Molecular Markers of Endothelial Dysfunction in Post-COVID Prediabetes: A Focus on NOS3 Gene Expression and Pro-Inflammatory Cytokine Profiles

Molecular Markers of Endothelial Dysfunction in Post-COVID Prediabetes: A Focus on NOS3 Gene Expression and Pro-Inflammatory Cytokine Profiles | 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 Molecular Markers of Endothelial Dysfunction in Post-COVID Prediabetes: A Focus on NOS3 Gene Expression and Pro-Inflammatory Cytokine Profiles Eswar Reddy Kandukuri, Dr. A Josephine, Dr. G Anitha, Dr. V Sureka, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7218746/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Prediabetes, marked by early insulin resistance and chronic low-grade inflammation, is closely linked to endothelial dysfunction and increased cardiovascular risk. Post-COVID-19 recovery may intensify this risk due to persistent vascular inflammation and endothelial damage. This study investigates the relationship between NOS3 gene expression and key pro-inflammatory cytokines (IL-6, IL-18, TNF-α, IL-1β) in post-COVID prediabetic individuals to identify early molecular markers of endothelial malfunction and inform preventive strategies. Methods and Results: A case-control study was conducted with 120 participants (60 post-COVID prediabetics and 60 healthy controls). Blood samples were analyzed for biochemical markers and cytokine levels using ELISA, while NOS3 gene expression was quantified using RT-PCR (normalized to GAPDH via the 2 −ΔΔCt method). Data were analyzed using Stata 17.0. Results indicated significantly elevated levels of IL-6, IL-18, IL-1β, TNF-α, and NOS3 expression in post-COVID prediabetics, suggesting heightened inflammation and endothelial activation. ROC analysis revealed IL-6 and TNF-α as strong discriminatory markers. A positive correlation was observed between NOS3 expression and all cytokines. Logistic regression showed that IL-18, IL-6, and TNF-α were significant independent predictors of NOS3 dysregulation, while IL-1β lost significance after adjustment. Conclusion: This study highlights a clear association between elevated pro-inflammatory cytokines and NOS3 overexpression in post-COVID prediabetes, reflecting a compensatory endothelial response to inflammation. IL-18 emerged as the strongest independent predictor, supporting the potential of NOS3 as an early biomarker for endothelial stress and emphasizing the role of inflammation in cardiometabolic risk post-COVID-19. Prediabetes Endothelial dysfunction NOS3 gene expression Nitric oxide synthase (eNOS) Chronic low-grade inflammation Pro-inflammatory cytokines Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Prediabetes is an intermediate metabolic state characterized by impaired glucose regulation, early insulin resistance, and chronic low-grade inflammation. Although often clinically silent, it is associated with early vascular changes that significantly increase the risk of developing type 2 diabetes mellitus (T2DM) and cardiovascular disease [1]. One of the earliest manifestations in this progression is endothelial dysfunction, which disrupts vascular homeostasis and accelerates the development of atherosclerosis. The emergence of Coronavirus Disease 2019 (COVID-19) has introduced increased difficulty to the treatment of cardiometabolic disorders. While fundamentally a respiratory illness, SARS-CoV-2 has a proven ability to destroy the vascular endothelium, causing microvascular inflammation, thrombosis, and broad endothelial injury [2]. Notably, individuals healing from COVID-19, especially those with preexisting metabolic conditions such as prediabetes, often continue to exhibit lingering vascular and metabolic disturbances [3]. At the molecular level, endothelial dysfunction is closely associated with diminished nitric oxide (NO) bioavailability, a key vasodilatory molecule manufactured by endothelial nitric oxide synthase (eNOS), which the NOS3 gene encodes for. The NOS3 gene, is placed on chromosome 7q35-36, composed of 21 kilobases (kb), and is a major player in vascular health [4]. Alterations in NOS3 expression or eNOS activity have been observed in both prediabetic and post-COVID-19 individuals, suggesting a convergence of metabolic and infectious insults that leads to sustained endothelial injury and increased cardiovascular risk [5]. In addition to impaired NO signaling, the pro-inflammatory state induced by SARS-CoV-2 illness typically extends into the post-acute phase, coinciding with the inflammatory profile similar to prediabetes. Elevated amounts of cytokines such as interleukin-1 beta (IL-1β), interleukin-6 (IL-6), interleukin-18 (IL-18), and tumor necrosis factor-alpha (TNF-α) are commonly observed in both conditions. These cytokines promote endothelial activation, suppress NOS3 expression, impair eNOS function, and contribute to vascular inflammation and dysfunction [6,7]. This study aims to investigate the molecular markers of endothelial dysfunction in individuals with post-COVID prediabetes, with a particular focus on NOS3 gene expression and the circulating levels of key pro-inflammatory cytokines (IL-6, TNF-α, and IL-1β). By examining the interplay between impaired NO synthesis and chronic inflammation, the study seeks to elucidate the molecular mechanisms basic to constant vascular dysfunction in this high-risk population. Awareness from this research may help recognize early biomarkers and notify targeted therapeutic methods to stop long-term cardiovascular problems. METHODOLOGY Study Design This case-control study was performed to observe the molecular mechanisms basic to endothelial dysfunction in individuals with post-COVID prediabetes, with a focus on NOS3 gene expression and circulating pro-inflammatory cytokine profiles. The study was executed by the ethical standards outlined in the Declaration of Helsinki (1964) and its revised editions. Ethical approval was received from the Institutional Ethics Committee of Genetika (IECG) under Ref. No: 07/2024/IECG. Study Area and Population A total of 120 participants were recruited for the study and were categorized into the following groups: Cases: 60 individuals with a history of confirmed COVID-19 (RT-PCR positive) who are currently diagnosed with prediabetes. Controls: 60 age- and sex-matched healthy individuals. The case subjects were recruited from Hridayalaya Heart and Robotics Research Centre, located in Thiruvananthapuram, Kerala. The control subjects were recruited from various medical camps conducted across Thiruvananthapuram. All laboratory analyses, including molecular and biochemical investigations, were conducted at Genetika, Centre for Advanced Genetic Studies, Thiruvananthapuram. Inclusion Criteria Participants included in the study were adults aged between 20 and 60 years. Eligibility required a documented history of SARS-CoV-2 infection, confirmed by either RT-PCR or antigen testing. All volunteers were detected with prediabetes according to the American Diabetes Association (ADA) criteria, which include one or more of the following parameters: Fasting blood glucose levels between 100 and 125 mg/dL HbA1c levels between 5.7% and 6.4% All participants were required to provide blood samples for analysis of NOS3 gene expression and cytokine profiling (IL-6, IL-18, TNF-α, and IL-1β). Written informed consent was secured before enlistment. Participants in the control group had no history of SARS-CoV-2 infection and demonstrated normal glucose regulation, defined as fasting plasma glucose (FPG) < 100 mg/dL and HbA1c < 5.7%. Additionally, they were age- and sex-matched with the individuals in the case group. Exclusion Criteria Diagnosis of Type 2 Diabetes Mellitus (FPG ≥ 126 mg/dL or HbA1c ≥ 6.5%) History of cardiovascular diseases, stroke, or chronic kidney disease Presence of autoimmune, infectious, or chronic inflammatory diseases Use of anti-inflammatory, immunosuppressive, or antioxidant supplements/medications Current smokers or individuals with alcohol/substance abuse Pregnant or lactating women Individuals with any malignancy or undergoing radiation/chemotherapy Age below 20 or above 60 years Data Gathering A detailed collection of demographic and clinical data was conducted through personal interviews using a pre-structured questionnaire. This included information on socio-demographic characteristics, anthropometric measurements, lifestyle factors, and family history of diabetes. Written informed consent was obtained from all participants before their inclusion in the study. Sample Collection and Preparation Fasting venous blood samples (6–8 mL) were collected from each participant using standard aseptic techniques. The samples were distributed into EDTA tubes and plain vacutainers. Serum was separated from the plain tubes by centrifugation and used for the analysis of inflammatory cytokines. Blood collected in EDTA tubes was utilized for molecular analysis, including RNA extraction, cDNA synthesis, and quantitative real-time PCR (qRT-PCR) to assess NOS3 gene expression. Laboratory Investigations Blood samples were analyzed for biochemical parameters following standardized laboratory protocols. Levels of inflammatory markers, including IL-6, IL-18, IL-1β, and TNF-α, were analyzed utilizing enzyme-linked immunosorbent assay (ELISA) kits acquired from Origin Diagnostics & Research, Kerala, India. All assays were run stringently as per the manufacturer’s guidelines to ensure the accuracy, reliability, and