Determinants of Vascular Impairment in Type 1 Diabetes; Impact of Sex and Connexin 37 Gene Polymorphism, Cross-sectional study.

Determinants of Vascular Impairment in Type 1 Diabetes; Impact of Sex and Connexin 37 Gene Polymorphism, Cross-sectional study. | 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 Determinants of Vascular Impairment in Type 1 Diabetes; Impact of Sex and Connexin 37 Gene Polymorphism, Cross-sectional study. Pavlina Pithova, Michaela Cichrova, Milan Kvapil, Jaroslav Hubacek, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4512208/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Aug, 2024 Read the published version in Cardiovascular Diabetology → Version 1 posted 11 You are reading this latest preprint version Abstract Background Predictors of cardiovascular complications are well established in type 2 diabetes but not in type 1 diabetes (T1D). We analyzed the association between traditional and novel cardiovascular risk factors and macro- and microvascular parameters in T1D patients and modification of these associations by sex and genetic factors. Methods In a cross-sectional study we analyzed in T1D patients younger than 65 years the association of wide range of cardiovascular risk factors with vascular parameters represented by ankle brachial index (ABI), toe brachial index (TBI), by duplex ultrasound measured presence of plaques in carotid and femoral arteries (Belcaro score) and intima media thickness of carotid arteries (CIMT), by photoplethysmography measured interbranch index expressed as Oliva/Roztocil index (ORI), and renal parameters represented by urine albumin/creatinine ratio (uACR) and cystatin C filtration rate. We evaluated these associations by multivariate regression analysis including interactions with sex and gene for connexin 37 (cx37) polymorphism (rs1764391). Results In 235 men and 227 women (mean age 43.6 ± 13.6 years; mean duration of diabetes 22.1 ± 11.3 years) pulse pressure was the strongest predictor of unfavorable values of most of vascular parameters under study (ABI, TBI, Belcaro scores, uACR and ORI) while plasma lipids represented by remnant cholesterol (cholesterol – LDL-HDL cholesterol), atherogenic index of plasma (log (triglycerides/HDL cholesterol) and Lp(a) were associated mainly with renal impairment (uACR, cystatin C clearance and lipoprotein (a)). Plasma non-HDL cholesterol (total – HDL cholesterol) was not associated with any vascular parameter under study. In contrast to the pulse pressure, the associations of lipid parameters with renal and vascular parameters were modified by sex and cx37 gene. Conclusion Pulse pressure was the strongest determinant for macro- and microvascular parameters in T1D and was not influenced by sex and genetic factors while lipid parameters were associated mostly with renal impairment and were modified by sex and genetic factors. type 1 diabetes mellitus vascular parameters cardiovascular risk factors sex gene for connexin 37 Figures Figure 1 Figure 2 Figure 3 Background Type 2 diabetes (T2D) but also type 1 diabetes (T1D) [ 1 ] ranks among the most deleterious cardiovascular risk factors. While in T2D the mechanisms of vascular disease are relatively well described [ 2 ], the association of T1D with vascular impairment seems to be more complex and different from T2D [ 3 ]. Moreover, despite documented decrease of cardiovascular mortality in T1D in some countries [ 4 ] this mortality in T1D is till several times higher than in general population [ 5 ]. Therefore, cardiovascular prevention in T1D should not be based only on data from T2D. This presumption is supported also by our previous work in diabetic women in which preclinical atherosclerosis expressed as intima-media thickness of common carotid and femoral arteries measured by high resolution ultrasound was in T1D women strongly associated with factors reflecting body fat and its distribution whereas in T2D women it was associated with factors reflecting mainly glucose and lipid disorders [ 6 ]. It is important to stress that in T1D the process of vascular changes starts insidiously at a young age, they clinically manifest later in life and wide range of metabolic and hemodynamic abnormalities directly but also indirectly associated with diabetic status could be responsible for vascular dysfunction and clinical events [ 7 – 8 ]. Therefore, identifying major predictors of vascular abnormalities in their early stages could lead to better prevention. Regarding predictors of cardiovascular events, metabolic control in T1D is proved to be critical in prevention of cardiovascular disease [ 10 ]. Nevertheless, correction of other risk factors including dyslipidemia, hypertension, nephropathy and, potentially, other factors, seem to be also of high importance. Therefore, better identification of additional non-glycemic predictors of cardiovascular disease might substantially improve therapeutic strategies in T1D subjects. Macro- and microvascular disease can be detected by history and physical examination, however, more sophisticated methods of detection of vascular changes by various non-invasive methodologies are available [ 11 – 14 ], some exploited also in assessment of vascular status in diabetic patients [ 15 ] including early vascular changes in young patients suffering from T1D [ 16 , 17 ]. Regarding predictors of cardiovascular events in T1D, genetic factors could play important role. For example, as shown in the Joslin Diabetes Center 50-Year Medalist Study [ 18 ] approximately 30–35% patients with T1D do not manifest significant microvascular complications for 50 years, regardless of their glycated hemoglobin (HbA1c) levels and traditional cardiovascular risk factors. This indicates that T1D patients may possess genetic factors that accelerate or diminish the adverse effects