Age, rather than hypertension duration, drives coronary endothelial degradation: an in situ post-mortem analysis

Age, rather than hypertension duration, drives coronary endothelial degradation: an in situ post-mortem analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Age, rather than hypertension duration, drives coronary endothelial degradation: an in situ post-mortem analysis Oleh Samchuk, Yevhen Panasyuk, Vladyslav Bardash, Orest Zolotukhin, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9463271/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Arterial hypertension drives coronary vascular remodeling, yet disentangling the independent effects of physiological aging and chronic hemodynamic overload on the endothelium (CD31) and glycocalyx (CD138) in situ remains challenging. Most clinical studies evaluate soluble circulating markers, while direct morphological evidence of tissue-level spatial degradation is scarce. Methods This observational post-mortem study evaluated coronary artery fragments from 30 deceased patients (10 controls, 20 with essential hypertension) using immunohistochemistry and digital pathology. To mitigate confounding bias caused by age discrepancies and acute pre-mortem systemic stressors in the control group (e.g., fatal trauma), multivariable linear regression modeling with robust standard errors was applied exclusively to the hypertensive cohort to isolate the independent impacts of chronological age and hypertension duration. Results Within the hypertensive cohort, chronological age emerged as a significant independent negative predictor of CD31 expression area (β = -0.74, 95% CI: -0.98 to -0.50, p = 0.016). The duration of hypertension did not independently predict CD31 loss, showing instead a marginal, non-significant positive trend (p = 0.076) suggestive of compensatory remodeling. While the multivariable model for CD138 did not reach statistical significance, a robust positive correlation was observed between CD31 and CD138 tissue expression levels (R = 0.50, p = 0.025), indicating synchronized structural degradation. Conclusions Chronological age, rather than the chronicity of hypertension, acts as a significant independent predictor of reduced CD31 expression in the coronary arteries of hypertensive patients. The coupled expression of CD31 and CD138 underscores a tightly linked biological relationship between the structural integrity of the endothelium and its protective glycocalyx. These findings highlight the critical necessity of isolating physiological senescence from pathological remodeling in vascular research. Vascular aging Essential hypertension Endothelial glycocalyx Syndecan-1 PECAM-1 Digital pathology Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Arterial hypertension remains the leading risk factor for cardiovascular disease and related mortality worldwide [ 1 , 2 ]. A key pathogenetic link in hypertensive complications is the structural remodeling of the vasculature, particularly the coronary arteries, which eventually leads to ischemic heart disease and microvascular dysfunction [ 3 ]. The primary target for hemodynamic stress is the endothelium [ 4 ], whose functional and structural alterations represent the initial stage of vascular injury, preceding the clinical manifestations of atherosclerosis and myocardial hypertrophy [ 5 ]. A critical structure ensuring the homeostasis and mechanotransduction of endothelial cells is the endothelial glycocalyx—a complex layer of macromolecules on the luminal surface of vessels [ 6 , 7 ]. Syndecan-1 (CD138) is the primary transmembrane proteoglycan of the glycocalyx, responsible for its stability and known to degrade rapidly under chronic hemodynamic load [ 8 ]. In turn, platelet endothelial cell adhesion molecule-1 (CD31) serves as a reliable histological marker of endothelial monolayer integrity [ 9 ], with changes in its expression closely correlating with vascular remodeling and chronological aging of the arterial wall [ 10 ]. Despite the profound understanding of these processes, the existing evidence base has significant limitations [ 11 , 12 ]. Most clinical studies focus on evaluating soluble syndecan-1 in the blood as a systemic biomarker of glycocalyx degradation, while direct immunohistochemical studies of the spatial distribution of CD31 and CD138 directly in human coronary artery tissues in situ remain scarce [ 13 ]. Furthermore, morphological cohort studies encounter the complex issue of confounding bias between physiological vascular aging and the pathological impact of hypertension duration [ 14 , 15 ], which continues to hinder the determination of their independent contributions to the degradation of the endothelial barrier. Given these gaps in knowledge, the primary objective of this study was to evaluate the spatial expression patterns of CD31 and CD138 in the coronary arteries of patients with essential hypertension compared to a non-hypertensive control group. Furthermore, we aimed to apply multivariable regression modeling within the hypertensive cohort to disentangle the independent effects of chronological age and hypertension duration on endothelial dysfunction and glycocalyx degradation at the tissue level. Materials and Methods This study was designed as an observational comparative post-mortem analysis. The study material consisted of coronary artery fragments (left anterior descending, circumflex, and right coronary arteries) harvested during autopsies. The research utilized archived biological material obtained during standard pathological or forensic autopsy procedures, without any interventions on the deceased beyond the standard protocol. All personal data were strictly anonymized prior to analysis. The study was conducted in accordance with the principles of the Declaration of Helsinki and current Ukrainian legislation regarding bioethics and human tissue research. The inclusion criteria for the study were as follows: (1) age of the deceased ≥ 18 years; (2) sufficient volume and structural preservation of coronary arteries for histological and immunohistochemical analysis; (3) documented clinical history of essential hypertension (for the primary study group) or its confirmed absence (for the control group); and (4) a post-mortem interval not exceeding 48 hours. Specimens were excluded based on the following criteria: (1) presence of systemic vasculitis or diffuse connective tissue diseases; (2) clinical evidence of sepsis or systemic inflammatory response syndrome (SIRS) prior to death; (3) oncological diseases with direct cardiac or vascular involvement; and (4) pronounced signs of vascular wall autolysis. Demographic and clinical data, including sex, age, cause of death, and comorbidities, were systematically extracted from inpatient medical records and autopsy reports. Coronary artery fragments were fixed in 10% neutral buffered formalin for 24 to 48 hours. Following standard automated tissue processing, the samples were embedded in paraffin blocks. Four-micrometer-thick histological sections were prepared and subjected to routine hematoxylin and eosin (H&E) staining as well as immunohistochemistry (IHC). For the IHC analysis, the following primary antibodies were utilized: GeneAb Monoclonal Mouse Anti-Human CD138 Antibody (ref. IHC138-7) and GeneAb Monoclonal Mouse Anti-Human CD31 Antibody (ref. IHC031-7). Staining was performed strictly according to the manufacturer's protocol, with a primary antibody incubation time of 40 minutes. The histological slides were digitized using a Morpholens 1 whole-slide scanner. The resulting whole-slide images were evaluated using QuPath open-source software, version 0.6.0. The quantity of the chromogen signal in the coronary arteries was measured using a thresholding function and expressed as the area of positive staining relative to the total annotated area of the endothelium and subendothelial matrix. To differentiate specific signals from non-specific background noise, a staining intensity threshold of 0.35 was applied. The endothelial and subendothelial matrix regions were manually annotated using the "brush" tool at high magnification (50×). Additionally, a semi-quantitative assessment of arterioles within the adjacent adipose tissue was performed. A scoring system was applied based on the proportion of arterioles exhibiting circumferential chromogen accumulation that covered more than 75% of the endothelial circumference: 0 points (0% of arterioles); 1 point (1–24%); 2 points (25–49%); 3 points (50–74%); and 4 points (75–100%). Data aggregation and initial systematization were performed using Microsoft Excel 2016. Advanced statistical modeling and visualization were conducted using the R programming environment (version 4.5.3). Missing data points within the routine biochemical panel were addressed using Multiple Imputation by Chained Equations. Notably, this imputation protocol was restricted exclusively to laboratory parameters and was not applied to the primary immunohistochemical targets or morphological markers. Due to the limited sample size and non-normal distribution of the data, continuous variables were summarized as the median and interquartile range (IQR). Categorical variables were presented as absolute counts and percentages, supplemented with 95% confidence intervals (CI) calculated using the Wilson score interval method. Intergroup comparisons were performed using the non-parametric Mann-Whitney U test for continuous variables and Fisher's exact test for categorical variables. Bivariate relationships between continuous and ordinal variables were evaluated using Spearman's rank-order correlation coefficient, with trends visually represented via Locally Estimated Scatterplot Smoothing curves. To identify independent predictors of CD31 and CD138 expression areas, multiple linear regression models were constructed exclusively within the hypertensive cohort to prevent confounding bias. Comprehensive regression diagnostics were performed to ensure model validity. The absence of multicollinearity among predictors was