Combating the obesity epidemic is one of the greatest challenges of modern era. Despite that weight loss diets have been used for more than 2,500 years, they have not yielded significant success given the persistent global rise in rates of overweight and obesity in recent decades.

For years, scientists have debated the ideal dietary plan for weight loss in terms of macronutrient composition. However, no singular dietary approach has been conclusively established to outperform others. Irrespective of the type of diet, people react differently to the same dietary treatment. This ranges from individuals who lose very little weight to others who lose a lot, and there are even some who may gain weight. The reasons for this large interindividual variability can be attributed to various factors such as distinctive genetic makeup and diverse mechanisms of food absorption and metabolism in the body, or even behavioural and psychological factors. It is believed that tailoring dietary intervention strategies according to an individual's metabolic profile holds considerable potential in the treatment of obesity, as opposed to relying solely on generalized dietary recommendations for the whole population.

Accordingly, the H2020 PREVENTOMICS project (Empowering consumers to PREVENT diet-

related diseases through OMICS sciences), coordinated by Eurecat in Spain, has developed a direct-to-consumer platform on the basis of integrating genetic, nutritional, biochemical and behavioural factors to assess the unique metabolic profile of individuals using metabolomics and machine-learning techniques, aimed at delivering personalized nutritional plans to ultimately drive sustainable behaviour change to tackle obesity and thereby, prevent nutrition-related chronic diseases.

The current PhD thesis is based on three publications out of the PREVENTOMICS project with an overall aim to investigate the efficacy of using such a platform to deliver personalized nutrition plans for reducing body fat mass and subsequently improving health outcomes. The three objectives and corresponding papers are summarized below.

1. To review the existing literature on precision nutrition for weight loss and design a study to assess such a personalized nutrition approach.

2. To investigate the efficacy of personalizing dietary plans, using genetic and health biomarkers, in producing more favourable health outcomes over dietary plans based on general recommendations.

3. To explore the impact of consuming an ad libitum high-fibre plant-based diet on gut microbiota composition and its associations with different metabolic biomarkers, in addition to whether baseline enterotypes can predict weight loss outcomes.

Paper 1 describes in detail the protocol used in the 10-week PREVENTOMICS randomized controlled trial conducted in Denmark, where an algorithm was developed with a priori definition of five distinct metabotypes associated with compromised metabolic processes related to (1) carbohydrate metabolism, (2) lipid metabolism, (3) oxidative stress, (4) inflammation, and (5) microbiota-related metabolism.

In Paper 2, we found that personalizing dietary plans did not provide additional benefits compared to a conventional approach on the primary outcomes (change in fat mass and body weight), or on improving health parameters beyond the changes induced by the control diet. Both predominantly plant-based diets were equally effective in improving body weight and health outcomes in individuals with overweight or obesity.

In Paper 3, we concluded that consuming ad libitum plant-based diet reduces body weight and exerts several health benefits. The addition of inulin-type fructans prebiotics to this naturally fibrerich diet selectively modifies gut microbiota composition and attenuated some of the realized cardiometabolic biomarkers. In addition, classifying participants based on their baseline Prevotella/Bacteroides ratio did not predict weight loss outcomes.

In summary, based on the approaches presented in this PhD thesis, metabotyping to provide tailored dietary advice did not support the hypothesis that personalized nutrition is superior to general dietary guidelines for successful weight loss and improved health outcomes. Future studies should focus on the effectiveness and cost-effectiveness of such precision nutrition approaches using more simplified methods while validating biomarkers for weight loss before integrating more complex omics of several markers at once. Moreover, future interventions should address both behaviour change and the surrounding obesogenic environment influences for better maintenance of weight loss outcomes. To combat obesity effectively, a comprehensive holistic and interdisciplinary approach is key requirement.