Transcriptomic Predictors of Paradoxical Cryptococcosis-Associated Immune Reconstitution Inflammatory Syndrome.

Irina Vlasova-St Louis , Christina Chang, Martyn French, Paul Bohjanen

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Background. Paradoxical cryptococcosis-associated immune reconstitution inflammatory syndrome (C-IRIS) affects ~25% of human immunodeficiency virus (HIV)-infected patients with cryptococcal meningitis (CM) after they commence antiretroviral therapy (ART) resulting in significant morbidity and mortality. Genomic studies in cryptococcal meningitis and C-IRIS are rarely performed. Methods. We assessed whole blood transcriptomic profiles in 54 HIV-infected subjects with CM who developed C-IRIS (27) and compared the results with control subjects (27) who did not experience neurological deterioration over 24 weeks after ART initiation. Samples were analyzed by whole genome microarrays. Results. The predictor screening algorithms identified the low expression of the components of interferon-driven antiviral defense pathways, such as interferon-inducible genes, and higher expression of transcripts that encode granulocyte-dependent proinflammatory response molecules as predictive biomarkers of subsequent C-IRIS. Subjects who developed early C-IRIS (occurred within 12 weeks of ART initiation) were characterized by upregulation of biomarker transcripts involved in innate immunity such as the inflammasome pathway, whereas those with late C-IRIS events (after 12 weeks of ART) were characterized by abnormal upregulation of transcripts expressed in T, B, and natural killer cells, such as IFNG, IL27, KLRB1, and others. The AIM2, BEX1, and C1QB were identified as novel biomarkers for both early and late C-IRIS events. Conclusions. An inability to mount effective interferon-driven antiviral immune response, accompanied by a systemic granulocyte proinflammatory signature, prior to ART initiation, predisposes patients to the development of C-IRIS. Although early and late C-IRIS have seemingly similar clinical manifestations, they have different molecular phenotypes (as categorized by bioinformatics analysis) and are driven by contrasting inflammatory signaling cascades. © The Author(s) 2018. Published by Oxford University Press on behalf of Infectious Diseases Society of America.
Original languageEnglish
JournalOpen Forum Infectious Diseases
Issue number7
Publication statusPublished - Jul 2018


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