A Meta-Analysis of the Human Gut Mycobiome Using Internal Transcribed Spacer Data
2024

Meta-Analysis of the Human Gut Mycobiome

Sample size: 2372 publication Evidence: moderate

Author Information

Author(s): Zhang Zeming, Zhang Yining, Yuan Qixiang, Wang Zuoyi, Hu Songnian, Yin Peng, He Zilong

Primary Institution: Beihang University

Hypothesis

The study investigates the overall impact of the gut mycobiome on human health and disease.

Conclusion

The diversity of intestinal fungi varies significantly across different diseases, and the mycobiome may serve as a molecular marker for disease prediction.

Supporting Evidence

  • The mycobiome diversity of human gut fungi varies significantly across diseases.
  • The study analyzed 2372 samples from seven studies.
  • Three main genera of gut fungi were identified: Saccharomyces, Candida, and Aspergillus.
  • Random forest models were constructed to predict diseases based on gut mycobiome data.
  • The study found significant changes in fungal diversity across different diseases.
  • Models showed varying performance, with some diseases having better predictive accuracy.
  • Limitations include small sample sizes for specific diseases and technical constraints in species identification.

Takeaway

This study looks at the tiny fungi in our guts and how they can change when we get sick, helping us understand health better.

Methodology

The study performed a meta-analysis using publicly available ITS data from seven studies, analyzing gut mycobiome diversity and constructing disease prediction models.

Potential Biases

Potential bias due to the reliance on existing datasets and the limitations of ITS sequencing technology.

Limitations

The study's paired data of case-control samples are relatively small, and the accuracy of species-level annotation is limited due to technical constraints.

Participant Demographics

The study included 1912 healthy controls and 460 disease cases, with a focus on various diseases including multiple sclerosis and diabetes.

Statistical Information

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.3390/microorganisms12122567

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