Document Type

Article

Publication Date

9-1-2018

JAX Source

Cardiovasc Res 2018 Sep 1; 114(11):1445-1461

Volume

114

Issue

11

First Page

1445

Last Page

1461

ISSN

1755-3245

PMID

30010800

DOI

https://doi.org/10.1093/cvr/cvy145

Grant

British Heart Foundation

Abstract

Following a myocardial infarction (MI), the immune system helps to repair ischaemic damage and restore tissue integrity, but excessive inflammation has been implicated in adverse cardiac remodelling and development towards heart failure (HF). Pre-clinical studies suggest that timely resolution of inflammation may help prevent HF development and progression. Therapeutic attempts to prevent excessive post-MI inflammation in patients have included pharmacological interventions ranging from broad immunosuppression to immunomodulatory approaches targeting specific cell types or factors with the aim to maintain beneficial aspects of the early post-MI immune response. These include the blockade of early initiators of inflammation including reactive oxygen species and complement, inhibition of mast cell degranulation and leucocyte infiltration, blockade of inflammatory cytokines, and inhibition of adaptive B and T-lymphocytes. Herein, we provide a systematic review on post-MI immunomodulation trials and a meta-analysis of studies targeting the inflammatory cytokine Interleukin-1. Despite an enormous effort into a significant number of clinical trials on a variety of targets, a striking heterogeneity in study population, timing and type of treatment, and highly variable endpoints limits the possibility for meaningful meta-analyses. To conclude, we highlight critical considerations for future studies including (i) the therapeutic window of opportunity, (ii) immunological effects of routine post-MI medication, (iii) stratification of the highly diverse post-MI patient population, (iv) the potential benefits of combining immunomodulatory with regenerative therapies, and at last (v) the potential side effects of immunotherapies.

Comments

The authors are grateful to Dr. Vivek Philip and Dr. Krishna Karuturi at Computational Sciences, The Jackson Laboratory, Bar Harbor, USA for advise on statistical models and analysis. This open access article is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)

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