KEY POINTS
Previously reported blood donor metabolic phenotypes and genetic traits independently impact hemoglobin increments following RBC transfusion
Donor genetic traits also impact downstream RBC transfusion events highlighting the need for refined donor screening to optimize outcomes
ABSTRACT
Recent large-scale population studies in humans and in murine models of red blood cell (RBC) function identified associations between metabolic phenotypes, or genetic traits linked to them, and transfusion effectiveness. These metabolic phenotypes were identified in independent studies focusing on different mechanistic aspects of the storage lesion. The lack of an integrated analysis raised the question as to whether these signatures were redundant measures of the same underlying processes or could be evaluated together to inform a Precision Medicine approach to clinical transfusion practice. To bridge this gap, we performed an integrated analysis in 5,386 patients who received 6,220 single-unit RBC transfusions, evaluating donor metabolic and genetic results from several studies on hemoglobin increments following RBC transfusion. Our results indicate that previously reported metabolic and genetic predictors of hemoglobin increments remain significant, with an effect size between 0.05 and 0.15 g/dL, when evaluated concurrently. Our observational findings indicate that transfusing RBC units from donors with specific genetic traits, are not only negatively associated with immediate effectiveness but also increased downstream RBC transfusion events, further highlighting the need for refined donor screening practices. Altogether, this evidence supports adoption of a Precision Medicine approach to transfusion practice, where genetic screening of donors at first donation and longitudinal metabolic profiling could inform blood inventory management and allocation strategies, ensuring optimal outcomes for transfusion recipients.
Author notes
Conflict of Interests: None
Data sharing: Details regarding access to the public use dataset through BioLINCC and statistical code available by email to the corresponding author