of metabolic and hemodynamic factors. In this respect, the role of connexin 37(cx37) gene polymorphism as a potential candidate gene has been evaluated; C1019T polymorphism in the human gene encoding connexin 37 (CX37, encoded by GJA4) has been reported to be associated with coronary artery disease [ 19 ] and its association with cardiovascular events seems to be strongly modified by the presence of T2D [ 20 ]; however, no data are available for T1D. Another obvious and robust non-modifiable factor associated with cardiovascular disease is sex. Data from large metanalysis indicate that females with T1D are at higher risk for fatal events than men [ 21 ] and sex differences in cardiovascular risk profile were already detected in adolescents and children [ 22 ]. Based on these facts, we evaluated associations between traditional and several novel cardiovascular risk factors with vascular parameters obtained by measurement in several territories in middle aged T1D patients. In addition, we evaluated potential modifications of those associations by sex and by gene cx37 polymorphism. METHODS Design of the study: The study was designed as a cross-sectional observational one in unselected patients with T1D followed in one center. Independent variables were traditional and novel cardiovascular risk factors and dependent variables were macro- and microvascular parameters. Study population and procedures: All consecutive women and men with T1D in one center were examined. The Institutional Review Board approved the study, and all participants signed informed consent. The investigation conformed to the principles outlined in the Declaration of Helsinki. The inclusion criteria were willingness to sign informed consent and age younger than 65 years. Before they were included in the study and after receiving comprehensive information, all participants provided informed consent. History was obtained with standardized questionnaire focused on the presence of cardiovascular disease of atherosclerotic origin, microvascular disease, and cardiovascular risk factors. Physical examination was focused on measurement of anthropometric parameters and blood pressure. Fasting venous blood samples and urine were taken in the morning before examination and were processed by certified local laboratory. Cardiovascular risk factors, renovascular and genetic parameters: Duration of diabetes was established by history and confirmed by medical reports. Patients who reported current or past regular smoking were defined as smokers. Hypertension and dyslipidemia were defined by current or previous treatment irrespectively on actual values of blood pressure and lipid concentration. Waist circumference was measured 5 cm above the umbilicus by paper tape in standing position. The total body fat in % was measured by Omron BF306 (Omron Healthcare Co., Ltd., Matsusaka, Japan) hand held body fat monitor. The blood pressure and heart rate were obtained by three measurements obtained by mercury sphygmomanometer in an interval of 1 minute in sitting position at right upper extremity and we included pulse pressure (difference between mean systolic and mean diastolic blood pressure obtained from last two measurements) into subsequent analyses. HbA1c was used as parameter of metabolic control and as parameter of insulin resistance Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) was calculated ((plasma fasting glucose (mmol/l) *concentration of insulin (IU)/22.5)) [ 23 ]. Lipid parameters including plasma non-HDL cholesterol (total cholesterol-HDL cholesterol), remnant cholesterol (RLPC) (total – LDL-HDL cholesterol), atherogenic index of plasma (AIP) ((log (triglycerides/HDL cholesterol)) [ 24 ], and lipoprotein(a) ((Lp(a)) were measured by standard laboratory methods. Similarly, laboratory parameters as total leukocyte, neutrophil, lymphocyte, platelet counts, C-reactive protein measured by highly sensitive method (hsCRP), cystatin C clearance and liver tests including gama-glutamyl transferase (GGT) were obtained in the local laboratory by routine laboratory measurements. Fibrosis-4 Liver Index (FIB-4) was estimated as follows (age in years, ALT and AST in µkat/l, and platelet count in 10 9 /L): (age *AST)/(platelet count* √ 2 ALT). Plasma vitamin D was measured by chromatography. Urine albumin/creatinine ratio (uACR) was measured from spot urine samples which were collected during the study visits in the local laboratory. Cx37 gene polymorphism (rs1764391) was established as previously described [ 25 ]. In short, DNA was isolated from frozen EDTA blood [ 26 ]. To genotype the C1019 > T (Pro319 > Ser) variant within Cx37 gene, oligonucleotides 5` CTGGACCCACCCCCTCAGAATGGCCAAAGA and 5` AGGAAGCCGTAGTGCCTGGTGG and restriction enzyme AasI (Fermentas, Lithuania) were used to distinguish the T (fragments of 240 bp and 35 bp) and C (275 bp) alleles. A set of 24 samples was analyzed three times within 3 weeks with 100% confirmity. Vascular parameters: Presence of cardiovascular disease was defined as by study participants reported cardiovascular disease of atherosclerotic origin (ischemic heart disease, ischemic stroke and manifest peripheral artery disease), microcirculatory disease (retinopathy, nephropathy) and diabetic foot. The directly measured vascular parameters were represented by ankle-brachial (ABI) and toe-brachial (TBI) indexes obtained as ratio of pressures at ankles and toes obtained by sphygmomanometer using the photoplethysmographic probe (Hadeco Smartdop 50) for signal detection divided by pressures at upper extremities measured with regular sphygmomanometer; ABI and TBI were then automatically calculated by the software. Oliva-Roztocil interbranch index (ORI) was calculated from photoplethysmographic curve by software obtained by the same photoplethysmographic probe. ORI was