Alterations of Platelet MicroRNAs Associated With Dapagliflozin Treatment in Individuals With Type 2 Diabetes Mellitus

Abstract

Background

Platelet hyperactivity contributes to elevated cardiovascular risk in type 2 diabetes mellitus (T2DM). Sodium-glucose cotransporter-2 inhibitors, including dapagliflozin, exert beneficial effects on platelet function and cardiovascular outcomes. As platelet microRNAs (miRNAs) are established during megakaryopoiesis, we aimed to characterize the platelet miRNA expression in T2DM and after dapagliflozin treatment.

Methods

Platelet miRNA profiles were compared between T2DM patients and controls using microarray, with qRT-PCR validation in an independent cohort (25 T2DM and 19 controls). T2DM patients were re-evaluated after 3-month dapagliflozin treatment.

Results

Exploratory microarray identified 602 candidate miRNAs with >2-fold differences between T2DM and control pools. qRT-PCR confirmed significant changes in miR-15b-3p, miR-146a-5p, miR-155-5p, and miR-223-3p (all q < 0.05), as well as nominally significant changes in miR-21-5p and miR-320a (both q = 0.052). In T2DM, miR-320a negatively correlated with mean platelet volume, platelet distribution width, and platelet large cell ratio, whereas miR-146a-5p showed positive correlations with platelet size parameters. Additionally, miR-21-5p positively and miR-223-3p negatively associated with soluble P-selectin. In an uncontrolled pre–post analysis, platelet miR-223-3p and miR-320a levels were significantly higher after dapagliflozin treatment. In silico target prediction yielded putative enrichment in pathways related to transcriptional regulation, insulin signaling, and autophagy, which likely reflects regulatory programs established in parent megakaryocytes and warrants functional validation.

Conclusion

Altered levels of miR-15b-3p, miR-146a-5p, miR-155-5p, and miR-223-3p are associated with platelet activation and maturation in T2DM patients. Dapagliflozin treatment may be associated with changes in platelet levels of miR-223-3p and miR-320a, hypothetically reflecting alterations in megakaryocytic programming during therapy.

Introduction

Diabetes mellitus (DM) is a chronic metabolic disorder characterized by persistent hyperglycemia due to impaired insulin secretion, defective insulin action, or both. The global prevalence of DM, particularly type 2 DM (T2DM), has reached epidemic proportions, imposing substantial burdens on public health and healthcare systems worldwide.^1,2 A major contributor to the increased morbidity and mortality in T2DM is the elevated risk of cardiovascular complications, including myocardial infarction, stroke, and peripheral arterial disease. ³ A key pathophysiological mechanism underlying this heightened thrombotic risk is platelet hyperactivity, a well-documented feature of the diabetic state. ⁴

In patients with T2DM, platelet function and coagulation pathways are significantly dysregulated, promoting a prothrombotic state. Chronic hyperglycemia and associated metabolic disturbances enhance platelet activation, aggregation, and adhesion, which are critical processes in the initiation and progression of atherosclerosis and its thrombotic sequelae.^5,6 MicroRNAs (miRNAs) are implicated in numerous physiological and pathological processes, including diabetes pathogenesis. ⁷ Platelets contain a diverse and functionally active repertoire of miRNAs and have emerged as active mediators of vascular homeostasis and thrombosis. Accumulating evidence indicates that platelets are not merely anucleate fragments but possess functional messenger RNA (mRNA), the machinery for pre-mRNA splicing, and the capacity for de novo protein synthesis.^8,9 This enables them to dynamically modulate responses in hemostasis, thrombosis, and inflammation. Given that miRNA expression in platelets is intricately linked to their biogenesis, activation status, and functional responses, platelet miRNAs represent promising candidates as both biomarkers of disease activity and potential therapeutic targets in T2DM and its vascular complications.

