Angiogenic T cells and cognitive function in older adults with type 2 diabetes treated with GLP-1 receptor agonists

Angiogenic T cells and cognitive function in older adults with type 2 diabetes treated with GLP-1 receptor agonists | 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 Angiogenic T cells and cognitive function in older adults with type 2 diabetes treated with GLP-1 receptor agonists Miriam Longo, Paola Caruso, Maria Chiara Auriemma, Antonietta Maio, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8814937/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: Older adults with type 2 diabetes mellitus (T2DM) are at high risk of both cardiovascular complications and cognitive decline, with major implications for independence and self-management. Endothelial dysfunction and impaired angiogenic capacity may play a key role. This study investigated the association between circulating angiogenic T cells (Tang cells) and cognitive function in older adults with T2DM and explored the potential impact of glucagon‑like peptide‑1 receptor agonist (GLP‑1RA) therapy. Methods: A cross-sectional study was conducted on 154 T2DM patients aged 60–80 years, treated either with GLP-1 receptor agonist (GLP-1RA) plus metformin or metformin alone. Cognitive function was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Circulating CD3 + CD31 + CXCR4 + Tang cells were quantified by flow cytometry. Propensity score matching was applied to control for age, body weight and HbA1c. Results: In the overall cohort, higher Tang cell levels were significantly associated with better cognitive performance (MoCA, r = 0.423; MMSE, r = 0.428; both P < 0.001). After matching, 40 patients in each treatment group were included in the comparative analysis. The GLP-1RA+MET group showed significantly higher circulating Tang cell levels than the MET group, both in absolute counts and as percentage of CD3 + T cells (P < 0.001). Conclusions: Circulating Tang cell levels are positively associated with cognitive function in older adults with T2DM. GLP‑1RA therapy is associated with higher Tang cell levels compared with metformin alone, suggesting a potential role of enhanced endothelial repair in mitigating diabetes‑related cognitive impairment in older age. Type 2 diabetes cognitive function angiogenic T cells GLP-1RA endothelial dysfunction Figures Figure 1 Figure 2 Introduction Type 2 diabetes mellitus (T2DM) is a complex chronic metabolic disorder highly prevalent in older adults. It is associated with an increased burden of cardiovascular and microvascular complications, disability and loss of independence [1-2]. In this age group, the coexistence of multimorbidity, polypharmacy and functional impairment makes diabetes management particularly challenging [3]. Beyond its vascular impact, T2DM is increasingly recognized as a major risk factor for cognitive decline and dementia, especially in older individuals [4]. Cognitive impairment in people with T2DM has important clinical consequences, as it may compromise treatment adherence, increase the risk of hypoglycemia and accelerate functional dependence [5]. However, the precise mechanisms linking T2DM to cognitive decline remain incompletely understood, with chronic low-grade inflammation, endothelial dysfunction and neurovascular unit impairment emerging as central contributors [6]. Endothelial dysfunction represents an early step in the development of atherosclerosis, and it is implicated in the pathogenesis of both macro- and micro-vascular complications of T2DM [7]. Adequate vascular repair mechanisms are essential to counteract endothelial injury and preserve tissue perfusion, particularly in the ageing vasculature [8]. Circulating angiogenic cells, which include both endothelial progenitor cells (EPCs) and angiogenic T cells (Tang cells), play key roles in repairing damaged endothelium and promoting angiogenesis and neovascularization [9]. Reduced angiogenic activity and aberrant angiogenesis have been associated with cerebral small vessel disease, white matter hyperintensities and cognitive impairment [10]. In recent years, GLP-1 receptor agonists (GLP-1RAs) have emerged as an effective therapeutic option for managing T2DM in older adults, providing not only effective glycemic control but also significant cardiovascular and renal protective effects [11-12]. These agents have also been suggested to exert neuroprotective actions, possibly through anti-inflammatory effects, improved endothelial function and modulation of neurovascular pathways [13]. In a previous study, older adults with T2DM treated with GLP-1RA in combination with metformin exhibited significantly higher circulating EPCs levels and better cognitive performance compared with those receiving metformin alone [14]. Tang cells, a subset of T lymphocytes characterized by the expression of CD3, CD31, and CD184, play a critical role in vascular repair by supporting EPC differentiation, facilitating the repair of damaged endothelium and stimulating neovascularization [15]. Reduced Tang cell levels have been reported in several conditions associated with endothelial dysfunction, including rheumatoid arthritis [16], hypertension‑related cerebral small vessel disease [17] and T2DM [18]. While the association of EPCs with cognitive function has been established, the relationship between Tang cells and cognitive function in T2DM remains underexplored. Given the critical role of Tang cells in endothelial function, which seems to be increasingly linked to cognitive performance, this study aims to investigate the association between circulating levels of Tang cells and cognitive outcomes in individuals with T2DM. A secondary objective was to explore whether treatment with GLP‑1RA plus metformin is associated with a more favorable angiogenic T‑cell profile compared with metformin alone in this population. Methods This cross-sectional study was conducted at the University of Campania "Luigi Vanvitelli" (Naples, Italy) and included community-dwelling older adults with T2DM. The study design and main inclusion criteria have been previously described [14]. Briefly, patients aged between 60 and 80 years, with type 2 diabetes duration > 5 years, with HbA1c ≥ 7 % and < 8.5 %, and in treatment for at least 12 months with GLP-1RA plus metformin (GLP-1RA + MET group) or metformin alone (MET group) according to clinical practice were included in the analysis. Exclusion criteria comprised acute illness, recent cardiovascular events, severe psychiatric disease, known dementia, major neurological disorders, unstable medical conditions and any condition potentially interfering with cognitive testing or blood sampling. The study protocol was approved by local ethical committee (n. 625/2018 of 12.09.2018) and conducted according to the principles of the Helsinki Declaration II. All participants provided written informed consent before enrolment. All participants underwent a detailed clinical evaluation, including medical history, physical examination and assessment of cardiovascular risk factors and complications. Clinical and metabolic variables, including age, sex, body mass index (BMI), blood pressure, diabetes duration, history of cardiovascular events and current medications, were recorded. Fasting blood samples were used to determine HbA1c and other routine biochemical parameters according to standard laboratory methods. Cognitive assessment Cognitive function was assessed using a comprehensive geriatric cognitive evaluation. Global