already used in several studies [ 27 – 29 ], in short, its calculation is based on the range measured between ascending and descending arm of pulse wave contour at two thirds of signal amplitude and is also standardized for heart rate period ( Graphical Abstract ). Macrovascular changes were represented by carotid intima media thickness (CIMT) at the far walls of common carotid arteries two times on both sides at 1 cm distance from the bulb; mean value calculated from two values on both sides was used for subsequent analysis. In addition to CIMT, we used semiquantitative method based on detection of focal changes called Belcaro score of carotid arteries (BSCar) and femoral bifurcation (BSFem) [ 30 ]. This classification defines the degree of preclinical atherosclerosis based on four ultrasound criteria. Class I represents normal three ultrasonic layers (intima media, adventitia, and periadventitia) clearly separated with no disruption of lumen-intima interface for at least 3.0 cm, and/or initial alterations (lumen-intima interface disruption at intervals of 1 mm). Class III represents plaque without hemodynamic disturbance, localized wall thickening and increased density involving all ultrasonic layers, intima-media thickness > 2 mm. Finally, class IV represents plaque as in Class III, but with stenosis on duplex scanning indicating stenosis > 50%. CIMT and Belcaro scores were measured by duplex ultrasound device (Toshiba Nemio MX, Japan) with Toshiba PLN-805AT linear array ultrasound transducer probe (frequency range of 6.0 to 12.0 MHz). All vascular measurements were accomplished after at least 5 minutes of rest in supine position by single experienced investigator (PP) during one session in quite room with stable temperature approximately 21 degrees of Celsius. Statistical analyses: The statistical analysis was conducted using two different types of regression models, selected according to the characteristics of the dependent variables: linear regression models based on ordinary least squares [ 31 ] were used for ABI, TBI, ORI, CIMT, Cystatin C clearance and uACR, and ordinal logistic regression through a cumulative link model [ 32 ] was used for Belcaro scores (3 groups were compared; in BSCar I vs. II vs. III-IV, in BSFem I, II vs. III vs. IV). The final models were built in a backward stepwise manner; the initial models incorporated all variables under study, along with their interactions with sex and cx37 gene polymorphism (CT/TT vs. CC). Through model comparisons and exploratory analyses, several continuous independent variables were transformed to more accurately represent their potential effects on the dependent variables, for example, in all models, hsCRP was categorized into intervals (0.5, 0.5–1.5, 1.5–2.5, and > 2.5 mg/l). Other transformations of continuous independent variables and details are listed in Supplement. The dependent variable uACR was log-transformed. For the final model, we evaluated both the overall effect of the independent variables (simultaneously testing all coefficients corresponding to the independent variables – main effects and interactions) and, specifically for ABI, TBI, ORI, uACR, BSCar and BSFem, the main effects and interactions separately, the corresponding p-values are listed and displayed graphically as inverse logarithms (Figs. 1 – 3 and Graphical Abstrac t). For the linear regression models, submodel F-tests with heteroscedasticity-consistent standard errors [ 33 , 34 ] were used in the model-building process and for testing the final model. For the ordinal logistic regression, p-values for the model coefficients were calculated using Wald tests and likelihood ratio tests were used during the model development. The population differences for males and females were assessed using t-tests and proportion tests. All statistical analyses were conducted using the R software [ 35 , 36 ] at a 5% significance level, and no adjustments were made to account for multiple testing. More detailed description of transformations of particular continuous independent variables and more detailed analyses for individual variables are listed in Supplement. Finally, because of multiple testing we consider associations and interactions as strong if p ≤ 0.01 and as moderate if p > 0.01. Results Basic characteristics of the study population and sex differences : In total, 260 women and 260 men younger than 65 years with T1D were included. Complete data for the purpose of this study were obtained from 227 men and 235 women (mean age 43.6 ± 13.6 years; mean duration of diabetes 22.1 ± 11.3 years). As shown in Table 1 , women and men did not differ in the mean age and mean duration of the diabetes but women had higher HbA1c than men while men had higher HOMA-IR than women. Men reported more often smoking and history of hypertension than women. Women and men reported similar frequency of dyslipidemia and cardiovascular and microvascular disease. No differences between women and men were found for prevalence of polymorphism of the gene for cx37. Body mass index and waist circumference were higher in men, whereas total body fat content was higher in women. Women and men did not differ in pulse pressure and lipid parameters with the exception of AIP which was higher (i.e. less favorable) in men. Men had higher values of vitamin D and GGT than women and no differences were detected for hsCRP and FIB-4. Regarding vascular parameters, women had lower ABI, TBI and higher ORI (less favorable value) than men, while men had higher CIMT, BSCar, BSFem, uACR and lower cystatin C clearance than women. Table 1: Demographics and history data (all data are means ± SD, if not stated differently) Women (n=227) Men (n=235) p Age (years) 43.8 ± 12.7 43.3 ± 14.4 0.693 Duration of diabetes (years) 21.7 ± 10.2 22.5 ± 12.3 0.448 Prevalence of smoking (%) 31.9 % 43 % 0.011 Prevalence of hypertension (%) 37.9 % 49.8 % < 0.001 Prevalence of dyslipidemia (%) 30.1 % 34.9 % 0.275 Gene for connexin 37 n (%) TT/CT/CC genotype 21/104/102 (9.3/45.8/44.9) 24/101/110 (10.2/43.0/46.8) 0.816 Prevalence of known ASCVD n (%) 21 (9.2) 30 (12.7) 0.239 Prevalence of retinopathy/treatment n (%) 111/47 (48.8/20.8) 115/54 (48.9/23.1) 1.000/0.575 Prevalence of nephropathy n (%) 65 (28.6) 73 (30.6) 0.612 Prevalence of diabetic foot n (%) 17 (7.4) 27 (11.5) 0.156 Body mass index (kg.m -2 ) 25.4 ± 4.5 26.9 ± 4.2 < 0.001 Waist circumference (cm) 80.2 ± 10.7 92.4 ± 12.0 < 0.001 Total body fat (%) 27.9 ± 7.3 19.29 ± 7.6 < 0.001 Pulse pressure (mm Hg) 53.2 ± 13.4 55.7 ± 14.4 0.054 Non- HDL cholesterol (mmol/l) 3.18 ± 0.85 3.33 ± 0.91 0.068 Atherogenic index of plasma -0.27 ± 0.26 -0.09 ± 0.27 < 0.001 Remnant cholesterol (mmol/l) 0.56 ± 0.37 0.60 ± 0.43 0.285 Lipoprotein (a) (mg/l) 254.1 ± 369.6 251.2 ± 332.1 0.929 hsCRP (mg/l) 2.21 ± 2.25 2.19 ± 3.29 0.939 HbA1c (mmol/mol) 68.1 ± 14.8 62.7 ± 14.6 < 0.001 HOMA-IR 0.99 ± 3.75 1.29 ± 2.88 < 0.001 Plasma vitamin D (nmol/l) 53.39 ± 27.17 58.12 ± 22.1 0.05 Gama-glutamyl transferase (ukat/l) 0.38 ± 0.35 0.63 ± 0.84 < 0.001 FIB-4 0.87 ± 0.49 0.98 ± 0.73 0.059 Ankle brachial index 1.04 ± 0.11 1.11 ± 0.18 < 0.001 Toe brachial index 0.8 ± 0.12 0.86 ± 0.14 < 0.001 CIMT (mm) 0.69 ± 0.16 0.76 ± 0.18 < 0.001 Belcaro score carotid I/II/III/IV n (%) 141/79/6/1 (61.7/35.2/2.6/0.004) 103/103/27/2 (43.8/43.8/11.5/0.008) < 0.001 Belcaro score femoral I/II/III/IV n (%) 166/37/24/0 (72.7/16.3/10.6/0) 136/67/31/1 (57.9/28.5/13.2/0.004) < 0.001 Oliva Roztocil index 0.27 ± 0.04 0.26 ± 0.04 < 0.001 Urine Albumine/Creatinine (mg/mol creatinine) 7.82 ± 37.37 17.3 ± 62.26 0.049 Cystatin C clearance (ml/s/1,73m 2 ) 1.80 ± 0.65 1.49 ± 0.42 < 0.001 Abbreviations: ASCVD: cardiovascular disease of atherosclerotic origin, CIMT: intima-media thickness of common carotid artery, FIB-4: fibrosis 4 liver index, HOMA-IR: Homeostatic Model Assessment for Insulin Resistance, hsCRP -C-reactive protein measured by high sensitivity method All patients were treated by intensified insulin therapy, 49% of women and 43% of men used the insulin pump therapy. In addition, 25% of women and 31% of men used continuous glucose sensors or flash glucose monitoring during last year regularly. In addition, 8% of women and 6% of men needed additional metformin therapy to improve their insulin sensitivity. Men were treated by higher mean insulin dose (0.66 ± 0.19 vs. 0.62 ± 0.22 IU/kg/day, p< 0.01) and more frequently treated by ACE/ARB1 inhibitors than women (46% vs. 35%, p< 0.01) while no difference was observed for hypolipidemic treatment (24% and 29%). In addition, 30% women reported menopausal status. Determinants of directly measured vascular and renovascular parameters : ABI ( Figure 1a) was positively and strongly associated with age, moderately with waist circumference, with Lp(a) lower than 600 mg/l, and with GGT (p<0.001, p=0.029 , p=0.025, and p=0.026 for GGT equal or more than 0.65 ukat/l, respectively) and it was inversely and strongly associated with female sex, pulse pressure, and inversely and moderately with RLPC (p=0.003, p<0.001, and p=0.022, respectively). No modifying effect of sex was observed. Regarding modifying effect of cx37 gene polymorphism, in CC homozygotes ABI was positively and moderately associated with RLPC (p=0.03) and it was inversely and moderately associated with GGT (p=0.032 for GGT equal or more than 0.65 ukat/l, respectively) and inversely and moderately with Lp(a) (p=0.027). TBI ( Figure 1b ) was inversely and strongly associated with age, female sex, pulse pressure, and Lp(a) (p<0.001, p=0.01, p<0.001, and p=0.01, respectively) and it was inversely and moderately associated with hsCRP (p=0.035, with individual coefficients p=0.005-0.49 with the highest predicted values for hsCRP 0.5, followed by 1.5-2.5 and 0.5-1.5, respectively). Regarding modifying effect of sex, in females it was positively and moderately associated with higher body fat and with higher AIP, and inversely and strongly with history of smoking (p=0.029 and p=0.04, and p=0.01, respectively). Regarding modifying effect of cx37 gene, in CC homozygotes TBI was inversely and strongly associated with reported dyslipidemia (p=0.007) and positively and moderately with female sex (p=0.04). Figure 1: Determinants of Ankle brachial index (a) and Toe brachial index (b) in type 1 diabetes ( x axis - logarithmic transformation of p-value/ p values depicted as inverse logarithm: longer bars correspond to lower p-value; black bars indicate significant association and/or modification by sex or connexin37 gene polymorphism; gray bars: no association and no interaction; minus/plus signs at the basis of the bars means positive or inverse association). Abbreviations: FIB-4- Fibrosis-4 Liver Index; GGT – gama-glutamyl transferase; HbA1c - glycated hemoglobin, HOMA-IR - Homeostatic Model Assessment for Insulin Resistance; Connexin37 gene CC - CC homozygotes BSCar ( Figure 2a ) was strongly and positively associated with age, CC homozygosity, HbA1c, history of smoking, pulse pressure, and waist circumference (p<0.001, p=0.006, p=0.01, p<0.001, p<0.001, and p=0.002, respectively). No modifying effect of sex was observed. Regarding modifying effect of cx37 gene polymorphism, in CC homozygotes BSCar was inversely and strongly associated with RLPC and positively and moderately with AIP (p=0.01 and p=0.04, respectively). BSFem ( Figure 2b ) was positively and strongly associated with age, HbA1c, smoking and waist circumference and moderately with female sex and pulse pressure (p<0.001, p=0.002, p=0.002, and p<0.001, and p=0.03 and p=0.03, respectively) and it was inversely and strongly associated with body fat (p<0.001). Regarding modifying effect of