Impaired HDL Metabolism Links GlycA, A Novel Inflammatory Marker, with Incident Cardiovascular Events

Genetic association of inflammatory marker GlycA with lung function and respiratory diseases

Association of circulating glycoprotein acetyls (GlycA), a systemic inflammation biomarker, with lung function and respiratory diseases remain to be investigated. We examined the genetic correlation, shared genetics, and potential causality of GlycA (N = 115,078) with lung function and respiratory diseases (N = 497,000). GlycA showed significant genetic correlation with FEV1 (rg = -0.14), FVC (rg = -0.18), asthma (rg = 0.21) and COPD (rg = 0.31). We consistently identified ten shared loci (including chr3p21.31 and chr8p23.1) at both SNP and gene level revealing potential shared biological mechanisms involving ubiquitination, immune response, Wnt/β-catenin signaling, cell growth and differentiation in tissues or cells including blood, epithelium, fibroblast, fetal thymus, and fetal intestine. Genetically elevated GlycA was significantly correlated with lung function and asthma susceptibility (354.13 ml decrement of FEV1, 442.28 ml decrement of FVC, and 144% increased risk of asthma per SD increment of GlycA) from MR analyses. Our findings provide insights into biological mechanisms of GlycA in relating to lung function, asthma, and COPD.

Towards clinical application of GlycA and GlycB for early detection of inflammation associated with (pre)diabetes and cardiovascular disease: recent evidence and updates

Cardiometabolic diseases are associated with low-grade inflammation early in life and persists into old age. The long latency period presents opportunities for early detection, lifestyle modification and intervention. However, the performance of conventional biomarker assays to detect low-grade inflammation has been variable, particularly for early-stage cardiometabolic disorder including prediabetes and subclinical atherosclerotic vascular inflammation. During the last decade, the application of nuclear magnetic resonance (NMR) spectroscopy for metabolic profiling of biofluids in translational and epidemiological research has advanced to a stage approaching clinical application. Proton (1H)-NMR profiling induces no destructible physical changes to specimens, and generates quantitative signals from deconvoluted spectra that are highly repeatable and reproducible. Apart from quantitative analysis of amino acids, lipids/lipoproteins, metabolic intermediates and small proteins, 1H-NMR technology is unique in being able to detect composite signals of acute-phase and low-grade inflammation indicated by glycosylated acetyls (GlycA) and N-acetylneuraminic acid (sialic acid) moieties (GlycB). Different from conventional immunoassays that target epitopes and are susceptible to conformational variation in protein structure and binding, GlycA and GlycB signals are stable over time, and maybe complementary as well as superior to high-sensitivity C-reactive protein and other inflammatory cytokines. Here we review the physicochemical principles behind 1H-NMR profiling of GlycA and GlycB, and the available evidence supporting their potential clinical application for the prediction of incident (pre)diabetes, cardiovascular disease, and adverse outcomes.

Both LDL and HDL particle concentrations associate positively with an increased risk of developing microvascular complications in patients with type 2 diabetes: lost protection by HDL (Zodiac-63)

BACKGROUND

Triglyceride-rich lipoproteins (TRL) and low-density lipoproteins (LDL) are associated positively whereas high-density lipoproteins (HDL) are associated inversely with the development of new-onset type 2 diabetes (T2D). Here we studied potential associations between these lipoprotein particle concentrations and the risk of developing microvascular complications in patients with established T2D.

METHODS

Lipoprotein particle concentrations (TRLP, LDLP, and HDLP) were determined in 278 patients with T2D participating in a primary care-based longitudinal cohort study (Zwolle Outpatient Diabetes project Integrating Available Care [ZODIAC] study) leveraging the Vantera nuclear magnetic resonance (NMR) platform using the LP4 algorithm. Associations between lipoprotein particles and incident microvascular complications (nephropathy, neuropathy, and retinopathy) were assessed using Cox proportional hazards regression models.

