Elevated whole blood viscosity is associated with an impaired insulin-stimulated myocardial glucose metabolism

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Impaired myocardial glucose metabolism is a risk factor for CVD. Whether an increased WBV is associated with myocardial insulin resistance is still undefined. Methods : To elucidate this issue, we evaluated the association between WBV and myocardial glucose metabolic rate (MRGlu) in 57 individuals with different glucose tolerance status. Myocardial MRGlu was assessed using dynamic cardiac 18 F-FDG PET combined with euglycemic hyperinsulinemic clamp. WBV was calculated using a validated equation including hematocrit and plasma proteins: WBV = [0.12 x h] + [0.17 x (p-2.07)], where h is the hematocrit (%) and p the plasma proteins (g/dl). Results : As compared with individuals in the highest myocardial MrGlu tertile, those in the lowest tertile showed an age-adjusted increase in WBV (5.54 ± 0.3 cP vs 6.13 ± 0.4 cP respectively; P=0.001), hematocrit (39.1 ± 3.1% vs 43.2 ± 3.7% respectively; P=0.004), and total proteins (7.06 ± 0.3 g/l vs 7.60 ± 0.3 g/l respectively; P<0.0001). WBV was negatively correlated with myocardial MRGlu (r= -0.416, P=0.001). In a stepwise multivariate regression analysis, including several cardiovascular risk factors, the only variables significantly associated with myocardial MrGlu were WBV (b -0.505; P<0.0001), fasting insulin (b -0.346; P=0.004), fasting plasma glucose (b -0.287; P=0.01), and sex (b 0.280; P=0.003) explaining the 69.6% of its variation. Conclusions : To the best of our knowledge, the current study was the first to show an association between WBV and myocardial glucose metabolism in individuals with a broad spectrum of glucose tolerance. blood viscosity myocardial glucose metabolism cardiovascular disease type 2 diabetes cardiac 18F-FDG PET hematocrit insulin resistance Figures Figure 1 Figure 2 Introduction Blood viscosity is a measure of the intrinsic resistance of blood to flow in vessels, and is produced by the frictional interactions between the main blood components including plasma, plasma proteins, and red blood cells ( 1 ). There is evidence indicating that raised whole blood viscosity (WBV) is associated with cardio-metabolic risk factors including dyslipidemia, prediabetes/type 2 diabetes (T2DM), hypertension, obesity, and metabolic syndrome ( 13 – 16 ), and target organ damage such as sub-clinical carotid atherosclerosis, vascular stiffness, reduced myocardial mechano-energetic efficiency and left ventricular hypertrophy ( 2 – 12 ) leading to higher risk of incident cardiovascular (CV) events ( 1 ). Impaired myocardial glucose metabolism is an early alteration observed in both individuals at increased risk of T2DM and in patients with overt T2DM ( 24 – 28 ). Furthermore, myocardial insulin resistance is an independent predictor of CV events in individuals with coronary heart disease (CHD), and has been associated with early carotid, aortic and coronary atherosclerosis ( 29 – 32 ). Previous studies have shown an association between increased WBV and impaired whole-body insulin sensitivity, assessed by euglycemic-hyperinsulinemic clamp technique ( 33 – 35 ) likely due to a reduced glucose and insulin delivery to metabolically active tissues. Whether an increased WBV is associated with myocardial insulin resistance is still undefined. To this purpose, we evaluated the relationship between WBV and insulin-stimulated myocardial glucose metabolic rate (MRGlu) assessed using cardiac dynamic PET with 18 F-Fluorodeoxyglucose ( 18 F-FDG) combined with euglycemic-hyperinsulinemic clamp, in individuals with a broad spectrum of glucose tolerance. Methods Study participants The study cohort comprised 57 subjects participating in the CATAnzaro MEtabolic RIsk factors (CATAMERI), an ongoing observational study recruiting adult individuals with one or more cardio-metabolic risk factors recruited at a referral hospital of the University “Magna Graecia” of Catanzaro ( 31 , 36 ). Eligible subjects were recruited according to the following inclusion criteria: age between 30 and 70 years, and positivity for one or more cardio-metabolic risk factors including family history of diabetes, impaired fasting glucose, hypertension, dyslipidemia, and overweight/obesity. Exclusion criteria were type 1 diabetes, end-stage renal disease, previous CVD on the basis of medical history, resting electrocardiogram and stress test or myocardial scintigraphy for individuals with T2DM, history of atrial fibrillation or other arrhythmias, right and left bundle branch block, dyssynchrony in ventricular contraction, valvular heart disease, liver cirrhosis, history of malignant or autoimmune diseases, acute or chronic infections, history of alcohol or drug abuse and treatment with drugs known to influence glucose tolerance such as steroids and estro-progestins and medicaments affecting heart function including beta blockers and antiarrhythmic drugs. All subjects underwent anthropometrical evaluation including measurements of body mass index (BMI), waist circumference and body composition by bioelectrical impedance, and assessment of whole-body and cardiac insulin sensitivity. Readings of clinic blood pressure (BP) were measured at 3-minute intervals using a standard sphygmomanometer, and BP values were the average of 3 measurements after a 10-minute period of rest in the supine position. After an overnight fasting, biochemical determinations and a 75g OGTT were performed in individuals with FPG < 126 mg/dl, HbA1c < 6.5% and no history of T2DM. According to the ADA criteria ( 37 ), individuals were classified as having normal glucose tolerance (NGT) when fasting plasma glucose was < 100 mg/dl (5.5 mmol/l), 2-h postload glucose < 140 mg/dl (< 7.77 mmol/l) and HbA1c < 5.7%, prediabetes when fasting plasma glucose was 100–125 mg/dl (5.5–6.9 mmol/l), 2-h postload glucose 140–199 mg/dl (7.77–11.0 mmol/l) or HbA1c 5.7–6.4%, T2DM when fasting plasma glucose was ≥ 126 mg/dl (> 7 mmol/l), 2-h post-load glucose was ≥ 200 mg/dl (> 11.1 mmol/l), HbA1c ≥ 6.5% or in treatment with antidiabetic drugs. On the second day, after 12-h fasting, all subjects underwent 18 F-FDG PET scan combined with euglycemic hyperinsulinemic clamp. The study was approved by the Ethics Committee (Comitato Etico Azienda Ospedaliera “Mater Domini”), and informed consent was obtained from each subject in accordance with principles of the Declaration of Helsinki. 18 F-FDG PET scan combined with euglycemic hyperinsulinemic clamp Myocardial glucose metabolic rate (MrGlu) was measured by 18 F-FDG-PET acquired during an euglycemic hyperinsulinemic clamp as previously described ( 28 , 38 ). Subjects received a priming dose of insulin (100 UI/mL) (Humulin R; Eli Lilly) during the initial 10 min to raise the serum insulin concentration acutely (80 mU/m2 × min), and then it was maintained by continuous insulin infusion fixed at 40 mU/m2 × min ( 36 ). The blood glucose level was maintained constant at 90 mg/dl for the next 120 min by infusing 20% glucose at varying rates according to blood glucose measurements performed at 5-min intervals (mean coefficient of variation of blood glucose was < 4%). Glucose metabolized by the whole body (M) was calculated as the mean rate of glucose infusion measured during the last 60 minutes of the clamp examination (steady state) and was expressed as milligrams per minute per kilogram fat-free mass (M FFM ). The 18 F-FDG-PET imaging procedure was performed on a hybrid PET/CT scanner (GE Discovery ST8- 2D PET scanner), starting 60 minutes after the insulin infusion. A 60-min dynamic acquisition was started simultaneously with the intravenous injection of 370 MBq 18 F-FDG, according to the following time frame sampling: 8 x 15s, 2 x 30s, 2 x 120s, 1 x 180s, 6 x 300s, 2 x 600s ( 39 ). PET images were reconstructed in a 128 x 128 matrix using a OSEM algorithm, and corrected for decay and attenuation based on co-registered CT. The insulin-glucose infusion continued during the entire PET acquisition. The estimation of myocardial MrGlu was performed by Patlak compartmental modelling ( 40 ), using the graphical tool specific for cardiac images analysis (PCARD) implemented in PMOD Software platform (Version 