Discovering metabolic disease gene interactions by correlated effects on cellular morphology

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. Epub 2019 Mar 13.