sex, in females BSFem was inversely and strongly associated with non-HDL cholesterol and positively and strongly with diabetes duration (p=0.007 and p=0.002, respectively). Regarding modifying effect of cx37 gene polymorphism, in CC homozygotes BSFem was positively and moderately associated with non-HDL cholesterol (p=0.02) Figure 2: Determinants of Belcaro score of carotid (a) and femoral (b) arteries in type 1 diabetes ( x axis: p values depicted as inverse logarithm: longer bars correspond to lower p-value; black bars indicate significant association and/or modification by sex or connexin37 gene polymorphism; gray bars: no association and no interaction; minus/plus signs at the basis of the bars means positive or inverse association). Abbreviations: FIB-4- Fibrosis-4 Liver Index ; GGT – gama-glutamyl transferase; HbA1c - glycated hemoglobin, HOMA-IR - Homeostatic Model Assessment for Insulin Resistance, Connexin37 gene CC - CC homozygotes CIMT was positively and strongly associated with age and non-HDL cholesterol, and moderately with diabetes duration and HbA1c (p<0.001 and p=0.007, and p=0.02 and p=0.02, respectively) and it was inversely and strongly associated with plasma vitamin D (p=0.009). Regarding modifying effect of sex, in females it was positively and moderately associated with Lp(a) (p=0.03) and inversely and moderately with non-HDL cholesterol (p=0.05). No modifying effect of cx37 gene polymorphism was detected. uACR ( Figure 3a ) was positively and strongly associated with female sex, duration of diabetes, HbA1c, history of hypertension, pulse pressure, AIP and FIB-4, and moderately with RLPC, Lp(a) and CC homozygosity (p=0.003, p=0.01, p<0.001, p<0.001, p=0.004 p<0.001 and p=0.01, and p=0.02, p=0.02 and p=0.02, respectively) and it was inversely and strongly associated with body fat (p<0.001). Regarding modifying effect of sex, in females uACR was inversely and strongly associated with duration of diabetes (p=0.01). Regarding modifying effect of cx37 gene polymorphism, in CC homozygotes uACR was inversely and strongly associated with HbA1c (p=0.01). ORI ( Figure 3b ) was positively and strongly associated with age, diabetes duration, smoking, and pulse pressure (p=0.002, p<0.001, p=0.004, and p<0.001, respectively) and it was inversely and moderately associated with female sex and strongly with plasma vitamin D (p=0.02 and p<0.001. respectively). Regarding modifying effect of sex, in females ORI was positively and strongly associated with plasma vitamin D (p=0.003). Regarding modifying effect of cx37 gene, in CC homozygotes ORI was positively and moderately associated with history of hypertension and RLPC (p=0.02 and p=0.02, respectively) and inversely and moderately with female sex (p=0.05). Figure 3: Determinants of urine albumin/ creatinine ratio (a) and Oliva Roztocil index (b) in type 1 diabetes ( x axis - logarithmic transformation of p-value/ p values depicted as inverse logarithm: longer bars correspond to lower p-value; black bars indicate significant association and/or modification by sex or connexin37 gene polymorphism; gray bars: no association and no interaction; minus/plus signs at the basis of the bars means positive or inverse association) Abbreviations: FIB-4- Fibrosis-4 Liver Index, GGT – gama-glutamyl transferase; HbA1c - glycated hemoglobin, HOMA-IR - Homeostatic Model Assessment for Insulin Resistance, ORI – Oliva Roztocil Index, Connexin37 gene CC - CC homozygotes Cystatin C clearance was inversely and strongly associated with AIP, Lp(a), hypertension, and moderately with pulse pressure and smoking (p<0.001, p=0.01, p=0.01, and p=0.02 and p=0.02, respectively) and it was positively and moderately associated with age (p=0.05). Regarding modifying effect of sex, in females, cystatin C clearance was positively and moderately associated with age (p=0.02). Regarding modifying effect of cx37 gene, in CC homozygotes cystatin C clearance was associated positively and strongly with AIP (p=0.01). Finally, regarding intercorrelations between continuous vascular parameters (ABI, TBI, uACR, ORI), inverse strong linear correlation was found only between TBI and ORI (r= -0.46). Discussion This cross-sectional study described associations of traditional and novel cardiovascular risk factors with different vascular parameters in middle-aged population of T1D patients. It also evaluated potential modification of these associations by sex and cx37 gene polymorphism. Specific diabetic risk factors and vascular parameters The main determinants considered to be associated with unfavorable vascular parameters in T1D were age, duration and metabolic control of diabetes, the latter represented by HbA1c. As expected, age was strongly associated with unfavorable values of most of vascular parameters with the exception of albuminuria while duration of diabetes was strongly associated with parameters representing mostly microvascular disease as were albuminuria and ORI but not with macrovascular parameters. Therefore, these data not only confirmed that duration of diabetes rather than chronological age was important for deleterious vascular changes but also indicated that hyperglycemia in T1D firstly affects microcirculatory parameters. This confirms that patients with longer T1D duration should be considered at high or very high cardiovascular risk [ 37 ]. The metabolic control of diabetes represented by HbA1c was associated mainly with macrovascular changes represented by plaques in carotid and femoral arteries but also with more subtle vascular and/or renovascular changes as were CIMT and albuminuria. Therefore, in addition to albuminuria also CIMT not recommended for individual risk assessment in recent guidelines [ 38 ] , could be still valuable tool for vascular risk assessment in specific populations. Traditional cardiovascular