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

被引:8
|
作者
Tebani, Abdellah [1 ]
Barbey, Frederic [2 ,3 ]
Dormond, Olivier [4 ,5 ]
Ducatez, Franklin [1 ,6 ]
Marret, Stephane [6 ]
Nowak, Albina [7 ,8 ]
Bekri, Soumeya [1 ,9 ]
机构
[1] Normandie Univ, Dept Metab Biochem, UNIROUEN, INSERM U1245,CHU Rouen, Rouen, France
[2] Univ Lausanne, Lausanne, Switzerland
[3] Univ Hosp Lausanne, Dept Immunol, Lausanne, Switzerland
[4] Lausanne Univ Hosp, Lausanne, Switzerland
[5] Univ Lausanne, Dept Visceral Surg, Lausanne, Switzerland
[6] Normandie Univ, Dept Neonatal Pediat, UNIROUEN, INSERM U1245, Rouen, France
[7] Univ Hosp, Zurich, Switzerland
[8] Univ Zurich, Dept Endocrinol & Clin Nutr, Zurich, Switzerland
[9] Rouen Univ Hosp, Dept Metab Biochem, 1 rue Germont, F-76000 Rouen, France
关键词
BIOMARKERS; PROFILES;
D O I
10.1016/j.trsl.2023.02.006
中图分类号
R446 [实验室诊断]; R-33 [实验医学、医学实验];
学科分类号
1001 ;
摘要
Fabry disease (FD) is an X-linked lysosomal rare disease due to a deficiency of & alpha;-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 cytokinemediated 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.
引用
收藏
页码:47 / 59
页数:13
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