reproducibility of the observations. Genetic Analysis RNA Isolation and cDNA Synthesis RNA was separated using an RNA extraction kit, quantified using a biospectrometer, and then reverse-transcribed into cDNA using a cDNA synthesis kit. Real-Time PCR (RT-PCR) NOS3 gene expression was analyzed using RT-PCR with specific primers (Forward: 5'-GAAGGCGACAATCCTGTATGGC-3' and Reverse: 5'-TGTTCGAGGGACACCACGTCAT-3'), and GAPDH was used as the reference housekeeping gene. The RT-PCR was performed on a CFX Opus 96 Real-Time PCR system. A 20 μL PCR reaction mixture was prepared, consisting of 2X Real-Time PCR Master Mix, primers, cDNA, and nuclease-free water. The thermal cycling conditions consist of an initial pre-denaturation at 95°C for 5 minutes, after which 30-40 cycles of denaturation at 94°C for 1 minute, followed by annealing at 56°C for 1 minute, and extension at 72°C for 1 minute. Next, a final extension at 72°C for 10 minutes was performed, followed by melt curve analysis. Gene expression levels were normalized to the housekeeping gene, and relative expression was calculated using the (2 −ΔΔCt ) method. Statistical Analysis Descriptive analysis summed up demographic and clinical data. Separate t-tests were utilized to compare normally distributed variables between groups. ROC analysis assessed biomarker diagnostic utility via AUC, sensitivity, and specificity. Quantile regression was used to analyze the associations between NOS3 gene expression (2 ^–ΔΔCT ) and clinical parameters. Bootstrap methods were employed to obtain robust p-values when normality assumptions were violated. All analyses were performed using Stata 17.0. RESULT The study employs a case–control design, comprising a total of 120 participants, of whom cases were recruited from Hridayalaya Heart and Robotics Research Centre, and controls from various medical camps in Thiruvananthapuram. Table 1: Comparison of Inflammatory and Endothelial Biomarkers Between Case and Control Groups Values are presented as minimum–maximum ranges and mean ± standard deviation (SD). The case group includes OVID-positive individuals with prediabetes, while the control group comprises age- and sex-matched healthy individuals. Cytokine concentrations (IL-1β, IL-18, IL-6, TNF-α) are expressed in pg/mL. NOS3 expression is presented as relative expression values. Variable Case (Min–Max) c Case (Mean ± SD) c Control (Min–Max) Control (Mean ± SD) IL-1β (pg/mL) a 2.21 – 25.7 11.74 ± 5.25 1.35 – 12.3 4.83 ± 2.52 IL-18 (pg/mL) a 84.5 – 240.6 132.1 ± 32.8 80 – 132.3 104.4 ± 13.5 IL-6 (pg/mL) a 1.20 – 15.6 7.67 ± 2.80 0.69 – 6.39 2.07 ± 1.35 TNF-α (pg/mL) a 10.5 – 48 27.8 ± 7.9 4.6 – 23.4 13.0 ± 4.0 NOS3 (2 −ΔΔCt ) b 0.685 – 3.158 1.36 ± 0.42 0.763 – 1.142 0.94 ± 0.09 ᵃ Cytokine concentrations are expressed in picograms per milliliter (pg/mL). ᵇ NOS3 gene expression values are presented using the 2^ −ΔΔCt method for relative quantification. C All values are expressed as minimum to maximum range and mean ± standard deviation (SD). Case includes COVID-positive individuals with prediabetes . Control group comprises age- and sex-matched healthy individuals. The comparison between the case and control groups reveals elevated levels of inflammatory markers and endothelial nitric oxide synthase (NOS3) in the case group. Specifically, IL-1β levels were notably higher in cases (mean 11.74 ± 5.25 pg/mL) compared to controls (mean 4.83 ± 2.52 pg/mL), suggesting increased pro-inflammatory activity. Similarly, IL-18 levels were elevated in the case group (132.1 ± 32.8 pg/mL) versus the control group (104.4 ± 13.5 pg/mL), presenting greater inflammasome actuation. IL-6 amounts in the case group (7.67 ± 2.80 pg/mL) were substantially higher than in the control group (2.07 ± 1.35 pg/mL), reflecting a state of heightened systemic inflammation. TNF-α levels followed the same trend, with significantly increased levels in cases (27.8 ± 7.9 pg/mL) compared to controls (13.0 ± 4.0 pg/mL), supporting the presence of an amplified inflammatory response. Additionally, NOS3 expression was elevated in the case group (1.36 ± 0.42) against the control group (0.94 ± 0.09). Since NOS3 is normally linked with protective vascular functions, its elevation in cases may indicate a compensatory reaction to inflammation-regulated endothelial stress. The ROC curve illustrates the relationship between sensitivity and specificity, with curves closer to the top-left corner indicating higher diagnostic accuracy. Among the biomarkers analyzed, IL-6 exhibits the strongest diagnostic performance, characterized by high sensitivity and specificity, making it the most reliable marker for distinguishing cases from controls. TNF-α also demonstrates good diagnostic potential, closely following IL-6 in performance. IL-1β and NOS3 exhibit moderate accuracy, with curves above the reference line but not as close to the ideal corner. In contrast, IL-18 shows the lowest diagnostic value, with its curve closest to the reference line, indicating limited ability to differentiate between cases and controls. The ROC curve illustrates the relationship between sensitivity and specificity, with curves closer to the top-left corner indicating higher diagnostic accuracy. Among the biomarkers analyzed, IL-6 exhibits the strongest diagnostic performance, characterized by high sensitivity and specificity, making it the most reliable marker for distinguishing cases from controls. TNF-α also demonstrates good diagnostic potential, closely following IL-6 in performance. IL-1β and NOS3 exhibit moderate accuracy, with curves above the reference line but not as close to the ideal corner. In contrast, IL-18 shows the lowest diagnostic value, with its curve closest to the reference line, indicating limited ability to differentiate between cases and controls. The scatter plot illustrates the relationship between IL-18 levels (x-axis) and NOS3 gene expression (y-axis) in individuals with prediabetes. The plot demonstrates a positive correlation: as IL-18 levels increase, NOS3 gene expression also increases. This trend suggests that elevated IL-18, a pro-inflammatory cytokine, may be associated with the upregulation of NOS3, a gene involved in endothelial function and vascular regulation. The scatter plot shows the relationship between IL-6 levels (x-axis) and NOS3 gene expression (y-axis) in prediabetic individuals. There is a clear and strong positive correlation: as IL-6 levels increase, NOS3 gene expression also increases. The findings suggest that increased systemic inflammation is closely linked with endothelial activation, possibly as a compensatory mechanism to counter vascular stress in the prediabetic state. The scatter plot presents the link between TNF-α levels (x-axis) and NOS3 gene expression (y-axis) in prediabetic individuals. The plot reveals a positive linear correlation between TNF-α, a pro-inflammatory cytokine, and NOS3 gene expression. As TNF-α levels increase, there is a corresponding increase in NOS3 expression. This implies that systemic inflammation may be driving endothelial activation, as NOS3 is involved in vascular homeostasis. The observed pattern supports the hypothesis that inflammation contributes to early endothelial changes in prediabetes. Table 2: Logistic Regression Results Predicting NOS3 Dysregulation among COVID-Positive Individuals Variable Category Unadjusted OR [95% CI] Adjusted OR [95% CI] IL-18 ≤100 pg/mL (ref) 1.00 1.00 >100 pg/mL 17.11 [4.59 – 63.77]*** 10.30 [1.93 – 55.03]** IL-1β ≤6.5 pg/mL (ref) 1.00 1.00 >6.5 pg/mL 1.72 [0.68 – 4.35] 0.33 [0.07 – 1.59] IL-6 ≤7 pg/mL (ref) 1.00 1.00 >7 pg/mL 10.11 [4.20 – 24.35]*** 4.05 [1.09 – 14.95]* TNF-α ≤25 pg/mL (ref) 1.00 1.00 >25 pg/mL 19.52 [7.45 – 51.13]*** 9.89 [2.53 – 38.71]** *Significance: *p < 0.05, **p < 0.01, *** p < 0.001 The table presents the unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals for the association between elevated levels of inflammatory markers and the likelihood of developing the condition, likely prediabetes, or a related metabolic disorder. Individuals with IL-18 levels above 100 pg/mL had significantly higher odds of the condition compared to those with levels ≤100 pg/mL. The unadjusted OR was 17.11, and even after adjusting for confounding variables, the OR remained significant at 10.30, indicating a strong independent association. For IL-6, those with levels above seven pg/mL showed increased risk, with an unadjusted OR of 10.11 and an adjusted OR of 4.05, suggesting IL-6 is also an independent predictor. TNF-α levels above 25 pg/mL were similarly associated with higher odds, with an unadjusted OR of 19.52 and an adjusted OR of 9.89, confirming its strong and independent association with the condition. In contrast, IL-1β levels above 6.5 pg/mL did not show a significant association. The unadjusted OR was 1.72, and the adjusted OR dropped to 0.33, indicating that IL-1β is not an independent predictor in this context. In summary, greater amounts of IL-18, IL-6, and TNF-α show notable and separate links with greater risk, but IL-1β does not imply a sensible link after adjustment. DISCUSSION This study detected distinctly increased amounts of IL-1β, IL-18, IL-6, TNF-α, and NOS3 gene expression in prediabetic persons, presenting early actuation of inflammatory pathways and endothelial malfunction. While prior research has separately explored the functions of pro-inflammatory cytokines in insulin resistance and metabolic syndrome [ 8 , 9 ], or endothelial malfunction in type 2 diabetes [ 10 ], the present study uniquely joins these components to explain their combined influence in prediabetes, a connection unexplored in this context. The elevated amounts of IL-6 and TNF-α observed in our study (Table 1 ) corroborate the findings of Bashir et al. (2020), who demonstrated that these cytokines increase before the development of type 2 diabetes [ 11 ]. Similarly, the elevation in IL-18 is consistent with Trøseid et al. (2010), who reported an association between it and metabolic syndrome and endothelial dysfunction [ 12 ]. Although NOS3 is typically downregulated in established diabetes (Zeng et al., 2010), its upregulation in our prediabetic cohort may indicate a compensatory response by the endothelium [ 13 ]. Despite elevated IL-1β levels, it did not exhibit independent predictive power, suggesting a limited or secondary role at this stage. This contrasts with the findings of Larsen et al. (2007), who implicated IL-1β in β-cell dysfunction during overt diabetes, highlighting its potentially evolving role in disease progression [ 14 ] Utilizing ROC curve analysis (Fig. 1), this study establishes a combined biomarker approach for the early detection of prediabetes. Among the markers evaluated, IL-6 demonstrated the highest diagnostic accuracy, closely followed by TNF-α, underscoring their prominent roles in early metabolic inflammation. Conversely, NOS3 and IL-1β exhibited moderate discriminatory power, while IL-18 showed limited diagnostic relevance. These findings highlight IL-6 and TNF-α as possible frontline biomarkers for seeking persons at risk of advancing to overt diabetes. A possible positive correlation was analyzed between pro-inflammatory cytokines (IL-1β, IL-18, IL-6, and TNF-α) and NOS3 gene expression in COVID-positive prediabetic individuals, as demonstrated by the scatter plots shown in Figs. 2–5. The scatter plots consistently show that as levels of these cytokines increase, NOS3 expression also rises, suggesting that inflammatory stress may trigger endothelial activation through NOS3 upregulation in the outset of metabolic dysfunction [ 15 ]. These findings highlight a distinct inflammatory-endothelial interplay in COVID-positive prediabetic individuals, suggesting that increased NOS3 expression may serve as an early indicator of endothelial adaptation in reaction to inflammation. Logistic regression analysis (Table 2 ) detected that greater amounts of IL-18, IL-6, and TNF-α were notably and separately related with greater odds of NOS3 augmentation, indicating a strong inflammatory effect on endothelial nitric oxide synthase activity. Specifically, IL-18 levels greater than 100pg/mL showed the strongest association, with an adjusted odds ratio (OR) of 10.30, followed by TNF-α levels greater than 25 pg/mL, with an OR of 9.89, and IL-6 levels greater than 7pg/mL, with an OR of 4.05. In contrast, IL-1β > 6.5 pg/mL did not demonstrate a significant independent association with NOS3 expression [ 16 ], as the adjusted OR dropped to 0.33 [ 16 ]. This finding partially contrasts with earlier work by Larsen et al. (2007), which linked IL-1β to β-cell malfunction in type 2 diabetes [ 14 ]. The exception may present variations in disease stage or modulation by post-COVID inflammatory pathways. In general, these observations detected IL-18, IL-6, and TNF-α as significant independent predictors of NOS3 dysregulation. This suggests that NOS3 expression may serve as a dynamic endothelial marker responsive to inflammatory activity in the prediabetic stage, particularly among individuals with a history of COVID-19 infection. Strengths and Limitations This study introduces a novel integrated approach that simultaneously assesses key inflammatory cytokines (IL-1β, IL-6, IL-18, and TNF-α) and NOS3 gene expression in COVID-positive prediabetic individuals, offering new insights into inflammation-endothelial interactions during early metabolic dysfunction. Its clinical relevance lies in identifying early vascular and inflammatory changes post-COVID that may signal progression to diabetes. Strengths include the use of adjusted logistic models and quantitative biomarker analysis. However, limitations include a small sample size, the absence of direct endothelial function assessment, potential unmeasured confounders, and single-center data, which may limit the generalizability of the findings. Further large-scale, longitudinal studies are warranted. CONCLUSION This study provides novel insight into the molecular mechanisms underlying endothelial dysfunction in post-COVID prediabetes by demonstrating a significant association between elevated pro-inflammatory cytokines (IL-6, IL-18, TNF-α) and increased NOS3 gene expression. The integrated analysis of inflammatory and endothelial markers, particularly the upregulation of NOS3 in response to cytokine elevation, suggests a compensatory endothelial adaptation to low-grade inflammation in the outset of metabolic dysregulation. Among the biomarkers measured, IL-6 and TNF-α exhibited the highest diagnostic utility, while IL-18 emerged as the strongest independent predictor of NOS3 dysregulation. These findings support the potential of NOS3 as a dynamic marker of early endothelial stress and highlight the importance of targeting inflammation to prevent vascular complications in individuals with prediabetes, especially those with prior COVID-19 exposure. Further longitudinal studies are warranted to validate NOS3 as a predictive biomarker and explore its therapeutic relevance in cardiometabolic risk stratification. Declarations ACKNOWLEDGMENTS We sincerely appreciate the support and resources provided by Meenakshi Academy of Higher Education and Research, Chennai, Tamil Nadu, India, and Genetika, Centre for Advanced Genetic Studies, Thiruvananthapuram, Kerala, India. FUNDING There are no funding sources to report. COMPETING INTERESTS The authors affirm that they have no known financial or interpersonal conflicts that would have seemed to have an impact on the research presented in this study. AUTHOR CONTRIBUTIONS Eswar Reddy Kandukuri: Conceptualization, Methodology, Investigation, Data Analysis, Writing – Original Draft. A Josephine: Supervision, Methodology, Writing – Review & Editing (corresponding author). G Anitha: Supervision, Validation, Writing – Review & Editing. V Sureka: Resources, Writing – Review & Editing. Ilangovan R: Formal Analysis, Data Curation, Writing – Review. Meivelu Moovendhan, Rajitha P P, Renjitha Ramachandran, Prince Thomas: Investigation, Data Collection, Laboratory Support. Dinesh Roy D: Supervision, Validation, Writing – Review & Editing. All authors read and approved the final manuscript. ETHICS APPROVAL Approved by the Institutional Ethics Committee of Genetika (07/2024/IECG). CONSENT TO PARTICIPANTS Informed consent was obtained from all individual participants included in the study CONSENT TO PUBLISH Springer Nature or its licensor (such as a society or partner organization) retains exclusive rights to this article under a formal publishing agreement with the author(s) or designated rightsholder(s). The self-archiving of the accepted manuscript version by the author is permitted only in accordance with the terms of this agreement and relevant legal provisions. References Lawal, Y., Bello, F., & Kaoje, Y. S. (2020). Prediabetes Deserves More Attention: A Review. Clinical diabetes : a publication of the American Diabetes Association , 38 (4), 328–338. https://doi.org/10.2337/cd19-0101 Roberts, K. A., Colley, L., Agbaedeng, T. A., Ellison-Hughes, G. M., & Ross, M. D. (2020). Vascular Manifestations of COVID-19 - Thromboembolism and Microvascular Dysfunction. 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Human genetics , 127 (4), 373–381. https://doi.org/10.1007/s00439-009-0783-x Larsen, C. M., Faulenbach, M., Vaag, A., Vølund, A., Ehses, J. A., Seifert, B., Mandrup-Poulsen, T., & Donath, M. Y. (2007). Interleukin-1-receptor antagonist in type 2 diabetes mellitus. The New England journal of medicine , 356 (15), 1517–1526. https://doi.org/10.1056/NEJMoa065213 Shu, X., Keller, T. C., 4th, Begandt, D., Butcher, J. T., Biwer, L., Keller, A. S., Columbus, L., & Isakson, B. E. (2015). Endothelial nitric oxide synthase in the microcirculation. Cellular and molecular life sciences : CMLS , 72 (23), 4561–4575. https://doi.org/10.1007/s00018-015-2021-0 Kim, M. E., & Lee, J. S. (2025). Advances in the Regulation of Inflammatory Mediators in Nitric Oxide Synthase: Implications for Disease Modulation and Therapeutic Approaches. International journal of molecular sciences , 26 (3), 1204. https://doi.org/10.3390/ijms26031204 Additional Declarations No competing interests reported. 