risk factors and vascular parameters: As traditional cardiovascular risk factors we analyzed smoking, blood pressure, waist circumference, body fat, HOMA-IR and plasma lipids. Smoking was associated with macrovascular changes represented by focal changes in carotid and femoral arteries and with ORI, the latter representing combination of arterial stiffness and microvascular changes [ 27-28 ] . Smoking was not associated with albuminuria and, surprisingly, it was not significantly associated with ABI and TBI. However, in women, smoking was strongly associated with lower TBI. This phenomenon in diabetic population was already described [ 39, 40 ] but our findings further indicate that this effect is enhanced in T1D women and affects their smaller vessels. More detailed description of the impact of sex on other associations is presented below. Very important and interesting finding was that pulse pressure was strongly associated with less favorable values of almost all macro- and microvascular parameters under study including renovascular parameters with the exception of CIMT. This indicates that in T1D pulse pressure even in the range of physiological values (Table 1 ) could be associated with vascular damage at multiple levels. The role of blood pressure in T1D was supported by results of large meta-analysis in which hypertension partly mediated the causal effects of T1D on peripheral and coronary atherosclerosis [ 6 ]. Pathophysiological explanation is that pulse pressure reflects also arterial stiffening in diabetic patients; it was already described to be higher in T1D than in non-diabetic population in a cross-sectional, case-control study of almost 3,000 patients. Moreover, whereas higher pulse pressure in this study was more pronounced in subjects with diabetic nephropathy, it was also found in patients with normal albumin excretion rate compared to controls [ 41 ], in another study, pulse pressure was used as the main endpoint in T1D [ 42 ]. Additionally, the association of pulse pressure with vascular parameters was not modified by sex and cx37 gene polymorphism. Therefore, increased pulse pressure as indicator for future cardiovascular events in older populations [ 43 ] should be considered also in younger T1D patients irrespectively of sex and genetic background. In contrast to pulse pressure, HOMA-IR as a marker of insulin resistance, was not associated with any vascular parameter. In contrast, waist circumference as simple parameter for insulin resistance was strongly associated with atherosclerotic changes in carotid and femoral arteries. Interesting finding was that amount of body fat was inversely associated with femoral atherosclerosis and albuminuria indicating its potential protective vascular effect in T1D; moreover, in women, this protective effect was observed also for smaller vessels (TBI). However, if this protection applies also for obese diabetic population (patients in this study had normal body mass index) is less probable. In addition to waist circumference, plasma triglycerides and triglycerides rich lipoproteins [ 44, 45 ] could be better indicators of insulin resistance than HOMA-IR. In our study, RLPC representing remnant lipoproteins and AIP representing reverse cholesterol transport [ 24, 46 ] were strongly associated with albuminuria. The association of AIP with lower cystatin C clearance further underlines potential interconnection of particular lipid parameters with renal impairment. Furthermore, the association of RLPC with lower ABI indicates potential greater impact of remnant lipoproteins on lower extremity arteries. In contrast to less frequently used lipid parameters, representant of atherogenic lipoproteins, non-HDL cholesterol was not associated with any vascular parameter under study. Lp(a) as lipid factor emerging recently for interventions [ 47 ] was strongly associated with impaired renal parameters but it was positively associated with ABI. In this case we can speculate that Lp(a) could be associated with increased arterial stiffness represented by relatively higher ABI. Moreover, the latter association was moderate (p=0.03) and only chance observation could not be excluded also because of abnormal distribution of Lp(a). Impact of potential insulin resistance on vasculature including renal parameters was in our study associated rather with waist circumference and lipid parameters representing remnant lipoproteins and reverse cholesterol transport rather than with HOMA-IR. Regarding renovascular factors, similar results were obtained for Lp(a) while none effect of atherogenic non-HDL cholesterol was found. These data might indicate potential connection of specific lipid factors with renal impairment. It should be admitted that because of cross-sectional character of the study we cannot exclude reverse associations between lipids and renal parameters. [ 48 ]. Nevertheless, prospectively evaluated effect of traditional cardiovascular risk factors on renal parameters was described in prospective study in almost 28,000 children and adolescents with T1D. Risk factors for albuminuria in this study were diabetes duration, HbA1C and blood pressure, but also LDL cholesterol, the latter not confirmed in our study. Difference in assessment of the effect of atherogenic lipids could be attributed to different characteristics of populations under study. In our study older patients were recruited. Moreover, in cross-sectional analysis in this prospective study diabetes duration, HbA1C, dyslipidemia, blood pressure, and male sex, but not lipids were identified as risk factors for nephropathy taking into account other cardiovascular risk factors [ 49 ] . In general, the exact role of lipid parameters in T1D is not definitely solved [ 50 ] and one of reasons could be close association of lipids with metabolic