confirmed using the Variance Inflation Factor (VIF < 2.0). The assumptions of residual normality and homoscedasticity were verified using the Shapiro-Wilk and Breusch-Pagan tests, respectively. Residual autocorrelation was assessed via the Durbin-Watson test. For models demonstrating significant autocorrelation (p < 0.05), Newey-West Heteroskedasticity and Autocorrelation Consistent robust standard errors were applied to compute adjusted 95% CIs and p values, ensuring reliable statistical inference. All statistical tests were two-sided, and a p value of < 0.05 was considered statistically significant. Results A total of 30 patients were enrolled in the study and stratified into a control group (without arterial hypertension, n = 10) and a primary study group (with essential hypertension, n = 20) (Table 1 ). The cohorts were well-matched regarding sex distribution (p = 0.682), with males comprising 80% and 70% of the control and hypertension groups, respectively. Table 1 Baseline demographic, clinical, and laboratory characteristics of the study patients. Characteristic Control (n = 10) Hypertension (n = 20) P value Demographics Age (years) 37.00 (31.00–38.00) 72.50 (67.00–76.00) < 0.001 Sex 0.682 — Female 2 (20.0%) [95% CI: 3.5–55.8] 6 (30.0%) [95% CI: 12.8–54.3] — Male 8 (80.0%) [95% CI: 44.2–96.5] 14 (70.0%) [95% CI: 45.7–87.2] Clinical parameters Hypertension stage 3 0 (0%) 20 (100%) [95% CI: 80.0–100] < 0.001 Hypertension degree < 0.001 — Grade 1 0 (0%) 2 (10.0%) [95% CI: 1.8–33.1] — Grade 2 0 (0%) 4 (20.0%) [95% CI: 6.6–44.3] — Grade 3 0 (0%) 14 (70.0%) [95% CI: 45.7–87.2] HTN duration (years) NA 15.00 (12.00–19.00) — Morphological markers CD31 Expression area in arteries (%) 8.01 (5.83–16.00) 8.95 (3.77–12.33) 0.912 CD138 Expression area in arteries (%) 2.00 (0.00–3.06) 2.28 (0.52–5.15) 0.841 Laboratory findings Hemoglobin (g/L) 85.00 (80.00–130.00) 143.50 (129.50–156.50) 0.004 Red blood cells (×10¹²/L) 2.85 (2.69–4.12) 4.75 (4.38–5.08) < 0.001 White blood cells (×10⁹/L) 14.57 (9.72–18.72) 13.96 (12.59–16.90) 0.800 Platelets (×10⁹/L) 198.00 (72.00–288.00) 290.00 (197.50–341.00) 0.078 AST (U/L) 171.00 (83.30–702.00) 47.30 (24.75–96.90) 0.013 ALT (U/L) 152.00 (32.80–1932.00) 21.80 (18.55–25.70) 0.009 Total bilirubin (µmol/L) 13.90 (7.10–66.40) 20.95 (6.90–47.60) > 0.999 Total protein (g/L) 67.85 (47.80–69.90) 69.45 (67.85–71.60) 0.120 Creatinine (µmol/L) 116.00 (61.60–213.00) 123.00 (89.90–294.00) 0.400 Urea (mmol/L) 10.05 (5.32–49.50) 10.28 (6.33–77.90) 0.600 C-reactive protein (mg/L) 11.90 (9.03–75.10) 44.05 (9.03–124.10) 0.600 Fibrinogen (g/L) 4.44 (2.88–4.44) 3.44 (2.88–4.32) 0.400 Note : Continuous variables are presented as median (interquartile range [IQR]). Categorical variables are presented as absolute counts (percentages) with 95% confidence intervals (CI) calculated using the Wilson score interval. P-values were calculated using the Mann-Whitney U test for continuous variables and Fisher's exact test for categorical variables. Significant P values (< 0.05) are highlighted in bold. HTN: Hypertension; AST: Aspartate Aminotransferase; ALT: Alanine Aminotransferase. Non-significant coagulation profile data were omitted for brevity but are available upon request. The primary distinguishing baseline characteristics between the cohorts were age and cardiovascular status. Patients in the hypertension group were significantly older (median 72.5 [IQR: 67.0–76.0] vs. 37.0 [31.0–38.0] years, p < 0.001). Within the primary study group, 100% of patients presented with stage 3 hypertension, and 70% exhibited grade 3 elevated blood pressure. The median duration of the hypertensive history in this cohort was 15.0 (12.0–19.0) years. Direct comparative analysis of the primary immunohistochemical targets did not reveal statistically significant intergroup differences at baseline (Fig. 1 ). The expression area of the endothelial marker CD31 in arteries was 8.95% (3.77–12.33%) in the hypertension group versus 8.01% (5.83–16.00%) in the control cohort (p = 0.912). Similarly, syndecan-1 (CD138) expression areas remained comparable between the groups (2.28% [0.52–5.15%] vs. 2.00% [0.00–3.06%], p = 0.841). The categorical distribution of marker expression in small arterioles also demonstrated no significant variance, underscoring the necessity of subsequent regression modeling to account for age-related confounding. A , CD31 expression area (%) in the Control and Hypertension groups. B , CD138 expression area (%) in the respective groups. Box plots display the median (thick horizontal line) and interquartile range (IQR, hinges). Whiskers extend to the most extreme data points no further than 1.5 × IQR from the hinge. Individual patient data points are overlaid to demonstrate data distribution (control, n = 10; hypertension, n = 20). Statistical comparisons were performed using the two-sided Wilcoxon rank-sum test. While the majority of routine biochemical and coagulation panels (including total protein, creatinine, urea, and fibrinogen) were comparable between the groups, specific significant differences were identified. The control group exhibited significantly elevated hepatic transaminases, with median AST at 171.0 (83.3–702.0) U/L compared to 47.3 (24.75–96.9) U/L in the hypertension group (p = 0.013), and ALT at 152.0 (32.8–1932.0) U/L versus 21.8 (18.55–25.70) U/L (p = 0.009). Additionally, the hypertension cohort demonstrated significantly higher red blood cell (RBC) counts (4.75 [4.38–5.08] vs. 2.85 [2.69–4.12] ×10¹²/L, p < 0.001) and hemoglobin levels (143.5 [129.5–156.5] vs. 85.0 [80.0–130.0] g/L, p = 0.004) compared to controls. To further investigate the pathogenetic basis of vascular remodeling at the tissue level, our quantitative analysis was supplemented with a qualitative visual assessment of the microsections. Detailed histological and immunohistochemical evaluations illustrate the specific spatial distribution patterns of CD31 and CD138 within the arterial bed across the study cohorts (Fig. 2 ). (A) A coronary artery fragment from a control group patient showing preserved CD138 expression (brown staining) along the continuous endothelium (arrow) and within the capillaries of the adjacent adipose tissue (stars). (B) A coronary artery from a hypertensive patient featuring an atherosclerotic plaque with lipid deposits and foamy macrophage infiltration (star). A significant loss of CD138 immunoreactivity is observed in the overlying endothelium (arrow), indicating structural disruption. (C) An arteriole in the adjacent adipose tissue of a hypertensive patient (arrow) exhibiting wall thickening and arteriolosclerosis, with visualized CD138 expression in the remaining endothelial layer. (D) Periphery of a fibrolipid plaque (star) in a hypertensive patient, showing a localized cluster of CD138-positive plasma cells (arrow) within the vascular wall. Immunohistochemical staining; positive signals appear brown (DAB chromogen), with hematoxylin counterstain (blue nuclei). Scale bars represent 200 µm (A, B) and 50 µm (C, D). While the comprehensive correlation matrix encompassing all clinical and laboratory parameters is accessible via the project's public repository (see Data Availability statement), our primary analysis focused on the key relationships between patient age and the expression of vascular markers within the hypertensive cohort (Fig. 3 ). Scatter plots illustrate the bivariate relationships between A , age and CD31 expression area; B , age and CD138 expression area; and C , CD31 and CD138 expression areas. Data points represent individual patients within the primary study group (n = 20). The blue curves represent Locally Estimated Scatterplot Smoothing (LOESS) trend lines to visualize underlying non-linear trajectories, surrounded by gray shading indicating 95% confidence intervals. Spearman’s rank correlation coefficients (R) and corresponding two-sided P values are embedded within each panel. Bivariate Spearman’s rank-order analysis revealed a weak-to-moderate inverse trend between age and the expression areas of both markers; however, these isolated monotonic associations did not reach statistical significance (CD31: R = -0.37, p = 0.11; CD138: R = -0.22, p = 0.36). Conversely, a robust and statistically significant positive correlation was identified between the expression levels of the endothelial marker CD31 and the glycocalyx marker CD138 (R = 0.50, p = 0.025). This synchronized expression pattern suggests a tightly coupled biological relationship between the structural degradation of the endothelium and its overlying glycocalyx during vascular remodeling. To evaluate the independent effects of clinical and demographic factors on endothelial dysfunction and glycocalyx degradation, multiple linear regression models were constructed within the hypertensive cohort (Table 2 , Fig. 4 ). Patient age and the duration of hypertension were included as independent predictors. The absence of multicollinearity was confirmed using the variance inflation factor (VIF < 2.0). Table 2 Multivariable linear regression models predicting the expression areas of morphological markers in the hypertensive cohort (n = 20). Predictor CD31 Model (Expression Area, %) CD138 Model (Expression Area, %) Beta (95% CI) P value Beta (95% CI) P value (Intercept) 53.00 (38.00 to 67.00) < 0.001 12.00 (-3.30 to 27.00) 0.120 Age (years) -0.74 (-0.98 to -0.50) 0.016 -0.17 (-0.42 to 0.07) 0.200 HTN Duration (years) 0.58 (-0.06 to 1.10) 0.076 0.21 (-0.06 to 0.48) 0.130 Model Diagnostics R² / Adjusted R² 0.298 / 0.215 0.147 / 0.047 Overall Model P value 0.049 0.300 Note : Beta represents the unstandardized regression coefficient. CI indicates the 95% confidence interval. Significant P values (< 0.05) are highlighted in bold. HTN: Hypertension. Due to identified residual autocorrelation (Durbin-Watson p = 0.0077), the 95% CIs and P values for the CD31 model were calculated using heteroskedasticity and autocorrelation consistent (HAC) robust standard errors. The CD138 model met all assumptions for ordinary least squares regression. The plots