Differences in the Platelet mRNA Landscape Portend Racial Disparities in Platelet Function and Suggest Novel Therapeutic Targets

Abstract

The African American (AA) population displays a 1.6 to 3‐fold higher incidence of thrombosis and stroke mortality compared with European Americans (EAs). Current antiplatelet therapies target the ADP‐mediated signaling pathway, which displays significant pharmacogenetic variation for platelet reactivity. The focus of this study was to define underlying population differences in platelet function in an effort to identify novel molecular targets for future antiplatelet therapy. We performed deep coverage RNA‐Seq to compare gene expression levels in platelets derived from a cohort of healthy volunteers defined by ancestry determination. We identified > 13,000 expressed platelet genes of which 480 were significantly differentially expressed genes (DEGs) between AAs and EAs. DEGs encoding proteins known or predicted to modulate platelet aggregation, morphology, or platelet count were upregulated in AA platelets. Numerous G‐protein coupled receptors, ion channels, and pro‐inflammatory cytokines not previously associated with platelet function were likewise differentially expressed. Many of the signaling proteins represent potential pharmacologic targets of intervention. Notably, we confirmed the differential expression of cytokines IL32 and PROK2 in an independent cohort by quantitative real‐time polymerase chain reaction, and provide functional validation of the opposing actions of these two cytokines on collagen‐induced AA platelet aggregation. Using Genotype‐Tissue Expression whole blood data, we identified 516 expression quantitative trait locuses with Fst values > 0.25, suggesting that population‐differentiated alleles may contribute to differences in gene expression. This study identifies gene expression differences at the population level that may affect platelet function and serve as potential biomarkers to identify cardiovascular disease risk. Additionally, our analysis uncovers candidate novel druggable targets for future antiplatelet therapies.

PROK2, HRNR, and FIG4 as potential genetic biomarkers of high bleeding propensity in East Asian patients with acute coronary syndrome using ticagrelor

“…PROK2 is therefore supposed to be relevant to platelet function. Incubation with a PROK2 antibody could significantly inhibit the rate of platelet aggregation, indicating the promotion of PROK2 aggregation 21 . Among East Asians in the 1000 Genomes Project, the MAF of PROK2 rs3796224 is 0.270 (consistent with the 0.269 determined in the present study), and 2.29‐fold higher than in Europeans, indicating that the rs3796224 variant resulted in platelet aggregation failure and increased the propensity of bleeding events in East Asians.…”

The Role of Global and Local Ancestry on Clopidogrel Response in African Americans

“… 40 Our previous work on population difference in the platelet transcriptome did not identify ITGA2 as differentially expressed. 41 …”

Prostate cancer cell-platelet bidirectional signaling promotes calcium mobilization, invasion and apoptotic resistance via distinct receptor-ligand pairs

“…Information regarding the RNA-Seq data of platelets from healthy volunteers, including exclusion criteria, demographic data, and sample processing can be found in our previous publication 24 . RNA from PCa cell lines MDA PCa 2b and RC77 T/E was isolated using TRIzol extraction (Invitrogen, Waltham, MA), isopropanol-precipitated with GlycoBlue (Fisher Scientific, Pittsburgh, PA) and quality assessed using an Agilent 2100 Bioanalyzer system where RIN scores of all isolated RNA were ≥ 9.0.…”

“…RNA from PCa cell lines MDA PCa 2b and RC77 T/E was isolated using TRIzol extraction (Invitrogen, Waltham, MA), isopropanol-precipitated with GlycoBlue (Fisher Scientific, Pittsburgh, PA) and quality assessed using an Agilent 2100 Bioanalyzer system where RIN scores of all isolated RNA were ≥ 9.0. The resulting RNA were subjected to RNA-Seq and quality control as previously described 24 . Additional PCa cell line RNA-Seq data were obtained from GEO accession GSE110903 for transcriptome analysis.…”

“…A gene was defined as expressed if it met two criteria: (1) expression in at least 50% of the sequenced samples, and (2) average expression across all sequenced samples was at least 1 transcript per million (TPM). RNA-Seq data were subjected to gene ontology and pathway analyses using the Ingenuity Pathway Analysis (IPA, RRID:SCR_008653) computational tool (Qiagen, Germantown, MD) as previously described 24 .…”