Albumin-to-globulin ratio (AGR) as a potential marker of predicting lupus nephritis in Chinese patients with systemic lupus erythematosus

Non-linear relationship of serum albumin-to-globulin ratio and cognitive function in American older people: a cross-sectional national health and nutrition examination survey 2011-2014 (NHANES) study

Background

Inflammation and liver function are associated with cognitive decline and dementia. Little is known about the serum albumin-to-globulin ratio on cognitive function.

Objective

The objective of this study was to investigate the association between albumin-to-globulin ratio and cognitive function among the American older people.

Methods

The public data available on the US National Health and Nutrition Examination Survey (NHANES) from 2011 to 2014 was used for this cross-sectional study. Participants aged ≥60 years completed the cognitive function assessments, including word learning and recall modules from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), the animal fluency (AF) test, and the digit symbol substitution test (DSST). A composite cognition score was calculated to evaluate global cognition. The univariate and multivariate linear regression analysis, curve fitting, a threshold effect, along with a subgroup analysis and interaction tests were conducted.

Results

Serum albumin-to-globulin ratio (per 0.1 unit) was positively associated DSST score (β = 0.36, 95% CI: 0.21, 0.51), AF score (β = 0.1, 95% CI: 0.04, 0.16) and global cognition score (β = 0.05, 95% CI: 0.02, 0.07), after being fully adjusted, while albumin-to-globulin ratio was not related to CERAD score (β = 0.05, 95% CI: -0.02, 0.12). A non-linear was observed in the dose-response relationship between albumin-to-globulin ratio and global cognition (P for non-linearity < 0.001). The subgroup analysis was overall stable, yet the interaction test was significant for age on global cognition (P for interaction = 0.036).

Conclusion

The findings of this cross-sectional study suggested a positive and non-linear association between albumin-to-globulin ratio and cognitive function in the American older people. Maintaining albumin-to-globulin ratio with an appropriate range may be one of the therapeutic strategies to limit the progression of cognitive decline for the older people.

Albumin to globulin ratio (AGR) in systemic lupus erythematosus: correlation with disease activity

OBJECTIVE

To investigate the role of albumin-to-globulin ratio (AGR) in systemic lupus erythematosus (SLE) and its relationship with disease activity.

METHODS

This retrospective study consecutively selected patients with SLE and healthy controls. Patients were divided into three groups according to the SLE Disease Activity Index 2000 (SLEDAI-2K): group 1 (mild disease activity, SLEDAI-2K ≤ 6), group 2 (moderate disease activity, SLEDAI-2K 7-12) and group 3 (severe disease activity, SLEDAI-2K > 12). Predictors of SLE disease activity were analysed by ordinal logistical regression.

RESULTS

A total of 101 Chinese patients with SLE and 75 healthy Chinese controls were included. Patients with SLE had lower AGR values than healthy individuals, and group 3 patients with SLE displayed lower AGR values than those in group 1, but similar values to group 2. AGR was inversely correlated with SLEDAI-2K (r = -0.543). Ordinal logistic regression analysis showed that lower AGR (β = -1.319) and lower complement C4 (β = -1.073) were independent risk factors for SLE disease activity.

CONCLUSIONS

AGR was decreased in patients with SLE and may be utilized as a useful inflammatory biomarker for monitoring SLE disease activity.

Early diagnosis and clinical application of systemic lupus erythematosus based on a nomogram model

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease involving multi-system and multi-organ dysfunction, and is easily misdiagnosed early in the disease course. We aimed to accurately predict early SLE nomogram to provide a reference basis for the early clinical diagnosis of SLE. Methods: We retrospectively analyzed 167 patients who were first diagnosed with SLE at Fengxian District Central Hospital, Shanghai, between March 2017 and October 2022. Three groups of 129 physically healthy subjects, 67 patients with rheumatoid arthritis, and 40 patients with rashes were selected as controls during the same period. Patients with SLE and control group were randomly divided into training (n = 217) and validation (n = 141) group. Univariate and multivariate analyses were used to identify independent risk factors for early SLE diagnosis. The independent risk factors for diagnosis were used to construct a nomogram to predict early SLE. Results: Based on the training group, three variables were identified as independently influencing early SLE: platelets (odds ratio OR = 0.993, P = 0.047), albumin (OR = 0.833, P = 0.007), and complement component 1q (OR = 0.956, P = 0.000). The precision of the nomogram was assessed using C-index values and calibration plot diagrams. The C-index values were 0.929 for training group and 0.898 for validation group. Both the training group and validation group calibration curves showed good predicted outcomes. Conclusion: The construction of a nomogram can accurately predict the risk of early SLE. The model showed good discriminatory power and calibration for use in the diagnosis of SLE, providing a visual tool and reference basis for the early diagnosis of SLE.

