Immunoglobulin free light chains: an inflammatory biomarker of diabetes

Emerging Biomarkers in Cardiac Sarcoidosis and Other Inflammatory Cardiomyopathies

PURPOSE OF REVIEW

Cardiac sarcoidosis and other inflammatory cardiomyopathies are disorders causing cardiac inflammation and leading to heart failure, arrythmias and cardiac arrest. Diagnosis of these entities remains challenging and multimodal. Thus, there is a growing need to develop reliable biomarkers that can aid in the diagnosis. This review aims to summarize and highlight recent findings in the field of biomarkers for cardiac sarcoidosis and inflammatory cardiomyopathy.

RECENT FINDINGS

Multiple categories of biomarkers including novel molecules are being investigated with the latest evidence showing promising results. Some of these biomarkers are proven to be useful as diagnostic and prognostic aids in cardiac sarcoid and inflammatory cardiomyopathy. The identification of cost-effective and accurate biomarkers is useful not only for enhancing diagnostic accuracy but also for informing therapeutic decision-making processes. This advancement would facilitate the timely institution of immunosuppressive therapies, ultimately leading to improved patient outcomes.

Preliminary Investigation of Potential Early Biomarkers for Gestational Diabetes Mellitus: Insights from PTRPG and IGKV2D-28 Expression Analysis

Gestational diabetes mellitus (GDM) poses significant health risks to both mothers and infants, emphasizing the need for early detection strategies to mitigate its impact. However, the existing diagnostic methods, particularly the oral glucose tolerance test (OGTT) administered in the second or third trimester, show limitations in the detection of GDM during its early stages. This study aimed to explore the potential of the genes Protein Tyrosine Phosphatase Receptor-type Gamma (PTPRG) and Immunoglobulin Kappa Variable 2D-28 (IGKV2D-28) as early indicators for GDM among Filipino pregnant women. Utilizing reverse transcription-quantitative polymerase chain reaction (RT-qPCR), the gene expressions were analyzed in first-trimester blood samples obtained from 24 GDM and 36 non-GDM patients. The diagnostic performance of PTPRG and IGKV2D-28 was analyzed and evaluated using receiver operating characteristic (ROC) curves. The findings revealed elevated expression levels of PTPRG and IGKV2D-28 within the GDM cohort. Remarkably, PTPRG exhibited a sensitivity of 83%, while IGKV2D-28 demonstrated a specificity of 94% at determined cut-off values. Combining both genes yielded an improved but limited diagnostic accuracy with an area under the curve (AUC) of 0.63. This preliminary investigation of PTPRG and IGKV2D-28 sheds light on novel avenues for early GDM detection. While these findings are promising, further validation studies in larger cohorts are necessary to confirm these results and explore additional biomarkers to enhance diagnostic precision in GDM pregnancies and, ultimately, to improve maternal and fetal outcomes.

Effects of aerobic and resistance exercise for 9 months on serum free light chains in type 2 diabetes

Background and aims: Serum polyclonal free light chains (FLCs) levels are associated with overall survival in the general population, reflecting their utility as a biomarker of underlying immune activation and inflammation. Regular exercise is known to ameliorate low-grade inflammation in chronic diseases such as type 2 diabetes; however, the effects of different exercise training modalities on FLCs in adults with type 2 diabetes is unknown. This study investigated the effects of 9-month of aerobic, resistance or combined supervised exercise on serum FLCs in 164 patients with type 2 diabetes (age 58 ± 8 years; 63% female). Methods: 164 participants from the Health Benefits of Aerobic and Resistance Training in individuals with type 2 diabetes trial (HART-D) were randomly assigned to no exercise (n = 27), aerobic exercise alone (n = 41), resistance exercise alone (n = 49), or a combination of aerobic and resistance exercise (n = 47). Fasting serum samples were collected before and after completion of the intervention to quantify changes in kappa and lambda FLCs, and serum creatinine, using commercially-available ELISAs. Results: At baseline, combined kappa and lambda FLCs (FLC sum; calculated as kappa + lambda FLCs) were positively correlated with high-sensitive C-reactive protein (hs-CRP) (r = 0.237, p < 0.05) and fat mass (r = 0.162, p < 0.05), and negatively associated with aerobic fitness (r = -0.238, p < 0.05). While non-exercise controls exhibited an increase in FLCs over the 9-month study, exercise training blunted this increase (Δ FLC sum control arm: 3.25 ± 5.07 mg∙L-1 vs. all exercise arms: -0.252 ± 6.60 mg∙L-1, p < 0.05), regardless of exercise modality. Conclusion: Serum FLCs were associated with physical fitness and body composition in patients with type 2 diabetes. 9-month of exercise training prevented the accumulation of FLCs, regardless of exercise modality. Unlike hs-CRP-which did not change during the trial-serum FLCs may serve as a more sensitive biomarker of chronic low-grade inflammation in this population.