Sodium-glucose cotransporter-2 (SGLT2) inhibitors, including canagliflozin, dapagliflozin, and empagliflozin, have demonstrated significant benefits in the management of T2DM.^10,11 By inhibiting glucose reabsorption in the proximal renal tubules, these agents promote urinary glucose excretion and lower systemic glycemia. Beyond their glucose-lowering effects, SGLT2 inhibitors confer robust cardiovascular and renal protective benefits, as evidenced in large-scale clinical trials, positioning them as cornerstone therapies in modern diabetes care.^12,13 Emerging evidence suggests that SGLT2 inhibitors may reduce platelet reactivity and improve endothelial function, potentially through attenuation of oxidative stress, inflammation, and hemodynamic alterations.^14,15 The present study aims to characterize differential miRNA profiles in platelets of T2DM patients, and to evaluate alterations in platelet miRNA expression associated with the initiation of dapagliflozin treatment. These findings may provide a foundation for future studies exploring the potential role of platelet miRNAs in the biological effects of SGLT2 inhibitors.

Materials and Methods

Clinical Samples

Blood samples were obtained from 44 participants at Changhai Hospital (25 T2DM patients and 19 nondiabetic controls). Inclusion criteria included diagnosed T2DM, age 18 to 75, no prior SGLT2 inhibitor use, and exclusion of acute cardiovascular events, malignancy, or blood disorders within the past year. All participants underwent coronary computed tomography angiography, confirming comparable atherosclerotic cardiovascular disease status between groups with no significant obstructive lesions. The 25 T2DM patients discontinued their previous glucose-lowering therapy at enrollment and received dapagliflozin (10 mg once daily) for 3 months before follow-up blood sampling. Concomitant nonglucose-lowering medications remained unchanged throughout the study. Platelet miRNA profiles were screened via microarray in a random subset (5 T2DM and 5 controls) and validated by qRT-PCR in all 44 samples. Written informed consent was obtained from all participants.

Platelet Preparation

Platelets were prepared by sequential centrifugation, as previously described. ¹⁶ Briefly, citrated venous blood was centrifuged at 190×g for 20 min to obtain platelet-rich plasma (PRP). Prostaglandin E1 (MedChemExpress, Monmouth Junction, New Jersey, USA) was added to a final concentration of 1 μmol/L to prevent platelet activation. The PRP was then subjected to a second centrifugation at 190×g for 10 min, and the upper PRP layer was carefully collected to minimize leukocyte contamination. Residual leukocytes were further depleted using CD45 Dynabeads (Thermo Fisher Scientific, Plainville, Massachusetts, USA) according to the manufacturer's instructions. After washing with HEPES-buffered Tyrode's solution containing 1 μmol/L PGE1, platelets were pelleted by centrifugation at 1000×g for subsequent RNA isolation.

MiRNA Microarray

Purified platelets were pooled into one composite sample per group (5 T2DM patients and 5 controls, respectively) to minimize individual variability during the initial screening and subjected to RNA extraction by using the mirVana PARIS Kit (Thermo Fisher Scientific) following the manufacturer's instructions. Due to resource constraints, the discovery phase used pooled RNA samples without biological replication; thus, results are considered exploratory and hypothesis-generating only. To generate an initial candidate list of dysregulated miRNAs in an exploratory manner, the miRNA profile in platelets was determined by the human miRNA microarray Version 19.0 (Agilent Technologies, Santa Clara, California, USA), with hybridization performed on a single array for each pool. Candidate miRNAs were selected based on a fold-change threshold (|Fold Change| ≥ 2.0) and detection signal intensity above background. Raw data of microarray have been deposited in the OMIX, China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences (https://ngdc.cncb.ac.cn/omix: accession no. OMIX015665). ¹⁷

Quantitative reverse transcription PCR (qRT-PCR)

Total RNA was reverse-transcribed into complementary DNA using the PrimeScript RT Reagent Kit (TaKaRa, Dalian, China) with miRNA-specific stem loop-RT primers, following quantification on a NanoDrop spectrophotometer (Thermo Fisher Scientific). Relative miRNA levels in platelets were analyzed by qRT-PCR using TB Green Premix Ex Taq II (TaKaRa) on a LightCycler 480 system (Roche, Basel, Switzerland). The small nucleolar RNA RNU43 and exogenous spike-in control cel-miR-39 were used as the reference gene for normalization. ¹⁸ The oligonucleotides used in the qRT-PCR assay were listed in Supplemental Table S5.