3.806) ( 40 ). In PCARD, the full dynamic study is used for MRGlu calculation, and the arterial input function is extracted from a volume of interest (VOI) semi-automatically placed in the left ventricular cavity ( 41 ). Whole blood viscosity Whole blood viscosity (WBV) at 208 s − 1 of shear rate was calculated by a previously validated equation that takes into account hematocrit and plasma proteins ( 6 ): WBV = [0.12 × h ] + [0.17 × ( p -2.07)], where h is hematocrit (%) and p is plasma protein levels (g/dl). Laboratory determinations Plasma glucose, total and HDL cholesterol, and triglycerides were assayed using enzymatic methods (Roche Diagnostics, Mannheim, Germany). HbA1c was measured with high performance liquid chromatography using an NGSP-certified automated analyzer (Adams HA-8160 HbA1c analyzer, Menarini, Italy). Haemoglobin, haematocrit and white blood cell count were analysed using an automated particle counter (Siemens Healthcare Diagnostics ADVIA® 120/2120 Haematology System). Serum insulin levels were determined by a chemiluminescence-based assay (Immulite®, Siemens Healthcare GmbH, Erlangen, Germany). Fibrinogen was measured by an automated nephelometric technology using the BNTMII System analyzer (Siemens Healthcare, Italy). Statistical analyses Triglycerides levels were natural log transformed for statistical analyses due to their skewed distribution. Continuous variables are expressed as means ± SD. Categorical variables were compared by χ2 test. A general linear model with post hoc Bonferroni correction for multiple comparisons was used to compare differences of continuous variables between groups. Relationships between variables were determined by Pearson’s correlation coefficient (r). Stepwise multivariate regression analysis was run to determine the independent contributors of myocardial glucose metabolic rate. For all analyses a P value < 0.05 was considered to be statistically significant. All analyses were performed using SPSS software Version 29 for Mac. Results Clinical characteristics of the three groups of individuals stratified into tertiles according to their insulin-stimulated myocardial MrGlu values are shown in Table 1. Of the 57 recruited individuals, 20 (35.1%) had NGT, 11 (19.3%) had prediabetes, and 26 (45.6%) had T2DM. No differences were observed in sex distribution. Subjects in the lowest tertile of insulin-stimulated myocardial MrGlu (range myocardial MrGlu 0.1-16.3 mmol/min/100g) were older and exhibited higher BMI than individuals in the highest tertile (range myocardial MrGlu 26.3-43 mmol/min/100g) (Table 1). Cardiovascular risk factors and metabolic parameters in individuals stratified according to insulin-stimulated myocardial MrGlu values As shown in Table 1, no differences between the three groups were observed in waist circumference, lipid profile, fasting plasma glucose and diastolic blood pressure (Table 1). Individuals in the lowest tertile showed an age-adjusted increase in systolic blood pressure, resting heart rate, fasting insulin and HbA1c, and a lower whole-body insulin-stimulated glucose disposal as compared with subjects in the highest tertile (3.16±1.8 vs 8.4±7.7 mg/min x Kg FFM, P=0.02) as compared with individuals in the highest tertile (Table 1). Furthermore, a higher proportion of individuals in the lowest tertile had prediabetes or T2DM than individuals in the highest tertile (Table 1). Hemorheological parameters in individuals stratified according to insulin-stimulated myocardial MrGlu values Hemorheological parameters of the study individuals stratified into tertiles according to insulin-stimulated myocardial MrGlu values are shown in Table 2. As compared with individuals in the highest tertile, those in the lowest tertile showed an age-adjusted increase in WBV (5.54 ± 0.3 cP vs 6.13 ± 0.4 cP respectively; P=0.001), hematocrit (39.1 ± 3.1% vs 43.2 ± 3.7% respectively; P=0.004), total proteins (7.60 ± 0.3 g/l vs 7.06 ± 0.2 g/l respectively; P<0.0001) and white blood cells (WBC) count (7868 ± 1817 x10 9 /l vs 6123 ± 917 x10 9 /l respectively; P=0.006) (Table 2). Association between insulin-stimulated myocardial MrGlu, cardiovascular risk factors and hemorheological parameters In a univariate analysis, WBV was negatively correlated with myocardial MRGlu (r= -0.416, P=0.001), whole-body insulin-stimulated glucose disposal (M FFM ) (r= -0.323, P=0.01), and positively correlated with fasting plasma glucose (r= 0.302, P=0.02), waist circumference (r= 0.414, P=0.001), systolic (r= 0.406, P=0.002), and diastolic blood pressure (r= 0.333, P=0.01) (Figure 1). Furthermore, myocardial MRGlu was negatively correlated with waist circumference (r= -0.378, P=0.004), fasting plasma glucose (r= -0.354, P=0.007), HbA1c (r= -0.489, P<0.0001), hematocrit (r= -0.353, P=0.007), fibrinogen (r= -0.329, P=0.01), fasting plasma insulin (r= -0.353, P=0.008), and positively correlated with whole-body insulin-stimulated glucose disposal (r= 0.441, P=0.001) (Figure 2). In order to evaluate the independent contributor of myocardial MRGlu, we performed a stepwise multivariate regression analysis running a model including age, sex, BMI, waist circumference, blood pressure, lipid profile, fasting plasma glucose, HbA1c, WBV, fasting insulin, and fibrinogen. The only variables significantly associated with myocardial MrGlu were whole blood viscosity (b -0.505; P<0.0001), fasting insulin (b -0.346; P=0.004), fasting plasma glucose (b -0.287; P=0.01), and sex(b 0.280; P=0.003) explaining the 69.6% of its variation (Table 3). Discussion In this cross-sectional study, we show that whole blood viscosity is associated with myocardial insulin resistance, estimated using cardiac dynamic 18 F-FDG-PET combined with euglycemic-hyperinsulinemic clamp, in individuals with different degrees of glucose tolerance and no history of coronary heart disease. These findings were strengthened by results of a stepwise multivariate regression analysis performed in order to investigate whether whole blood viscosity was associated with decreased myocardial MrGlu independently of well-established cardio-metabolic risk factors including age, sex, BMI, waist circumference, blood pressure, lipid profile, fasting plasma glucose, HbA1c, WBV, fasting plasma insulin, and fibrinogen. We found that WBV was a major determinant of myocardial MrGlu independently of cardiovascular risk factors known to be associated with myocardial MrGlu explaining the 69.6% of its variation. Our study extends previous findings showing an association between WBV and with whole-body insulin resistance measured by either euglycemic-hyperinsulinemic clamp in small numbers of subjects ( 33 – 35 ) or proxy indices of insulin resistance in larger samples ( 14 , 15 , 42 , 43 ). However, to the best of our knowledge, the current study was the first to show an association between WBV and myocardial glucose metabolism in individuals with a broad spectrum of glucose tolerance. There is evidence that increased blood viscosity is an independent predictor of ischemic heart disease and stroke in the general population ( 1 ). Furthermore, blood viscosity has been shown to be associated with target organ damage such as subclinical atherosclerosis, vascular stiffness, decrease of myocardial mechano-energetic efficiency, and left ventricular hypertrophy ( 2 – 12 ). Myocardial insulin resistance is a condition related to an unfavorable cardiometabolic risk profile and early carotid, aortic and coronary atherosclerosis, and has been shown to be a predictor of CV events ( 29 – 32 ). Moreover, previous studies have demonstrated that impaired myocardial glucose metabolism is associated with reduced myocardial mechano-energetic efficiency, and increased cardiac workload ( 31 , 37 ), both alterations linked to the development of heart failure and CV events ( 45 , 46 ). Taken together, these data support the idea that reduced myocardial glucose metabolism may represent one of the pathophysiologic mechanisms contributing to the increased risk of CV disease observed in individuals with increased WBV. The mechanism by which WBV negatively affect myocardial glucose uptake remains to be fully established. Elevated whole blood viscosity and high hematocrit, his major determinant, are associated to peripheral