Application of SWATH Mass Spectrometry and Machine Learning in the Diagnosis of Inflammatory Bowel Disease Based on the Stool Proteome

Inflammatory bowel disease (IBD) flare-ups exhibit symptoms that are similar to other diseases and conditions, making diagnosis and treatment complicated. Currently, the gold standard for diagnosing and monitoring IBD is colonoscopy and biopsy, which are invasive and uncomfortable procedures, and the fecal calprotectin test, which is not sufficiently accurate. Therefore, it is necessary to develop an alternative method. In this study, our aim was to provide proof of concept for the application of Sequential Window Acquisition of All Theoretical Mass Spectra-Mass spectrometry (SWATH-MS) and machine learning to develop a non-invasive and accurate predictive model using the stool proteome to distinguish between active IBD patients and symptomatic non-IBD patients. Proteome profiles of 123 samples were obtained and data processing procedures were optimized to select an appropriate pipeline. The differentially abundant analysis identified 48 proteins. Utilizing correlation-based feature selection (Cfs), 7 proteins were selected for proceeding steps. To identify the most appropriate predictive machine learning model, five of the most popular methods, including support vector machines (SVMs), random forests, logistic regression, naive Bayes, and k-nearest neighbors (KNN), were assessed. The generated model was validated by implementing the algorithm on 45 prospective unseen datasets; the results showed a sensitivity of 96% and a specificity of 76%, indicating its performance. In conclusion, this study illustrates the effectiveness of utilizing the stool proteome obtained through SWATH-MS in accurately diagnosing active IBD via a machine learning model.

An interdisciplinary therapy for lifestyle change is effective in improving psychological and inflammatory parameters in women with grade I obesity

Obesity and depression, disorders associated with inflammation, have high incidences in women. Understanding the derangements present in the initial phase of obesity may point to factors that could help avoiding disease aggravation. The present study aimed at investigating the effects of a 6-months interdisciplinary therapy for weight loss in women with grade I obesity. Before and after the therapy, 37 middle-aged women donated blood and responded to questionnaires for depression and anxiety symptoms. Inflammatory parameters were evaluated in serum and a preliminary screening of the plasma proteome was performed. The therapy decreased anthropometric, psychological scores, and serum levels of inflammatory parameters. Depression and anxiety scores correlated positively with some inflammatory parameters. The proteomic analysis showed changes in proteins related to cholesterol metabolism and inflammatory response. Interdisciplinary therapy improves anthropometric and inflammatory statuses and ameliorating psychological symptoms. The decrease of MCP-1 levels after interdisciplinary therapy has not been reported so far, at the best of our knowledge. The present demonstration of positive associations of inflammatory markers and psychological scores indicate that these mediators may be useful to monitor psychological status in obesity. The present proteome data, although preliminary, pointed to plasma alterations indicative of improvement of inflammation after interdisciplinary therapy.

Nuclear Factor-κB is a Prime Candidate for the Diagnosis and Control of Inflammatory Cardiovascular Disease

Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is responsible for the regulation of genes involved in inflammation and immune responses. NF-κB may play an important role in cardiovascular diseases (CVDs), atherosclerosis and diabetes. Several therapeutic agents used for the treatment of CVDs and diabetes, such as pimobendan and sodium-glucose cotransporter 2 inhibitors, exert anti-inflammatory effects by inhibiting NF-κB activation; anti-inflammatory therapy may have beneficial effects in CVDs and diabetes. Several pharmacological agents and natural compounds may inhibit NF-κB, and these agents alone or in combination may be used to treat various inflammatory diseases. Immunoglobulin-free light chains could be surrogate biomarkers of NF-κB activation and may be useful for evaluating the efficacy of these agents. This review discusses recent advances in our understanding of how the NF-κB signalling pathway controls inflammation, metabolism and immunity, and how improved knowledge of these pathways may lead to better diagnostics and therapeutics for various human diseases.

