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MIA Talks

Linking gut microbiomes, genomes and phenotypes via linear mixed models and kernel methods

February 28, 2018
Price Group, Harvard School of Public Health

The gut microbiome is increasingly recognized as having fundamental roles in human physiology and health, and is often referred to as our second genome. However, the associations between microbiome, our genome, our environment and our health are not well understood. I will discuss our recent work to elucidate these relations, using a cohort of ~1,000 Israeli individuals with detailed microbiome, genotype, clinical and environmental measurements, with an emphasis on methods to handle the large dimensionality and heterogeneity of such data. Our approaches combine linear mixed models – the statistical backbone of GWAS and phenotype prediction methods – with common techniques from statistical ecology, and with kernel regression approaches from machine learning.

In the first part of the talk, I will describe approaches to investigate the role of host genetics in shaping the gut microbiome. In the second part, I will describe approaches to investigate how host genetics and the microbiome interact with traits such as obesity and glucose levels. I will show that the fraction of phenotypic variance explained by the microbiome is often comparable to that of host genetics, which provides a positive outlook towards microbiome-based therapeutics of metabolic disorders.

This is a joint work with Daphna Rothschild and Elad Barkan from Eran Segal's group at the Weizmann Institute of Science. It has recently been accepted for publication in Nature.