Granzyme A in Human Platelets Regulates the Synthesis of Proinflammatory Cytokines by Monocytes in Aging

This information is current as Robert A. Campbell, Zechariah Franks, Anish Bhatnagar, of September 24, 2021. Jesse W. Rowley, Bhanu K. Manne, Mark A. Supiano, Hansjorg Schwertz, Andrew S. Weyrich and Matthew T. Rondina J Immunol published online 22 November 2017

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The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2017 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published November 22, 2017, doi:10.4049/jimmunol.1700885 The Journal of Immunology

Granzyme A in Human Platelets Regulates the Synthesis of Proinflammatory Cytokines by Monocytes in Aging

Robert A. Campbell,*,† Zechariah Franks,* Anish Bhatnagar,* Jesse W. Rowley,*,‡ Bhanu K. Manne,* Mark A. Supiano,x,{ Hansjorg Schwertz,*,‖ Andrew S. Weyrich,*,‡ and Matthew T. Rondina*,†,x

Dysregulated inflammation is implicated in the pathobiology of aging, yet platelet–leukocyte interactions and downstream cytokine synthesis in aging remains poorly understood. Platelets and monocytes were isolated from healthy younger (age <45, n = 37) and older (age ‡65, n = 30) adults and incubated together under autologous and nonautologous conditions. Synthesis of inflammatory cytokines by monocytes, alone or in the presence of platelets, was examined. Next-generation RNA-sequencing allowed for unbiased profiling of the platelet transcriptome in aging. Basal IL-8 and MCP-1 synthesis by monocytes alone did not differ between older and younger adults. However, in the presence of autologous platelets, monocytes from older adults synthesized Downloaded from greater IL-8 (41 6 5 versus 9 6 2 ng/ml, p < 0.0001) and MCP-1 (867 6 150 versus 216 6 36 ng/ml, p < 0.0001) than younger adults. Platelets from older adults were sufficient for upregulating the synthesis of inflammatory cytokines by monocytes. Using RNA-sequencing of platelets followed by validation via RT-PCR and immunoblot, we discovered that granzyme A (GrmA), a serine protease not previously identified in human platelets, increases with aging (∼9-fold versus younger adults, p < 0.05) and governs increased IL-8 and MCP-1 synthesis through TLR4 and caspase-1. Inhibiting GrmA reduced excessive IL-8 and MCP-1 synthesis in aging to levels similar to younger adults. In summary, human aging is associated with changes in the platelet http://www.jimmunol.org/ transcriptome and proteome. GrmA is present and bioactive in human platelets, is higher in older adults, and controls the synthesis of inflammatory cytokines by monocytes. Alterations in the platelet molecular signature and signaling to monocytes may contribute to dysregulated inflammatory syndromes in older adults. The Journal of Immunology, 2018, 200: 000–000.

latelets are anucleate cells with long-established roles functions in aging are thought to contribute to this heightened central to hemostasis initiation and vascular wall repair. thrombosis risk (6), but remain under studied. Thrombosis and Initially thought to be merely circulating cell fragments inflammation are centrally linked and injurious inflammation is P by guest on September 24, 2021 with a relatively fixed repertoire of functional responses, platelets central to the pathobiology of aging. For example, aging is asso- are increasingly recognized to be versatile effector cells that bridge ciated with elevated levels of IL-6, IL-8, and C-reactive protein thrombotic, inflammatory, and immune continuums (1, 2). Activated (7, 8). IL-6 has been implicated in mediating thrombosis during platelets stably adhere to and tether monocytes via P-selectin/P-selectin systemic inflammatory insults (9, 10). Increased levels of IL-6, IL-8, glycoprotein ligand 1 (PSGL-1) and, in parallel, secrete RANTES and MCP-1 during aging may contribute to adverse outcomes in older from platelet a granules. RANTES then binds to CCL5 on monocytes, adults (11–13). driving downstream synthesis of proinflammatory gene products by Whereas classic platelet hemostatic functions have been examined monocytes (3, 4). in aging, age-associated alterations in the platelet transcriptome and Thromboembolic events remain the most common cause of proteome and their effects on platelet–monocyte signaling events morbidity and mortality in older adults (5) and dysregulated platelet have not previously been examined. In this study, we examined

*Molecular Medicine Program, University of Utah, Salt Lake City, UT 84112; Award Number UL1TR001067. This work was also supported by the University of †Division of General Internal Medicine, Department of Internal Medicine, School Utah Flow Cytometry Facility in addition to the National Cancer Institute through of Medicine, University of Utah, Salt Lake City, UT 84132; ‡Division of Respiratory, Award Number 5P30CA042014-24. The contents of this article are the responsibility Critical Care, and Occupational Pulmonary Medicine, University of Utah, Salt Lake of the authors and do not necessarily represent the official views of the U.S. Depart- City, UT 84132; xGeorge E. Wahlen Veterans Affairs Medical Center, Geriatric ment of Veterans Affairs, the U.S. Government, or the National institutes of Health. Research, Education and Clinical Center, Salt Lake City, UT 84148; {Division of The sequences presented in this article have been submitted to Gene Expression Geriatrics, School of Medicine, University of Utah, Salt Lake City, UT 84132; and ‖ Omnibus under accession number SRA2779748. Fastq files have been submitted to Division of Vascular Surgery, School of Medicine, University of Utah, Salt Lake the Sequence Read Archive under accession numbers SRR5907423–SRR5907428. City, UT 84132 Address correspondence and reprint requests to Dr. Matthew T. Rondina, Molecular ORCIDs: 0000-0003-0027-694X (R.A.C.); 0000-0001-7078-6959 (A.B.); 0000- Medicine Program, University of Utah Health Sciences Center, Eccles Institute of 0001-6848-4484 (B.K.M.); 0000-0003-3455-3730 (M.T.R.). Human Genetics, Building 533, Room 4220A, 15 North 2030 East, Salt Lake City, Received for publication June 16, 2017. Accepted for publication October 30, 2017. UT 84112. E-mail address: [email protected] This work was supported by National Heart, Lung, and Blood Institute Grants The online version of this article contains supplemental material. HL112311, HL130541, HL126547 (all to A.S.W. and M.T.R.), and HL066277 (to Abbreviations used in this article: FPKM, fragment per kilobase of transcript per A.S.W.), National Institute on Aging Grant AG048022 (to M.T.R.), National Institute million mapped reads; GrmA, granzyme A; HSA, human serum albumin; PF4, plate- of Diabetes and Digestive and Kidney Diseases Grant GM103806 (to J.W.R.), and a let factor 4; PMA, platelet–monocyte aggregation; PSGL-1, P-selectin glycoprotein pilot award funded by the University of Utah Center on Aging (to M.T.R.). This ligand 1; qRT-PCR, quantitative RT-PCR; rhGrmA, recombinant human GrmA; material is the result of work supported with resources and the use of facilities at the RNA-seq, RNA-sequencing. George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT. The research reported in this publication was supported (in part or in full) by the National Center Ó for Advancing Translational Sciences of the National Institutes of Health under Copyright 2017 by The American Association of Immunologists, Inc. 0022-1767/17/$35.00

