Cell-type deconvolution with immune pathways identifies gene networks of host defense and immunopathology in leprosy
Megan S. Inkeles, … , Matteo Pellegrini, Robert L. Modlin
Megan S. Inkeles, … , Matteo Pellegrini, Robert L. Modlin
Published September 22, 2016
Citation Information: JCI Insight. 2016;1(15):e88843. https://doi.org/10.1172/jci.insight.88843.
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Research Article Immunology Infectious disease

Cell-type deconvolution with immune pathways identifies gene networks of host defense and immunopathology in leprosy

Abstract

Transcriptome profiles derived from the site of human disease have led to the identification of genes that contribute to pathogenesis, yet the complex mixture of cell types in these lesions has been an obstacle for defining specific mechanisms. Leprosy provides an outstanding model to study host defense and pathogenesis in a human infectious disease, given its clinical spectrum, which interrelates with the host immunologic and pathologic responses. Here, we investigated gene expression profiles derived from skin lesions for each clinical subtype of leprosy, analyzing gene coexpression modules by cell-type deconvolution. In lesions from tuberculoid leprosy patients, those with the self-limited form of the disease, dendritic cells were linked with MMP12 as part of a tissue remodeling network that contributes to granuloma formation. In lesions from lepromatous leprosy patients, those with disseminated disease, macrophages were linked with a gene network that programs phagocytosis. In erythema nodosum leprosum, neutrophil and endothelial cell gene networks were identified as part of the vasculitis that results in tissue injury. The present integrated computational approach provides a systems approach toward identifying cell-defined functional networks that contribute to host defense and immunopathology at the site of human infectious disease.

Authors

Megan S. Inkeles, Rosane M.B. Teles, Delila Pouldar, Priscila R. Andrade, Cressida A. Madigan, David Lopez, Mike Ambrose, Mahdad Noursadeghi, Euzenir N. Sarno, Thomas H. Rea, Maria T. Ochoa, M. Luisa Iruela-Arispe, William R. Swindell, Tom H.M. Ottenhoff, Annemieke Geluk, Barry R. Bloom, Matteo Pellegrini, Robert L. Modlin

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Figure 2

Cell-type–specific enrichment (deconvolution).

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Cell-type–specific enrichment (deconvolution). (A) Cell-type–specific de...
(A) Cell-type–specific deconvolution of all leprosy clinical subtypes. For each of 19 immune cell–type–specific signatures, signature enrichment scores were calculated using average gene expression for each leprosy subtype and normalized to Z scores. Each Z score represents the enrichment for a particular immune cell–type signature in the gene expression profile of one leprosy subtype relative to the other subtypes. Enrichment profiles for each condition were clustered using Euclidean distance and displayed in a heatmap, for which columns correspond to leprosy subtypes and rows correspond to cell types. Each individual square corresponds to the enrichment for one immune cell type in a specific leprosy subtype, with darker squares indicating higher enrichment. (B) Cell-type deconvolution of the proportional median lists for all leprosy subtypes. The gene count represents the number of genes in the proportional median list that overlapped with the specific cell-type list. ENL, erythema nodosum leprosum; L-lep, lepromatous leprosy; RR, reversal reaction; T-lep, tuberculoid leprosy.