display the unstandardized regression coefficients and their corresponding 95% confidence intervals for A , the CD31 expression model, and B , the CD138 expression model. The red dashed line represents the null effect (Beta = 0). Predictors whose confidence intervals do not cross the zero line are considered statistically significant. For the CD31 model (Panel A), confidence intervals and significance were adjusted using HAC robust standard errors to account for residual autocorrelation. The predictive model for CD31 expression was statistically significant (p = 0.049), accounting for 21.5% of the variance in the marker’s expression area (Adjusted R² = 0.215). Due to the detection of residual autocorrelation during model diagnostics (Durbin-Watson p = 0.0077), Newey-West heteroskedasticity and autocorrelation consistent (HAC) robust standard errors were applied to ensure reliable inference. The analysis identified age as an independent and significant negative predictor: each one-year increase in age was associated with a 0.74% decrease in CD31 expression area (95% CI: -0.98 to -0.50, p = 0.016). The duration of hypertension exhibited a trend toward a positive association (β = 0.58) but did not reach statistical significance (p = 0.076). Conversely, the regression model for CD138 expression did not achieve overall statistical significance (p = 0.30, Adjusted R² = 0.047), despite fully meeting all linear regression assumptions (Shapiro-Wilk p = 0.36; Breusch-Pagan p = 0.56). Neither age (p = 0.20) nor hypertension duration (p = 0.13) demonstrated a significant independent effect on CD138 expression in this multivariable model. Discussion The primary objective of this study was to evaluate the spatial expression of endothelial (CD31) and glycocalyx (CD138) markers in coronary arteries and to disentangle the effects of chronological age and hypertension duration. Our central finding is that chronological age, rather than the chronicity of hypertension, emerges as a significant independent predictor of reduced CD31 expression within the hypertensive cohort. The multivariable regression analysis demonstrated a significant inverse relationship between age and CD31 expression area. This aligns closely with recent global literature emphasizing the concept of "endothelial senescence," whereby physiological aging inherently drives the progressive loss of endothelial tight junctions and adhesion molecules [ 16 – 19 ]. Several robust cohorts have recently shown that aging microvasculature exhibits impaired angiogenesis and a natural decline in CD31 density, independent of systemic blood pressure [ 20 , 21 ]. Our post-mortem tissue data corroborate these clinical observations, suggesting that the structural vulnerability of the coronary endothelium is strongly age-dependent, which likely lowers the threshold for subsequent pressure-induced damage. Secondly, while the multivariable model for CD138 did not reach statistical significance, we observed a robust positive correlation between the tissue expression levels of CD31 and CD138. This synchronized expression pattern supports the hypothesis of "coupled degradation" during vascular remodeling [ 22 , 23 ]. Current literature predominantly focuses on the acute shedding of the glycocalyx into the bloodstream, measuring soluble syndecan-1 during acute hypertensive crises or sepsis [ 24 – 26 ]. In contrast, our in situ tissue analysis reflects the chronic state of the arterial wall. The lack of an independent predictive value of hypertension duration for CD138 tissue expression may indicate that glycocalyx degradation occurs as an early, rapid event in the pathogenesis of hypertension, subsequently reaching a steady state of depletion that does not linearly progress with disease duration [ 27 , 28 ]. This highlights a crucial discrepancy between dynamic circulating biomarkers and static tissue morphology, necessitating a cautious interpretation of purely serological studies. Interestingly, our regression model revealed a marginal, albeit non-significant, trend toward a positive association between the duration of hypertension and CD31 expression (p = 0.076). Rather than indicating endothelial preservation, this trend may reflect a compensatory adaptive response of the microvasculature to chronic pathological stress [ 29 , 30 ]. Prolonged hypertension is known to induce adaptive structural remodeling, including compensatory neoangiogenesis and endothelial hyperplasia in specific vascular beds attempting to restore impaired perfusion [ 31 – 33 ]. This phenomenon underscores the complexity of interpreting cross-sectional morphological data, where severe age-related endothelial rarefaction may be partially masked by pathological, dysfunctional hyperproliferation driven by chronic hemodynamic overload [ 3 , 34 ]. The initial lack of significance in direct intergroup comparisons underscores the necessity of our multivariable approach to control for age-related confounding bias. Several limitations of this study should be acknowledged. First, the investigation is constrained by a relatively small sample size (n = 30), which is inherent to post-mortem histopathological studies utilizing archived autopsy material. Consequently, the design is primarily exploratory. While the use of robust statistical methods and 95% confidence intervals confirmed the reliability of the observed significant effects regarding age, the lack of statistical significance regarding the duration of hypertension may reflect limited statistical power rather than a true absence of biological effect. Therefore, these preliminary findings warrant further validation in larger, multicenter cohorts. Second, the substantial age discrepancy between the control and hypertensive groups precluded simple direct comparisons; however, this confounding bias was rigorously addressed by restricting the multivariable regression analysis exclusively to the hypertensive cohort. Conclusions In conclusion, this in situ immunohistochemical analysis indicates that chronological age is a significant independent predictor of reduced CD31 expression in the coronary arteries of hypertensive patients, reflecting age-related structural endothelial alterations. Furthermore, the significant correlation between CD31 and CD138 expression highlights a tightly coupled biological relationship between the structural integrity of the endothelium and its protective glycocalyx. Our findings emphasize that future investigations of vascular remodeling must critically separate the inherent effects of physiological senescence from the pathological impact of chronic hemodynamic overload. Further large-scale studies combining in situ morphological assessment with circulating biomarkers are required to fully elucidate the timeline of glycocalyx shedding and endothelial decay in essential hypertension. Abbreviations ALT Alanine Aminotransferase AST Aspartate Aminotransferase CD31 Platelet Endothelial Cell Adhesion Molecule-1 (PECAM-1) CD138 Syndecan-1 CI:Confidence Interval HAC Heteroskedasticity and Autocorrelation Consistent H&E Hematoxylin and Eosin HTN Hypertension IHC Immunohistochemistry IQR Interquartile Range Declarations Ethics approval and consent to participate The study was conducted in accordance with the principles of the Declaration of Helsinki and current Ukrainian legislation regarding bioethics and human tissue research. The research protocol, including the retrospective collection of clinical data and the use of post-mortem tissue samples, was reviewed and officially approved by the Institutional Ethics Committee of Danylo Halytsky Lviv National Medical University (Protocol Number: No. 10, Date of Approval: September 10, 2023). Since the study utilized anonymized, archived autopsy material obtained during standard pathological or forensic procedures, the requirement for direct informed consent was waived by the Ethics Committee . Clinical trial number: not applicable. Consent for publication Not applicable. Availability of data and materials The datasets generated and analyzed during the current study, along with the complete R scripts for statistical modeling and visualization, are publicly available in the GitHub repository (https://github.com/NefroStat/morphological-htn-study) and archived in Zenodo with the DOI: 10.5281/zenodo.19626466. Competing interests The authors declare that they have no competing interests. Funding The authors declare that no specific funding was received for this study. Authors' contributions VB conceptualized and designed the study, performed the statistical analysis, and drafted the manuscript. YP and OZ performed the tissue processing, histological and immunohistochemical staining, and conducted the digital pathology measurements. OS facilitated the collection of the post-mortem material and provided critical administrative and institutional support. ES and IS supervised the research project, verified the analytical methodology, and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript. Acknowledgements The authors express their gratitude to the Armed Forces of Ukraine. References Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019: Update From the GBD 2019 Study. J Am Coll Cardiol. 2020;76(25):2982–3021. 10.1016/j.jacc.2020.11.010 . Mancia G, Kreutz R, Brunström M, Burnier M, Grassi G, Januszewicz A, et al. 2023 ESH Guidelines for the management of arterial hypertension. 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The role of endothelial glycocalyx in health and disease. Clin Kidney J. 2019;12(5):611–9. 10.1093/ckj/sfz042 . Mitra R, O'Neil GL, Harding IC, Cheng MJ, Mensah SA, Ebong EE. Glycocalyx in Atherosclerosis-Relevant Endothelium Function and as a Therapeutic Target. Curr Atheroscler Rep. 2017;19(12):63. 10.1007/s11883-017-0691-9 . Iba T, Levy JH. Derangement of the endothelial glycocalyx in sepsis. J Thromb Haemost. 2019;17(2):283–94. 10.1111/jth.14371 . Liew H, Roberts MA, Pope A, McMahon LP. Endothelial glycocalyx damage in kidney disease correlates with uraemic toxins and endothelial dysfunction. BMC Nephrol. 