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Mapping the behavioural causes of weight change variability with genetic lottery

Project description

What causes weight loss variability?

Obesity is a major health issue, and despite treatments weight reduction results are quite variable. Weight change and obesity treatment outcomes are influenced by various factors that involve psychosocial, environmental, behavioural, biological and life quality parameters. Integration of these multifaceted influences into a framework offers a comprehensive model for their in-depth understanding. Funded by the European Research Council, the OBECAUSE project aims to further consolidate and validate these measures. Researchers will investigate potential genetic variants that impact weight change and develop an intervention toolbox in the form of a commercial weight loss application. The work has the potential to enhance behavioural health science and pave the way towards improved obesity management.

Objective

Obesity is a heritable chronic condition, costing 2% GDP worldwide. Many obesity treatments - behavioural, pharmacological, and surgical have been developed. Intriguingly, people’s responses to treatments vary widely - some may lose a lot of weight whereas others may even gain weight! To predict such weight change variability, close to 200 measures have been proposed in the past. The measures can be organised into a PEBBL framework across five domains – Psychosocial, Environment, Behavioural, Biology, and Life quality. Still, there are too many measures to be used as predictors or intervention targets. To move the field forward, we propose a novel 3-step OBECAUSE pipeline consisting of consolidation, genomic causation, and validation. 1) In consolidation, we will use machine learning to find best-predicting PEBBL measures in several large-scale weight loss datasets. The PEBBL measures will be integrated into a new PEBBL short questionnaire with wide coverage and good psychometric properties. The questionnaire will be then distributed to all participants of Estonian Biobank to study the genomics of PEBBL. 2) For genomic causation, we will detect genetic variants behind PEBBL measures and weight change. Knowing these variants enables discovering additions to the PEBBL framework through genetic correlations and functional mapping. Importantly, as genetic variants are randomised through genetic lottery, they enable systematic causal mapping of PEBBL measures that have causal effects on weight change. 3) For validation, these causal measures will be used as inputs to design an OBECAUSE toolbox of weight loss interventions. The value of these interventions will be tested in a commercial weight loss app. In summary, the OBECAUSE pipeline of narrowing scattered associations down to potential causal mechanisms with machine learning and genomic causal inference will set a new standard for the behavioural health sciences allowing for quicker discovery of intervention targets.

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Call for proposal

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(opens in new window) ERC-2023-STG

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Host institution

TARTU ULIKOOL
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 497 500,00
Address
ULIKOOLI 18
51005 TARTU
Estonia

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Region
Eesti Eesti Lõuna-Eesti
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 497 500,00

Beneficiaries (1)

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