Plasma proteome signatures are predictive of mortality in sickle cell disease

Sickle cell disease (SCD) is one of the most common monogenic diseases in the world. This blood disorder damages all organs and is associated with severe systemic complications and increased mortality risk. Predicting SCD severity is currently difficult due to a lack of biomarkers. Here, we measured 5,411 plasma proteins in 376 SCD patients and 103 non-SCD participants to find new predictors of SCD mortality. We used protein signatures of mortality that were developed in non-SCD populations to calculate predicted mortality risk scores in our SCD dataset. The mortality scores were higher in SCD patients than non-SCD participants (P-value=3.7×10 ^-10 ) and were associated with increased mortality in SCD patients (risk factors-adjusted hazard ratio [HR] and 95% confidence interval=2.2 [1.3-3.6], P-value=0.0032). The mortality scores correlated with several clinical variables (e.g. white blood cell count, hemoglobin concentration) and complications (e.g. leg ulcers, stroke) that are clinically relevant yet insufficient individually to predict SCD mortality. In addition to the protein signatures, we found 499 plasma proteins that associate with mortality in SCD patients (false discovery rate ≤5%), including many proteins involved in inflammatory responses such as the IL18 signaling cascade (IL18R1, IL18BP, IL18). Finally, we estimated biological age in SCD patients and non-SCD participants using the plasma proteome data. We confirmed that SCD patients age prematurely (+6.0±5.4 years older than their chronological age) and found that brain biological age positively associates with past occurrences of stroke. Altogether, our results support the use of the plasma proteome to monitor and predict clinical severity in SCD.