2021;22(1):21. 10.1186/s12882-020-02219-4 . Cao RN, Tang L, Xia ZY, Xia R. Endothelial glycocalyx as a potential therapeutic target in organ injuries. Chin Med J (Engl). 2019;132(8):963–75. 10.1097/CM9.0000000000000177 . Uchimido R, Schmidt EP, Shapiro NI. The glycocalyx: a novel diagnostic and therapeutic target in sepsis. Crit Care. 2019;23(1):16. 10.1186/s13054-018-2292-6 . Foote CA, Soares RN, Ramirez-Perez FI, Ghiarone T, Aroor A, Manrique-Acevedo C, et al. Endothelial Glycocalyx Compr Physiol. 2022;12(4):3781–811. 10.1002/cphy.c210029 . Durante A, Mazzapicchi A, Baiardo Redaelli M. Systemic and Cardiac Microvascular Dysfunction in Hypertension. Int J Mol Sci. 2024;25(24):13294. 10.3390/ijms252413294 . Ma J, Li Y, Yang X, et al. Signaling pathways in vascular function and hypertension: molecular mechanisms and therapeutic interventions. Signal Transduct Target Ther. 2023;8:168. 10.1038/s41392-023-01430-7 . Rizzoni D, Mengozzi A, Masi S, Agabiti Rosei C, De Ciuceis C, Virdis A. New Noninvasive Methods to Evaluate Microvascular Structure and Function. Hypertension. 2022;79(5):874–86. 10.1161/HYPERTENSIONAHA.121.17954 . Rizzoni D, Agabiti-Rosei C, Boari GEM, Muiesan ML, De Ciuceis C. Microcirculation in Hypertension: A Therapeutic Target to Prevent Cardiovascular Disease? J Clin Med. 2023;12(15):4892. 10.3390/jcm12154892 . Martinez-Quinones P, McCarthy CG, Watts SW, Klee NS, Komic A, Calmasini FB, et al. Hypertension Induced Morphological and Physiological Changes in Cells of the Arterial Wall. Am J Hypertens. 2018;31(10):1067–78. 10.1093/ajh/hpy083 . Chandra AA, Espiche C, Maliha M, Virani SS, Blumenthal RS, Rodriguez F, et al. American society for preventive cardiology 2024 cardiovascular disease prevention: Highlights and key sessions. Am J Prev Cardiol. 2024;21:100919. 10.1016/j.ajpc.2024.100919 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 13 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviewers agreed at journal 04 May, 2026 Reviewers agreed at journal 30 Apr, 2026 Reviewers invited by journal 30 Apr, 2026 Editor invited by journal 22 Apr, 2026 Editor assigned by journal 21 Apr, 2026 Submission checks completed at journal 21 Apr, 2026 First submitted to journal 19 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9463271","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":635683463,"identity":"c0ea7455-f498-420f-a377-d489e1385a1f","order_by":0,"name":"Oleh Samchuk","email":"","orcid":"","institution":"St. Panteleimon Hospital, First Lviv Medical Union","correspondingAuthor":false,"prefix":"","firstName":"Oleh","middleName":"","lastName":"Samchuk","suffix":""},{"id":635683464,"identity":"38dc7617-71c9-43be-bd12-ed57b18a8df6","order_by":1,"name":"Yevhen Panasyuk","email":"","orcid":"","institution":"St. Panteleimon Hospital, First Lviv Medical Union","correspondingAuthor":false,"prefix":"","firstName":"Yevhen","middleName":"","lastName":"Panasyuk","suffix":""},{"id":635683465,"identity":"9ccbcf0c-8372-4bad-8367-6e1b2a44eca7","order_by":2,"name":"Vladyslav Bardash","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYFACHiBmY2AwYG9sALIsQGxitfAcBumRIEWLRDpEC0FgcID34OeKMjt7c8mH7Y9uVEgk9kkkMH74mINPC1+y5JlzyYk7Zyc2NueckUhsk0hglpy5DbcWyQYeA8nGNuYEg9tALbltEsZsPAfYmHnxazH+2dhWb29w8yCRWvgZeMyAthxm3HCDEaxFjo29gYAWZr40y4ZzxxM3nElsnA30C1BLYzNev7Cx9x6+2VBWbW9w/PiDzzkVNjzyzcwHP3zEo4WBGVOIsQGP+lEwCkbBKBgFxAAAzi5LcjdESSQAAAAASUVORK5CYII=","orcid":"","institution":"St. Panteleimon Hospital, First Lviv Medical Union","correspondingAuthor":true,"prefix":"","firstName":"Vladyslav","middleName":"","lastName":"Bardash","suffix":""},{"id":635683466,"identity":"a43508c9-e68f-49d4-8565-117d68fafe4d","order_by":3,"name":"Orest Zolotukhin","email":"","orcid":"","institution":"St. Panteleimon Hospital, First Lviv Medical Union","correspondingAuthor":false,"prefix":"","firstName":"Orest","middleName":"","lastName":"Zolotukhin","suffix":""},{"id":635683467,"identity":"ac165568-b286-4dd4-b178-8c182d8f3132","order_by":4,"name":"Eugen Sklyarov","email":"","orcid":"","institution":"Danylo Halytsky Lviv National Medical University","correspondingAuthor":false,"prefix":"","firstName":"Eugen","middleName":"","lastName":"Sklyarov","suffix":""},{"id":635683470,"identity":"5f6d6af3-f4d1-4dc9-8918-0077fdf5962f","order_by":5,"name":"Igor Skrypnyk","email":"","orcid":"","institution":"Poltava State Medical University","correspondingAuthor":false,"prefix":"","firstName":"Igor","middleName":"","lastName":"Skrypnyk","suffix":""}],"badges":[],"createdAt":"2026-04-19 15:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9463271/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9463271/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108968615,"identity":"035486fa-69c6-46cf-965d-40cf65d446fe","added_by":"auto","created_at":"2026-05-11 10:03:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":88460,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eExpression of morphological markers in arterial vessels.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e, CD31 expression area (%) in the Control and Hypertension groups. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e, CD138 expression area (%) in the respective groups. Box plots display the median (thick horizontal line) and interquartile range (IQR, hinges). Whiskers extend to the most extreme data points no further than 1.5 × IQR from the hinge. Individual patient data points are overlaid to demonstrate data distribution (control, n = 10; hypertension, n = 20). Statistical comparisons were performed using the two-sided Wilcoxon rank-sum test.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9463271/v1/ed67256a2a16aa33c233d941.png"},{"id":108968614,"identity":"5ea7331f-9f35-4265-9080-61818813aae4","added_by":"auto","created_at":"2026-05-11 10:03:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":787848,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSpatial distribution of syndecan-1 (CD138) in the coronary artery wall and adjacent microvasculature.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003e(A)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e A coronary artery fragment from a control group patient showing preserved CD138 expression (brown staining) along the continuous endothelium (arrow) and within the capillaries of the adjacent adipose tissue (stars). \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(B)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e A coronary artery from a hypertensive patient featuring an atherosclerotic plaque with lipid deposits and foamy macrophage infiltration (star). A significant loss of CD138 immunoreactivity is observed in the overlying endothelium (arrow), indicating structural disruption. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(C)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e An arteriole in the adjacent adipose tissue of a hypertensive patient (arrow) exhibiting wall thickening and arteriolosclerosis, with visualized CD138 expression in the remaining endothelial layer. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(D)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003ePeriphery of a fibrolipid plaque (star) in a hypertensive patient, showing a localized cluster of CD138-positive plasma cells (arrow) within the vascular wall.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eImmunohistochemical staining; positive signals appear brown (DAB chromogen), with hematoxylin counterstain (blue nuclei). Scale bars represent 200 μm (A, B) and 50 μm (C, D).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9463271/v1/b4be6c1d889ccabff231dacd.jpg"},{"id":108978327,"identity":"b48139ae-edff-4daf-92da-4e7d008cdbba","added_by":"auto","created_at":"2026-05-11 11:36:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":104308,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSpearman correlation analysis of age and morphological markers in the hypertensive cohort.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eScatter plots illustrate the bivariate relationships between \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e, age and CD31 expression area; \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e, age and CD138 expression area; and \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e, CD31 and CD138 expression areas. Data points represent individual patients within the primary study group (n = 20). The blue curves represent Locally Estimated Scatterplot Smoothing (LOESS) trend lines to visualize underlying non-linear trajectories, surrounded by gray shading indicating 95% confidence intervals. Spearman’s rank correlation coefficients (R) and corresponding two-sided P values are embedded within each panel.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9463271/v1/ada1b0482bbe3b9dfd8fa55b.png"},{"id":108978237,"identity":"45e18fb3-71a1-46ca-b07d-11fc203e713a","added_by":"auto","created_at":"2026-05-11 11:35:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":42874,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eForest plots of multivariable linear regression models evaluating predictors of endothelial and glycocalyx markers.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe plots display the unstandardized regression coefficients and their corresponding 95% confidence intervals for \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e, the CD31 expression model, and \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e, the CD138 expression model. The red dashed line represents the null effect (Beta = 0). Predictors whose confidence intervals do not cross the zero line are considered statistically significant. For the CD31 model (Panel A), confidence intervals and significance were adjusted using HAC robust standard errors to account for residual autocorrelation.