Factors associated with aspirin resistance in diabetic patients: A metabolic and inflammatory profile analysis

Bo Chen; Zisheng Li; Jianyong Zhao; Huamei Dong; Long Tong; Jiaqing Dou

doi:10.1371/journal.pone.0332323

. 2025 Sep 11;20(9):e0332323. doi: 10.1371/journal.pone.0332323

Factors associated with aspirin resistance in diabetic patients: A metabolic and inflammatory profile analysis

Bo Chen ^1,^#, Zisheng Li ^1,^#, Jianyong Zhao ^2,^#, Huamei Dong ^2,^#, Long Tong ², Jiaqing Dou ^2,^*

Editor: Jeffrey J Rade³

PMCID: PMC12425219 PMID: 40934219

Abstract

Background

Diabetes mellitus (DM) is strongly linked to both first-time and recurrent atherosclerotic thrombotic events. Although aspirin (ASA) is commonly used to prevent cardiovascular diseases, studies have shown that ASA does not significantly reduce the risk of cardiovascular events in DM patients. This inconsistency highlights the need for further research into the underlying mechanisms of ASA resistance. Therefore, this study investigates the factors associated with aspirin resistance in DM patients, aiming to offer insights for improving cardiovascular disease prevention in this group. This study specifically investigated biochemical aspirin resistance, defined as inadequate suppression of thromboxane biosynthesis.

Methods

This prospective case-control study enrolled 53 DM patients and 66 age-/sex-matched healthy controls. Baseline metabolic-inflammatory markers—including BMI, LDL-C, cystatin C (CysC), hs-CRP, and HOMA-IR—were assessed alongside urinary 11-dehydrothromboxane B2 (11dhTxB2) levels pre- and post-aspirin intervention (81–100 mg/day × 7 days). Biochemical aspirin resistance was defined as post-administration urinary 11dhTxB2 ≥ 1500 pg/mg creatinine, reflecting inadequate suppression of total body thromboxane biosynthesis. Group comparisons utilized nonparametric tests (Mann-Whitney U) for skewed variables and χ² tests for categorical data. The influencing factors of ASA resistance were investigated through univariate analysis and logistic regression analysis, with multiple linear regression analysis being applied to model the Δ11dhTxB2 (post- vs. pre-administration difference).

Results

Compared to age-/sex-matched controls, diabetic patients exhibited significantly elevated metabolic-inflammatory markers (BMI, LDL-C, CysC, hs-CRP, HOMA-IR; all P < 0.01) and 60% higher baseline urinary 11dhTxB2 levels (2,324.58 vs. 1,452.51 pg/mg creatinine; P = 0.001), with persistent post-ASA disparity (1,205.31 vs. 1,058.02 pg/mg creatinine; P = 0.007). Biochemical aspirin resistance prevalence was 2.7-fold higher in diabetes (20.8% [11/53] vs. 7.6% [5/66]; P = 0.036). Univariate analysis linked Pre-11dhTxB2,higher BMI, hs-CRP, and HOMA-IR to ASA resistance (all P < 0.05), though multivariable logistic regression showed nonsignificant trends. Logistic regression analysis revealed that each unit increase in baseline 11dhTxB2 was associated with a 0.2% increase in the odds of aspirin resistance. Multivariable linear regression identified systemic inflammation (hs-CRP: B = 2,147.6, P < 0.001) and higher BMI (BMI: B = 204.9, P = 0.021) were strongly associated with attenuated thromboxane suppression (Δ11dhTxB2).

Conclusion

Patients with diabetes exhibit heightened thromboxane biosynthesis and a markedly elevated prevalence of biochemical aspirin resistance compared to healthy individuals, underscoring a prothrombotic phenotype linked to metabolic-inflammatory dysregulation. Higher BMI and systemic inflammation emerged as key factors associated with attenuated aspirin efficacy, suggesting platelet activation pathways beyond conventional COX-1 inhibition or involving non-platelet sources. Early identification of platelet hyperreactivity, coupled with targeted metabolic control and anti-inflammatory strategies, may refine personalized cardiovascular prevention in this high-risk population,while acknowledging that persistent urinary 11dhTxB2 elevation post-aspirin likely reflects significant non-platelet thromboxane generation.

Introduction

Diabetes mellitus (DM) is a major risk factor for both initial cardiovascular events and the subsequent worsening of conditions [1]. Individuals with diabetes have a significantly higher risk of cardiovascular (CV) diseases compared to non-diabetic patients with similar characteristics, primarily due to metabolic and functional changes in vascular cells [2]. This disproportionate risk is not only attributed to the direct impact of diabetes on blood glucose regulation, but also to its exacerbation of the cardiovascular system’s burden through pathophysiological mechanisms such as oxidative stress, chronic low-grade inflammation, dyslipidemia, and insulin resistance. These factors increase susceptibility to severe cardiovascular events like myocardial infarction and stroke [3].

Antiplatelet agents, such as aspirin (ASA), ticagrelor, and clopidogrel, are widely used to inhibit platelet function and lower the risk of atherosclerotic thrombosis [4]. Given the elevated cardiovascular risk in diabetic patients, antithrombotic therapy could provide greater clinical benefits for primary and secondary prevention [5]. However, the benefit-risk balance of aspirin in primary cardiovascular prevention remains controversial. Three large randomized, placebo-controlled trials in diverse populations, including healthy elderly individuals and diabetic patients, have been conducted. Results indicated that aspirin did not significantly lower cardiovascular event risk in diabetic patients, and its mechanism requires further investigation [6,7]. Due to insufficient evidence supporting aspirin’s widespread use, international guidelines do not advocate its routine use in diabetic patients without atherosclerotic cardiovascular disease (ASCVD). Instead, individualized treatment strategies are recommended to balance aspirin’s protective effects against ischemic events with bleeding risk [8].

Aspirin irreversibly acetylates cyclooxygenase-1 (COX-1), blocking the conversion of arachidonic acid into thromboxane A2 (TxA2) and prostacyclin (PGI2), thus inhibiting platelet activation and aggregation [9]. TxA2, a biologically active thromboxane metabolite, is clinically significant, making its detection crucial. However, TxA2’s high instability and short half-life (20–30 seconds) make conventional measurement technically difficult. Therefore, urinary 11-dehydro-thromboxane B2 (11dhTxB2), a stable enzymatic metabolite of TxA2, serves as a biomarker for total body TxA2 biosynthesis [10]. In the absence of aspirin therapy, it reflects contributions from both platelets and other cellular sources (e.g., monocytes, endothelium). Following aspirin administration, which irreversibly inhibits platelet COX-1, persistently elevated urinary 11dhTxB2 levels are thought to predominantly reflect TxA2 biosynthesis from non-platelet sources (e.g., via COX-2 or rapidly regenerated COX-1 in nucleated cells) [11,12], although the relative contributions pre-therapy in conditions like diabetes remain incompletely defined. Despite this complexity, elevated urinary 11dhTxB2 levels, particularly post-aspirin, have been consistently associated with increased cardiovascular risk [13].

Evidence suggests that premature and widespread vascular lesions in diabetes patients, coupled with a prothrombotic environment, contribute to platelet hyperactivity, which plays a key role in cardiovascular outcomes [14]. Oxidative stress, dyslipidemia, and diabetes-specific factors like insulin resistance and hyperglycemia are key contributors to platelet dysfunction [15]. Based on this, we hypothesize that diabetes-related metabolic states, such as hyperglycemia, insulin resistance, low-grade inflammation, obesity, dyslipidemia, and renal insufficiency, promote platelet activation, resulting in increased urinary 11dhTxB2 levels. Therefore, this study aims to assess the association between urinary 11dhTxB2 levels and metabolic parameters in diabetes patients, further exploring potential mechanisms underlying poor aspirin response in this population. Specifically, we investigate biochemical aspirin resistance, defined as persistent elevation of urinary 11dhTxB2 post-aspirin administration, acknowledging its reflection of total body thromboxane biosynthesis with likely significant non-platelet contributions under therapy.

Methods

Study design and participants

This study employed a prospective cohort design with matching. A total of 53 patients with type 2 DM were recruited from the outpatient and inpatient departments of Chaohu Hospital Affiliated to Anhui Medical University. All participants were diagnosed according to internationally recognized diagnostic criteria for diabetes. The control group consisted of 66 age- and sex-matched healthy individuals, who were selected from hospital staff and local community members, all of whom had normal blood glucose levels. The study period extended from February 1 to December 31, 2024. All participants provided written informed consent, and the study protocol was approved by the Ethics Committee of Chaohu Hospital Affiliated to Anhui Medical University (approval number: KYXM202401001). The study was conducted in accordance with the Declaration of Helsinki.

Inclusion criteria.

Participants were screened by the attending physician based on internationally recognized diagnostic criteria for diabetes, specifically defined by at least one of the following metabolic markers: fasting plasma glucose (FPG) levels ≥ 7.0 mmol/L, 2-hour postprandial blood glucose ≥ 11.1 mmol/L during an oral glucose tolerance test (OGTT), or elevated glycated hemoglobin (HbA1c) ≥ 6.5%, confirmed through laboratory testing.

Exclusion criteria.

Pregnant or lactating women; individuals allergic to or intolerant of enteric-coated aspirin; those with organic gastrointestinal diseases, such as gastrointestinal tumors, peptic ulcers, or inflammatory bowel disease; individuals with severe dysfunction of the heart, brain, liver, or kidneys (e.g., NYHA Class III/IV heart failure), or other major systemic diseases; current or recent use (within the preceding 3 months) of antithrombotic medications other than aspirin; and individuals with a documented history of major cardiovascular diseases (e.g., myocardial infarction, stroke, or coronary revascularization).

Data collection.