www.jimmunol.org/cgi/doi/10.4049/jimmunol.1700885 2 PLATELET GRANZYME A REGULATES CYTOKINE SYNTHESIS whether the platelet molecular signature was altered in older adults evaluated by flow cytometry (13, 18–20). All Abs were from BD Biosci- and dissected a previously unrecognized mechanism whereby platelet– ences. Isolated, unstimulated monocytes were costained for CD14 FITC monocyte interactions drive excessive inflammation in aging. and CD16 PE with appropriate isotype controls. Platelet surface P-selectin expression and the formation of PMAs were evaluated as before (13, 18–20). Briefly, whole blood was left alone (baseline) or stimulated with Materials and Methods the PAR1 agonist SFLLRN for 10 min at 37˚C (5 mM for P-selectin and Human subjects 15 mM for PMAs). Whole blood was then incubated with Abs against P-selectin (CD62p), CD14 FITC, or CD41 PE for 20 min at room tem- The University of Utah Institutional Review Board approved this study perature. Samples were then immediately fixed and run using a FACScan (# 00051506) and all subjects provided informed consent. Healthy younger (BD Biosciences) with appropriate isotype controls. Samples were ana- , (aged 45 y) and older (aged $65 y) adults were eligible for participation lyzed using FlowJo v9 (TreeStar, OR). For whole blood platelet activation and recruited through advertising flyers approved by the Institutional Re- studies, platelets were gated by forward and side scatter using a loga- view Board. All study procedures and data capture were done in accor- rithmic scale followed by specific platelet Ag staining compared with dance with ethical regulations and patient data were anonymized. The age isotype control. For monocyte studies, cells were gated by forward and cut-off for older adults was based on commonly accepted definitions of side scatter using a linear scale followed by specific monocyte Ag staining aging, and the age cut-off for younger adults was chosen to give sufficient compared with isotype controls. A gating strategy for measuring the per- age separation between groups. Age cut-offs were all chosen a priori. centage of platelets expressing surface P-selectin (CD62p) in whole blood Subjects were excluded from the study if they were pregnant (self- is shown in Supplemental Fig. 1C–E. reported), had received a blood transfusion within the last 30 d, or had a history of cardiopulmonary disease (including myocardial infarction, ar- Platelet and monocyte incubations rhythmia, chronic obstructive pulmonary disease, or asthma), infection 6 8 within the past 30 d, inherited platelet disorder, cancer (whether active or Monocytes (2 3 10 cells per ml, final concentration) and platelets (2 3 10 cells per ml, final concentration) were incubated either separately or together, in remission), venous or arterial thromboembolic disease, liver or renal Downloaded from disease, or diabetes. Subjects taking clopidogrel, dipyridamole, selective depending on experimental conditions, at 37˚C for 18 h, as before (3). serotonin reuptake inhibitors, and phosphodiesterase inhibitors at any dose Cell-free supernatants were then harvested by centrifugation. In select or frequency were excluded. Subjects refrained from taking nonsteroidal experiments, human recombinant granzyme A (GrmA) (R&D Systems, anti-inflammatory drugs for 4 wk prior to study participation. Aspirin was Minneapolis, MN) was added (100 nM, final concentration) to incubating not an exclusionary criterion as many older adults take aspirin for the cells. Platelets were preincubated with an anti-GrmA Ab (R&D Systems) or prevention of cardiovascular disease and stroke. When approved by sub- control IgG (10 mg/ml, final concentration) that specifically blocks GrmA for jects’ medical providers, aspirin was temporarily discontinued for 4 wk 1 h, before the addition of monocytes. To identify the cognate receptors prior to study participation. regulating cytokine synthesis, monocytes were preincubated with the specific http://www.jimmunol.org/ TLR4 inhibitor, CLI-095 (1 mM, final concentration; InvivoGen, San Diego, Platelet and monocyte isolation CA) or a specific WEHD-FMK caspase-1 inhibitor (1 mM, final concen- tration; R&D Systems) for 1 h. Human peripheral venous blood was drawn into acid citrate dextrose (1.4 ml per 8.6 ml blood) through standard venipuncture technique and used immediately Chemokine and cytokine protein expression upon collection. The whole blood was first centrifuged at 150 3 g for 20 min at 20˚C to separate platelet-rich plasma from RBCs and WBCs. From the Platelet chemokines (e.g., P-selectin, RANTES, platelet factor 4 (PF4)] and platelet-rich plasma, platelets were leukocyte reduced and isolated as pre- monocyte cytokines (IL-6, IL-8, and MCP-1) were measured in harvested viously described (14–17) to yield a highly purified population of cells. supernatants by commercially available ELISA (R&D Systems) per the Isolated platelets were resuspended in serum-free M199 (Lonza, Walkersville, manufacturer’s instructions. For determination of chemokines in cell ly- 8 MD) medium in round-bottom polypropylene tubes (Becton Dickinson, sates, platelets (2 3 10 cells per ml, final concentration) were lysed in by guest on September 24, 2021 Franklin Lakes, NJ). The purity of isolated platelets was confirmed by flow radioimmunoprecipitation assay buffer. P-selectin, RANTES, and PF4 cytometry and direct counting via a hemocytometer, where ,3 leukocytes were measured by ELISA (R&D Systems) per the manufacturer’s in- were observed in each preparation containing 1 3 107 platelets (.99.9% structions. purity, Supplemental Fig. 1A). The number of leukocytes in each preparation did not vary by age (data not shown). Next-generation RNA-sequencing and RNA expression For the isolation of monocytes, the RBC/WBC mixture was resuspended Highly purified platelets were isolated as described above. For next- with 0.9% sterile saline back to the original volume and layered over an equal generation RNA-sequencing (RNA-seq), isolated platelets were carefully volume of Ficoll-Paque Plus (GE Healthcare Biosciences, Piscataway, NJ). lysed in Trizol, and DNAse-treated total RNA was isolated, as previously The layered cells were then centrifuged for 30 min at 400 3 g at 20˚C. After described (14, 16, 21–23). An Agilent bioanalyzer was used for quality 30 min, the mononuclear leukocyte layer was removed and washed with control and to quantitate RNA. RNA Integrity Number scores were similar HBSS (Sigma-Aldrich, St. Louis, MO) with 1% human serum albumin between all samples (data not shown). RNA-seq libraries were prepared (HSA; University of Utah Hospital, Salt Lake City, UT), and centrifuged for with TruSeq V2 with oligo-dT selection (Illumina, San Diego, CA). Reads 3 g 10 min at 400 at 20˚C. The cell pellet was then resuspended in HSA and were aligned (Novoalign) to the reference genome GRCh37/hg19 and a CD14 microbeads (Miltenyi Biotec, Bergisch Gladbach, Germany) were pseudo-transcriptome containing splice junctions. The Deseq2 analysis added for 15 min at 4˚C. The cells were then washed with HSA to remove package was used to assign reads to composite transcripts (one per gene) any free CD14 microbeads and then resuspended in HSA. The monocytes and quantitate fragments per kilobase of transcript per million mapped were then isolated by running the suspended cells through an autoMACs reads (FPKMs) as previously described (24). The expression of candi- cell separator (Miltenyi Biotec) using the PosselD2 program. The date transcripts identified by RNA-seq was further examined using quan- monocyteswerewashedwithHSAandresuspendedinM199(Bio- titative RT-PCR (qRT-PCR). Forward and reverse primers were as Whitaker, Walkersville, MD) and counted. The purity of monocytes was . follows, respectively: 1) GrmA:59-CATTGATTGATGTGGGGACA-39, confirmed to be 99.4% by flow cytometry (Supplemental Fig. 1B). 59-TCTGGGATTTCTGGTTCAGG-39;2)GrmH:59-GCCTTCCTGA- Flow cytometry GAAAATGCAG-39,59-GAGCAGCTGTCAGCACAAAG-39;3)GrmM: 59-AGCTGGACGGGAAAGTGAAG-39,59-CCAGAAGCGGCTGTTGT- The expression of monocyte surface markers, platelet surface adhesion TAC-39;4)Granulysin:59-GATGAGGCTGCTGAAAGGTC-39,59-GTG- molecules (e.g., P-selectin), and platelet–monocyte aggregation (PMA) was GAGGGAGTTTGGTGAGA-39.

Table I. Characteristics of study cohort

Young (n = 37) Old (n = 30) p Value Age, y 27.1 6 7.2 71.9 6 6.1 p , 0.001 Males, n (%) 17 (46%) 13 (43%) p = 0.85 Body mass index, kg/m2 23.7 6 4.0 28.7 6 5.5 p , 0.001 Aspirin use, n (%) 1 (3%) 10 (34%) p , 0.05 Data represent the mean 6 SD, unless otherwise indicated. The Journal of Immunology 3

layered onto Vectabond (Vector Laboratories, Burlingame, CA)-coated coverslips using a cytospin centrifuge (Shandon Cytospin; Thermo Fisher Scientific, Waltham, MA). Fluorescence microscopy was performed using an Olympus IX81, FV300 (Olympus, Melville, NY) confocal- scanning microscope equipped with a 603/1.42 NA oil objective for viewing platelets. An Olympus FVS-PSU/IX2-UCB camera and scanning unit and Olympus Fluoview FV 300 image acquisition software version 5.0 were used for recording. Protein expression studies All samples were normalized for starting cell concentrations. The samples were centrifuged at 13,000 3 g for 4 min and then resuspended in 0.5 ml of deionized water. The protein was pelleted by centrifugation at 13,000 3 g for 4 min. The protein pellets were solubilized in sample buffer containing 0.1 M Tris, 2% SDS, 1% (v/v) glycerol, 0.1% bromophenol blue, and 100 mM DTT then boiled for 10 min. Proteins were resolved by SDS polyacrylamide gels and transferred to nitrocellulose membrane (Whatman Protran). Membranes were blocked with Odyssey blocking buffer for 1 h at ambient temperature, incubated overnight at 4˚C with the desired pri- mary Ab for GrmA (Santa Cruz Biotechnology), and then washed four times with TBST. Membranes were then incubated with appropriate secondary infrared dye-labeled Ab for 60 min at room temperature and washed four times with TBST. Membranes were examined and quantified Downloaded from with a Li-Cor Odyssey infrared imaging system. In select experiments, platelets were stimulated with thrombin for the appropriate time under stirring conditions at 37˚C, and the reaction was stopped by the addition of 0.6 NHClO4. Statistical methods

For RNA-seq analysis, Deseq2 was used to identify differentially http://www.jimmunol.org/ expressed transcripts, as we have previously described (24). To focus on robustly expressed transcripts, only transcripts with per-group average .3 FPKM were included in the analysis. RNAs .2-fold differentially FIGURE 1. Aged platelets enhance IL-8 and MCP-1 synthesis. Mono- expressed between older and younger adults and with a nominal p value cytes and platelets were isolated from younger (age ,45 y, n = 27) or older ,0.05 (for discovery) were included in the analysis. To make these data adults (age $65 y, n = 27). (A and B) Monocytes alone were incubated in publicly available, a complete dataset of the RNA-seq studies was the presence or absence of thrombin (IIa, 0.1 U/ml) for 18 h. IL-8 and uploaded to Gene Expression Omnibus (SRA2779748). For relevant MCP-1 synthesis by monocytes alone did not significantly increase with studies, we calculated the mean 6 SEM and performed ANOVA to thrombin and was similar between younger and older adults. (C and D) identify differences among multiple experimental groups. If significant

Isolated monocytes were incubated with thrombin activated, autologous differences existed, a Student Newman–Keuls post hoc procedure was by guest on September 24, 2021 used to determine the location of the difference between groups. When platelets, or nonautologous (switch) platelets. IL-8 and MCP-1 synthesis single comparisons were performed, data were tested for normality and was significantly increased in the presence of platelets from older adults. In skewness and a Student t test or Wilcoxon rank sum was employed, comparison, in switch experiments, when monocytes from an older adult as appropriate. Statistical significance was set at a two-tailed p value were incubated with platelets from a younger adult, IL-8 and MCP-1 ,0.05. synthesis was significantly decreased. *p , 0.05. Results Immunocytochemistry Platelets from older adults enhance IL-8 and MCP-1 synthesis Freshly isolated platelets were fixed in suspension with paraformaldehyde (2% final concentration), placed in chamber slides, and subsequently in- Table I shows the clinical characteristics of the study cohort. The cubated with IgG or a specific Ab against GrmA (1:100 dilution, 60 min; two groups [younger (age ,45 y) and older (age $65 y)] were Santa Cruz Biotechnology, Dallas, TX). Fixed platelets were subsequently well balanced with regards to gender. Older adults had a higher

FIGURE 2. Aging does not alter monocyte CD14 or CD16 surface expression, platelet surface P-selectin expression, or the formation of platelet- monocyte aggregates. Whole blood was drawn from younger (age ,45 y) and older (age $65 y) subjects. Blood was stained for surface monocyte markers CD14 or CD16 [(A), n = 6 younger and n = 6 older], surface adhesion platelet P-selectin marker CD62p [(B), n = 23 younger and n =13 older], or platelet–monocyte aggregates as measured by double positivity for CD41 and CD14 [(C), n = 26 younger and n = 14 older]. Expression was adjusted for nonspecific staining by using appropriate isotype controls. In (B and C), whole blood was fixed immediately (baseline, BL) or activated with thrombin-receptor activating peptide (TRAP: 5 mM for CD41/CD14, 15 mM for P-selectin) prior to Ab staining and assessment by flow cytometry. *p , 0.05. 4 PLATELET GRANZYME A REGULATES CYTOKINE SYNTHESIS Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 3. Aging does not alter platelet expression or secretion of the adhesion molecule P-selectin, the signaling molecule RANTES, or the monocyte chemotactic molecule PF4. (A) Platelets were freshly isolated from younger (age ,45 y, n = 3) and older subjects (age $65 y, n = 3). Total RNA was isolated from platelets and the platelet transcriptome was assessed by next-generation RNA-seq. The total RNA expression of P-selectin, RANTES, and PF4 was examined in RNA-sequenced, highly purified platelet lysates. Shown are representative Integrative Genomics Viewer browser images of each transcript in platelets from a younger (top panels, blue) and older (bottom panels, red) adult with quantified transcript FKPM levels on the right (FPKM: n = 3 per group). The y-axis represents the relative expression of each mRNA, with higher peaks indicating increased expression. (B–D) To determine the protein expression, platelets were isolated from younger (age ,45 y, n = 11) and older subjects (age $65 y, n = 11). Platelets were either immediately lysed (baseline, BL) or activated with thrombin (IIa, 0.1 U/ml, t = 30 min). Platelet supernatants were harvested by centrifugation. Total P-selectin (B), RANTES (C), and PF4 (D) protein levels were measured in platelets lysates (for total protein) and in supernatants (Sups) by ELISA. body mass index and were taking aspirin more commonly (Table I). To determine whether platelets were the cellular drivers of the When monocytes were allowed to incubate alone (i.e., in the ab- increased synthesis of IL-8 and MCP-1 in older adults, we next sence of platelets), basal IL-8 and MCP-1 protein levels in the su- performed switch experiments. In these switch experiments, pernatant were negligible and did not differ between younger and monocytes from an older adult were coincubated with platelets older adults (Fig. 1A, 1B). In comparison, when monocytes were isolated from a gender-matched younger adult (e.g., nonautologous coincubated with autologous platelets (i.e., monocytes and platelets conditions). In parallel, monocytes from a younger adult were from the same subject), IL-8 and MCP-1 synthesis increased ro- coincubated with platelets from an older adult. In all these ex- bustly in both groups but was significantly higher (∼4-fold) in older periments, monocytes and platelets from younger or older adults adults compared with younger adults (Fig. 1C, 1D). In older sub- were isolated simultaneously and experiments performed on the jects, the synthesis of IL-8 and MCP-1 did not significantly differ same day in parallel. As shown in Fig. 1C and 1D, IL-8 and MCP-1 between aspirin users and nonusers (IL-8: 35.8 6 14.8 versus 24.9 synthesis by monocytes from older adults was rescued when 6 6.7 ng/ml, MCP-1: 1105 6 267 versus 710 6 309 ng/ml). We coincubated with platelets from younger adults. Conversely, IL-8 also observed increased IL-6 synthesis in older adults, when and MCP-1 synthesis by monocytes from younger adults was cocultured with autologous platelets, as compared with younger significantly enhanced when coincubated with platelets from older subjects, but the differences did not meet statistical significance adults. Synthesis of IL-8 by young monocytes was similar to that (Supplemental Fig. 2A). seen in older monocytes, when coincubated with aged platelets The Journal of Immunology 5 Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 4. GrmA is present in human platelets and its expression increases with aging. (A) Platelets were isolated from younger (n = 3) and older (n =3) adults. Total RNA was isolated from platelets and the platelet transcriptome was interrogated using next-generation RNA-seq. All transcripts identified by