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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-7218746","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":492108671,"identity":"22895092-fb13-455c-8c04-5d8dbdcc1802","order_by":0,"name":"Eswar Reddy Kandukuri","email":"","orcid":"","institution":"Meenakshi Academy of Higher Education and Research (Deemed to be University)","correspondingAuthor":false,"prefix":"","firstName":"Eswar","middleName":"Reddy","lastName":"Kandukuri","suffix":""},{"id":492108672,"identity":"c218ca70-744a-4963-9d9c-5d81d1463600","order_by":1,"name":"Dr. A Josephine","email":"data:image/png;base64,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","orcid":"","institution":"Meenakshi Academy of Higher Education and Research (Deemed to be University)","correspondingAuthor":true,"prefix":"Dr.","firstName":"A","middleName":"","lastName":"Josephine","suffix":""},{"id":492108674,"identity":"691f94e1-16db-48da-a873-453f43774d8c","order_by":2,"name":"Dr. G Anitha","email":"","orcid":"","institution":"Fathima Institute of Medical Sciences","correspondingAuthor":false,"prefix":"Dr.","firstName":"G","middleName":"","lastName":"Anitha","suffix":""},{"id":492108676,"identity":"d38a360b-02d4-4742-9105-12ded3d5d2bf","order_by":3,"name":"Dr. V Sureka","email":"","orcid":"","institution":"Meenakshi Academy of Higher Education and Research (Deemed to be University)","correspondingAuthor":false,"prefix":"Dr.","firstName":"V","middleName":"","lastName":"Sureka","suffix":""},{"id":492108677,"identity":"d3d757b3-3b34-41ea-90f2-78f03ecdfc83","order_by":4,"name":"Dr. R Ilangovan","email":"","orcid":"","institution":"DR. ALMPGIBMS University of Madras","correspondingAuthor":false,"prefix":"Dr.","firstName":"R","middleName":"","lastName":"Ilangovan","suffix":""},{"id":492108684,"identity":"2c1c2dc2-c85e-4433-9f12-5da2823bf1ff","order_by":5,"name":"Dr. Meivelu Moovendhan","email":"","orcid":"","institution":"Center for Global Health Research, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS),","correspondingAuthor":false,"prefix":"Dr.","firstName":"Meivelu","middleName":"","lastName":"Moovendhan","suffix":""},{"id":492108690,"identity":"4a25c2ee-ac25-43c0-9270-37cf5134e4f5","order_by":6,"name":"Ms. Rajitha P P","email":"","orcid":"","institution":"Meenakshi Academy of Higher Education and Research (MAHER- Deemed to be University), West K.K Nagar, Chennai, Tamil Nadu, India.","correspondingAuthor":false,"prefix":"Ms.","firstName":"Rajitha","middleName":"P","lastName":"P","suffix":""},{"id":492108692,"identity":"3eda2459-5dd5-47cc-ab12-c39de0f7b699","order_by":7,"name":"Ms. Renjitha Ramachandran","email":"","orcid":"","institution":"Meenakshi Academy of Higher Education and Research (MAHER- Deemed to be University), West K.K Nagar, Chennai, Tamil Nadu, India.","correspondingAuthor":false,"prefix":"Ms.","firstName":"Renjitha","middleName":"","lastName":"Ramachandran","suffix":""},{"id":492108693,"identity":"809639b6-09a1-4aca-bafa-8ad19469cec0","order_by":8,"name":"Mr. Prince Thomas","email":"","orcid":"","institution":"Chettinad Academy of Research and Education","correspondingAuthor":false,"prefix":"Mr.","firstName":"Prince","middleName":"","lastName":"Thomas","suffix":""},{"id":492108695,"identity":"a29f9f43-12ea-426b-aebc-4569916306bf","order_by":9,"name":"Dr. Dinesh Roy D","email":"","orcid":"","institution":"CEO \u0026 Senior Cytogeneticist","correspondingAuthor":false,"prefix":"Dr.","firstName":"Dinesh","middleName":"Roy","lastName":"D","suffix":""}],"badges":[],"createdAt":"2025-07-26 05:53:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7218746/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7218746/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87917304,"identity":"78781ad7-810d-4d11-b6c6-31e820d7fd42","added_by":"auto","created_at":"2025-07-30 11:12:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":44433,"visible":true,"origin":"","legend":"\u003cp\u003eDiagnostic Performance Metrics of Inflammatory and Vascular Markers for Predicting Case-Control Status\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe pink line represents the ROC curve for interleukin-18 (IL-18), while the red line corresponds to interleukin-1 beta (IL-1β). The blue line depicts the ROC curve for interleukin-6 (IL-6), and the green line shows the curve for endothelial nitric oxide synthase (NOS3). Tumor necrosis factor-alpha (TNF-α) is represented by the teal line. The yellow diagonal line serves as the reference line, indicating no discriminative ability with an AUC of 0.5.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eROC analysis was conducted to assess the predictive performance of the cytokines and NOS3. A higher area under the curve (AUC) value reflects greater sensitivity and specificity in distinguishing between groups.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7218746/v1/8009975db4e64b7dda8b4b86.png"},{"id":87917305,"identity":"b8497f00-67b2-4a12-ada2-ed1ffb0eccdc","added_by":"auto","created_at":"2025-07-30 11:12:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38313,"visible":true,"origin":"","legend":"\u003cp\u003eScatter Plot Showing the Association Between IL-1β and NOS3 Gene Expression Among COVID-Positive Prediabetic Individuals\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe scatter plot illustrates the relationship between IL-1β levels (x-axis) and NOS3 gene expression (y-axis) in prediabetic individuals. Each blue dot represents an individual participant, while the red line indicates the linear trend.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eA positive correlation was observed between IL-1β and NOS3 gene expression among prediabetic subjects. The upward slope of the regression line suggests a moderate association.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7218746/v1/98300b5bf2bcc6e187b27f7d.png"},{"id":87916549,"identity":"1520f557-b1f0-476c-8861-198d8c3c6e6e","added_by":"auto","created_at":"2025-07-30 11:04:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26070,"visible":true,"origin":"","legend":"\u003cp\u003eScatter Plot Showing the Association Between IL-18 and NOS3 Gene Expression Among COVID-Positive Prediabetic Individuals\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe scatter plot displays the association between IL-18 levels (x-axis) and NOS3 gene expression (y-axis) in prediabetic participants. Each blue dot represents a subject, and the red line shows the trend.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eA positive correlation is seen between IL-18 and NOS3 expression, indicating that NOS3 levels tend to rise with increasing IL-18 in prediabetic individuals.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7218746/v1/ced5328dd44cd4c12cf58d67.png"},{"id":87916547,"identity":"51fc97da-a204-4d51-b913-886b170f2c99","added_by":"auto","created_at":"2025-07-30 11:04:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":33007,"visible":true,"origin":"","legend":"\u003cp\u003eScatter Plot Showing the Association Between IL-6 and NOS3 Gene Expression Among COVID-Positive Prediabetic Individuals\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThis scatter plot illustrates the relationship between IL-6 levels and NOS3 gene expression in prediabetic individuals. Each blue dot represents a participant, and the red line indicates the linear trend.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eA clear positive correlation is observed, suggesting that higher IL-6 levels are associated with increased NOS3 expression in the prediabetic group.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7218746/v1/5e7f628061cde2a87c646406.png"},{"id":87917650,"identity":"cc128d43-516e-4d35-a0c3-6a4bf1d67697","added_by":"auto","created_at":"2025-07-30 11:20:35","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":33338,"visible":true,"origin":"","legend":"\u003cp\u003eScatter Plot Showing the Association Between TNF-α and NOS3 Gene Expression Among COVID-Positive Prediabetic Individuals\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eScatter plot showing the association between TNF-α and NOS3 gene expression in prediabetic individuals. Blue dots represent subjects; the red line shows the trend.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eA positive correlation is observed, indicating that higher TNF-α levels are linked to increased NOS3 expression.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7218746/v1/b9b18a4d73d9492af77f61e2.png"},{"id":89307216,"identity":"3cce89e8-001f-47d8-8eed-3e5e613dbe63","added_by":"auto","created_at":"2025-08-18 15:24:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1118461,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7218746/v1/bc3c4490-8f03-4161-96d1-98b661af68be.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Molecular Markers of Endothelial Dysfunction in Post-COVID Prediabetes: A Focus on NOS3 Gene Expression and Pro-Inflammatory Cytokine Profiles","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003ePrediabetes is an intermediate metabolic state characterized by impaired glucose regulation, early insulin resistance, and chronic low-grade inflammation. Although often clinically silent, it is associated with early vascular changes that significantly increase the risk of developing type 2 diabetes mellitus (T2DM) and cardiovascular disease [1]. One of the earliest manifestations in this progression is endothelial dysfunction, which disrupts vascular homeostasis and accelerates the development of atherosclerosis.\u003c/p\u003e\n\u003cp\u003eThe emergence of Coronavirus Disease 2019 (COVID-19) has introduced increased difficulty to the treatment of cardiometabolic disorders. While fundamentally a respiratory illness, SARS-CoV-2 has a proven ability to destroy the vascular endothelium, causing microvascular inflammation, thrombosis, and broad endothelial injury [2]. Notably, individuals healing from COVID-19, especially those with preexisting metabolic conditions such as prediabetes, often continue to exhibit lingering vascular and metabolic disturbances [3].