Reconstruction of the Cytokine Signaling in Lysosomal Storage Diseases by Literature Mining and Network Analysis

Machine Learning-Driven Biomarker Discovery for Skeletal Complications in Type 1 Gaucher Disease Patients

Type 1 Gaucher disease (GD1) is a rare, autosomal recessive disorder caused by glucocerebrosidase deficiency. Skeletal manifestations represent one of the most debilitating and potentially irreversible complications of GD1. Although imaging studies are the gold standard, early diagnostic/prognostic tools, such as molecular biomarkers, are needed for the rapid management of skeletal complications. This study aimed to identify potential protein biomarkers capable of predicting the early diagnosis of bone skeletal complications in GD1 patients using artificial intelligence. An in silico study was performed using the novel Therapeutic Performance Mapping System methodology to construct mathematical models of GD1-associated complications at the protein level. Pathophysiological characterization was performed before modeling, and a data science strategy was applied to the predicted protein activity for each protein in the models to identify classifiers. Statistical criteria were used to prioritize the most promising candidates, and 18 candidates were identified. Among them, PDGFB, IL1R2, PTH and CCL3 (MIP-1α) were highlighted due to their ease of measurement in blood. This study proposes a validated novel tool to discover new protein biomarkers to support clinician decision-making in an area where medical needs have not yet been met. However, confirming the results using in vitro and/or in vivo studies is necessary.

Increased Soluble Interleukin 6 Receptors in Fabry Disease

Fabry disease (FD) is an X-linked lysosome storage disease that results in the accumulation of globotriaosylceramide (Gb3) throughout the body leading to irreversible target organ damage. As the role of secondary mediators (inflammatory molecules) and their mechanisms has not been fully elucidated, we focused on the interleukin (IL)-6 system in adult FD patients and in matched healthy subjects. To obtain insights into the complex regulation of IL-6 actions, we used a novel approach that integrates information from plasma and exosomes of FD patients (n = 20) and of healthy controls (n = 15). Soluble IL-6 receptor (sIL-6R) levels were measured in plasma with the ELISA method, and membrane-bound IL-6R was quantified in plasma and urinary exosomes using flow cytometry. In FD patients, the levels of soluble IL-6R in plasma were higher than in control subjects (28.0 ± 5.4 ng/mL vs. 18.9 ± 5.4 ng/mL, p < 0.0001); they were also higher in FD subjects with the classical form as compared to those with the late-onset form of the disease (36.0 ± 11.4 ng/mL vs. 26.1 ± 4.5 ng/mL, p < 0.0001). The percentage of urinary exosomes positive for IL-6R was slightly lower in FD (97 ± 1 vs. 100 ± 0% of events positive for IL-6R, p < 0.05); plasma IL-6 levels were not increased. These results suggest a potential role of IL-6 in triggering the inflammatory response in FD. As in FD patients only the levels of sIL-6Rs are consistently higher than in healthy controls, the IL-6 pathogenic signal seems to prevail over the homeostatic one, suggesting a potential mechanism causing multi-systemic damage in FD.

Achieving big with small: quantitative clinical pharmacology tools for drug development in pediatric rare diseases

Pediatric populations represent a major fraction of rare diseases and compound the intrinsic challenges of pediatric drug development and drug development for rare diseases. The intertwined complexities of pediatric and rare disease populations impose unique challenges to clinical pharmacologists and require integration of novel clinical pharmacology and quantitative tools to overcome multiple hurdles during the discovery and development of new therapies. Drug development strategies for pediatric rare diseases continue to evolve to meet the inherent challenges and produce new medicines. Advances in quantitative clinical pharmacology research have been a key component in advancing pediatric rare disease research to accelerate drug development and inform regulatory decisions. This article will discuss the evolution of the regulatory landscape in pediatric rare diseases, the challenges encountered during the design of rare disease drug development programs and will highlight the use of innovative tools and potential solutions for future development programs.

Deep next-generation proteomics and network analysis reveal systemic and tissue-specific patterns in Fabry disease

Fabry disease (FD) is an X-linked lysosomal rare disease due to a deficiency of α-galactosidase A activity. The accumulation of glycosphingolipids mainly affects the kidney, heart, and central nervous system, considerably reducing life expectancy. Although the accumulation of undegraded substrate is considered the primary cause of FD, it is established that secondary dysfunctions at the cellular, tissue, and organ levels ultimately give rise to the clinical phenotype. To parse this biological complexity, a large-scale deep plasma targeted proteomic profiling has been performed. We analyzed the plasma protein profiles of FD deeply phenotyped patients (n = 55) compared to controls (n = 30) using next-generation plasma proteomics including 1463 proteins. Systems biology and machine learning approaches have been used. The analysis enabled the identification of proteomic profiles that unambiguously separated FD patients from controls (615 differentially expressed proteins, 476 upregulated, and 139 downregulated) and 365 proteins are newly reported. We observed functional remodeling of several processes, such as cytokine-mediated pathways, extracellular matrix, and vacuolar/lysosomal proteome. Using network strategies, we probed patient-specific tissue metabolic remodeling and described a robust predictive consensus protein signature including 17 proteins CD200, SPINT1, CD34, FGFR2, GRN, ERBB4, AXL, ADAM15, PTPRM, IL13RA1, NBL1, NOTCH1, VASN, ROR1, AMBP, CCN3, and HAVCR2. Our findings highlight the pro-inflammatory cytokines' involvement in FD pathogenesis along with extracellular matrix remodeling. The study shows a tissue-wide metabolic remodeling connection to plasma proteomics in FD. These results will facilitate further studies to understand the molecular mechanisms in FD to pave the way for better diagnostics and therapeutics.