Disciplines
Biology (25%); Computer Sciences (25%); Clinical Medicine (25%); Medical-Theoretical Sciences, Pharmacy (25%)
Keywords
Obesity,
Adipose Tissue,
Spatial Transcriptomics,
Metabolic Disease,
Personalized Medicine
Abstract
The global obesity pandemic is worsening in many parts of the world resulting in an increased
prevalence of metabolic disease like type 2 diabetes. Despite its strong association with the risk of
morbidity, marked interindividual differences in the manifestation of metabolic disease exist, with a
subset of obese individuals being classified as metabolically healthy. In detail, these individuals are
characterized by retained metabolic health despite excess fat. One of the main factors that predicts
metabolic disease risk in obese is the degree of adipose tissue dysfunction. In metabolically healthy
obese individuals, adipocytes safely store lipids to maintain systemic health. In contrast, excessive
adipocyte expansion drives tissue dysfunction and metabolic disease development. Considering this
variability in the metabolic phenotype of obese, one of the main drawbacks in the treatment of obesity
is that obese individuals are considered as a uniform population, being defined by a simple and non-
informative biometric parameter (BMI > 30). Thus, in this project we aim to elucidate adipocyte-specific
factors that drive metabolic disease progression to develop risk-stratified, personalized options for
obesity treatment.