insulin resistance and impaired blood flow ( 15 , 43 , 47 ). Decreased blood flow might affect myocardial glucose metabolism by limiting delivery of glucose and, consequently, myocardial glucose uptake ( 15 , 43 , 47 ). Furthermore, a reduction in whole-body glucose uptake causes an increase in circulating glucose levels leading to increased insulin secretion and compensatory hyperinsulinemia. On the other hand, hyperinsulinemia may cause vasoconstriction via sympathetic neural activation, which, in turn, would lead to hemoconcentration by increasing hematopoiesis, and hematocrit and, thereby, increased whole blood viscosity ( 43 , 47 ). This study has several strengths that merit considerations. A main strength is the use of gold standard methods to assess myocardial glucose metabolism by cardiac FDG PET combined with the euglycemic-hyperinsulinemic clamp technique, which allows the valuation of insulin-stimulated myocardial glucose uptake under uniform experimental conditions of euglycemia and physiological hyperinsulinemia ( 29 , 48 ). Moreover, glucose tolerance was accurately assessed using FPG, 2 h post-load glucose levels during an OGTT, and HbA1c according to ADA criteria thus excluding any potential misclassification of participants ( 37 ). Additionally, all tests including anthropometric measures, OGTT, and 18 F-FGD PET scan combined with euglycemic hyperinsulinemic clamp were collected by skilled examiners after a standardized training, who were blinded to the clinical data of the study participants. Nevertheless, some limitations should be taken into account. First, whole blood viscosity has not been directly measured by capillary viscometry. However, we estimated whole blood viscosity using an indirect measure that has been previously validated, and is suitable in clinical practice and large observational studies ( 6 ). Moreover, this analysis includes only White individuals aging between 30 and 70 years with at least one cardiovascular risk factors attending a referral university hospital, thus limiting the generalizability of the present results to other ethnicities or to the general population. Furthermore, the cross-sectional design of the study precludes causal inferences, and, therefore, no conclusions regarding cause-effect relationships can be made. Additionally, the present findings were observed in an observational study, rather than in a randomized controlled trial thus the results may be subject to residual unknown confounding factors. Conclusions In conclusion, to the best of our knowledge, the current study is the first to show an association between WBV and myocardial glucose metabolism in individuals with a broad spectrum of glucose tolerance. These data support the idea that reduced myocardial glucose metabolism may represent one of the pathophysiologic mechanisms contributing to the increased risk of CV disease observed in individuals with increased WBV. Abbreviations WBV whole blood viscosity T2DM type 2 diabetes mellitus CV cardiovascular CHD coronary heart disease MRGlu myocardial glucose metabolic rate PET positron emission tomography 18 F-FDG 18 F-Fluorodeoxyglucose BMI body mass index BP blood pressure OGTT oral glucose tolerance test FPG fasting plasma glucose ADA American Diabetes Association NGT normal glucose tolerance M FFM Insulin-stimulated glucose disposal corrected for fat-free mass FFM fat-free mass PCARD tool specific for cardiac images analysis VOI volume of interest WBC white blood cells Declarations Ethics approval and consent to participate The study was approved by the Ethics Committee (Comitato Etico Azienda Ospedaliera “Mater Domini”), and informed consent was obtained from each subject in accordance with principles of the Declaration of Helsinki. Consent for publication Not applicable. Availability of data and materials The datasets used and analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research received no external funding. Authors' contributions E.S. designed the study, researched and analyzed data and wrote and edited the manuscript. P.Vi. and P.H.G. analyzed the data from the cardiac PET scans, F.C. performed cardiac PET scans. M.R., T.V.F., M.P., G.C.M., and A.S.. researched data and reviewed the manuscript. P.Ve., G.L.C. and F.A. contributed to the discussion and reviewed the manuscript. G.S. designed the study, analyzed the data, and wrote and reviewed the manuscript. All authors have read and approved the final manuscript. G.S. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. 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Hanley AJ, Retnakaran R, Qi Y, Gerstein HC, Perkins B, Raboud J, et al. Association of hematological parameters with insulin resistance and beta-cell dysfunction in nondiabetic subjects. J Clin Endocrinol Metab. 2009;94:3824-32. Kofoed KF, Carstensen S, Hove JD, Freiberg J, Bangsgaard R, Holm S, et al. Low whole-body insulin sensitivity in patients with ischaemic heart disease is associated with impaired myocardial glucose uptake predictive of poor outcome after revascularisation. Eur J Nucl Med Mol Imaging. 2002;29:991-8. Losi MA, Izzo R, Mancusi C, Wang W, Roman MJ, Lee ET, et al. Depressed myocardial energetic efficiency increases risk of incident heart failure: The Strong Heart Study. J Clin Med. 2019;8:1044. de Simone G, Izzo R, Losi MA, Stabile E, Rozza F, Canciello G, et al. Depressed myocardial energetic efficiency is associated with increased cardiovascular risk in hypertensive left ventricular hypertrophy. J Hypertens. 2016;34:1846–53. Shoelson SE, Lee J, Goldfine AB. Inflammation and insulin resistance. J Clin Invest 2006;116:1793–1801. Gerber BL, Ordoubadi FF, Wijns W, Vanoverschelde JL, Knuuti MJ, Janier M, et al. Positron emission tomography using (18)F-fluoro-deoxyglucose and euglycaemic hyperinsulinaemic glucose clamp: optimal criteria for the prediction of recovery of post-ischaemic left ventricular dysfunction: results from the European Community Concerted Action Multicenter Study on Use of (18)F-Fluoro-Deoxyglucose Positron Emission Tomography for the Detection of Myocardial Viability. Eur Heart J. 2001;22:1691–701. Tables Tables 1 to 3 are available in the Supplementary Files section Additional Declarations No competing interests reported. Supplementary Files Table1.docx Table2.docx Table3.docx Cite Share Download PDF Status: Published Journal Publication published 04 Dec, 2024 Read the published version in Cardiovascular Diabetology → Version 1 posted Editorial decision: Revision requested 16 Oct, 2024 Reviews received at journal 15 Oct, 2024 Reviews received at journal 14 Oct, 2024 Reviews received at journal 13 Oct, 2024 Reviews received at journal 11 Oct, 2024 Reviews received at journal 06 Oct, 2024 Reviewers agreed at journal 25 Sep, 2024 Reviewers agreed at journal 25 Sep, 2024 Reviewers agreed at journal 25 Sep, 2024 Reviewers agreed at journal 24 Sep, 2024 Reviewers agreed at journal 23 Sep, 2024 Reviewers invited by journal 23 Sep, 2024 Editor assigned by journal 23 Sep, 2024 Submission checks completed at journal 23 Sep, 2024 First submitted to journal 21 Sep, 2024 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. 