cognition was measured by the Mini‑Mental State Examination (MMSE), corrected for age and educational level, and by the Montreal Cognitive Assessment (MoCA), which explores multiple cognitive domains including memory, executive function, attention and visuospatial abilities. Tests were administered by trained personnel in a quiet setting, following standardized procedures. Higher scores indicate better cognitive performance for both MMSE and MoCA. Assessment of Tang cells Circulating Tang cells were measured by flow cytometry. Peripheral blood mononuclear cells (PBMCs) were isolated from venous blood samples by density‑gradient centrifugation using Ficoll. Cells were incubated at 4°C for 30 minutes with fluorochrome‑conjugated monoclonal antibodies, including anti‑CD3‑FITC, anti‑CD31‑PE and anti‑CD184‑Cy5 (CXCR4). Data acquisition was performed on a FACSCalibur flow cytometer (Becton‑Dickinson), with 500,000 events recorded per sample. The CD3 + lymphocyte population was first identified from the total lymphocyte gate. Within this subset, CD3 + CD31 + CD184 + Tang cells were quantified and expressed both as absolute counts (cells/ml) and as percentage of total CD3 + T cells. Statistical analysis Continuous variables are presented as mean ± standard deviation or median (interquartile range) according to their distribution, and categorical variables as counts and percentages. Correlations between Tang cell levels and cognitive scores (MoCA and MMSE) in the overall cohort were evaluated using Pearson or Spearman correlation coefficients, as appropriate. To compare Tang cell levels between treatment groups while reducing confounding, propensity score matching was performed. The propensity score was calculated for each participant based on age, body weight and HbA1c, and patients treated with GLP‑1RA+MET were matched to those receiving MET alone using a caliper width equal to 0.2 of the standard deviation of the logit of the propensity score. The balance of covariates after matching was assessed using the standardized difference method. Between‑group comparisons were carried out using the independent two‑sample t‑test or Mann‑Whitney U test for continuous variables, and the chi‑square test for categorical variables, as appropriate. Variables with non‑normal distribution were log‑transformed before analysis. A multivariable linear regression analysis was performed with MoCA score and MMSE score as the dependent variables and Tang cell counts, age, sex, BMI, HbA1c and diabetes duration as independent variables, to assess whether Tang cells were independently associated with cognitive performance . A two‑sided P value < 0.05 was considered statistically significant. All analyses were conducted using Stata, version 16.0 (Stata Corp, College Station, TX, USA). Results A total of 154 older adults with T2DM were included, 78 treated with GLP-1RA plus metformin (GLP-1RA + MET group) and 76 with only metformin (MET group). The median age of the overall cohort was 69 years, with a median BMI 30.2 kg/m 2 , and a median HbA1c level 7.2% (55 mmol/mol). Thirty-nine percent of participants were women, and 25% had a previous cardiovascular event. Median MMSE and MoCA scores were 27 and 24, respectively. Baseline clinical and metabolic characteristics are reported in Table 1. Table 1. Clinical and metabolic characteristic of overall participants in the study. Overall (N = 154) Age, years 69 (66, 75) Duration of diabetes, years Female gender, n (%) 15 (8, 25) 60 (39) Fasting glucose, mg/dl 114 (101, 141) HbA1c, % 7.2 (7.0, 7.6) HbA1c, mmol/mol 55 (53, 60) Weight, Kg 83.5 (75, 95) BMI, Kg/m 2 WC, cm 30.2 (27.7, 33) 100 (90, 105) SBP, mmHg 130 (120, 140) DBP, mmHg HR, bpm/min Total Cholesterol, mg/dl HDL-Cholesterol, mg/dl LDL- Cholesterol, mg/dl Triglycerides, mg/dl Creatinine, mg/dl 80 (75, 80) 75 (68, 84) 157 (135, 181) 49 (42, 62) 81 (68, 108) 107 (77, 150) 0.86 (0.7, 1.0) eGFR, ml/min/1.73m 2 UACR, mg/g CRP, mg/L Diabetic retinopathy, n (%) Diabetic kidney disease, n (%) Diabetic neuropathy, n (%) Prior cardiovascular event, n (%) 79 (64, 89) 10 (8, 50) 1 (0.6, 1.7) 34 (22) 24 (15) 18 (16) 39 (25) MoCA 27 (24.4, 29) MMSE 24 (19, 28) Abbreviations: BMI, body mass index; WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; HR, heart rate; HDL, high-density lipoprotein; LDL, low-density lipoprotein; eGFR, estimated glomerular filtration rate; UACR, urinary albumin-to-creatinine ratio; CRP, C-reactive protein; MoCA, Montreal Cognitive Assessment; MMSE, Mini-Mental State Examination; HbA1c, glycated hemoglobin. In the overall cohort, circulating Tang cell levels showed a significant positive correlation with cognitive performances. Higher Tang cells counts were associated with higher MoCA (r = 0.423, p < 0.001) and higher MMSE (r = 0.428, p < 0.001) scores (Figure 1). To assess whether this association was independent of major clinical variables, a multivariable linear regression model was fitted with MoCA score and MMSE score as the dependent variables and Tang cell counts, age, sex, BMI, HbA1c and diabetes duration as independent. In the model with MoCA as the dependent variable, Tang cell counts remained independently and positively associated with cognitive performance (β = 0.424; 95% CI 0.23–0.62; P < 0.001). Age was independently and inversely associated with MoCA scores (β = −0.373; 95% CI −0.59 to −0.16; P = 0.001). In contrast, sex (β = 0.018; P = 0.881), BMI (β = −0.146; P = 0.251), and diabetes duration (β = 0.141; P = 0.186) were not independently associated with MoCA scores (Table 2). Table 2. Multivariable linear regression analyses assessing the independent association between MoCA score and Tang cells count, age, sex, BMI and diabetes duration. Variables β coefficient 95% CI P Tang cells count (cells/ml) 0.424 0.23 0.62 < 0.001 Age -0.373 -0.59 -0.16 0.001 Sex 0.018 - 0.22 0.26 0.881 BMI -0.146 -0.40 0.11 0.251 Diabetes duration 0.141 -0.07 0.35 0.186 R² = 0.421, Adjusted R² = 0.401 In the model with MMSE as the dependent variable, Tang cell counts were the only variable independently and positively associated with cognitive performance (β = 0.390; 95% CI 0.18–0.60; P < 0.001). None of the other covariates showed a significant independent association with MMSE scores (age, β = −0.176; P = 0.140; sex, β = −0.173; P = 0.193; BMI, β = −0.256; P = 0.066; diabetes duration, β = 0.111; P = 0.336) (Table 3). Table 3. Multivariable linear regression analyses assessing the independent association between MMSE score and Tang cells count, age, sex, BMI and diabetes duration. Variables β coefficient 95% CI P Tang cells count (cells/ml) 0.390 0.18 0.60 < 0.001 Age -0.176 -0.41 -0.06 0.140 Sex -0.173 - 0.43 0.09 0.193 BMI -0.256 -0.53 0.02 0.066 Diabetes duration 0.111 -0.12 0.34 0.336 R² = 0.321, Adjusted R² = 0.291 After matching patients in the two groups for age, weight and HbA1c we obtained 40 patients in the GLP-1RA + MET group and 40 in the MET Group (Supplementary Table S1). Figure 2 shows the data for CD3 + T cells and CD3 + CD31 + CD184 + Tang cells levels across the two patient groups. Patients in the GLP-1RA + MET group exhibited significantly higher levels of CD3 + T cells, in absolute count but not in percentage, compared to those in the MET group [620,000 (467,000–727,000) vs. 480,000 (363,000–635,000) cells/ml, P = 0.028; and 70% (57–74) vs. 68% (61–71), P = 0.207] (Panel A and C). Similarly, levels of circulating CD3 + CD31 + CD184 + Tang cells were markedly more elevated, both in absolute count and in