\u003c/p\u003e\n\u003cp\u003eAt the molecular level, endothelial dysfunction is closely associated with diminished nitric oxide (NO) bioavailability, a key vasodilatory molecule manufactured by endothelial nitric oxide synthase (eNOS), which the NOS3 gene encodes for. The NOS3 gene, is placed on chromosome 7q35-36, composed of 21 kilobases (kb), and is a major player in vascular health [4]. Alterations in NOS3 expression or eNOS activity have been observed in both prediabetic and post-COVID-19 individuals, suggesting a convergence of metabolic and infectious insults that leads to sustained endothelial injury and increased cardiovascular risk [5].\u003c/p\u003e\n\u003cp\u003eIn addition to impaired NO signaling, the pro-inflammatory state induced by SARS-CoV-2 illness typically extends into the post-acute phase, coinciding with the inflammatory profile similar to prediabetes. Elevated amounts of cytokines such as interleukin-1 beta (IL-1β), interleukin-6 (IL-6), interleukin-18 (IL-18), and tumor necrosis factor-alpha (TNF-α) are commonly observed in both conditions. These cytokines promote endothelial activation, suppress NOS3 expression, impair eNOS function, and contribute to vascular inflammation and dysfunction [6,7].\u003c/p\u003e\n\u003cp\u003eThis study aims to investigate the molecular markers of endothelial dysfunction in individuals with post-COVID prediabetes, with a particular focus on NOS3 gene expression and the circulating levels of key pro-inflammatory cytokines (IL-6, TNF-α, and IL-1β). By examining the interplay between impaired NO synthesis and chronic inflammation, the study seeks to elucidate the molecular mechanisms basic to constant vascular dysfunction in this high-risk population. Awareness from this research may help recognize early biomarkers and notify targeted therapeutic methods to stop long-term cardiovascular problems.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003e\u003cstrong\u003eStudy Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis case-control study was performed to observe the molecular mechanisms basic to endothelial dysfunction in individuals with post-COVID prediabetes, with a focus on NOS3 gene expression and circulating pro-inflammatory cytokine profiles. The study was executed by the ethical standards outlined in the Declaration of Helsinki (1964) and its revised editions. Ethical approval was received from the Institutional Ethics Committee of Genetika (IECG) under Ref. No: 07/2024/IECG.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Area and Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 120 participants were recruited for the study and were categorized into the following groups:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eCases: 60\u0026nbsp;\u003c/strong\u003eindividuals with a history of confirmed COVID-19 (RT-PCR positive) who are currently diagnosed with prediabetes.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eControls: 60\u0026nbsp;\u003c/strong\u003eage- and sex-matched healthy individuals.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe case subjects were recruited from Hridayalaya Heart and Robotics Research Centre, located in Thiruvananthapuram, Kerala. The control subjects were recruited from various medical camps conducted across Thiruvananthapuram. All laboratory analyses, including molecular and biochemical investigations, were conducted at Genetika, Centre for Advanced Genetic Studies, Thiruvananthapuram.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants included in the study were adults aged between 20 and 60 years. Eligibility required a documented history of SARS-CoV-2 infection, confirmed by either RT-PCR or antigen testing. All volunteers were detected with prediabetes according to the American Diabetes Association (ADA) criteria, which include one or more of the following parameters:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eFasting blood glucose levels between 100 and 125 mg/dL\u003c/li\u003e\n \u003cli\u003eHbA1c levels between 5.7% and 6.4%\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAll participants were required to provide blood samples for analysis of NOS3 gene expression and cytokine profiling (IL-6, IL-18, TNF-α, and IL-1β). Written informed consent was secured before enlistment. Participants in the control group had no history of SARS-CoV-2 infection and demonstrated normal glucose regulation, defined as fasting plasma glucose (FPG) \u0026lt; 100 mg/dL and HbA1c \u0026lt; 5.7%. Additionally, they were age- and sex-matched with the individuals in the case group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eDiagnosis of Type 2 Diabetes Mellitus (FPG ≥ 126 mg/dL or HbA1c ≥ 6.5%)\u003c/li\u003e\n \u003cli\u003eHistory of cardiovascular diseases, stroke, or chronic kidney disease\u003c/li\u003e\n \u003cli\u003ePresence of autoimmune, infectious, or chronic inflammatory diseases\u003c/li\u003e\n \u003cli\u003eUse of anti-inflammatory, immunosuppressive, or antioxidant supplements/medications\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCurrent smokers or individuals with alcohol/substance abuse\u003c/li\u003e\n \u003cli\u003ePregnant or lactating women\u003c/li\u003e\n \u003cli\u003eIndividuals with any malignancy or undergoing radiation/chemotherapy\u003c/li\u003e\n \u003cli\u003eAge below 20 or above 60 years\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eData Gathering\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA detailed collection of demographic and clinical data was conducted through personal interviews using a pre-structured questionnaire. This included information on socio-demographic characteristics, anthropometric measurements, lifestyle factors, and family history of diabetes. Written informed consent was obtained from all participants before their inclusion in the study.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eSample Collection and Preparation\u003c/strong\u003e\u003c/h4\u003e\n\u003ch4\u003eFasting venous blood samples (6–8 mL) were collected from each participant using standard aseptic techniques. The samples were distributed into EDTA tubes and plain vacutainers. Serum was separated from the plain tubes by centrifugation and used for the analysis of inflammatory cytokines. Blood collected in EDTA tubes was utilized for molecular analysis, including RNA extraction, cDNA synthesis, and quantitative real-time PCR (qRT-PCR) to assess NOS3 gene expression.\u003c/h4\u003e\n\u003cp\u003e\u003cstrong\u003eLaboratory Investigations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlood samples were analyzed for biochemical parameters following standardized laboratory protocols. Levels of inflammatory markers, including IL-6, IL-18, IL-1β, and TNF-α, were analyzed utilizing enzyme-linked immunosorbent assay (ELISA) kits acquired from Origin Diagnostics \u0026amp; Research, Kerala, India. All assays were run stringently as per the manufacturer’s guidelines to ensure the accuracy, reliability, and reproducibility of the observations.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eGenetic Analysis\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eRNA Isolation and cDNA Synthesis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA was separated using an RNA extraction kit, quantified using a biospectrometer, and then reverse-transcribed into cDNA using a cDNA synthesis kit.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReal-Time PCR (RT-PCR)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNOS3 gene expression was analyzed using RT-PCR with specific primers (Forward: 5'-GAAGGCGACAATCCTGTATGGC-3' and Reverse: 5'-TGTTCGAGGGACACCACGTCAT-3'), and GAPDH was used as the reference housekeeping gene. The RT-PCR was performed on a CFX Opus 96 Real-Time PCR system. A 20 μL PCR reaction mixture was prepared, consisting of 2X Real-Time PCR Master Mix, primers, cDNA, and nuclease-free water. The thermal cycling conditions consist of an initial pre-denaturation at 95°C for 5 minutes, after which 30-40 cycles of denaturation at 94°C for 1 minute, followed by annealing at 56°C for 1 minute, and extension at 72°C for 1 minute. Next, a final extension at 72°C for 10 minutes was performed, followed by melt curve analysis. Gene expression levels were normalized to the housekeeping gene, and relative expression was calculated using the (2\u003csup\u003e−ΔΔCt\u003c/sup\u003e) method.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive analysis summed up demographic and clinical data. Separate t-tests were utilized to compare normally distributed variables between groups. ROC analysis assessed biomarker diagnostic utility via AUC, sensitivity, and specificity. Quantile regression was used to analyze the associations between NOS3 gene expression (2\u003csup\u003e^–ΔΔCT\u003c/sup\u003e) and clinical parameters. Bootstrap methods were employed to obtain robust p-values when normality assumptions were violated. All analyses were performed using Stata 17.0.\u003c/p\u003e"},{"header":"RESULT","content":"\u003cp\u003eThe study employs a case\u0026ndash;control design, comprising a total of 120 participants, of whom cases were recruited from Hridayalaya Heart and Robotics Research Centre, and controls from various medical camps in Thiruvananthapuram.