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Kasher M, Freidin MB, Williams FMK, Cherny SS, Ashkenazi S, Livshits G. Glycoprotein Acetyls Is a Novel Biomarker Predicting Cardiovascular Complications in Rheumatoid Arthritis. Int J Mol Sci 2024; 25:5981. [PMID: 38892172 PMCID: PMC11173129 DOI: 10.3390/ijms25115981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 05/25/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024] Open
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 (p-value = 0.001 and <0.001, respectively), while GlycA may causally predict atherosclerosis (p-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 SLC22A1. 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.
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Affiliation(s)
- Melody Kasher
- Department of Morphological Sciences, Adelson School of Medicine, Ariel University, Ariel 4070000, Israel; (M.K.); (S.A.)
| | - Maxim B. Freidin
- Department of Biology, School of Biological and Behavioural Sciences, Queen Mary University of London, London E1 4NS, UK;
| | - Frances M. K. Williams
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, London WC2R 2LS, UK;
| | - Stacey S. Cherny
- Human Population Biology Research Unit, Department of Anatomy and Anthropology, School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel;
- Department of Epidemiology and Preventive Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Shai Ashkenazi
- Department of Morphological Sciences, Adelson School of Medicine, Ariel University, Ariel 4070000, Israel; (M.K.); (S.A.)
| | - Gregory Livshits
- Department of Morphological Sciences, Adelson School of Medicine, Ariel University, Ariel 4070000, Israel; (M.K.); (S.A.)
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, London WC2R 2LS, UK;
- Human Population Biology Research Unit, Department of Anatomy and Anthropology, School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel;
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Andreychuk N, Llop D, Moreno-Vedia J, Girona J, Ibarretxe D, Rodríguez-Borjabad C, Plana N, Masana L. Glycoprotein Serum Concentrations Assessed By 1H-NMR are Increased in Patients With High Blood Pressure. Hypertension 2023; 80:460-469. [PMID: 36384288 DOI: 10.1161/hypertensionaha.122.20137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
BACKGROUND Patients with hypertension present a permanent state of low-grade inflammation, as the disease activates several pro-inflammatory cells and inflammatory pathways. Glycoproteins A, B, and F, determined by proton nuclear magnetic resonance, provide a highly sensitive method for determining a group of liver-derived pro-inflammatory proteins, and their role has not yet been explored in patients with hypertension. In this study, we evaluated the impact of plasma concentrations of these glycoproteins in patients with hypertension. METHODS This cross-sectional study involved 340 patients attending our vascular and metabolism medicine unit. Of them, 129 were normotensive and 211 were hypertensive. Standard biochemistry and carotid ultrasound measures were performed. Serum concentrations of glycoproteins A, B, and F were determined by proton nuclear magnetic resonance. RESULTS Hypertensive patients presented a higher prevalence of obesity, metabolic syndrome, and diabetes and higher glycoprotein A, B, and F concentrations. Glycoproteins A, B, and F were positively correlated with systolic and diastolic blood pressure. Multivariate logistic models showed that glycoproteins A, B, and F were associated with higher odds of being hypertensive. Machine learning methods corroborated the relationship between glycoproteins and high blood pressure. The higher prevalence of carotid plaques in patients with high blood pressure was partially mediated by glycoproteins A and F. CONCLUSIONS Patients with hypertension present systemic, subclinical inflammation as assessed by liver-derived glycoprotein A, B, and F serum levels. These results support the effect of hypertension on the mechanisms of systemic inflammation. Hypertension-associated systemic inflammation plays a role in hypertension-associated vascular injury and probably in hypertension-induced damage to other organs.