Lupus Nephritis Biomarkers: A Critical Review

Lupus nephritis (LN), a major complication in individuals diagnosed with systemic lupus erythematosus, substantially increases morbidity and mortality. Despite marked improvements in the survival of patients with severe LN over the past 50 years, complete clinical remission after immunosuppressive therapy is achieved in only half of the patients. Therefore, timely detection of LN is vital for initiating prompt therapeutic interventions and improving patient outcomes. Biomarkers have emerged as valuable tools for LN detection and monitoring; however, the complex role of these biomarkers in LN pathogenesis remains unclear. Renal biopsy remains the gold standard for the identification of the histological phenotypes of LN and guides disease management. However, the molecular pathophysiology of specific renal lesions remains poorly understood. In this review, we provide a critical, up-to-date overview of the latest developments in the field of LN biomarkers.

Analysis of risk factors and development of a nomogram prediction model for lupus nephritis in systemic lupus erythematosus patients

BACKGROUND

This study aimed to explore risk factors for lupus nephritis (LN) in systemic lupus erythematosus (SLE) patients and establish a Nomogram prediction model based on LASSO-logistic regression.

METHODS

The clinical and laboratory data of SLE patients in Meishan People's Hospital from July 2012 to December 2021 were analyzed retrospectively. All SLE patients were divided into two groups with or without LN. Risk factors were screened based on LASSO-logistic regression analysis, and a Nomogram prediction model was established. The receiver operating characteristic curve, calibration curves, and decision curve analysis were adopted to evaluate the performance of the Nomogram model.

RESULTS

A total of 555 SLE patients were enrolled, including 303 SLE patients with LN and 252 SLE patients without LN. LASSO regression and multivariate logistic regression analyses showed that ESR, mucosal ulcer, proteinuria, and hematuria were independent risk factors for LN in SLE patients. The four clinical features were incorporated into the Nomogram prediction model. Results showed that calibration curve was basically close to the diagonal dotted line with slope 1 (ideal prediction case), which proved that the prediction ability of the model was acceptable. In addition, the decision curve analysis showed that the Nomogram prediction model could bring net clinical benefits to patients when the threshold probability was 0.12-0.54.

CONCLUSION

Four clinical indicators of ESR, mucosal ulcer, proteinuria, and hematuria were independent risk factors for LN in SLE patients. The predictive power of the Nomogram model based on LASSO-logistic regression was acceptable and could be used to guide clinical work.

Short-term clinical observations of belimumab in the treatment of recently diagnosed systemic lupus erythematosus

OBJECTIVE

To explore the therapeutic effectiveness and safety of belimumab in the treatment of recently diagnosed systemic lupus erythematosus (SLE).

METHODS

Between January 2019 and February 2022, a total of 30 patients who had been recently diagnosed with SLE were selected for 6 months of belimumab treatment at the Department of Rheumatology and Immunology, Tianjin First Central Hospital. Laboratory test results and related adverse reactions were recorded at baseline and after treatment.

RESULTS

Participants' white blood cell counts and complement 3, complement 4, and hemoglobin levels were higher after treatment than at baseline. Participants' immunoglobulin G and immunoglobulin M levels, SLE Disease Activity Index 2000 scores, glucocorticoid doses, erythrocyte sedimentation rates, and serum albumin/globulin ratios were lower after treatment. These differences were all statistically significant (p &lt; .05).

CONCLUSION

Belimumab was safe and effective in patients recently diagnosed with SLE and might help to reduce the use of glucocorticoids and to improve anemia with few adverse reactions. Belimumab might be applied in the treatment of patients recently diagnosed with SLE with high disease activity.

Risk Factors and the Role of the Albumin-to-Globulin Ratio in Predicting Recurrence Among Patients with Idiopathic Granulomatous Mastitis

Background

Idiopathic granulomatous mastitis (IGM) is a rare inflammatory disease of the breast with a high recurrence rate. The serum albumin to globulin ratio (AGR) is a relatively novel biomarker in inflammatory diseases, and one whose role in the recurrence of IGM remains unknown. This study primarily investigated the potential risk factors for IGM recurrence and whether AGR can be used as a predictive factor.

Methods

Patients diagnosed with IGM from pathology reports between 2016 and 2021 were enrolled in the study, and their medical records were analyzed retrospectively. The patients were divided into two groups – recurrence and non-recurrence. Clinical, demographic characteristics, and laboratory parameters were compared.

Results

Eighty-five patients were included in the study, recurrence being detected in 16 (18.8%) of these, with a median follow-up time of 39.99±18.93 months. No relationship was determined between childbearing, breastfeeding, disease severity, or therapeutic approaches and IGM recurrence. While AGR was significantly lower in the recurrence group (p < 0.001), neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) results were comparable in the two groups (p = 0.472 and p = 0.421, respectively). Multivariate analysis identified low AGR (odds ratio (OR): 50.7, 95% CI 5.93–434.1 P < 0.001) and smoking (OR: 4.45, 95% CI 1.04–18.9 P = 0.044) as independent risk factors for IGM recurrence.

