Microbiome in Health and Disease

Another rich source of information with the potential to contain pertinent disease risk factor data is the human microbiome – the collective genome of trillions of microbes, including bacteria, viruses, fungi, and parasites that reside in the human gastrointestinal tract. The microbiome contains 100-fold more genes than the human genome, and is considered a bona-fide ‘second genome’ with fundamental roles in multiple aspects of human physiology and health, including obesity, non-alcoholic fatty liver disease, inflammatory diseases, cancer, metabolic diseases, cardiovascular disease, aging, and neurodegenerative disorders. As such, it should capture different aspects of disease than existing risk factors, and their combination can lead to earlier and more robust disease detection. However, very few microbiome-based markers predictive of disease onset and progression were found to date and none are currently used by healthcare systems. Thus, discovery of microbiome-based risk factors is a promising yet mostly unexplored research area.

Growing evidence supports a causal role for the microbiome in obesity, diabetes, metabolic disorders, cardiovascular disease, and immune-mediated disease. For example, transplanting microbiota from human subjects discordant for obesity into germ-free mice induced the corresponding phenotype in the recipient mice, and cohousing mice harboring the obese human microbiota with mice harboring the lean human microbiota prevented obesity. Atherosclerosis susceptibility was also shown to be transmitted by gut microbiota transfer. We previously showed that weight gain and glucose intolerance are induced in recipient mice following transplantation of microbiota from mice that either consumed artificial sweeteners, had a history of obesity, or had altered feeding patterns or host mutations in circadian genes. We also showed that microbiota transplantations in human, improved clinical outcomes in subjects with Atopic Dermatitis, a severe skin disease.

Our goal is to find novel disease risk factors based on the human microbiome that are more accurate than existing ones in their ability to predict the likelihood of a person to develop a particular condition or disease within 5-10 years. We work numerous conditions including diabetes, cardiovascular disease, obesity, inflammatory bowel disease, fatty liver disease, multiple sclerosis, Alzheimer’s disease, Parkinson’s disease, and cancer. In each setting we collaborate with clinicians to assemble cohorts for which we obtain clinical profiles and microbiome data. We develop algorithms using microbiome features at recruitment time for unravelling the role of the microbiome in each of these conditions.

Our research identifies microbiome-derived features that are predictive of disease and that may be causal for disease, paving the way towards diagnostic and prognostic microbiome applications and towards microbiome-based therapeutics.