In a paper published last week in The ISME Journal, a team lead by Prof. MA Zhanshan (Kunming Institute of Zoology, Chinese Academy of Sciences) and Prof. Nicholas Gotelli (University of Vermont) discovered that, in only approximately 1/3 of cases, there is a statistical difference in the microbiome diversity of healthy versus diseased individuals.
Launched a decade ago, the human microbiome project (HMP) opened a new chapter of modern biomedicine by revealing the far-reaching health implications of the human microbiome, predominantly the human gut microbiome. A growing list of diseases including obesity, IBD (inflammatory bowel disease), type-I diabetes, Periodontitis, BV (bacterial vaginosis), Cystic Fibrosis, Parkinson’s Disease, Schizophrenia, Depression, Autism, and Mastitis have been found to be associated with the human microbiome, and in particular with the human gut microbiome.
The main reason why they were termed human microbiome associate diseases (MADs) is because whether the microbiome is a cause or a consequence of the disease is still unclear in majority case. At this stage, the mechanistic and/or etiological studies of the MAD are still preliminary or even lacking in most cases. A standard analysis in the human MADs is the comparison of replicated samples of microbiome diversity (usually measured with the number of microbial species or other more comprehensive metrics such as Shannon’s entropy) in healthy versus diseased. However, some of these analyses did not use statistical tests or metrics that are standardized for sampling effects.
Prof. MA, Prof. Gotelli, and Mr. LI Lianwei used rigorous statistical tests developed by ecologists to compare microbiome species richness and developed two new simulation algorithms to compare microbiome species composition. For species richness, in only approximately 1/3 of the tested cases, the MAD diseases and microbiome diversity are related. In remaining 2/3 of the cases, the differences were no larger than expected by chance. However, in most studies there were significant differences in microbiome species composition between diseased and healthy individuals, which could aid researchers in the development of diagnostic tests and early warning indicators of disease.
The study highlights the importance of further mechanistic and/or etiological studies for deepening our inquiry into this important category of human diseases, and ultimately, for more precise and personalized diagnosis and treatments. In the meantime, the team has been investigating the relationships between MADs and other alternative ecological indicators, as well as the possible ecological/etiological mechanisms underlying the “1/3 DDR (diversity-disease relationship) conjecture”.
The study received funding from the National Science Foundation of China, a China-US Collaborative Grant, and the YunRidge Industry Technology Talents Program, from Yunnan Province of China. Link to the article:.https://www.nature.com/articles/s41396-019-0395-y.