LOOBesity: Closing the loop towards precision medicine in obesity

Obesity (adipositas) is a global health problem and a major risk factor for developing multiple chronic diseases, including type 2 diabetes, fatty liver, and high blood pressure which may contribute to a premature death.

Cortisol is a stress related hormone, which if produced or used at high amounts results in health issues similar to those of obese individuals. Cortisol may play an important role in the development of obesity related co‐morbidities and offers a target for personalized treatment strategies. LOOBesity seeks to understand what makes obesity so risky for some patients, but not for others. This knowledge will be used for personalizing therapies according to individual molecular and imaging characteristics, the best available evidence from treatment trials, and patient preferences.

We will use a prospective randomized clinical trial to determine whether a personalized treatment strategy that modulates cortisol action can help patients enjoy the maximum benefits and minimal harms of treatments for obesity.  Our research team is in a unique position to combine molecular and imaging methods and advanced machine learning to extract detailed measurements of fat distribution and function. This will offer the possibility to introduce fast and less expensive MRI protocols and novel molecular methods as a future routine screening tool for obese patients and provide a firm basis for personalized approaches for obese patients with far reaching prospects for clinical practice.

People responsible: Prof. Felix Beuschlein (UZH/USZ). Mitantragsteller: Prof. Thomas Frauenfelder (UZH/USZ), Prof. Ender Konukoglu (ETH Zürich), Prof. Milo Puhan (UZH), Prof. Christian Wolfrum (ETH Zürich)

Videopresentation LOOBesity (in the context of the application)