Funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3, Theme 10.
Funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3, Theme 10.
Dietary habits and gut microbiome as a target of sustainable intervent...
Highlights
Coordinator
Profiling of vulnerable targets (in connection with SPOKE 5) through: a) analyses of existing data in children affected by obesity and ageing population at risk of malnutrition and non-communicable diseases (NCDs) b) screening of socioeconomic factors, lifestyle and dietary habits, environmental factors, food knowledge, nutritional status, body composition, functional status and disability, quality of life, genetic, metagenetic, phenotypic profiles, exposure to endocrine disruptors chemicals (EDCs), immune system functions in children and aging population with malnutrition c) human-derived biological samples analysis (including samples for the gut microbiome structure analysis and function).
Identification and application of biomarkers of malnutrition (including inflammatory, metabolic, microbiological, genetic and epigenetic ones) and biochemical pathways associated with diet and age-related diseases/ syndromes for early malnutrition detection and quality of life restoration in target specific categories.
Assessing microbiome–host interaction in malnutrition (in connection with Spoke 4 and 5). a) Evaluation of gut microbiome features in paediatric and ageing subjects affected by malnutrition and malnutrition-related conditions, with a focus on immune and metabolic pathways; b) Investigation of gut microbiome cell wall constituents on immune and metabolic pathways involved in human malnutrition; c) Investigation of the diet, environmental factors and drugs influencing human gut microbiome structure and function; d) Design of an algorithm to predict the risk of gut dysbiosis associated with malnutrition and malnutrition-related diseases.
Identification and mapping of specific target groups with malnutrition (M24)
Creation of a biobank for biological samples in connection with Spoke 5 (M36)
New biomarkers of malnutrition specific for diseases and age and related to diet (M24)
Identification of biochemical pathways interconnected with biomarkers of malnutrition and immunological responses (M36)
Identification of gut microbiome-derived biomarkers facilitating the prediction as well as the early diagnosis and the management of human malnutrition. (M24)
Definition of the modifiable factors facilitating malnutrition-related gut microbiome alteration (M16)
Definition of a set of gut microbiome-derived molecules able to tackle gut dysbiosis, modulate immune response and metabolic pathways in specific targets with malnutrition. (M24)
New algorithm supporting prediction of gut dysbiosis associated with malnutrition and related diseases (M24)
Obesity is the main form of malnutrition in developed countries. This condition is the main risk factor for a cluster of metabolic alterations, also known as metabolic syndrome (MetS).
Gut microbiome could impact the development of obesity and its complications, playing a pivotal role in influencing energy homeostasis and substrates metabolism. Diet is the main environmental factor able to influence the gut microbiome structure and function. The evaluation of dietary habits and gut microbiome characteristics of patients affected by obesity complicated or not by metabolic syndrome could pave the way to the identification of new sustainable intervention for preventing and treating obesity and MetS.
It will be enrolled at least n=50 obese patients, n=50 obese patients complicated by MetS of both sexes, aged 6-18, and n=100 normal weight healthy controls, and at least n=50 obese patients, n=50 obese patients complicated by MetS of both sexes, aged 18- 65, and n=100 normal weight healthy controls.
The following variables will be evaluated: dietary habits [ultraprocessed foods (UPFs) and advanced glycation end-products (AGEs) intake], skin AGEs accumulation, AGEs receptor expression, mitochondrial metabolism and oxidative stress, serum proinflammatory cytokines and hormones, microRNAs, and the gut microbiome features. The GM characteristics will be evaluated in a subgroup of patients (n=30 obese pediatric patients, n=30 obese pediatric patients complicated by MetS, and n=60 normal weight pediatric healthy controls; and n=30 obese adult patients, n=30 obese adult patients complicated by MetS, and n=60 normal weight adult healthy controls). Furthermore, the AGEs effects on a dynamic in vitro simulator model of human gut microbiome system (SHIME) will be carried out.
The goal of this project will investigate the potential role of dietary habits in determining obesity and MetS in obese pediatric patients. These data will pave the way to the development of innovative preventive strategies to limit the occurrence of obesity and MetS in pediatric subject, and the creation of a predictive algorithm able to predict the occurrence of MetS combining anamnestic, clinical, nutritional and laboratory data, with the help of Machine Learning a subset of Artificial Intelligence. The project will also contribute to the creation of gut microbiome biobank. Finally, the results of this study will inspire the development of a specific App able to promote the avoidance of UPFs consumption and to validate a sustainable nutritional counseling approach able to promote the choice of hand-made meals and unprocessed or minimally processed foods for the prevention and treatment of malnutrition and malnutrition related conditions.
