Observational studyCardiovascular research2021
Quantifying technical confounders in microbiome studies.
Observational study in Cardiovascular research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 4 of them syntheses that pooled 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.
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.
Who cites it
46 citing papers in PubMed, 4 syntheses or guidelines pooled it, 79 citations in OpenAlex.
- Cross-cohort analysis identifies shared gut microbial signatures and validates microbial risk scores for colorectal cancer.Journal of translational medicine · 2025Pooled it
- Gut Microbiome Composition in Polycystic Ovary Syndrome Adult Women: A Systematic Review and Meta-analysis of Observational Studies.Reproductive sciences (Thousand Oaks, Calif.) · 2024Pooled it
- Effects of Stool Sample Preservation Methods on Gut Microbiota Biodiversity: New Original Data and Systematic Review with Meta-Analysis.Microbiology spectrum · 2023Pooled it
- Gut Microbiome Composition in Obese and Non-Obese Persons: A Systematic Review and Meta-Analysis.Nutrients · 2021Pooled it
- Machine learning identifies microbiome and clinical predictors of sustained weight loss following prolonged fasting.Genome medicine · 2026Trial
- Systematic quantification and removal of host DNA contamination in 16S rRNA gene sequencing.Quantitative biology (Beijing, China) · 2026Article
- An Update and Overview of the Ocular and Extraocular Microbiome and Its Impact on Ophthalmic Care.Advances in therapy · 2026Review
- Associations of Adiposity With Gut Microbiota Composition Among Adults-Results From a Federated Analysis of Individual Participant Data From Eight European Observational Studies.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026Review
- Analytic attributes of the 16S rRNA gene sequencing methodology for human gut microbiota characterization.Applied microbiology and biotechnology · 2026Article
- Targeted isolation of bacteria with potential to competitively exclude Staphylococcus aureus in the upper respiratory tract of pigs.BMC microbiology · 2026Article
- metadeconfoundR: Covariate analysis of high-dimensional cross-sectional omics data.Bioinformatics advances · 2026Article
- Probiotic ice cream influences gut and vaginal microbiota in women at high risk of preterm birth: a randomized controlled study.Maternal health, neonatology and perinatology · 2025Article
- Absolute quantification of prokaryotes in the microbiome by 16S rRNA qPCR or ddPCR.Nature protocols · 2025Review
- Mucosal washes are useful for sampling intestinal mucus-associated microbiota despite low biomass.Gut microbes · 2025Article
- Unravelling the impacts of captivity on saltwater crocodile (Crocodylus porosus) cloacal bacterial communities and physiology.FEMS microbiology ecology · 2025Article
- Harnessing gut microbiota for colorectal cancer therapy: from clinical insights to therapeutic innovations.NPJ biofilms and microbiomes · 2025Review
- Comparative study of sample storage conditions on gut dysbiosis in peripheral artery disease.Research square · 2025Article
- Fecal microbiomes from screening sampling tubes are stable despite varying sampling and storage conditions.Scientific reports · 2025Article
- Impact of DNA Extraction Methods on Gut Microbiome Profiles: A Comparative Metagenomic Study.Phenomics (Cham, Switzerland) · 2025Article
- Sex hormone-dependent host-microbiome interactions and cardiovascular risk (XCVD): design of a longitudinal multi-omics cohort study.BMJ open · 2025Observational
Corrections and comments
- Commented on by
Authors and funding
14 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsRecent technical developments have allowed the study of the human microbiome to accelerate at an unprecedented pace. Methodological differences may have considerable impact on the results obtained. Thus, we investigated how different storage, isolation, and DNA extraction methods can influence the characterization of the intestinal microbiome, compared to the impact of true biological signals such as intraindividual variability, nutrition, health, and demographics. METHODS AND
resultsAn observative cohort study in 27 healthy subjects was performed. Participants were instructed to collect stool samples twice spaced by a week, using six different methods (naive and Zymo DNA/RNA Shield on dry ice, OMNIgene GUT, RNALater, 95% ethanol, Zymo DNA/RNA Shield at room temperature). DNA extraction from all samples was performed comparatively using QIAamp Power Fecal and ZymoBIOMICS DNA Kits. 16S rRNA sequencing of the gut microbiota as well as qPCRs were performed on the isolated DNA. Metrics included alpha diversity as well as multivariate and univariate comparisons of samples, controlling for covariate patterns computationally. Interindividual differences explained 7.4% of overall microbiome variability, whereas the choice of DNA extraction method explained a further 5.7%. At phylum level, the tested kits differed in their recovery of Gram-positive bacteria, which is reflected in a significantly skewed enterotype distribution.
conclusionDNA extraction methods had the highest impact on observed microbiome variability, and were comparable to interindividual differences, thus may spuriously mimic the microbiome signatures of various health and nutrition factors. Conversely, collection methods had a relatively small influence on microbiome composition. The present study provides necessary insight into the technical variables which can lead to divergent results from seemingly similar study designs. We anticipate that these results will contribute to future efforts towards standardization of microbiome quantification procedures in clinical research.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.