Characteristics of lupus and lupus nephritis at a tertiary care center in Lebanon

Advances in Mass Spectrometry-Based Blood Metabolomics Profiling for Non-Cancer Diseases: A Comprehensive Review

Blood metabolomics profiling using mass spectrometry has emerged as a powerful approach for investigating non-cancer diseases and understanding their underlying metabolic alterations. Blood, as a readily accessible physiological fluid, contains a diverse repertoire of metabolites derived from various physiological systems. Mass spectrometry offers a universal and precise analytical platform for the comprehensive analysis of blood metabolites, encompassing proteins, lipids, peptides, glycans, and immunoglobulins. In this comprehensive review, we present an overview of the research landscape in mass spectrometry-based blood metabolomics profiling. While the field of metabolomics research is primarily focused on cancer, this review specifically highlights studies related to non-cancer diseases, aiming to bring attention to valuable research that often remains overshadowed. Employing natural language processing methods, we processed 507 articles to provide insights into the application of metabolomic studies for specific diseases and physiological systems. The review encompasses a wide range of non-cancer diseases, with emphasis on cardiovascular disease, reproductive disease, diabetes, inflammation, and immunodeficiency states. By analyzing blood samples, researchers gain valuable insights into the metabolic perturbations associated with these diseases, potentially leading to the identification of novel biomarkers and the development of personalized therapeutic approaches. Furthermore, we provide a comprehensive overview of various mass spectrometry approaches utilized in blood metabolomics research, including GC-MS, LC-MS, and others discussing their advantages and limitations. To enhance the scope, we propose including recent review articles supporting the applicability of GC×GC-MS for metabolomics-based studies. This addition will contribute to a more exhaustive understanding of the available analytical techniques. The Integration of mass spectrometry-based blood profiling into clinical practice holds promise for improving disease diagnosis, treatment monitoring, and patient outcomes. By unraveling the complex metabolic alterations associated with non-cancer diseases, researchers and healthcare professionals can pave the way for precision medicine and personalized therapeutic interventions. Continuous advancements in mass spectrometry technology and data analysis methods will further enhance the potential of blood metabolomics profiling in non-cancer diseases, facilitating its translation from the laboratory to routine clinical application.

Lupus nephritis or not? A simple and clinically friendly machine learning pipeline to help diagnosis of lupus nephritis

OBJECTIVE

Diagnosis of lupus nephritis (LN) is a complex process, which usually requires renal biopsy. We aim to establish a machine learning pipeline to help diagnosis of LN.

METHODS

A cohort of 681 systemic lupus erythematosus (SLE) patients without LN and 786 SLE patients with LN was established, and a total of 95 clinical, laboratory data and 17 meteorological indicators were collected. After tenfold cross-validation, the patients were divided into training set and test set. The features selected by collective feature selection method of mutual information (MI) and multisurf were used to construct the models of logistic regression, decision tree, random forest, naive Bayes, support vector machine (SVM), light gradient boosting (LGB), extreme gradient boosting (XGB), and artificial neural network (ANN), the models were compared and verified in post-analysis.

RESULTS

Collective feature selection method screens out antistreptolysin (ASO), retinol binding protein (RBP), lupus anticoagulant 1 (LA1), LA2, proteinuria and other features, and the hyperparameter optimized XGB (ROC: AUC = 0.995; PRC: AUC = 1.000, APS = 1.000; balance accuracy: 0.990) has the best performance, followed by LGB (ROC: AUC = 0.992; PRC: AUC = 0.997, APS = 0.977; balance accuracy: 0.957). The worst performance is naive Bayes model (ROC: AUC = 0.799; PRC: AUC = 0.822, APS = 0.823; balance accuracy: 0.693). In the composite feature importance bar plots, ASO, RF, Up/Ucr, and other features play important roles in LN.

CONCLUSION

We developed and validated a new and simple machine learning pathway for diagnosis of LN, especially the XGB model based on ASO, LA1, LA2, proteinuria, and other features screened out by collective feature selection.

Prevalence and Patterns of Renal Involvement Among Patients With Systemic Lupus Erythematous at a Tertiary Center

BACKGROUND

Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder characterized by widespread inflammation and damage to multiple organ systems. One of the most common and severe manifestations of SLE is lupus nephritis (LN).

OBJECTIVES

To determine the prevalence of LN among subjects with SLE and to identify the demographic, clinical, and laboratory parameters of SLE in subjects diagnosed with LN.

METHODS

This is a descriptive study conducted at a tertiary hospital. Medical records were reviewed from outpatients who visited between January 2015 and October 2019 and who has fulfilled the classification criteria for diagnosis of SLE and had LN.