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9463271/v1/e7fc97b46b24cbbe3ebc31af.png"},{"id":108979985,"identity":"42069a8c-46ef-4d35-8ce1-d0acebe632ca","added_by":"auto","created_at":"2026-05-11 12:02:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1330815,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9463271/v1/ecda3d64-b4e8-400e-bbc9-0039276aac9b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Age, rather than hypertension duration, drives coronary endothelial degradation: an in situ post-mortem analysis","fulltext":[{"header":"Background","content":"\u003cp\u003eArterial hypertension remains the leading risk factor for cardiovascular disease and related mortality worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A key pathogenetic link in hypertensive complications is the structural remodeling of the vasculature, particularly the coronary arteries, which eventually leads to ischemic heart disease and microvascular dysfunction [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The primary target for hemodynamic stress is the endothelium [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], whose functional and structural alterations represent the initial stage of vascular injury, preceding the clinical manifestations of atherosclerosis and myocardial hypertrophy [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA critical structure ensuring the homeostasis and mechanotransduction of endothelial cells is the endothelial glycocalyx\u0026mdash;a complex layer of macromolecules on the luminal surface of vessels [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Syndecan-1 (CD138) is the primary transmembrane proteoglycan of the glycocalyx, responsible for its stability and known to degrade rapidly under chronic hemodynamic load [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In turn, platelet endothelial cell adhesion molecule-1 (CD31) serves as a reliable histological marker of endothelial monolayer integrity [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], with changes in its expression closely correlating with vascular remodeling and chronological aging of the arterial wall [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the profound understanding of these processes, the existing evidence base has significant limitations [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Most clinical studies focus on evaluating soluble syndecan-1 in the blood as a systemic biomarker of glycocalyx degradation, while direct immunohistochemical studies of the spatial distribution of CD31 and CD138 directly in human coronary artery tissues \u003cem\u003ein situ\u003c/em\u003e remain scarce [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Furthermore, morphological cohort studies encounter the complex issue of confounding bias between physiological vascular aging and the pathological impact of hypertension duration [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], which continues to hinder the determination of their independent contributions to the degradation of the endothelial barrier.\u003c/p\u003e \u003cp\u003eGiven these gaps in knowledge, the primary objective of this study was to evaluate the spatial expression patterns of CD31 and CD138 in the coronary arteries of patients with essential hypertension compared to a non-hypertensive control group. Furthermore, we aimed to apply multivariable regression modeling within the hypertensive cohort to disentangle the independent effects of chronological age and hypertension duration on endothelial dysfunction and glycocalyx degradation at the tissue level.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis study was designed as an observational comparative post-mortem analysis. The study material consisted of coronary artery fragments (left anterior descending, circumflex, and right coronary arteries) harvested during autopsies. The research utilized archived biological material obtained during standard pathological or forensic autopsy procedures, without any interventions on the deceased beyond the standard protocol. All personal data were strictly anonymized prior to analysis. The study was conducted in accordance with the principles of the Declaration of Helsinki and current Ukrainian legislation regarding bioethics and human tissue research.\u003c/p\u003e \u003cp\u003eThe inclusion criteria for the study were as follows: (1) age of the deceased\u0026thinsp;\u0026ge;\u0026thinsp;18 years; (2) sufficient volume and structural preservation of coronary arteries for histological and immunohistochemical analysis; (3) documented clinical history of essential hypertension (for the primary study group) or its confirmed absence (for the control group); and (4) a post-mortem interval not exceeding 48 hours.\u003c/p\u003e \u003cp\u003eSpecimens were excluded based on the following criteria: (1) presence of systemic vasculitis or diffuse connective tissue diseases; (2) clinical evidence of sepsis or systemic inflammatory response syndrome (SIRS) prior to death; (3) oncological diseases with direct cardiac or vascular involvement; and (4) pronounced signs of vascular wall autolysis.\u003c/p\u003e \u003cp\u003eDemographic and clinical data, including sex, age, cause of death, and comorbidities, were systematically extracted from inpatient medical records and autopsy reports.\u003c/p\u003e \u003cp\u003eCoronary artery fragments were fixed in 10% neutral buffered formalin for 24 to 48 hours. Following standard automated tissue processing, the samples were embedded in paraffin blocks. Four-micrometer-thick histological sections were prepared and subjected to routine hematoxylin and eosin (H\u0026amp;E) staining as well as immunohistochemistry (IHC). For the IHC analysis, the following primary antibodies were utilized: GeneAb Monoclonal Mouse Anti-Human CD138 Antibody (ref. IHC138-7) and GeneAb Monoclonal Mouse Anti-Human CD31 Antibody (ref. IHC031-7). Staining was performed strictly according to the manufacturer's protocol, with a primary antibody incubation time of 40 minutes.\u003c/p\u003e \u003cp\u003eThe histological slides were digitized using a Morpholens 1 whole-slide scanner. The resulting whole-slide images were evaluated using QuPath open-source software, version 0.6.0. The quantity of the chromogen signal in the coronary arteries was measured using a thresholding function and expressed as the area of positive staining relative to the total annotated area of the endothelium and subendothelial matrix. To differentiate specific signals from non-specific background noise, a staining intensity threshold of 0.35 was applied. The endothelial and subendothelial matrix regions were manually annotated using the \"brush\" tool at high magnification (50\u0026times;).\u003c/p\u003e \u003cp\u003eAdditionally, a semi-quantitative assessment of arterioles within the adjacent adipose tissue was performed. A scoring system was applied based on the proportion of arterioles exhibiting circumferential chromogen accumulation that covered more than 75% of the endothelial circumference: 0 points (0% of arterioles); 1 point (1\u0026ndash;24%); 2 points (25\u0026ndash;49%); 3 points (50\u0026ndash;74%); and 4 points (75\u0026ndash;100%).\u003c/p\u003e \u003cp\u003eData aggregation and initial systematization were performed using Microsoft Excel 2016. Advanced statistical modeling and visualization were conducted using the R programming environment (version 4.5.3). Missing data points within the routine biochemical panel were addressed using Multiple Imputation by Chained Equations. Notably, this imputation protocol was restricted exclusively to laboratory parameters and was not applied to the primary immunohistochemical targets or morphological markers.\u003c/p\u003e \u003cp\u003eDue to the limited sample size and non-normal distribution of the data, continuous variables were summarized as the median and interquartile range (IQR). Categorical variables were presented as absolute counts and percentages, supplemented with 95% confidence intervals (CI) calculated using the Wilson score interval method. Intergroup comparisons were performed using the non-parametric Mann-Whitney U test for continuous variables and Fisher's exact test for categorical variables.\u003c/p\u003e \u003cp\u003eBivariate relationships between continuous and ordinal variables were evaluated using Spearman's rank-order correlation coefficient, with trends visually represented via Locally Estimated Scatterplot Smoothing curves. To identify independent predictors of CD31 and CD138 expression areas, multiple linear regression models were constructed exclusively within the hypertensive cohort to prevent confounding bias.\u003c/p\u003e \u003cp\u003eComprehensive regression diagnostics were performed to ensure model validity. The absence of multicollinearity among predictors was confirmed using the Variance Inflation Factor (VIF\u0026thinsp;\u0026lt;\u0026thinsp;2.0). The assumptions of residual normality and homoscedasticity were verified using the Shapiro-Wilk and Breusch-Pagan tests, respectively. Residual autocorrelation was assessed via the Durbin-Watson test. For models demonstrating significant autocorrelation (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), Newey-West Heteroskedasticity and Autocorrelation Consistent robust standard errors were applied to compute adjusted 95% CIs and \u003cem\u003ep\u003c/em\u003e values, ensuring reliable statistical inference. All statistical tests were two-sided, and a \u003cem\u003ep\u003c/em\u003e value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 30 patients were enrolled in the study and stratified into a control group (without arterial hypertension, n\u0026thinsp;=\u0026thinsp;10) and a primary study group (with essential hypertension, n\u0026thinsp;=\u0026thinsp;20) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The cohorts were well-matched regarding sex distribution (p\u0026thinsp;=\u0026thinsp;0.682), with males comprising 80% and 70% of the control and hypertension groups, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline demographic, clinical, and laboratory characteristics of the study patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHypertension (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.00 (31.00\u0026ndash;38.