Characterization of Lipids in Saliva, Tears and Minor Salivary Glands of Sjögren's Syndrome Patients Using an HPLC/MS-Based Approach

Metal-Organic Framework-Based Surface-Enhanced Raman Scattering Sensing Platform for Trace Malondialdehyde Detection in Tears

Disease biomarkers in tears are crucial for clinical diagnosis and health monitoring. However, the limited volume of tear samples, low concentration of tear biomarkers, and complex tear composition present challenges for precise testing. We introduce a spot-on testing platform of metal-organic framework (MOF)-based surface-enhanced Raman scattering (SERS) capillary column, which is capable of target molecules selective separation and enrichment for tear biomarkers in situ detection. It consists of Au nanostars for effective SERS signal and a porous MOF shell for separating impurities through molecular sieving effect. This platform allows for simultaneous collection and detection of tear, capturing the disease biomarker malondialdehyde in tears with a 9.38 × 10-9 mol/L limit of detection. Moreover, we designed a hand-held device based on this tubular SERS sensor, successfully diagnosing patients with dry eye disease. This functional capillary column enables noninvasive and rapid diagnosis of biomarkers in biofluids, providing potential for disease diagnosis and healthcare monitoring.

Salivary lipid changes in young adult tobacco smokers and e-cigarette users: a hidden risk to oral health?

STUDY DESIGN

A cross-sectional, age- and gender-matched study was conducted to investigate the effects of different forms of nicotine delivery on salivary lipid profiles among young adult novice smokers compared to non-smokers.

OBJECTIVE

To assess the effect of smoking traditional cigarettes, e-cigarettes, and heated tobacco products (HTPs) on the levels of specific sphingolipids (sphingosine, sphinganine, and sphingosine-1-phosphate), various ceramides, and lipid peroxidation products [malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE)] in both unstimulated and stimulated saliva samples collected from healthy young adults who had been smoking for 1-3 years and used only 1 of the 3 nicotine delivering methods.

METHODS

Selection criteria included healthy young adults under 30 years old, with normal BMI and typical diet composition, and with no oral inflammatory lesions, orthodontic/dental appliances, or recent intake of medications or supplements. A total of 75 smokers and 25 non-smokers were enrolled in the study. Smokers were categorized into three groups, each comprising 25 individuals: traditional cigarette smokers, e-cigarette users, and HTPs smokers. Saliva samples were collected and analyzed for sphingolipid concentrations using ultra-high-performance liquid chromatography-tandem mass spectrometry. The concentrations of MDA and 4-HNE were measured using colorimetric and ELISA assays, respectively.

RESULTS

The average smoking intensity in the traditional cigarette group was 10 cigarettes per day. Salivary sphingolipid and ceramides concentrations were significantly lower in smokers compared to non-smokers across all nicotine delivery methods (p < 0.0001). Moreover, traditional cigarette smokers exhibited higher levels of 4-HNE and MDA in both stimulated and unstimulated saliva, compared to non-smokers (p < 0.01). In stimulated saliva, both MDA and 4-HNE in e-cigarette users, and MDA in HTPs users, showed significantly lower concentrations than their comparators in traditional cigarette smokers (p < 0.01).

CONCLUSION

Different nicotine delivery methods impact salivary lipid profile during the initial period of smoking habit. Reduced sphingolipids and elevated lipid peroxidation products suggest a disturbed lipid balance in the oral cavity due to enhanced oxidative stress within the salivary glands of novice smokers.

Salivary fatty acids in humans: a comprehensive literature review

Fatty acids (FAs) exert diverse biological functions in humans, influencing physiological responses and, ultimately, health and disease risk. The analysis of FAs in human samples has significant implications and attracts interest in diagnostics and research. The standard method for assessing FA profiles involves the collection of blood samples, which can be inconvenient, invasive, and potentially painful, particularly for young individuals outside hospital settings. Saliva emerged as a promising alternative for evaluating FA profiles in both clinical and research settings. However, to the best of our knowledge, an updated synthesis of the related evidence is unavailable. This comprehensive review aims to summarize data on FA analysis and highlight the potential of the use of salivary FAs as a biomarker in health and disease. Over the past decade, there has been a growing interest in studying salivary FAs in chronic diseases, and more recently, researchers have explored the prognostic value of FAs in acute conditions to check the availability of a non-invasive sampling methodology. A deeper understanding of salivary FAs could have relevant implications both for healthy individuals and patients, particularly in elucidating the correlation between the dietary lipidic content and salivary FA level, Finally, it is crucial to address the standardization of the methods as the sampling, processing, and analysis of saliva are heterogeneous among studies, and limited correlation between blood FAs and salivary FAs is available.