Enzyme-Linked Immunosorbent Assay (ELISA)

Plasma levels of soluble P-selectin (sP-selectin) and soluble CD40 ligand (sCD40L) were measured using the commercial ELISA kits (Meimian, Jiangsu, China) according to the manufacturer's instructions. Blood was collected in EDTA tubes and centrifuged at 3000 × g for 10 min at 4 °C within 30 min to obtain platelet-poor plasma, which was stored at −80 °C until analysis. Samples were thawed on ice, briefly re-centrifuged, and assayed in triplicate. Plasma concentrations of sP-selectin and sCD40L were calculated from standard curves.

Bioinformatic Analysis

Potential targets of the miRNAs were predicted using the TargetScan algorithm (version 8.0; https://www.targetscan.org). ¹⁹ Subsequently, functional enrichment analyses, including Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, were performed on the predicted target genes using the OECloud platform at https://cloud.oebiotech.com.

Statistical Analysis

All statistical analyses were performed by SPSS software (Version 22.0). Categorical variables are presented as numbers and percentages, and were compared using the chi-square test or Fisher's exact test when appropriate. Continuous variables are expressed as mean ± standard deviation (SD) or median and interquartile range (IQR). The normality of continuous variables was assessed using the Shapiro-Wilk test and visual inspection of Q–Q plots. Normally distributed variables were compared between groups using the unpaired two-tailed Student's t-test; nonnormally distributed variables were analyzed with the Mann-Whitney U-test. Paired samples were analyzed using the Wilcoxon signed-rank test. Correlations between variables were assessed using Spearman's rank correlation coefficient. Given the multiple comparisons inherent in the qRT-PCR validation and correlation analyses, the Benjamini-Hochberg method was applied to control the false discovery rate (FDR), and a q-value < 0.05 was considered statistically significant for these tests. A two-sided P-value < .05 was considered statistically significant for the other comparisons.

Results

Altered Expression Profiles of Platelet miRNAs in Patients With T2DM

To generate hypotheses regarding platelet miRNA profiles in T2DM, we performed an exploratory microarray screen using pooled platelet RNA samples. The microarray detected a total of 381 miRNAs in platelets from the control pool and 554 miRNAs in the T2DM pool. Notably, miR-4454 was the most abundantly expressed miRNA in platelets from both groups (Figure 1A and B). The screen yielded a candidate list of 602 miRNAs showing >2-fold differences in signal intensity between the T2DM and control pools, including 377 upregulated and 225 downregulated miRNAs (Supplemental Table S1). Hierarchical clustering of the top 40 candidates is presented in a heatmap (Figure 1C). Furthermore, several candidates implicated in platelet function and activation were dysregulated in T2DM, including upregulation of miR-15a/b-5p, miR-21-5p, miR-26a/b-5p, miR-140-5p, miR-146a-5p, and miR-155-5p, as well as downregulation of miR-200a/b-5p, miR-223-3p, and members of the miR-320 family (Figure 1D). These findings, based on nonreplicated pooled samples, do not support formal statistical inference but provide a prioritized set of candidates for validation in biologically replicated cohorts.

Figure 1.

Altered platelet miRNA expression profiles in patients with T2DM. Platelets were purified and pooled in groups of 5 samples, followed by RNA extraction and miRNA profiling using microarray analysis. (A, B) miRNA signal intensity profiles from platelets of nondiabetic controls and T2DM patients. (C) Heatmap showing hierarchical clustering of the top 40 differentially expressed miRNAs between the control and T2DM groups. (D) Expression levels of 20 miRNAs associated with platelet function and activation, identified as dysregulated in T2DM platelets.

