic respiratory diseases. Collated genome-wide association study data covering RA with 4199 cases against 208,254 controls, asthma comprising 8216 cases versus 201,592 controls, and chronic obstructive pulmonary disease (COPD) detailing 3315 cases in contrast to 201,592 controls were derived from the repository of the Japanese Biobank. A selection of 10 RA-related, 8 asthma-related, and 4 COPD-related single nucleotide polymorphisms notable for their statistical significance (P < 5 × 10-8) were identified as instrumental variables. The primary analytical technique was the inverse variance-weighted (IVW) method, alongside the MR-Egger protocol, weighted median, and weighted mode to reinforce the validity and solidity of the principal results. For scrutinizing possible implications of horizontal pleiotropy, we harnessed the MR-Egger intercept examination and the Mendelian Randomization Pleiotropy REsidual Sum and Outlier test. Employing the inverse variance-weighted technique, we established a positive correlation between genetic predispositions for RA and actual occurrences of asthma (odds ratios [OR] = 1.14; 95% confidence intervals [CI]: 1.04-1.24; P = .003). This correlation remained strong when testing the results utilizing various methods, including the MR-Egger method (OR = 1.32; 95% CI: 1.09-1.60; P = .023), the weighted median (OR = 1.16; 95% CI: 1.06-1.26; P < .001), and the weighted mode (OR = 1.21; 95% CI: 1.11-1.32; P = .002). Furthermore, our findings from the inverse variance-weighted method also demonstrated a positive association between genetically predicted RA and COPD (OR = 1.12; 95% CI: 1.02-1.29; P = .021). However, no such link was discerned in supplementary analyses. In a shifted perspective-the reverse MR analysis-no correlation was identified between genetically predicted instances of asthma (IVW, P = .717) or COPD (IVW, P = .177) and RA. The findings confirm a causal correlation between genetically predicted RA and an elevated risk of either asthma or COPD. In contrast, our results offer no support to the presumed causal relationship between genetic susceptibility to either asthma or COPD and the subsequent development of RA.

Authors

Institutions

Publication Details

Journal
Medicine
Published
2024-08-16
DOI
https://doi.org/10.1097/md.0000000000039319
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Association between rheumatoid arthritis and chronic respiratory diseases in a Japanese population: A Mendelian randomization study

Hanbing Zeng, Shaoning Shen, Lianguo Wu, Hao Wei
Medicine
Genetic Associations and Epidemiology
article

Association between rheumatoid arthritis and chronic respiratory diseases in a Japanese population: A Mendelian randomization study

Hanbing Zeng, Shaoning Shen, Lianguo Wu, Hao Wei
article en

Abstract

Past observational studies have documented an association between rheumatoid arthritis (RA) and chronic respiratory diseases. Undertaking the approach of Mendelian randomization (MR) analysis, this research aims to delve deeper into the probability of a causal connection between RA and chronic respiratory diseases. Collated genome-wide association study data covering RA with 4199 cases against 208,254 controls, asthma comprising 8216 cases versus 201,592 controls, and chronic obstructive pulmonary disease (COPD) detailing 3315 cases in contrast to 201,592 controls were derived from the repository of the Japanese Biobank. A selection of 10 RA-related, 8 asthma-related, and 4 COPD-related single nucleotide polymorphisms notable for their statistical significance (P < 5 × 10-8) were identified as instrumental variables. The primary analytical technique was the inverse variance-weighted (IVW) method, alongside the MR-Egger protocol, weighted median, and weighted mode to reinforce the validity and solidity of the principal results. For scrutinizing possible implications of horizontal pleiotropy, we harnessed the MR-Egger intercept examination and the Mendelian Randomization Pleiotropy REsidual Sum and Outlier test. Employing the inverse variance-weighted technique, we established a positive correlation between genetic predispositions for RA and actual occurrences of asthma (odds ratios [OR] = 1.14; 95% confidence intervals [CI]: 1.04-1.24; P = .003). This correlation remained strong when testing the results utilizing various methods, including the MR-Egger method (OR = 1.32; 95% CI: 1.09-1.60; P = .023), the weighted median (OR = 1.16; 95% CI: 1.06-1.26; P < .001), and the weighted mode (OR = 1.21; 95% CI: 1.11-1.32; P = .002). Furthermore, our findings from the inverse variance-weighted method also demonstrated a positive association between genetically predicted RA and COPD (OR = 1.12; 95% CI: 1.02-1.29; P = .021). However, no such link was discerned in supplementary analyses. In a shifted perspective-the reverse MR analysis-no correlation was identified between genetically predicted instances of asthma (IVW, P = .717) or COPD (IVW, P = .177) and RA. The findings confirm a causal correlation between genetically predicted RA and an elevated risk of either asthma or COPD. In contrast, our results offer no support to the presumed causal relationship between genetic susceptibility to either asthma or COPD and the subsequent development of RA.

MedicineVol. 103(33)
Zhejiang Chinese Medical University (CN), Second Affiliated Hospital of Zhejiang University (CN)
Good health and well-being
Openalex Percentile: Top 85%
Genetic Associations and Epidemiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.