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Glycoprotein Acetyls Is a Novel Biomarker Predicting Cardiovascular Complications in Rheumatoid Arthritis

Overview
Journal Int J Mol Sci
Publisher MDPI
Date 2024 Jun 19
PMID 38892172
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Abstract

The relationship between rheumatoid arthritis (RA) and early onset atherosclerosis is well depicted, each with an important inflammatory component. Glycoprotein acetyls (GlycA), a novel biomarker of inflammation, may play a role in the manifestation of these two inflammatory conditions. The present study examined a potential mediating role of GlycA within the RA-atherosclerosis relationship to determine whether it accounts for the excess risk of cardiovascular disease over that posed by lipid risk factors. The UK Biobank dataset was acquired to establish associations among RA, atherosclerosis, GlycA, and major lipid factors: total cholesterol (TC), high- and low-density lipoprotein (HDL, LDL) cholesterol, and triglycerides (TGs). Genome-wide association study summary statistics were collected from various resources to perform genetic analyses. Causality among variables was tested using Mendelian Randomization (MR) analysis. Genes of interest were identified using colocalization analysis and gene enrichment analysis. MR results appeared to indicate that the genetic relationship between GlycA and RA and also between RA and atherosclerosis was explained by horizontal pleiotropy (-value = 0.001 and <0.001, respectively), while GlycA may causally predict atherosclerosis (-value = 0.017). Colocalization analysis revealed several functionally relevant genes shared between GlycA and all the variables assessed. Two loci were apparent in all relationships tested and included the HLA region as well as GlycA appears to mediate the RA-atherosclerosis relationship through several possible pathways. GlycA, although pleiotropically related to RA, appears to causally predict atherosclerosis. Thus, GlycA is suggested as a significant factor in the etiology of atherosclerosis development in RA.

References
1.
Chopra A, Abdel-Nasser A . Epidemiology of rheumatic musculoskeletal disorders in the developing world. Best Pract Res Clin Rheumatol. 2008; 22(4):583-604. DOI: 10.1016/j.berh.2008.07.001. View

2.
Frostegard J . Immunity, atherosclerosis and cardiovascular disease. BMC Med. 2013; 11:117. PMC: 3658954. DOI: 10.1186/1741-7015-11-117. View

3.
MacGregor A, Snieder H, Rigby A, Koskenvuo M, Kaprio J, Aho K . Characterizing the quantitative genetic contribution to rheumatoid arthritis using data from twins. Arthritis Rheum. 2000; 43(1):30-7. DOI: 10.1002/1529-0131(200001)43:1<30::AID-ANR5>3.0.CO;2-B. View

4.
Lin Z, Deng Y, Pan W . Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model. PLoS Genet. 2021; 17(11):e1009922. PMC: 8639093. DOI: 10.1371/journal.pgen.1009922. View

5.
Verbanck M, Chen C, Neale B, Do R . Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018; 50(5):693-698. PMC: 6083837. DOI: 10.1038/s41588-018-0099-7. View