Award
2024.01.31
Genomics and Precision Medicine in the Merino Group
The Merino Group investigates how molecular and environmental factors modulate variable metabolic responses to therapeutic interventions and shape food choice behavior. The group aims to generate actionable knowledge to inform more effective obesity and diabetes prevention and treatment strategies.
We focus on the interplay between molecular and environmental factors underlying variable metabolic responses to therapeutic strategies. We are particularly interested in understanding the molecular heterogeneity that characterizes obesity and diabetes, and how differences in fundamental molecular processes lead to variable clinical presentation, response to behavioral or pharmacological interventions, and propensity for developing cardiovascular complications. Towards this goal, and inspired by our recent precision medicine/nutrition work, we use multi-omics profiling coupled with wearable devices and deep phenotypic in observational studies and large-scale clinical interventions.
Another central focus area of the group is dissecting key molecular processes underlying appetite. The group leverages human genetics and advanced bioinformatic techniques to cover the arc from gene discovery to regulatory network characterization. The group has broad expertise in designing and implementing human physiological studies to offer clinically actionable insights into the neurobiology of appetite.
Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits
Published in Nature Human Behaviour in 2022, this study integrates genetic and diet data from up to 280.000 individuals from the UK Biobank and the CHARGE Consortium to identify genetic variants, brain-specific cell types, and molecular processes underlying food intake.
Validity of continuous glucose monitoring for categorizing glycemic responses to diet: implications for use in personalized nutrition
Published in The American Journal of Clinical Nutrition in 2022, this secondary analysis from the PREDICT study demonstrated that continuous glucose monitors are reliable for categorizing glycemic responses to diet and highlighted their potential application for precision nutrition.
Quality of dietary fat and genetic risk of type 2 diabetes: individual participant data meta-analysis
Published in The British Medical Journal in 2019, this individual participant data meta-analysis showed that both genetic risk and dietary quality were each associated with the development of diabetes with no evidence of interactions. Results from this study provided evidence that additional axes of molecular data are needed to predict individual responses to diet.
Metabolomics insights into early type 2 diabetes pathogenesis and detection in individuals with normal fasting glucose
This study published in Diabetologia in 2018 provided evidence of metabolites and metabolic pathways contributing to the earliest stages of type 2 diabetes pathogenesis. The study showed that a subset of identified metabolites improved diabetes prediction beyond conventional risk factors.
Staff list
| Name | Title | Phone | |
|---|---|---|---|
| Jardon, Kelly | Postdoc | +4535327434 | |
| Le, Minh Thanh | Academic Research Staff | +4535327782 | |
| Merino, Jordi | Associate Professor | +4551424055 | |
| Mou Sequeira Fernandes, Maria I | Postdoc | +4535336261 | |
| Nielsen, Lise Birk | Guest Researcher | +4535329083 | |
| Zhou, Xuan | Postdoc | +4535327776 |