Literature DB >> 34357354

Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses.

Ulla T Schultheiss1,2, Robin Kosch3, Fruzsina Kotsis1,2, Michael Altenbuchinger4, Helena U Zacharias5,6.   

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.

Entities:  

Keywords:  chronic kidney disease; epidemiology; human cohort studies; kidney disease etiologies; metabolomics study design; nephrology

Year:  2021        PMID: 34357354     DOI: 10.3390/metabo11070460

Source DB:  PubMed          Journal:  Metabolites        ISSN: 2218-1989


  160 in total

1.  Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in 1H NMR metabonomics.

Authors:  Frank Dieterle; Alfred Ross; Götz Schlotterbeck; Hans Senn
Journal:  Anal Chem       Date:  2006-07-01       Impact factor: 6.986

2.  Metabolomic analysis and visualization engine for LC-MS data.

Authors:  Eugene Melamud; Livia Vastag; Joshua D Rabinowitz
Journal:  Anal Chem       Date:  2010-11-04       Impact factor: 6.986

Review 3.  Measured GFR as a confirmatory test for estimated GFR.

Authors:  Lesley A Stevens; Andrew S Levey
Journal:  J Am Soc Nephrol       Date:  2009-10-15       Impact factor: 10.121

4.  Human metabolic individuality in biomedical and pharmaceutical research.

Authors:  So-Youn Shin; Ann-Kristin Petersen; Nicole Soranzo; Christian Gieger; Karsten Suhre; Robert P Mohney; David Meredith; Brigitte Wägele; Elisabeth Altmaier; Panos Deloukas; Jeanette Erdmann; Elin Grundberg; Christopher J Hammond; Martin Hrabé de Angelis; Gabi Kastenmüller; Anna Köttgen; Florian Kronenberg; Massimo Mangino; Christa Meisinger; Thomas Meitinger; Hans-Werner Mewes; Michael V Milburn; Cornelia Prehn; Johannes Raffler; Janina S Ried; Werner Römisch-Margl; Nilesh J Samani; Kerrin S Small; H-Erich Wichmann; Guangju Zhai; Thomas Illig; Tim D Spector; Jerzy Adamski
Journal:  Nature       Date:  2011-08-31       Impact factor: 49.962

5.  A Novel Metabolic Signature To Predict the Requirement of Dialysis or Renal Transplantation in Patients with Chronic Kidney Disease.

Authors:  Helena U Zacharias; Michael Altenbuchinger; Ulla T Schultheiss; Claudia Samol; Fruzsina Kotsis; Inga Poguntke; Peggy Sekula; Jan Krumsiek; Anna Köttgen; Rainer Spang; Peter J Oefner; Wolfram Gronwald
Journal:  J Proteome Res       Date:  2019-03-12       Impact factor: 4.466

6.  Genetic studies of urinary metabolites illuminate mechanisms of detoxification and excretion in humans.

Authors:  Pascal Schlosser; Yong Li; Peggy Sekula; Johannes Raffler; Franziska Grundner-Culemann; Maik Pietzner; Yurong Cheng; Matthias Wuttke; Inga Steinbrenner; Ulla T Schultheiss; Fruzsina Kotsis; Tim Kacprowski; Lukas Forer; Birgit Hausknecht; Arif B Ekici; Matthias Nauck; Uwe Völker; Gerd Walz; Peter J Oefner; Florian Kronenberg; Robert P Mohney; Michael Köttgen; Karsten Suhre; Kai-Uwe Eckardt; Gabi Kastenmüller; Anna Köttgen
Journal:  Nat Genet       Date:  2020-01-20       Impact factor: 38.330

Review 7.  Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases.

Authors:  Hayley Abbiss; Garth L Maker; Robert D Trengove
Journal:  Metabolites       Date:  2019-02-14

8.  Comparison of Kidney Transcriptomic Profiles of Early and Advanced Diabetic Nephropathy Reveals Potential New Mechanisms for Disease Progression.

Authors:  Ying Fan; Zhengzi Yi; Vivette D D'Agati; Zeguo Sun; Fang Zhong; Weijia Zhang; Jiejun Wen; Ting Zhou; Ze Li; Li He; Qunzi Zhang; Kyung Lee; John Cijiang He; Niansong Wang
Journal:  Diabetes       Date:  2019-10-02       Impact factor: 9.461

9.  MetaboAnalyst: a web server for metabolomic data analysis and interpretation.

Authors:  Jianguo Xia; Nick Psychogios; Nelson Young; David S Wishart
Journal:  Nucleic Acids Res       Date:  2009-05-08       Impact factor: 16.971

10.  MWASTools: an R/bioconductor package for metabolome-wide association studies.

Authors:  Andrea Rodriguez-Martinez; Joram M Posma; Rafael Ayala; Ana L Neves; Maryam Anwar; Enrico Petretto; Costanza Emanueli; Dominique Gauguier; Jeremy K Nicholson; Marc-Emmanuel Dumas
Journal:  Bioinformatics       Date:  2018-03-01       Impact factor: 6.937

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  1 in total

Review 1.  Metabolomic Fingerprinting for the Detection of Early-Stage Lung Cancer: From the Genome to the Metabolome.

Authors:  Jean-François Haince; Philippe Joubert; Horacio Bach; Rashid Ahmed Bux; Paramjit S Tappia; Bram Ramjiawan
Journal:  Int J Mol Sci       Date:  2022-01-21       Impact factor: 5.923

  1 in total

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