RNA-seq were then filtered to identify only those that were differentially expressed (log2 fold-change $2). The heat map illustrates only those differentially expressed (log2 fold-change $2), upregulated (red), and downregulated (blue) transcripts that were identified in platelets from older adults as compared with younger adults. (B) Representative Integrative Genomics Viewer browser images of GrmA transcript expression in platelets isolated from a younger (top, blue) and older (bottom, red) adult. The y-axis represents the relative expression of GrmA, with higher peaks indicating increased total mRNA expression. On the bottom, the thick bars on the x-axis illustrate the exons and the 59 and 39 ends of the transcript are annotated (left and right, respectively). (C) GrmA expression was quantified by qRT-PCR in platelets isolated from older and younger adults. GrmA expression, but not GrmH, GrmM,or granulysin expression, was significantly increased in older adults. (D) Protein expression of GrmA was measured in isolated platelets (5 3 107 platelets equally loaded for each subject) by immunoblot and quantified by densitometry in older (n = 7) and younger (n = 7) adults. The left panel illustrates a representative immunoblot from n = 4 younger subjects and n = 3 older subjects with actin as a loading control in the bottom. The right panel shows normalized quantification of GrmA protein expression. *p , 0.05 versus younger adults.

(Fig. 1C). These results indicate that aged platelets are responsible We next examined whether aging was associated with changes in for triggering increased IL-8 and MCP-1 produced by monocytes the mRNA levels, intracellular expression, or secretion of proteins in older adults. required for platelet–monocyte interactions and downstream signal- dependent cytokine synthesis. In unstimulated platelets, there was The expression of cell-surface adhesion molecules and the no difference in the basal mRNA or intracellular protein expres- secretion of platelet chemokines that regulate IL-8 and MCP-1 sion of P-selectin and RANTES (required for platelet signaling to synthesis are not altered in aging monocytes and cytokine synthesis), or PF4 [a chemotactic factor Induction of IL-8 and MCP-1 synthesis by monocytes requires stable for monocytes (25)] between younger and older adults (Fig. 3). adhesion of platelets to monocytes, primarily through engagement of Similarly, the secretion of P-selectin, RANTES, or PF4 by acti- P-selectin on the platelet surface to PSGL-1 on monocytes (3). Thus, vated platelets was similar between younger and older adults we sought to determine whether the expression of monocyte and (Fig. 3). Together, these findings suggest that the increased IL-8 platelet surface adhesion or signaling molecules was increased in and MCP-1 synthesis by monocytes from older adults was not due our cohort of older adults. We did not identify any differences to enhanced expression of these platelet surface adhesion and in basal or activation-dependent expression of platelet surface signaling molecules. Accordingly, we turned our attention to P-selectin, platelet–monocyte aggregate formation, or the number heretofore unidentified proteins in human platelets with the ca- of monocytes positive for CD14+ or CD16+ between younger and pacity for regulating proinflammatory gene synthesis by mono- older adults (Fig. 2). cytes. 6 PLATELET GRANZYME A REGULATES CYTOKINE SYNTHESIS Downloaded from

FIGURE 5. GrmA is present in human platelets, secreted upon activation, and induces synthesis of IL-8 and MCP-1. (A) Platelets were isolated from an older adult (age $65) and stained with an anti-GrmA Ab (GrmA, magenta, right panels) or isotype IgG control (left panels). Platelets were costained with wheat germ agglutinin (WGA, green), which stains granules and membranes of platelets. The merged image and inset on the right illustrates the overlay of GrmA (yellow arrows) and WGA. Scale bar is shown on the lower left. Representative of n = 3 independent experiments. (B) Platelets were isolated from young (age ,45) or older adults (age $65) and either left alone or stimulated with thrombin (IIa, 0.1 U/ml; t = 30 min). The immunoblot shows that GrmA http://www.jimmunol.org/ is present at baseline in the platelet lysate and is secreted almost entirely into the platelet supernatant upon stimulation (WBC: WBC lysate, positive control). Levels of both intracellular and secreted GrmA were increased in older adults, as compared with younger adults. Actin is shown as a loading control (note that actin is absent from the supernatant, as expected). Representative of n = 3 independent experiments. (C and D) Platelets are necessary for GrmA-induced synthesis of IL-8 and MCP-1 by monocytes. Human monocytes and platelets were isolated as described in the Materials and Methods. Monocytes (2 3 106 cells per ml, final concentration) were left alone or incubated with rhGrmA (100 nM final, t = 18 h). Platelets (2 3 108 cells per ml, final concentration) were left alone or activated with thrombin (IIa, 0.1 U/ml, t = 30 min). Monocytes and platelets were also incubated together in the absence or presence of rhGrmA (100 nM final, t = 18 h). Supernatants were harvested by centrifugation. IL-8 (C) and MCP-1 (D) levels were measured by ELISA. n $ 3 independent experiments. *p , 0.05 versus all other conditions. by guest on September 24, 2021

GrmA is expressed in human platelets and increases with aging GrmA increases IL-8 and MCP-1 synthesis To globally interrogate the platelet transcriptome and identify other To examine the role of GrmA in potentiating IL-8 and MCP-1 molecules governing enhanced cytokine synthesis during aging, we synthesis by monocytes, we next incubated monocytes and next performed RNA-seq on isolated platelets from a subset of platelets with recombinant human GrmA (rhGrmA), at a con- younger (n = 3) and older (n = 3) adults. We identified numerous centration (100 nM) similar to that used by other investigators in (n = 514) transcripts significantly differentially expressed with prior publications (28, 29). When either monocytes or platelets aging, with most being increased in older adults (455 mRNAs were incubated alone in the presence or absence of rhGrmA, increased and 59 mRNAs decreased; Fig. 4A, Supplemental IL-8, and MCP-1 synthesis did not significantly increase Tables I, II). Among the differentially expressed candidates, we (Fig. 5C, 5D). These data indicate that under these experi- focused on GrmA, a serine protease that governs proinflammatory mental conditions and in the absence of platelets, GrmA is responses and protein synthesis by monocytes that, in some set- insufficient to trigger appreciable IL-8 and MCP-1 synthesis. tings, may be perforin independent (26, 27). By RNA-seq, GrmA However, when monocytes were coincubated with platelets in expression was robustly increased in platelets from older adults as the presence of rhGrmA, IL-8, and MCP-1 synthesis was sig- compared with younger adults (Fig. 4B). Subsequent interrogation nificantly upregulated (Fig. 5C, 5D). We did not identify GrmA of GrmA expression by qRT-PCR on a larger cohort confirmed that in resting human monocytes (Fig. 6A). As a positive control, platelet GrmA expression was significantly increased in older we confirmed that the TLR4 inhibitor blocked LPS-induced adults (Fig. 4C). The expression of GrmH, GrmM, and granulysin synthesis of IL-8 by resting monocytes (Fig. 6B). The addi- did not differ between younger and older adults (Fig. 4C). GrmA tion of polymyxin B, which blocks LPS-induced activation of protein expression was also significantly increased in platelets TLR4, did not prevent GrmA-induced cytokine synthesis, in- from older adults (Fig. 4D). Immunofluorescence studies con- dicating that LPS contamination was not causing the observed firmed the presence of GrmA protein within human platelets in increase in IL-8 and MCP-1 synthesis (Supplemental Fig. 2B, submembranous areas and in a granular pattern that did not ap- 2C). Inhibition of GrmA, using a specific anti-GrmA Ab, re- preciably colocalize with a granules (Fig. 5A). When platelets duced cytokine production to levels similar to conditions where from younger or older adults were activated with thrombin, GrmA GrmA was absent (Fig. 6C). Control IgG had no effect on IL-8 was almost entirely secreted into the extracellular milieu (Fig. 5B). or MCP-1 synthesis, indicating that this reduction of GrmA- Thus, GrmA in platelets is under signal-dependent secretion and induced synthesis of IL-8 and MCP-1 is independent of FcgR released extracellularly (where it may signal to monocytes). GrmA Ab binding (Fig. 6C). Taken together, these findings identify secretion was higher in platelets from older adults as compared with that platelet GrmA controls the synthesis of IL-8 and MCP-1 platelets from younger adults (Fig. 5B). protein by monocytes. The Journal of Immunology 7 Downloaded from http://www.jimmunol.org/

FIGURE 6. GrmA is not present in resting human monocytes and blocking FcgR does not reduce GrmA-induced IL-8 or MCP-1 synthesis. (A) GrmA mRNA is not present in resting human monocytes. Human monocytes were isolated as described in the Materials and Methods. Isolated monocytes were interrogated by next-generation RNA-seq. On the bottom, the thick bars on the x-axis illustrate the exons with the 59 and 39 ends annotated (left and right, respectively). Shown are Integrative Genomics Viewer browser images from n = 3 independent experiments. (B) Blocking TLR4 on monocytes prevents IL-8 synthesis. Monocytes were isolated from younger adults. Monocytes were stimulated with LPS (100 ng/ml, t = 18 h) in the presence or absence of a TLR4 inhibitor. IL-8 was measured by ELISA in harvested supernatants. (C) Blocking FcgR does not inhibit GrmA-induced IL-8 or MCP-1 synthesis. Human platelets and monocytes were isolated as described in the Materials and Methods. Platelets (activated with thrombin, 0.1 U/ml) and monocytes were left alone (i.e., not treated [NT]) or stimulated with rhGrmA (100 nM). At the same time, either an IgG1 Ab, which blocks FcgR, or a specific Ab against GrmA

(anti-GrmA) was added to the incubating cells (t = 18 h). IL-8 and MCP-1 were measured by ELISA in harvested supernatants. n = 3 independent by guest on September 24, 2021 experiments. *p , 0.05.