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Affiliation(s)
- Natalia Andreychuk
- Unitat de Medicina Vascular i Metabolisme (UVASMET), Unitat de Recerca en Lípids i Arteriosclerosis, Hospital Universitari Sant Joan, Universitat Rovira i Virgili, CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, IISPV, Reus, Spain
| | - Dídac Llop
- Unitat de Medicina Vascular i Metabolisme (UVASMET), Unitat de Recerca en Lípids i Arteriosclerosis, Hospital Universitari Sant Joan, Universitat Rovira i Virgili, CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, IISPV, Reus, Spain
| | - Juan Moreno-Vedia
- Unitat de Medicina Vascular i Metabolisme (UVASMET), Unitat de Recerca en Lípids i Arteriosclerosis, Hospital Universitari Sant Joan, Universitat Rovira i Virgili, CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, IISPV, Reus, Spain
| | - Josefa Girona
- Unitat de Medicina Vascular i Metabolisme (UVASMET), Unitat de Recerca en Lípids i Arteriosclerosis, Hospital Universitari Sant Joan, Universitat Rovira i Virgili, CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, IISPV, Reus, Spain
| | - Daiana Ibarretxe
- Unitat de Medicina Vascular i Metabolisme (UVASMET), Unitat de Recerca en Lípids i Arteriosclerosis, Hospital Universitari Sant Joan, Universitat Rovira i Virgili, CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, IISPV, Reus, Spain
| | - Cèlia Rodríguez-Borjabad
- Unitat de Medicina Vascular i Metabolisme (UVASMET), Unitat de Recerca en Lípids i Arteriosclerosis, Hospital Universitari Sant Joan, Universitat Rovira i Virgili, CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, IISPV, Reus, Spain
| | - Núria Plana
- Unitat de Medicina Vascular i Metabolisme (UVASMET), Unitat de Recerca en Lípids i Arteriosclerosis, Hospital Universitari Sant Joan, Universitat Rovira i Virgili, CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, IISPV, Reus, Spain
| | - Lluís Masana
- Unitat de Medicina Vascular i Metabolisme (UVASMET), Unitat de Recerca en Lípids i Arteriosclerosis, Hospital Universitari Sant Joan, Universitat Rovira i Virgili, CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, IISPV, Reus, Spain
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Glycoprotein Profile Measured by a 1H-Nuclear Magnetic Resonance Based on Approach in Patients with Diabetes: A New Robust Method to Assess Inflammation. Life (Basel) 2021; 11:life11121407. [PMID: 34947938 PMCID: PMC8709228 DOI: 10.3390/life11121407] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 12/12/2021] [Accepted: 12/15/2021] [Indexed: 01/04/2023] Open
Abstract
Patients with type 2 diabetes mellitus (T2DM) and atherogenic dyslipidemia (AD) are at higher risk of developing cardiovascular diseases (CVDs), so an interest in discovering inflammation biomarkers as indicators of processes related to CVD progression is increasing. This study aims (a) to characterize the plasma glycoprotein profile of a cohort of 504 participants, including patients with and without T2DM and/or AD and controls, and (b) to study the associations between the glycoprotein profile and other lipid and clinical variables in these populations. We characterized the plasma glycoprotein profiles by using 1H-NMR. We quantified the two peaks associated with the concentration of plasma glycoproteins (GlycA and GlycB) and their height/width ratios (H/W GlycA and H/W GlycB), as higher and narrower signals have been related to inflammation. We also quantified GlycF, the signal of which is proportional to the concentration of the acetyl groups of free N-acetylglucosamine, N-acetylgalactosamine, and N-acetylneuraminic in the samples. The lipoprotein profile was also determined (Liposcale®). Standard clinical and anthropometric measurements were taken. Multivariate classification models were developed to study the differences between the study groups. Reduced HDL-C levels, increased small dense LDL and HDL particles, and elevated TG levels were significantly associated with glycoprotein variables. Glycoprotein values in the diagnostic groups were significantly different from those in the CT groups. AD and DM conditions together contribute to a positive and significant synergetic effect on the GlycA area (<0.05) and the H/W ratios of GlycA (<0.01) and GlycB (<0.05). By adding the new glycoprotein variables to the traditionally used marker of inflammation C-reactive protein (CRP), the AUC increased sharply for classification models between the CT group and the rest (0.68 to 0.84), patients with and without dyslipidemia (0.54 to 0.86), and between patients with and without diabetes (0.55 to 0.75). 1H-NMR-derived glycoproteins can be used as possible markers of the degree of inflammation associated with T2DM and AD.
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