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eComparison of Inflammatory and Endothelial Biomarkers Between Case and Control Groups\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eValues are presented as minimum\u0026ndash;maximum ranges and mean \u0026plusmn; standard deviation (SD). The case group includes\u0026nbsp;\u003c/em\u003e\u003cem\u003eOVID-positive\u003c/em\u003e\u003cem\u003e\u0026nbsp;individuals with prediabetes, while the control group comprises age- and sex-matched healthy individuals. Cytokine concentrations (IL-1\u0026beta;, IL-18, IL-6, TNF-\u0026alpha;) are expressed in pg/mL. NOS3 expression is presented as relative expression values.\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"632\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCase\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003e(Min\u0026ndash;Max)\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCase\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003e(Mean \u0026plusmn; SD)\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Min\u0026ndash;Max)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003csup\u003eIL-1\u0026beta; (pg/mL)\u003c/sup\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2.21 \u0026ndash; 25.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e11.74 \u0026plusmn; 5.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e1.35 \u0026ndash; 12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e4.83 \u0026plusmn; 2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003csup\u003eIL-18 (pg/mL)\u003c/sup\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e84.5 \u0026ndash; 240.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e132.1 \u0026plusmn; 32.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e80 \u0026ndash; 132.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e104.4 \u0026plusmn; 13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003csup\u003eIL-6 (pg/mL)\u003c/sup\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1.20 \u0026ndash; 15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e7.67 \u0026plusmn; 2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e0.69 \u0026ndash; 6.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e2.07 \u0026plusmn; 1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003csup\u003eTNF-\u0026alpha; (pg/mL)\u003c/sup\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e10.5 \u0026ndash; 48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e27.8 \u0026plusmn; 7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e4.6 \u0026ndash; 23.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e13.0 \u0026plusmn; 4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003csup\u003eNOS3\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003csup\u003e(2\u003c/sup\u003e\u003csup\u003e\u0026minus;\u0026Delta;\u0026Delta;Ct\u003c/sup\u003e\u003csup\u003e)\u003c/sup\u003e\u003csup\u003eb\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.685 \u0026ndash; 3.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e1.36 \u0026plusmn; 0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e0.763 \u0026ndash; 1.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e0.94 \u0026plusmn; 0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eᵃ Cytokine concentrations are expressed in picograms per milliliter (pg/mL).\u003cbr\u003e ᵇ NOS3 gene expression values are presented using the 2^\u003csup\u003e\u0026minus;\u0026Delta;\u0026Delta;Ct\u003c/sup\u003e method for relative quantification.\u003cbr\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003eC\u003c/sup\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eAll values are expressed as minimum to maximum range and mean \u0026plusmn; standard deviation (SD).\u003cbr\u003e\u003c/em\u003e\u003cem\u003eCase\u003c/em\u003e\u003cem\u003e\u0026nbsp;includes\u0026nbsp;\u003c/em\u003e\u003cem\u003eCOVID-positive\u003c/em\u003e\u003cem\u003e\u0026nbsp;individuals with prediabetes\u003c/em\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003e\u003cem\u003eControl group comprises age- and sex-matched healthy individuals.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe comparison between the case and control groups reveals elevated levels of inflammatory markers and endothelial nitric oxide synthase (NOS3) in the case group. Specifically, IL-1\u0026beta; levels were notably higher in cases (mean 11.74 \u0026plusmn; 5.25 pg/mL) compared to controls (mean 4.83 \u0026plusmn; 2.52 pg/mL), suggesting increased pro-inflammatory activity. Similarly, IL-18 levels were elevated in the case group (132.1 \u0026plusmn; 32.8 pg/mL) versus the control group (104.4 \u0026plusmn; 13.5 pg/mL), presenting greater inflammasome actuation. IL-6 amounts in the case group (7.67 \u0026plusmn; 2.80 pg/mL) were substantially higher than in the control group (2.07 \u0026plusmn; 1.35 pg/mL), reflecting a state of heightened systemic inflammation. TNF-\u0026alpha; levels followed the same trend, with significantly increased levels in cases (27.8 \u0026plusmn; 7.9 pg/mL) compared to controls (13.0 \u0026plusmn; 4.0 pg/mL), supporting the presence of an amplified inflammatory response. Additionally, NOS3 expression was elevated in the case group (1.36 \u0026plusmn; 0.42) against the control group (0.94 \u0026plusmn; 0.09). Since NOS3 is normally linked with protective vascular functions, its elevation in cases may indicate a compensatory reaction to inflammation-regulated endothelial stress.\u003c/p\u003e\n\u003cp\u003eThe ROC curve illustrates the relationship between sensitivity and specificity, with curves closer to the top-left corner indicating higher diagnostic accuracy. Among the biomarkers analyzed, IL-6 exhibits the strongest diagnostic performance, characterized by high sensitivity and specificity, making it the most reliable marker for distinguishing cases from controls. TNF-\u0026alpha; also demonstrates good diagnostic potential, closely following IL-6 in performance. IL-1\u0026beta; and NOS3 exhibit moderate accuracy, with curves above the reference line but not as close to the ideal corner. In contrast, IL-18 shows the lowest diagnostic value, with its curve closest to the reference line, indicating limited ability to differentiate between cases and controls.\u003c/p\u003e\n\u003cp\u003eThe ROC curve illustrates the relationship between sensitivity and specificity, with curves closer to the top-left corner indicating higher diagnostic accuracy. Among the biomarkers analyzed, IL-6 exhibits the strongest diagnostic performance, characterized by high sensitivity and specificity, making it the most reliable marker for distinguishing cases from controls. TNF-\u0026alpha; also demonstrates good diagnostic potential, closely following IL-6 in performance. IL-1\u0026beta; and NOS3 exhibit moderate accuracy, with curves above the reference line but not as close to the ideal corner. In contrast, IL-18 shows the lowest diagnostic value, with its curve closest to the reference line, indicating limited ability to differentiate between cases and controls.\u003c/p\u003e\n\u003cp\u003eThe scatter plot illustrates the relationship between IL-18 levels (x-axis) and NOS3 gene expression (y-axis) in individuals with prediabetes. The plot demonstrates a positive correlation: as IL-18 levels increase, NOS3 gene expression also increases. This trend suggests that elevated IL-18, a pro-inflammatory cytokine, may be associated with the upregulation of NOS3, a gene involved in endothelial function and vascular regulation.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The scatter plot shows the relationship between IL-6 levels (x-axis) and NOS3 gene expression (y-axis) in prediabetic individuals. There is a clear and strong positive correlation: as IL-6 levels increase, NOS3 gene expression also increases. The findings suggest that increased systemic inflammation is closely linked with endothelial activation, possibly as a compensatory mechanism to counter vascular stress in the prediabetic state.\u003c/p\u003e\n\u003cp\u003eThe scatter plot presents the link between TNF-\u0026alpha; levels (x-axis) and NOS3 gene expression (y-axis) in prediabetic individuals. The plot reveals a positive linear correlation between TNF-\u0026alpha;, a pro-inflammatory cytokine, and NOS3 gene expression. As TNF-\u0026alpha; levels increase, there is a corresponding increase in NOS3 expression. This implies that systemic inflammation may be driving endothelial activation, as NOS3 is involved in vascular homeostasis. The observed pattern supports the hypothesis that inflammation contributes to early endothelial changes in prediabetes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eLogistic Regression Results Predicting NOS3 Dysregulation among COVID-Positive Individuals\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"616\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnadjusted OR [95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR [95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eIL-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026le;100 pg/mL (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026gt;100 pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003e17.11 [4.59 \u0026ndash; 63.77]***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e10.30 [1.93 \u0026ndash; 55.03]**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eIL-1\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026le;6.5 pg/mL (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026gt;6.5 pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003e1.72 [0.68 \u0026ndash; 4.35]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e0.33 [0.07 \u0026ndash; 1.59]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eIL-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026le;7 