Stratification de la population de patients vers la découverte de traitements personnalisés pour la maladie rénale chronique

Chronic kidney disease (CKD) is a highly heterogeneous disease comprising of a wide range of etiologies with variable clinical presentation. Classical staging of CKD uses indirect systemic measures, such as estimated glomerular filtration rate and albuminuria, and does not consider the underlying molecular processes in the kidney driving the disease. Additionally, the kidneys are structurally complex, with more than 50 cell populations working together to carry out its diverse functions. These factors make CKD treatment and therapy development challenging. Using human omics data and advanced data analysis methods, this PhD thesis groups patients into subtypes and characterizes the underlying biological pathways to advance our understanding of CKD. This project also includes exploratory analyses of CKD omics data to generate testable hypotheses to deepen our disease understanding. These studies aim to open new opportunities for biomarker and drug discovery leading to personalized treatments. This thesis is composed of the following chapters: Chapter 1: "Kidney transcriptomics signature of prospective rapid diabetic kidney disease (DKD) progression" identifies a 265-gene signature from the analysis of kidney biopsy transcriptomes of rapid progressors in DKD based on five-year post-biopsy clinical data; Chapter 2: "Kidney 'pathway-orphan' genes as a potential overlooked source of novel insights into kidney health and disease" explores the unannotated and understudied protein-coding genes and their possible roles in kidney physiology and CKD pathophysiology; Chapter 3: "Kidney protein-mRNA expression correlation discordance in the Human Protein Atlas" brings attention to the observed difference in the protein and mRNA abundance levels in the kidney and discusses the potential reasons; Chapter 4: "Urinary metabolomics characterization of the chronic kidney disease molecular categories" determines if the urine metabolome can differentiate the CKD subgroups from each other; Chapter 5: "Drug signature characterization of the chronic kidney disease molecular categories" explores how the different CKD subgroups respond to medicines; Chapter 6: "Pseudo-time trajectory analysis reveals intermediate cell markers for kidney tubular atrophy" examines healthy and atrophied tubular cells to track potential intermediate markers for disease; and lastly, Appendix 1: "Phenotypic spectrum of FAM47E-SHROOM3 haplotype composition in a general population sample" identifies and characterizes the several haplotypes in the FAM47E-SHROOM3 locus and its probable effect on kidney function (co-author).