percentage, in the GLP-1RA + MET group [115,000 (94,000–134,000) vs. 76,000 (54,000–102,000) cells/ml, P < 0.001; and 21.1% (16–28.6) vs. 17% (13.4–18.3), P = 0.004] than MET group (Panel B and D). Discussion In this cross-sectional study, circulating Tang cells were positively associated with cognitive performance in older adults with T2DM. In addition, treatment with GLP-1RAs in combination with metformin was associated with significantly higher Tang cell levels compared with metformin alone. Circulating Tang cell counts were independently and positively associated with cognitive performance, as assessed by both MoCA and MMSE, after adjustment for major clinical and metabolic confounders. The stronger association observed with MoCA, together with the independent inverse effect of age, is consistent with the higher sensitivity of this tool in detecting early cognitive impairment. The lack of independent associations with BMI, glycemic control, and diabetes duration suggests that Tang cells may reflect a distinct pathophysiological pathway, possibly related to endothelial dysfunction and microvascular health. These findings suggest that Tang cells may reflect a specific aspect of neurovascular health that is particularly relevant in the aging diabetic population. Cognitive impairment in older adults with T2DM is increasingly recognized as the result of complex interactions between metabolic dysregulation, vascular damage, and age-related neurodegenerative processes [19]. Endothelial dysfunction and impaired microvascular repair play a central role in this context. Our results support the hypothesis that angiogenic competence, as reflected by circulating Tang cell levels, may represent an important determinant of cognitive health in this vulnerable population. Previous studies have shown that GLP-1RA therapy is associated with improved endothelial function, increased circulating endothelial progenitor cells (EPCs), and better cognitive performance in individuals with T2DM [14]. EPCs are bone marrow–derived cells that contribute to vascular repair and maintenance, and their reduction has been associated with increased cardiovascular risk and cognitive impairment in diabetes [20,21]. In particular, circulating CD34⁺KDR⁺CD133⁺ EPCs have been identified as independent predictors of cognitive function in patients with T2DM [14]. In line with these observations, the present study demonstrates that higher levels of CD3⁺CD31⁺CD184⁺ Tang cells are associated with better cognitive performance, further supporting the close relationship between endothelial repair mechanisms and brain health. Tang cells play a key role in vascular homeostasis by supporting EPC function and promoting endothelial repair. Reduced Tang cell levels have been reported in several conditions characterized by endothelial dysfunction, including rheumatoid arthritis [16], hypertension-related cerebral small vessel disease [17], and T2DM [18]. Neuroimaging studies have linked impaired angiogenic activity to markers of cerebral small vessel disease, such as white matter hyperintensities, which are highly prevalent in older adults and are known contributors to cognitive decline [10]. Although cognitive consequences may not always be evident in early stages, these findings suggest that angiogenic dysfunction may contribute to the progression of neurovascular damage over time. In a previous study involving 41 patients with T2DM and matched healthy controls, patients with diabetes exhibited reduced Tang cell levels compared to the controls [18]. Treatment with the DPP-4 inhibitor linagliptin over 26 weeks led to a significant increase in CD3 + Tang cells, further supporting the potential for pharmacological interventions to restore Tang levels and vascular repair mechanisms [18]. In our current study, the percentage of Tang cells observed in the GLP-1RA + MET group [21.1% (16–28.6)] closely mirrors the levels found in healthy controls from this last study [20.4% (16.6–27.3)] [18]. This suggests that GLP-1RA therapy may help restore circulating Tang cell levels to a range comparable to that of healthy individuals, potentially contributing to improved vascular health. The mechanisms underlying the association between GLP-1RA therapy and increased Tang cell levels remain to be fully clarified. However, GLP-1RAs exert pleiotropic effects beyond glycemic control, including anti-inflammatory actions and improvements in endothelial function, which may favor the mobilization or survival of angiogenic immune cells [22-23]. The higher circulating Tang cell levels observed in GLP-1RA–treated patients are consistent with a role for these agents in enhancing endogenous vascular repair processes. Strengths of this study include the use of a comprehensive battery of validated tests for the evaluation of cognitive functions, the assessment of CD3 + T-cells and Tang cells by flow cytometry in two homogenous groups of subjects with type 2 diabetes treated with GLP-1RA + MET or MET alone, and the relatively long duration of GLP-1RA treatment. The cross-sectional nature of the study represents the main limit as it does not allow to firmly establish causal relationship between variables. Longitudinal studies are needed to determine the long-term impact of GLP-1RA therapy on both Tang cell levels and cognitive health. Conclusion In conclusion, this cross-sectional study highlights a strong association between circulating Tang cells levels and cognitive performances in older adults with type 2 diabetes. Additionally, after matching patients for age, weight and HbA1c, subjects treated with GLP-1RA combined to metformin exhibited significantly higher levels of circulating levels of angiogenic T cells as compared to those treated with metformin alone. This finding suggests that increased circulating Tang cells may contribute to protective role in cognitive health, representing one potential mechanism by which GLP-1RA therapy exerts its neuroprotective benefits. Further longitudinal studies are needed to better understand the link between GLP-1RA and neurovascular health. Declarations Competing interests: The authors declare no conflict of interest. Funding: The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author contributions statements: All authors contributed to the brief report conception and draft. All authors read and approved the final manuscript. Data availability statement: The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. References Dal Canto E, Ceriello A, Rydén L, et al. Diabetes as a cardiovascular risk factor: an overview of global trends of macro- and microvascular complications. Eur J Prev Cardiol. 2019;26(2 Suppl):32. doi:10.1177/2047487319878371. American Diabetes Association Professional Practice Committee. 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Diabetes Obes Metab. 2025;27(7):3891–3900. doi:10.1111/dom.16419. Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 15 Mar, 2026 Reviews received at journal 15 Mar, 2026 Reviewers agreed at journal 04 Mar, 2026 Reviewers invited by journal 18 Feb, 2026 Editor assigned by journal 17 Feb, 2026 Submission checks completed at journal 08 Feb, 2026 First submitted to journal 07 Feb, 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-8814937","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":593777078,"identity":"564b6339-a491-4371-a374-c20e60d64f5c","order_by":0,"name":"Miriam 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Vanvitelli\"","correspondingAuthor":false,"prefix":"","firstName":"Irene","middleName":"Di","lastName":"Meo","suffix":""},{"id":593777083,"identity":"a6d23a51-3a9d-4d09-bbc9-e0b3fc9392a0","order_by":5,"name":"Lorenzo Scappaticcio","email":"","orcid":"","institution":"University of Campania \"Luigi Vanvitelli\"","correspondingAuthor":false,"prefix":"","firstName":"Lorenzo","middleName":"","lastName":"Scappaticcio","suffix":""},{"id":593777084,"identity":"bc3cfde4-2348-4491-bd6e-95fa7eba9463","order_by":6,"name":"Maria Ida Maiorino","email":"","orcid":"","institution":"University of Campania \"Luigi Vanvitelli\"","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Ida","lastName":"Maiorino","suffix":""},{"id":593777085,"identity":"3bb7a0cf-d5ab-40b9-a18f-c048b8b273c9","order_by":7,"name":"Giuseppe Bellastella","email":"","orcid":"","institution":"University of Campania \"Luigi Vanvitelli\"","correspondingAuthor":false,"prefix":"","firstName":"Giuseppe","middleName":"","lastName":"Bellastella","suffix":""},{"id":593777089,"identity":"fe746850-920f-4b15-b75e-69831e2b7f9d","order_by":8,"name":"Maria Rosaria Rizzo","email":"","orcid":"","institution":"University of Campania \"Luigi Vanvitelli\"","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Rosaria","lastName":"Rizzo","suffix":""},{"id":593777090,"identity":"0256481e-6374-43cf-ae9c-e6256b9f5413","order_by":9,"name":"Giuseppe Paolisso","email":"","orcid":"","institution":"University of Campania \"Luigi Vanvitelli\"","correspondingAuthor":false,"prefix":"","firstName":"Giuseppe","middleName":"","lastName":"Paolisso","suffix":""},{"id":593777091,"identity":"d4b5299a-9e6c-4655-9c75-ce1e589d60cf","order_by":10,"name":"Katherine Esposito","email":"","orcid":"","institution":"University of Campania \"Luigi Vanvitelli\"","correspondingAuthor":false,"prefix":"","firstName":"Katherine","middleName":"","lastName":"Esposito","suffix":""}],"badges":[],"createdAt":"2026-02-07 11:10:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8814937/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8814937/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103322293,"identity":"4dfaa360-f669-4511-b778-07c7c18a5689","added_by":"auto","created_at":"2026-02-24 12:11:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47787,"visible":true,"origin":"","legend":"\u003cp\u003eStatistical associations between cognitive test scores and circulating levels of Tang cells by univariate analysis.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8814937/v1/15b60ed3ede1d3da36a58b03.png"},{"id":103322399,"identity":"100b530c-d261-4e4e-b61e-5b1cc8099aa9","added_by":"auto","created_at":"2026-02-24 12:11:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":105322,"visible":true,"origin":"","legend":"\u003cp\u003eBox plots with median and error bars for counts of T-cells CD3\u003csup\u003e+\u003c/sup\u003e and angiogenic T-cells. Significant differences are indicated. ** P\u0026lt; 0.05, *** P\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8814937/v1/6650d2903a3f47bd154ad969.png"},{"id":103322547,"identity":"dca269ca-9886-4c85-a7f5-e64b85f3b7a3","added_by":"auto","created_at":"2026-02-24 12:12:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":687833,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8814937/v1/5504c714-f5e3-4fe0-ba24-75a413c07613.pdf"},{"id":103322508,"identity":"9b670ee0-c1d5-4b88-814a-28d65237f7a7","added_by":"auto","created_at":"2026-02-24 12:12:18","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":20891,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-8814937/v1/1cea4f108f6c8e8c3d433ca8.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Angiogenic T cells and cognitive function in older adults with type 2 diabetes treated with GLP-1 receptor agonists","fulltext":[{"header":"Introduction","content":"\u003cp\u003eType 2 diabetes mellitus (T2DM) is a complex chronic metabolic disorder highly prevalent in older adults. It is associated with an increased burden of cardiovascular and microvascular complications, disability and loss of independence\u0026nbsp;\u0026nbsp;[1-2]. In this age group, the coexistence of multimorbidity, polypharmacy and functional impairment makes diabetes management particularly challenging [3].\u0026nbsp;Beyond its vascular impact, T2DM is increasingly recognized as a major risk factor for cognitive decline and dementia, especially in older individuals\u0026nbsp;[4]. Cognitive impairment in people with T2DM has important clinical consequences, as it may compromise treatment adherence, increase the risk of hypoglycemia and accelerate functional dependence [5]. However, the precise mechanisms linking T2DM to cognitive decline remain incompletely understood, with chronic low-grade inflammation, endothelial dysfunction and neurovascular unit impairment emerging as central contributors [6].\u003c/p\u003e\n\u003cp\u003eEndothelial dysfunction represents an early step in the development of atherosclerosis, and it is implicated in the pathogenesis of both macro- and micro-vascular complications of T2DM [7]. Adequate vascular repair mechanisms are essential to counteract endothelial injury and preserve tissue perfusion, particularly in the ageing vasculature [8]. Circulating angiogenic cells, which include both endothelial progenitor cells (EPCs) and angiogenic T cells (Tang cells), play key roles in repairing damaged endothelium and promoting angiogenesis and neovascularization [9]. Reduced angiogenic activity and aberrant angiogenesis have been associated with cerebral small vessel disease, white matter hyperintensities and cognitive impairment\u0026nbsp;[10].\u003c/p\u003e\n\u003cp\u003eIn recent years, GLP-1 receptor agonists (GLP-1RAs) have emerged as an effective therapeutic option for managing T2DM in older adults, providing not only effective glycemic control but also significant cardiovascular and renal protective effects [11-12]. These agents have also been suggested to exert neuroprotective actions, possibly through anti-inflammatory effects, improved endothelial function and modulation of neurovascular pathways [13]. In a previous study, older adults with T2DM treated with GLP-1RA in combination with metformin exhibited significantly higher circulating EPCs levels and better cognitive performance compared with those receiving metformin alone [14].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTang cells, a subset of T lymphocytes characterized by the expression of CD3, CD31, and CD184, play a critical role in vascular repair by supporting EPC differentiation, facilitating the repair of damaged endothelium and stimulating neovascularization [15]. Reduced Tang cell levels have been reported in several conditions associated with endothelial dysfunction, including rheumatoid arthritis [16], hypertension‑related cerebral small vessel disease [17] and T2DM [18]. While the association of EPCs with cognitive function has been established, the relationship between Tang cells and cognitive function in T2DM remains underexplored. Given the critical role of Tang cells in endothelial function, which seems to be increasingly linked to cognitive performance, this study aims to investigate the association between circulating levels of Tang cells and cognitive outcomes in individuals with T2DM. A secondary objective was to explore whether treatment with GLP‑1RA plus metformin is associated with a more favorable angiogenic T‑cell profile compared with metformin alone in this population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis cross-sectional study was conducted at the