Blood samples were collected from all participants after an overnight fast (≥8 hours) to minimize diurnal and dietary variability. Venous blood was drawn into EDTA-anticoagulated tubes for plasma separation and serum-separating tubes (SST) for serum biomarkers. Plasma and serum were isolated by centrifugation at 3,000 rpm for 10 minutes within 30 minutes of collection. Aliquots were stored at −80°C until analysis to prevent analyte degradation. Hemolyzed or lipemic samples were excluded based on visual inspection. Data included the following: demographic data (age, gender); anthropometric parameters (body mass index, BMI);glucose metabolism biomarkers: glycated serum protein (GSP), homeostatic model assessment for insulin resistance (HOMA-IR) index, calculated as [fasting insulin (μU/mL) × fasting glucose (mmol/L)]/22.5; lipid markers (low-density lipoprotein cholesterol, LDL-C); renal function biomarkers (cystatin C, Cysc); systemic inflammation markers (high-sensitivity C-reactive protein, hs-CRP); and baseline urinary 11dhTxB2 levels.

Intervention.

Following baseline assessments, both the experimental group (DM patients) and the control group (healthy individuals) received enteric-coated low-dose aspirin (81–100 mg/day) orally once daily for 7 consecutive days. Urine samples for 11dhTxB2 measurement were collected 24 hours after the last aspirin intake to standardize the timing of sample collection relative to the final dose.

11dhTxB2 quantification and ASA response assessment

Urinary 11dhTxB2 levels were measured using chemiluminescence immunoassay (CLIA; RangeCL-300i analyzer), while urinary creatinine concentrations were determined via enzyme-linked immunosorbent assay (ELISA). To simplify sample collection protocols, randomly collected urine samples were utilized based on established evidence that urinary 11dhTxB2 levels exhibit a strong correlation with creatinine-adjusted values (r > 0.85 in prior validation studies) [16], eliminating the need for 24-hour urine collection. The 11dhTxB2 concentration was calculated using a standard curve generated from a reference solution, with results normalized to urinary creatinine and expressed as pg 11dhTxB2 per mg creatinine (pg/mg).

Participants were classified as good biochemical responders (post-aspirin urinary 11dhTxB2 < 1500 pg/mg creatinine) or poor biochemical responders (exhibiting biochemical aspirin resistance/non-response) (≥ 1500 pg/mg creatinine) [13,17,18]. This threshold of 1500 pg/mg creatinine was selected based on the manufacturer’s validation data for the specific assay used in this study [13,18], which established it through analytical comparison to a first-generation assay with an arbitrary threshold. We acknowledge this cutoff lacks robust clinical outcome validation. Recent studies report variable outcome associations with different thresholds for this assay [19]. Therefore, our definition reflects assay-specific biochemical non-suppression.

Biochemical aspirin resistance, defined here as persistent elevation of urinary 11dhTxB2 (≥ 1500 pg/mg creatinine) despite therapy, primarily signifies persistent systemic thromboxane biosynthesis. It is crucial to note that while pre-aspirin urinary 11dhTxB2 reflects total body TxA2 production from both platelet and non-platelet sources, post-aspirin levels in compliant individuals predominantly reflect TxA2 generation from non-platelet sources (e.g., vascular endothelium, monocytes via COX-2 or rapidly resynthesized COX-1) [17]. Therefore, this biochemical resistance likely originates extra-plateletly, rather than solely indicating a failure to inhibit platelet COX-1. While this specific cutoff has been employed in previous research to distinguish responders from non-responders, we acknowledge it is assay-specific and not a universal consensus criterion. Although direct associations between this exact threshold and clinical outcomes are limited, elevated urinary 11dhTxB2 levels have been consistently linked to increased cardiovascular risk in multiple studies [13,17,18]. The study specifically investigates this biochemical aspirin resistance/non-response and its association with metabolic dysregulation in DM.

Statistical methods

Statistical analyses were performed using IBM SPSS Statistics 25.0. Continuous variables with skewed distributions (assessed via Shapiro-Wilk test, P < 0.05) were expressed as median and interquartile range (IQR) and compared between DM and control groups using the Mann-Whitney U test. Categorical variables were presented as numbers (%) and analyzed with the χ² test or Fisher’s exact test (if expected cell counts <5). Potential factors associated with aspirin resistance in patients with DM were preliminarily screened via univariate analysis. Independent predictors were subsequently determined through multivariable logistic regression, with adjusted ORs and 95% CIs reported. Additionally, multivariable linear regression adjusted for age, sex, and baseline metabolic markers was used to evaluate independent determinants of Δ11dhTxB2 (post- vs. pre-administration difference). To evaluate within-subject changes in Δ11dhTxB2 levels, we utilized the Wilcoxon signed-rank test. All tests were two-tailed, with statistical significance defined as P < 0.05.

Results

Comparative analysis of metabolic profiles, inflammatory markers, and ASA response phenotypes

This study compared metabolic, inflammatory, and aspirin resistance-related indicators between DM patients and healthy controls. The results indicated no significant differences in age and gender distribution between the two groups (P > 0.05). However, DM patients exhibited significantly elevated levels of BMI, LDL-C, CysC, hs-CRP, and HOMA-IR compared to the control group (all P < 0.05).

Aspirin intervention reduced urinary 11dhTxB2 levels by an average of 41.39% in DM patients, compared to a 31.12% reduction in healthy controls; however, the intergroup difference in suppression magnitude did not reach statistical significance (P = 0.067). As illustrated in Fig 1, the distribution of 11dhTxB2 level changes pre- and post-ASA administration demonstrates higher baseline thromboxane biosynthesis in DM patients (pre-ASA: 2324.58 vs. 1452.51 pg/mg creatinine in controls; P = 0.001), with persistently elevated post-intervention levels (1205.31 vs. 1058.02 pg/mg creatinine; P = 0.007). Critically, biochemical aspirin resistance incidence was significantly higher in DM patients (20.8%, 11/53) than in controls (7.6%, 5/66; P = 0.036) (Table 1).

Fig 1 — Data are presented as median (IQR). *P = 0.001, **P = 0.007 vs. control group.

Table 1. Comparison of metabolic, inflammatory, and ASA resistance-related indicators between DM patients and the control group.

Variable	DM	Control group	P	U/χ²
Age	62 (57, 71)	61 (53.75, 70.25)	0.272	1.1
Gender (Male/Female)	30/23	37/29	0.953	0.004
BMI (kg/m²)	25.35 (24.30, 26.64)	24.11 (21.63, 25.93)	0.003*	2.970
LDL-C (mmol/L)	2.76 (2.37, 3.34)	2.23 (1.63, 2.65)	0.000*	4.379
Cysc (mg/L)	1.24 (0.99, 1.96)	0.99 (0.84, 1.26)	0.000*	3.738
hs-crp(mg/L)	0.65 (0.44, 0.84)	0.34 (0.21, 0.46)	0.000*	4.185
HOMA-IR	2.77 (2.03, 4.11)	1.35 (1.03, 2.26)	0.000*	5.285
Pre-ASA 11dhTxB2(pg/mg creatinine)	2324.58 (1447.50, 3401.08)	1452.51 (819.70, 2302.12)	0.001*	3.310
Post-ASA 11dhTxB2(pg/mg creatinine)	1205.31 (877.52, 1446.69)	1058.02 (641.41, 1252.66)	0.007*	2.711
Biochemical ASA resistance	11/53	5/66	0.036*	4.387

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*Note: Comparison between the two groups, P < 0.05, indicates a statistically significant difference;BMI: body mass index;11dhTxB2(pg/mg creatinine)= [Urinary 11dhTxB2 (pg/mL)]/ [Urinary creatinine (mg/mL)];Biochemical ASA resistance (poor ASA responder) was defined as post-administration urinary 11dhTxB2 ≥ 1500 pg/mg creatinine.

Fig 2 depicts the urinary 11dhTxB2 level distributions in healthy controls and DM patients at baseline and post-ASA administration. At baseline, healthy controls predominantly exhibited levels below 2000 pg/mg creatinine, whereas DM patients demonstrated a broader distribution range, with a subset exceeding 10,000 pg/mg creatinine. Following ASA administration, both groups showed reduced thromboxane levels, with the control group displaying a tighter post-administration distribution (majority <2000 pg/mg creatinine). Notably, persistent thromboxane overproduction was observed in a proportion of DM patients.

Univariate analysis of aspirin resistance-related factors in DM patients

To delineate determinants of ASA resistance in DM patients, a comparative analysis was conducted between ASA-resistant and ASA-sensitive subgroups. The results indicated that, compared to the ASA-sensitive group, the ASA-resistant group had significantly higher Pre-11dhTxB2(4719.54 vs 2053.08 pg/mg creatinine, P = 0.000), BMI (26.14 vs 25.02 kg/m², P = 0.035), HOMA-IR levels (3.51 vs 2.64, P = 0.046), and hs-CRP levels (0.75 vs 0.61 mg/L, P = 0.032). No significant differences were found between the two groups for other indicators, including GSP, LDL-C, and CysC (P > 0.05) (Table 2).

Table 2. Univariate analysis results of aspirin resistance-related factors in DM.

Variable	ASA sensitive	ASA resistance.	P	U
Pre-11dhTxB2(pg/mg creatinine)	2053.08(1314.93, 2461.63)	4719.54(3765.26, 6270.46)	0.000	440.000
BMI (kg/m²)	25.02 (24.09, 26.29)	26.14 (25.86, 27.25)	0.035	2.106
GSP (umol/L)	281.00 (220.75, 383.75)	349.00 (310.50, 441.00)	0.091	1.689
LDL-C (mmol/L)	2.67 (2.36, 3.20)	3.26 (2.65, 3.47)	0.151	1.437
Cysc (mg/L)	1.58 (1.01, 1.96)	1.08 (1.02, 1.61)	0.476	−0.713
hs-CRP(mg/L)	0.61 (0.36, 0.84)	0.75 (0.73, 0.82)	0.032	2.139
HOMA-IR	2.64 (2.01, 3.52)	3.51 (2.96, 4.94)	0.046	1.996

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Multivariable analysis of aspirin resistance-related factors in DM patients

Multivariable logistic regression was employed to identify independent determinants of ASA resistance in DM patients. The results indicated that BMI, GSP, LDL-C, CysC, hs-CRP, and HOMA-IR were not identified as independent factors influencing ASA resistance (all P > 0.05) (Table 3).

