GlycA is not a useful biomarker of inflammation in sickle cell disease

Weisman, Julie K.; Meeks, Daveena; Mendelsohn, Laurel; Remaley, Alan T.; Sampson, Maureen; Allen, Darlene; Nichols, Jim; Shet, Arun S.; Thein, Swee Lay

doi:10.1111/ijlh.12907

Cited by 3 publications

(5 citation statements)

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“…GlycA has been shown to be a robust marker of inflammatory and proinflammatory conditions including inflammatory bowel disease, 29 gestational diabetes, 30 alcoholic liver disease, 31 cardiovascular risk, 32 rheumatoid arthritis 33 and certain cancers, 28 although GlycA is confounded by hemolysis and is not an appropriate marker of inflammatory conditions such as sickle cell disease. 34 In general, GlycA has been found to be a better predictor of inflammatory conditions than either C reactive protein (CRP) or interleukin-6 (IL-6), and is independent of both, although GlycA and CRP have been found to be strongly correlated in many studies. 28 Kettunen et al reported GlycA to be predictive of mortality risk in angiography patients 31 and has also been shown to be an early predictor of subclinical cardiovascular disease and treatment response in the early stage of rheumatoid arthritis 33 and in the development of gestational diabetes.…”

Section: Resultsmentioning

confidence: 99%

“…The NMR signals for GlycA at δ 2.03 and GlycB at δ 2.07 were integrated and significant intensity differences were found between groups, with SARS-CoV-2 positive samples containing the highest median concentrations of both GlycA and GlycB, followed by SARS-CoV-2 negative samples (Figure S2). GlycA has been shown to be a robust marker of inflammatory and proinflammatory conditions including inflammatory bowel disease, gestational diabetes, alcoholic liver disease, cardiovascular risk, rheumatoid arthritis and certain cancers, although GlycA is confounded by hemolysis and is not an appropriate marker of inflammatory conditions such as sickle cell disease . In general, GlycA has been found to be a better predictor of inflammatory conditions than either C reactive protein (CRP) or interleukin-6 (IL-6), and is independent of both, although GlycA and CRP have been found to be strongly correlated in many studies .…”

Section: Resultsmentioning

confidence: 99%

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NMR Spectroscopic Windows on the Systemic Effects of SARS-CoV-2 Infection on Plasma Lipoproteins and Metabolites in Relation to Circulating Cytokines

et al. 2021

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To investigate the systemic metabolic effects of SARS-CoV-2 infection, we analyzed 1 H NMR spectroscopic data on human blood plasma and co-modeled with multiple plasma cytokines and chemokines (measured in parallel). Thus, 600 MHz 1 H solvent-suppressed single-pulse, spin-echo, and 2D J-resolved spectra were collected on plasma recorded from SARS-CoV-2 rRT-PCR-positive patients (n = 15, with multiple sampling timepoints) and agematched healthy controls (n = 34, confirmed rRT-PCR negative), together with patients with COVID-19/influenza-like clinical symptoms who tested SARS-CoV-2 negative (n = 35). We compared the single-pulse NMR spectral data with in vitro diagnostic research (IVDr) information on quantitative lipoprotein profiles (112 parameters) extracted from the raw 1D NMR data. All NMR methods gave highly significant discrimination of SARS-CoV-2 positive patients from controls and SARS-CoV-2 negative patients with individual NMR methods, giving different diagnostic information windows on disease-induced phenoconversion. Longitudinal trajectory analysis in selected patients indicated that metabolic recovery was incomplete in individuals without detectable virus in the recovery phase. We observed four plasma cytokine clusters that expressed complex differential statistical relationships with multiple lipoproteins and metabolites. These included the following: cluster 1, comprising MIP-1β, SDF-1α, IL-22, and IL-1α, which correlated with multiple increased LDL and VLDL subfractions; cluster 2, including IL-10 and IL-17A, which was only weakly linked to the lipoprotein profile; cluster 3, which included IL-8 and MCP-1 and were inversely correlated with multiple lipoproteins. IL-18, IL-6, and IFN-γ together with IP-10 and RANTES exhibited strong positive correlations with LDL1−4 subfractions and negative correlations with multiple HDL subfractions. Collectively, these data show a distinct pattern indicative of a multilevel cellular immune response to SARS CoV-2 infection interacting with the plasma lipoproteome giving a strong and characteristic immunometabolic phenotype of the disease. We observed that some patients in the respiratory recovery phase and testing virus-free were still metabolically highly abnormal, which indicates a new role for these technologies in assessing full systemic recovery.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