Conclusion

The study findings indicated that AGR at a cut-off value of ≤1.179 at diagnosis and smoking exhibited a remarkable performance in predicting the recurrence of IGM. Developing new risk stratification systems for IGM recurrences and using AGR in these classifications may increase the success of treatment.

Trial Registration

This study was registered with ClinicalTrials.gov, NCT05409586.

Efficiency of Disease and Disease Activity Diagnosis Models of Systemic Lupus Erythematosus Based on Protein Array Analysis

Background

Systemic lupus erythematosus (SLE) has become increasingly common in the clinic and requires complicated evidence of both clinical manifestations and laboratory examinations. Additionally, the assessment and monitoring of lupus disease activity are challenging. We hope to find efficient biomarkers and establish diagnostic models of SLE.

Materials and Methods

We detected and quantified 40 proteins using a quantitative protein array of 76 SLE patients and 21 healthy controls, and differentially expressed proteins were screened out by volcano plot. Logistic regression analysis was used to recognize biomarkers that could be enrolled in the disease diagnosis model and disease activity diagnosis model, and a receiver operating characteristic (ROC) curve was drawn to evaluate the efficiency of the model. A nomogram was depicted for convenient and visualized application of our models in the clinic. Decision curves and clinical impact curves were also plotted to validate our models.

Results

The protein levels of TNF RII, BLC, TNF RI, MIP-1b, eotaxin, MIG, MCSF, IL-8, MCP-1, and IL-10 showed significant differences between patients with SLE and healthy controls. TNF RII and MIP-1b were included in the SLE diagnosis model with logistic regression analysis, and the value of the area under the ROC curve (AUC) was 0.914 (95% confidence interval (CI), 0.859-0.969). TNF RII, BLC, and MIP-1b were enrolled in the disease activity diagnosis model, and the AUC value was 0.823 (95% CI 0.729-0.916). Both of the models that we established showed high efficiency. Additionally, the three protein biomarkers contained in the disease activity distinguish model provided additional benefit to conventional biomarkers in predicting active lupus.

Conclusions

The disease diagnosis model and disease activity diagnosis model that we developed based on protein array chip results showed high efficiency in differentiating patients with SLE from healthy controls and recognizing SLE patients with high disease activity, and they have also been validated. This implied that they might greatly benefit clinical decisions and the treatment of SLE.

The predictive value of fibrinogen‐to‐albumin ratio in the active, severe active, and poor prognosis of systemic lupus erythematosus: A single‐center retrospective study

Objective

To evaluate the prediction and effect of fibrinogen‐to‐albumin ratio (FAR) on active, severe active, and poor prognosis of systemic lupus erythematosus (SLE).

Methods

One hundred and sixty‐eight patients with SLE who were treated in our hospital were enrolled, the clinical data, laboratory indexes, and disease prognosis of all patients were collected and analyzed.

Results

Triglyceride (TG), FAR, ESR, and anti‐dsDNA (+) were the influencing factors, while complement 3 (C3) was the protective factor of active SLE, the odds ratio (OR) values were 2.968, 3.698, 2.114, 2.727, and 0.652, respectively (p < 0.05). FAR, ESR, and anti‐dsDNA (+) were the influencing factors, while C3 was the protective factor of severe active SLE, the OR values were 3.791, 1.953, 2.187, and 0.742, respectively (p < 0.05). SLE disease activity index (SLEDAI), TG, FAR, and anti‐dsDNA (+) were the influencing factors, while C3 was the protective factor of poor prognosis SLE, the OR values were 3.024, 2.293, 3.012, 2.323, and 0.801, respectively (p < 0.05). FAR and FIB were positively correlated with SLEDAI, while ALB was negatively correlated with SLEDAI, the related coefficient (r) were 0.398, 0.267, −0.270, respectively. The receiver operating curve (ROC) analysis showed that the predictive values of FAR for active, severe active and poor prognosis SLE were 0.769, 0.769, and 0.734, respectively, were significant higher than FIB and ALB (p < 0.05).

Conclusion

Fibrinogen‐to‐albumin ratio was an influencing factor of active, severe active, and poor prognosis SLE had higher predictive value than FIB and ALB for the activity and prognosis of SLE.

Radiomics analysis of contrast-enhanced CT for staging liver fibrosis: an update for image biomarker

BACKGROUND

To establish and validate a radiomics-based model for staging liver fibrosis at contrast-enhanced CT images.