pg/mL (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026gt;7 pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003e10.11 [4.20 \u0026ndash; 24.35]***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e4.05 [1.09 \u0026ndash; 14.95]*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eTNF-\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026le;25 pg/mL (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026gt;25 pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003e19.52 [7.45 \u0026ndash; 51.13]***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e9.89 [2.53 \u0026ndash; 38.71]**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Significance: *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***\u003cem\u003ep \u0026lt; 0.001\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe table presents the unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals for the association between elevated levels of inflammatory markers and the likelihood of developing the condition, likely prediabetes, or a related metabolic disorder. Individuals with IL-18 levels above 100 pg/mL had significantly higher odds of the condition compared to those with levels \u0026le;100 pg/mL. The unadjusted OR was 17.11, and even after adjusting for confounding variables, the OR remained significant at 10.30, indicating a strong independent association. For IL-6, those with levels above seven pg/mL showed increased risk, with an unadjusted OR of 10.11 and an adjusted OR of 4.05, suggesting IL-6 is also an independent predictor. TNF-\u0026alpha; levels above 25 pg/mL were similarly associated with higher odds, with an unadjusted OR of 19.52 and an adjusted OR of 9.89, confirming its strong and independent association with the condition. In contrast, IL-1\u0026beta; levels above 6.5 pg/mL did not show a significant association. The unadjusted OR was 1.72, and the adjusted OR dropped to 0.33, indicating that IL-1\u0026beta; is not an independent predictor in this context. In summary, greater amounts of IL-18, IL-6, and TNF-\u0026alpha; show notable and separate links with greater risk, but IL-1\u0026beta; does not imply a sensible link after adjustment.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study detected distinctly increased amounts of IL-1β, IL-18, IL-6, TNF-α, and NOS3 gene expression in prediabetic persons, presenting early actuation of inflammatory pathways and endothelial malfunction. While prior research has separately explored the functions of pro-inflammatory cytokines in insulin resistance and metabolic syndrome [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], or endothelial malfunction in type 2 diabetes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], the present study uniquely joins these components to explain their combined influence in prediabetes, a connection unexplored in this context.\u003c/p\u003e\u003cp\u003eThe elevated amounts of IL-6 and TNF-α observed in our study (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) corroborate the findings of Bashir et al. (2020), who demonstrated that these cytokines increase before the development of type 2 diabetes [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Similarly, the elevation in IL-18 is consistent with Tr\u0026oslash;seid et al. (2010), who reported an association between it and metabolic syndrome and endothelial dysfunction [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Although NOS3 is typically downregulated in established diabetes (Zeng et al., 2010), its upregulation in our prediabetic cohort may indicate a compensatory response by the endothelium [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Despite elevated IL-1β levels, it did not exhibit independent predictive power, suggesting a limited or secondary role at this stage. This contrasts with the findings of Larsen et al. (2007), who implicated IL-1β in β-cell dysfunction during overt diabetes, highlighting its potentially evolving role in disease progression [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eUtilizing ROC curve analysis (Fig.\u0026nbsp;1), this study establishes a combined biomarker approach for the early detection of prediabetes. Among the markers evaluated, IL-6 demonstrated the highest diagnostic accuracy, closely followed by TNF-α, underscoring their prominent roles in early metabolic inflammation. Conversely, NOS3 and IL-1β exhibited moderate discriminatory power, while IL-18 showed limited diagnostic relevance. These findings highlight IL-6 and TNF-α as possible frontline biomarkers for seeking persons at risk of advancing to overt diabetes.\u003c/p\u003e\u003cp\u003eA possible positive correlation was analyzed between pro-inflammatory cytokines (IL-1β, IL-18, IL-6, and TNF-α) and NOS3 gene expression in COVID-positive prediabetic individuals, as demonstrated by the scatter plots shown in Figs.\u0026nbsp;2\u0026ndash;5. The scatter plots consistently show that as levels of these cytokines increase, NOS3 expression also rises, suggesting that inflammatory stress may trigger endothelial activation through NOS3 upregulation in the outset of metabolic dysfunction [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These findings highlight a distinct inflammatory-endothelial interplay in COVID-positive prediabetic individuals, suggesting that increased NOS3 expression may serve as an early indicator of endothelial adaptation in reaction to inflammation.\u003c/p\u003e\u003cp\u003eLogistic regression analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) detected that greater amounts of IL-18, IL-6, and TNF-α were notably and separately related with greater odds of NOS3 augmentation, indicating a strong inflammatory effect on endothelial nitric oxide synthase activity. Specifically, IL-18 levels greater than 100pg/mL showed the strongest association, with an adjusted odds ratio (OR) of 10.30, followed by TNF-α levels greater than 25 pg/mL, with an OR of 9.89, and IL-6 levels greater than 7pg/mL, with an OR of 4.05. In contrast, IL-1β\u0026thinsp;\u0026gt;\u0026thinsp;6.5 pg/mL did not demonstrate a significant independent association with NOS3 expression [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], as the adjusted OR dropped to 0.33 [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This finding partially contrasts with earlier work by Larsen et al. (2007), which linked IL-1β to β-cell malfunction in type 2 diabetes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The exception may present variations in disease stage or modulation by post-COVID inflammatory pathways. In general, these observations detected IL-18, IL-6, and TNF-α as significant independent predictors of NOS3 dysregulation. This suggests that NOS3 expression may serve as a dynamic endothelial marker responsive to inflammatory activity in the prediabetic stage, particularly among individuals with a history of COVID-19 infection.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStrengths and Limitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study introduces a novel integrated approach that simultaneously assesses key inflammatory cytokines (IL-1β, IL-6, IL-18, and TNF-α) and NOS3 gene expression in COVID-positive prediabetic individuals, offering new insights into inflammation-endothelial interactions during early metabolic dysfunction. Its clinical relevance lies in identifying early vascular and inflammatory changes post-COVID that may signal progression to diabetes. Strengths include the use of adjusted logistic models and quantitative biomarker analysis. However, limitations include a small sample size, the absence of direct endothelial function assessment, potential unmeasured confounders, and single-center data, which may limit the generalizability of the findings. Further large-scale, longitudinal studies are warranted.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study provides novel insight into the molecular mechanisms underlying endothelial dysfunction in post-COVID prediabetes by demonstrating a significant association between elevated pro-inflammatory cytokines (IL-6, IL-18, TNF-α) and increased NOS3 gene expression. The integrated analysis of inflammatory and endothelial markers, particularly the upregulation of NOS3 in response to cytokine elevation, suggests a compensatory endothelial adaptation to low-grade inflammation in the outset of metabolic dysregulation. Among the biomarkers measured, IL-6 and TNF-α exhibited the highest diagnostic utility, while IL-18 emerged as the strongest independent predictor of NOS3 dysregulation. These findings support the potential of NOS3 as a dynamic marker of early endothelial stress and highlight the importance of targeting inflammation to prevent vascular complications in individuals with prediabetes, especially those with prior COVID-19 exposure. Further longitudinal studies are warranted to validate NOS3 as a predictive biomarker and explore its therapeutic relevance in cardiometabolic risk stratification.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely appreciate the support and resources provided by Meenakshi Academy of Higher Education and Research, Chennai, Tamil Nadu, India, and Genetika, Centre for Advanced Genetic Studies, Thiruvananthapuram, Kerala, India.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere are no funding sources to report.