Discovering metabolic disease gene interactions by correlated effects on cellular morphology

Abstract

Objective: Impaired expansion of peripheral fat contributes to the pathogenesis of insulin resistance and Type 2 Diabetes (T2D). We aimed to identify novel disease-gene interactions for adipogenesis and insulin resistance. Methods: To this end, we mined disease associated loci for T2D, adiposity and insulin resistance for adipose expressed genes and ablated the top 100 in human pre-adipocytes via CRISPR/CAS9. The resulting cellular phenotypes were quantified during adipocyte differentiation with high-content imaging to obtain over 107 morphometric measurements. Morphologic profiles were constructed for each gene from these measurements and clustered by morphologic similarity. Results: Clustering revealed a group of 14 genes characterized by decreased lipid accumulation, and enriched with known lipodystrophy genes. For two lipodystrophy genes, BSCL2 and AGPAT2, sub-clusters with PLIN1 and CEBPA based on morphology were validated by independent experiments as novel protein-protein and gene regulatory interactions. Conclusions: Thus, a morphometric approach in adipocytes can resolve multiple cellular mechanisms for metabolic disease loci; the platform enables mechanistic interrogation of the hundreds of metabolic disease loci whose function still remains unknown.