Inhibiting GrmA in older adults rescues IL-8 and MCP-1 rapid, short-lived functions primarily for hemostasis and wound synthesis through TLR4 and caspase-1–dependent mechanisms repair (2). Emerging evidence indicates, however, that platelets We next sought to determine if inhibiting GrmA in platelets from possess a broad and dynamic repertoire of functions (2, 30–32). older adults would normalize (to levels seen in younger adults) IL-8 Platelets process precursor mRNAs in response to activating sig- and MCP-1 synthesis by monocytes. To establish this, platelets and nals, synthesize new proteins, and have activities that span in- monocytes from older adults were coincubated in the presence or flammatory and immune continuums (16, 32). absence of an anti-GrmA Ab. When GrmA was blocked, the Aging is associated with injurious thromboinflammation and synthesis of IL-8 and MCP-1 was reduced to levels similar to those alterations in platelet functions (33–35). In older adults with acute, seen in younger adults (Fig. 7A). systemic inflammatory syndromes, increased platelet activation To dissect the mechanisms of action whereby GrmA was in- correlates with increased circulating, proinflammatory cytokine ducing cytokine synthesis, we next measured GrmA-induced IL-8 levels, and adverse clinical outcomes (13). Circulating plasma and MCP-1 cytokine synthesis in the presence or absence of levels of IL-6 increase with age (11, 12) and monocytes from older specific inhibitors to TLR4 or caspase-1. In younger adults, GrmA- adults express greater intracellular IL-6 and IL-8 (8). MCP-1 is induced production of IL-8 and MCP-1 was blocked completely chemotactic for mononuclear leukocytes into inflamed vascular when TLR4 was inhibited (Fig. 7B). In contrast, when caspase-1 tissues and IL-8 orchestrates firm adhesion of monocytes to vas- was inhibited, we observed partial rescue of IL-8 whereas MCP-1 cular endothelium (36). As we and others have shown, the for- synthesis was completed blocked (Fig. 7B). Similar findings were mation of circulating platelet–monocyte aggregates is increased in observed in older adults (Fig. 7C). TL4 mRNA and protein ex- older adults with systemic inflammatory syndromes (13) and PMA pression in either isolated platelets or monocytes did not differ results in the synthesis of IL-8 and MCP-1 (3). Stable adhesion of between younger and older subjects (Fig. 7D–G). Consistent with platelets to monocytes requires the expression of P-selectin on the this, gene ontology analyses also did not identify any differences platelet surface and subsequent engagement of PSGL-1 on the in the TLR pathway in platelets based on RNA-seq data (data not monocyte. The release of the platelet a granule protein RANTES shown). (through binding to CCR5 on the monocyte surface) causes translocation of NF-Kb into the nucleus of the monocyte and triggers the synthesis of IL-8 and MCP-1 (3). Discussion In this study, using both autologous and nonautologous mono- Platelets are circulating anucleate blood cells traditionally thought cytes (switch co-culture conditions), we demonstrate that aged to have a relatively fixed transcriptome and proteome, and have platelets drive excessive production of IL-6, IL-8, and MCP-1 by 8 PLATELET GRANZYME A REGULATES CYTOKINE SYNTHESIS Downloaded from FIGURE 7. Blocking endogenous GrmA inhibits IL-8 and MCP-1 synthesis in a TLR4- and caspase-1–dependent mechanism. (A) Monocytes (2 3 106 cells per ml, final concentration) and platelets (2 3 108 cells per ml, final concentration) were isolated from younger (age ,45 y, n = 5) or older adults (age $65 y, n = 5). Monocytes and platelets were coincubated together (t = 18 h) together in the presence of thrombin (IIa, 0.1 U/ml, t = 30 min) and an anti-GrmA blocking Ab or IgG control Ab (IgG). Supernatants were harvested by centrifugation. IL-8 and MCP-1 protein levels in supernatants were then measured by ELISA. Shown is the fold-change in IL-8 and MCP-1 synthesis in older adults (red) as compared with younger adults (blue). (B) Monocytes and platelets were isolated from younger adults (age ,45 y, n = 5). rhGrmA (100 nM final) was added to the cells in the presence of a TLR4 inhibitor or, separately, a caspase-1 inhibitor. Cells were allowed to incubate together for 18 h. Supernatants were harvested by centrifugation. IL-8 and MCP-1 protein http://www.jimmunol.org/ levels in supernatants were measured by ELISA. (C) Blocking endogenous GrmA in older adults reduces IL-8 and MCP-1 synthesis in a TLR4- and caspase-1–dependent mechanism. Monocytes (2 3 106 cells per ml, final concentration) and platelets (2 3 108 cells per ml, final concentration) were isolated from older adults (age $65 y, n = 5). rhGrmA (100 nM final) was added to the cells in the presence of a TLR4 inhibitor or, separately, a caspase-1 inhibitor. Platelets and monocytes were allowed to incubate together for 18 h in the presence of thrombin (0.1 U/ml). Supernatants were harvested by centrifugation. IL-8 and MCP-1 protein levels in supernatants were measured by ELISA. (D–G) TLR4 expression on platelets and monocytes does not differ between younger and older subjects. Human platelets and monocytes were isolated from younger (,45 y) and older ($65 y) subjects as described in the Materials and Methods. Platelet TLR4 mRNA expression was examined by RNA-seq [(D), n = 3 subjects per group] and by qRT-PCR [(E), n =3 subjects per group]. (F) Monocyte TLR4 mRNA expression was examined by qRT-PCR (n = 3 subjects per group). (G) TLR4 protein expression was determined in platelets and monocytes from younger (,45 y) and older ($65 y) subjects by immunoblot (n = 3–4 subjects per group). Actin, shown on the by guest on September 24, 2021 bottom of each blot, was used as a loading control. *p , 0.05. monocytes. We identify that, molecularly, platelet GrmA mediates reduced cytokine synthesis in response to GrmA. These findings the heightened synthesis of these proinflammatory cytokines and are consistent with prior reports showing that GrmA enhances that platelet GrmA is significantly enriched (at both the mRNA and activation of the inflammasome (a caspase-1–dependent event) and protein level) and bioactive in older adults. Inhibiting GrmA LPS-mediated signaling, which acts via TLR4 (29). In addition, in vitro in older adults reduced IL-8 and MCP-1 synthesis to levels mice globally deficient in GrmA exhibit better survival in response comparable to those in younger adults. Importantly, we confirmed to a lethal LPS challenge, as compared with wild-type mice where that our findings were not due to any inadvertent contamination by GrmA is endogenously present (29, 40). LPS. We could not find any prior studies that identified GrmA in The strengths of our study include the use of freshly isolated, human platelets. This is also the first evidence, to our knowledge, primary human cells (e.g., platelets and monocytes), our approxi- that shows where aging-associated increases in GrmA are sufficient mation of physiological conditions when incubating platelets and to drive proinflammatory gene synthesis by monocytes. monocytes together, and our rigorous validation of the expression and These findings build upon and extend our understanding of the activity of GrmA in younger and older human participants. We have cellular expression and function of GrmA. In humans, granzymes also made all the platelet RNA-seq data publicly available. Fastq files are a family of five structurally related serine proteases found have been submitted to the Sequence Read Archive so that readers ubiquitously in cytotoxic lymphocytes that differ in their substrate and investigators may query the data directly (National Center for specificity (27, 37). GrmA was initially identified within cyto- Biotechnology Information BioProject PRJNA397446, accession num- plasmic granules within cytotoxic T cells and NK cells (38). More bers SRR5907423–SRR5907428). The BioProject can be accessed at recently, GrmA has been found within other nucleated cells and in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA397446. the extracellular space (39), been shown to activate macrophages, Nonetheless, whether GrmA is acting specifically and selectively monocytes, and mast cells, and induces inflammatory responses on monocytes, platelets, or both remains to be determined. Although independent of perforins (26, 27). human platelets are not known to express or synthesize IL-8 and Our studies also provide new evidence that GrmA functionally MCP-1 protein, they do express TLR4 on their surface and have a regulates the production of cytokines by monocytes. Although we functional inflammasome (22, 41–43). Thus, altered signaling focused on elucidating the mechanism of excessive cytokine through these pathways may influence how platelets interact production in aging, our data demonstrate that even in younger with monocytes, leading to increased monocyte-driven cytokine adults, modulating GrmA (either by addition of exogenous GrmA synthesis in older adults. Platelets are increasingly recognized as or by inhibiting endogenous GrmA) serves to control IL-8 and effector cells during systemic, injurious inflammatory responses. MCP-1 synthesis. Moreover, inhibition of TLR4 or caspase-1 Our data support established and emerging investigations examining The Journal of Immunology 9 whether antiplatelet therapies modulate cytokine synthesis (and thus 12. Donato, A. J., A. D. Black, K. L. Jablonski, L. B. Gano, and D. R. Seals. 2008. Aging is associated with greater nuclear NF kappa B, reduced I kappa B alpha, inflammation). For example, dipyridamole, but not aspirin, attenu- and increased expression of proinflammatory cytokines in vascular endothelial ates nuclear translocation of NF-kB and MCP-1 synthesis (44). This cells of healthy humans. Aging Cell 7: 805–812. may explain in part why the combination of aspirin plus extended- 13. Rondina, M. T., M. Carlisle, T. Fraughton, S. M. Brown, R. R. Miller, III, E. S. Harris, A. S. Weyrich, G. A. Zimmerman, M. A. Supiano, and release dipyridamole offered better secondary stroke risk reduction C. K. Grissom. 2015. Platelet-monocyte aggregate formation and mortality risk than aspirin alone in clinical trials (45, 46). Whether targeting in older patients with severe sepsis and septic shock. J. Gerontol. A Biol. Sci. platelets in other inflammatory diseases offers clinical benefits Med. Sci. 70: 225–231. 14. Rondina, M. T., M. Freitag, F. G. Pluthero, W. H. Kahr, J. W. Rowley, remains an active area of study. L. W. Kraiss, Z. Franks, G. A. Zimmerman, A. S. Weyrich, and H. Schwertz. Although not a central focus of our study, our findings also 2016. Non-genomic activities of retinoic acid receptor alpha control actin cy- toskeletal events in human platelets. J. Thromb. Haemost. 14: 1082–1094. demonstrate that the platelet transcriptome is altered in aging. We 15. Franks, Z., R. A. Campbell, A. Vieira de Abreu, J. T. Holloway, J. E. Marvin, identified numerous differentially expressed transcripts in platelets B. F. Kraemer, G. A. Zimmerman, A. S. Weyrich, and M. T. Rondina. 2013. isolated from older adults with enrichment of pathways implicated Methicillin-resistant Staphylococcus aureus-induced thrombo-inflammatory re- sponse is reduced with timely antibiotic administration. Thromb. Haemost. 109: in cell-cell signaling and inflammatory pathways (data not shown). 684–695. Our age-related changes in the platelet transcriptome were simi- 16. Rondina, M. T., H. Schwertz, E. S. Harris, B. F. Kraemer, R. A. Campbell, larly noted in a younger cohort of healthy patients aged 18–46 y, N. Mackman, C. K. Grissom, A. S. Weyrich, and G. A. Zimmerman. 2011. The septic milieu triggers expression of spliced tissue factor mRNA in human where more than 120 mRNAs and 15 microRNAs demonstrated platelets. J. Thromb. Haemost. 9: 748–758. age-dependent expression levels (47). We extend this published 17. Schwertz, H., N. D. Tolley, J. M. Foulks, M. M. Denis, B. W. Risenmay, M. Buerke, R. E. Tilley, M. T. Rondina, E. M. Harris, L. W. Kraiss, et al. 2006. work by offering, to our knowledge, the first human platelet Signal-dependent splicing of tissue factor pre-mRNA modulates the thrombo- RNA-seq dataset comparing younger (age ,45 y) and older genicity of human platelets. J. Exp. Med. 203: 2433–2440. Downloaded from (age $65 y) individuals. We have made this dataset available and 18. Shih, L., D. Kaplan, L. W. Kraiss, T. C. Casper, R. C. Pendleton, C. L. Peters, M. A. Supiano, G. A. Zimmerman, A. S. Weyrich, and M. T. Rondina. 2016. hope it will serve as a discovery tool for investigators in the field. Platelet-monocyte aggregates and c-reactive protein are associated with vte in In conclusion, human aging is associated with changes in the older surgical patients. Sci. Rep. 6: 27478. platelet transcriptome and proteome. GrmA is present and bioactive 19. Rondina, M. T., C. K. Grissom, S. Men, E. S. Harris, H. Schwertz, G. A. Zimmerman, and A. S. Weyrich. 2012. Whole blood flow cytometry in human platelets, increases during aging, and regulates inflam- measurements of in vivo platelet activation in critically-Ill patients are influenced matory gene synthesis by monocytes. Alterations in the platelet by variability in blood sampling techniques. Thromb. Res. 129: 729–735. http://www.jimmunol.org/ 20. Rondina, M. T., B. Brewster, C. K. Grissom, G. A. Zimmerman, molecular signature and downstream signaling to monocytes may D. H. Kastendieck, E. S. Harris, and A. S. Weyrich. 2012. In vivo platelet ac- contribute to dysregulated inflammatory syndromes and adverse tivation in critically ill patients with primary 2009 influenza A(H1N1). Chest outcomes in older adults. 141: 1490–1495. 21. Rowley, J. W., S. Chappaz, A. Corduan, M. M. Chong, R. Campbell, A. Khoury, B. K. Manne, J. G. Wurtzel, J. V. Michael, L. E. Goldfinger, et al. 2016. Dicer1- Acknowledgments mediated miRNA processing shapes the mRNA profile and function of murine We thank Diana Lim for creativity and excellent figure preparation, Kendra platelets. Blood 127: 1743–1751. 22. Rowley, J. W., A. J. Oler, N. D. Tolley, B. N. Hunter, E. N. Low, D. A. Nix, Richardson for editorial assistance, and Antoinette Blair for careful reading C. C. Yost, G. A. Zimmerman, and A. S. Weyrich. 2011. Genome-wide RNA-seq of the manuscript. analysis of human and mouse platelet transcriptomes. Blood 118: e101–e111.