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Succurro","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAs0lEQVRIiWNgGAWjYDADfiA+AMQ8xGuRbIBqIV6PwQEog6AW+RnJDz/z7rknZ3wj9+CBH38YZOwJGn4jzVia51mxsdmNvISDPTxEOMxAIoeNmedAQuK2GzkGhxkkiNAiPwOqZfMMkBYDYrx/A6plgwRISwIxDjvzzFhyzoEEY4kzbwwO9hyQ4OE5QMhh7ckPP7w5kCDH355j/OHHHxt79gaCLkMFEiSqHwWjYBSMglGAFQAAJ9A3wa84J1sAAAAASUVORK5CYII=","orcid":"","institution":"University Magna Graecia of Catanzaro","correspondingAuthor":true,"prefix":"","firstName":"Elena","middleName":"","lastName":"Succurro","suffix":""},{"id":366625436,"identity":"df75347c-6764-4053-a1b8-2b4d9fe7fb44","order_by":1,"name":"Patrizia Vizza","email":"","orcid":"","institution":"University Magna Graecia of Catanzaro","correspondingAuthor":false,"prefix":"","firstName":"Patrizia","middleName":"","lastName":"Vizza","suffix":""},{"id":366625437,"identity":"14e7e87d-16a6-4d5a-bd37-97d6de585811","order_by":2,"name":"Francesco 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Catanzaro","correspondingAuthor":false,"prefix":"","firstName":"Pietro","middleName":"Hiram","lastName":"Guzzi","suffix":""},{"id":366625444,"identity":"6850b8ec-aa51-439d-a012-897e66d63012","order_by":9,"name":"Pierangelo Veltri","email":"","orcid":"","institution":"University of Calabria","correspondingAuthor":false,"prefix":"","firstName":"Pierangelo","middleName":"","lastName":"Veltri","suffix":""},{"id":366625445,"identity":"0e52a8ef-e85d-427f-8927-05e7fe7684d6","order_by":10,"name":"Giuseppe Lucio Cascini","email":"","orcid":"","institution":"University Magna Graecia of Catanzaro","correspondingAuthor":false,"prefix":"","firstName":"Giuseppe","middleName":"Lucio","lastName":"Cascini","suffix":""},{"id":366625446,"identity":"3d0b7d4c-c127-4b0b-826d-b7aa2de32b7e","order_by":11,"name":"Francesco Andreozzi","email":"","orcid":"","institution":"University Magna Graecia of Catanzaro","correspondingAuthor":false,"prefix":"","firstName":"Francesco","middleName":"","lastName":"Andreozzi","suffix":""},{"id":366625447,"identity":"5eb66f25-0a47-4e1f-9438-605143eee21c","order_by":12,"name":"Giorgio Sesti","email":"","orcid":"","institution":"University of Rome-Sapienza","correspondingAuthor":false,"prefix":"","firstName":"Giorgio","middleName":"","lastName":"Sesti","suffix":""}],"badges":[],"createdAt":"2024-09-21 09:29:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5127910/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5127910/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12933-024-02513-7","type":"published","date":"2024-12-04T15:58:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":69236307,"identity":"07d235ab-f52c-4157-bb71-a796794ee1cc","added_by":"auto","created_at":"2024-11-18 09:44:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":145701,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between WBV and insulin-stimulated myocardial MrGlu (a), M\u003csub\u003eFFM\u003c/sub\u003e\u003cstrong\u003e \u003c/strong\u003e(b),\u003cstrong\u003e \u003c/strong\u003efasting plasma glucose (c), waist circumference (d), systolic blood pressure (e), diastolic blood pressure (f).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5127910/v1/789a1869d92ce261a252bee9.png"},{"id":69236306,"identity":"4c05d48d-025b-4709-a4a3-9f4d1914e385","added_by":"auto","created_at":"2024-11-18 09:44:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":150594,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between insulin-stimulated myocardial MrGlu and waist circumference (a), fasting plasma glucose (b), hematocrit (c), fibrinogen (d), M\u003csub\u003eFFM \u003c/sub\u003e(e)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5127910/v1/ad88414ba732cda7618812a3.png"},{"id":70964878,"identity":"54023c7d-208d-4fc4-9405-931294eecb5b","added_by":"auto","created_at":"2024-12-09 16:17:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":637061,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5127910/v1/62e05d52-0d3b-46fe-b21e-546bf1a5599f.pdf"},{"id":69236304,"identity":"58ff9836-3d0d-4ddd-a919-42b042a9322a","added_by":"auto","created_at":"2024-11-18 09:44:02","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18721,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5127910/v1/68136738e1f3c59f75f8b4aa.docx"},{"id":69236305,"identity":"1385f31b-b47b-42ca-8f79-5dd8109d27a8","added_by":"auto","created_at":"2024-11-18 09:44:02","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":22028,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-5127910/v1/a19dc8496510807a0700b853.docx"},{"id":69236309,"identity":"88649e50-5462-4e0e-b23f-785b47b64e54","added_by":"auto","created_at":"2024-11-18 09:44:02","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":15125,"visible":true,"origin":"","legend":"","description":"","filename":"Table3.docx","url":"https://assets-eu.researchsquare.com/files/rs-5127910/v1/0f3b9e058c52abba35435711.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Elevated whole blood viscosity is associated with an impaired insulin-stimulated myocardial glucose metabolism","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBlood viscosity is a measure of the intrinsic resistance of blood to flow in vessels, and is produced by the frictional interactions between the main blood components including plasma, plasma proteins, and red blood cells (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). There is evidence indicating that raised whole blood viscosity (WBV) is associated with cardio-metabolic risk factors including dyslipidemia, prediabetes/type 2 diabetes (T2DM), hypertension, obesity, and metabolic syndrome (\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), and target organ damage such as sub-clinical carotid atherosclerosis, vascular stiffness, reduced myocardial mechano-energetic efficiency and left ventricular hypertrophy (\u003cspan additionalcitationids=\"CR3 CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) leading to higher risk of incident cardiovascular (CV) events (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImpaired myocardial glucose metabolism is an early alteration observed in both individuals at increased risk of T2DM and in patients with overt T2DM (\u003cspan additionalcitationids=\"CR25 CR26 CR27\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Furthermore, myocardial insulin resistance is an independent predictor of CV events in individuals with coronary heart disease (CHD), and has been associated with early carotid, aortic and coronary atherosclerosis (\u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Previous studies have shown an association between increased WBV and impaired whole-body insulin sensitivity, assessed by euglycemic-hyperinsulinemic clamp technique (\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) likely due to a reduced glucose and insulin delivery to metabolically active tissues. Whether an increased WBV is associated with myocardial insulin resistance is still undefined. To this purpose, we evaluated the relationship between WBV and insulin-stimulated myocardial glucose metabolic rate (MRGlu) assessed using cardiac dynamic PET with \u003csup\u003e18\u003c/sup\u003eF-Fluorodeoxyglucose (\u003csup\u003e18\u003c/sup\u003eF-FDG) combined with euglycemic-hyperinsulinemic clamp, in individuals with a broad spectrum of glucose tolerance.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy participants\u003c/h2\u003e \u003cp\u003eThe study cohort comprised 57 subjects participating in the CATAnzaro MEtabolic RIsk factors (CATAMERI), an ongoing observational study recruiting adult individuals with one or more cardio-metabolic risk factors recruited at a referral hospital of the University \u0026ldquo;Magna Graecia\u0026rdquo; of Catanzaro (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Eligible subjects were recruited according to the following inclusion criteria: age between 30 and 70 years, and positivity for one or more cardio-metabolic risk factors including family history of diabetes, impaired fasting glucose, hypertension, dyslipidemia, and overweight/obesity. Exclusion criteria were type 1 diabetes, end-stage renal disease, previous CVD on the basis of medical history, resting electrocardiogram and stress test or myocardial scintigraphy for individuals with T2DM, history of atrial fibrillation or other arrhythmias, right and left bundle branch block, dyssynchrony in ventricular contraction, valvular heart disease, liver cirrhosis, history of malignant or autoimmune diseases, acute or chronic infections, history of alcohol or drug abuse and treatment with drugs known to influence glucose tolerance such as steroids and estro-progestins and medicaments affecting heart function including beta blockers and antiarrhythmic drugs. All subjects underwent anthropometrical evaluation including measurements of body mass index (BMI), waist circumference and body composition by bioelectrical impedance, and assessment of whole-body and cardiac insulin sensitivity. Readings of clinic blood pressure (BP) were measured at 3-minute intervals using a standard sphygmomanometer, and BP values were the average of 3 measurements after a 10-minute period of rest in the supine position. After an overnight fasting, biochemical determinations and a 75g OGTT were performed in individuals with FPG\u0026thinsp;\u0026lt;\u0026thinsp;126 mg/dl, HbA1c\u0026thinsp;\u0026lt;\u0026thinsp;6.5% and no history of T2DM. According to the ADA criteria (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), individuals were classified as having normal glucose tolerance (NGT) when fasting plasma glucose was \u0026lt;\u0026thinsp;100 mg/dl (5.5 mmol/l), 2-h postload glucose\u0026thinsp;\u0026lt;\u0026thinsp;140 mg/dl (\u0026lt;\u0026thinsp;7.77 mmol/l) and HbA1c\u0026thinsp;\u0026lt;\u0026thinsp;5.7%, prediabetes when fasting plasma glucose was 100\u0026ndash;125 mg/dl (5.5\u0026ndash;6.9 mmol/l), 2-h postload glucose 140\u0026ndash;199 mg/dl (7.77\u0026ndash;11.0 mmol/l) or HbA1c 5.7\u0026ndash;6.4%, T2DM when fasting plasma glucose was \u0026ge;\u0026thinsp;126 mg/dl (\u0026gt;\u0026thinsp;7 mmol/l), 2-h post-load glucose was \u0026ge;\u0026thinsp;200 mg/dl (\u0026gt;\u0026thinsp;11.1 mmol/l), HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;6.5% or in treatment with antidiabetic drugs.