title: Modulation of red blood cell population dynamics is a fundamental homeostatic response to disease.
abstract: Increased red blood cell (RBC) volume variation (RDW) has recently been shown to predict a wide range of mortality and morbidity: death due to cardiovascular disease, cancer, infection, renal disease, and more; complications in heart failure and coronary artery disease, advanced stage and worse prognosis in many cancers, poor outcomes in autoimmune disease, and many more. The mechanisms by which all of these diseases lead to increased RDW are unknown. Here we use a semi-mechanistic mathematical model of in vivo RBC population dynamics to dissect the factors controlling RDW and show that elevated RDW results largely from a slight reduction in the in vivo rate of RBC turnover. RBCs become smaller as they age, and a slight reduction in the rate of RBC turnover allows smaller cells to continue circulating, expanding the low-volume tail of the RBC population's volume distribution, and thereby increasing RDW. Our results show that mildly extended RBC lifespan is a previously unrecognized homeostatic adaptation common to a very wide range of pathologic states, likely compensating for subtle reductions in erythropoietic output. A mathematical model-based estimate of the clearance rate may provide a novel early-warning biomarker for a wide range of morbidity and mortality.
authors.affiliation: Center for Systems Biology and Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts.
authors.forename: Harsh H
authors.initials: HH
authors.lastname: Patel
authors.forename: Hasmukh R
authors.initials: HR
authors.lastname: Patel
authors.forename: John M
authors.initials: JM
authors.lastname: Higgins
mesh_terms: D015415:Biomarkers / Q000097:blood; D002318:Cardiovascular Diseases / Q000097:blood* / Q000175:diagnosis / Q000473:pathology; D004909:Erythrocyte Indices; D004911:Erythrocyte Volume; D004912:Erythrocytes / Q000473:pathology*; D004920:Erythropoiesis; D006706:Homeostasis; D006801:Humans; D008954:Models, Biological; D011379:Prognosis
chemical_list: D015415:Biomarkers