BACH2 inhibition reverses β cell failure in type 2 diabetes models
Jinsook Son, … , Domenico Accili, Andrea Califano
Jinsook Son, … , Domenico Accili, Andrea Califano
Published December 15, 2021
Citation Information: J Clin Invest. 2021;131(24):e153876. https://doi.org/10.1172/JCI153876.
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Research Article Endocrinology Metabolism

BACH2 inhibition reverses β cell failure in type 2 diabetes models

Abstract

Type 2 diabetes (T2D) is associated with defective insulin secretion and reduced β cell mass. Available treatments provide a temporary reprieve, but secondary failure rates are high, making insulin supplementation necessary. Reversibility of β cell failure is a key translational question. Here, we reverse engineered and interrogated pancreatic islet–specific regulatory networks to discover T2D-specific subpopulations characterized by metabolic inflexibility and endocrine progenitor/stem cell features. Single-cell gain- and loss-of-function and glucose-induced Ca2+ flux analyses of top candidate master regulatory (MR) proteins in islet cells validated transcription factor BACH2 and associated epigenetic effectors as key drivers of T2D cell states. BACH2 knockout in T2D islets reversed cellular features of the disease, restoring a nondiabetic phenotype. BACH2-immunoreactive islet cells increased approximately 4-fold in diabetic patients, confirming the algorithmic prediction of clinically relevant subpopulations. Treatment with a BACH inhibitor lowered glycemia and increased plasma insulin levels in diabetic mice, and restored insulin secretion in diabetic mice and human islets. The findings suggest that T2D-specific populations of failing β cells can be reversed and indicate pathways for pharmacological intervention, including via BACH2 inhibition.

Authors

Jinsook Son, Hongxu Ding, Thomas B. Farb, Alexander M. Efanov, Jiajun Sun, Julie L. Gore, Samreen K. Syed, Zhigang Lei, Qidi Wang, Domenico Accili, Andrea Califano

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Figure 2

iterClust classifies ND and T2D islet cells into different biological states.

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iterClust classifies ND and T2D islet cells into different biological st...
(A) iterClust analyses performed using ND and T2D islet cells. The resulting cluster architecture was visualized as a heatmap. Each subgroup is color coded. Each bar denotes a single cell. Black bars represent T2D cells and white bars ND cells. KRT19, AMY2A, PPY, SST, GCG, and INS mRNA expression is plotted at the single-cell level. metaViper-inferred protein activity for β or α cell factors, metabolic inflexibility, endocrine progenitor, and stemness markers is plotted at the single-cell level. RPM, reads per million mapped reads. (B) Violin plots showing the distribution of cells in each cluster based on integrated activity of β cell factors (top), α cell factors (middle), or stemness markers (bottom). (C) 3D plot showing integrated β cell factor, α cell factor, and stemness activity on the x, y, and z axes, respectively, at the single-cell level. (D) 3D plot as in C but based on the average cell behaviors of each cluster. Red arrows indicate T2D-enriched clusters, MI+2 (T2D-β-like) and MI–4 and MI–5 (both T2D-α-like).