Multi-Sample Validation of Platelet miRNAs in Patients With T2DM

To validate the miRNA microarray findings, a total of 25 patients with T2DM and 19 nondiabetic controls were enrolled in this study. No significant differences were observed in baseline clinical characteristics between the 2 groups, except for the diabetes-related parameters (Supplemental Table S2). Subsequently, a qRT-PCR assay was performed to validate the expression levels of 13 miRNAs (Supplemental Table S3), which were selected based on (1) a fold-change magnitude of |FC| ≥ 2.0 in the microarray screening, and (2) their established or potential roles in platelet biology.^20,21 The results confirmed that the expression levels of miR-15b-3p, miR-146a-5p, and miR-155-5p were significantly upregulated in platelets from T2DM patients compared to nondiabetic controls (q < 0.01; Figure 2A to C). In contrast, miR-223-3p expression was markedly downregulated in the T2DM group (q < 0.01; Figure 2D). Although miR-21-5p and miR-320a exhibited nominally lower expression in T2DM (uncorrected P < .05 for both), but did not reach statistical significance after correction for multiple testing (q = 0.052 for both; Figure 2E and F). No significant differences were detected in the expression levels of miR-26a-5p, miR-107, miR-140-5p, miR-150-5p, miR-197-3p, miR-200a-5p, and miR-495-3p between the 2 groups (all q > 0.05; Figure 2G). These data provide evidence for specific dysregulation of platelet miRNAs in this cohort of T2DM patients.

Figure 2.

Validation of platelet miRNA expression in patients with T2DM. Platelet miRNA expression levels were measured in 19 nondiabetic controls and 25 individuals with T2DM using qRT-PCR. (A-C), miR-15b-3p, miR-146a-5p, and miR-155-5p were significantly upregulated in T2DM patients compared to controls. (D) miR-223-3p was markedly downregulated in the T2DM group. (E, F) miR-21-5p and miR-320a showed nominally lower expression in T2DM (uncorrected P < .05 for both), but did not reach statistical significance after correction for multiple testing (q = 0.052 for both). (G) No significant differences were observed in the expression of miR-26a-5p, miR-107, miR-140-5p, miR-150-5p, miR-197-3p, miR-200a-5p, and miR-495-3p between the 2 groups. Comparisons between independent groups were performed using the Mann-Whitney U-test followed by FDR correction using the Benjamini-Hochberg method. ** q < 0.01.

Correlation Analyses Between miRNA Levels and Platelet Parameters

Based on the validation results, we focused the correlation analyses between the 4 significantly dysregulated miRNAs (miR-15b-3p, miR-146a-5p, miR-155-5p, and miR-223-3p) and key platelet parameters in patients with T2DM. Given their biological relevance to platelet function and nominally altered expression, we additionally included miR-21-5p and miR-320a in these analyses. Spearman rank correlation analysis revealed no significant associations between any of the 6 miRNAs and either platelet count or plateletcrit (all q > 0.05; Supplemental Table S4). Notably, miR-320a expression was significantly and negatively correlated with mean platelet volume (MPV; correlation coefficient = −0.736, q < 0.01), platelet distribution width (PDW; correlation coefficient = −0.782, q < 0.01), and platelet large cell ratio (P-LCR; correlation coefficient = −0.747, q < 0.01; Figure 3A). In contrast, miR-146a-5p expression showed strong positive correlations with MPV (correlation coefficient = 0.898, q < 0.01), PDW (correlation coefficient = 0.872, q < 0.01), and P-LCR (correlation coefficient = 0.875, q < 0.01; Figure 3B). These findings reveal a potential link between miR-320a/miR-146a-5p and platelet size indices in T2DM, which may reflect underlying differences in megakaryopoiesis or platelet production dynamics.

Figure 3.

Correlation between miRNA levels and platelet parameters. (A-C) miR-320a expression was significantly and negatively correlated with mean platelet volume (MPV; correlation coefficient = −0.736, q < 0.01), platelet distribution width (PDW; correlation coefficient = −0.782, q < 0.01), and platelet large cell ratio (P-LCR; correlation coefficient = −0.747, q < 0.01). (D-F) miR-146a-5p expression showed strong positive correlations with MPV (correlation coefficient = 0.898, q < 0.01), PDW (correlation coefficient = 0.872, q < 0.01), and P-LCR (correlation coefficient = 0.875, q < 0.01). All correlations were assessed using Spearman's rank correlation coefficient, followed by FDR correction using the Benjamini-Hochberg method.

