Journal
METABOLITES
Volume 11, Issue 7, Pages -Publisher
MDPI
DOI: 10.3390/metabo11070460
Keywords
metabolomics study design; nephrology; chronic kidney disease; human cohort studies; epidemiology; kidney disease etiologies
Categories
Funding
- German Federal Ministry of Education and Research (BMBF) [01ZX1912A, 01ZX1912B, 01ZX1912C]
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Kidney diseases present a major challenge in global health, with their complexity hindering the understanding of underlying mechanisms and optimal patient care. Metabolomics, studying small organic compounds in biological specimens, is becoming increasingly important in nephrology research. Conducting metabolomics studies in human kidney disease cohorts requires thorough knowledge of study planning, sample collection, data processing, statistical analysis, and interpretation of results within a biomedical context.
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.
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