RESULTS

In total, 136 patients had microvascular complications at baseline. During a median follow-up of 3.2 years, 49 (34.5%) of 142 patients without microvascular complications at baseline developed new-onset microvascular complications. In multivariable Cox proportional hazards regression analyses, both total LDLP and HDLP concentrations, but not total TRLP concentrations, were positively associated with an increased risk of developing any microvascular complications after adjustment for potential confounding factors, including age, sex, disease duration, HbA1c levels, history of macrovascular complications, and statin use (adjusted hazard ratio [HR] per 1 SD increment: 1.70 [95% CI 1.24-2.34], P < 0.001 and 1.63 [95% CI 1.19-2.23], P = 0.002, respectively). When analyzing each microvascular complication individually, total LDLP concentrations were positively associated with retinopathy (adjusted HR 3.35, 95% CI 1.35-8.30, P = 0.009) and nephropathy (adjusted HR 2.13, 95% CI 1.27-3.35, P = 0.004), and total HDLP concentrations with neuropathy (adjusted HR 1.77, 95% CI 1.15-2.70, P = 0.009). No significant associations were observed for lipoprotein particle subfractions.

CONCLUSIONS

Total lipoprotein particle concentrations of both LDL and HDL associate positively with an increased risk of developing microvascular complications in T2D. We propose that the protective role of HDL on the development of microvascular complications may be lost in established T2D.

Association of Advanced Lipoprotein Subpopulation Profiles with Insulin Resistance and Inflammation in Patients with Type 2 Diabetes Mellitus

Plasma lipoproteins exist as several subpopulations with distinct particle number and size that are not fully reflected in the conventional lipid panel. In this study, we sought to quantify lipoprotein subpopulations in patients with type 2 diabetes mellitus (T2DM) to determine whether specific lipoprotein subpopulations are associated with insulin resistance and inflammation markers. The study included 57 patients with T2DM (age, 61.14 ± 9.99 years; HbA1c, 8.66 ± 1.60%; mean body mass index, 35.15 ± 6.65 kg/m²). Plasma lipoprotein particles number and size were determined by nuclear magnetic resonance spectroscopy. Associations of different lipoprotein subpopulations with lipoprotein insulin resistance (LPIR) score and glycoprotein acetylation (GlycA) were assessed using multi-regression analysis. In stepwise regression analysis, VLDL and HDL large particle number and size showed the strongest associations with LPIR (R² = 0.960; p = 0.0001), whereas the concentrations of the small VLDL and HDL particles were associated with GlycA (R² = 0.190; p = 0.008 and p = 0.049, respectively). In adjusted multi-regression analysis, small and large VLDL particles and all sizes of lipoproteins independently predicted LPIR, whereas only the number of small LDL particles predicted GlycA. Conventional markers HbA1c and Hs-CRP did not exhibit any significant association with lipoprotein subpopulations. Our data suggest that monitoring insulin resistance-induced changes in lipoprotein subpopulations in T2DM might help to identify novel biomarkers that can be useful for effective clinical intervention.

Glycosylation and Cardiovascular Diseases

Cardiovascular disease (CVD) is the leading cause of death worldwide, accounting for approximately 18 million deaths in 2017. Coronary artery disease is the predominant cause of death from CVD, followed by stroke. Owing to recent technological advancements, glycans and glycosylation patterns of proteins have been investigated in association with CVD risk factors and clinical events. These studies have found significant associations of glycans as biomarkers of systemic inflammation and major CVD risk factors and events. While more limited, studies have also shown that glycans may be useful for monitoring response to anti-inflammatory therapies and may be responsive to changes in lifestyle, particularly in patients with chronic inflammatory diseases. Glycans capture summative risk information related to inflammatory, immune, and signaling pathways and are promising biomarkers for CVD risk prediction and therapeutic monitoring.

High-Density Lipoprotein Cholesterol: A Component of the Metabolic Syndrome with a New Role in Lung Function

Background

A considerable uncertainty exists about the relationship between adult metabolic syndrome (MS) and obstructive lung disease (OLD), perhaps owing to systemic inflammation. Therefore, this study aimed to investigate the relationship between MS (with its components) and the patterns of lung function impairment.

Methods

The participants in this study were 3978 adults aged 30-78 years from the baseline cohort of the Ningxia Cohort Study. The participants underwent pulmonary function tests, questionnaire surveys, physical examinations, and analysis of blood specimens.

