Platelet microRNA-mRNA coexpression profiles correlate with platelet reactivity

• Published in: Blood Vol. 117; no. 19; pp. 5189 - 5197
• Main Authors: Nagalla, Srikanth, Shaw, Chad, Kong, Xianguo, Kondkar, Altaf A., Edelstein, Leonard C., Ma, Lin, Chen, Junmei, McKnight, G. Stanley, López, José A., Yang, Linghai, Jin, Ying, Bray, Molly S., Leal, Suzanne M., Dong, Jing-fei, Bray, Paul F.
• Format: Journal Article
• Language: English
• Published: Washington, DC Elsevier Inc 12.05.2011; Americain Society of Hematology; American Society of Hematology
• Subjects: Biological and medical sciences; Blood Platelets - metabolism; Cluster Analysis; Gene Expression; Gene Expression Profiling; Genome-Wide Association Study; Hematologic and hematopoietic diseases; Humans; Medical sciences; MicroRNAs - analysis; Oligonucleotide Array Sequence Analysis; Platelet Activation - genetics; Platelets and Thrombopoiesis; RNA, Messenger - analysis; Gene silencing; Platelet; RNA interference; Messenger RNA; Reactivity; Hematology; Coexpression; Micro RNA
• ISSN: 0006-4971; 1528-0020; 1528-0020
• DOI: 10.1182/blood-2010-09-299719

MicroRNAs (miRNAs) regulate cell physiology by altering protein expression, but the biology of platelet miRNAs is largely unexplored. We tested whether platelet miRNA levels were associated with platelet reactivity by genome-wide profiling using platelet RNA from 19 healthy subjects. We found that human platelets express 284 miRNAs. Unsupervised hierarchical clustering of miRNA profiles resulted in 2 groups of subjects that appeared to cluster by platelet aggregation phenotypes. Seventy-four miRNAs were differentially expressed (DE) between subjects grouped according to platelet aggregation to epinephrine, a subset of which predicted the platelet reactivity response. Using whole genome mRNA expression data on these same subjects, we computationally generated a high-priority list of miRNA-mRNA pairs in which the DE platelet miRNAs had binding sites in 3′-untranslated regions of DE mRNAs, and the levels were negatively correlated. Three miRNA-mRNA pairs (miR-200b:PRKAR2B, miR-495:KLHL5, and miR-107:CLOCK) were selected from this list, and all 3 miRNAs knocked down protein expression from the target mRNA. Reduced activation from platelets lacking PRKAR2B supported these findings. In summary, (1) platelet miRNAs are able to repress expression of platelet proteins, (2) miRNA profiles are associated with and may predict platelet reactivity, and (3) bioinformatic approaches can successfully identify functional miRNAs in platelets.