Table 3. Logistic regression analysis results of factors influencing ASA resistance in DM.

Influencing factors	β	S.E	Wals	P	OR	OR (95% CI)
BMI	0.177	0.208	0.727	0.394	1.194	0.795 ~ 1.793
GSP	0.003	0.004	0.887	0.346	1.003	0.996 ~ 1.010
LDL-C	0.377	0.603	0.391	0.532	1.458	0.447 ~ 4.748
Cysc	−0.293	0.737	0.158	0.691	0.746	0.176 ~ 3.165
hs-CRP	0.910	1.263	0.519	0.471	2.483	0.209 ~ 29.505
HOMA-IR	0.158	0.200	0.625	0.429	1.171	0.791 ~ 1.734

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Evaluating baseline 11dhTxB2 levels as a predictive biomarker for aspirin resistance in DM patients

Logistic regression analysis further revealed that each unit increase in baseline 11dhTxB2 was associated with a 0.2% increase in the odds of aspirin resistance (OR: 1.002, 95% CI: 1.001–1.003, P = 0.002) (Table 4).

Table 4. Logistic regression analysis of baseline 11dhTxB2 association with biochemical aspirin resistance in DM.

Influencing factors	β	S.E	Wals	P	OR	OR (95% CI)
Pre-11dhTxB2	0.002	0.001	9.788	0.002	1.002	1.001 ~ 1.003

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Multiple linear regression analysis of the difference in urinary 11dhTxB2 levels before and after ASA administration in DM patients

Multivariable linear regression identified systemic inflammation (hs-CRP: B = 2,147.6, P < 0.001) and higher BMI (B = 204.9, P = 0.021) were independently associated with attenuated thromboxane suppression (Δ11dhTxB2). In contrast, disease duration,GSP, LDL-C,CysC, and HOMA-IR showed no independent associations with Δ11dhTxB2 (all P > 0.05) (Table 5).

Table 5. Results of multiple linear regression analysis of the difference in urinary 11dhTxB2 levels before and after ASA administration in DM patients.

Parameter	B	SE	Beta	t	P
hs-CRP	2147.623	517.558	0.481	4.150	<0.001
BMI	204.881	86.021	0.276	2.382	0.021
Disease Duration	—	—	0.203	1.543	0.129
GSP	—	—	0.097	0.799	0.428
LDL-C	—	—	0.178	1.489	0.143
Cysc	—	—	0.058	0.463	0.646
HOMA-IR	—	—	−0.058	−0.478	0.633

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Biochemical aspirin resistance and response variability in DM patients

The Wilcoxon signed-rank test demonstrated a statistically significant decrease in urinary 11dhTxB2 levels following aspirin administration (Z = −6.123, P < 0.001). The median change in 11dhTxB2 levels (Δ11dhTxB2 = pre-aspirin – post-aspirin) was 1119.27 pg/mg creatinine, with an interquartile range (IQR) of 800.00–1500.00 pg/mg creatinine, reflecting considerable inter-individual variability in aspirin response. Of the 53 diabetic patients, 11 (20.8%) exhibited post-aspirin 11dhTxB2 levels ≥1500 pg/mg creatinine and were classified as aspirin-resistant. This subgroup had a median baseline 11dhTxB2 level of 4500 pg/mg creatinine(IQR: 3200–6800 pg/mg creatinine), significantly higher than the overall cohort median of 2324.58 pg/mg creatinine. Notably, a subset of three patients displayed minimal reduction (Δ11dhTxB2 < 10%) despite baseline levels ranging from 1800–2500 pg/mg creatinine.

Discussion

The relationship between DM patients and urinary 11dhTxB2 levels

This study revealed significantly elevated baseline urinary 11dhTxB2 levels in DM patients compared to healthy controls (2324.58 vs. 1452.51 pg/mg creatinine; P = 0.001), indicating a prothrombotic phenotype characterized by heightened thromboxane biosynthesis. This finding aligns with established evidence of platelet hyperreactivity in diabetes, characterized by enhanced activation, aggregation, and thromboxane biosynthesis [17,20,21]. Mechanistically, hyperglycemia-induced oxidative stress and endothelial dysfunction amplify COX-1 activity, promoting TxA2 synthesis [22]. Concurrently, insulin resistance—a hallmark of DM—elevates intracellular calcium flux in platelets, potentiating degranulation and further TxA2 release [23]. Beyond glycemic dysregulation, proatherogenic lipid profiles (e.g., elevated LDL-C) and chronic low-grade inflammation (evidenced by hs-CRP elevation) synergistically enhance platelet adhesion molecule expression (e.g., P-selectin, GPIIb/IIIa), culminating in a self-reinforcing cycle of thromboxane-driven thrombosis [4,24]. Our data thus corroborate the hypothesis that metabolic-inflammatory dysregulation is associated with heightened systemic thromboxane biosynthesis, contributing to increased thrombotic risk in DM.

The elevated baseline urinary 11dhTxB2 levels in diabetic patients (2324.58 vs. 1452.51 pg/mg creatinine in controls, P = 0.001) underscore a heightened thrombotic risk, consistent with prior evidence linking thromboxane biosynthesis to cardiovascular events [16]. Eikelboom et al. (2002) reported that higher 11dhTxB2 levels independently predict myocardial infarction, stroke, or cardiovascular death, with a hazard ratio of 1.8 for the highest versus lowest quartile (P < 0.001) [13]. Post-aspirin, the persistence of elevated 11dhTxB2 (1205.31 vs. 1058.02 pg/mg creatinine in controls, P = 0.007) and a 20.8% prevalence of biochemical resistance (≥1500 pg/mg creatinine) in our diabetic cohort further suggest an attenuated risk reduction. Previous studies indicate that post-ASA 11dhTxB2 levels ≥1500 pg/mg creatinine are associated with a 2- to 4-fold increased risk of adverse cardiovascular outcomes [17], highlighting the potential prognostic utility of this biomarker in identifying high-risk diabetic patients. While our study did not assess clinical events, these findings support the need for personalized risk stratification and therapeutic optimization in this population.

The effect of aspirin on urinary 11dhTxB2 levels

Following ASA administration, urinary 11dhTxB2 levels decreased by 41.39% in DM patients versus 31.12% in controls, suggesting some suppression of thromboxane biosynthesis despite metabolic dysregulation. Although this numerical disparity favored greater thromboxane suppression in DM, the intergroup difference did not attain statistical significance (P = 0.067), potentially reflecting type II error due to limited sample size or heterogeneous ASA responsiveness within the DM cohort [11,13]. Our observations align with studies demonstrating ASA-mediated attenuation of thromboxane biosynthesis in diabetes [17], yet contrast with reports of “aspirin failure” in subsets with severe insulin resistance or chronic inflammation [12]. Notably, persistent elevation of urinary 11dhTxB2 post-ASA (Fig 2) likely arises predominantly from hyperglycemia-driven COX-2 upregulation in non-platelet cells (e.g., endothelium, monocytes)---a pathway less sensitive to ASA---and/or rapid resynthesis of COX-1 in these cells [12]. Furthermore, glucose variability and oxidative stress in DM may accelerate platelet turnover, replenishing COX-1 pools and blunting ASA’s irreversible inhibition [17]. These mechanisms, coupled with interindividual pharmacokinetic differences, likely contribute to the attenuated statistical signal observed.

It is noteworthy that, even in patients classified as ASA-resistant based on the arbitrary cutoff (11dhTxB2 ≥ 1500 pg/mg creatinine), a substantial relative reduction in 11dhTxB2 levels—such as the 41.39% decrease observed in the DM group—may still indicate clinical benefit. Previous studies have demonstrated that urinary 11dhTxB2 levels correlate with cardiovascular outcomes [13], suggesting that any reduction in thromboxane biosynthesis could mitigate thrombotic risk. Thus, the clinical implications of ASA resistance should be interpreted cautiously.

Exploration of the mechanisms of aspirin resistance

This study further examined the factors related to aspirin resistance in diabetic patients. Univariate analysis revealed that BMI, HOMA-IR, and hs-CRP were significantly associated with ASA resistance, consistent with the findings of several studies. Previous studies have indicated a strong association between higher BMI and ASA resistance. Overweight or obese individuals often exhibit higher levels of inflammation and abnormal blood glucose, which may be linked to their poor response to ASA [25,26]. Additionally, studies have shown that hs-CRP, a blood marker of inflammation, is closely associated with the antithrombotic effect of aspirin [27]. Our results further support these findings, suggesting that chronic inflammatory states may reduce aspirin efficacy by enhancing platelet activation or altering thrombosis formation mechanisms.

The discrepancy between univariate and multivariable analyses may reflect collinearity among metabolic-inflammatory variables (e.g., BMI and hs-CRP) or heterogeneous ASA responsiveness within the DM cohort. For instance, subsets with severe insulin resistance or genetic polymorphisms in COX-1/PEAR1 may exhibit distinct pharmacodynamic profiles, diluting the independent effect of individual factors in logistic regression. This result suggests that these variables may not be independent factors influencing aspirin resistance. The mechanisms of aspirin resistance are complex, and factors such as genetics, changes in platelet function, aspirin metabolism, small sample sizes, or other confounding factors may interact to influence the results of this study [28,29].

