New frontiers in precision medicine for sepsis-induced immunoparalysis

ABSTRACT

Introduction: In the last decade, the sepsis research field has shifted focus from targeting hyperinflammation to reversing sepsis-induced immunoparalysis. Sepsis-induced immunoparalysis is very heterogeneous: the magnitude and the nature of the underlying immune defects differ considerably between patients, but also within individuals over time. Therefore, a ‘one-treatment-fits-all’ strategy for sepsis-induced immunoparalysis is bound to fail, and an individualized ‘precision medicine’ approach is required. Such a strategy is nevertheless hampered by the unsuitability of the currently available markers to identify the many immune defects that can manifest in individual patients.

Areas covered: We describe the currently available markers for sepsis-induced immunoparalysis and limitations pertaining to their use. Furthermore, future prospects and caveats are discussed, focusing on ‘omics’ approaches: genomics, transcriptomics, epigenomics, and metabolomics. Finally, we present a contemporary overview of adjuvant immunostimulatory therapies.

Expert opinion: The integration of multiple omics techniques offers a systems biology approach which can yield biomarker profiles that accurately and comprehensively gauge the extent and nature of sepsis-induced immunoparalysis. We expect this development to be instrumental in facilitating precision medicine for sepsis-induced immunoparalysis, consisting of the application of targeted immunostimulatory therapies and follow-up measurements to monitor the response to treatment and to titrate or adjust medication.

KEYWORDS:

• Biomarkers
• genomics
• immunostimulory therapy
• metabolomics
• multi-omics
• precision medicine
• sepsis-induced immunoparalysis
• transcriptomics

Article highlights

• More patients survive the consequences of sepsis-induced hyperinflammation, which has led the sepsis research field to shift focus towards preventing or reversing sepsis-induced immunoparalysis, which is characterized by a severely blunted immune response that may result in ineffective clearance of a primary infection and increased susceptibility towards secondary (opportunistic) infections.

• Sepsis-induced immunoparalysis is a heterogeneous condition, of which the magnitude and the nature of the underlying immune defects differ considerably between patients, but also within the same individual over time, rendering a ‘one-treatment-fits-all’ policy inadequate.

• Due to heterogeneity, intrinsically effective immunotherapies (e.g. IFNγ, GM-CSF, IL-7, and anti-PD-1) cannot be used effectively, and routine use of adjunctive immunostimulatory therapy is therefore currently not supported.

• An individualized ‘precision medicine’ approach is required for adjuvant immunostimulatory therapy in patients with sepsis-induced immunoparalysis. Comprehensive immunological phenotyping is a prerequisite for targeted immunostimulatory treatment and is therefore critical for precision medicine to succeed.

• Currently available biomarkers for sepsis-induced immunoparalysis are unlikely suitable for precision medicine. There remains a large gray area consisting of sepsis patients in which immunoparalysis is more subtle or not reflected by a specific marker, as it can be caused by various underlying immune defects which may be independent of one another.

• Omics approaches, such as genomics, epigenomics, transcriptomics, and metabolomics are increasingly used in sepsis research, but up till now, focus has been placed on identifying biomarker profiles that predict outcome.

• Omics approaches have great potential to provide comprehensive insights into the many immune defects that underlie sepsis-induced immunoparalysis. Especially the integration of multiple techniques, a ‘multi-omics’ approach, will likely yield accurate biomarker profiles to gauge the extent and nature of sepsis-induced immunoparalysis.

• The clinical application of (multi-)omics approaches still faces several challenges. Focus should be placed on standardization of analysis techniques, adequate sample sizes, handling of multidimensional datasets, and moving from the currently used terminology approach to an ontology-based disease classification.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.