University of Campania \u0026quot;Luigi Vanvitelli\u0026quot; (Naples, Italy) and included community-dwelling older adults with T2DM. The study design and main inclusion criteria have been previously described [14]. Briefly, patients aged between 60 and 80 years, with type 2 diabetes duration \u0026gt; 5 years, with HbA1c \u0026ge; 7 % and \u0026lt; 8.5 %, and in treatment for at least 12 months with GLP-1RA plus metformin (GLP-1RA + MET group) or metformin alone (MET group) according to clinical practice were included in the analysis. Exclusion criteria comprised acute illness, recent cardiovascular events, severe psychiatric disease, known dementia, major neurological disorders, unstable medical conditions and any condition potentially interfering with cognitive testing or blood sampling. The study protocol was approved by local ethical committee (n. 625/2018 of 12.09.2018) and conducted according to the principles of the Helsinki Declaration II. All participants provided written informed consent before enrolment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll participants underwent a detailed clinical evaluation, including medical history, physical examination and assessment of cardiovascular risk factors and complications. Clinical and metabolic variables, including age, sex, body mass index (BMI), blood pressure, diabetes duration, history of cardiovascular events and current medications, were recorded. Fasting blood samples were used to determine HbA1c and other routine biochemical parameters according to standard laboratory methods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCognitive assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCognitive function was assessed using a comprehensive geriatric cognitive evaluation. Global cognition was measured by the Mini‑Mental State Examination (MMSE), corrected for age and educational level, and by the Montreal Cognitive Assessment (MoCA), which explores multiple cognitive domains including memory, executive function, attention and visuospatial abilities. Tests were administered by trained personnel in a quiet setting, following standardized procedures. Higher scores indicate better cognitive performance for both MMSE and MoCA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of Tang cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCirculating Tang cells were measured by flow cytometry. Peripheral blood mononuclear cells (PBMCs) were isolated from venous blood samples by density‑gradient centrifugation using Ficoll. Cells were incubated at 4\u0026deg;C for 30 minutes with fluorochrome‑conjugated monoclonal antibodies, including anti‑CD3‑FITC, anti‑CD31‑PE and anti‑CD184‑Cy5 (CXCR4). Data acquisition was performed on a FACSCalibur flow cytometer (Becton‑Dickinson), with 500,000 events recorded per sample. The CD3\u003csup\u003e+\u003c/sup\u003e lymphocyte population was first identified from the total lymphocyte gate. Within this subset, CD3\u003csup\u003e+\u003c/sup\u003eCD31\u003csup\u003e+\u003c/sup\u003eCD184\u003csup\u003e+\u003c/sup\u003e Tang cells were quantified and expressed both as absolute counts (cells/ml) and as percentage of total CD3\u003csup\u003e+\u003c/sup\u003e T cells.\u003cbr\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContinuous variables are presented as mean \u0026plusmn; standard deviation or median (interquartile range) according to their distribution, and categorical variables as counts and percentages. Correlations between Tang cell levels and cognitive scores (MoCA and MMSE) in the overall cohort were evaluated using Pearson or Spearman correlation coefficients, as appropriate. To compare Tang cell levels between treatment groups while reducing confounding, propensity score matching was performed. The propensity score was calculated for each participant based on age, body weight and HbA1c, and patients treated with GLP‑1RA+MET were matched to those receiving MET alone using a caliper width equal to 0.2 of the standard deviation of the logit of the propensity score. The balance of covariates after matching was assessed using the standardized difference method.\u003c/p\u003e\n\u003cp\u003eBetween‑group comparisons were carried out using the independent two‑sample t‑test or Mann‑Whitney U test for continuous variables, and the chi‑square test for categorical variables, as appropriate. Variables with non‑normal distribution were log‑transformed before analysis. A multivariable linear regression analysis was performed with MoCA score and MMSE score as the dependent variables and\u0026nbsp;Tang cell counts, age, sex, BMI, HbA1c and diabetes duration as independent variables, to assess whether Tang cells were independently associated with cognitive performance\u003cem\u003e.\u003c/em\u003e A two‑sided P value \u0026lt; 0.05 was considered statistically significant. All analyses were conducted using Stata, version 16.0 (Stata Corp, College Station, TX, USA).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 154 older adults with T2DM were included, 78 treated with GLP-1RA plus metformin (GLP-1RA\u0026nbsp;+\u0026nbsp;MET group) and 76 with only metformin (MET group). The median age of the overall cohort was 69\u0026nbsp;years, with a median BMI 30.2\u0026nbsp;kg/m\u003csup\u003e2\u003c/sup\u003e, and a median HbA1c level 7.2% (55\u0026nbsp;mmol/mol). Thirty-nine percent of participants were women, and 25% had a previous cardiovascular event. Median MMSE and MoCA scores were 27 and 24, respectively. Baseline clinical and metabolic characteristics are reported in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Clinical and metabolic characteristic of overall participants in the study.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"299\" class=\"fr-table-selection-hover\" style=\"margin-right: calc(36%); width: 64%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N = 154)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e69 (66, 75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eDuration of diabetes, years\u003c/p\u003e\n \u003cp\u003eFemale gender, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e15 (8, 25)\u003c/p\u003e\n \u003cp\u003e60 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eFasting glucose, mg/dl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e114 (101, 141)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eHbA1c, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e7.2 (7.0, 7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eHbA1c, mmol/mol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e55 (53, 60)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eWeight, Kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e83.5 (75, 95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eBMI, Kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eWC, cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e30.2 (27.7, 33)\u003c/p\u003e\n \u003cp\u003e100 (90, 105)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eSBP, mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e130 (120, 140)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eDBP, mmHg\u003c/p\u003e\n \u003cp\u003eHR, bpm/min\u003c/p\u003e\n \u003cp\u003eTotal Cholesterol, mg/dl\u003c/p\u003e\n \u003cp\u003eHDL-Cholesterol, mg/dl\u003c/p\u003e\n \u003cp\u003eLDL- Cholesterol, mg/dl\u003c/p\u003e\n \u003cp\u003eTriglycerides, mg/dl\u003c/p\u003e\n \u003cp\u003eCreatinine, mg/dl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e80 (75, 80)\u003c/p\u003e\n \u003cp\u003e75 (68, 84)\u003c/p\u003e\n \u003cp\u003e157 (135, 181)\u003c/p\u003e\n \u003cp\u003e49 (42, 62)\u003c/p\u003e\n \u003cp\u003e81 (68, 108)\u003c/p\u003e\n \u003cp\u003e107 (77, 150)\u003c/p\u003e\n \u003cp\u003e0.86 (0.7, 1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eeGFR, ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eUACR, mg/g\u003c/p\u003e\n \u003cp\u003eCRP, mg/L\u003c/p\u003e\n \u003cp\u003eDiabetic retinopathy, n (%)\u003c/p\u003e\n \u003cp\u003eDiabetic kidney disease, n (%)\u003c/p\u003e\n \u003cp\u003eDiabetic neuropathy, n (%)\u003c/p\u003e\n \u003cp\u003ePrior cardiovascular event, n (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e79 (64, 89)\u003c/p\u003e\n \u003cp\u003e10 (8, 50)\u003c/p\u003e\n \u003cp\u003e1 (0.6, 1.7)\u003c/p\u003e\n \u003cp\u003e34 (22)\u003c/p\u003e\n \u003cp\u003e24 (15)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 18 (16)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 39 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eMoCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e27 (24.4, 29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55.6186%;\"\u003e\n \u003cp\u003eMMSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44.125%;\"\u003e\n \u003cp\u003e24 (19, 28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 299px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e BMI, body mass index; WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; HR, heart rate; HDL, high-density lipoprotein; LDL, low-density lipoprotein; eGFR, estimated glomerular filtration rate; UACR, urinary albumin-to-creatinine ratio; CRP, C-reactive protein; MoCA, Montreal Cognitive Assessment; MMSE, Mini-Mental State Examination; HbA1c, glycated hemoglobin.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn the overall cohort, circulating Tang cell levels showed a significant positive correlation with cognitive performances. Higher Tang cells counts were associated with higher MoCA (r = 0.423, p \u0026lt; 0.001) and higher MMSE (r = 0.428, p \u0026lt; 0.001) scores (Figure 1).\u003c/p\u003e\n\u003cp\u003eTo assess whether this association was independent of major clinical variables, a multivariable linear regression model was fitted with MoCA score and MMSE score as the dependent variables and Tang cell counts, age, sex, BMI, HbA1c and diabetes duration as independent. In the model with MoCA as the dependent variable, Tang cell counts remained independently and positively associated with cognitive performance (\u0026beta; = 0.424; 95% CI 0.23\u0026ndash;0.62; P \u0026lt; 0.001). Age was independently and inversely associated with MoCA scores (\u0026beta; = \u0026minus;0.373; 95% CI \u0026minus;0.59 to \u0026minus;0.16; P = 0.001). In contrast, sex (\u0026beta; = 0.018; P = 0.881), BMI (\u0026beta; = \u0026minus;0.146; P = 0.251), and diabetes duration (\u0026beta; = 0.141; P = 0.186) were not independently associated with MoCA scores (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Multivariable linear regression analyses assessing the independent association between MoCA score and Tang cells count, age, sex, BMI and diabetes duration.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"613\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta; coefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003eTang cells count (cells/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 153px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e-0.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 153px;\"\u003e\n \u003cp\u003e-0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 153px;\"\u003e\n \u003cp\u003e- 0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.881\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e-0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 153px;\"\u003e\n \u003cp\u003e-0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003eDiabetes duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 153px;\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.186\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 332px;\"\u003e\n \u003cp\u003eR\u0026sup2; = 0.421, Adjusted R\u0026sup2; = 0.401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn the model with MMSE as the dependent variable, Tang cell counts were the only variable independently and positively associated with cognitive performance (\u0026beta; = 0.390; 95% CI 0.18\u0026ndash;0.60; P \u0026lt; 0.001). None of the other covariates showed a significant independent association with MMSE scores (age, \u0026beta; = \u0026minus;0.176; P = 0.140; sex, \u0026beta; = \u0026minus;0.173; P = 0.193; BMI, \u0026beta; = \u0026minus;0.256; P = 0.066; diabetes duration, \u0026beta; = 0.111; P = 0.336) (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Multivariable linear regression analyses assessing the independent association between MMSE score and Tang cells count, age, sex, BMI and diabetes duration.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"613\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta; coefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003eTang cells count (cells/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 153px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e-0.176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 153px;\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e-0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 153px;\"\u003e\n \u003cp\u003e- 0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.193\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e-0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 153px;\"\u003e\n \u003cp\u003e-0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003eDiabetes duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 153px;\"\u003e\n \u003cp\u003e-0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.336\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 332px;\"\u003e\n \u003cp\u003eR\u0026sup2; = 0.321, Adjusted R\u0026sup2; = 0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAfter matching patients in the two groups for age, weight and HbA1c we obtained 40 patients in the GLP-1RA + MET group and 40 in the MET Group (Supplementary Table S1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 2 shows the data for CD3\u003csup\u003e+\u003c/sup\u003e T cells and CD3\u003csup\u003e+\u003c/sup\u003e CD31\u003csup\u003e+\u003c/sup\u003eCD184\u003csup\u003e+\u003c/sup\u003e Tang cells levels across the two patient groups. Patients in the GLP-1RA + MET group exhibited significantly higher levels of CD3\u003csup\u003e+\u003c/sup\u003e T cells, in absolute count but not in percentage, compared to those in the MET group [620,000 (467,000\u0026ndash;727,000) vs. 480,000 (363,000\u0026ndash;635,000) cells/ml, P = 0.028; and 70% (57\u0026ndash;74) vs. 68% (61\u0026ndash;71), P = 0.207] (Panel A and C). Similarly, levels of circulating CD3\u003csup\u003e+\u003c/sup\u003e CD31\u003csup\u003e+\u003c/sup\u003eCD184\u003csup\u003e+\u003c/sup\u003e Tang cells were markedly more elevated, both in absolute count and in percentage, in the GLP-1RA + MET group [115,000 (94,000\u0026ndash;134,000) vs. 76,000 (54,000\u0026ndash;102,000) cells/ml, P \u0026lt; 0.001; and 21.1% (16\u0026ndash;28.6) vs. 17% (13.4\u0026ndash;18.3), P = 0.004] than MET group (Panel B and D).