Aspirin’s effects of platelet gene expression
After quality analysis of the platelet RNA sequencing data there were 312 platelet mRNA datasets available for analysis from 73 unique patients representing 14333 transcripts. In general, the level of contamination by granulocytes was low (proportion of samples withPTPRC /ITGA2B count ratio ≥ 0.01 =6/312) and did not vary by treatment (likelihood ratio test P-value = 0.11). We have previously shown that platelet gene expression levels are highly correlated within an individual between Visits 1 and Visit 4.[23] Therefore in all subsequent analyses, these two visits were treated equivalently as no-drug treatment visits and no adjustment for leukocyte contamination was performed.
To test our primary hypothesis that aspirin exposure alters the platelet mRNA transcriptome, we used a mixed-effects regression framework to identify transcripts that changed with any aspirin exposure compared to no drug treatment visits. In a univariate analysis using the false discovery rate (FDR) q-value < 0.10 to account for multiple testing we identified 208 transcripts that were differentially expressed (43 down regulated, 165 upregulated, Figure 2, Supplemental Data File 1) after aspirin exposure. To test for aspirin-dose response relationships we used two complementary approaches: 1) contrasting the effects of 81mg vs. 325mg/day and 2) correlating gene expression with salicylate concentrations during aspirin treatment. We found no evidence for differences on platelet gene expression for the set of 208 gene aspirin differentially expressed genes and higher aspirin dose or salicylate concentrations (enrichment p-values = 0.3 and 0.9, respectively).
We used banked platelet RNA from prior research cohorts[19] of healthy adults and patients with diabetes (n= 91 across both cohorts) exposed to 81mg/day or 325mg/day aspirin using a custom Nanostring assay to validate the effects of aspirin. Due to limits on the number of transcripts available in a Nanostring assay, we prioritized the list 208 transcripts based on mean expression and robustness to various starting points for quantifying expression, and genes that exhibited positive correlation (r > 0.25) between RNAseq and Nanostring to a subset of 51 genes to test for validation. Among these 51 genes, we found five that independently validated in the replication cohorts (fixed effects meta-analysis p-value for aspirin effect < 0.05) as changing in response to aspirin exposure: EIF2S3, CHRNB1, EPAS1, SLC9A3R2, and HLA-DRA . (Figure 2B)