Back

Ticagrelor responsive platelet genes are associated with platelet function and bleeding

Myers, R. A.; Ortel, T. L.; Waldrop, A.; Dave, S.; Ginsburg, G.; Voora, D.

2022-03-18 cardiovascular medicine
10.1101/2022.03.18.22270280
Show abstract

Structured AbstractO_ST_ABSImportanceC_ST_ABSTicagrelor inhibits platelet function, prevents myocardial infarction, and causes bleeding. A comprehensive analysis of the on- and off-target platelet effects of ticagrelor that underlie its clinical effects is lacking. ObjectiveTo test the hypothesis that platelet transcripts that change in response to ticagrelor exposure are associated with platelet function or bleeding. DesignA discovery cohort of healthy volunteers were sequentially exposed to aspirin, aspirin washout, and ticagrelor. Messenger RNA sequencing (mRNAseq) of purified platelets was performed pre/post each exposure. We defined the ticagrelor exposure signature (TES) as the ratio of mean expression of up-vs. down-regulated genes by ticagrelor that were prioritized based on lasso regression, weighted gene co-expression networks, and isoform level analyses. A separate healthy cohort was recruited to validate ticagrelors effects on TES genes measured using Nanostring. Platelet function was measured at baseline and in response to ticagrelor exposure in all participants. Self-reported bleeding was systematically queried during periods of ticagrelor exposure. SettingAn early phase, academic, clinical research unit. ParticipantsSelf-reported, healthy volunteers age > 30 and < 75, non-smoking, taking no daily prescribed medications. ExposuresTicagrelor (90 mg twice daily) and aspirin (81 mg/day and 325 mg/day) each for 4 weeks. Main outcomes and measuresExpression levels of platelet messenger RNA, platelet count, mean platelet volume, and 9 different measures of ex vivo platelet function (aggregated into a previously described platelet function score), and self-reported bleeding at baseline and after each exposure. ResultsIn the discovery cohort (n = 58, mean age 43, 39 female) platelet mRNAseq identified (FDR < 5%) 1820 up- and 1589 down-regulated genes associated with ticagrelor exposure. We prioritized 84 of these transcripts to calculate a TES score, which was increased by ticagrelor and unaffected by either dose of aspirin. In an independent cohort (n = 49, mean age 44, 24 female) we validated that ticagrelor exposure (beta = 0.48, SE = 0.08, p < 0.0001) increases TES scores. In combined analyses of discovery and validation cohorts, when TES levels were calculated using baseline platelet RNA, higher TES levels were associated with lower levels of baseline platelet function (meta-analysis beta = -0.60, standard error [SE] 0.29, P = 0.04) and self-reported bleeding during ticagrelor exposure (meta-analysis beta = 0.28, standard error [SE] = 0.14, P = 0.04). In contrast, we found no associations between bleeding with baseline platelet count, platelet volume, or platelet function. Conclusions and RelevanceTicagrelor exposure reproducibly and specifically changes a set of platelet transcripts, the baseline levels of which are a biomarker for platelet function and bleeding tendency on ticagrelor. Key PointsO_ST_ABSQuestionC_ST_ABSWhat are the global effects of ticagrelor exposure on platelets beyond platelet inhibition? FindingsIn an experimental human study of different antiplatelet therapies, we comprehensively characterized the effects of ticagrelor on platelet messenger RNA (mRNA). We found that 4 weeks of 90mg twice daily ticagrelor therapy specifically and reproducibly changes the levels of selected platelet mRNA. At baseline, volunteers with levels of platelet gene expression that mimic ticagrelor exposure had lower levels of platelet function and when exposed to ticagrelor a greater tendency for minor bleeding. MeaningBy using ticagrelor exposure as a molecular probe, we identified a platelet RNA biomarker that may identify patients at higher risk for ticagrelor-associated bleeding.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Circulation
based on 37 papers
Top 0.1%
16.0%
2
Journal of Thrombosis and Haemostasis
based on 10 papers
Top 0.1%
13.0%
3
Arteriosclerosis, Thrombosis, and Vascular Biology
based on 11 papers
Top 0.2%
8.6%
4
Circulation: Genomic and Precision Medicine
based on 30 papers
Top 1.0%
6.6%
5
Journal of the American Heart Association
based on 92 papers
Top 5%
4.7%
6
Atherosclerosis
based on 16 papers
Top 0.7%
4.7%
50% of probability mass above
7
eLife
based on 262 papers
Top 8%
2.9%
8
Blood
based on 14 papers
Top 0.5%
1.9%
9
Scientific Reports
based on 701 papers
Top 68%
1.8%
10
Journal of Clinical Investigation
based on 50 papers
Top 2%
1.8%
11
Open Heart
based on 18 papers
Top 3%
1.8%
12
Nature Communications
based on 483 papers
Top 30%
1.6%
13
Hypertension
based on 20 papers
Top 2%
1.6%
14
BMC Medicine
based on 155 papers
Top 12%
1.6%
15
Clinical Pharmacology & Therapeutics
based on 19 papers
Top 0.9%
1.6%
16
Frontiers in Cardiovascular Medicine
based on 33 papers
Top 5%
1.4%
17
Nature Genetics
based on 72 papers
Top 7%
1.4%
18
PLOS ONE
based on 1737 papers
Top 91%
1.4%
19
Genome Medicine
based on 56 papers
Top 5%
1.4%
20
Nature
based on 58 papers
Top 7%
1.2%
21
JCI Insight
based on 63 papers
Top 5%
0.8%
22
Journal of Clinical Medicine
based on 77 papers
Top 15%
0.8%
23
PLOS Genetics
based on 39 papers
Top 5%
0.8%
24
Clinical and Translational Science
based on 14 papers
Top 2%
0.8%
25
EBioMedicine
based on 21 papers
Top 2%
0.7%
26
The American Journal of Cardiology
based on 15 papers
Top 4%
0.7%
27
The American Journal of Human Genetics
based on 77 papers
Top 7%
0.7%
28
iScience
based on 74 papers
Top 8%
0.7%