Multi-omics & type 2 diabetes

In this episode, Alice Limonciel and Sapna Sharma discuss how to make the most of the omic data already generated in cohort studies, the place of metabolomics in multi-omics strategies, and how to go beyond associations and towards causal relationships and their implications for medicine in general and diabetes in particular.

Sapna Sharma

Sapna Sharma is group leader at Technical University Munich (TUM) in Germany

Favorite metabolite
lysophosphatidylcholines (LPCs)

Papers we discussed in this episode
Effect of BMI on type 2 diabetes | Metabolic Signatures Elucidate the Effect of Body Mass Index on Type 2 Diabetes
More on the KORA cohort discussed in this episode and in the first paper.

Paper on medication associations with multiple omics | Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models
More on the IMI-direct project

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Finally available – Alices first book
The STORY principle – A guide to the biological interpretation of metabolomics
Also featuring some of the Metabolomists from Season 1
Available on Amazon and the biocrates webshop