Results

No significant difference in the prevalence of OLD was observed between male (15.9%) and female (14.2%) participants. After adjusting for possible confounding factors (e.g., age and family income), impaired lung function was found to be related to some MS components, such as abdominal obesity, high blood pressure, and low levels of high-density lipoprotein cholesterol (HDL-C) (all P < 0.05).

Conclusions

As an important component of MS, abdominal obesity is related to impaired lung function. Surprisingly, this study found that increased HDL-C levels could accelerate the decline of lung function; it also suggests that in the presence of different metabolic health conditions, especially abdominal obesity and low levels of HDL-C, various metabolic indicators should be comprehensively considered to prevent the decline of lung function. This partly explains the increase in the incidence of two or more chronic diseases. Therefore, the prevention of chronic diseases should shift from single-disease prevention to a comprehensive consideration of multi-disease prevention in the future. Therefore, a more sensitive evaluation of the role of HDL-C in lung function is warranted.

High Density Lipoprotein Cholesterol Efflux Capacity and Atherosclerosis in Cardiovascular Disease: Pathophysiological Aspects and Pharmacological Perspectives

Over the years, the relationship between high-density lipoprotein (HDL) and atherosclerosis, initially highlighted by the Framingham study, has been revealed to be extremely complex, due to the multiple HDL functions involved in atheroprotection. Among them, HDL cholesterol efflux capacity (CEC), the ability of HDL to promote cell cholesterol efflux from cells, has emerged as a better predictor of cardiovascular (CV) risk compared to merely plasma HDL-cholesterol (HDL-C) levels. HDL CEC is impaired in many genetic and pathological conditions associated to high CV risk such as dyslipidemia, chronic kidney disease, diabetes, inflammatory and autoimmune diseases, endocrine disorders, etc. The present review describes the current knowledge on HDL CEC modifications in these conditions, focusing on the most recent human studies and on genetic and pathophysiologic aspects. In addition, the most relevant strategies possibly modulating HDL CEC, including lifestyle modifications, as well as nutraceutical and pharmacological interventions, will be discussed. The objective of this review is to help understanding whether, from the current evidence, HDL CEC may be considered as a valid biomarker of CV risk and a potential pharmacological target for novel therapeutic approaches.

Nuclear Magnetic Resonance Derived Biomarkers for Evaluating Cardiometabolic Risk in Youth and Young Adults Across the Spectrum of Glucose Tolerance

Youth with obesity have an increased risk for cardiometabolic disease, but identifying those at highest risk remains a challenge. Four biomarkers that might serve this purpose are "by products" of clinical NMR LipoProfile^® lipid testing: LPIR (Lipoprotein Insulin Resistance Index), GlycA (inflammation marker), BCAA (total branched-chain amino acids), and glycine. All are strongly related to insulin resistance and type 2 diabetes (T2DM) in adults (glycine inversely) and are independent of biological and methodological variations in insulin assays. However, their clinical utility in youth is unclear. We compared fasting levels of these biomarkers in 186 youth (42 lean normal glucose tolerant (NGT), 88 obese NGT, 23 with prediabetes (PreDM), and 33 with T2DM. All four biomarkers were associated with obesity and glycemia in youth. LPIR and GlycA were highest in youth with PreDM and T2DM, whereas glycine was lowest in youth with T2DM. While all four were correlated with HOMA-IR (Homeostatic Model Assessment for Insulin Resistance), LPIR had the strongest correlation (LPIR: r = 0.6; GlycA: r = 0.4, glycine: r = -0.4, BCAA: r = 0.2, all P < 0.01). All four markers correlated with HbA1c (LPIR, GlycA, BCAA: r ≥ 0.3 and glycine: r = -0.3, all P < 0.001). In multi-variable regression models, LPIR, GlycA, and glycine were independently associated with HOMA-IR (Adjusted R² = 0.473, P < 0.001) and LPIR, glycine, and BCAA were independently associated with HbA1c (Adjusted R² = 0.33, P < 0.001). An LPIR index of >44 was associated with elevated blood pressure, BMI, and dyslipidemia. Plasma NMR-derived markers were related to adverse markers of cardiometabolic risk in youth. LPIR, either alone or in combination with GlycA, should be explored as a non-insulin dependent predictive tool for development of insulin resistance and diabetes in youth.

