Combined plasma metabolomic and transcriptomic analysis identify histidine as a biomarker and potential contributor in SLE pathogenesis

A review on the novel biomarkers of systemic lupus erythematosus discovered via metabolomic profiling

Systemic lupus erythematosus (SLE) is a multifaceted autoimmune disease affecting various body organs and systems. The diagnosis of SLE and its complications is based on evident clinical symptoms, serological marker levels, and pathological findings. Some serological markers have a low sensitivity and specificity, and biopsy procedures are invasive in nature. Hence, metabolomics has emerged as a valuable tool for SLE screening and categorization. Its application has contributed significantly to identifying SLE pathogenesis, improving clinical diagnosis, and developing treatment approaches. This review provides an overview of the utilization of metabolomics in the study of SLE, focusing on advancements in understanding the disease's pathogenesis, aiding in diagnosis, and monitoring treatment efficacy.

Biomarkers for systemic lupus erythematosus: A scoping review

BACKGROUND

In recent years, newly discovered potential biomarkers have great research potential in the diagnosis, disease activity prediction, and treatment of systemic lupus erythematosus (SLE).

OBJECTIVE

In this study, a scoping review of potential biomarkers for SLE over several years has identified the extent to which studies on biomarkers for SLE have been conducted, the specificity, sensitivity, and diagnostic value of potential biomarkers of SLE, the research potential of these biomarkers in disease diagnosis, and activity detection is discussed.

METHODS

In PubMed and Google Scholar databases, "SLE," "biomarkers," "predictor," "autoimmune diseases," "lupus nephritis," "neuropsychiatric SLE," "diagnosis," "monitoring," and "disease activity" were used as keywords to systematically search for SLE molecular biomarkers published from 2020 to 2024. Analyze and summarize the literature that can guide the article.

CONCLUSIONS

Recent findings suggest that some potential biomarkers may have clinical application prospects. However, to date, many of these biomarkers have not been subjected to repeated clinical validation. And no single biomarker has sufficient sensitivity and specificity for SLE. It is not scientific to choose only one or several biomarkers to judge the complex disease of SLE. It may be a good direction to carry out a meta-analysis of various biomarkers to find SLE biomarkers suitable for clinical use, or to evaluate SLE by combining multiple biomarkers through mathematical models. At the same time, advanced computational methods are needed to analyze large data sets and discover new biomarkers, and strive to find biomarkers that are sensitive and specific enough to SLE and can be used in clinical practice, rather than only staying in experimental research and data analysis.

Identification of amino acids metabolomic profiling in human plasma distinguishes lupus nephritis from systemic lupus erythematosus

Lupus nephritis (LN) is an immunoinflammatory glomerulonephritis associated with renal involvement in systemic lupus erythematosus (SLE). Given the close relationship between plasma amino acids (AAs) and renal function, this study aimed to elucidate the plasma AA profiles in LN patients and identify key AAs and diagnostic patterns that distinguish LN patients from those with SLE and healthy controls. Participants were categorized into three groups: normal controls (NC), SLE, and LN. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was employed to quantify AA levels in human plasma. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were utilized to identify key AAs. The diagnostic capacity of the models was assessed using receiver operating characteristic (ROC) curve analysis and area under the ROC curve (AUC) values. Significant alterations in plasma AA profiles were observed in LN patients compared to the SLE and NC groups. The OPLS-DA model effectively separated LN patients from the SLE and NC groups. A joint model using histidine (His), lysine (Lys), and tryptophan (Trp) demonstrated exceptional diagnostic performance, achieving an AUC of 1.0 with 100% sensitivity, specificity, and accuracy in predicting LN. Another joint model comprising arginine (Arg), valine (Val), and Trp also exhibited robust predictive performance, with an AUC of 0.998, sensitivity of 93.80%, specificity of 100%, and accuracy of 95.78% in distinguishing between SLE and LN. The joint forecasting models showed excellent predictive capabilities in identifying LN and categorizing lupus disease status. This approach provides a novel perspective for the early identification, prevention, treatment, and management of LN based on variations in plasma AA levels.

The influence and therapeutic effect of microbiota in systemic lupus erythematosus

Systemic erythematosus lupus (SLE) is an autoimmune disease involving multiple organs that poses a serious risk to the health and life of patients. A growing number of studies have shown that commensals from different parts of the body and exogenous pathogens are involved in SLE progression, causing barrier disruption and immune dysregulation through multiple mechanisms. However, they sometimes alleviate the symptoms of SLE. Many factors, such as genetic susceptibility, metabolism, impaired barriers, food, and sex hormones, are involved in SLE, and the microbiota drives the development of SLE either by depending on or interacting with these factors. Among these, the crosstalk between genetic susceptibility, metabolism, and microbiota is a hot topic of research and is expected to lay the groundwork for the amelioration of the mechanism, diagnosis, and treatment of SLE. Furthermore, the microbiota has great potential for the treatment of SLE. Ideally, personalised therapeutic approaches should be developed in combination with more specific diagnostic methods. Herein, we provide a comprehensive overview of the role and mechanism of microbiota in lupus of the intestine, oral cavity, skin, and kidney, as well as the therapeutic potential of the microbiota.

Functional Genome Analysis for Immune Cells Provides Clues for Stratification of Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is caused by a combination of genetic and environmental factors. Recently, analysis of a functional genome database of genetic polymorphisms and transcriptomic data from various immune cell subsets revealed the importance of the oxidative phosphorylation (OXPHOS) pathway in the pathogenesis of SLE. In particular, activation of the OXPHOS pathway is persistent in inactive SLE, and this activation is associated with organ damage. The finding that hydroxychloroquine (HCQ), which improves the prognosis of SLE, targets toll-like receptor (TLR) signaling upstream of OXPHOS suggests the clinical importance of this pathway. IRF5 and SLC15A4, which are regulated by polymorphisms associated with SLE susceptibility, are functionally associated with OXPHOS as well as blood interferon activity and metabolome. Future analyses of OXPHOS-associated disease-susceptibility polymorphisms, gene expression, and protein function may be useful for risk stratification of SLE.