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37. Voskoboinik, I., J. C. Whisstock, and J. A. Trapani. 2015. Perforin and gran- 43. Hottz, E. D., J. F. Lopes, C. Freitas, R. Valls-de-Souza, M. F. Oliveira, zymes: function, dysfunction and human pathology. Nat. Rev. Immunol. 15: 388– M. T. Bozza, A. T. Da Poian, A. S. Weyrich, G. A. Zimmerman, F. A. Bozza, and 400. P. T. Bozza. 2013. Platelets mediate increased endothelium permeability in 38. Masson, D., M. Zamai, and J. Tschopp. 1986. Identification of granzyme A dengue through NLRP3-inflammasome activation. Blood 122: 3405–3414. isolated from cytotoxic T-lymphocyte-granules as one of the proteases encoded 44. Weyrich, A. S., M. M. Denis, J. R. Kuhlmann-Eyre, E. D. Spencer, D. A. Dixon, by CTL-specific genes. FEBS Lett. 208: 84–88. G. K. Marathe, T. M. McIntyre, G. A. Zimmerman, and S. M. Prescott. 2005. 39. Cullen, S. P., M. Brunet, and S. J. Martin. 2010. Granzymes in cancer and im- Dipyridamole selectively inhibits inflammatory gene expression in platelet- munity. Cell Death Differ. 17: 616–623. monocyte aggregates. Circulation 111: 633–642. 40. Anthony, D. A., D. M. Andrews, M. Chow, S. V. Watt, C. House, S. Akira, 45. Diener, H. C., L. Cunha, C. Forbes, J. Sivenius, P. Smets, and A. Lowenthal. P. I. Bird, J. A. Trapani, and M. J. Smyth. 2010. A role for granzyme M in TLR4- 1996. European stroke prevention study. 2. Dipyridamole and acetylsalicylic driven inflammation and endotoxicosis. J. Immunol. 185: 1794–1803. acid in the secondary prevention of stroke. J. Neurol. Sci. 143: 1–13. 41. Aslam, R., E. R. Speck, M. Kim, A. R. Crow, K. W. Bang, F. P. Nestel, H. Ni, 46. ESPRIT Study Group, P. H. Halkes, J. van Gijn, L. J. Kappelle, P. J. Koudstaal, and A. H. Lazarus, J. Freedman, and J. W. Semple. 2006. Platelet Toll-like receptor A. Algra. 2006. Aspirin plus dipyridamole versus aspirin alone after cerebral ischaemia expression modulates lipopolysaccharide-induced thrombocytopenia and tumor of arterial origin (ESPRIT): randomised controlled trial. Lancet 367: 1665–1673. necrosis factor-alpha production in vivo. Blood 107: 637–641. 47. Simon, L. M., L. C. Edelstein, S. Nagalla, A. B. Woodley, E. S. Chen, X. Kong, 42. Hottz, E. D., A. P. Monteiro, F. A. Bozza, and P. T. Bozza. 2015. Inflammasome L. Ma, P. Fortina, S. Kunapuli, M. Holinstat, et al. 2014. Human platelet in platelets: allying coagulation and inflammation in infectious and sterile dis- microRNA-mRNA networks associated with age and gender revealed by eases? Mediators Inflamm. 2015: 435783. integrated plateletomics. Blood 123: e37–e45. Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021 A B 10 5 10 5 250K 250K

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Supplemental Figure 1. Surface expression markers in isolated platelets and monocytes. Platelets and monocytes were isolated from human subjects, as described in the methods. (Panel A) Platelets were stained with CD41, for αIIb (right panel), or with an IgG isotype control (left panel). (Panel B) Monocytes were stained with CD14 (right panel) or with an IgG isotype control (left panel). (Panels C-E) . Gating strategy for investigating the percentage of P-selectin positive cells (CD62p) in whole blood. Whole blood was drawn from human subjects and stained with CD62p, for P-selectin. Shown is the gating strategy used to detect CD62p on isolated platelets with CD41 for αIIb, a platelet specific surface marker. A p = 0.0658 B C 80 15 ** 800 60 600 10 40 400 5

IL-8 (ng/mL) IL-8 IL-6(ng/mL) 20 200

MCP-1 (pg/mL) MCP-1 0 0 0 < 45 ≥ 65 IIa – + + + + IIa – + + + + IIa + + rhGrmA ––– + + rhGrmA ––– + + PolyB –––– + PolyB –––– +

MonoPltsMono Mono + plts Mono + plts Plts

Supplemental Figure 2. IL-6 synthesis is increased in older subjects and Granzyme A induced synthesis of IL-8 and MCP-1 is independent of LPS. (Panel A) Platelets and monocytes were isolated from younger (age<45 years, n=10) or older (age≥65 years, n=15) subjects. Autologous cells were allowed to incubate overnight (t=18 hours) in the presence of thrombin (0/1U/mL). IL-6 was measured by ELISA in harvested supernatants. (Panels B-C) Monocytes and platelets were isolated from younger adults. In some conditions, human recombinant granzyme A (rhGrmA, 100nM final) was added in the presence or absence of polymixin B (PolyB, 10μg/mL) in sufficient concentration to bind and inactivate LPS. Granzyme A induced IL-8 (Panel B) and MCP-1 (Panel C) synthesis was independent of polymixin B (*p<0.05, n=3 independent experiments). Supplement Table 1. List of differentially expressed mRNAs from next-generation platelet RNA-sequencing

Log2 P-Value Gene ID Gene Name Fold-Change (Nominal) ENSG00000181031 RPH3AL 2.662 1.31E-09 ENSG00000141736 ERBB2 2.233 3.39E-06 ENSG00000168758 SEMA4C 2.180 4.99E-06 ENSG00000225143 NA 2.167 5.89E-07 ENSG00000180739 S1PR5 2.105 1.94E-05 ENSG00000100385 IL2RB 2.091 5.18E-06 ENSG00000211766 TRBJ2-2P 2.075 7.85E-05 ENSG00000205336 GPR56 2.059 2.21E-05 ENSG00000133067 LGR6 2.048 3.76E-05 ENSG00000171596 NMUR1 2.025 3.63E-05 ENSG00000159674 SPON2 2.008 5.11E-05 ENSG00000186827 TNFRSF4 1.997 5.07E-05 ENSG00000150687 PRSS23 1.986 2.50E-05 ENSG00000181877 AC092535.1 1.963 6.16E-05 ENSG00000153563 CD8A 1.929 6.32E-05 ENSG00000115085 ZAP70 1.911 6.91E-05 ENSG00000212339 NA 1.907 2.37E-04 ENSG00000139182 CLSTN3 1.899 6.89E-05 ENSG00000224376 AC017104.6 1.887 2.50E-04 ENSG00000229993 NA 1.877 3.85E-04 ENSG00000096433 ITPR3 1.873 1.30E-04 ENSG00000180644 PRF1 1.861 1.47E-04 ENSG00000135127 CCDC64 1.860 1.49E-04 ENSG00000234389 AC007278.3 1.859 7.69E-05 ENSG00000185920 PTCH1 1.849 4.82E-05 ENSG00000141622 RNF165 1.847 2.14E-04 ENSG00000139194 RBP5 1.846 3.85E-04 ENSG00000212352 NA 1.836 3.88E-04 ENSG00000178573 MAF 1.830 8.93E-05 ENSG00000103522 IL21R 1.829 1.02E-04 ENSG00000198821 CD247 1.829 1.44E-04 ENSG00000075234 TTC38 1.813 6.32E-05 ENSG00000100450 GZMH 1.798 2.55E-04 ENSG00000163564 PYHIN1 1.792 9.09E-05 ENSG00000100453 GZMB 1.791 1.41E-04 ENSG00000205045 SLFN12L 1.779 3.85E-04 ENSG00000130787 HIP1R 1.773 1.96E-04 ENSG00000073350 LLGL2 1.771 4.92E-04 ENSG00000099889 ARVCF 1.736 7.47E-04 ENSG00000181847 TIGIT 1.734 1.82E-04 ENSG00000007402 CACNA2D2 1.729 6.37E-04 ENSG00000173200 PARP15 1.728 2.10E-04 ENSG00000107331 ABCA2 1.721 5.23E-04 ENSG00000139626 ITGB7 1.718 4.24E-04 ENSG00000143842 SOX13 1.712 2.72E-04 ENSG00000178498 DTX3 1.707 6.91E-04 ENSG00000226864 RP11-500G22.2 1.704 1.27E-03 ENSG00000213402 PTPRCAP 1.701 4.15E-04 ENSG00000027869 SH2D2A 1.693 1.16E-04 ENSG00000142173 COL6A2 1.688 1.04E-03 ENSG00000096996 IL12RB1 1.683 5.45E-04 ENSG00000135362 PRR5L 1.681 1.82E-04 ENSG00000198719 DLL1 1.678 1.11E-03 ENSG00000206190 ATP10A 1.675 6.71E-04