Management of Atrial Fibrillation Using Immunoglobulin Free Light Chains, Novel Biomarkers of Inflammation

AF is the most common cardiac arrhythmia. There is growing evidence that inflammatory mechanisms play an important role in its pathogenesis; inflammasome activation contributes to the onset and progression of AF. An increase in NOD-like-receptor-pyrin domain-containing-3 (NLRP3) inflammasome activation releases proinflammatory cytokines that activate nuclear factor (NF)-κB, which regulates the production of immunoglobulin free light chains (FLCs). Serum FLC levels are increased in patients with AF, and FLCs are biomarkers of inflammation. Inflammasomes and NF-κB may be targets for anti-inflammatory strategies to prevent and treat AF when FLC levels are elevated. This review discusses the role of inflammation in the pathogenesis of AF, as well as FLCs as novel inflammatory biomarkers for the management of AF.

Novel Biomarkers of Inflammation for the Management of Diabetes: Immunoglobulin-Free Light Chains

Virus infection, inflammation and genetic factors are important factors in the pathogenesis of diabetes mellitus. The nuclear factor-kappa B (NF-κB) is a family of transcription factors that bind the enhancer of the κ light chain gene of B cell immunoglobulin. NF-κB plays an essential role in the activation and development of B cells, and the activation of NF-κB is critical in the inflammation and development of diabetes mellitus. Recently, immunoglobulin-free light chain (FLC) λ was found to be increased in the sera of patients with diabetes mellitus, and the FLC λ and κ/λ ratios are more specific and sensitive markers for the diagnosis of diabetes relative to glycated hemoglobin A1c. Thus, FLCs may be promising biomarkers of inflammation that could relate to the activation of NF-κB. We suggest that NF-κB could be a target for an anti-inflammatory strategy in preventing and treating diabetes when FLCs are modified. FLCs could be a surrogate endpoint in the management of diabetes. In this review, the role of inflammation in the pathogenesis of diabetes, as well as the novel inflammatory biomarkers of FLCs for the management of diabetes, are discussed.

Targeting Inflammation in the Diagnosis, Management, and Prevention of Cardiovascular Diseases

Inflammation plays an important role in the development and progression of cardiovascular diseases (CVDs). Hypertension and hyperlipidemia are the key risk factors of CVDs and induce inflammation in the heart and vessels. Unhealthy diet, infection, and smoking coupled with genetic factors lead to the development of CVDs as well as induce inflammation. Risk factors of CVDs such as hypertension and hyperlipidemia along with diabetes activate nuclear factor kappa B, which regulates the transcription of immunoglobulin free light chain (FLC) κ in B cells and the production of multiple inflammatory molecules, leading to inflammation. FLCs are novel biomarkers of inflammation, and their levels have been associated with overall mortality in a general population and with cardiovascular outcomes. In this review, the role of inflammation in the pathogenesis of CVDs, new biomarkers of inflammation, and dietary options counterbalancing inflammatory processes, such as the polyphenol-rich French maritime pine bark extract Pycnogenol, are discussed.

Increased concentrations of myeloperoxidase in serum and serum extracellular vesicles are associated with type 2 diabetes mellitus

BACKGROUND

Inflammatory response plays a critical role in the initiation and progression of type 2 diabetes mellitus (T2DM). Myeloperoxidase (MPO), a leukocyte-derived protagonist, exerts its proinflammatory properties in many complications. We explored the associations between serum extracellular vesicle (EV)-derived MPO as well as serum MPO and T2DM.

METHODS

We performed a cross-sectional study in 151 individuals, including 93 patients with T2DM and 58 non-T2DM controls. The concentrations of serum EV-derived MPO and serum MPO were measured by Luminex Assay.

RESULTS

Our data showed that serum EV-derived MPO concentrations and serum MPO concentrations were significantly higher in T2DM patients compared with non-T2DM subjects. In addition, multivariate logistic regression analysis revealed that serum EV-derived MPO as well as serum MPO was independently associated with the presence of T2DM even after adjusting for confounding factors (OR = 1.836 /1 ng EV-derived MPO, 95% CI = 1.395-2.417, P < 0.001; OR = 4.135 /10 ng serum MPO, 95% CI = 2.285-7.483, P < 0.001). Furthermore, serum MPO showed marginally higher discriminatory accuracy than serum EV-derived MPO in screening T2DM (AUC = 0.858; AUC = 0.779).

CONCLUSION

Increased concentrations of the inflammatory marker MPO either in serum or in serum EVs were independently associated with T2DM.

Serum free light chain is associated with histological activity and cirrhosis in patients with chronic hepatitis B

BACKGROUND

The antiviral immune response is the main cause of hepatocyte damage and inflammatory necrosis. The serum free light chain, reflecting the immune function of B-cells, is strongly associated with inflammation and disease activity. We aimed to investigate the association of serum free light chain with the progression of chronic hepatitis B.

