Mathematical framework for human SLE Nephritis: disease dynamics and urine biomarkers

Abstract

BackgroundAlthough the prognosis for Lupus Nephritis (LN) has dramatically improved with aggressive immunosuppressive therapies, these drugs carry significant side effects. To improve the effectiveness of these drugs, biomarkers of renal flare cycle could be used to detect the onset, severity, and responsiveness of kidney relapses, and to modify therapy accordingly. However, LN is a complex disease and individual biomarkers have so far not been sufficient to accurately describe disease activity. It has been postulated that biomarkers would be more informative if integrated into a pathogenic-based model of LN.ResultsThis work is a first attempt to integrate human LN biomarkers data into a model of kidney inflammation. Our approach is based on a system of differential equations that capture, in a simplified way, the complexity of interactions underlying disease activity. Using this model, we have been able to fit clinical urine biomarkers data from individual patients and estimate patient-specific parameters to reproduce disease dynamics, and to better understand disease mechanisms. Furthermore, our simulations suggest that the model can be used to evaluate therapeutic strategies for individual patients, or a group of patients that share similar data patterns.ConclusionsWe show that effective combination of clinical data and physiologically based mathematical modeling may provide a basis for more comprehensive modeling and improved clinical care for LN patients.

Human systems immunology: Hypothesis-based modeling and unbiased data-driven approaches

“…In one approach [96], a dynamical model was used to explain the cyclic fluctuations observed in circulating T cells in NOD mice, an animal model of T1D; the authors suggested that this may arise from a positive relation between the rate of T cell activation and the level of self-antigen on the one hand, and a negative relation between this level and the rate of immune cells differentiation on the other. In another study [97], urine biomarkers were incorporated into a mechanistic model of lupus nephritis to explain and predict the occurrence of flares in this disease.…”

“…This approach, which was recently demonstrated in models of SLE [97], acute HCV infections in chimpanzees [112] and influenza A virus infection [113], may be particularly reasonable in diseases featuring periodic exacerbations (flares), as changes in parameter values may correspond to and point to unknown disease processes contributing to disease exacerbation. This can be done systematically by searching for the most plausible (e.g.…”

Modelling the Impact of NETosis During the Initial Stage of Systemic Lupus Erythematosus

“…This distinguishes our work from models in the literature which focus on the chronic stage of SLE and assume an established autoimmune response (Budu-Grajdeanu et al. 2010 ; Gao et al. 2022 ), study organ damage in the case of Lupus nephritis (Hao et al.…”

Urinary Neutrophil Gelatinase-Associated Lipocalin to Monitor Lupus Nephritis Disease Activity

“…For example is the urinary biomarker, which samples are easy to collect and thought to be more accurate in distinguishing kidney disease from other organs. 5 , 6 Neutrophil gelatinase-associated lipocalin (NGAL) is a protein with a molecular weight of 25 kDa and a member of the lipocalin family. It is mainly synthesized by epithelial cells of proximal tubules, the loop of Henle, and collecting ducts of the kidney.…”