MATERIALS AND METHODS

This retrospective study developed two radiomics-based models (R-score: radiomics signature; R-fibrosis: integrate radiomic and serum variables) in a training cohort of 332 patients (median age, 59 years; interquartile range, 51-67 years; 256 men) with biopsy-proven liver fibrosis who underwent contrast-enhanced CT between January 2017 and December 2020. Radiomic features were extracted from non-contrast, arterial and portal phase CT images and selected using the least absolute shrinkage and selection operator (LASSO) logistic regression to differentiate stage F3-F4 from stage F0-F2. Optimal cutoffs to diagnose significant fibrosis (stage F2-F4), advanced fibrosis (stage F3-F4) and cirrhosis (stage F4) were determined by receiver operating characteristic curve analysis. Diagnostic performance was evaluated by area under the curve, Obuchowski index, calibrations and decision curve analysis. An internal validation was conducted in 111 randomly assigned patients (median age, 58 years; interquartile range, 49-66 years; 89 men).

RESULTS

In the validation cohort, R-score and R-fibrosis (Obuchowski index, 0.843 and 0.846, respectively) significantly outperformed aspartate transaminase-to-platelet ratio (APRI) (Obuchowski index, 0.651; p < .001) and fibrosis-4 index (FIB-4) (Obuchowski index, 0.676; p < .001) for staging liver fibrosis. Using the cutoffs, R-fibrosis and R-score had a sensitivity range of 70-87%, specificity range of 71-97%, and accuracy range of 82-86% in diagnosing significant fibrosis, advanced fibrosis and cirrhosis.

CONCLUSION

Radiomic analysis of contrast-enhanced CT images can reach great diagnostic performance of liver fibrosis.

Diagnostic, predictive and prognostic biomarkers in systemic lupus erythematosus: current insights

PURPOSE OF REVIEW

Biomarkers for diagnosis, monitoring and prognosis still constitute an unmet need for systemic lupus erythematosus (SLE). Focusing on recent findings, this review summarises the current landscape of biomarkers in lupus.

RECENT FINDINGS

Urine activated leukocyte cell adhesion molecule (ALCAM) exhibited good diagnostic ability in SLE and lupus nephritis (LN) whereas cerebrospinal fluid neutrophil gelatinase-associated lipocalin (NGAL) showed promise in neuropsychiatric SLE. Urine ALCAM, CD163 and vascular cell adhesion molecule 1 (VCAM-1) may be useful in surveillance of LN. Urine monocyte chemoattractant protein 1 was found to predict treatment response in SLE, and urine CD163 and NGAL treatment response in LN. Serum complement component 3 (C3) and urinary VCAM-1 have been reported to portend long-term renal prognosis in LN.

SUMMARY

NGAL holds promise as a versatile biomarker in SLE whereas urine ALCAM, CD163 and VCAM-1 displayed good performance as biomarkers in LN. The overall lack of concerted corroboration of leading candidates across multiple cohorts and diverse populations leaves the current biomarker landscape in SLE in an urgent need for further survey and systematic validation.

Exposure levels of mycophenolic acid are associated with comorbidities in children with systemic lupus erythematosus

INTRODUCTION

Little is known about the relationship between exposure levels of mycophenolic acid (MPA), the active metabolite of mycophenolate mofetil (MMF), and comorbidities of systemic lupus erythematosus (SLE) in children. This study aims to explore this association.

METHODS

Longitudinal data from SLE children, who were taking MMF for immunosuppression and under therapeutic drug monitoring (TDM), were retrospectively collected. Area under the concentration-time curve of mycophenolic acid (MPA) over 24 hours (AUC_0-24h) was estimated with Bayesian methods. Logistic regression and random forest models were used to explore the association between comorbidities and MPA exposure levels.

RESULTS

This study included 107 children with 358 times of follow-up (median age 169.02 months). The incidence of diabetes, acute kidney injury (AKI), or pneumonia was significantly associated with AUC_0-24h (odds ratio [OR] 0.991, 95% confidence interval [CI] 0.982-0.999), SLE duration (OR 1.012, 95% CI 1.002-1.022), lymphocyte percentage (OR 0.959, 95% CI 0.925-0.991), plasma albumin levels (OR 0.891, 95% CI 0.843-0.940), use of aspirin (OR 0.292, 95% CI 0.126-0.633) and hydroxychloroquine (OR 0.407, 95% CI 0.184-0.906). The random forest model showed that albumin and AUC_0-24h were two important predictors. The case group (with the three comorbidities) had a mean AUC_0-24h of 73.63 mg · h/L, while the control group had a mean AUC_0-24h of 100.39 mg · h/L.

CONCLUSIONS

Increased levels of MPA exposure are associated with decreased incidence odds of diabetes, AKI or pneumonia in SLE children. An AUC_0-24h of 100.39 mg · h/L or an AUC_0-12h of 50.20 mg · h/L could be used as the targeted exposure level for clinical practice.