Discovering metabolic disease gene interactions by correlated effects on cellular morphology

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 during adipocyte differentiation. Genes in disease-associated loci for T2D, adiposity and insulin resistance were ranked according to expression in human adipocytes. The top 125 genes were ablated in human pre-adipocytes via CRISPR/CAS9 and the resulting cellular phenotypes quantified during adipocyte differentiation with high-content microscopy and automated image analysis. Morphometric measurements were extracted from all images and used to construct morphologic profiles for each gene. Over 107 morphometric measurements were obtained. Clustering of the morphologic profiles accross all genes revealed a group of 14 genes characterized by decreased lipid accumulation, and enriched for known lipodystrophy genes. For two lipodystrophy genes, BSCL2 and AGPAT2, sub-clusters with PLIN1 and CEBPA identifed by morphological similarity were validated by independent experiments as novel protein–protein and gene regulatory interactions. A morphometric approach in adipocytes can resolve multiple cellular mechanisms for metabolic disease loci; this approach enables mechanistic interrogation of the hundreds of metabolic disease loci whose function still remains unknown. •Loss-of-function genetic screen in human adipocytes for 125 genes selected from metabolic disease-associated loci.•Genetic screen read out by cellular morphometry— 77,000 images taken with 400 morphological features extracted per image.•Pairwise mechanistic interactions between genes identified by correlations of cellular morphometry—two interactions validated.•Novel interaction between BSCL2 and PLIN1 from biophysical association of proteins at lipid droplet surface.•Novel interaction between CEBPA and AGPAT2 from CEBPA dependent transcription of AGPAT2.