Furthermore, our study identified baseline 11dhTxB2 levels as a significant predictor of aspirin resistance in diabetic patients. The univariate analysis showed markedly higher baseline levels in the ASA-resistant subgroup (4719.54 vs. 2053.08 pg/mg creatinine, P = 0.000), and logistic regression confirmed that each unit increase in baseline 11dhTxB2 was associated with a 0.2% higher odds of resistance (OR: 1.002, 95% CI: 1.001–1.003, P = 0.002). This suggests that elevated thromboxane biosynthesis at baseline may reflect a prothrombotic state less responsive to ASA, potentially driven by accelerated platelet turnover or non-COX-1 pathways, predominantly originating from non-platelet sources as discussed, warranting further mechanistic exploration.

Emerging evidence suggests that non-platelet sources of thromboxane (e.g., endothelial COX-2) may contribute to residual thromboxane biosynthesis despite ASA therapy [17]. Furthermore, accelerated platelet turnover in diabetic patients could replenish uninhibited cyclooxygenase-1 pools, potentially explaining the lack of independent associations in multivariable models [25].

The role of oxidative stress in thromboxane biosynthesis

A critical consideration not addressed in our analysis is the potential contribution of oxidative stress to persistent thromboxane generation. Hyperglycemia in diabetes potently induces oxidative stress through mitochondrial superoxide overproduction, advanced glycation end-product (AGE) formation, and protein kinase C (PKC) activation [30]. This pro-oxidant state directly upregulates COX-2 expression in vascular endothelial cells and monocytes [31], while simultaneously enhancing substrate availability for thromboxane synthesis via lipid peroxidation [32,33]. Compelling evidence positions oxidative stress as a primary driver of systemic thromboxane generation, potentially surpassing traditional risk factors. In the large-scale Framingham Heart Study cohort, oxidative stress markers demonstrated the strongest association with urinary 11dhTxB2 levels among over 3,000 participants, exceeding the predictive value of diabetes status or systemic inflammation [34]. This suggests oxidative stress may be a fundamental mechanism underlying the attenuated aspirin response observed in our diabetic cohort, particularly through its stimulation of non-platelet thromboxane pathways.

The role of hs-CRP and BMI in ASA response

Multiple linear regression analysis showed that hs-CRP, a marker of systemic inflammation, and BMI were significantly associated with the difference in urinary 11dhTxB2 levels after ASA administration in diabetic patients. Previous studies have indicated that hs-CRP, is closely associated with the risk of cardiovascular diseases [35,36]. Additionally, the relationship between BMI, cardiovascular events, and drug responsiveness has been extensively studied [37,38]. Higher BMI not only contributes to insulin resistance and chronic low-grade inflammation, but it may also directly affect platelet function and thrombus formation [39,40]. The results of this study further validate these findings, suggesting that the attenuation of total thromboxane biosynthesis suppression by aspirin in diabetic patients may be related to the combined presence of these factors, potentially through their promotion of non-platelet (e.g., COX-2 mediated) TxA2 production.

Persistent thromboxane overproduction post-ASA may arise from hyperglycemia-driven COX-2 upregulation in endothelial cells or monocytes—a pathway less sensitive to ASA inhibition [31]. Emerging evidence highlights that adipose tissue-derived exosomes in obese individuals carry microRNAs (e.g., miR-155) capable of enhancing platelet COX-1 expression, potentiating thromboxane biosynthesis despite ASA therapy [41]. Furthermore, systemic inflammation in diabetes may induce COX-2-mediated thromboxane production in endothelial cells, a pathway resistant to ASA inhibition [42].

Heterogeneity in aspirin response among patients with diabetes

Despite a greater median reduction in 11dhTxB2 levels in the DM group (1119.27 pg/mg creatinine) compared to controls (394.49 pg/mg creatinine), fewer DM patients achieved the threshold of <1500 pg/mg (79.2% vs. 92.4%). This is likely due to significantly higher baseline 11dhTxB2 levels in the DM group (median: 2324.58 pg/mg creatinine) requiring a larger absolute reduction to fall below the threshold.

Our findings highlight heterogeneity in aspirin response among diabetic patients, with a small subgroup showing minimal reduction in 11dhTxB2 levels despite moderate baseline values. This observation points to the existence of true aspirin resistance, potentially linked to mechanisms such as accelerated platelet turnover or, more likely given the biomarker used, robust non-platelet (e.g., COX-2 mediated) thromboxane production, consistent with previous reports [6,17]. These results emphasize the importance of tailoring aspirin therapy, particularly for high-risk diabetic patients with elevated baseline thromboxane levels or suboptimal responses to standard doses.

Limitations

Several limitations should be acknowledged. First, the cohort’s modest sample size (53 diabetic patients and 66 controls) may restrict the generalizability of our findings, particularly given the clinical and metabolic heterogeneity inherent to diabetic populations. A larger, multicenter cohort with predefined stratification criteria could enhance external validity. Second, the cross-sectional design precludes causal inference—while metabolic-inflammatory markers (BMI, hs-CRP, HOMA-IR) correlate with aspirin resistance, their temporal relationship and mechanistic contributions remain undefined. The observed associations between metabolic-inflammatory markers (e.g., BMI, hs-CRP) and attenuated aspirin response (Δ11dhTxB2 or ASA resistance status) should therefore be interpreted as correlational, not causal. Longitudinal studies tracking dynamic changes in platelet reactivity alongside metabolic parameters are needed to establish causality.

Third, although urinary 11dhTxB2 is a validated biomarker of thromboxane biosynthesis, notably, complementary assessments of platelet function—such as agonist-induced aggregation assays or flow cytometric analysis of activation markers—were not performed. Moreover, unmeasured inflammatory mediators (e.g., IL-6, TNF-α) and oxidative stress markers (e.g., 8-iso-prostaglandin F2α, malondialdehyde) could provide further mechanistic insights into COX-2-driven thromboxane biosynthesis. Oxidative stress is a particularly significant unmeasured confounder, as it has been robustly established as one of the strongest predictors of thromboxane generation—even surpassing traditional risk factors like diabetes and inflammation in large cohort studies [32–34]. In aspirin-treated individuals, oxidative stress predominantly drives non-platelet (e.g., endothelial/monocytic) TxA2 production via COX-2 upregulation, directly contributing to thrombosis risk and mortality [32,33]. Our observed associations between metabolic-inflammatory markers (hs-CRP, HOMA-IR) and attenuated thromboxane suppression may partly reflect underlying oxidative stress pathways.

Fourth, our reliance on urinary 11dhTxB2 as the sole measure of aspirin response is an important limitation. As discussed, this biomarker reflects total body TxA2 biosynthesis, and post-aspirin levels are predominantly influenced by non-platelet sources. We did not employ platelet-specific functional assays (e.g., light transmission aggregometry in response to arachidonic acid or collagen, VerifyNow Aspirin test, or thromboxane-dependent platelet activation markers like P-selectin expression) which could more directly assess the inhibition of platelet COX-1-dependent pathways. Consequently, our definition of “biochemical resistance” captures systemic thromboxane overproduction under therapy but cannot definitively distinguish true platelet COX-1 resistance from significant non-platelet contributions. Future studies incorporating both urinary metabolites and platelet-specific functional assays would provide a more comprehensive picture.

Regarding methodology, the use of an arbitrary cutoff for ASA resistance (urinary 11dhTxB2 ≥ 1500 pg/mg creatinine) may not fully reflect the clinical benefit of aspirin, particularly in patients who exhibit substantial relative reductions in 11dhTxB2 levels. To address this limitation, future studies should consider both absolute and relative changes in 11dhTxB2 to better elucidate the relationship between biochemical markers and clinical outcomes.

Conclusion

In summary, this study demonstrates that patients with diabetes exhibit a prothrombotic phenotype characterized by elevated baseline urinary 11dhTxB2 levels, which also serve as a predictive biomarker for biochemical aspirin resistance (OR: 1.002, P = 0.002). The incidence of biochemical aspirin resistance was 2.7-fold higher in diabetic patients compared to healthy controls (20.8% vs. 7.6%, P = 0.036). Notably, metabolic-inflammatory dysregulation—reflected by higher BMI and hs-CRP—emerged as key factors associated with attenuated aspirin efficacy, with persistent thromboxane biosynthesis (likely originating predominantly from non-platelet sources) post-intervention suggesting pathways beyond conventional platelet COX-1 inhibition, such as COX-2 in nucleated cells or rapidly regenerated COX-1 in diabetic thrombogenesis.

While ASA intervention reduced urinary 11dhTxB2 by 41.4% in diabetic patients versus 31.1% in controls, the intergroup difference (P = 0.067) and residual thromboxane overproduction highlight the unmet need for personalized antiplatelet strategies targeting platelet hyperreactivity driven by insulin resistance and chronic inflammation. These findings underscore the imperative to integrate metabolic control with tailored antiplatelet therapies in diabetes management.

Future investigations should prioritize:

Mechanistic studies dissecting platelet turnover dynamics and non-platelet thromboxane sources (e.g., endothelial COX-2) in diabetic populations,incorporating direct measurements of oxidative stress biomarkers (e.g., urinary 8-iso-PGF2α, plasma oxidized LDL);
Pharmacogenomic profiling to identify genetic variants(e.g.,COX-1 haplotypes, PEAR1 polymorphisms) influencing ASA pharmacodynamics;
Randomized trials evaluating combinatorial therapies targeting oxidative stress pathways (e.g., ASA + NRF2 activators like sulforaphane or mitochondria-targeted antioxidants) or anti-inflammatory agents (e.g., IL-6 inhibitors) to mitigate inflammation-enhanced thrombotic risk.

Supporting information

S1 File. Data.

(XLSX)

pone.0332323.s001.xlsx^{(34.4KB, xlsx)}

Acknowledgments

We express our sincere gratitude to all diabetic patients and healthy volunteers who participated in this study. We are deeply grateful to the healthcare professionals from the Department of Endocrinology and nuclear medicine technicians at Chaohu Hospital Affiliated to Anhui Medical University for their dedicated support and technical assistance.

