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Interferon at the cellular, individual, and population level in hepatitis C virus infection: Its role in the interferon‐free treatment era
Author(s) -
Raja Rubesh,
Baral Subhasish,
Dixit Narendra M.
Publication year - 2018
Publication title -
immunological reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.839
H-Index - 223
eISSN - 1600-065X
pISSN - 0105-2896
DOI - 10.1111/imr.12689
Subject(s) - interferon , biology , hepatitis c virus , population , immunology , hepatitis c , viral replication , virology , hepacivirus , replication (statistics) , virus , medicine , environmental health
Summary The advent of powerful direct‐acting antiviral agents ( DAA s) has revolutionized the treatment of hepatitis C. DAA s cure nearly all patients with short duration, oral treatments. Significant efforts are now underway to optimize DAA ‐based treatments. We discuss the potential role of interferon in this optimization. Clinical studies present compelling evidence that DAA s perform better in treatment‐naive individuals than in individuals who previously failed treatment with interferon, a surprising correlation because interferon and DAA s are thought to act independently. Recent mathematical models explore a mechanistic hypothesis underlying this correlation. The hypothesis invokes the action of interferon at the cellular, individual, and population levels. Strong interferon responses prevent the productive infection of cells, reduce viral replication, and impede the development of resistance to DAA s in infected individuals and improve cure rates elicited by DAA s in treated populations. The models develop descriptions of these processes, integrate them into a comprehensive framework, and capture clinical data quantitatively, providing a successful test of the hypothesis. Individuals with strong endogenous interferon responses thus present a promising subpopulation for reducing DAA treatment durations. This review discusses the conceptual advances made by the models, highlights the new insights they unravel, and examines their applicability to optimize DAA ‐based treatments.