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

Molecular Metabolism (Jun 2019)

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

Affiliations

Yang Jiao: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
Umer Ahmed: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
M.F. Michelle Sim: University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
Andrea Bejar: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
Xiaolan Zhang: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
M. Mesbah Uddin Talukder: Department of Pharmacology, University of Cambridge, Cambridge CB2 1PD, UK
Robert Rice: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
Jason Flannick: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
Anna I. Podgornaia: Genetics and Pharmacogenomics, Merck & Co., Inc., Boston, MA 02115, USA
Dermot F. Reilly: Genetics and Pharmacogenomics, Merck & Co., Inc., Boston, MA 02115, USA
Jesse M. Engreitz: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
Maria Kost-Alimova: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
Kate Hartland: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
Josep-Maria Mercader: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
Sara Georges: Genetics and Pharmacogenomics, Merck & Co., Inc., Boston, MA 02115, USA
Vilas Wagh: Genetics and Pharmacogenomics, Merck & Co., Inc., Boston, MA 02115, USA
Marija Tadin-Strapps: Genetics and Pharmacogenomics, Merck & Co., Inc., Boston, MA 02115, USA
John G. Doench: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
J. Michael Edwardson: Department of Pharmacology, University of Cambridge, Cambridge CB2 1PD, UK
Justin J. Rochford: University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK; Rowett Institute and the Aberdeen Cardiovascular and Diabetes Centre, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
Evan D. Rosen: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Endocrinology, Diabetes and Obesity, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA; Harvard Medical School, Department of Genetics, Boston, MA 02215, USA
Amit R. Majithia: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Corresponding author. Biomedical Research Facility II building (3A19), University of California San Diego, La Jolla, CA 92093-0688, USA.

Journal volume & issue: Vol. 24
pp. 108 – 119

Abstract

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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 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 protein–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. Keywords: Gene discovery, Functional genomics, Metabolic syndrome, Insulin resistance, Type 2 diabetes, Genetic screen, High content imaging, Lipodystrophy

Published in Molecular Metabolism

ISSN: 2212-8778 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Medicine: Internal medicine
Website: https://www.journals.elsevier.com/molecular-metabolism/

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