Data Availability

All relevant data are within the manuscript and its Supporting information files.

Funding Statement

This study was supported by the Anhui Medical University School Fund Grant (2023xkj069). No additional external funding was received for this study. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0332323.r001

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19 Mar 2025

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Additional Editor Comments:

Please find the comments from the reviewers below:

Reviewer 1:

1. Blood sample collection data for biochemical analysis is not reported.

2. Why did seven-day treatment used what would be the impact if the drug is prescribed for longer duration of time, provide some reference.

3. Were the samples collected 24 h after the last aspirin intake?

4. Was the drug given in the range of 81-100mg according to body weight or was some specific dose given to patients?

5. Provide information about the risk assessment based on levels of 11-dehydro-TXB2.

6. Was the study involved patients with type1 and type2 diabetes?

7. Consider revising sentence structures, refining the flow of ideas, and ensuring consistency throughout.

Reviewer 2:

Overall I found the manuscript to be informative and well-written. My comments are minor, but I feel resolution would lend greater clarity to the message.

ABSTRACT: The abstract is concise and reflective of the manuscript.

INTRODUCTION: The introduction is clear and informative.

METHODS: The authors state this is a 'prospective case-control design.' Technically, a case-control design is, by definition, a retrospective study in which 'cases' are patients with the outcome in question while 'controls' are patients without the outcome. The purpose of these studies is to define the exposures most associated with the outcome, with the presumption that these exposures are implicated in the cause. The current study is more of a matched prospective cohort design, as patients do or do not have an exposure of interest (diabetes), and they are being evaluated for an outcome of interest (aspirin resistance). There is a question about matching as noted below.

It would be helpful to know if these subjects have Type 1 DM or Type 2 DM. The BMI suggests Type 1 DM; however, this may not be the case. This is important because of the proposed mechanism (insulin resistance) is considered to be the underlying pathobiology in Type 2 but not Type 1 DM (though itt can exist in both). Also, given the age of 62 in the DM group, since Type 1 DM is often a disease of onset in the childhood or teenage years, the duration of exposure to the disease would be substantially longer in those with Type 1 DM vs those with Type 2, which often has onset in adulthood.

As far as the outcome, the authors defined it as a specific threshold of 11dhTxB2 level of <1500 pg/mg. They give a reference that this threshold is in accordance with consensus criteria, but this does not seem to be entirely accurate. The reference cited is that of a cutoff value for a specific assay as found in the FDA submission (https://www.accessdata.fda.gov/cdrh_docs/reviews/K062025.pdf). This may be appropriate, but more clarification on why this specific value is used would be helpful - has this specific threshold been associated with specific outcomes?

A brief desciption of recruitment methods would be helpful to understand how these patients were identified and from what population they were selected.

For statistical methods, given that this is a repeated measure (each patient contributed two values, one pre- and one post- exposure), an analysis of repeated measures would be appropriate. In its current form, the entire populations are measured with pre- and post-values; however, the change per individual may be more appropriate to identfiy a group of patients in whom aspirin has little effect. For example, are those who do not achieve the pre-defined threshold of 1500 pg/mL those who started well above this threshold, or are there some patients who have little to no response at all? This may signifcantly impact the results and the discussion.

RESULTS:

In the results, the authors mention that there is not difference between age and gender distribution. Elsewhere, it is mentioned that this is an age/sex-matched cohort. If this is indeed 'matched,' then the process of matching should be disclosed. If there was no intentional matching during the enrollment period, then this is not the appropriate terminology.

As noted above, a analysis for repeated measures would be helpful. If available, inclusion of glycosylated hemoglobin measurements may be helpful, and this may be a contributing factor to ASA resistance. The DM group had a more substantial reduction in the outcome measure but fewer achieved the predefined threshold. A better representation of this would be helpful, as noted above, to see exactly in whom this threshold was not acheived. Were higher baseline 11dhTxB2 levels evaluated as a predictor of who did or did not achieve this threshold?

The BMI is quite low, and the 75th percentile is well under the threshold typically used to define obesity of 30 kg/m2. Obesity is mentioned as a risk for aspirin resistance; however, there seems to be a relatively low prevalence in this cohort. Perhaps increasing BMI, but not obesity, is the risk?

Within the results, there are many instances of interpretation. This should be saved for the discussion, and results should be purely objective and without interpretation. For example, line 239-240 "suggesting that these variables may not independently affect ASA resistance" could be seen as interpretive.

DISCUSSION:

Also, there is mention of hs-CRP as a 'primary driver.' This is a bold statement - there may be an association, but it is difficult to say this is a driver. If it is a 'driver,' then the presumption is that reducing this level would, in turn, result in improving the outcome in question. That is highly speculative. Also note that hs-CRP is an assay, not a molecule.

I feel that with the above analyses included, especially an assessment of DM control such as HbA1c, may be informative (for example, are those with poor control more likely to have an attenuated response) and an analysis of repeatead measures, may inform the discussion. Also, acknowleding the limitation of the arbitrary cuttoff for ASA resistance may be important. It seems unlikely that there is no benefit in substantial relative reduction if, indeed, the measure is correlated with clinical outcomes.

Reviewer 3:

This study examines the factors contributing to aspirin resistance in patients with diabetes mellitus, aiming to enhance cardiovascular disease prevention strategies for this population. It investigates the relationship between urinary 11-dehydro-thromboxane B2 (11dhTxB2) levels and metabolic parameters in diabetic patients to better understand the mechanisms behind inadequate aspirin response.

The findings indicate that diabetes patients exhibit heightened thromboxane production, as evidenced by elevated urinary 11dhTxB2 levels, and a significantly higher prevalence of biochemical aspirin resistance compared to healthy individuals. Increased body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), cystatin-C, high-sensitivity C-reactive protein (hs-CRP), and homeostatic model assessment for insulin resistance (HOMA-IR) suggest that obesity and systemic inflammation are key factors modulating reduced aspirin efficacy. These results imply that platelet activation pathways beyond COX-1 inhibition are involved, highlighting the complexity of aspirin resistance in diabetic patients.

Major remarks

Contrary to the hypothesis, aspirin (ASA) administration reduced 11-dehydro-thromboxane B2 (11dhTxB2) levels in diabetes mellitus (DM) patients compared to controls, indicating greater thromboxane suppression in DM, the intergroup difference did not reach statistical significance. This lack of significance may be attributed to the limited sample size. The study suggested that persistent thromboxane overproduction could be due to hyperglycemia-driven COX-2 upregulation. However, further clarification was not provided. To support this hypothesis, additional analysis of inflammatory or oxidative stress markers could be beneficial.

Univariate analysis showed that body mass index (BMI), homeostatic model assessment for insulin resistance (HOMA-IR), and the inflammatory marker high-sensitivity C-reactive protein (hs-CRP) were significantly associated with aspirin resistance, aligning with previous studies. However, logistic regression analysis did not confirm BMI, hs-CRP, and HOMA-IR as independent risk factors, suggesting they may not individually influence aspirin resistance.

In contrast, multiple linear regression analysis found that hs-CRP and BMI were significant factors affecting the change in urinary 11-dehydro-thromboxane B2 levels after aspirin administration in diabetic patients. This indicates that hs-CRP and obesity, both linked to chronic low-grade inflammation, could collectively impact the aspirin response in diabetes mellitus. The reliance on multiple statistical analyses to support the hypothesis of aspirin resistance in diabetes due to inflammatory pathway activation suggests a complex interplay of factors, making the observation inconclusive, mainly because of the sample size and existence of both ASA sensitive and ASA resistance sub-group within the experimental group. As discussed in the limitation section, metabolic inflammatory markers correlate with aspirin resistance with the existing cohort, their temporal relationship and mechanistic contributions need to be defined.

Finally, more parameters or markers need to be included in the study to assess the inflammation to better understand the ASA resistance in Diabetes patients, which will offer insights for improving cardiovascular disease prevention in this group.

Minor remarks

1. Explanation of how ASA resistance is calculated in Table 1 is not provided.

2. The second and third result titles are the same. Used “Univariate analysis” instead of “Multivariate analysis” for the third result title.

3. Resize the figures for better clarity. Multiple font sizes are used and inconsistent across two figures.

4. Add significance in figure 1.

5. Inconsistency in font used across the manuscript.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

Reviewer #1: 1. Blood sample collection data for biochemical analysis is not reported.

2. Why did seven-day treatment used what would be the impact if the drug is prescribed for longer duration of time, provide some reference.

3. Were the samples collected 24 h after the last aspirin intake?

4. Was the drug given in the range of 81-100mg according to body weight or was some specific dose given to patients?

5. Provide information about the risk assessment based on levels of 11-dehydro-TXB2.

6. Was the study involved patients with type1 and type2 diabetes?

7. Consider revising sentence structures, refining the flow of ideas, and ensuring consistency throughout.

Reviewer #2: Overall I found the manuscript to be informative and well-written. My comments are minor, but I feel resolution would lend greater clarity to the message.

ABSTRACT: The abstract is concise and reflective of the manuscript.

INTRODUCTION: The introduction is clear and informative.

A brief desciption of recruitment methods would be helpful to understand how these patients were identified and from what population they were selected.

RESULTS:

DISCUSSION:

Reviewer #3: This study examines the factors contributing to aspirin resistance in patients with diabetes mellitus, aiming to enhance cardiovascular disease prevention strategies for this population. It investigates the relationship between urinary 11-dehydro-thromboxane B2 (11dhTxB2) levels and metabolic parameters in diabetic patients to better understand the mechanisms behind inadequate aspirin response.

