Abstract
Kidney diseases still pose one of the biggest challenges for global health, and their heterogeneity and often high comorbidity load seriously hinders the unraveling of their underlying pathomechanisms and the delivery of optimal patient care. Metabolomics, the quantitative study of small organic compounds, called metabolites, in a biological specimen, is gaining more and more importance in nephrology research. Conducting a metabolomics study in human kidney disease cohorts, however, requires thorough knowledge about the key workflow steps: study planning, sample collection, metabolomics data acquisition and preprocessing, statistical/bioinformatics data analysis, and results interpretation within a biomedical context. This review provides a guide for future metabolomics studies in human kidney disease cohorts. We will offer an overview of important a priori considerations for metabolomics cohort studies, available analytical as well as statistical/bioinformatics data analysis techniques, and subsequent interpretation of metabolic findings. We will further point out potential research questions for metabolomics studies in the context of kidney diseases and summarize the main results and data availability of important studies already conducted in this field.
Highlights
Chronic kidney disease (CKD) has become one of the major global health burdens in the 21st century [1], with a typically chronic progressive disease course
This review provides a guide for future metabolomics studies in kidney disease cohorts using observational study designs
The field of metabolomics already has been of unmeasurable value for nephrology research
Summary
Chronic kidney disease (CKD) has become one of the major global health burdens in the 21st century [1], with a typically chronic progressive disease course. Even though randomized controlled trials (RCTs) are the gold standard for a research question of the effect of an exposure on an outcome, the majority of interventions investigated by RCTs in nephrology have so far been unable to demonstrate treatment benefits or have even caused harm [2] This may well be due to the aforementioned heterogeneity of CKD populations. The research field shifted towards the identification of metabolites associated with the patient’s glomerular filtration rate (GFR) [15,16], to metabolic fingerprints of adverse patient events [17], and has extended towards the understanding of the underlying mechanisms in CKD progression. Replication cohort) metabolites predicting CVD mortality in incident KRT patients
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