Learning from inconsistencies: refining biomarker discovery in viral diseases.

Abstract

Acute viral infections of pandemic potential continue to expose major vulnerabilities in global health systems. The heterogeneous clinical trajectories of these infections, ranging from asymptomatic to life-threatening disease, underscore the urgent need for reliable diagnostic and prognostic biomarkers to support early case identification, risk stratification, and timely intervention. Although traditional diagnostics focused on pathogen detection confirm infection, they provide little insight into disease trajectory, and classical prognostic markers, such as IL-6, C-reactive protein, and D-dimer, lack specificity across viral aetiologies and patient populations. Multi-omics technologies capture molecular signatures with high resolution and have transformed the understanding of chronic diseases with more stable signatures, but acute infections bring unique challenges, as molecular signatures fluctuate rapidly with viral kinetics and immune activation. Biomarkers in acute viral infections are highly time-sensitive, compounded by population-level differences, inconsistent sampling timelines, and non-harmonised testing methods. This Personal View presents a forward-looking framework for developing clinically actionable biomarker signatures that strengthen precision prognostics and improve patient outcomes across the spectrum of acute viral infections.