Evidence map›Paper›PMID 34357354›Full record

ReviewMetabolites2021

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

Ulla T Schultheiss, Robin Kosch, Fruzsina Kotsis, Michael Altenbuchinger, Helena U Zacharias

Open access · goldAbstract readReview
In one paragraph

Review in Metabolites, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 41% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 1 country.

Ulla T SchultheissInstitute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, 79106 Freiburg, Germany.ORCID 0000-0002-7541-5310
Robin KoschComputational Biology, University of Hohenheim, 70599 Stuttgart, Germany.ORCID 0000-0001-5127-3912
Fruzsina KotsisInstitute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, 79106 Freiburg, Germany.ORCID 0000-0001-5018-9305
Michael AltenbuchingerInstitute of Medical Bioinformatics, University Medical Center Göttingen, 37077 Göttingen, Germany.
Helena U ZachariasDepartment of Internal Medicine I, University Medical Center Schleswig-Holstein, Campus Kiel, 24105 Kiel, Germany.
University of Freiburg · DEChristian-Albrechts-Universität zu Kiel · DEUniversitätsmedizin Göttingen · DEUniversity of Hohenheim · DE

Funding

Bundesministerium für Bildung, Wissenschaft und Forschung 01ZX1912ABundesministerium für Bildung, Wissenschaft und Forschung 01ZX1912BBundesministerium für Bildung, Wissenschaft und Forschung 01ZX1912C
6 · The paper itself

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.

Indexed as

chronic kidney diseaseepidemiologyhuman cohort studieskidney disease etiologiesmetabolomics study designnephrology

Identifiers

PMID34357354
PMCPMC8304377
OpenAlexW3186336067

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.