Yang Jiao, Umer Ahmed, M.F. Michelle Sim, Andrea Bejar, Xiaolan Zhang, M. Mesbah Uddin Talukder, Robert Rice, Jason Flannick, Anna I. Podgornaia, Dermot F. Reilly, Jesse M. Engreitz, Maria Kost-Alimova, Kate Hartland, Josep-Maria Mercader, Sara Georges, Vilas Wagh, Marija Tadin-Strapps, John G. Doench, J. Michael Edwardson, Justin J. Rochford, Evan D. Rosen, Amit R. Majithia
Objective: Impaired expansion of peripheral fat contributes to the pathogenesis of insulin resistance and Type 2 Diabetes (T2D). We aimed to
identify novel diseaseegene interactions during adipocyte differentiation.
Methods: 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.
Results: 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 proteine
protein and gene regulatory interactions.
Conclusions: 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.
Mol Metab. 2019 Jun; 24: 108–119. https://doi.org/10.1016/j.molmet.2019.03.001. Epub 2019 Mar 13.