Supplement Table 1 | page 1 Log2 P-Value Gene ID Gene Name Fold-Change (Nominal) ENSG00000137501 SYTL2 1.674 1.01E-04 ENSG00000021762 OSBPL5 1.671 4.54E-04 ENSG00000121716 PILRB 1.670 3.73E-04 ENSG00000147168 IL2RG 1.666 5.57E-04 ENSG00000006075 CCL3 1.660 8.69E-04 ENSG00000156453 PCDH1 1.655 1.09E-03 ENSG00000020633 RUNX3 1.654 6.26E-04 ENSG00000174080 CTSF 1.651 8.03E-04 ENSG00000005448 WDR54 1.648 1.02E-03 ENSG00000168421 RHOH 1.648 7.89E-04 ENSG00000167633 KIR3DL1 1.638 9.28E-04 ENSG00000129277 CCL4 1.633 6.79E-04 ENSG00000154760 SLFN13 1.628 2.97E-04 ENSG00000232434 C9orf172 1.628 1.20E-03 ENSG00000005379 BZRAP1 1.622 5.08E-04 ENSG00000170989 S1PR1 1.620 6.98E-04 ENSG00000115523 GNLY 1.620 1.61E-04 ENSG00000196374 HIST1H2BM 1.607 2.24E-03 ENSG00000149294 NCAM1 1.595 6.10E-04 ENSG00000162676 GFI1 1.591 1.06E-03 ENSG00000168060 NAALADL1 1.586 1.18E-03 ENSG00000162729 IGSF8 1.586 1.11E-03 ENSG00000235576 AC092580.4 1.582 1.30E-03 ENSG00000101665 SMAD7 1.578 7.86E-04 ENSG00000036448 MYOM2 1.577 1.83E-03 ENSG00000197471 SPN 1.568 1.17E-03 ENSG00000167775 CD320 1.566 1.29E-03 ENSG00000162739 SLAMF6 1.560 6.92E-04 ENSG00000140545 MFGE8 1.556 1.19E-03 ENSG00000116824 CD2 1.552 1.31E-03 ENSG00000148019 CEP78 1.551 8.05E-04 ENSG00000130940 CASZ1 1.551 2.14E-03 ENSG00000211770 TRBJ2-6 1.550 3.35E-03 ENSG00000085563 ABCB1 1.549 7.38E-04 ENSG00000186891 TNFRSF18 1.547 2.33E-03 ENSG00000182173 TSEN54 1.546 5.41E-04 ENSG00000073861 TBX21 1.539 1.25E-03 ENSG00000218226 TATDN2P2 1.538 2.13E-03 ENSG00000185885 IFITM1 1.538 1.54E-03 ENSG00000134545 KLRC1 1.533 2.43E-03 ENSG00000124256 ZBP1 1.531 2.02E-03 ENSG00000105374 NKG7 1.530 1.03E-03 ENSG00000167984 NLRC3 1.528 4.37E-04 ENSG00000102837 OLFM4 1.528 1.43E-03 ENSG00000185022 MAFF 1.527 1.90E-03 ENSG00000161395 PGAP3 1.522 1.06E-03 ENSG00000189430 NCR1 1.522 2.75E-03 ENSG00000104490 NCALD 1.521 1.65E-03 ENSG00000168329 CX3CR1 1.511 1.62E-03 ENSG00000119650 IFT43 1.508 3.54E-03 ENSG00000167508 MVD 1.505 1.15E-03 ENSG00000164047 CAMP 1.497 2.71E-03 ENSG00000174600 CMKLR1 1.489 2.81E-03 ENSG00000159733 ZFYVE28 1.487 3.15E-03 ENSG00000008438 PGLYRP1 1.480 4.29E-03 ENSG00000148362 C9orf142 1.479 2.54E-03 ENSG00000226778 NA 1.478 5.17E-03

Supplement Table 1 | page 2 Log2 P-Value Gene ID Gene Name Fold-Change (Nominal) ENSG00000137441 FGFBP2 1.477 2.10E-03 ENSG00000130827 PLXNA3 1.476 2.65E-03 ENSG00000004777 ARHGAP33 1.475 2.26E-03 ENSG00000205810 KLRC3 1.472 3.42E-03 ENSG00000203896 LIME1 1.472 2.50E-03 ENSG00000213809 KLRK1 1.465 3.02E-03 ENSG00000175093 SPSB4 1.464 2.08E-03 ENSG00000142102 ATHL1 1.462 3.68E-03 ENSG00000104731 KLHDC4 1.460 2.52E-03 ENSG00000115607 IL18RAP 1.456 1.94E-03 ENSG00000056558 TRAF1 1.455 2.56E-03 ENSG00000182325 FBXL6 1.454 4.03E-03 ENSG00000110651 CD81 1.453 1.94E-03 ENSG00000176845 METRNL 1.452 5.17E-03 ENSG00000103326 SOLH 1.450 1.98E-03 ENSG00000211768 TRBJ2-4 1.446 5.05E-03 ENSG00000167664 TMIGD2 1.445 2.99E-03 ENSG00000182866 LCK 1.440 2.26E-03 ENSG00000196684 HSH2D 1.437 3.58E-03 ENSG00000181036 FCRL6 1.436 3.02E-03 ENSG00000163508 EOMES 1.434 2.15E-03 ENSG00000127152 BCL11B 1.430 3.61E-03 ENSG00000145649 GZMA 1.430 2.89E-03 ENSG00000185697 MYBL1 1.429 1.80E-03 ENSG00000169252 ADRB2 1.428 5.63E-03 ENSG00000225864 HCG4P11 1.427 5.65E-03 ENSG00000167543 TP53I13 1.424 5.28E-03 ENSG00000196839 ADA 1.420 2.72E-03 ENSG00000189319 FAM53B 1.419 2.55E-03 ENSG00000237683 RP11-34P13.11 1.416 2.40E-03 ENSG00000163453 IGFBP7 1.412 3.16E-03 ENSG00000058453 CROCC 1.411 2.13E-03 ENSG00000178971 CTC1 1.405 3.88E-03 ENSG00000107742 SPOCK2 1.402 6.80E-03 ENSG00000135469 COQ10A 1.401 4.60E-03 ENSG00000168056 LTBP3 1.398 4.24E-03 ENSG00000141524 TMC6 1.396 3.62E-03 ENSG00000005844 ITGAL 1.396 2.24E-03 ENSG00000054654 SYNE2 1.395 2.09E-03 ENSG00000135736 CCDC102A 1.388 4.98E-03 ENSG00000114388 NPRL2 1.387 3.51E-03 ENSG00000172575 RASGRP1 1.385 2.42E-03 ENSG00000069667 RORA 1.385 4.82E-03 ENSG00000082512 TRAF5 1.381 3.93E-03 ENSG00000156711 MAPK13 1.379 2.23E-03 ENSG00000225032 RP11-228B15.4 1.379 5.20E-03 ENSG00000183542 KLRC4 1.377 5.80E-03 ENSG00000158006 PAFAH2 1.377 4.01E-03 ENSG00000007264 MATK 1.376 4.11E-03 ENSG00000122188 LAX1 1.375 7.05E-03 ENSG00000108292 MLLT6 1.374 3.30E-03 ENSG00000159753 RLTPR 1.371 4.30E-03 ENSG00000184381 PLA2G6 1.370 4.81E-03 ENSG00000012223 LTF 1.369 6.08E-03 ENSG00000105122 RASAL3 1.369 3.34E-03 ENSG00000167851 CD300A 1.366 4.38E-03 ENSG00000179979 CRIPAK 1.362 3.72E-03

Supplement Table 1 | page 3 Log2 P-Value Gene ID Gene Name Fold-Change (Nominal) ENSG00000174996 KLC2 1.359 2.33E-03 ENSG00000159618 GPR114 1.358 6.59E-03 ENSG00000161405 IKZF3 1.357 7.35E-03 ENSG00000141458 NPC1 1.357 1.30E-03 ENSG00000198286 CARD11 1.351 4.05E-03 ENSG00000127586 CHTF18 1.349 4.24E-03 ENSG00000004468 CD38 1.349 6.12E-03 ENSG00000119714 GPR68 1.348 5.82E-03 ENSG00000160318 CLDND2 1.346 8.22E-03 ENSG00000177721 C5orf39 1.345 4.82E-03 ENSG00000153395 LPCAT1 1.343 4.48E-03 ENSG00000026751 SLAMF7 1.342 8.33E-03 ENSG00000113263 ITK 1.342 5.27E-03 ENSG00000154451 GBP5 1.341 3.37E-03 ENSG00000198574 SH2D1B 1.340 5.17E-03 ENSG00000078687 TNRC6C 1.339 2.69E-03 ENSG00000226210 ABC7-42389800N19.1 1.338 1.03E-03 ENSG00000187961 KLHL17 1.333 9.05E-03 ENSG00000071575 TRIB2 1.331 6.35E-03 ENSG00000175463 TBC1D10C 1.329 8.10E-03 ENSG00000107317 PTGDS 1.327 1.08E-02 ENSG00000069493 CLEC2D 1.326 3.00E-03 ENSG00000101224 CDC25B 1.326 3.75E-03 ENSG00000160072 ATAD3B 1.323 9.05E-03 ENSG00000101445 PPP1R16B 1.323 3.54E-03 ENSG00000178685 PARP10 1.322 4.95E-03 ENSG00000006025 OSBPL7 1.322 5.99E-03 ENSG00000206549 PRSS50 1.320 9.93E-03 ENSG00000140463 BBS4 1.313 1.16E-02 ENSG00000154734 ADAMTS1 1.312 9.20E-03 ENSG00000130511 SSBP4 1.310 6.01E-03 ENSG00000196476 C20orf96 1.309 4.77E-03 ENSG00000198792 TMEM184B 1.308 5.28E-03 ENSG00000103264 FBXO31 1.308 6.61E-03 ENSG00000120662 MTRF1 1.307 7.06E-03 ENSG00000117394 SLC2A1 1.305 5.43E-03 ENSG00000177337 AP002478.1 1.303 3.98E-04 ENSG00000183734 ASCL2 1.302 9.13E-03 ENSG00000166289 PLEKHF1 1.299 8.29E-03 ENSG00000126264 HCST 1.297 5.46E-03 ENSG00000236525 AC007278.2 1.296 9.09E-03 ENSG00000158321 AUTS2 1.294 9.96E-03 ENSG00000235999 RP11-403I13.8 1.293 5.85E-03 ENSG00000108556 CHRNE 1.287 4.76E-03 ENSG00000196358 NTNG2 1.281 1.15E-02 ENSG00000175066 GK5 1.279 1.15E-02 ENSG00000158805 ZNF276 1.279 4.54E-03 ENSG00000134324 LPIN1 1.277 3.29E-03 ENSG00000180902 D2HGDH 1.277 6.64E-03 ENSG00000099849 RASSF7 1.275 1.00E-02 ENSG00000167992 VWCE 1.275 1.10E-02 ENSG00000099821 POLRMT 1.273 1.05E-02 ENSG00000007350 TKTL1 1.271 9.39E-03 ENSG00000229813 RP4-740C4.4 1.270 1.61E-02 ENSG00000187688 TRPV2 1.269 1.06E-02 ENSG00000111371 SLC38A1 1.267 7.18E-03 ENSG00000027075 PRKCH 1.266 4.24E-03