Correlation Analyses Between miRNA Levels and Platelet Activation

Given the reported association between diabetes and enhanced platelet reactivity, we examined correlations between platelet miRNAs and circulating markers of platelet activation (sP-selectin and sCD40L). Compared to nondiabetic controls, the plasma levels of both sP-selectin (2.73 ± 0.37 ng/mL vs 1.80 ± 0.37 ng/mL) and sCD40L (4.12 ± 0.86 ng/mL vs 2.20 ± 0.28 ng/mL) were significantly increased in T2DM patients (both P < .01; Figure 4A and B). In T2DM patients, Spearman correlation analysis revealed a significant positive correlation between miR-21-5p and sP-selectin (correlation coefficient = 0.529, q < 0.05; Figure 4C), and a significant negative correlation between miR-223-3p and sP-selectin (correlation coefficient = −0.752, q < 0.01; Figure 4D). No significant correlations were observed between any of the 6 miRNAs and sCD40L levels (all q > 0.05; Supplemental Table S4).

Figure 4.

Correlation between miRNA expression and platelet activation markers. (A, B) Plasma levels of soluble P-selectin (sP-selectin; 2.73 ± 0.37 ng/mL vs 1.80 ± 0.37 ng/mL) and soluble CD40 ligand (sCD40L; 4.12 ± 0.86 ng/mL vs 2.20 ± 0.28 ng/mL) were significantly elevated in individuals with T2DM compared to non-diabetic controls, as determined by ELISA. An unpaired two-tailed Student's t-test was used for comparison of independent groups. ** P < .01. (C) miR-21-5p was positively correlated with sP-selectin (correlation coefficient = 0.529, q = 0.029). (D) miR-223-3p was negatively correlated with sP-selectin (correlation coefficient = −0.752, q < 0.01). Correlations were assessed using Spearman's rank correlation analysis, followed by FDR correction using the Benjamini-Hochberg method.

Changes in Platelet miRNA Expression During Dapagliflozin Treatment in T2DM

To explore whether platelet miRNA levels change over time in patients with T2DM receiving dapagliflozin, we analyzed the levels of 6 selected miRNAs (miR-15b-3p, miR-21-5p, miR-146a-5p, miR-155-5p, miR-223-3p, and miR-320a) in platelets isolated at baseline and after 3 months of ongoing dapagliflozin treatment. All participants had well-controlled fasting blood glucose levels within the normal range throughout the study period. Results of the qRT-PCR assay revealed that platelet levels of miR-223-3p and miR-320a were significantly higher at 3 months compared to baseline (both q < 0.05; Figure 5A and B). In contrast, no significant changes were observed in the platelet levels of miR-146a-5p, miR-15b-3p, miR-21-5p, or miR-155-5p (all q > 0.05; Figure 5C to F). These findings suggest a potential association between dapagliflozin treatment and increased levels of miR-223-3p and miR-320a in platelets over time, despite stable fasting glycemia.

Figure 5.

Platelet miRNA expression was altered in response to dapagliflozin treatment. The expression levels of miR-15b-3p, miR-21-5p, miR-146a-5p, miR-155-5p, miR-223-3p, and miR-320a were measured in platelets from individuals at enrollment and after 3 months of ongoing dapagliflozin treatment by qRT-PCR assay. (A, B) Platelet levels of miR-223-3p and miR-320a were significantly increased after 3-month treatment. (C-F) No significant changes were observed in the expression of miR-146a-5p, miR-15b-3p, miR-21-5p, or miR-155-5p (all q > 0.05). Paired samples were analyzed using the Wilcoxon signed-rank test, followed by FDR correction using the Benjamini-Hochberg method. * q < 0.05.

Prediction and Functional Enrichment Analysis of miRNA Targets

To explore the potential biological relevance of miR-223-3p and miR-320a, 2 miRNAs that showed increased platelet levels after 3 months of dapagliflozin treatment, putative target genes were predicted using the TargetScan algorithm. A total of 416 and 848 putative targets were identified for miR-223-3p and miR-320a, respectively (Supplemental Data S2). Subsequent bioinformatic analysis was performed to explore the functional implications of these targets. GO functional analysis revealed that the target genes were predominantly enriched in the regulation of transcription (both positive and negative) within the biological process category. In terms of cellular components, these targets were significantly localized to the nucleoplasm. In the molecular function category, they were primarily linked to DNA binding and protein binding (Figure 6A to C). Furthermore, KEGG pathway enrichment analysis indicated significant enrichment in the Insulin signaling pathway (Figure 6D to F). Notably, pathways related to mitophagy and autophagy were also significantly enriched among the putative targets of both miRNAs (Figure 6D to F). It should be noted that these pathway enrichment results are based solely on computational predictions and have not been validated by direct functional experiments. Moreover, given that platelets are anucleate and transcriptionally inactive, the predicted enrichment in nuclear processes cannot reflect active pathways within platelets themselves, but may instead mirror the molecular landscape of their parent megakaryocytes.