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this cross-sectional study, circulating Tang cells were positively associated with cognitive performance in older adults with T2DM. In addition, treatment with GLP-1RAs in combination with metformin was associated with significantly higher Tang cell levels compared with metformin alone. Circulating Tang cell counts were independently and positively associated with cognitive performance, as assessed by both MoCA and MMSE, after adjustment for major clinical and metabolic confounders. The stronger association observed with MoCA, together with the independent inverse effect of age, is consistent with the higher sensitivity of this tool in detecting early cognitive impairment. The lack of independent associations with BMI, glycemic control, and diabetes duration suggests that Tang cells may reflect a distinct pathophysiological pathway, possibly related to endothelial dysfunction and microvascular health. These findings suggest that Tang cells may reflect a specific aspect of neurovascular health that is particularly relevant in the aging diabetic population.\u003c/p\u003e\n\u003cp\u003eCognitive impairment in older adults with T2DM is increasingly recognized as the result of complex interactions between metabolic dysregulation, vascular damage, and age-related neurodegenerative processes [19]. Endothelial dysfunction and impaired microvascular repair play a central role in this context. Our results support the hypothesis that angiogenic competence, as reflected by circulating Tang cell levels, may represent an important determinant of cognitive health in this vulnerable population.\u003c/p\u003e\n\u003cp\u003ePrevious studies have shown that GLP-1RA therapy is associated with improved endothelial function, increased circulating endothelial progenitor cells (EPCs), and better cognitive performance in individuals with T2DM [14]. EPCs are bone marrow\u0026ndash;derived cells that contribute to vascular repair and maintenance, and their reduction has been associated with increased cardiovascular risk and cognitive impairment in diabetes [20,21]. In particular, circulating CD34⁺KDR⁺CD133⁺ EPCs have been identified as independent predictors of cognitive function in patients with T2DM [14]. In line with these observations, the present study demonstrates that higher levels of CD3⁺CD31⁺CD184⁺ Tang cells are associated with better cognitive performance, further supporting the close relationship between endothelial repair mechanisms and brain health.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTang cells play a key role in vascular homeostasis by supporting EPC function and promoting endothelial repair. Reduced Tang cell levels have been reported in several conditions characterized by endothelial dysfunction, including rheumatoid arthritis [16], hypertension-related cerebral small vessel disease [17], and T2DM [18]. Neuroimaging studies have linked impaired angiogenic activity to markers of cerebral small vessel disease, such as white matter hyperintensities, which are highly prevalent in older adults and are known contributors to cognitive decline [10]. Although cognitive consequences may not always be evident in early stages, these findings suggest that angiogenic dysfunction may contribute to the progression of neurovascular damage over time.\u003c/p\u003e\n\u003cp\u003eIn a previous study involving 41 patients with T2DM and matched healthy controls, patients with diabetes exhibited reduced Tang cell levels compared to the controls [18]. Treatment with the DPP-4 inhibitor linagliptin over 26 weeks led to a significant increase in CD3\u003csup\u003e+\u003c/sup\u003e Tang cells, further supporting the potential for pharmacological interventions to restore Tang levels and vascular repair mechanisms [18]. In our current study, the percentage of Tang cells observed in the GLP-1RA + MET group [21.1% (16\u0026ndash;28.6)] closely mirrors the levels found in healthy controls from this last study [20.4% (16.6\u0026ndash;27.3)] [18]. This suggests that\u0026nbsp;GLP-1RA therapy\u0026nbsp;may help restore circulating Tang cell levels to a range comparable to that of healthy individuals, potentially contributing to improved vascular health.\u003c/p\u003e\n\u003cp\u003eThe mechanisms underlying the association between GLP-1RA therapy and increased Tang cell levels remain to be fully clarified. However, GLP-1RAs exert pleiotropic effects beyond glycemic control, including anti-inflammatory actions and improvements in endothelial function, which may favor the mobilization or survival of angiogenic immune cells [22-23]. The higher circulating Tang cell levels observed in GLP-1RA\u0026ndash;treated patients are consistent with a role for these agents in enhancing endogenous vascular repair processes.\u003c/p\u003e\n\u003cp\u003eStrengths of this study include the use of a comprehensive battery of validated tests for the evaluation of cognitive functions, the assessment of CD3\u003csup\u003e+\u003c/sup\u003e T-cells and Tang cells by flow cytometry in two homogenous groups of subjects with type 2 diabetes treated with GLP-1RA + MET or MET alone, and the relatively long duration of GLP-1RA treatment. The cross-sectional nature of the study represents the main limit as it does not allow to firmly establish causal relationship between variables. Longitudinal studies are needed to determine the long-term impact of GLP-1RA therapy on both Tang cell levels and cognitive health.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this cross-sectional study highlights a strong association between circulating Tang cells levels and cognitive performances in older adults with type 2 diabetes. Additionally, after matching patients for age, weight and HbA1c, subjects treated with GLP-1RA combined to metformin exhibited significantly higher levels of circulating levels of angiogenic T cells as compared to those treated with metformin alone. This finding suggests that increased circulating Tang cells may contribute to protective role in cognitive health, representing one potential mechanism by which GLP-1RA therapy exerts its neuroprotective benefits. Further longitudinal studies are needed to better understand the link between GLP-1RA and neurovascular health.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions statements:\u0026nbsp;\u003c/strong\u003eAll authors contributed to the brief report conception and draft. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDal Canto E, Ceriello A, Ryd\u0026eacute;n L, et al. Diabetes as a cardiovascular risk factor: an overview of global trends of macro- and microvascular complications. Eur J Prev Cardiol. 2019;26(2 Suppl):32. doi:10.1177/2047487319878371.\u003c/li\u003e\n\u003cli\u003eAmerican Diabetes Association Professional Practice Committee. Older adults: standards of care in diabetes\u0026mdash;2026. Diabetes Care. 2026;49(Suppl 1):S277\u0026ndash;S296. doi:10.2337/dc26-S013.\u003c/li\u003e\n\u003cli\u003eLongo M, Bellastella G, Maiorino MI, Meier JJ, Esposito K, Giugliano D. Diabetes and aging: from treatment goals to pharmacologic therapy. Front Endocrinol (Lausanne). 2019;10:45. doi:10.3389/fendo.2019.00045.\u003c/li\u003e\n\u003cli\u003eGudala K, Bansal D, Schifano F, Bhansali A. Diabetes mellitus and risk of dementia: a meta-analysis of prospective observational studies. J Diabetes Investig. 2013;4(6):640\u0026ndash;650. doi:10.1111/jdi.12087.\u003c/li\u003e\n\u003cli\u003eKan W, Qu M, Wang Y, Zhang X, Xu L. A review of type 2 diabetes mellitus and cognitive impairment.Front Endocrinol (Lausanne). 2025;16:1624472. doi:10.3389/fendo.2025.1624472.\u003c/li\u003e\n\u003cli\u003eBiessels GJ, Despa F. Cognitive decline and dementia in diabetes mellitus: mechanisms and clinical implications. Nat Rev Endocrinol. 