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Exhausted-like CD8+ T cell phenotypes linked to C-peptide preservation in alefacept-treated T1D subjects
Kirsten E. Diggins, … , S. Alice Long, Peter S. Linsley
Kirsten E. Diggins, … , S. Alice Long, Peter S. Linsley
Published December 22, 2020
Citation Information: JCI Insight. 2021;6(3):e142680. https://doi.org/10.1172/jci.insight.142680.
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Research Article Immunology

Exhausted-like CD8+ T cell phenotypes linked to C-peptide preservation in alefacept-treated T1D subjects

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Abstract

Clinical trials of biologic therapies in type 1 diabetes (T1D) aim to mitigate autoimmune destruction of pancreatic β cells through immune perturbation and serve as resources to elucidate immunological mechanisms in health and disease. In the T1DAL trial of alefacept (LFA3-Ig) in recent-onset T1D, endogenous insulin production was preserved in 30% of subjects for 2 years after therapy. Given our previous findings linking exhausted-like CD8+ T cells to beneficial response in T1D trials, we applied unbiased analyses to sorted CD8+ T cells to evaluate their potential role in T1DAL. Using RNA sequencing, we found that greater insulin C-peptide preservation was associated with a module of activation- and exhaustion-associated genes. This signature was dissected into 2 CD8 memory phenotypes through correlation with cytometry data. These cells were hypoproliferative, shared expanded rearranged TCR junctions, and expressed exhaustion-associated markers including TIGIT and KLRG1. The 2 phenotypes could be distinguished by reciprocal expression of CD8+ T and NK cell markers (GZMB, CD57, and inhibitory killer cell immunoglobulin-like receptor [iKIR] genes), versus T cell activation and differentiation markers (PD-1 and CD28). These findings support previous evidence linking exhausted-like CD8+ T cells to successful immune interventions for T1D, while suggesting that multiple inhibitory mechanisms can promote this beneficial cell state.

Authors

Kirsten E. Diggins, Elisavet Serti, Virginia Muir, Mario Rosasco, TingTing Lu, Elisa Balmas, Gerald Nepom, S. Alice Long, Peter S. Linsley

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Cohort demographics for RNA-seq and cytometry analyses

Cohort demographics for RNA-seq and cytometry analyses


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