Major remarks

Minor remarks

1. Explanation of how ASA resistance is calculated in Table 1 is not provided.

2. The second and third result titles are the same. Used “Univariate analysis” instead of “Multivariate analysis” for the third result title.

3. Resize the figures for better clarity. Multiple font sizes are used and inconsistent across two figures.

4. Add significance in figure 1.

5. Inconsistency in font used across the manuscript.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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PLoS One. 2025 Sep 11;20(9):e0332323. doi: 10.1371/journal.pone.0332323.r002

Author response to Decision Letter 1

14 Apr 2025

Dear Editor and Reviewers:

Thanks for your letter and for the reviewers’ comments concerning our manuscript entitled “Factors Influencing Aspirin Resistance in Diabetic Patients: A Metabolic and Inflammatory Profile Analysis” (ID: PONE-D-25-04526). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. Revised portion are marked in red in the paper. The main corrections in the paper and the responds to the reviewer’s comments are as following:

The academic editor:

loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

Response: Thank you for your suggestion. After checking, the experimental methods involved in my research have been described in detail in the paper, and there are no specific laboratory protocols that need to be uploaded independently. If necessary, I am happy to provide further explanations or make adjustments according to your guidance.

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Response: Thank you very much for your reminder. We have checked it again, and ensured that the manuscript meet PLOS ONE’s style requirements, including those for file naming.

2.We note that your Data Availability Statement is currently as follows: [All relevant data are within the manuscript and its Supporting Information files.]

For example, authors should submit the following data:

- The values behind the means, standard deviations and other measures reported;

- The values used to build graphs;

- The points extracted from images for analysis.

Authors do not need to submit their entire data set if only a portion of the data was used in the reported study.

Response: Thank you for your feedback. We confirm that our submission fully complies with PLOS's data availability policy.

(1).Data Availability Statement Update:We have uploaded the complete minimal dataset required to replicate all study findings as a Supporting Information file named "data" (format: .xlsx). This file contains:Raw numerical values underlying summary statistics (means, SDs, etc.);Source data for all figures and graphs;Coordinates/extracted points from image analyses;Metadata describing variables, experimental protocols, and data processing steps.

(2).Accessibility:The dataset is freely accessible alongside the manuscript files. No ethical, legal, or third-party restrictions apply to this de-identified data.

(3).Compliance Statement:Our updated Data Availability Statement now explicitly references the uploaded file:"All raw data required to replicate the study findings are available in the Supporting Information file 'data'."

Please let us know if any additional clarifications or data formatting adjustments are needed.

Reviewer 1:

1. Blood sample collection data for biochemical analysis is not reported.

Response: Thank you for highlighting this omission. We have now added detailed blood sample collection protocols to the Methods section to improve methodological transparency. Below is the revised text:”Blood samples were collected from all participants after an overnight fast (≥8 hours) to minimize diurnal and dietary variability. Venous blood was drawn into EDTA-anticoagulated tubes for plasma separation and serum-separating tubes (SST) for serum biomarkers. Plasma and serum were isolated by centrifugation at 3,000 rpm for 10 minutes within 30 minutes of collection. Aliquots were stored at −80°C until analysis to prevent analyte degradation. Hemolyzed or lipemic samples were excluded based on visual inspection.”(Page [6], Lines [132-138]).

We appreciate your feedback, which has strengthened the methodological rigor of our study.

2.Why did seven-day treatment used what would be the impact if the drug is prescribed for longer duration of time, provide some reference.

Response: We thank the reviewer for their thoughtful inquiry regarding our decision to implement a seven-day treatment period for aspirin administration and the potential effects of extending this duration. We provide a comprehensive explanation below, grounded in the biological properties of platelets and supported by relevant literature.

Rationale for the Seven-Day Treatment Period�

The selection of a seven-day treatment period with low-dose enteric-coated aspirin (81–100 mg/day) was deliberate and based on established scientific principles. Platelets have a lifespan of approximately 7–10 days, and aspirin exerts its antiplatelet effect by irreversibly inhibiting COX-1, thereby preventing the synthesis of TxA2. This inhibition persists for the lifespan of the affected platelets. A seven-day duration ensures that the majority of circulating platelets are exposed to aspirin’s effect, enabling a reliable evaluation of its cumulative antiplatelet activity. In our study, this was measured through urinary 11dhTxB2 levels following the intervention.

This timeframe aligns with widely accepted research protocols for assessing aspirin’s pharmacodynamic effects. For example:

Eikelboom et al. (2002) employed a minimum of seven days of aspirin administration to evaluate thromboxane biosynthesis in patients at high cardiovascular risk, setting a benchmark for this duration.

Lopez et al. (2014) utilized a seven-day regimen to study platelet thromboxane responses in diabetic patients with coronary artery disease, validating its relevance to our study population.

Parish et al. (2023) reinforced this approach by establishing consensus criteria for classifying aspirin responders based on 11dhTxB2 levels after a seven-day protocol.

These studies collectively affirm that a seven-day treatment period is optimal for investigating aspirin’s short-term impact on platelet function and thromboxane suppression.

Implications of a Longer-Term Aspirin Regimen�

Extending aspirin administration beyond seven days—potentially to weeks or months—would likely maintain thromboxane suppression, given aspirin’s irreversible COX-1 inhibition and the continuous turnover of platelets. However, prolonged use could introduce additional considerations, particularly in our study population of diabetic individuals. These include:

Aspirin Resistance: Extended therapy might increase the risk of aspirin resistance in some patients, potentially due to accelerated platelet turnover or alternative thromboxane production pathways (e.g., COX-2 upregulation under hyperglycemic conditions), as noted by Simeone et al. (2018). This could reduce efficacy over time.

Confounding Variables: Longer treatment durations may be affected by factors such as changes in glycemic control, patient compliance, or side effects (e.g., gastrointestinal bleeding), which could obscure the interpretation of thromboxane levels.

In conclusion, the seven-day treatment period was chosen to correspond with the platelet lifespan and established research standards, providing a robust framework for assessing aspirin’s antiplatelet efficacy. While a longer duration might sustain thromboxane suppression, it is unnecessary for our study’s objectives and could introduce confounding factors. We believe this approach is scientifically justified and consistent with prior literature.

References

1.Eikelboom JW, Hirsh J, Weitz JI, Johnston M, Yi Q, Yusuf S. Aspirin-resistant thromboxane biosynthesis and the risk of myocardial infarction, stroke, or cardiovascular death in patients at high risk for cardiovascular events. Circulation. 2002;105(14):1650-1655.

2.Lopez LR, Guyer KE, Torre IG, Pitts KR, Matsuura E, Ames PR. Platelet thromboxane (11-dehydro-Thromboxane B2) and aspirin response in patients with diabetes and coronary artery disease. World J Diabetes. 2014;5(2):115-127.

3.Parish S, Buck G, Aung T, Mafham M, Clark S, Hill MR, et al. Effect of low-dose aspirin on urinary 11-dehydro-thromboxane B2 in the ASCEND (A Study of Cardiovascular Events iN Diabetes) randomized controlled trial. Trials. 2023;24(1):166.

4.Simeone P, Boccatonda A, Liani R, Santilli F. Significance of urinary 11-dehydro-thromboxane B(2) in age-related diseases: Focus on atherothrombosis. Ageing Res Rev. 2018;48:51-78.

3.Were the samples collected 24 h after the last aspirin intake?

Response: We thank the reviewer for their careful attention to the timing of sample collection. In response to the query, we confirm that urine samples for the measurement of 11dhTxB2 were indeed collected 24 hours after the last aspirin intake. This timing was deliberately chosen to ensure a standardized assessment of aspirin's antiplatelet effect. By collecting samples at this interval, we could evaluate thromboxane suppression at a consistent time point following the final dose. Given that aspirin irreversibly inhibits COX-1, the 24-hour post-dose collection ensures that the observed 11dhTxB2 levels reflect the cumulative impact of the seven-day treatment period.

To make this detail explicit and address the reviewer’s concern, we have updated the revised manuscript with the following clarification in the Methods section (Page [7], Lines [148-150]):

"Urine samples for 11dhTxB2 measurement were collected 24 hours after the last aspirin intake to standardize the timing of sample collection relative to the final dose."

We believe this addition enhances the transparency of our methodology and aligns with established practices in studies evaluating aspirin’s pharmacodynamic effects. We appreciate the reviewer’s diligence in raising this point, as it has helped us strengthen the manuscript.

4.Was the drug given in the range of 81-100mg according to body weight or was some specific dose given to patients?

Response: Thank you for your query regarding the aspirin dosage in our study. To address your question directly: all patients received a fixed daily dose of 100 mg of low-dose enteric-coated aspirin for seven consecutive days. The dosage was not adjusted based on body weight or any other individual characteristics. Instead, a specific dose of 100 mg per day was administered uniformly to all participants.

To provide further context, the dosage range of 81-100 mg mentioned in the study reflects the commonly accepted therapeutic range for aspirin’s antiplatelet effects. In this case, we selected a fixed dose of 100 mg/day as the standard for all participants, which aligns with typical clinical study designs evaluating aspirin’s inhibition of platelet COX-1 activity in adults. This fixed-dose approach eliminates the need for weight-based adjustments, as the therapeutic effect is achieved consistently within this dosage range across adult populations.

We hope this clarifies the administration protocol used in our study!

5.Provide information about the risk assessment based on levels of 11-dehydro-TXB2.

Response:Thank you for your valuable suggestion. We acknowledge the importance of elaborating on the risk assessment associated with levels of urinary 11dhTxB2 in the context of our study. Below, we have provided additional information based on the data presented in our manuscript and supported by relevant literature, which has been integrated into the revised manuscript under the “Discussion” section.