control of T1D in contrast to non-diabetic population [ 51 ]. Novel risk factors Novel risk factors including inflammatory markers represented by plasma vitamin D, hsCRP and markers of liver impairment represented by GGT and FIB-4 did not show robust associations with most of vascular markers under study. Vitamin D concentration was associated with less favorable values of CIMT and ORI and this association was more pronounced in women. Vitamin D deficiency is considered a risk marker for major adverse cardiovascular events in T1D but not for microvascular complications or all-cause mortality [ 52 ]. Based on our data, plasma vitamin D might be associated both with macro- and microvascular changes represented by CIMT and by ORI and this association could be sex dependent at similar plasma levels of vitamin D ( Table 1 ). Inflammatory factors were already proposed as one of the strongest non-lipid determinants of vascular damage [ 53 ]. Particularly, in patients with T1D inflammatory markers were associated with carotid atherosclerosis in a cross-sectional study from Spain by Mariaca et al. with comparable size and age of study population as in our study [ 54 ]. In contrast to data of Mariaca et al., hsCRP in our study was associated with impairment of smaller vessels represented by lower TBI but not with atherosclerosis in carotid and femoral arteries. The explanation of this difference is that our population was less selected, also patients with duration of T1D less than 10 years were included and less than 3% women and 12% men had detectable carotid plaques (BSCar > II) compared to 41% in the study of Mariaca et al. Revealing association of inflammatory factors with vascular damage is also important because there are data from intervention study using combination of empagliflozin and metformin decreased inflammatory parameters including CRP and improved arterial function in adults with T1D [5 5 ]. GGT considered as another risk factor especially for microvascular disease [ 56 ] was in our study associated with lower ABI which means with macrovascular parameter. However, in this case GGT measurement by standard laboratory methods could miss particular GGT iso-enzymes which could play different roles in metabolic diseases [ 57 ]; additionally, substantial non-linear relationship with vascular parameters under study was detected interfering with interpretation of studied relationships as already described in diabetes [ 58 ] . Finally, FIB-4 as a marker of liver fibrosis, insulin resistance, but also of cardiovascular disease in T1D [ 59 ] was in our study associated mainly with albuminuria. This finding underlines potential role of non-glycemic and non-lipid factors in vascular disease. Sex and cx37 gene polymorphism modifications of observed associations In women we observed reversed association of diabetes duration with albuminuria whereas the association of diabetes duration with atherosclerosis in femoral arteries was further enhanced. At the same time, in women higher non-HDL cholesterol was associated with less femoral atherosclerosis. This indicates potential protection of renal function and arteries in lower extremities against long lasting glycemia and lipid factors in women. However, the effect of long lasting glycemia on lower extremity arteries could be accelerated in women. In addition, more deleterious effect of smoking on smaller arteries in women was described above. We are not able to reliably propose mechanisms responsible for these findings based on design if this study. In the literature proposed mechanisms of between sex differences are based on psychosocial and biological factors. Psychosocial factors including behavioral patterns and differences in treatment strategies are difficult to exactly characterize. Regarding biological mechanisms it is proposed that sex hormonal disbalance in women with T1D may contribute to more atherogenic lipid profile, insulin resistance, higher inflammation, and loss of vasoprotective effect of female sex seen on epidemiological level in non-diabetic population. However, even in this respect, not unequivocal data are presented. On one hand, in adolescents with T1D lower levels of estradiol were proposed as potential cause of increased risk in women compared to nondiabetic control women [ 60 ] ; furthermore, among premenopausal women with diabetes, hypothalamic hypoestrogenism was more prevalent and associated with coronary artery disease [61 ]. On the other hand, in T1D women, higher concentration of estradiol was proposed to be associated with increased vascular damage [ 62 ] . Sex differences were also highlighted using Steno type 1 risk engine to estimate the 10-year risk of developing cardiovascular events in multicenter, cross-sectional study involving 2,041 middle aged patients with T1D including 45% women. In this study, the 10-year estimated cardiovascular risk was higher in men younger than 55 years than in women of similar age and sex differences disappeared at age equal or more than 55 years. Therefore, age could play also important role in sex differences and as suggested by authors, female sex is no longer protective at certain age, which could correspond to age of menopause. Therefore, in our study attenuation or acceleration of the impact of particular risk factor on different vascular territories could reflect also different hormonal status of T1D women. In addition, interesting in our study was that reported frequency of macro- and microvascular disease was similar in women and men, whereas directly measured vascular parameters have shown marked differences between women and men. Regarding, cx37 gene polymorphism in our study, we observed that CC homozygosity might attenuate or even reverse the effect of metabolic control of diabetes (HbA1c) on albuminuria, while it accelerates