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Related Concept Videos

Confounding in Epidemiological Studies01:27

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Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
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Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
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Updated: Dec 22, 2025

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
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Quantifying technical confounders in microbiome studies.

Theda U P Bartolomaeus1,2,3,4, Till Birkner1,2,3, Hendrik Bartolomaeus1,2,3,4,5

  • 1Experimental and Clinical Research Center, a Cooperation of Charité-Universitätsmedizin Berlin, Max Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125 Berlin, Germany.

Cardiovascular Research
|May 7, 2020
PubMed
Summary
This summary is machine-generated.

DNA extraction methods significantly impact human gut microbiome studies, comparable to individual biological differences. Standardizing these methods is crucial for reliable clinical research and accurate microbiome analysis.

Keywords:
16S sequencingConfoundersDNA extractionMicrobiomeMicrobiota

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Area of Science:

  • Microbiology
  • Genomics
  • Bioinformatics

Background:

  • Human microbiome research is rapidly advancing due to new technologies.
  • Methodological variations can significantly affect study outcomes.
  • Understanding these variations is key to accurate microbiome characterization.

Purpose of the Study:

  • To investigate the influence of different storage, isolation, and DNA extraction methods on intestinal microbiome characterization.
  • To compare the impact of technical variables against biological signals like nutrition and demographics.
  • To provide insights for standardizing microbiome quantification procedures.

Main Methods:

  • An observational cohort study involving 27 healthy subjects.
  • Collection of stool samples using six different methods.
  • Comparative DNA extraction using two kits, followed by 16S rRNA sequencing and qPCR.

Main Results:

  • DNA extraction methods explained 5.7% of microbiome variability, comparable to interindividual differences (7.4%).
  • Extraction kits showed differential recovery of Gram-positive bacteria, affecting enterotype distribution.
  • Sample collection methods had a minor influence on microbiome composition.

Conclusions:

  • DNA extraction methods are a major technical variable influencing microbiome data.
  • Technical variability can mimic biological signals, potentially confounding research findings.
  • Standardization of DNA extraction is essential for robust and reproducible microbiome research.