\u003c/p\u003e \u003cp\u003eOn the second day, after 12-h fasting, all subjects underwent \u003csup\u003e18\u003c/sup\u003eF-FDG PET scan combined with euglycemic hyperinsulinemic clamp.\u003c/p\u003e \u003cp\u003e The study was approved by the Ethics Committee (Comitato Etico Azienda Ospedaliera \u0026ldquo;Mater Domini\u0026rdquo;), and informed consent was obtained from each subject in accordance with principles of the Declaration of Helsinki.\u003c/p\u003e \u003cp\u003e \u003csup\u003e \u003cem\u003e18\u003c/em\u003e \u003c/sup\u003e \u003cem\u003eF-FDG PET scan combined with euglycemic hyperinsulinemic clamp\u003c/em\u003e \u003c/p\u003e \u003cp\u003eMyocardial glucose metabolic rate (MrGlu) was measured by \u003csup\u003e18\u003c/sup\u003eF-FDG-PET acquired during an euglycemic hyperinsulinemic clamp as previously described (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Subjects received a priming dose of insulin (100 UI/mL) (Humulin R; Eli Lilly) during the initial 10 min to raise the serum insulin concentration acutely (80 mU/m2 \u0026times; min), and then it was maintained by continuous insulin infusion fixed at 40 mU/m2 \u0026times; min (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). The blood glucose level was maintained constant at 90 mg/dl for the next 120 min by infusing 20% glucose at varying rates according to blood glucose measurements performed at 5-min intervals (mean coefficient of variation of blood glucose was \u0026lt;\u0026thinsp;4%). Glucose metabolized by the whole body (M) was calculated as the mean rate of glucose infusion measured during the last 60 minutes of the clamp examination (steady state) and was expressed as milligrams per minute per kilogram fat-free mass (M\u003csub\u003eFFM\u003c/sub\u003e).\u003c/p\u003e \u003cp\u003eThe \u003csup\u003e18\u003c/sup\u003eF-FDG-PET imaging procedure was performed on a hybrid PET/CT scanner (GE Discovery ST8- 2D PET scanner), starting 60 minutes after the insulin infusion. A 60-min dynamic acquisition was started simultaneously with the intravenous injection of 370 MBq\u003csup\u003e18\u003c/sup\u003eF-FDG, according to the following time frame sampling: 8 x 15s, 2 x 30s, 2 x 120s, 1 x 180s, 6 x 300s, 2 x 600s (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). PET images were reconstructed in a 128 x 128 matrix using a OSEM algorithm, and corrected for decay and attenuation based on co-registered CT. The insulin-glucose infusion continued during the entire PET acquisition. The estimation of myocardial MrGlu was performed by Patlak compartmental modelling (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), using the graphical tool specific for cardiac images analysis (PCARD) implemented in PMOD Software platform (Version 3.806) (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). In PCARD, the full dynamic study is used for MRGlu calculation, and the arterial input function is extracted from a volume of interest (VOI) semi-automatically placed in the left ventricular cavity (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eWhole blood viscosity\u003c/h3\u003e\n\u003cp\u003eWhole blood viscosity (WBV) at 208 s\u0026thinsp;\u0026minus;\u0026thinsp;1 of shear rate was calculated by a previously validated equation that takes into account hematocrit and plasma proteins (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e): WBV = [0.12 \u0026times; \u003cem\u003eh\u003c/em\u003e] + [0.17 \u0026times; (\u003cem\u003ep\u003c/em\u003e-2.07)], where \u003cem\u003eh\u003c/em\u003e is hematocrit (%) and \u003cem\u003ep\u003c/em\u003e is plasma protein levels (g/dl).\u003c/p\u003e\n\u003ch3\u003eLaboratory determinations\u003c/h3\u003e\n\u003cp\u003ePlasma glucose, total and HDL cholesterol, and triglycerides were assayed using enzymatic methods (Roche Diagnostics, Mannheim, Germany). HbA1c was measured with high performance liquid chromatography using an NGSP-certified automated analyzer (Adams HA-8160 HbA1c analyzer, Menarini, Italy). Haemoglobin, haematocrit and white blood cell count were analysed using an automated particle counter (Siemens Healthcare Diagnostics ADVIA\u0026reg; 120/2120 Haematology System). Serum insulin levels were determined by a chemiluminescence-based assay (Immulite\u0026reg;, Siemens Healthcare GmbH, Erlangen, Germany). Fibrinogen was measured by an automated nephelometric technology using the BNTMII System analyzer (Siemens Healthcare, Italy).\u003c/p\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eTriglycerides levels were natural log transformed for statistical analyses due to their skewed distribution. Continuous variables are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Categorical variables were compared by χ2 test. A general linear model with post hoc Bonferroni correction for multiple comparisons was used to compare differences of continuous variables between groups. Relationships between variables were determined by Pearson\u0026rsquo;s correlation coefficient (r). Stepwise multivariate regression analysis was run to determine the independent contributors of myocardial glucose metabolic rate.\u003c/p\u003e \u003cp\u003eFor all analyses a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to be statistically significant. All analyses were performed using SPSS software Version 29 for Mac.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eClinical characteristics of the three groups of individuals stratified into tertiles according to their insulin-stimulated myocardial MrGlu values are shown in Table 1. Of the 57 recruited individuals, 20 (35.1%) had NGT, 11 (19.3%) had prediabetes, and 26 (45.6%) had T2DM. No differences were observed in sex distribution. Subjects in the lowest tertile of insulin-stimulated myocardial MrGlu (range myocardial MrGlu 0.1-16.3\u0026nbsp;mmol/min/100g) were older and exhibited higher BMI than individuals in the highest tertile (range myocardial MrGlu 26.3-43\u0026nbsp;mmol/min/100g) (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCardiovascular risk factors and metabolic parameters in individuals stratified according to\u0026nbsp;\u003c/em\u003e\u003cem\u003einsulin-stimulated\u003c/em\u003e \u003cem\u003emyocardial MrGlu values\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table 1, no differences between the three groups were observed in waist circumference, lipid profile, fasting plasma glucose and diastolic blood pressure (Table 1). Individuals in the lowest tertile showed an age-adjusted increase in systolic blood pressure, resting heart rate, fasting insulin and HbA1c, and a lower whole-body\u0026nbsp;insulin-stimulated glucose disposal as compared with subjects in the highest tertile (3.16±1.8 vs 8.4±7.7 mg/min x Kg FFM, P=0.02) as compared with individuals in the\u0026nbsp;highest\u0026nbsp;tertile (Table 1). Furthermore, a higher proportion of individuals in the lowest tertile had prediabetes or T2DM than individuals in the\u0026nbsp;highest\u0026nbsp;tertile (Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHemorheological parameters\u0026nbsp;\u003c/em\u003e\u003cem\u003ein\u0026nbsp;\u003c/em\u003e\u003cem\u003eindividuals\u003c/em\u003e \u003cem\u003estratified according to\u0026nbsp;\u003c/em\u003e\u003cem\u003einsulin-stimulated\u003c/em\u003e \u003cem\u003emyocardial MrGlu values\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHemorheological parameters of the study individuals stratified into tertiles according to insulin-stimulated myocardial MrGlu values are shown in Table 2. As compared with individuals in the\u0026nbsp;highest\u0026nbsp;tertile, those in the lowest tertile showed an age-adjusted increase in WBV (5.54 ± 0.3 cP vs 6.13 ± 0.4 cP respectively; P=0.001), hematocrit \u0026nbsp;(39.1 ± 3.1% vs 43.2 ± 3.7% respectively; P=0.004), total proteins (7.60 ± 0.3 g/l vs 7.06 ± 0.2 g/l respectively; P\u0026lt;0.0001) and white blood cells (WBC) count (7868 ± 1817 x10\u003csup\u003e9\u003c/sup\u003e/l vs 6123 ± 917 x10\u003csup\u003e9\u003c/sup\u003e/l respectively; P=0.006) (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAssociation between insulin-stimulated\u003c/em\u003e \u003cem\u003emyocardial\u003c/em\u003e\u003cem\u003eMrGlu, cardiovascular risk factors\u003c/em\u003e\u003cem\u003e\u0026nbsp;and hemorheological parameters\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn a univariate analysis, WBV\u0026nbsp;was negatively correlated with myocardial MRGlu (r= -0.416, P=0.001), whole-body insulin-stimulated glucose disposal (M\u003csub\u003eFFM\u003c/sub\u003e) (r= -0.323, P=0.01), and positively correlated with fasting plasma glucose (r= 0.302, P=0.02), waist circumference (r= 0.414, P=0.001), systolic (r= 0.406, P=0.002), and diastolic blood pressure (r= 0.333, P=0.01) (Figure 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, myocardial MRGlu\u0026nbsp;was negatively correlated with waist circumference (r= -0.378, P=0.004), fasting plasma glucose (r= -0.354, P=0.007), HbA1c (r= -0.489, P\u0026lt;0.0001), hematocrit (r= -0.353, P=0.007), fibrinogen (r= -0.329, P=0.01), fasting plasma insulin (r= -0.353, P=0.008), and positively correlated with whole-body\u0026nbsp;insulin-stimulated glucose disposal\u0026nbsp;(r= 0.441, P=0.001) (Figure 2).\u003c/p\u003e\n\u003cp\u003eIn order to evaluate the independent contributor of myocardial MRGlu, we performed a stepwise multivariate regression analysis\u0026nbsp;running a model including age, sex, BMI, waist circumference, blood pressure, lipid profile, fasting plasma glucose, HbA1c, WBV, fasting insulin, and fibrinogen. The only variables significantly associated with myocardial MrGlu were whole blood viscosity (b\u0026nbsp;\u0026nbsp;-0.505; P\u0026lt;0.0001), fasting insulin (b\u0026nbsp;\u0026nbsp;-0.346; P=0.004), fasting plasma glucose (b\u0026nbsp;\u0026nbsp;-0.287; P=0.01), and\u0026nbsp;sex(b \u0026nbsp;0.280; P=0.003) explaining the 69.6% of its variation (Table 3).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this cross-sectional study, we show that whole blood viscosity is associated with myocardial insulin resistance, estimated using cardiac dynamic \u003csup\u003e18\u003c/sup\u003eF-FDG-PET combined with euglycemic-hyperinsulinemic clamp, in individuals with different degrees of glucose tolerance and no history of coronary heart disease. These findings were strengthened by results of a stepwise multivariate regression analysis performed in order to investigate whether whole blood viscosity was associated with decreased myocardial MrGlu independently of well-established cardio-metabolic risk factors including age, sex, BMI, waist circumference, blood pressure, lipid profile, fasting plasma glucose, HbA1c, WBV, fasting plasma insulin, and fibrinogen. We found that WBV was a major determinant of myocardial MrGlu independently of cardiovascular risk factors known to be associated with myocardial MrGlu explaining the 69.6% of its variation.\u003c/p\u003e \u003cp\u003eOur study extends previous findings showing an association between WBV and with whole-body insulin resistance measured by either euglycemic-hyperinsulinemic clamp in small numbers of subjects (\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) or proxy indices of insulin resistance in larger samples (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). However, to the best of our knowledge, the current study was the first to show an association between WBV and myocardial glucose metabolism in individuals with a broad spectrum of glucose tolerance.\u003c/p\u003e \u003cp\u003eThere is evidence that increased blood viscosity is an independent predictor of ischemic heart disease and stroke in the general population (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Furthermore, blood viscosity has been shown to be associated with target organ damage such as subclinical atherosclerosis, vascular stiffness, decrease of myocardial mechano-energetic efficiency, and left ventricular hypertrophy (\u003cspan additionalcitationids=\"CR3 CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Myocardial insulin resistance is a condition related to an unfavorable cardiometabolic risk profile and early carotid, aortic and coronary atherosclerosis, and has been shown to be a predictor of CV events (\u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Moreover, previous studies have demonstrated that impaired myocardial glucose metabolism is associated with reduced myocardial mechano-energetic efficiency, and increased cardiac workload (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), both alterations linked to the development of heart failure and CV events (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Taken together, these data support the idea that reduced myocardial glucose metabolism may represent one of the pathophysiologic mechanisms contributing to the increased risk of CV disease observed in individuals with increased WBV. The mechanism by which WBV negatively affect myocardial glucose uptake remains to be fully established. Elevated whole blood viscosity and high hematocrit, his major determinant, are associated to peripheral insulin resistance and impaired blood flow (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Decreased blood flow might affect myocardial glucose metabolism by limiting delivery of glucose and, consequently, myocardial glucose uptake (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Furthermore, a reduction in whole-body glucose uptake causes an increase in circulating glucose levels leading to increased insulin secretion and compensatory hyperinsulinemia. On the other hand, hyperinsulinemia may cause vasoconstriction via sympathetic neural activation, which, in turn, would lead to hemoconcentration by increasing hematopoiesis, and hematocrit and, thereby, increased whole blood viscosity (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study has several strengths that merit considerations. A main strength is the use of gold standard methods to assess myocardial glucose metabolism by cardiac FDG PET combined with the euglycemic-hyperinsulinemic clamp technique, which allows the valuation of insulin-stimulated myocardial glucose uptake under uniform experimental conditions of euglycemia and physiological hyperinsulinemia (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). Moreover, glucose tolerance was accurately assessed using FPG, 2 h post-load glucose levels during an OGTT, and HbA1c according to ADA criteria thus excluding any potential misclassification of participants (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Additionally, all tests including anthropometric measures, OGTT, and \u003csup\u003e18\u003c/sup\u003eF-FGD PET scan combined with euglycemic hyperinsulinemic clamp were collected by skilled examiners after a standardized training, who were blinded to the clinical data of the study participants.\u003c/p\u003e \u003cp\u003eNevertheless, some limitations should be taken into account. First, whole blood viscosity has not been directly measured by capillary viscometry. However, we estimated whole blood viscosity using an indirect measure that has been previously validated, and is suitable in clinical practice and large observational studies (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Moreover, this analysis includes only White individuals aging between 30 and 70 years with at least one cardiovascular risk factors attending a referral university hospital, thus limiting the generalizability of the present results to other ethnicities or to the general population. Furthermore, the cross-sectional design of the study precludes causal inferences, and, therefore, no conclusions regarding cause-effect relationships can be made. Additionally, the present findings were observed in an observational study, rather than in a randomized controlled trial thus the results may be subject to residual unknown confounding factors.