bioRxivCell Biology
Differential effects of voclosporin and tacrolimus on insulin secretion from human islets
J. Kolic, L. Beet, P. Overby, H. H. Cen, E. Panzhinskiy, D. R. Ure, J. L. Cross, R. B. Huizinga, J. D. Johnson
Abstract
ContextThe incidence of new onset diabetes after transplant (NODAT) has increased over the past decade, likely due to calcineurin inhibitor-based immunosuppressants, including tacrolimus (TAC) and cyclosporin (CsA). Voclosporin (VCS), a next generation calcineurin inhibitor is reported to cause fewer incidences of NODAT but the reason is unclear. ObjectiveWhilst calcineurin signaling plays important roles in pancreatic {beta}-cell survival, proliferation, and function, its effects on human {beta}-cells remain understudied. In particular, we do not understand why some calcineurin inhibitors have more profound effects on the incidence of NODAT. MethodsWe compared the effects of TAC and VCS on the dynamics of insulin secretory function, programmed cell death rate, and the transcriptomic profile of human islets. We studied two clinically relevant doses of TAC (10 ng/ml, 30 ng/ml) and VCS (20 ng/ml, 60 ng/ml), meant to approximate the clinical trough and peak concentrations. ResultsTAC, but not VCS, caused a significant impairment of 15 mM glucose-stimulated and 30 mM KCl-stimulated insulin secretion. This points to molecular defects in the distal stages of exocytosis after voltage-gated Ca2+ entry. No significant effects on islet cell survival or total insulin content were identified. RNA sequencing showed that TAC significantly decreased the expression of 17 genes, including direct and indirect regulators of exocytosis (SYT16, TBC1D30, PCK1, SMOC1, SYT5, PDK4, and CREM), whereas VCS has less broad and milder effects on gene expression. ConclusionsClinically relevant doses of TAC, but not VCS, directly inhibit insulin secretion from human islets, likely via transcriptional control of exocytosis machinery.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
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