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.50 (67.00\u0026ndash;76.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026mdash; Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (20.0%) [95% CI: 3.5\u0026ndash;55.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (30.0%) [95% CI: 12.8\u0026ndash;54.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026mdash; Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (80.0%) [95% CI: 44.2\u0026ndash;96.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (70.0%) [95% CI: 45.7\u0026ndash;87.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical parameters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension stage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (100%) [95% CI: 80.0\u0026ndash;100]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026mdash; Grade 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (10.0%) [95% CI: 1.8\u0026ndash;33.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026mdash; Grade 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (20.0%) [95% CI: 6.6\u0026ndash;44.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026mdash; Grade 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (70.0%) [95% CI: 45.7\u0026ndash;87.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHTN duration (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.00 (12.00\u0026ndash;19.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMorphological markers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD31 Expression area in arteries (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.01 (5.83\u0026ndash;16.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.95 (3.77\u0026ndash;12.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD138 Expression area in arteries (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.00 (0.00\u0026ndash;3.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.28 (0.52\u0026ndash;5.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory findings\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85.00 (80.00\u0026ndash;130.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143.50 (129.50\u0026ndash;156.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed blood cells (\u0026times;10\u0026sup1;\u0026sup2;/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.85 (2.69\u0026ndash;4.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.75 (4.38\u0026ndash;5.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cells (\u0026times;10⁹/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.57 (9.72\u0026ndash;18.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.96 (12.59\u0026ndash;16.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelets (\u0026times;10⁹/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e198.00 (72.00\u0026ndash;288.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e290.00 (197.50\u0026ndash;341.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171.00 (83.30\u0026ndash;702.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.30 (24.75\u0026ndash;96.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e152.00 (32.80\u0026ndash;1932.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.80 (18.55\u0026ndash;25.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bilirubin (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.90 (7.10\u0026ndash;66.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.95 (6.90\u0026ndash;47.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal protein (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.85 (47.80\u0026ndash;69.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.45 (67.85\u0026ndash;71.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116.00 (61.60\u0026ndash;213.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123.00 (89.90\u0026ndash;294.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.05 (5.32\u0026ndash;49.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.28 (6.33\u0026ndash;77.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-reactive protein (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.90 (9.03\u0026ndash;75.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.05 (9.03\u0026ndash;124.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibrinogen (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.44 (2.88\u0026ndash;4.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.44 (2.88\u0026ndash;4.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eNote\u003c/b\u003e: \u003cem\u003eContinuous variables are presented as median (interquartile range [IQR]). Categorical variables are presented as absolute counts (percentages) with 95% confidence intervals (CI) calculated using the Wilson score interval. P-values were calculated using the Mann-Whitney U test for continuous variables and Fisher's exact test for categorical variables. Significant P values (\u0026lt;\u0026thinsp;0.05) are highlighted in bold. HTN: Hypertension; AST: Aspartate Aminotransferase; ALT: Alanine Aminotransferase. Non-significant coagulation profile data were omitted for brevity but are available upon request.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe primary distinguishing baseline characteristics between the cohorts were age and cardiovascular status. Patients in the hypertension group were significantly older (median 72.5 [IQR: 67.0\u0026ndash;76.0] vs. 37.0 [31.0\u0026ndash;38.0] years, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Within the primary study group, 100% of patients presented with stage 3 hypertension, and 70% exhibited grade 3 elevated blood pressure. The median duration of the hypertensive history in this cohort was 15.0 (12.0\u0026ndash;19.0) years.\u003c/p\u003e \u003cp\u003eDirect comparative analysis of the primary immunohistochemical targets did not reveal statistically significant intergroup differences at baseline (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The expression area of the endothelial marker CD31 in arteries was 8.95% (3.77\u0026ndash;12.33%) in the hypertension group versus 8.01% (5.83\u0026ndash;16.00%) in the control cohort (p\u0026thinsp;=\u0026thinsp;0.912). Similarly, syndecan-1 (CD138) expression areas remained comparable between the groups (2.28% [0.52\u0026ndash;5.15%] vs. 2.00% [0.00\u0026ndash;3.06%], p\u0026thinsp;=\u0026thinsp;0.841). The categorical distribution of marker expression in small arterioles also demonstrated no significant variance, underscoring the necessity of subsequent regression modeling to account for age-related confounding.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eA\u003c/b\u003e, \u003cem\u003eCD31 expression area (%) in the Control and Hypertension groups.\u003c/em\u003e \u003cb\u003eB\u003c/b\u003e, \u003cem\u003eCD138 expression area (%) in the respective groups. Box plots display the median (thick horizontal line) and interquartile range (IQR, hinges). Whiskers extend to the most extreme data points no further than 1.5 \u0026times; IQR from the hinge. Individual patient data points are overlaid to demonstrate data distribution (control, n\u0026thinsp;=\u0026thinsp;10; hypertension, n\u0026thinsp;=\u0026thinsp;20). Statistical comparisons were performed using the two-sided Wilcoxon rank-sum test.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eWhile the majority of routine biochemical and coagulation panels (including total protein, creatinine, urea, and fibrinogen) were comparable between the groups, specific significant differences were identified. The control group exhibited significantly elevated hepatic transaminases, with median AST at 171.0 (83.3\u0026ndash;702.0) U/L compared to 47.3 (24.75\u0026ndash;96.9) U/L in the hypertension group (p\u0026thinsp;=\u0026thinsp;0.013), and ALT at 152.0 (32.8\u0026ndash;1932.0) U/L versus 21.8 (18.55\u0026ndash;25.70) U/L (p\u0026thinsp;=\u0026thinsp;0.009). Additionally, the hypertension cohort demonstrated significantly higher red blood cell (RBC) counts (4.75 [4.38\u0026ndash;5.08] vs. 2.85 [2.69\u0026ndash;4.12] \u0026times;10\u0026sup1;\u0026sup2;/L, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and hemoglobin levels (143.5 [129.5\u0026ndash;156.5] vs. 85.0 [80.0\u0026ndash;130.0] g/L, p\u0026thinsp;=\u0026thinsp;0.004) compared to controls.\u003c/p\u003e \u003cp\u003eTo further investigate the pathogenetic basis of vascular remodeling at the tissue level, our quantitative analysis was supplemented with a qualitative visual assessment of the microsections. Detailed histological and immunohistochemical evaluations illustrate the specific spatial distribution patterns of CD31 and CD138 within the arterial bed across the study cohorts (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e(A)\u003c/b\u003e \u003cem\u003eA coronary artery fragment from a control group patient showing preserved CD138 expression (brown staining) along the continuous endothelium (arrow) and within the capillaries of the adjacent adipose tissue (stars).\u003c/em\u003e \u003cb\u003e(B)\u003c/b\u003e \u003cem\u003eA coronary artery from a hypertensive patient featuring an atherosclerotic plaque with lipid deposits and foamy macrophage infiltration (star). A significant loss of CD138 immunoreactivity is observed in the overlying endothelium (arrow), indicating structural disruption.\u003c/em\u003e \u003cb\u003e(C)\u003c/b\u003e \u003cem\u003eAn arteriole in the adjacent adipose tissue of a hypertensive patient (arrow) exhibiting wall thickening and arteriolosclerosis, with visualized CD138 expression in the remaining endothelial layer.\u003c/em\u003e \u003cb\u003e(D)\u003c/b\u003e \u003cem\u003ePeriphery of a fibrolipid plaque (star) in a hypertensive patient, showing a localized cluster of CD138-positive plasma cells (arrow) within the vascular wall.\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eImmunohistochemical staining; positive signals appear brown (DAB chromogen), with hematoxylin counterstain (blue nuclei). Scale bars represent 200 \u0026micro;m (A, B) and 50 \u0026micro;m (C, D).