RESULTS

Among 365 patients with SLE, 36% had LN. The most prevalent World Health Organization class of LN was IV, which significantly correlated with both abnormal creatinine levels and nephrotic range proteinuria. Elevated serum creatinine correlated with the presence of hypertension and thrombocytopenia. Cutaneous manifestations were noted to be present in 100% of LN patients, followed by arthritis and/or arthralgia (82.9%), anemia (94.6%), and lymphopenia (87.6%).

CONCLUSION

This study aids in the recognition of the demographic, clinical, laboratory features, and the histological patterns of LN patients in Saudi Arabia, that probably has a role in the development and disease progression. A significant correlation was found between abnormal kidney function and hypertension, thrombocytopenia and nephrotic range proteinuria. The presence of World Health Organization class IV LN correlated with both impaired kidney function and nephrotic range proteinuria.

Elevated mean platelet volume in oral lichen planus and increased blood urea nitrogen level in its red-form: an observational study

Background

This retrospective observational study aims to assess platelet count, mean platelet volume (MPV), blood biochemical tests for liver and kidney function in Chinese oral lichen planus (OLP) patients.

Methods

Eighty pathologically confirmed OLP patients and 51 healthy controls were enrolled. Data on full blood count and biochemical tests were obtained from the electronic medical record system of the hospital.

Results

MPV was elevated in OLP patients compared to controls (10.68 ± 0.97 fL versus 10.33 ± 0.89 fL, P = 0.042) while platelet count showed no difference between them. Red-form OLP group had increased blood urea nitrogen (BUN, 5.24 ± 1.15 mmol/L versus 4.69 ± 0.98 mmol/L, P = 0.036) than white-form OLP group. By contrast, there were no differences between those two groups in the other variables including MPV, alanine aminotransferase (ALT), aspartate aminotransferase (AST), and creatinine. In terms of C-reactive protein (CRP), 92.5% of the OLP patients had a value of less than 3.48 mg/L. Besides, 75% of the OLP patients were overweight with body mass index (BMI) more than 25 kg/m².

Conclusions

These findings indicate MPV might play roles in inflammation in OLP. The red-form OLP might be associated with damage or reduction of kidney function.

Diffusion tensor imaging of renal cortex in lupus nephritis

PURPOSE

To evaluate the diagnostic value of diffusion tensor imaging (DTI) of renal cortex in assessment of lupus nephritis (LN) and prediction of its pathological subtypes.

METHODS

Prospective study was performed upon 39 female patients with pathologically proven LN and 16 sex- and age-matched healthy controls. Patients and controls underwent DTI of kidney. Mean diffusivity (MD) and fractional anisotropy (FA) of renal cortex were calculated by two radiologists. LN patients were pathologically classified into either non-proliferative (n = 15) or proliferative (n = 24).

RESULTS

Mean MD of renal cortex in LN was significantly lower (p = 0.001) than that of controls with cut-off (2.16 and 2.2 X10^-3mm²/s), area under curve (AUC) of (0.92, 0.94) and accuracy of (91%, 89%) for both observers. Mean FA of renal cortex in LN was significantly higher (p = 0.001) than that of controls with cut-off (0.20, 0.21), AUC of (0.86, 0.82) and accuracy of (86%, 84%) for both observers. Renal cortex MD and FA in non-proliferative LN were significantly different (p = 0.001) from that of proliferative LN for both observers. There was excellent inter-observer agreement of MD and FA (ICC = 0.96 and 0.81).

CONCLUSION

MD and FA of renal cortex may help to assess renal affection in LN patients and predict its pathological subtypes.

Clinical and histopathological features and short-term outcomes of lupus nephritis: a prospective study of 100 Egyptian patients

OBJECTIVE

The short-term outcomes of lupus nephritis (LN) are variable and unpredictable among individuals. We aimed to evaluate the clinical and histopathological features and short-term renal outcomes in LN patients.

METHODS

This was a prospective cohort study carried out at nephrology and rheumatology units in Egypt between 2018 and 2019. A total of 100 patients with biopsy-proven LN were studied. Patients were evaluated for response after six months.

RESULTS

The female-to-male ratio was 8.1:1. About 70% of patients were hypertensive at disease onset, with rates for classes I, II, III, IV, V and VI LN being 1%, 7%, 20%, 53%, 14% and 6%, respectively. Among the immunosuppressive drugs used for induction, mycophenolate mofetil (MMF) represented the most commonly used (44%) followed by cyclophosphamide (CYC; 37%). After six months of follow-up, about two thirds of patients achieved remission. There was no significant difference in remission rate between MMF and CYC. On multivariate analysis, serum creatinine (SCr) at presentation was the most significant predictor of renal recovery. According to the receiver operating characteristic curve, the cut-off value of SCr was 1.6 mg/dL, with a sensitivity of 76% and specificity of 71% predicting renal recovery. Repeat renal biopsy was needed in 10 patients; class and treatment strategy changed in 40% and 70% of them, respectively.

CONCLUSION

Our findings in Egyptian LN patients compare favourably with most studies.