Impact of Smoking on Salivary Lipid Profile and Oxidative Stress in Young Adults: A Comparative Analysis between Traditional Cigarettes, E-Cigarettes, and Heat-Not-Burn Products

BACKGROUND Smoking nicotine is considered to be one of the most harmful addictions, leading to the development of a number of health complications, including many pathologies in the oral cavity. The aim of this study was to examine the effect of smoking traditional cigarettes, e-cigarettes, and heat-not-burn products on profiles of salivary lipids and lipid peroxidation products in the unstimulated and stimulated saliva of healthy young adults with a smoking habit of up to 3 years. MATERIAL AND METHODS We enrolled 3 groups of 25 smoking patients each and a control group matched for age, gender, and oral status. In saliva collected from patients from the study groups and participants from the control group, the concentrations of sphingolipids: sphingosine, sphinganine, sphingosine-1-phosphate, ceramides, and salivary lipid peroxidation products - malondialdehyde (MDA) and 4-hydroxynonenal (HNE) - were measured. The normality of distribution was assessed using the Shapiro-Wilk test. For comparison of the results, one-way analysis of variance (ANOVA) followed by post hoc Tukey test was used. RESULTS We demonstrated that each type of smoking causes a decrease in the concentration of salivary lipids, and there was an increased concentration of salivary MDA and 4-HNE. CONCLUSIONS Smoking in the initial period of addiction leads to an increase in the concentration of lipid peroxidation products through increased oxidative stress, leading to disturbance of the lipid balance of the oral cavity (eg, due to damage to cell membranes).

Using machine learning model explanations to identify proteins related to severity of meibomian gland dysfunction

Meibomian gland dysfunction is the most common cause of dry eye disease and leads to significantly reduced quality of life and social burdens. Because meibomian gland dysfunction results in impaired function of the tear film lipid layer, studying the expression of tear proteins might increase the understanding of the etiology of the condition. Machine learning is able to detect patterns in complex data. This study applied machine learning to classify levels of meibomian gland dysfunction from tear proteins. The aim was to investigate proteomic changes between groups with different severity levels of meibomian gland dysfunction, as opposed to only separating patients with and without this condition. An established feature importance method was used to identify the most important proteins for the resulting models. Moreover, a new method that can take the uncertainty of the models into account when creating explanations was proposed. By examining the identified proteins, potential biomarkers for meibomian gland dysfunction were discovered. The overall findings are largely confirmatory, indicating that the presented machine learning approaches are promising for detecting clinically relevant proteins. While this study provides valuable insights into proteomic changes associated with varying severity levels of meibomian gland dysfunction, it should be noted that it was conducted without a healthy control group. Future research could benefit from including such a comparison to further validate and extend the findings presented here.

Salivary biomarkers: novel noninvasive tools to diagnose chronic inflammation

Several chronic disorders including type 2 diabetes (T2D), obesity, heart disease and cancer are preceded by a state of chronic low-grade inflammation. Biomarkers for the early assessment of chronic disorders encompass acute phase proteins (APP), cytokines and chemokines, pro-inflammatory enzymes, lipids and oxidative stress mediators. These substances enter saliva through the blood flow and, in some cases, there is a close relation between their salivary and serum concentration. Saliva can be easily collected and stored with non-invasive and cost-saving procedures, and it is emerging the concept to use it for the detection of inflammatory biomarkers. To this purpose, the present review aims to discuss the advantages and challenges of using standard and cutting-edge techniques to discover salivary biomarkers which may be used in diagnosis/therapy of several chronic diseases with inflammatory consequences with the pursuit to possibly replace conventional paths with detectable soluble mediators in saliva. Specifically, the review describes the procedures used for saliva collection, the standard approaches for the measurement of salivary biomarkers and the novel methodological strategies such as biosensors to improve the quality of care for chronically affected patients.

Plasma lipidomics of primary biliary cholangitis and its comparison with Sjögren's syndrome

Background

Abnormal lipid metabolism is common in patients with primary biliary cholangitis (PBC). PBC and Sjögren's syndrome (SS) frequently coexist in clinical practice; however, the lipid characteristics of both diseases are unknown. Therefore, we aimed to analyze the plasma lipid profiles of both diseases.

Methods

Plasma samples from 60 PBC patients, 30 SS patients, and 30 healthy controls (HC) were collected, and untargeted lipidomics was performed using ultrahigh-performance liquid chromatography high-resolution mass spectrometry. Potential lipid biomarkers were screened through an orthogonal projection to latent structure discriminant analysis and further evaluated using receiver operating characteristic (ROC) analysis.

Results

A total of 115 lipids were differentially upregulated in PBC patients compared with HC. Seventeen lipids were positively associated with the disease activity of PBC, and ROC analysis showed that all of these lipids could differentiate between ursodeoxycholic acid (UDCA) responders and UDCA non-responders. The top six lipids based on the area under the curve (AUC) values were glycerophosphocholine (PC) (16:0/16:0), PC (18:1/18:1), PC (42:2), PC (16:0/18:1), PC (17:1/14:0), and PC (15:0/18:1). In comparison with SS, 44 lipids were found to be differentially upregulated in PBC. Additionally, eight lipids were found to have a good diagnostic performance of PBC because of the AUC values of more than 0.9 when identified from SS and HC groups, which were lysophosphatidylcholines (LysoPC) (16:1), PC (16:0/16:0), PC (16:0/16:1), PC (16:1/20:4), PC (18:0/20:3), PC (18:1/20:2), PC (20:0/22:5), and PC (20:1/22:5).