Supplement Table 1 | page 4 Log2 P-Value Gene ID Gene Name Fold-Change (Nominal) ENSG00000207567 MIR142 1.265 1.50E-02 ENSG00000148824 MTG1 1.263 2.43E-03 ENSG00000171476 HOPX 1.259 5.85E-03 ENSG00000162894 FAIM3 1.258 1.02E-02 ENSG00000108963 DPH1 1.257 1.33E-02 ENSG00000072818 ACAP1 1.255 8.78E-03 ENSG00000198917 C9orf114 1.255 7.05E-03 ENSG00000169991 IFFO2 1.253 9.08E-03 ENSG00000101695 RNF125 1.250 6.63E-03 ENSG00000171604 CXXC5 1.248 8.30E-03 ENSG00000081059 TCF7 1.247 1.20E-02 ENSG00000132879 FBXO44 1.245 1.69E-02 ENSG00000183718 TRIM52 1.245 6.62E-03 ENSG00000187193 MT1X 1.243 1.54E-02 ENSG00000059573 ALDH18A1 1.239 1.09E-02 ENSG00000234290 AC116366.6 1.237 1.18E-02 ENSG00000085998 POMGNT1 1.237 1.57E-02 ENSG00000197536 C5orf56 1.236 1.85E-03 ENSG00000006530 AGK 1.227 5.31E-03 ENSG00000142765 SYTL1 1.221 1.66E-02 ENSG00000130810 PPAN 1.217 1.30E-02 ENSG00000169583 CLIC3 1.216 1.40E-02 ENSG00000184682 C11orf89 1.216 1.43E-02 ENSG00000128159 TUBGCP6 1.214 8.54E-03 ENSG00000206805 YRNA 1.213 2.08E-02 ENSG00000207556 MIR636 1.213 2.13E-02 ENSG00000205560 CPT1B 1.213 1.21E-02 ENSG00000168763 CNNM3 1.212 1.02E-02 ENSG00000177542 SLC25A22 1.211 1.31E-02 ENSG00000171163 ZNF692 1.210 6.80E-03 ENSG00000204165 CXorf65 1.208 1.93E-02 ENSG00000196139 AKR1C3 1.207 1.15E-02 ENSG00000173917 HOXB2 1.206 1.66E-02 ENSG00000175048 ZDHHC14 1.205 7.50E-03 ENSG00000134539 KLRD1 1.204 9.03E-03 ENSG00000185187 SIGIRR 1.202 1.09E-02 ENSG00000189190 ZNF600 1.202 1.96E-02 ENSG00000124608 AARS2 1.202 2.01E-02 ENSG00000085978 ATG16L1 1.198 1.20E-02 ENSG00000177595 PIDD 1.197 1.64E-02 ENSG00000074582 BCS1L 1.196 9.27E-03 ENSG00000164483 SAMD3 1.196 8.43E-03 ENSG00000130038 EFCAB4B 1.195 1.60E-02 ENSG00000104043 ATP8B4 1.193 4.77E-03 ENSG00000168209 DDIT4 1.193 1.79E-02 ENSG00000133460 SLC2A11 1.192 2.71E-03 ENSG00000005381 MPO 1.190 1.36E-02 ENSG00000132182 NUP210 1.190 8.17E-03 ENSG00000215252 GOLGA8B 1.188 2.09E-02 ENSG00000134262 AP4B1 1.188 1.07E-02 ENSG00000125384 PTGER2 1.184 1.54E-02 ENSG00000185163 DDX51 1.184 2.29E-02 ENSG00000074966 TXK 1.182 3.70E-03 ENSG00000213906 LTB4R2 1.181 1.60E-02 ENSG00000168016 TRANK1 1.179 1.10E-02 ENSG00000205744 DENND1C 1.177 1.29E-02 ENSG00000127980 PEX1 1.176 8.92E-03

Supplement Table 1 | page 5 Log2 P-Value Gene ID Gene Name Fold-Change (Nominal) ENSG00000224298 AC069363.1 1.176 2.54E-02 ENSG00000101474 C20orf3 1.170 5.71E-03 ENSG00000137337 MDC1 1.170 9.33E-03 ENSG00000132600 PRMT7 1.169 1.40E-02 ENSG00000125498 KIR2DL1 1.167 2.62E-02 ENSG00000155363 MOV10 1.167 9.15E-03 ENSG00000064687 ABCA7 1.166 5.61E-03 ENSG00000100027 YPEL1 1.164 4.50E-03 ENSG00000124181 PLCG1 1.163 1.38E-02 ENSG00000068028 RASSF1 1.159 4.60E-03 ENSG00000183696 UPP1 1.158 8.79E-03 ENSG00000180900 SCRIB 1.154 7.95E-03 ENSG00000145214 DGKQ 1.152 1.24E-02 ENSG00000111203 ITFG2 1.151 2.67E-02 ENSG00000101104 PABPC1L 1.149 2.41E-02 ENSG00000113088 GZMK 1.149 2.05E-02 ENSG00000058668 ATP2B4 1.146 1.91E-02 ENSG00000148400 NOTCH1 1.146 1.17E-02 ENSG00000231936 NA 1.146 2.98E-02 ENSG00000179087 MGAM 1.146 2.64E-02 ENSG00000140398 NEIL1 1.143 2.03E-02 ENSG00000076604 TRAF4 1.143 2.21E-02 ENSG00000135077 HAVCR2 1.142 7.46E-03 ENSG00000133134 BEX2 1.142 2.94E-02 ENSG00000128016 ZFP36 1.140 2.24E-02 ENSG00000108798 ABI3 1.140 1.56E-02 ENSG00000137070 IL11RA 1.140 2.93E-02 ENSG00000238120 CTA-941F9.9 1.139 3.11E-02 ENSG00000184551 AC132872.1 1.135 3.18E-02 ENSG00000114395 CYB561D2 1.135 1.48E-02 ENSG00000140688 C16orf58 1.135 2.06E-02 ENSG00000160932 LY6E 1.134 1.22E-02 ENSG00000100023 PPIL2 1.133 1.73E-02 ENSG00000165684 SNAPC4 1.132 1.77E-02 ENSG00000177192 PUS1 1.131 2.70E-02 ENSG00000108669 CYTH1 1.131 1.70E-02 ENSG00000185745 IFIT1 1.128 2.25E-02 ENSG00000118971 CCND2 1.128 1.19E-02 ENSG00000185669 SNAI3 1.127 3.01E-02 ENSG00000168434 COG7 1.127 2.05E-02 ENSG00000124574 ABCC10 1.122 2.60E-02 ENSG00000200259 SNORD35A 1.122 2.52E-02 ENSG00000143554 SLC27A3 1.121 2.07E-02 ENSG00000230149 RP3-508I15.19 1.121 3.40E-02 ENSG00000168792 ABHD15 1.119 1.29E-02 ENSG00000185347 C14orf80 1.119 2.55E-02 ENSG00000133250 ZNF414 1.118 1.45E-02 ENSG00000124659 TBCC 1.118 1.64E-02 ENSG00000106948 AKNA 1.117 2.25E-02 ENSG00000086506 HBQ1 1.117 1.79E-03 ENSG00000171101 AC063977.1 1.116 2.48E-02 ENSG00000127418 FGFRL1 1.115 2.64E-02 ENSG00000100949 RABGGTA 1.113 1.41E-02 ENSG00000126246 IGFLR1 1.113 1.06E-02 ENSG00000131018 SYNE1 1.111 9.42E-03 ENSG00000198133 TMEM229B 1.111 2.33E-02 ENSG00000114423 CBLB 1.108 1.31E-02

Supplement Table 1 | page 6 Log2 P-Value Gene ID Gene Name Fold-Change (Nominal) ENSG00000174165 ZDHHC24 1.108 1.09E-02 ENSG00000105135 ILVBL 1.106 2.72E-02 ENSG00000136059 VILL 1.106 2.52E-02 ENSG00000108771 DHX58 1.105 2.37E-02 ENSG00000105519 CAPS 1.105 2.25E-02 ENSG00000163993 S100P 1.105 3.23E-02 ENSG00000116663 FBXO6 1.103 2.68E-02 ENSG00000235878 AP001468.1 1.102 3.66E-02 ENSG00000134014 ELP3 1.102 1.24E-02 ENSG00000105655 ISYNA1 1.100 2.23E-02 ENSG00000197530 MIB2 1.099 7.33E-03 ENSG00000169660 HEXDC 1.099 1.13E-02 ENSG00000231074 HCG18 1.093 1.01E-02 ENSG00000125637 PSD4 1.091 1.58E-02 ENSG00000238881 SCARNA2 1.089 3.09E-02 ENSG00000126709 IFI6 1.089 1.54E-02 ENSG00000204282 AC021593.1 1.089 3.49E-02 ENSG00000108773 KAT2A 1.088 2.17E-02 ENSG00000048028 USP28 1.088 1.38E-02 ENSG00000065802 ASB1 1.086 2.39E-02 ENSG00000221963 APOL6 1.086 2.61E-02 ENSG00000223496 EXOSC6 1.085 2.11E-02 ENSG00000117280 RAB7L1 1.085 2.03E-02 ENSG00000165282 PIGO 1.084 1.70E-02 ENSG00000121281 ADCY7 1.081 2.66E-02 ENSG00000172183 ISG20 1.081 2.74E-02 ENSG00000172232 AZU1 1.079 1.30E-02 ENSG00000181035 SLC25A42 1.079 2.30E-02 ENSG00000143179 UCK2 1.079 3.93E-02 ENSG00000111801 BTN3A3 1.078 1.03E-02 ENSG00000112763 BTN2A1 1.078 3.23E-02 ENSG00000090104 RGS1 1.077 3.38E-02 ENSG00000132361 KIAA0664 1.077 3.02E-02 ENSG00000075914 EXOSC7 1.075 2.58E-02 ENSG00000100413 POLR3H 1.075 1.71E-02 ENSG00000148399 WDR85 1.074 3.02E-02 ENSG00000164674 SYTL3 1.073 2.52E-02 ENSG00000100139 MICALL1 1.073 1.44E-02 ENSG00000150990 DHX37 1.072 2.55E-02 ENSG00000148843 PDCD11 1.071 2.52E-02 ENSG00000186866 POFUT2 1.070 2.14E-02 ENSG00000228274 RP3-508I15.9 1.070 3.53E-02 ENSG00000158555 GDPD5 1.070 2.54E-02 ENSG00000199753 SNORD104 1.070 4.30E-02 ENSG00000104814 MAP4K1 1.069 2.60E-02 ENSG00000168970 JMJD7-PLA2G4B 1.067 2.71E-02 ENSG00000185198 PRSS57 1.067 3.07E-02 ENSG00000156521 TYSND1 1.067 2.00E-02 ENSG00000233540 DNM3-IT1 1.066 3.85E-02 ENSG00000168995 SIGLEC7 1.065 3.43E-02 ENSG00000112592 TBP 1.063 3.17E-02 ENSG00000215041 NEURL4 1.062 3.49E-02 ENSG00000237669 HCG4P3 1.062 3.52E-02 ENSG00000184967 NOC4L 1.061 2.97E-02 ENSG00000166313 APBB1 1.061 2.53E-02 ENSG00000204536 CCHCR1 1.061 2.85E-02 ENSG00000172613 RAD9A 1.060 1.79E-02