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, to the best of our knowledge, the current study is the first to show an association between WBV and myocardial glucose metabolism in individuals with a broad spectrum of glucose tolerance. These data support the idea that reduced myocardial glucose metabolism may represent one of the pathophysiologic mechanisms contributing to the increased risk of CV disease observed in individuals with increased WBV.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWBV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ewhole blood viscosity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eT2DM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etype 2 diabetes mellitus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecardiovascular\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCHD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecoronary heart disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRGlu\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emyocardial glucose metabolic rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePET\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epositron emission tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003csup\u003e18\u003c/sup\u003eF-FDG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003csup\u003e18\u003c/sup\u003eF-Fluorodeoxyglucose\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eblood pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOGTT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eoral glucose tolerance test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFPG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efasting plasma glucose\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican Diabetes Association\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNGT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enormal glucose tolerance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eM\u003csub\u003eFFM\u003c/sub\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInsulin-stimulated glucose disposal corrected for fat-free mass\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFFM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efat-free mass\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCARD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etool specific for cardiac images analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVOI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003evolume of interest\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ewhite blood cells\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee (Comitato Etico Azienda Ospedaliera “Mater Domini”), and informed consent was obtained from each subject in accordance with principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors' contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eE.S. designed the study, researched and analyzed data and wrote and edited the manuscript. P.Vi. and P.H.G. analyzed the data from the cardiac PET scans, F.C. performed cardiac PET scans. M.R., T.V.F., M.P., G.C.M., and A.S.. researched data and reviewed the manuscript. P.Ve., G.L.C. and F.A. contributed to the discussion and reviewed the manuscript. G.S. designed the study, analyzed the data, and wrote and reviewed the manuscript. All authors have read and approved the final manuscript. G.S. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eLowe G, Lee A, Rumley A, Price J, Fowkes F. Blood viscosity and risk of cardiovascular events: the Edinburgh Artery study. 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Haematocrit, viscosity, erythrocyte sedimentation rate: meta-analyses of prospective studies of coronary heart disease. Eur Heart J. 2000;21:515-20.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSuccurro E, Pedace E, Andreozzi F, Papa A, Vizza P, Fiorentino TV, et al.\u0026nbsp;Reduction in Global Myocardial Glucose Metabolism in Subjects With 1-Hour Postload Hyperglycemia and Impaired Glucose Tolerance. Diabetes Care. 2020;43:669-76.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eOhtake T, Yokoyama I, Watanabe T, Momose T, Serezawa T, Nishikawa J, et al. Myocardial glucose metabolism in noninsulin-dependent diabetes mellitus patients evaluated by FDG-PET. J Nucl Med. 1995;36:456\u0026ndash;63.\u003c/li\u003e\n \u003cli\u003eHu L, Qiu C, Wang X, Shao X, Wang Y. The association between diabetes mellitus and reduction in myocardial glucose uptake: a population-based \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT study. BMC Cardiovasc Disord. 2018;18:203.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eNielsen R, Jorsal A, Iversen P, Tolbod L, Bouchelouche K, S\u0026oslash;rensen J, et al. Heart failure patients with prediabetes and newly diagnosed diabetes display abnormalities in myocardial metabolism. J Nucl Cardiol. 2018;25:169-76.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSuccurro E, Vizza P, Papa A, Cicone F, Monea G, Tradigo G, et al.\u0026nbsp;Metabolic Syndrome Is Associated With Impaired Insulin-Stimulated Myocardial Glucose Metabolic Rate in Individuals With Type 2 Diabetes: A Cardiac Dynamic \u003csup\u003e18\u003c/sup\u003e F-FDG-PET Study.\u0026nbsp;Front Cardiovasc Med. 2022;9:924787.\u003c/li\u003e\n \u003cli\u003eIozzo P, Chareonthaitawee P, Dutka D, Betteridge DJ, Ferrannini E, Camici PG.\u0026nbsp;Independent association of type 2 diabetes and coronary artery disease with myocardial insulin resistance.\u0026nbsp;Diabetes. 2002;51:3020-4.\u003c/li\u003e\n \u003cli\u003eDevesa A, Fuster V, Vazirani R, Garc\u0026iacute;a-Lunar I, Oliva B, Espa\u0026ntilde;a S, et al.\u0026nbsp;Cardiac Insulin Resistance in Subjects With Metabolic Syndrome Traits and Early Subclinical Atherosclerosis.\u0026nbsp;Diabetes Care. 2023;46:2050-7.\u003c/li\u003e\n \u003cli\u003eSuccurro E, Cicone F, Papa A, Miceli S, Vizza P, Fiorentino TV, et al.\u0026nbsp;Impaired insulin-stimulated myocardial glucose metabolic rate is associated with reduced estimated myocardial energetic efficiency in subjects with different degrees of glucose tolerance. Cardiovasc Diabetol. 2023;22:4.\u003c/li\u003e\n \u003cli\u003eTang K, Lin J, Ji X, Lin T, Sun D, Zheng X, et al. Non-alcoholic fatty liver disease with reduced myocardial FDG uptake is associated with coronary atherosclerosis.\u0026nbsp;J Nucl Cardiol. 2021;28:610-20.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMoan A, Nordby G, Os I, Birkeland KI, Kjeldsen SE. Relationship between hemorrheologic factors and insulin sensitivity in healthy young men. Metabolism. 1994;43:423\u0026ndash;7.\u003c/li\u003e\n \u003cli\u003eNordby G, Moan A, Kjeldsen SE, Os I. Relationship between hemorheological factors and insulin sensitivity in normotensive and hypertensive premenopausal women. Am J Hypertens. 1995; 8: 439-44.\u003c/li\u003e\n \u003cli\u003eCatalano C, Muscelli E, Natali A, Mazzoni A,Masoni A, Bernardini B, et al.\u0026nbsp;Reciprocal association between insulin sensitivity and the haematocrit in man. Eur J Clin Invest. 1997;27:634 -7.\u003c/li\u003e\n \u003cli\u003e\u0026nbsp;Succurro E, Vizza P, Cicone F, Cassano V, Massimino M, Giofr\u0026egrave; F, et al.\u0026nbsp;Sex-specific differences in myocardial glucose metabolic rate in non-diabetic, pre-diabetic and type 2 diabetic subjects.\u0026nbsp;Cardiovasc Diabetol. 2024;23:144\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eEl Sayed NA, Aleppo G, Bannuru RR, Bruemmer D, Collins BS, Ekhlaspour L, et al, on behalf of the American Diabetes Association Professional Practice Committee. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes-2024. Diabetes Care. 2024; 47(Suppl 1):S20-S42.\u003c/li\u003e\n \u003cli\u003eSuccurro E, Vizza P, Papa A, Miceli S, Cicone F, Fiorentino TV, et al.\u0026nbsp;Effects of 26\u0026thinsp;weeks of treatment with empagliflozin versus glimepiride on the myocardial glucose metabolic rate in patients with type 2 diabetes: The randomized, open-label, crossover, active-comparator FIORE trial. Diabetes Obes Metab. 