In our study, diabetic patients exhibited significantly higher baseline urinary 11dhTxB2 levels (median: 2324.58 pg/mg creatinine, IQR: 1447.50–3401.08) compared to healthy controls (median: 1452.51 pg/mg creatinine, IQR: 819.70–2302.12; P = 0.001). Post-aspirin intervention, 11dhTxB2 levels remained elevated in the diabetic group (median: 1205.31 pg/mg creatinine, IQR: 877.52–1446.69) compared to controls (median: 1058.02 pg/mg creatinine, IQR: 641.41–1252.66; P = 0.007). These persistently elevated levels suggest a prothrombotic state in diabetic patients, even after aspirin therapy, which aligns with the observed 2.7-fold higher prevalence of biochemical aspirin resistance (20.8% vs. 7.6%, P = 0.036).

The clinical relevance of 11dhTxB2 levels as a risk marker for cardiovascular events has been well-documented. Eikelboom et al. (2002) demonstrated that elevated urinary 11dhTxB2 levels are strongly associated with an increased risk of myocardial infarction, stroke, or cardiovascular death in high-risk patients, independent of traditional risk factors such as hypertension, hyperlipidemia, or smoking [1]. Specifically, their study reported a dose-response relationship, with higher quartiles of 11dhTxB2 correlating with incrementally greater cardiovascular risk (hazard ratio: 1.8 for the highest vs. lowest quartile, P < 0.001). Although our study did not directly assess clinical outcomes, the elevated baseline 11dhTxB2 levels in diabetic patients (60% higher than controls) suggest a heightened thrombotic risk profile, consistent with this prior evidence.

Furthermore, post-aspirin 11dhTxB2 levels provide insight into aspirin’s efficacy in mitigating this risk. Our threshold for biochemical aspirin resistance (≥1500 pg/mg creatinine) aligns with consensus criteria [2], and the 20.8% resistance rate in diabetic patients indicates a substantial subset with inadequate thromboxane suppression. Persistent 11dhTxB2 levels ≥1500 pg/mg creatinine post-therapy have been linked to a 2- to 4-fold increased risk of adverse cardiovascular events in prior studies [3]. For instance, McCullough et al. (2017) found that patients with stable coronary artery disease and elevated 11dhTxB2 had higher all-cause mortality (adjusted HR: 1.67, 95% CI: 1.03–2.71, P = 0.038) [4]. While our study focused on biochemical resistance rather than clinical endpoints, these findings imply that diabetic patients with post-ASA 11dhTxB2 levels ≥1500 pg/mg creatinine (approximately 20.8% of our cohort) may face elevated cardiovascular risk, warranting closer monitoring or alternative therapeutic strategies.

To enhance the risk assessment discussion in our manuscript, we have revised the “Discussion” section as follows:

"The elevated baseline urinary 11dhTxB2 levels in diabetic patients (2324.58 vs. 1452.51 pg/mg creatinine

Attachment

Submitted filename: Response to Reviewers.docx

pone.0332323.s003.docx^{(58.5KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0332323.r003

Decision Letter 1

Jeffrey J Rade

28 Jul 2025

Dear Dr. Chen,

=====

I was not the original Academic Editor for this manuscript but was assigned after three reviewers weighed in on the revised manuscript. While they are satisfied with the author's responses I strongly believe that the authors need to address several additional points, predominantly with respect to the interpretation of the data. These include:

1. The use of the phrase "factors influencing aspirin resistance" in the title suggests a causal link between the examines variables and the entity referred to as "aspirin resistance." This type of analysis cannot determine causality, it can only investigate an association between the risk variables and the outcome. I would strongly urge the authors to change the title, perhaps to "Factors associated with.." and edit the text to remove any claim of causality.

2. The term "aspirin resistance" is often used but I would ask the authors to reflect on and perhaps clarify to what it actually refers. In the broadest sense, it may mean the failure of aspirin to prevent recurrent cardiovascular events. In the narrowest sense, and the one that many experts in the field prefer, it means the failure of aspirin to inhibit platelet thromboxane generation. There is a large body of evidence to suggest that aspirin is very effective at inhibiting platelet thromboxane generation, even in diabetics, and the authors should review these studies. In that sense, "aspirin resistance" defined narrowly is rather rare. The authors use the measurement of thromboxane metabolites in the urine to assess "aspirin resistance." At the time the assay was developed, it was thought that that all thromboxane in the body was produced by platelets and therefore elevated urinary thromboxane metabolites in aspirin users reflected failure of aspirin to inhibit platelet thromboxane generation. Studies that utilized assays reflecting both platelet-specific and total body thromboxane generation using urine metabolite measurement revealed that non-platelet sources of thromboxane generation account for the overwhelming majority of total body thromboxane in compliant aspirin users, even those with diabetes. The reason is thought to be due to the fact that aspirin has a very short half-life (~20 min) and while it inhibits platelet COX-1 for the life of the platelet, nucleated cells can regenerate COX-1 in a few hours after a once daily aspirin dose, or as the authors correctly point out make TXA2 from a COX-2 pathway. The statement that " urinary 11-dehydrothromboxane B2, the primary TXA2 metabolite, directly reflects platelet-derived TXA2 production (line 88) is simply not true. Rather, urine TXA2 metabolites in aspirin non-users reflects both platelet and non-platelet thromboxane generation and in aspirin users reflects predominantly thromboxane generation from non-platelet sources. The truth is, no one really knows how much thromboxane is made from platelet versus non-platelet sources in individuals not on aspirin with systemic diseases such as diabetes. The authors should revise their language to reflect these important nuances.

3. The authors did not measure and consider oxidative stress as a variable in their analysis. While they touch on this briefly under Limitations, they should expanding this discussion of this limitation. Oxidative stress has been shown in multiple studies by several groups to be one of the strongest risk factors for thromboxane generation. For example, in a study of aspirin users with documented complete suppression of platelet TXA2 generation, our group found oxidative stress was the most important variable contributing to elevated urinary TXA2 metabolites (i.e. non-platelet TXA2 generation) that was directly associated with increased thrombosis and mortality (PMID 27068626, 29097390). Similar results were found in the largest study to date to investigate the association of urinary TXA2 metabolites and outcome (involving over 3000 Framingham participants), where oxidative stress was a stronger risk factor for elevated urinary thromboxane levels than diabetes and inflammation (PMID 35660296)

4. The authors should be aware that the 1500 pg/mg creatinine threshold for determining aspirin responsiveness was derived from the manufacturer of the assay and not based on any outcome analysis but rather on comparison to results from a first-generation assay whose threshold was determined arbitrarily (see PMID 38416712 for an outcome analysis of different thresholds for this assay).

==============================

Please submit your revised manuscript by Sep 11 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Jeffrey J. Rade, MD

Academic Editor

PLOS ONE

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If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions??>

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

Reviewer #1: I am satisfied with the content and revisions provided. The manuscript quality has significantly increased.

Reviewer #2: My concerns and comments have been acceptably addressed. The authors have clarified all methodologic procedures and provided rationale as appropriate.

Reviewer #3: All comments have been addressed by the author. The authors expanded the discussion section which may explain residual thromboxane biosynthesis despite ASA therapy. They also added a discussion on potential collinearity between metabolic-inflammatorymarkers (e.g., BMI and hs-CRP) and subgroup heterogeneity within the DM cohort, which may explain why these factors were not independent predictors in logistic regression but emerged as significant in linear regression. Minor corrections such as lack of consistent font size, lack of significance in the figures have be addressed.

**********

what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

**********

PLoS One. 2025 Sep 11;20(9):e0332323. doi: 10.1371/journal.pone.0332323.r004

Author response to Decision Letter 2

26 Aug 2025

Dear Academic Editor :

Thanks for your letter and for the reviewers’ comments concerning our manuscript entitled “Factors Influencing Aspirin Resistance in Diabetic Patients: A Metabolic and Inflammatory Profile Analysis” (ID: PONE-D-25-04526R1). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. Revised portion are marked in red in the paper. The main corrections in the paper and the responds to the reviewer’s comments are as following:

The academic editor:

1.The use of the phrase "factors influencing aspirin resistance" in the title suggests a causal link between the examines variables and the entity referred to as "aspirin resistance." This type of analysis cannot determine causality, it can only investigate an association between the risk variables and the outcome. I would strongly urge the authors to change the title, perhaps to "Factors associated with.." and edit the text to remove any claim of causality.

Response: We sincerely thank the academic editor for this crucial and insightful comment regarding the interpretation of our study findings. We fully acknowledge and agree that the observational, cross-sectional nature of our case-control design inherently limits our ability to establish “causality” between the examined metabolic-inflammatory variables and biochemical aspirin resistance. The term "influencing" in the original title could indeed imply a direct causal relationship that our data and study design cannot support. We appreciate the academic editor's constructive suggestion to use more precise language that accurately reflects the associative nature of our findings.

Revisions made:

Title Revision:The title has been changed to: "Factors associated with aspirin resistance in diabetic patients: A metabolic and inflammatory profile analysis". This revision explicitly frames the study as investigating associations.

Comprehensive Text Revision:We have conducted a thorough review of the entire manuscript (Abstract, Introduction, Discussion, and Conclusion) to identify and modify any language that might inadvertently imply causation. Key terms implying causality (e.g., "influence," "promote," "drive," "determine," "effect," "leads to," "contributes to" [when implying direct causation]) have been systematically replaced with terms explicitly denoting association or correlation (e.g., "associated with," "related to," "linked to," "correlates with," "found in," "exhibited by"). We have meticulously ensured that the conclusions drawn strictly reflect the observed “associations” within the limitations of the study design.

Emphasis on Study Design Limitation: We have reinforced statements in the Discussion and Limitations sections explicitly stating that our study design identifies associations but cannot establish causation. Specifically, the sentence "Second, the cross-sectional design precludes causal inference..." in the Limitations section now serves as a clearer anchor for this point.

We believe these revisions significantly improve the accuracy and clarity of our manuscript by precisely reflecting the associative nature of our findings, as appropriately constrained by our study design. We are grateful to the academic editor for highlighting this important aspect, which strengthens the scientific rigor of our presentation.