Supplement Table 1 | page 7 Log2 P-Value Gene ID Gene Name Fold-Change (Nominal) ENSG00000199382 RNU12 1.059 4.44E-02 ENSG00000213445 SIPA1 1.056 2.06E-02 ENSG00000185112 FAM43A 1.056 3.53E-02 ENSG00000143851 PTPN7 1.055 1.47E-02 ENSG00000167615 LENG8 1.053 2.47E-02 ENSG00000047365 ARAP2 1.051 2.88E-02 ENSG00000165802 NELF 1.050 3.57E-02 ENSG00000134107 BHLHE40 1.050 3.20E-02 ENSG00000184164 CRELD2 1.049 3.77E-02 ENSG00000238164 RP3-395M20.8 1.049 2.36E-02 ENSG00000189227 C15orf61 1.047 4.21E-02 ENSG00000123329 ARHGAP9 1.046 3.70E-02 ENSG00000167083 GNGT2 1.045 2.70E-02 ENSG00000127580 WDR24 1.045 3.43E-02 ENSG00000173653 RCE1 1.044 2.71E-02 ENSG00000114841 DNAH1 1.044 3.04E-02 ENSG00000185201 IFITM2 1.043 4.11E-02 ENSG00000121310 ECHDC2 1.043 3.29E-02 ENSG00000100342 APOL1 1.042 4.03E-02 ENSG00000211765 TRBJ2-2 1.040 4.17E-02 ENSG00000090971 NAT14 1.039 4.18E-02 ENSG00000125731 SH2D3A 1.038 3.54E-02 ENSG00000138378 STAT4 1.037 3.61E-02 ENSG00000079263 SP140 1.034 3.67E-02 ENSG00000233927 RPS28 1.034 1.12E-02 ENSG00000185275 CD24P4 1.033 4.31E-02 ENSG00000176783 RUFY1 1.032 2.24E-02 ENSG00000141086 CTRL 1.032 4.40E-02 ENSG00000131242 RAB11FIP4 1.032 3.70E-02 ENSG00000143185 XCL2 1.030 4.25E-02 ENSG00000148296 SURF6 1.028 3.12E-02 ENSG00000215305 VPS16 1.027 1.18E-02 ENSG00000225576 NA 1.027 4.09E-02 ENSG00000215908 CROCCP2 1.026 3.77E-02 ENSG00000232347 RP11-488L18.8 1.024 3.91E-02 ENSG00000157353 FUK 1.023 4.66E-02 ENSG00000117226 GBP3 1.023 2.84E-02 ENSG00000081985 IL12RB2 1.021 4.07E-02 ENSG00000203747 FCGR3A 1.020 3.94E-02 ENSG00000204316 MRPL38 1.018 4.19E-02 ENSG00000100416 TRMU 1.017 4.15E-02 ENSG00000127528 KLF2 1.014 4.92E-02 ENSG00000141582 CBX4 1.014 4.04E-02 ENSG00000130589 RP4-697K14.7 1.013 4.22E-02 ENSG00000177606 JUN 1.013 4.64E-02 ENSG00000149262 INTS4 1.012 1.68E-02 ENSG00000136463 TACO1 1.012 4.08E-02 ENSG00000105607 GCDH 1.010 4.49E-02 ENSG00000197043 ANXA6 1.009 2.69E-02 ENSG00000186654 PRR5 1.009 3.71E-02 ENSG00000103168 TAF1C 1.008 3.92E-02 ENSG00000177548 RABEP2 1.008 3.51E-02 ENSG00000133316 WDR74 1.006 3.66E-02 ENSG00000133794 ARNTL 1.005 4.01E-02 ENSG00000171603 CLSTN1 1.005 2.84E-02 ENSG00000117560 FASLG 1.005 4.52E-02 ENSG00000167747 C19orf48 1.004 3.23E-02

Supplement Table 1 | page 8 Log2 P-Value Gene ID Gene Name Fold-Change (Nominal) ENSG00000159496 RGL4 1.003 3.78E-02 ENSG00000150045 KLRF1 1.002 2.86E-02 ENSG00000230207 RP11-87M1.1 -1.005 4.74E-02 ENSG00000180398 MCFD2 -1.010 1.40E-02 ENSG00000172915 NBEA -1.013 2.41E-02 ENSG00000213029 SPHAR -1.019 3.22E-02 ENSG00000230989 HSBP1 -1.025 1.21E-02 ENSG00000198162 MAN1A2 -1.030 3.33E-02 ENSG00000186310 NAP1L3 -1.035 3.98E-02 ENSG00000137710 RDX -1.037 1.53E-02 ENSG00000205269 TMEM170B -1.044 2.81E-02 ENSG00000171385 KCND3 -1.052 1.63E-02 ENSG00000167914 GSDMA -1.054 3.92E-02 ENSG00000139289 PHLDA1 -1.056 2.03E-02 ENSG00000204920 ZNF155 -1.057 2.71E-02 ENSG00000196705 ZNF431 -1.073 2.44E-02 ENSG00000187391 MAGI2 -1.076 1.28E-02 ENSG00000203668 CHML -1.083 1.81E-02 ENSG00000121101 TEX14 -1.091 9.82E-03 ENSG00000224576 NA -1.104 3.21E-02 ENSG00000135045 C9orf40 -1.107 5.46E-03 ENSG00000170017 ALCAM -1.109 3.90E-03 ENSG00000106546 AHR -1.109 8.45E-03 ENSG00000122786 CALD1 -1.121 1.57E-03 ENSG00000156414 TDRD9 -1.139 7.25E-03 ENSG00000224228 RP1-15D23.2 -1.142 1.64E-02 ENSG00000218305 AC006024.4 -1.163 2.33E-02 ENSG00000205213 LGR4 -1.169 9.89E-03 ENSG00000119900 OGFRL1 -1.171 1.23E-03 ENSG00000229941 AC012499.1 -1.176 2.32E-02 ENSG00000106443 PHF14 -1.197 9.08E-03 ENSG00000226435 AC073135.1 -1.199 1.26E-02 ENSG00000204529 RP11-672A2.2 -1.205 2.26E-02 ENSG00000211935 IGHV1-3 -1.213 4.81E-03 ENSG00000211896 IGHG1 -1.214 1.42E-02 ENSG00000235070 AC068138.1 -1.222 1.94E-02 ENSG00000231841 RP11-206F17.2 -1.244 1.86E-02 ENSG00000229660 RP5-1142J19.1 -1.271 1.17E-02 ENSG00000149131 SERPING1 -1.282 5.12E-03 ENSG00000234782 RP11-442A13.1 -1.299 1.07E-02 ENSG00000116985 BMP8B -1.319 7.74E-04 ENSG00000171033 PKIA -1.345 2.31E-03 ENSG00000131711 MAP1B -1.364 6.37E-03 ENSG00000160999 SH2B2 -1.371 4.39E-05 ENSG00000124275 MTRR -1.381 4.01E-03 ENSG00000224070 HMGN1P6 -1.447 5.83E-03 ENSG00000227850 SEPT2P1 -1.472 4.87E-03 ENSG00000224091 AC104389.16 -1.476 3.65E-03 ENSG00000217228 RP1-152L7.1 -1.494 4.72E-03 ENSG00000109272 PF4V1 -1.531 2.58E-04 ENSG00000224649 AF124730.4 -1.537 2.99E-03 ENSG00000212224 SNORA26 -1.552 2.98E-03 ENSG00000121570 DPPA4 -1.642 3.74E-05 ENSG00000237164 SLC25A15P2 -1.652 1.79E-03 ENSG00000198829 SUCNR1 -1.695 2.23E-04 ENSG00000225231 AC091814.2 -1.756 8.62E-04 ENSG00000182534 MXRA7 -1.766 5.31E-04

Supplement Table 1 | page 9 Log2 P-Value Gene ID Gene Name Fold-Change (Nominal) ENSG00000135426 KIAA0748 -1.906 8.24E-06 ENSG00000183386 FHL3 -2.297 3.52E-11 ENSG00000101638 ST8SIA5 -2.619 7.82E-08 ENSG00000237990 CNTN4-AS1 -2.903 6.74E-10

Supplement Table 1 | page 10 Supplement Table 2. Enriched gene ontology (GO) terms, pathways, or keywords1

Enrichment Adjusted GO Term, Keyword, or KEGG Pathway2 Count3 Score P-Value4 Immunity 5.41 32 2.7E-5 Adaptive Immunity 5.41 16 4.6E-4 Clathrin Binding 5.41 6 6.7E-3 Disulfide Bond 3.12 13 1.1E-3 Receptor 3.12 62 7.4E-4 Membrane 3.12 200 9.6E-4 Cell Membrane 3.12 91 4.0E-2 T Cell Receptor Signaling Pathway 2.33 11 1.4E-2 Immunoglobulin Domain 2.22 27 3.9E-3 Inflammatory Bowel Disease 1.80 10 2.5E-3 SH2 Domain 1.16 12 9.3E-4

1 Identified by next generation RNA-seq in isolated platelets from older vs. younger adults (n=3 subjects/group). 2 Only terms or pathways with a significant p-value (<0.05) after adjustment were included in this table. 3 Count refers to the number of transcripts. 4 P-value is adjusted for multiple comparisons (Benjamini-Hochberg).