Plasma proteome signatures are predictive of mortality in sickle cell disease

ABSTRACT 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. Competing Interest Statement The authors have declared no competing interest. Funding Statement This work was funded by the Canadian Institutes of Health Research (PJT #186159) and the Canada Research Chair program (Lettre). Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: We collected data according to the Helsinki declaration and the study was approved by the Montreal Heart Institute ethics committee, Project #2009-106 (09-1137). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes DATA AVAILABILITY The GEN-MOD proteomic data has not been deposited in a public repository because the data is not public but is available from the corresponding author on request. Scripts to analyze the data and draw figures are available at: http://www.mhi-humangenetics.org/en/resources/#anc_software.