Bidirectional Mendelian randomization reveals causal immune cell phenotypes in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent inflammation in synovial joints and influenced by genetic and environmental factors. The immune system, comprising various cells that either exacerbate or reduce inflammation, plays a central role in RA pathogenesis. Despite extensive research, the causal relationships between immune cell phenotypes and RA remain unclear. We employed a two-sample Mendelian randomization (MR) approach to investigate the causal associations between 731 immune cell phenotypes and RA. Genetic variants, carefully selected based on rigorous criteria, served as instrumental variables to ensure analytical validity. Data on RA were derived from the FinnGen database, whereas immune cell phenotype data were obtained from the genome-wide association studies catalog. We employed 5 MR methods, including inverse variance weighted and MR Egger, to ensure robust causal inference. We assessed for pleiotropy and heterogeneity and adjusted findings using the False Discovery Rate. After False Discovery Rate adjustment (threshold < 0.05), inverse variance weighted analysis revealed potential causal relationships between 4 immune cell types and RA: CD62L- dendritic cells %dendritic cells (P = 3.88E-05; 95% confidence interval [CI] = 1.056), CD19 on IgD+ CD38- naive cells (P = 1.75E-04; 95% CI = 0.969), CD45RA on TD CD8br (P = 5.59E-04; 95% CI = 0.919), and HLA DR on CD33- HLA DR+ (P = 8.13E-05; 95% CI = 1.422). In reverse Mendelian studies, specific immune cell phenotypes were found to be associated with RA risk and progression: the percentage of memory B cells among lymphocytes (P = 2.74E-04; 95% CI = 0.861), IgD+ CD24+ cells among lymphocytes (P = 6.93E-04; 95% CI = 0.867), CD4+ CD8dim cells among lymphocytes (P = 2.92E-04; 95% CI = 0.802), CD4+ CD8dim cells among leukocytes (P = 4.37E-04; 95% CI = 0.814), and CD24 expression on IgD+CD24+ cells (P = 1.05E-04; 95% CI = 0.857). These results identify immune cell phenotypes closely linked to RA susceptibility and progression. The findings suggest that specific immune cell phenotypes are not only influenced by RA but may also contribute to its development and progression. These results offer new insights into the immunological underpinnings of RA and highlight potential targets for therapeutic intervention. Future research should focus on validating these causal relationships in diverse populations and exploring the molecular mechanisms involved.

Authors

Institutions

Publication Details

Journal
Medicine
Published
2025-02-07
DOI
https://doi.org/10.1097/md.0000000000041512
Citations
1
Primary Topic
Lymphoma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.47
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bidirectional Mendelian randomization reveals causal immune cell phenotypes in rheumatoid arthritis

Han Li, Jian Shi, Lixue Huang, Qing Lin
1 citations
Medicine
Lymphoma Diagnosis and Treatment
1.47
article

Bidirectional Mendelian randomization reveals causal immune cell phenotypes in rheumatoid arthritis

Han Li, Jian Shi, Lixue Huang, Qing Lin
article en
1 citations

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent inflammation in synovial joints and influenced by genetic and environmental factors. The immune system, comprising various cells that either exacerbate or reduce inflammation, plays a central role in RA pathogenesis. Despite extensive research, the causal relationships between immune cell phenotypes and RA remain unclear. We employed a two-sample Mendelian randomization (MR) approach to investigate the causal associations between 731 immune cell phenotypes and RA. Genetic variants, carefully selected based on rigorous criteria, served as instrumental variables to ensure analytical validity. Data on RA were derived from the FinnGen database, whereas immune cell phenotype data were obtained from the genome-wide association studies catalog. We employed 5 MR methods, including inverse variance weighted and MR Egger, to ensure robust causal inference. We assessed for pleiotropy and heterogeneity and adjusted findings using the False Discovery Rate. After False Discovery Rate adjustment (threshold < 0.05), inverse variance weighted analysis revealed potential causal relationships between 4 immune cell types and RA: CD62L- dendritic cells %dendritic cells (P = 3.88E-05; 95% confidence interval [CI] = 1.056), CD19 on IgD+ CD38- naive cells (P = 1.75E-04; 95% CI = 0.969), CD45RA on TD CD8br (P = 5.59E-04; 95% CI = 0.919), and HLA DR on CD33- HLA DR+ (P = 8.13E-05; 95% CI = 1.422). In reverse Mendelian studies, specific immune cell phenotypes were found to be associated with RA risk and progression: the percentage of memory B cells among lymphocytes (P = 2.74E-04; 95% CI = 0.861), IgD+ CD24+ cells among lymphocytes (P = 6.93E-04; 95% CI = 0.867), CD4+ CD8dim cells among lymphocytes (P = 2.92E-04; 95% CI = 0.802), CD4+ CD8dim cells among leukocytes (P = 4.37E-04; 95% CI = 0.814), and CD24 expression on IgD+CD24+ cells (P = 1.05E-04; 95% CI = 0.857). These results identify immune cell phenotypes closely linked to RA susceptibility and progression. The findings suggest that specific immune cell phenotypes are not only influenced by RA but may also contribute to its development and progression. These results offer new insights into the immunological underpinnings of RA and highlight potential targets for therapeutic intervention. Future research should focus on validating these causal relationships in diverse populations and exploring the molecular mechanisms involved.

MedicineVol. 104(6)
Guangxi University of Science and Technology (CN), Liuzhou General Hospital (CN), Second People’s Hospital of Yibin (CN)
Good health and well-being
Openalex Percentile: Top 23%
Lymphoma Diagnosis and Treatment
1.47
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.