METHODS

A total of 208 eligible chronic hepatitis B patients who had undergone a liver biopsy were studied. Serum free light chains of all patients were measured by turbidimetry using an immunoassay. Liver histology was assessed according to the METAVIR scoring system (which grades the stage of fibrosis on a five-point scale, F0 = no fibrosis to F4 = cirrhosis, and histological activity on a four-point scale, A0 = no activity to A3 = severe activity). The association of serum free light chains with histological activity and fibrosis progression was evaluated.

RESULTS

The concentration of serum free light chains in CHB patients increased gradually with histological activity and fibrosis progression. The intensity of histological activity was significantly correlated with the serum free kappa chain (r = 0.658, P < 0.001) and the serum free lambda chain (0.675, P < 0.001). The stages of fibrosis were correlated with the serum free kappa chain (r = 0.683, P < 0.001) and serum free lambda chain (0.664, P < 0.001). After adjusting for age, sex and other synergic factors, the serum free kappa chain remained a potential risk factor, but the serum free lambda chain was no longer associated with liver cirrhosis. Similar to FIB-4 and RPR, the serum free kappa chain exhibited excellent performance in the prediction of liver cirrhosis. The AUCs of serum free Kappa chain, FIB-4 and RPR were 0.873, 0.880 and 0.895, respectively, which were significantly higher than those of the AAR and APRI (0.718 and 0.746).

CONCLUSION

Our work revealed that serum free light chains were associated with histological activity and cirrhosis in chronic hepatitis B, which could play a crucial role in the immunopathogenesis of HBV-associated cirrhosis. In addition, free kappa light chain could be a useful predictor of liver cirrhosis.

Diagnosis and treatment of HCV heart diseases

INTRODUCTION

Hepatitis C virus (HCV) infection is an important cause of a variety of otherwise unexplained heart diseases and myocardial injury. A high prevalence of HCV infection has been noted in patients with hypertrophic cardiomyopathy, dilated cardiomyopathy, arrhythmogenic right ventricular dysplasia/cardiomyopathy and myocarditis. Various arrhythmias, conduction disturbances and QT prolongation were also associated with HCV infection. A possible role of HCV infection in the pathogenesis of diabetes and atherosclerosis, and the role of immunogenetics of HCV cardiomyopathies is discussed. Recent studies suggest that mononuclear cells may be the major target of HCV, and clinical applications to test this new hypothesis are discussed.

AREAS COVERED

In this review, we will evaluate the evidence that HCV causes various cardiovascular diseases, and discuss on the pathogenesis of these disorders.

EXPERT OPINION

HCV is the cause of many different forms of heart disease worldwide, but their existence has not been recognized by most of cardiologists. The recognition and diagnosis are indispensable for the early treatment of these diseases. The diverse clinical manifestation of HCV infection and the presence of multiple extrahepatic disease syndromes could be explained by a new hypothesis that the target of HCV is leukocytes.

Salivary Biomarkers in COVID-19 Patients: Towards a Wide-Scale Test for Monitoring Disease Activity

The ongoing outbreak of coronavirus disease 2019 (COVID-19), which impairs the functionality of several organs, represents a major threat to human health. One of the hardest challenges in the fight against COVID-19 is the development of wide-scale, effective, and rapid laboratory tests to control disease severity, progression, and possible sudden worsening. Monitoring patients in real-time is highly demanded in this pandemic era when physicians need reliable and quantitative tools to prioritize patients’ access to intensive care departments. In this regard, salivary biomarkers are extremely promising, as they allow for the fast and non-invasive collection of specimens and can be repeated multiple times. Methods: We compare salivary levels of immunoglobulin A subclasses (IgA1 and IgA2) and free light chains (kFLC and λFLC) in a cohort of 29 SARS-CoV-2 patients and 21 healthy subjects. Results: We found that each biomarker differs significantly between the two groups, with p-values ranging from 10⁻⁸ to 10⁻⁴. A Receiving Operator Curve analysis shows that λFLC level is the best-suited candidate to discriminate the two groups (AUC = 0.96), with an accuracy of 0.94 (0.87–1.00 95% CI), a precision of 0.91 (0.81–1.00 95% CI), a sensitivity of 1.00 (0.96–1.00 95% CI), and a specificity of 0.86 (0.70–1.00 95% CI). Conclusion: These results suggest λFLC as an ideal indicator of patient conditions. This hypothesis is strengthened by the consideration that the λFLC half-life (approximately 6 h) is significantly shorter than the IgA one (21 days), thus confirming the potential of λFLC for effectively monitoring patients’ fluctuation in real-time.