Biomolecular map of albumin identifies signatures of severity and early mortality in acute liver failure

•Albumin is hyperoxidised and hyperglycated and shows reduced (60%) binding capacity in ALF. •Albumin biomolecular composition (bound multi-omics profile) is severely deranged and correlates with severity in ALF. •Albumin biomolecular integration highlights hyperinflammation and mitochondrial failure linked to non-survival in ALF. •Albumin-bound metabolome showed the highest diagnostic accuracy for the prediction of early mortality in ALF. Background & Aims Acute liver failure (ALF) is associated with high mortality. Alterations in albumin structure and function have been shown to correlate with outcomes in cirrhosis. We undertook a biomolecular analysis of albumin to determine its correlation with hepatocellular injury and early mortality in ALF. Methods Altogether, 225 participants (200 patients with ALF and 25 healthy controls [HC]) were enrolled. Albumin was purified from the baseline plasma of the training cohort (ALF, n = 40; survivors, n = 8; non-survivors, n = 32; and HC, n = 5); analysed for modifications, functionality, and bound multi-omics signatures; and validated in a test cohort (ALF, n = 160; survivors, n = 53; non-survivors, n = 107; and HC, n = 20). Results In patients with ALF, albumin is more oxidised and glycosylated with a distinct multi-omics profile than that in HC, more so in non-survivors (p <0.05). In non-survivors, albumin was more often bound (p <0.05, false discovery rate <0.01) to proteins associated with inflammation, advanced glycation end product, metabolites linked to arginine, proline metabolism, bile acid, and mitochondrial breakdown products. Increased bacterial taxa (Listeria, Clostridium, etc.) correlated with lipids (triglycerides [4:0/12:0/12:0] and phosphatidylserine [39:0]) and metabolites (porphobilinogen and nicotinic acid) in non-survivors (r2 >0.7). Multi-omics signature-based probability of detection for non-survival was >90% and showed direct correlation with albumin functionality and clinical parameters (r2 >0.85). Probability-of-detection metabolites built on the top five metabolites, namely, nicotinic acid, l-acetyl carnitine, l-carnitine, pregnenolone sulfate, and N-(3-hydroxybutanoyl)-l-homoserine lactone, showed diagnostic accuracy of 98% (AUC 0.98, 95% CI 0.95–1.0) and distinguish patients with ALF predisposed to early mortality (log-rank <0.05). On validation using high-resolution mass spectrometry and five machine learning algorithms in test cohort 1 (plasma and paired one-drop blood), the metabolome panel showed >92% accuracy/sensitivity and specificity for prediction of mortality. Conclusions In ALF, albumin is hyperoxidised and substantially dysfunctional. Our study outlines distinct ‘albuminome’ signatures capable of distinguishing patients with ALF predisposed to early mortality or requiring emergency liver transplantation. Impacts and Implications Here, we report that the biomolecular map of albumin is distinct and linked to severity and outcome in patients with acute liver failure (ALF). Detailed structural, functional, and albumin-omics analysis in patients with ALF led to the identification and classification of albumin-bound biomolecules, which could segregate patients with ALF predisposed to early mortality. More importantly, we found albumin-bound metabolites indicative of mitochondrial damage and hyperinflammation as a putative indicator of <30-day mortality in patients with ALF. This preclinical study validates the utility of albuminome analysis for understanding the pathophysiology and development of poor outcome indicators in patients with ALF. Acute liver failure (ALF) is associated with high mortality. Alterations in albumin structure and function have been shown to correlate with outcomes in cirrhosis. We undertook a biomolecular analysis of albumin to determine its correlation with hepatocellular injury and early mortality in ALF. Altogether, 225 participants (200 patients with ALF and 25 healthy controls [HC]) were enrolled. Albumin was purified from the baseline plasma of the training cohort (ALF, n = 40; survivors, n = 8; non-survivors, n = 32; and HC, n = 5); analysed for modifications, functionality, and bound multi-omics signatures; and validated in a test cohort (ALF, n = 160; survivors, n = 53; non-survivors, n = 107; and HC, n = 20). In patients with ALF, albumin is more oxidised and glycosylated with a distinct multi-omics profile than that in HC, more so in non-survivors (p <0.05). In non-survivors, albumin was more often bound (p <0.05, false discovery rate <0.01) to proteins associated with inflammation, advanced glycation end product, metabolites linked to arginine, proline metabolism, bile acid, and mitochondrial breakdown products. Increased bacterial taxa (Listeria, Clostridium, etc.) correlated with lipids (triglycerides [4:0/12:0/12:0] and phosphatidylserine [39:0]) and metabolites (porphobilinogen and nicotinic acid) in non-survivors (r2 >0.7). Multi-omics signature-based probability of detection for non-survival was >90% and showed direct correlation with albumin functionality and clinical parameters (r2 >0.85). Probability-of-detection metabolites built on the top five metabolites, namely, nicotinic acid, l-acetyl carnitine, l-carnitine, pregnenolone sulfate, and N-(3-hydroxybutanoyl)-l-homoserine lactone, showed diagnostic accuracy of 98% (AUC 0.98, 95% CI 0.95–1.0) and distinguish patients with ALF predisposed to early mortality (log-rank <0.05). On validation using high-resolution mass spectrometry and five machine learning algorithms in test cohort 1 (plasma and paired one-drop blood), the metabolome panel showed >92% accuracy/sensitivity and specificity for prediction of mortality. In ALF, albumin is hyperoxidised and substantially dysfunctional. Our study outlines distinct ‘albuminome’ signatures capable of distinguishing patients with ALF predisposed to early mortality or requiring emergency liver transplantation.