Obesity is a major risk factor for development of life-threatening comorbidities including T2D, cardiovascular diseases, and metabolic associated steatotic liver disease (MASLD). However, some obese individuals are metabolically healthy, and appear to be protected from these complications. While differences in lifestyle may contribute to metabolically healthy obesity, it is well-established that there is a strong genetic component that appears to associate with the capacity to store fat in adipose tissue.
In WP3, we will explore the association between genetic variation and health status of obese subjects and the regulatory mechanisms of adipose tissue identified in WP1. We will use single nucleus RNA-seq to map baseline and insulin-responsive gene signatures in adipose tissue associated with healthy and unhealthy obesity and predict key molecular drivers of cellular populations and transcriptional states associated with adipose tissue health. We will use a combination of genotyping, sequence-based machine-learning and expression quantitative trait analyses to identify novel potential disease variant and to explore the regulatory mechanisms involved in their impact on adipose tissue health. We will further integrate bulk- and single nucleus RNA-seq data from liver and adipose tissue in WP1 and WP2 to explore bi-directional crosstalk between the two tissues. Key predicted regulators of adipose tissue health and intra- and inter-tissue crosstalk will be further investigated by gain- or loss-of function studies in relevant mouse models of obesity and MASLD.