Learning causal graphical models for obesity and other nutrition-related disorders

• Grant number: 22/03420-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: May 01, 2022
• End date: February 29, 2024
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Applied Probability and Statistics
• Principal Investigator: Andressa Cerqueira
• Grantee: Milena Crnkovic Luzia
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Associated research grant: 17/05125-7 - Lifestyle, biochemical and genetic markers as cardiometabolic risk factors: Health Survey in São Paulo City, AP.TEM
• Associated scholarship(s): 23/08647-5 - Application of causal structure learning algorithms to obesity and other risk factors for cardiovascular diseases, BE.EP.IC

Abstract

The study of cause-effect relationships from observational data has received a lot of attention in the empirical sciences, but it is still underdeveloped in the nutritional area. In this way, the goal of this project is the construction of graphical causal models for nutritional disorders using genotypic and phenotypic information from individuals. In this project, phenotypic variables of interest will be selected with the help of domain experts. Then, a descriptive analysis of the data will be carried out followed by a Genome-Wide Association Study (GWAS) in order to select the Single Nucleotide Polymorphisms (SNPs) associated with the phenotype features. After that, causal structure learning algorithms will be applied to learning a graphical casual model from the selected genotypic and phenotypic features. These results allow us to better understand the factors and mechanisms of nutritional disorders in order to establish more effective therapeutic and preventive measures.(AU)