\u003c/em\u003e \u003c/p\u003e \u003cp\u003eWhile the comprehensive correlation matrix encompassing all clinical and laboratory parameters is accessible via the project's public repository (see Data Availability statement), our primary analysis focused on the key relationships between patient age and the expression of vascular markers within the hypertensive cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eScatter plots illustrate the bivariate relationships between\u003c/em\u003e \u003cb\u003eA\u003c/b\u003e, \u003cem\u003eage and CD31 expression area;\u003c/em\u003e \u003cb\u003eB\u003c/b\u003e, \u003cem\u003eage and CD138 expression area; and\u003c/em\u003e \u003cb\u003eC\u003c/b\u003e, \u003cem\u003eCD31 and CD138 expression areas. Data points represent individual patients within the primary study group (n\u0026thinsp;=\u0026thinsp;20). The blue curves represent Locally Estimated Scatterplot Smoothing (LOESS) trend lines to visualize underlying non-linear trajectories, surrounded by gray shading indicating 95% confidence intervals. Spearman\u0026rsquo;s rank correlation coefficients (R) and corresponding two-sided P values are embedded within each panel.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eBivariate Spearman\u0026rsquo;s rank-order analysis revealed a weak-to-moderate inverse trend between age and the expression areas of both markers; however, these isolated monotonic associations did not reach statistical significance (CD31: R = -0.37, p\u0026thinsp;=\u0026thinsp;0.11; CD138: R = -0.22, p\u0026thinsp;=\u0026thinsp;0.36). Conversely, a robust and statistically significant positive correlation was identified between the expression levels of the endothelial marker CD31 and the glycocalyx marker CD138 (R\u0026thinsp;=\u0026thinsp;0.50, p\u0026thinsp;=\u0026thinsp;0.025). This synchronized expression pattern suggests a tightly coupled biological relationship between the structural degradation of the endothelium and its overlying glycocalyx during vascular remodeling.\u003c/p\u003e \u003cp\u003eTo evaluate the independent effects of clinical and demographic factors on endothelial dysfunction and glycocalyx degradation, multiple linear regression models were constructed within the hypertensive cohort (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Patient age and the duration of hypertension were included as independent predictors. The absence of multicollinearity was confirmed using the variance inflation factor (VIF\u0026thinsp;\u0026lt;\u0026thinsp;2.0).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable linear regression models predicting the expression areas of morphological markers in the hypertensive cohort (n\u0026thinsp;=\u0026thinsp;20).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCD31 Model (Expression Area, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCD138 Model (Expression Area, %)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBeta (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Intercept)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.00 (38.00 to 67.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.00 (-3.30 to 27.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.74 (-0.98 to -0.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.17 (-0.42 to 0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHTN Duration (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.58 (-0.06 to 1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21 (-0.06 to 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel Diagnostics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u0026sup2; / Adjusted R\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.298 / 0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.147 / 0.047\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall Model P value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eNote\u003c/b\u003e: \u003cem\u003eBeta represents the unstandardized regression coefficient. CI indicates the 95% confidence interval. Significant P values (\u0026lt;\u0026thinsp;0.05) are highlighted in bold. HTN: Hypertension. Due to identified residual autocorrelation (Durbin-Watson p\u0026thinsp;=\u0026thinsp;0.0077), the 95% CIs and P values for the CD31 model were calculated using heteroskedasticity and autocorrelation consistent (HAC) robust standard errors. The CD138 model met all assumptions for ordinary least squares regression.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eThe plots display the unstandardized regression coefficients and their corresponding 95% confidence intervals for\u003c/em\u003e \u003cb\u003eA\u003c/b\u003e, \u003cem\u003ethe CD31 expression model, and\u003c/em\u003e \u003cb\u003eB\u003c/b\u003e, \u003cem\u003ethe CD138 expression model. The red dashed line represents the null effect (Beta\u0026thinsp;=\u0026thinsp;0). Predictors whose confidence intervals do not cross the zero line are considered statistically significant. For the CD31 model (Panel A), confidence intervals and significance were adjusted using HAC robust standard errors to account for residual autocorrelation.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eThe predictive model for CD31 expression was statistically significant (p\u0026thinsp;=\u0026thinsp;0.049), accounting for 21.5% of the variance in the marker\u0026rsquo;s expression area (Adjusted R\u0026sup2; = 0.215). Due to the detection of residual autocorrelation during model diagnostics (Durbin-Watson p\u0026thinsp;=\u0026thinsp;0.0077), Newey-West heteroskedasticity and autocorrelation consistent (HAC) robust standard errors were applied to ensure reliable inference. The analysis identified age as an independent and significant negative predictor: each one-year increase in age was associated with a 0.74% decrease in CD31 expression area (95% CI: -0.98 to -0.50, p\u0026thinsp;=\u0026thinsp;0.016). The duration of hypertension exhibited a trend toward a positive association (β\u0026thinsp;=\u0026thinsp;0.58) but did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.076).\u003c/p\u003e \u003cp\u003eConversely, the regression model for CD138 expression did not achieve overall statistical significance (p\u0026thinsp;=\u0026thinsp;0.30, Adjusted R\u0026sup2; = 0.047), despite fully meeting all linear regression assumptions (Shapiro-Wilk p\u0026thinsp;=\u0026thinsp;0.36; Breusch-Pagan p\u0026thinsp;=\u0026thinsp;0.56). Neither age (p\u0026thinsp;=\u0026thinsp;0.20) nor hypertension duration (p\u0026thinsp;=\u0026thinsp;0.13) demonstrated a significant independent effect on CD138 expression in this multivariable model.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe primary objective of this study was to evaluate the spatial expression of endothelial (CD31) and glycocalyx (CD138) markers in coronary arteries and to disentangle the effects of chronological age and hypertension duration. Our central finding is that chronological age, rather than the chronicity of hypertension, emerges as a significant independent predictor of reduced CD31 expression within the hypertensive cohort. The multivariable regression analysis demonstrated a significant inverse relationship between age and CD31 expression area. This aligns closely with recent global literature emphasizing the concept of \"endothelial senescence,\" whereby physiological aging inherently drives the progressive loss of endothelial tight junctions and adhesion molecules [\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Several robust cohorts have recently shown that aging microvasculature exhibits impaired angiogenesis and a natural decline in CD31 density, independent of systemic blood pressure [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Our post-mortem tissue data corroborate these clinical observations, suggesting that the structural vulnerability of the coronary endothelium is strongly age-dependent, which likely lowers the threshold for subsequent pressure-induced damage.\u003c/p\u003e \u003cp\u003eSecondly, while the multivariable model for CD138 did not reach statistical significance, we observed a robust positive correlation between the tissue expression levels of CD31 and CD138. This synchronized expression pattern supports the hypothesis of \"coupled degradation\" during vascular remodeling [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Current literature predominantly focuses on the acute shedding of the glycocalyx into the bloodstream, measuring soluble syndecan-1 during acute hypertensive crises or sepsis [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In contrast, our \u003cem\u003ein situ\u003c/em\u003e tissue analysis reflects the chronic state of the arterial wall. The lack of an independent predictive value of hypertension duration for CD138 tissue expression may indicate that glycocalyx degradation occurs as an early, rapid event in the pathogenesis of hypertension, subsequently reaching a steady state of depletion that does not linearly progress with disease duration [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This highlights a crucial discrepancy between dynamic circulating biomarkers and static tissue morphology, necessitating a cautious interpretation of purely serological studies.\u003c/p\u003e \u003cp\u003eInterestingly, our regression model revealed a marginal, albeit non-significant, trend toward a positive association between the duration of hypertension and CD31 expression (p\u0026thinsp;=\u0026thinsp;0.076). Rather than indicating endothelial preservation, this trend may reflect a compensatory adaptive response of the microvasculature to chronic pathological stress [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Prolonged hypertension is known to induce adaptive structural remodeling, including compensatory neoangiogenesis and endothelial hyperplasia in specific vascular beds attempting to restore impaired perfusion [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This phenomenon underscores the complexity of interpreting cross-sectional morphological data, where severe age-related endothelial rarefaction may be partially masked by pathological, dysfunctional hyperproliferation driven by chronic hemodynamic overload [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The initial lack of significance in direct intergroup comparisons underscores the necessity of our multivariable approach to control for age-related confounding bias.