2018;14(10):591\u0026ndash;604. doi:10.1038/s41574-018-0048-7.\u003c/li\u003e\n\u003cli\u003eVanhoutte PM, Shimokawa H, Feletou M, Tang EH. Endothelial dysfunction and vascular disease: a 30th anniversary update. Acta Physiol (Oxf). 2017;219(1):22\u0026ndash;96. doi:10.1111/apha.12646.\u003c/li\u003e\n\u003cli\u003eLacolley P, Avril S, G\u0026aacute;ll T, et al. Aging in the vascular system: lessons from mechanobiology, computational approaches, and oxidative stress. Cardiovasc Res. 2025;121(10):1566\u0026ndash;1581. doi:10.1093/cvr/cvaf137.\u003c/li\u003e\n\u003cli\u003eKul A, Ozturk N, Kurt AK, Arslan Y. Detection of angiogenic T cells and endothelial progenitor cells in Beh\u0026ccedil;et disease and determination of their relationship with disease activity. Life (Basel). 2023;13(6):1259. doi:10.3390/life13061259.\u003c/li\u003e\n\u003cli\u003eCallahan CM, Apostolova LG, Gao S, et al. Novel markers of angiogenesis in the setting of cognitive impairment and dementia. J Alzheimers Dis. 2020;75(3):959\u0026ndash;969. doi:10.3233/JAD-191293.\u003c/li\u003e\n\u003cli\u003eGiugliano D, Scappaticcio L, Longo M, et al. GLP-1 receptor agonists and cardiorenal outcomes in type 2 diabetes: an updated meta-analysis of eight CVOTs. Cardiovasc Diabetol. 2021;20(1):189. doi:10.1186/s12933-021-01366-8.\u003c/li\u003e\n\u003cli\u003eGiugliano D, Longo M, Signoriello S, et al. The effect of DPP-4 inhibitors, GLP-1 receptor agonists and SGLT2 inhibitors on cardiorenal outcomes: a network meta-analysis of 23 CVOTs. Cardiovasc Diabetol. 2022;21(1):42. doi:10.1186/s12933-022-01474-z\u003c/li\u003e\n\u003cli\u003eSabbagh MN, Cummings JL, Ballard C, et al. Repurposing glucagon-like peptide-1 receptor agonists for the treatment of neurodegenerative disorders. Nat Aging. 2025. doi:10.1038/s43587-025-01029-3.\u003c/li\u003e\n\u003cli\u003eLongo M, Di Meo I, Caruso P, et al. Circulating levels of endothelial progenitor cells are associated with better cognitive function in older adults with glucagon-like peptide-1 receptor agonist-treated type 2 diabetes. Diabetes Res Clin Pract. 2023;200:110688. doi:10.1016/j.diabres.2023.110688.\u003c/li\u003e\n\u003cli\u003eHur J, Yang HM, Yoon CH, et al. Identification of a novel role of T cells in postnatal vasculogenesis: characterization of endothelial progenitor cell colonies. Circulation. 2007;116(15):1671\u0026ndash;1682. doi:10.1161/CIRCULATIONAHA.107.694778.\u003c/li\u003e\n\u003cli\u003eRodr\u0026iacute;guez-Carrio J, Alperi-L\u0026oacute;pez M, L\u0026oacute;pez P, et al. Angiogenic T cells are decreased in rheumatoid arthritis patients. Ann Rheum Dis. 2015;74(5):921\u0026ndash;927. doi:10.1136/annrheumdis-2013-204250.\u003c/li\u003e\n\u003cli\u003eRouhl RP, Mertens AE, van Oostenbrugge RJ, et al. Angiogenic T-cells and putative endothelial progenitor cells in hypertension-related cerebral small vessel disease. Stroke. 2012;43(1):256\u0026ndash;258. doi:10.1161/STROKEAHA.111.632208.\u003c/li\u003e\n\u003cli\u003ede Boer SA, Reijrink M, Abdulahad WH, et al. 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Effect of a Mediterranean diet on endothelial progenitor cells and carotid intima-media thickness in type 2 diabetes: follow-up of a randomized trial. Eur J Prev Cardiol. 2017;24(4):399\u0026ndash;408. doi:10.1177/2047487316676133.\u003c/li\u003e\n\u003cli\u003eRos-Madrid I, Cano-M\u0026aacute;rmol R, Ferrer-Gomez M, Ramos-Molina B. Anti-inflammatory properties of GLP-1 receptor agonists and other ancillary benefits from a pharmacological perspective. Can J Physiol Pharmacol. 2025;103(12):369\u0026ndash;377. doi:10.1139/cjpp-2025-0148.\u003c/li\u003e\n\u003cli\u003eCaruso P, Maiorino MI, Longo M, et al. Liraglutide improves peripheral perfusion and markers of angiogenesis and inflammation in people with type 2 diabetes and peripheral artery disease: an 18-month follow-up of a randomized clinical trial. Diabetes Obes Metab. 2025;27(7):3891\u0026ndash;3900. doi:10.1111/dom.16419.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Type 2 diabetes, cognitive function, angiogenic T cells, GLP-1RA, endothelial dysfunction","lastPublishedDoi":"10.21203/rs.3.rs-8814937/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8814937/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Older adults with type 2 diabetes mellitus (T2DM) are at high risk of both cardiovascular complications and cognitive decline, with major implications for independence and self-management. Endothelial dysfunction and impaired angiogenic capacity may play a key role. This study investigated the association between circulating angiogenic T cells (Tang cells) and cognitive function in older adults with T2DM and explored the potential impact of glucagon‑like peptide‑1 receptor agonist (GLP‑1RA) therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A cross-sectional study was conducted on 154 T2DM patients aged 60–80 years, treated either with GLP-1 receptor agonist (GLP-1RA) plus metformin or metformin alone. Cognitive function was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Circulating CD3\u003csup\u003e+\u003c/sup\u003eCD31\u003csup\u003e+\u003c/sup\u003eCXCR4\u003csup\u003e+\u003c/sup\u003e Tang cells were quantified by flow cytometry. Propensity score matching was applied to control for age, body weight and HbA1c.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e In the overall cohort, higher Tang cell levels were significantly associated with better cognitive performance (MoCA, r = 0.423; MMSE, r = 0.428; both P \u0026lt; 0.001). After matching, 40 patients in each treatment group were included in the comparative analysis. The GLP-1RA+MET group showed significantly higher circulating Tang cell levels than the MET group, both in absolute counts and as percentage of CD3\u003csup\u003e+\u003c/sup\u003e T cells (P \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Circulating Tang cell levels are positively associated with cognitive function in older adults with T2DM. GLP‑1RA therapy is associated with higher Tang cell levels compared with metformin alone, suggesting a potential role of enhanced endothelial repair in mitigating diabetes‑related cognitive impairment in older age.\u003c/p\u003e","manuscriptTitle":"Angiogenic T cells and cognitive function in older adults with type 2 diabetes treated with GLP-1 receptor agonists","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-24 12:08:48","doi":"10.21203/rs.3.rs-8814937/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-15T16:55:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-15T16:44:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"142906390799060865353162258041899797923","date":"2026-03-04T19:06:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-18T18:13:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-17T12:50:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-09T04:34:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Aging Clinical and Experimental Research","date":"2026-02-07T10:48:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"302182ca-591d-43dd-bb07-84f9d07611f6","owner":[],"postedDate":"February 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T13:25:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-24 12:08:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8814937","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8814937","identity":"rs-8814937","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}