CLINICAL TRIAL REGISTRATION

Clinicaltrials.gov, identifier NCT:02960659.

GlycA measured by NMR spectroscopy is associated with disease activity and cardiovascular disease risk in chronic inflammatory diseases

GlycA is a biomarker of systemic inflammation, quantifying both the protein concentrations and glycosylation states of several acute phase proteins. GlycA has been shown to be associated with both subclinical atherosclerosis and with cardiovascular disease (CVD). GlycA levels are higher in acute and chronic inflammation. During ongoing systemic inflammatory processes, GlycA specific acute phase reactants and proteins undergo circulating concentration and glycosylation pattern changes, and these alterations are reflected in the GlycA NMR signal. Additionally, levels associate with ongoing disease severity in individuals with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and psoriasis thus capturing active inflammation. Furthermore, in these disease states, GlycA is associated with cardiovascular disease (CVD) independent of traditional risk factors including C-reactive protein (CRP). Finally, GlycA levels decrease with exercise, weight loss, and systemic anti-inflammatory agents. Therefore, GlycA appears to be a promising new composite biomarker of active systemic inflammation including assessing CVD risk in patients with inflammatory diseases.

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Patients with chronic inflammatory disorders are at increased risk for cardiovascular diseasenot captured by traditional risk factors.

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GlycA is a biomarker of acute phase reactants by NMR spectroscopy which captures disease activity in human inflammatory diseases.

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GlycA associates with cardiovascular disease and offers a tool to monitor primary disease activity and assess CVD risk in inflammatory diseases.

Omics-Driven Biomarkers of Psoriasis: Recent Insights, Current Challenges, and Future Prospects

Advances in omics technologies have made it possible to unravel biomarkers from different biological levels. Intensive studies have been carried out to uncover the dysregulations in psoriasis and to identify molecular signatures associated with the pathogenesis of psoriasis. In this review, we presented an overview of the current status of the omics-driven biomarker research and emphasized the transcriptomic, epigenomic, proteomic, metabolomic, and glycomic signatures proposed as psoriasis biomarkers. Furthermore, insights on the limitations and future directions of the current biomarker discovery strategies were discussed, which will continue to comprehend broader visions of psoriasis research, diagnosis, and therapy especially in the context of personalized medicine.

Neopterin is Associated with Disease Severity and Outcome in Patients with Non-Ischaemic Heart Failure

Inflammation and immune activation play an important role in the pathogenesis of cardiac remodelling in patients with heart failure. The aim of this study was to assess whether biomarkers of inflammation and immune activation are linked to disease severity and the prognosis of heart failure patients. In 149 patients (65.8% men, median age 49.7 years) with heart failure from nonischaemic cardiomyopathy, the biomarkers neopterin and C-reactive protein were tested at the time of diagnosis. Patients were followed-up for a median of 58 months. During follow-up, nineteen patients died, five had a heart transplantation, two needed a ventricular assistance device, and twenty-one patients had to be hospitalised because of heart failure decompensation. Neopterin concentrations correlated with N-terminal prohormone of brain natriuretic peptide (NT-proBNP) concentrations (rs = 0.399, p < 0.001) and rose with higher New York Heart Association (NYHA) class (I: 5.60 nmol/L, II: 6.90 nmol/L, III/IV: 7.80 nmol/L, p = 0.033). Higher neopterin levels were predictive for an adverse outcome (death or hospitalisation due to HF decompensation), independently of age and sex and of established predictors in heart failure such as NYHA class, NT-proBNP, estimated glomerular filtration rate (eGFR), and left ventricular ejection fraction (LV-EF) (HR 2.770; 95% CI 1.419-5.407; p = 0.003). Patients with a neopterin/eGFR ratio ≥ 0.133 (as a combined marker for immune activation and kidney function) had a more than eightfold increased risk of reaching an endpoint compared to patients with a neopterin/eGFR ratio ≤0.065 (HR 8.380; 95% CI 2.889-24.308; p < 0.001). Neopterin is associated with disease severity and is an independent predictor of prognosis in patients with heart failure.