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors affirm that they have no known financial or interpersonal conflicts that would have seemed to have an impact on the research presented in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEswar Reddy Kandukuri:\u003c/strong\u003e Conceptualization, Methodology, Investigation, Data Analysis, Writing – Original Draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA Josephine:\u003c/strong\u003e Supervision, Methodology, Writing – Review \u0026amp; Editing (corresponding author).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eG Anitha:\u003c/strong\u003e Supervision, Validation, Writing – Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eV Sureka:\u003c/strong\u003e Resources, Writing – Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIlangovan R:\u003c/strong\u003e Formal Analysis, Data Curation, Writing – Review.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeivelu Moovendhan, Rajitha P P, Renjitha Ramachandran, Prince Thomas:\u003c/strong\u003e Investigation, Data Collection, Laboratory Support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDinesh Roy D:\u003c/strong\u003e Supervision, Validation, Writing – Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAll authors read and approved the final manuscript.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICS APPROVAL\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproved by the Institutional Ethics Committee of Genetika (07/2024/IECG).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONSENT TO PARTICIPANTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONSENT TO PUBLISH\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSpringer Nature or its licensor (such as a society or partner organization) retains exclusive rights to this article under a formal publishing agreement with the author(s) or designated rightsholder(s). The self-archiving of the accepted manuscript version by the author is permitted only in accordance with the terms of this agreement and relevant legal provisions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eLawal, Y., Bello, F., \u0026amp; Kaoje, Y. S. (2020). Prediabetes Deserves More Attention: A Review. \u003cem\u003eClinical diabetes : a publication of the American Diabetes Association\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(4), 328\u0026ndash;338. https://doi.org/10.2337/cd19-0101\u003c/li\u003e\n \u003cli\u003eRoberts, K. A., Colley, L., Agbaedeng, T. A., Ellison-Hughes, G. M., \u0026amp; Ross, M. D. (2020). Vascular Manifestations of COVID-19 - Thromboembolism and Microvascular Dysfunction. \u003cem\u003eFrontiers in cardiovascular medicine\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e, 598400. https://doi.org/10.3389/fcvm.2020.598400\u003c/li\u003e\n \u003cli\u003eScherer, P. E., Kirwan, J. P., \u0026amp; Rosen, C. J. (2022). 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(2021). Pro-inflammatory CXCL-10, TNF-\u0026alpha;, IL-1\u0026beta;, and IL-6: biomarkers of SARS-CoV-2 infection. \u003cem\u003eArchives of virology\u003c/em\u003e, \u003cem\u003e166\u003c/em\u003e(12), 3301\u0026ndash;3310. https://doi.org/10.1007/s00705-021-05247-z\u003c/li\u003e\n \u003cli\u003eHotamisligil G. S. (2006). Inflammation and metabolic disorders. \u003cem\u003eNature\u003c/em\u003e, \u003cem\u003e444\u003c/em\u003e(7121), 860\u0026ndash;867. https://doi.org/10.1038/nature05485\u003c/li\u003e\n \u003cli\u003eDonath, M. Y., \u0026amp; Shoelson, S. E. (2011). Type 2 diabetes as an inflammatory disease. \u003cem\u003eNature reviews. Immunology\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(2), 98\u0026ndash;107. https://doi.org/10.1038/nri2925\u003c/li\u003e\n \u003cli\u003eTabit, C. E., Chung, W. B., Hamburg, N. M., \u0026amp; Vita, J. A. (2010). Endothelial dysfunction in diabetes mellitus: molecular mechanisms and clinical implications. \u003cem\u003eReviews in endocrine \u0026amp; metabolic disorders\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(1), 61\u0026ndash;74. https://doi.org/10.1007/s11154-010-9134-4\u003c/li\u003e\n \u003cli\u003eBashir, H., Ahmad Bhat, S., Majid, S., Hamid, R., Koul, R. K., Rehman, M. U., Din, I., Ahmad Bhat, J., Qadir, J., \u0026amp; Masood, A. (2020). Role of inflammatory mediators (TNF-\u0026alpha;, IL-6, CRP), biochemical and hematological parameters in type 2 diabetes mellitus patients of Kashmir, India. \u003cem\u003eMedical journal of the Islamic Republic of Iran\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e, 5. https://doi.org/10.34171/mjiri.34.5\u003c/li\u003e\n \u003cli\u003eTr\u0026oslash;seid, M., Seljeflot, I., \u0026amp; Arnesen, H. (2010). The role of interleukin-18 in the metabolic syndrome. \u003cem\u003eCardiovascular diabetology\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e, 11. https://doi.org/10.1186/1475-2840-9-11\u003c/li\u003e\n \u003cli\u003eZeng, Z., Li, L., Zhang, Z., Li, Y., Wei, Z., Huang, K., He, L., \u0026amp; Shi, Y. (2010). A meta-analysis of three polymorphisms in the endothelial nitric oxide synthase gene (NOS3) and their effect on the risk of diabetic nephropathy. \u003cem\u003eHuman genetics\u003c/em\u003e, \u003cem\u003e127\u003c/em\u003e(4), 373\u0026ndash;381. https://doi.org/10.1007/s00439-009-0783-x\u003c/li\u003e\n \u003cli\u003eLarsen, C. M., Faulenbach, M., Vaag, A., V\u0026oslash;lund, A., Ehses, J. A., Seifert, B., Mandrup-Poulsen, T., \u0026amp; Donath, M. Y. (2007). Interleukin-1-receptor antagonist in type 2 diabetes mellitus. \u003cem\u003eThe New England journal of medicine\u003c/em\u003e, \u003cem\u003e356\u003c/em\u003e(15), 1517\u0026ndash;1526. https://doi.org/10.1056/NEJMoa065213\u003c/li\u003e\n \u003cli\u003eShu, X., Keller, T. C., 4th, Begandt, D., Butcher, J. T., Biwer, L., Keller, A. S., Columbus, L., \u0026amp; Isakson, B. E. (2015). Endothelial nitric oxide synthase in the microcirculation. \u003cem\u003eCellular and molecular life sciences : CMLS\u003c/em\u003e, \u003cem\u003e72\u003c/em\u003e(23), 4561\u0026ndash;4575. https://doi.org/10.1007/s00018-015-2021-0\u003c/li\u003e\n \u003cli\u003eKim, M. E., \u0026amp; Lee, J. S. (2025). Advances in the Regulation of Inflammatory Mediators in Nitric Oxide Synthase: Implications for Disease Modulation and Therapeutic Approaches. \u003cem\u003eInternational journal of molecular sciences\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(3), 1204. https://doi.org/10.3390/ijms26031204\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Prediabetes, Endothelial dysfunction, NOS3 gene expression, Nitric oxide synthase (eNOS), Chronic low-grade inflammation, Pro-inflammatory cytokines","lastPublishedDoi":"10.21203/rs.3.rs-7218746/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7218746/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003cbr\u003e\nPrediabetes, marked by early insulin resistance and chronic low-grade inflammation, is closely linked to endothelial dysfunction and increased cardiovascular risk. Post-COVID-19 recovery may intensify this risk due to persistent vascular inflammation and endothelial damage. This study investigates the relationship between NOS3 gene expression and key pro-inflammatory cytokines (IL-6, IL-18, TNF-α, IL-1β) in post-COVID prediabetic individuals to identify early molecular markers of endothelial malfunction and inform preventive strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods and Results:\u003c/strong\u003e\u003cbr\u003e\nA case-control study was conducted with 120 participants (60 post-COVID prediabetics and 60 healthy controls). Blood samples were analyzed for biochemical markers and cytokine levels using ELISA, while NOS3 gene expression was quantified using RT-PCR (normalized to GAPDH via the 2\u003csup\u003e−ΔΔCt\u003c/sup\u003e method). Data were analyzed using Stata 17.0. Results indicated significantly elevated levels of IL-6, IL-18, IL-1β, TNF-α, and NOS3 expression in post-COVID prediabetics, suggesting heightened inflammation and endothelial activation. ROC analysis revealed IL-6 and TNF-α as strong discriminatory markers. A positive correlation was observed between NOS3 expression and all cytokines. Logistic regression showed that IL-18, IL-6, and TNF-α were significant independent predictors of NOS3 dysregulation, while IL-1β lost significance after adjustment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003cbr\u003e\nThis study highlights a clear association between elevated pro-inflammatory cytokines and NOS3 overexpression in post-COVID prediabetes, reflecting a compensatory endothelial response to inflammation. IL-18 emerged as the strongest independent predictor, supporting the potential of NOS3 as an early biomarker for endothelial stress and emphasizing the role of inflammation in cardiometabolic risk post-COVID-19.\u003c/p\u003e","manuscriptTitle":"Molecular Markers of Endothelial Dysfunction in Post-COVID Prediabetes: A Focus on NOS3 Gene Expression and Pro-Inflammatory Cytokine Profiles","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-30 11:04:30","doi":"10.21203/rs.3.rs-7218746/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"00cba681-ede4-4c3d-b9aa-c56d253ec8d1","owner":[],"postedDate":"July 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-18T15:23:46+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-30 11:04:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7218746","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7218746","identity":"rs-7218746","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}