Conclusion

Our study revealed differentially expressed lipid signatures in PBC compared with HC and SS. PC is the main lipid species associated with disease activity and the UDCA response in patients with PBC.

Ceramides in Autoimmune Rheumatic Diseases: Existing Evidence and Therapeutic Considerations for Diet as an Anticeramide Treatment

Autoimmune rheumatic diseases (AIRDs) constitute a set of connective tissue disorders and dysfunctions with akin clinical manifestations and autoantibody responses. AIRD treatment is based on a comprehensive approach, with the primary aim being achieving and attaining disease remission, through the control of inflammation. AIRD therapies have a low target specificity, and this usually propels metabolic disturbances, dyslipidemias and increased cardiovascular risk. Ceramides are implicated in inflammation through several different pathways, many of which sometimes intersect. They serve as signaling molecules for apoptosis, altering immune response and driving endothelial dysfunction and as regulators in the production of other molecules, including sphingosine 1-phosphate (S1P) and ceramide 1-phosphate (C1P). With lipid metabolism being severely altered in AIRD pathology, several studies show that the concentration and variety of ceramides in human tissues is altered in patients with rheumatic diseases compared to controls. As a result, many in vitro and some in vivo (animal) studies research the potential use of ceramides as therapeutic targets in rheumatoid arthritis (RA), ankylosing spondylitis, systemic lupus erythematosus, fibromyalgia syndrome, primary Sjögren's syndrome, systemic sclerosis, myositis, systemic vasculitis and psoriatic arthritis. Furthermore, the majority of ceramide synthesis is diet-centric and, as a result, dietary interventions may alter ceramide concentrations in the blood and affect health. Subsequently, more recently several clinical trials evaluated the possibility of distinct dietary patterns and nutrients to act as anti-ceramide regimes in humans. With nutrition being an important component of AIRD-related complications, the present review details the evidence regarding ceramide levels in patients with AIRDs, the results of anti-ceramide treatments and discusses the possibility of using medical nutritional therapy as a complementary anti-ceramide treatment in rheumatic disease.

Predicting an unstable tear film through artificial intelligence

Dry eye disease is one of the most common ophthalmological complaints and is defined by a loss of tear film homeostasis. Establishing a diagnosis can be time-consuming, resource demanding and unpleasant for the patient. In this pilot study, we retrospectively included clinical data from 431 patients with dry eye disease examined in the Norwegian Dry Eye Clinic to evaluate how artificial intelligence algorithms perform on clinical data related to dry eye disease. The data was processed and subjected to numerous machine learning classification algorithms with the aim to predict decreased tear film break-up time. Moreover, feature selection techniques (information gain and information gain ratio) were applied to determine which clinical factors contribute most to an unstable tear film. The applied machine learning algorithms outperformed baseline classifications performed with ZeroR according to included evaluation metrics. Clinical features such as ocular surface staining, meibomian gland expressibility and dropout, blink frequency, osmolarity, meibum quality and symptom score were recognized as important predictors for tear film instability. We identify and discuss potential limitations and pitfalls.

Tear Biomarkers in Alzheimer's and Parkinson's Diseases, and Multiple Sclerosis: Implications for Diagnosis (Systematic Review)

Biological material is one of the most important aspects that allow for the correct diagnosis of the disease, and tears are an interesting subject of research because of the simplicity of collection, as the well as the relation to the components similar to other body fluids. In this review, biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), and multiple sclerosis (MS) in tears are investigated and analyzed. Records were obtained from the PubMed and Google Scholar databases in a timeline of 2015-2022. The keywords were: tear film/tear biochemistry/tear biomarkers + diseases (AD, PD, or MS). The recent original studies were analyzed, discussed, and biomarkers present in tears that can be used for the diagnosis and management of AD, PD, and MS diseases were shown. α-synTotal and α-synOligo, lactoferrin, norepinephrine, adrenaline, epinephrine, dopamine, α-2-macroglobulin, proteins involved in immune response, lipid metabolism and oxidative stress, apolipoprotein superfamily, and others were shown to be biomarkers in PD. For AD as potential biomarkers, there are: lipocalin-1, lysozyme-C, and lacritin, amyloid proteins, t-Tau, p-Tau; for MS there are: oligoclonal bands, lipids containing choline, free carnitine, acylcarnitines, and some amino acids. Information systematized in this review provides interesting data and new insight to help improve clinical outcomes for patients with neurodegenerative disorders.