Figure 6.

Functional enrichment analysis of predicted microRNA (miRNA) targets. Putative targets of miR-223-3p and miR-320a were predicted using the TargetScan algorithm. (A, B) Gene Ontology (GO) enrichment analysis of target genes for miR-223-3p and miR-320a, categorized into biological process (BP), cellular component (CC), and molecular function (MF) domains. (C, D) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the predicted target genes for miR-223-3p and miR-320a.

Discussion

The present study provided a comprehensive characterization of platelet miRNA dysregulation in T2DM, with several dysregulated miRNAs correlating with markers of platelet activation. Notably, platelet levels of miR-223-3p and miR-320a were significantly higher following 3 months of dapagliflozin treatment in an uncontrolled pre–post analysis, consistent with the hypothesis that SGLT2 inhibition might influence megakaryocytic programming. Bioinformatic prediction of miRNA targets highlighted enrichment in insulin signaling and autophagy-related pathways. Given that platelets lack nuclei and transcriptional activity, these predicted functions likely reflect regulatory programs established during megakaryopoiesis. The observed changes in platelet miRNA content may therefore represent systemic effects of SGLT2 inhibition on megakaryocytic maturation or mitochondrial homeostasis, rather than active gene regulation within circulating platelets.

Platelets are generated via the fragmentation of proplatelet extensions from megakaryocytes. Dysregulation of miRNAs during megakaryopoiesis can disrupt normal platelet production, leading to thrombocytopenia or thrombocytosis, both of which carry significant clinical implications. Although comprehensive miRNA profiling in human megakaryocyte precursors remains limited, extensive studies in murine hematopoietic progenitor populations have identified key regulatory miRNAs. ²² Specific miRNAs, including miR-34a, miR-155-5p, and miR-150, have been implicated in the differentiation and maturation of megakaryocyte progenitors.^23,24 In the present study, platelet levels of miR-320a, miR-146a-5p, and miR-155-5p were significantly correlated with platelet volume indices. While platelet size can be influenced by multiple factors beyond production dynamics, these associations may suggest alterations in megakaryocytic maturation or platelet biogenesis in the context of T2DM.

Accumulating evidence has proved that platelet-derived miRNAs are not passive bystanders, but active regulators of platelet reactivity. It was reported that miR-223-3p, one of the most abundant miRNAs in megakaryocytes and platelets, was dispensable for platelet production and function. ²⁵ However, clinical studies have revealed that reduced platelet miR-223-3p levels are associated with high on-clopidogrel platelet reactivity in patients with coronary artery disease, ²⁶ suggesting a context-dependent regulatory role in pathological settings. Similarly, miR-21-5p has been shown to enhance platelets hyperresponsive to agonists such as arachidonic acid. ²⁷ In this study, platelet levels of miR-223-3p and miR-21-5p were significantly correlated with circulating sP-selectin in patients with T2DM. Although sP-selectin can also derive from endothelial cells, this correlation is suggestive of a link between these miRNAs and systemic platelet activation in the context of diabetes.

A notable observation in this single-arm before-after analysis is an increase in the levels of miR-223-3p and miR-320a in platelets following 3 months of dapagliflozin treatment in patients with T2DM. These changes occurred in the context of SGLT2 inhibition and may reflect systemic or megakaryocytic responses to the drug or its metabolic consequences, such as improved mitochondrial function, reduced oxidative stress, or modulation of sodium–hydrogen exchanger activity. ²⁸ Although miR-223-3p has been shown to directly suppress P2Y12 expression in platelets, ²⁹ and proteomic analyses of platelets from miR-223-deficient mice reveal increased levels of coagulation factor XIII-A, a validated miR-223 target, ³⁰ it is important to note that GO and KEGG enrichment analyses predicting involvement of these miRNAs in insulin signaling and autophagy pathways are derived from computational algorithms and lack direct functional validation in platelets or their megakaryocytic precursors. Furthermore, given that platelets are anucleate cytoplasts, these predicted targets likely reflect regulatory events established in parent megakaryocytes rather than autonomous protein synthesis in mature platelets. Therefore, these pathway analyses should be interpreted as generating specific hypotheses for future research, rather than describing confirmed mechanisms.