NMR Spectroscopic Windows on the Systemic Effects of SARS-CoV-2 Infection on Plasma Lipoproteins and Metabolites in Relation to Circulating Cytokines

et al. 2021

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“…GlycA levels are decreased in SCL. [132] Human African Trypanosomiasis Significant increase of N-acetyl glycoprotein in HAT patients. [133]…”

Section: Sickle Cell Diseasementioning

confidence: 99%

“…This result goes against what is reflected in this review and has been attributed to the fact that hemolysis is observed in SCD patients but not in patients with other pathologies. It should also be noted that haptoglobin is one of the major proteins in the GlycA signal and in this case, it depletes rapidly during intravascular hemolysis [132].…”

Section: Sickle Cell Disease (Scd)mentioning

confidence: 99%

Title: Human Serum/Plasma Glycoprotein Analysis by 1H-NMR, an Emerging Method of Inflammatory Assessment

Fuertes-Martín

Correig

Vallvé

et al. 2020

JCM

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Several studies suggest that variations in the concentration of plasma glycoproteins can influence cellular changes in a large number of diseases. In recent years, proton nuclear magnetic resonance (1H-NMR) has played a major role as an analytical tool for serum and plasma samples. In recent years, there is an increasing interest in the characterization of glycoproteins through 1H-NMR in order to search for reliable and robust biomarkers of disease. The objective of this review was to examine the existing studies in the literature related to the study of glycoproteins from an analytical and clinical point of view. There are currently several techniques to characterize circulating glycoproteins in serum or plasma, but in this review, we focus on 1H-NMR due to its great robustness and recent interest in its translation to the clinical setting. In fact, there is already a marker in H-NMR representing the acetyl groups of the glycoproteins, GlycA, which has been increasingly studied in clinical studies. A broad search of the literature was performed showing a general consensus that GlycA is a robust marker of systemic inflammation. The results also suggested that GlycA better captures systemic inflammation even more than C-reactive protein (CRP), a widely used classical inflammatory marker. The applications reviewed here demonstrated that GlycA was potentially a key biomarker in a wide range of diseases such as cancer, metabolic diseases, cardiovascular risk, and chronic inflammatory diseases among others. The profiling of glycoproteins through 1H-NMR launches an encouraging new paradigm for its future incorporation in clinical diagnosis.

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“…Decreased GlycA in SCD has been reported before, and the plasma level of GlycA is confounded by hemolysis, thus not a suitable biomarker of inflammation in SCD. (Weisman, Meeks, Mendelsohn, Remaley, Sampson, Allen, Nichols et al 2018 ).…”

Section: Discussionmentioning

confidence: 99%

Metabolomic profiling for dyslipidemia in pediatric patients with sickle cell disease, on behalf of the IHCC consortium

Glessner

et al. 2022

Metabolomics

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Background Previous study has shown that dyslipidemia is common in patients with Sickle cell disease (SCD) and is associated with more serious SCD complications. Methods This study investigated systematically dyslipidemia in SCD using a state-of-art nuclear magnetic resonance (NMR) metabolomics platform, including 147 pediatric cases with SCD and 1234 controls without SCD. We examined 249 metabolomic biomarkers, including 98 biomarkers for lipoprotein subclasses, 70 biomarkers for relative lipoprotein lipid concentrations, plus biomarkers for fatty acids and phospholipids. Results Specific patterns of hypolipoproteinemia and hypocholesterolemia in pediatric SCD were observed in lipoprotein subclasses other than larger VLDL subclasses. Triglycerides are not significantly changed in SCD, except increased relative concentrations in lipoprotein subclasses. Decreased plasma FFAs (including total-FA, SFA, PUFA, Omega-6, and linoleic acid) and decreased plasma phospholipids were observed in SCD. Conclusion This study scrutinized, for the first time, lipoprotein subclasses in pediatric patients with SCD, and identified SCD-specific dyslipidemia from altered lipoprotein metabolism. The findings of this study depict a broad panorama of lipid metabolism and nutrition in SCD, suggesting the potential of specific dietary supplementation of the deficient nutrients for the management of SCD.

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GlycA is not a useful biomarker of inflammation in sickle cell disease

Cited by 3 publications

References 36 publications

NMR Spectroscopic Windows on the Systemic Effects of SARS-CoV-2 Infection on Plasma Lipoproteins and Metabolites in Relation to Circulating Cytokines

NMR Spectroscopic Windows on the Systemic Effects of SARS-CoV-2 Infection on Plasma Lipoproteins and Metabolites in Relation to Circulating Cytokines

Title: Human Serum/Plasma Glycoprotein Analysis by 1H-NMR, an Emerging Method of Inflammatory Assessment

Metabolomic profiling for dyslipidemia in pediatric patients with sickle cell disease, on behalf of the IHCC consortium

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