2022;24:2319-30.\u003c/li\u003e\n \u003cli\u003eDeFronzo RA, Tobin JD, Andres R. Glucose clamp technique: a method for quantifying insulin secretion and resistance Am J Physiol. 1979;237:E214-23.\u003c/li\u003e\n \u003cli\u003eCarson RE. Tracer kinetic modeling in PET. In Positron Emission Tomography. London, Springer; 2005. p. 127\u0026ndash;59.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eVizza P, Guzzi PH, Veltri P, Papa A, Cascini GL, Sesti G, Succurro E. Experiences on quantitative cardiac pet analysis.\u0026nbsp;2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).\u0026nbsp;Shenzen, China, 2016. p. 1148-53.\u003c/li\u003e\n \u003cli\u003eFacchini FS, Carantoni M, Jeppesen J, Reaven GM.\u0026nbsp;Hematocrit and hemoglobin are independently related to insulin resistance and compensatory hyperinsulinemia in healthy, non-obese men and women. Metabolism. 1998;47:831\u0026ndash;5.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHanley AJ, Retnakaran R, Qi Y, Gerstein HC, Perkins B, Raboud J, et al. Association of hematological parameters with insulin resistance and beta-cell dysfunction in nondiabetic subjects. J Clin Endocrinol Metab. 2009;94:3824-32.\u003c/li\u003e\n \u003cli\u003eKofoed KF, Carstensen S, Hove JD, Freiberg J, Bangsgaard R, Holm S, et al. Low whole-body insulin sensitivity in patients with ischaemic heart disease is associated with impaired myocardial glucose uptake predictive of poor outcome after revascularisation. Eur J Nucl Med Mol Imaging. 2002;29:991-8.\u003c/li\u003e\n \u003cli\u003eLosi MA, Izzo R, Mancusi C, Wang W, Roman MJ, Lee ET, et al.\u0026nbsp;Depressed myocardial energetic efficiency increases risk of incident heart failure: The Strong Heart Study.\u0026nbsp;J Clin Med. 2019;8:1044.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u0026nbsp;de Simone G, Izzo R, Losi MA, Stabile E, Rozza F, Canciello G, et al.\u0026nbsp;Depressed myocardial energetic efficiency is associated with increased cardiovascular risk in hypertensive left ventricular hypertrophy.\u0026nbsp;J Hypertens. 2016;34:1846\u0026ndash;53.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eShoelson SE, Lee J, Goldfine AB. Inflammation and insulin resistance. J Clin Invest 2006;116:1793\u0026ndash;1801.\u003c/li\u003e\n \u003cli\u003eGerber BL, Ordoubadi FF, Wijns W, Vanoverschelde JL, Knuuti MJ, Janier M, et al. Positron emission tomography using (18)F-fluoro-deoxyglucose and euglycaemic hyperinsulinaemic glucose clamp: optimal criteria for the prediction of recovery of post-ischaemic left ventricular dysfunction: results from the European Community Concerted Action Multicenter Study on Use of (18)F-Fluoro-Deoxyglucose Positron Emission Tomography for the Detection of Myocardial Viability. Eur Heart J. 2001;22:1691\u0026ndash;701.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section\u003c/p\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":"cardiovascular-diabetology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cvdb","sideBox":"Learn more about [Cardiovascular Diabetology](http://cardiab.biomedcentral.com/)","snPcode":"12933","submissionUrl":"https://submission.nature.com/new-submission/12933/3","title":"Cardiovascular Diabetology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"blood viscosity, myocardial glucose metabolism, cardiovascular disease, type 2 diabetes, cardiac 18F-FDG PET, hematocrit, insulin resistance","lastPublishedDoi":"10.21203/rs.3.rs-5127910/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5127910/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Increased whole blood viscosity (WBV) was associated with peripheral insulin resistance, type 2 diabetes, and cardiovascular disease (CVD). Impaired myocardial glucose metabolism is a risk factor for CVD. Whether an increased WBV is associated with myocardial insulin resistance is still undefined.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: To elucidate this issue, we evaluated the association between WBV and myocardial glucose metabolic rate (MRGlu) in 57 individuals with different glucose tolerance status. Myocardial MRGlu was assessed using dynamic cardiac \u003csup\u003e18\u003c/sup\u003eF-FDG PET combined with euglycemic hyperinsulinemic clamp. WBV was calculated using a validated equation including hematocrit and plasma proteins: WBV = [0.12 x h] + [0.17 x (p-2.07)], where h is the hematocrit (%) and p the plasma proteins (g/dl).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: As compared with individuals in the highest myocardial MrGlu tertile, those in the lowest tertile showed an age-adjusted increase in WBV (5.54 ± 0.3 cP vs 6.13 ± 0.4 cP respectively; P=0.001), hematocrit (39.1 ± 3.1% vs 43.2 ± 3.7% respectively; P=0.004), and total proteins (7.06 ± 0.3 g/l vs 7.60 ± 0.3 g/l respectively; P\u0026lt;0.0001). WBV was negatively correlated with myocardial MRGlu (r= -0.416, P=0.001). In a stepwise multivariate regression analysis, including several cardiovascular risk factors, the only variables significantly associated with myocardial MrGlu were WBV (b \u0026nbsp;-0.505; P\u0026lt;0.0001), fasting insulin (b \u0026nbsp;-0.346; P=0.004), fasting plasma glucose (b \u0026nbsp;-0.287; P=0.01), and sex\u003csub\u003e \u003c/sub\u003e(b \u0026nbsp;0.280; P=0.003) explaining the 69.6% of its variation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: To the best of our knowledge, the current study was the first to show an association between WBV and myocardial glucose metabolism in individuals with a broad spectrum of glucose tolerance.\u003c/p\u003e","manuscriptTitle":"Elevated whole blood viscosity is associated with an impaired insulin-stimulated myocardial glucose metabolism","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-18 09:43:57","doi":"10.21203/rs.3.rs-5127910/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-16T07:22:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-15T22:17:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-15T01:46:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-13T08:57:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-11T19:12:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-07T01:02:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"262177536681149522247591484904705451021","date":"2024-09-25T22:50:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"109631310156734502158226422660494207646","date":"2024-09-25T22:42:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188787549953336482462449324502525889812","date":"2024-09-25T13:50:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115409532891064416261858019421465240827","date":"2024-09-24T17:17:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"218953221692054228412389113815645973","date":"2024-09-23T20:46:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-23T20:32:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-23T20:12:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-23T14:46:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cardiovascular Diabetology","date":"2024-09-21T09:28:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-diabetology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cvdb","sideBox":"Learn more about [Cardiovascular Diabetology](http://cardiab.biomedcentral.com/)","snPcode":"12933","submissionUrl":"https://submission.nature.com/new-submission/12933/3","title":"Cardiovascular Diabetology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d9388456-acfa-4e60-adc4-148a4b578fa8","owner":[],"postedDate":"November 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-09T16:07:01+00:00","versionOfRecord":{"articleIdentity":"rs-5127910","link":"https://doi.org/10.1186/s12933-024-02513-7","journal":{"identity":"cardiovascular-diabetology","isVorOnly":false,"title":"Cardiovascular Diabetology"},"publishedOn":"2024-12-04 15:58:10","publishedOnDateReadable":"December 4th, 2024"},"versionCreatedAt":"2024-11-18 09:43:57","video":"","vorDoi":"10.1186/s12933-024-02513-7","vorDoiUrl":"https://doi.org/10.1186/s12933-024-02513-7","workflowStages":[]},"version":"v1","identity":"rs-5127910","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5127910","identity":"rs-5127910","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}