Monogenic diabetes is an underdiagnosed form of diabetes that is caused by DNA variation of strong effect in a single gene. While it is an exciting area for targeted drug development, as some forms of monogenic diabetes can be treated with gene-specific therapies, there are currently few targeted therapies available. Additionally, existing treatments are not able to cure or modify the underlying disease. Therefore, to identify novel therapies, we leveraged CMap, a data resource developed at the Broad Institute that contains over one million gene expression signatures from treatment of cell types with perturbagens including drugs, bioactive small molecules, gene overexpression, and gene knockdown reagents. We analyzed connectivity, or the similarity between two gene expression signatures, to search for perturbagen gene expression signatures opposing gene expression changes associated with monogenic diabetes. We were able to identify 15 classes of medications with significantly enriched connectivity with HNF1A-knockdown by Mann-Whitney U-test (BH-adjusted P< 0.05). Included in these classes were sulfonylureas, which are known to have preferential therapeutic benefit for this specific condition, supporting this method for drug discovery. Other medications included HDAC inhibitors, tyrosine kinase inhibitors, and riboflavin. We also surveyed other genes causing monogenic syndromes that include diabetes, such as PPARG, where CMap indicated high connectivity with thiazolidinediones (BH-adjusted P=0.015), a type 2 diabetes drug class with known mechanism targeting PPARγ, opposing PPARγ-knockdown and beneficial for treating patients with PPARγ-driven familial partial lipodystrophy. Our findings support the use of expression signature mapping as a novel approach for identifying therapies for monogenic diabetes. Further exploration of databases like CMap and validation of identified medication classes could lead to new pharmacological treatments for diabetes.


R.J.Kreienkamp: None. C.Bryan: None. J.C.Florez: Consultant; AstraZeneca, Novo Nordisk, Other Relationship; AstraZeneca, Merck & Co., Inc. M.Udler: None.


National Institutes of Health (T32GM774844, K24HL157960, K23DK114551); Pediatric Endocrine Society

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