While this study provides valuable insights into platelet miRNA dysregulation in T2DM, several limitations warrant acknowledgment. First, the current findings are based on a limited clinical sample size, necessitating validation in larger and more diverse cohorts and precluding formal multivariable analyses. Second, functional validation of the predicted miRNA targets and their roles in platelet biology was not performed in vitro or in vivo, limiting mechanistic conclusions. Third, the before-after design without a concurrent control group precludes causal inference due to potential confounding by background therapies, regression to the mean, or temporal effects. Fourth, residual leukocyte contamination following CD45 depletion was not quantified; thus, trace nucleated cell contamination could have contributed to the observed miRNA signals. Moreover, the absence of universally stable endogenous reference miRNAs in anucleate platelets introduces uncertainty into normalization and relative quantification. Collectively, these constraints underscore the exploratory nature of our findings and highlight the need for cautious interpretation.

The observed alterations in platelet microRNA profiles following SGLT2 inhibitor therapy underscore a potential link between this treatment modality and modifications in a key cellular component of thrombosis. This finding carries direct clinical relevance, as it points toward a novel, quantifiable dimension of the drug's pleiotropic effects that may contribute to its established cardiovascular protective benefits in patients with T2DM. From a translational standpoint, these dynamic changes in circulating platelet-associated microRNAs warrant investigation as candidate biomarkers for monitoring therapeutic response or residual cardiovascular risk. Future efforts should therefore focus on validating these signatures in larger, prospective cohorts with hard cardiovascular endpoints, employing rigorous platelet purity assessment and functional assays, and exploring their utility in refining personalized risk stratification and guiding antiplatelet therapy in this high-risk population.

Elucidating changes in platelet miRNA profiles observed during SGLT2 inhibitor therapy may generate hypotheses regarding underlying biological processes relevant to diabetes. Further research in this area holds promise for deepening our understanding of diabetic pathophysiology and, pending validation of platelet specificity and functional relevance, could contribute to the identification of candidate biomarkers linked to platelet-associated pathways, potentially informing future strategies to improve cardiovascular outcomes in this high-risk population.

Supplemental Material

sj-docx-1-cpt-10.1177_10742484261452727 - Supplemental material for Alterations of Platelet MicroRNAs Associated With Dapagliflozin Treatment in Individuals With Type 2 Diabetes Mellitus

Supplemental material, sj-docx-1-cpt-10.1177_10742484261452727 for Alterations of Platelet MicroRNAs Associated With Dapagliflozin Treatment in Individuals With Type 2 Diabetes Mellitus by Feng Chen, MD, Xueyan Ding, MD, Feifei Dong, MD, Xinghua Shan, MD, Chao Liu, MD, Rongbing Peng, MD, Lina Liu, MD, Yangyong Sun, MD, and Manli Yu, MD in Journal of Cardiovascular Pharmacology and Therapeutics

Supplemental Material

sj-xlsx-1-cpt-10.1177_10742484261452727 - Supplemental material for Alterations of Platelet MicroRNAs Associated With Dapagliflozin Treatment in Individuals With Type 2 Diabetes Mellitus

Supplemental material, sj-xlsx-1-cpt-10.1177_10742484261452727 for Alterations of Platelet MicroRNAs Associated With Dapagliflozin Treatment in Individuals With Type 2 Diabetes Mellitus by Feng Chen, MD, Xueyan Ding, MD, Feifei Dong, MD, Xinghua Shan, MD, Chao Liu, MD, Rongbing Peng, MD, Lina Liu, MD, Yangyong Sun, MD, and Manli Yu, MD in Journal of Cardiovascular Pharmacology and Therapeutics