Volume 10 Number 2 2026
Multi-omics integration in sepsis-associated multi-organ dysfunction
Fahdah Mehsan Alotaibi 1, Fatimah Abdullah Alammar 1, Khalid Ali Al Mazirai 1, Kesavaram Padmavathy 2
Integrative Biomedical Research 10 (2) 1-8 https://doi.org/10.25163/biomedical.10210965
Submitted: 07 April 2026 Revised: 25 May 2026 Accepted: 03 June 2026 Published: 05 June 2026
Sepsis kills millions of people every year, and yet the tools clinicians rely on at the bedside still say surprisingly little about why one patient recovers while another, with an identical score, slides into multi-organ failure. This review asks whether systems biology, and multi-omics integration in particular, can begin to close that gap. We conducted a structured narrative review of genomic, epigenomic, transcriptomic, proteomic, phosphoproteomic, metabolomic, lipidomic and metagenomic studies of sepsis-associated organ dysfunction, together with clinical multi-marker and machine-learning studies, and organised the evidence across four biological scales, from subcellular bioenergetics to whole-patient risk. Several patterns recur. Mitochondrial failure, a pyruvate dehydrogenase blockade and regulated cell death, notably ferroptosis, appear as shared drivers, while each organ seems to fail in its own way: glutathione and STING signalling in the liver, VDAC2 malonylation in the heart, succinate accumulation in the brain, Hippo/ACSL4-dependent pericyte loss in the kidney, and loss of short-chain fatty acid producers in the gut. Time-resolved integration exposed dual TLR4 signalling arms that no single omics layer detected. At the bedside, a four-marker panel of procalcitonin, presepsin, bioactive adrenomedullin and interferon-λ3 identified patients with in-hospital mortality near 58%, roughly three times the hazard captured by SOFA alone, and gradient-boosted metabolomic classifiers reached validation AUCs above 0.92. Still, most of this evidence comes from small, single-centre or animal cohorts, turnaround times remain too slow for septic shock, and prospective validation is scarce. Multi-scale integration looks promising, but it is not yet ready to guide therapy at the bedside.
Keywords: sepsis; multiple organ dysfunction syndrome; multi-omics integration; systems biology; biomarkers; machine learning; precision critical care
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