\u003c/p\u003e \u003cp\u003eSeveral limitations of this study should be acknowledged. First, the investigation is constrained by a relatively small sample size (n\u0026thinsp;=\u0026thinsp;30), which is inherent to post-mortem histopathological studies utilizing archived autopsy material. Consequently, the design is primarily exploratory. While the use of robust statistical methods and 95% confidence intervals confirmed the reliability of the observed significant effects regarding age, the lack of statistical significance regarding the duration of hypertension may reflect limited statistical power rather than a true absence of biological effect. Therefore, these preliminary findings warrant further validation in larger, multicenter cohorts. Second, the substantial age discrepancy between the control and hypertensive groups precluded simple direct comparisons; however, this confounding bias was rigorously addressed by restricting the multivariable regression analysis exclusively to the hypertensive cohort.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, this \u003cem\u003ein situ\u003c/em\u003e immunohistochemical analysis indicates that chronological age is a significant independent predictor of reduced CD31 expression in the coronary arteries of hypertensive patients, reflecting age-related structural endothelial alterations. Furthermore, the significant correlation between CD31 and CD138 expression highlights a tightly coupled biological relationship between the structural integrity of the endothelium and its protective glycocalyx. Our findings emphasize that future investigations of vascular remodeling must critically separate the inherent effects of physiological senescence from the pathological impact of chronic hemodynamic overload. Further large-scale studies combining \u003cem\u003ein situ\u003c/em\u003e morphological assessment with circulating biomarkers are required to fully elucidate the timeline of glycocalyx shedding and endothelial decay in essential hypertension.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlanine Aminotransferase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAST\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAspartate Aminotransferase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCD31\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePlatelet Endothelial Cell Adhesion Molecule-1 (PECAM-1)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCD138\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSyndecan-1 CI:Confidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHAC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeteroskedasticity and Autocorrelation Consistent\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eH\u0026amp;E\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHematoxylin and Eosin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHTN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eImmunohistochemistry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile Range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the principles of the Declaration of Helsinki and current Ukrainian legislation regarding bioethics and human tissue research. The research protocol, including the retrospective collection of clinical data and the use of post-mortem tissue samples, was reviewed and officially approved by the Institutional Ethics Committee of Danylo Halytsky Lviv National Medical University (Protocol Number: No. 10, Date of Approval: September 10, 2023). Since the study utilized anonymized, archived autopsy material obtained during standard pathological or forensic procedures, the requirement for direct informed consent was waived by the Ethics Committee\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u0026nbsp;\u003c/strong\u003enot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study, along with the complete R scripts for statistical modeling and visualization, are publicly available in the GitHub repository (https://github.com/NefroStat/morphological-htn-study) and archived in Zenodo with the DOI: 10.5281/zenodo.19626466.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that no specific funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVB conceptualized and designed the study, performed the statistical analysis, and drafted the manuscript. YP and OZ performed the tissue processing, histological and immunohistochemical staining, and conducted the digital pathology measurements. OS facilitated the collection of the post-mortem material and provided critical administrative and institutional support. ES and IS supervised the research project, verified the analytical methodology, and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors express their gratitude to the Armed Forces of Ukraine.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRoth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990\u0026ndash;2019: Update From the GBD 2019 Study. 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Am J Prev Cardiol. 2024;21:100919. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ajpc.2024.100919\u003c/span\u003e\u003cspan address=\"10.1016/j.ajpc.2024.100919\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Vascular aging, Essential hypertension, Endothelial glycocalyx, Syndecan-1, PECAM-1, Digital pathology","lastPublishedDoi":"10.21203/rs.3.rs-9463271/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9463271/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eArterial hypertension drives coronary vascular remodeling, yet disentangling the independent effects of physiological aging and chronic hemodynamic overload on the endothelium (CD31) and glycocalyx (CD138) \u003cem\u003ein situ\u003c/em\u003e remains challenging. Most clinical studies evaluate soluble circulating markers, while direct morphological evidence of tissue-level spatial degradation is scarce.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis observational post-mortem study evaluated coronary artery fragments from 30 deceased patients (10 controls, 20 with essential hypertension) using immunohistochemistry and digital pathology. To mitigate confounding bias caused by age discrepancies and acute pre-mortem systemic stressors in the control group (e.g., fatal trauma), multivariable linear regression modeling with robust standard errors was applied exclusively to the hypertensive cohort to isolate the independent impacts of chronological age and hypertension duration.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWithin the hypertensive cohort, chronological age emerged as a significant independent negative predictor of CD31 expression area (β = -0.74, 95% CI: -0.98 to -0.50, p\u0026thinsp;=\u0026thinsp;0.016). The duration of hypertension did not independently predict CD31 loss, showing instead a marginal, non-significant positive trend (p\u0026thinsp;=\u0026thinsp;0.076) suggestive of compensatory remodeling. While the multivariable model for CD138 did not reach statistical significance, a robust positive correlation was observed between CD31 and CD138 tissue expression levels (R\u0026thinsp;=\u0026thinsp;0.50, p\u0026thinsp;=\u0026thinsp;0.025), indicating synchronized structural degradation.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eChronological age, rather than the chronicity of hypertension, acts as a significant independent predictor of reduced CD31 expression in the coronary arteries of hypertensive patients. The coupled expression of CD31 and CD138 underscores a tightly linked biological relationship between the structural integrity of the endothelium and its protective glycocalyx. These findings highlight the critical necessity of isolating physiological senescence from pathological remodeling in vascular research.\u003c/p\u003e","manuscriptTitle":"Age, rather than hypertension duration, drives coronary endothelial degradation: an in situ post-mortem analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 10:03:43","doi":"10.21203/rs.3.rs-9463271/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-13T14:37:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81007375898030446640133142156678002483","date":"2026-05-06T16:57:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227224769770197264439197646604051764739","date":"2026-05-04T08:05:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"71918636143001424656820264726893403048","date":"2026-04-30T19:49:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-30T09:06:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-22T08:45:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-22T02:53:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-22T02:53:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2026-04-19T15:33:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2a5eddd8-4621-46b2-91ba-8e7abc67e976","owner":[],"postedDate":"May 11th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-13T14:37:30+00:00","index":104,"fulltext":""},{"type":"reviewerAgreed","content":"81007375898030446640133142156678002483","date":"2026-05-06T16:57:02+00:00","index":102,"fulltext":""},{"type":"reviewerAgreed","content":"227224769770197264439197646604051764739","date":"2026-05-04T08:05:15+00:00","index":97,"fulltext":""},{"type":"reviewerAgreed","content":"71918636143001424656820264726893403048","date":"2026-04-30T19:49:48+00:00","index":91,"fulltext":""},{"type":"reviewersInvited","content":"68","date":"2026-04-30T09:06:19+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T10:03:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-11 10:03:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9463271","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9463271","identity":"rs-9463271","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}