Response: We sincerely thank the academic editor for this exceptionally insightful and critical comment regarding the precise definition of "aspirin resistance" and the interpretation of urinary 11dhTxB2 levels, particularly in the context of non-platelet sources. We appreciate the opportunity to clarify these crucial nuances, which significantly strengthen the scientific accuracy and interpretation of our findings.

Actions Taken in Response:

Clarified Definition of Aspirin Resistance: We have explicitly defined the specific type of "aspirin resistance" investigated in our study as "biochemical aspirin resistance" throughout the manuscript (Abstract, Methods, Results, Discussion, Conclusion). We emphasize that this definition is based “solely” on persistent thromboxane biosynthesis (urinary 11dhTxB2 ≥ 1500 pg/mg creatinine post-ASA) and “does not imply clinical treatment failure” (i.e., recurrent cardiovascular events). We have added text in the Introduction and Methods sections explicitly stating this distinction and referencing the ongoing debate regarding its clinical relevance. We also acknowledge that true failure of aspirin to inhibit “platelet-specific” COX-1 is likely rare.

Revised Interpretation of Urinary 11dhTxB2: We have completely revised statements regarding the source specificity of urinary 11dhTxB2. Crucially, we have removed the claim that it "directly reflects platelet-derived TxA2 production" (original line 88). We now accurately state that urinary 11dhTxB2 reflects “total body TxA2 biosynthesis”. We explicitly acknowledge that in aspirin-treated individuals, the “majority” of urinary 11dhTxB2 likely originates from “non-platelet sources” (e.g., endothelial cells, monocytes via COX-2 or regenerated COX-1), especially given aspirin's short systemic half-life and the ability of nucleated cells to resynthesize COX. This revision is incorporated into the Introduction (where the biomarker is first described) and extensively discussed in the context of our findings.

Incorporated Discussion of Non-Platelet Sources: We have significantly expanded the Discussion section to address the critical point raised by the academic editor regarding non-platelet sources of TxA2 biosynthesis. We discuss:

The evidence that in aspirin-treated individuals (including diabetics), urinary TxA2 metabolites predominantly reflect non-platelet sources.

The potential mechanisms driving non-platelet TxA2 production in diabetes (e.g., hyperglycemia-induced COX-2 upregulation in endothelial/monocytic cells).

How this understanding contextualizes our finding of persistent 11dhTxB2 elevation post-ASA in diabetics, suggesting it may reflect “systemic (potentially COX-2 mediated) thromboxane overproduction” rather than (or in addition to) true platelet COX-1 resistance.

That the relative contribution of platelet vs. non-platelet sources to baseline (pre-ASA) urinary 11dhTxB2 in individuals with systemic diseases like diabetes remains

Nuanced Language Throughout:We have carefully revised language related to 11dhTxB2 and aspirin resistance across the entire manuscript (Abstract, Introduction, Methods, Results, Discussion) to incorporate these nuances, replacing definitive claims about platelet specificity with accurate descriptions of total body TxA2 biosynthesis and the complexity of its sources, particularly under aspirin therapy.

Re-evaluation of "Resistance" Terminology:While we retain the term "biochemical aspirin resistance" for consistency with established literature using this urinary metabolite threshold, we now explicitly frame it within its limitations: it indicates “inadequate suppression of ‘total body’ TxA2 biosynthesis” by the administered aspirin regimen, the source of which is likely predominantly extra-platelet. We discuss the potential clinical implications (association with cardiovascular risk) despite this lack of source specificity.

We are deeply grateful to the academic editor for highlighting these fundamental aspects of thromboxane biology and aspirin pharmacology. Their critique has led to substantial improvements in the accuracy, depth, and scholarly rigor of our manuscript.

3.The authors did not measure and consider oxidative stress as a variable in their analysis. While they touch on this briefly under Limitations, they should expanding this discussion of this limitation. Oxidative stress has been shown in multiple studies by several groups to be one of the strongest risk factors for thromboxane generation. For example, in a study of aspirin users with documented complete suppression of platelet TXA2 generation, our group found oxidative stress was the most important variable contributing to elevated urinary TXA2 metabolites (i.e. non-platelet TXA2 generation) that was directly associated with increased thrombosis and mortality (PMID 27068626, 29097390). Similar results were found in the largest study to date to investigate the association of urinary TXA2 metabolites and outcome (involving over 3000 Framingham participants), where oxidative stress was a stronger risk factor for elevated urinary thromboxane levels than diabetes and inflammation (PMID 35660296).

Response: We sincerely thank the academic editor for this critically important insight and for highlighting a significant limitation in our study design. We fully acknowledge that oxidative stress is a pivotal driver of thromboxane biosynthesis, particularly from non-platelet sources, and its omission as a measured variable represents a substantial gap in our analysis. We appreciate the academic editor's guidance in directing us to seminal studies, including their own foundational work and the large-scale Framingham cohort analysis, which robustly demonstrate that oxidative stress is a stronger predictor of thromboxane overproduction than traditional risk factors like diabetes or inflammation.

In response to this valuable critique, we have substantially expanded the discussion of this limitation in the manuscript. Specifically, we have:

Added detailed text in the Limitations section explicitly acknowledging oxidative stress as an unmeasured confounder and discussing its established mechanistic role in driving non-platelet thromboxane generation.

Enhanced the Discussion section to contextualize how oxidative stress pathways may underlie our observed associations between metabolic-inflammatory markers (hs-CRP, HOMA-IR) and persistent 11dhTxB2 elevation.

Cited the recommended references (PMID 27068626, 29097390, 35660296) to support these points.

Proposed specific oxidative stress biomarkers and targeted therapeutic strategies in the Future Directions section.

These revisions significantly strengthen the manuscript by providing a more comprehensive perspective on the determinants of thromboxane biosynthesis and aspirin response variability. We are deeply grateful to the academic editor for this expert guidance, which has greatly enhanced the scholarly rigor of our work.

Response: We sincerely thank the academic editor for highlighting this important methodological consideration regarding the 1500 pg/mg creatinine threshold for defining biochemical aspirin resistance. We acknowledge that this threshold was primarily derived from the manufacturer's assay validation data and lacks robust outcome-based clinical validation. As appropriately noted, recent evidence (PMID 38416712) demonstrates significant variability in outcome associations across different thresholds for this assay.

To address this limitation, we have:

Revised the Methods section (11dhTxB2 Quantification subsection) to explicitly state the origin of the threshold and its limitation regarding clinical outcome correlation.

Added the suggested reference (PMID 38416712) to support this clarification.

These revisions enhance the transparency of our methodology and appropriately contextualize the interpretation of "biochemical aspirin resistance" prevalence. We believe these changes strengthen the manuscript without altering our core findings.

We tried our best to improve the manuscript and made some changes in the manuscript. These changes will not influence the content and framework of the paper. And here we did not list the changes but marked in red in revised paper.

We appreciate for Editors’ warm work earnestly, and hope that the correction will meet with approval.

Once again, thank you very much for your comments and suggestions.

Yours sincerely

Bo Chen

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PLoS One. doi: 10.1371/journal.pone.0332323.r005

Decision Letter 2

Jeffrey J Rade

29 Aug 2025

Factors associated with aspirin resistance in diabetic patients: A metabolic and inflammatory profile analysis

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PLoS One. doi: 10.1371/journal.pone.0332323.r006

Acceptance letter

Jeffrey J Rade

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PERMALINK

Factors associated with aspirin resistance in diabetic patients: A metabolic and inflammatory profile analysis

Bo Chen

Zisheng Li

Jianyong Zhao

Huamei Dong

Long Tong

Jiaqing Dou

Roles

Abstract

Background

Methods

Results

Conclusion

Introduction

Methods

Study design and participants

Inclusion criteria.

Exclusion criteria.

Data collection.

Intervention.

11dhTxB2 quantification and ASA response assessment

Statistical methods

Results

Comparative analysis of metabolic profiles, inflammatory markers, and ASA response phenotypes

Fig 1. Urinary 11dhTxB2 levels in DM patients and healthy controls at baseline and post-ASA administration.

Table 1. Comparison of metabolic, inflammatory, and ASA resistance-related indicators between DM patients and the control group.

Fig 2. Frequency distribution of urinary 11dhTxB2 Levels in DM patients and healthy controls at baseline and Post-ASA administration.

Univariate analysis of aspirin resistance-related factors in DM patients

Table 2. Univariate analysis results of aspirin resistance-related factors in DM.

Multivariable analysis of aspirin resistance-related factors in DM patients

Table 3. Logistic regression analysis results of factors influencing ASA resistance in DM.

Evaluating baseline 11dhTxB2 levels as a predictive biomarker for aspirin resistance in DM patients

Table 4. Logistic regression analysis of baseline 11dhTxB2 association with biochemical aspirin resistance in DM.

Multiple linear regression analysis of the difference in urinary 11dhTxB2 levels before and after ASA administration in DM patients

Table 5. Results of multiple linear regression analysis of the difference in urinary 11dhTxB2 levels before and after ASA administration in DM patients.

Biochemical aspirin resistance and response variability in DM patients

Discussion

The relationship between DM patients and urinary 11dhTxB2 levels

The effect of aspirin on urinary 11dhTxB2 levels

Exploration of the mechanisms of aspirin resistance

The role of oxidative stress in thromboxane biosynthesis

The role of hs-CRP and BMI in ASA response

Heterogeneity in aspirin response among patients with diabetes

Limitations

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Santhosh Arul

Roles

Author response to Decision Letter 1

Decision Letter 1

Jeffrey J Rade

Roles

Author response to Decision Letter 2

Decision Letter 2

Jeffrey J Rade

Roles

Acceptance letter

Jeffrey J Rade

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

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