the effect of remnant lipoproteins on carotid atherosclerosis. In addition, in CC homozygotes dyslipidemia was associated with lower values of TBI but in the same group, higher values of remnant lipoproteins represented by RLPC were associated with less atherosclerotic changes in carotid arteries. This indicates potential selective effect of CC genotype on risk factors-vascular associations in patients with T1D . Carrier s of T or C allele of cx37 gene are reported to be at increased or decreased cardiovascular risk and the main proposed modifying factor making these differences was diabetic status, namely type 2 diabetes. Our data indicate potential modifying effect of this gene also in T1D. From pathophysiological perspective we speculate sensitivity of connexin 37 produced by different gene could be differently affected by glycation affecting is function in gap junctions and affecting intercell communication in the vessel wall [ 63, 64 ] . However, our study was not designed to answer this question, and, to our knowledge, no data are available to support or discard this presumption. Therefore, potential modification of functionality of cx37 by hyperglycemia remains hypothetical. Strengths and limitations The main strength of this study is that unselected population of patients with T1D followed in one center in a standard manner were included. Regarding study of traditional and novel cardiovascular risk factors, we exploited several methods of detection of vascular disease including less frequently used parameters. Whereas screening in T1D is not generally recommended [ 65 ], evaluating data obtained from different vascular territories could help in targeting important determinants of vascular disfunction in T1D. In this respect, wide range of hemodynamic, metabolic cardiovascular factors were studied including vitamin D and markers of inflammation and liver fibrosis. Regarding hemodynamic factors, we focused on pulse pressure as indicator of blood pressure because it reflects also arterial stiffness and could be early and simply obtainable parameter for risk assessment in diabetic population. In addition, we focused on the effect of non-LDL lipid parameters on vascular system. In particular we studied non-HDL cholesterol rather than LDL cholesterol, despite we had this parameter (correlation between both parameters was 0.89) and focused rather on representatives of triglyceride rich lipoproteins and on Lp(a), discussed as important risk factors in diabetic population [ 66, 67 ]. The main limitation of our study is its cross-sectional character not allowing us to definitely establish cause and effect relationships. However, because multitude factors and vascular parameters were studied with similar results, we could consider most of observed associations as valid. Another limitation is that our findings are based on preclinical vascular parameters which not always transform to clinical events. But as proved from previous studies, most of studied vascular parameters really reflect future risk of cardiovascular and often fatal events and patients with T1D are not exceptional in this respect. While connexin 37 gene was proposed as candidate gene for ischemic heart disease it represents simple single nucleotide polymorphism and more extensive and sophisticated genetic markers are now studied including genome wide associations. But this particular gene marker was intensively studied and its potential association with ischemic heart disease was repeatedly described including potential modification by diabetes and central obesity [ 19, 20, 25, 63, 64, 68 ]. In addition, this approach also offers some pathophysiological background regarding impaired communication between cells in vascular wall in diabetic patients. Finally, another limitation is that only Caucasian population was studied and we should be cautious to generalize these results to other ethnic groups. Conclusion This cross-sectional study on one hand confirms already described findings, nevertheless, on the other hand, to the best of our knowledge interesting new associations were revealed regarding blood pressure, lipid parameters and modification of these associations by sex and genetic factors. In particular, we demonstrated that in middle aged T1D patients, pulse pressure was consistently associated with less favorable values in almost all macro- and microvascular parameters independently on sex and cx37 gene polymorphism and that lipid parameters were strongly associated with renal impairment and were modified by sex and cx37 gene polymorphism. Therefore, easily obtainable parameter as pulse pressure should be taken into account in patients with T1D irrespectively of sex and genetic background. Regarding plasma lipids, their association with renal function is more complex and we might detect reverse relationships because of design of our study. Decision whether pulse pressure, remnant lipoproteins, Lp(a) and other determinants of vascular damage should become treatment targets in T1D remains should be based on results of clinical trials. Abbreviations ABI: ankle brachial index AIP: atherogenic index of plasma ALT: alanine-amino transferase ASCVD: cardiovascular disease of atherosclerotic origin AST: aspartate-amino transferase BSCar: Belcaro score carotid BSFem: Belcaro score femoral Cx37: connexin 37 CIMT: carotid intima media thickness of common carotid artery FIB-4: Fibrosis-4 Liver Index GGT: gama-glutamyl transferase HbA1c: glycated hemoglobin HOMA-IR: Homeostatic Model Assessment for Insulin Resistance hsCRP: C-reactive protein measured by high sensitivity method LDL cholesterol: low density cholesterol Lp(a): lipoprotein (a) Non-HDL cholesterol: total cholesterol – HDL cholesterol ORI: Oliva-Roztocil interbranch index RLPC: remnant plasma cholesterol (total – LDL-HDL cholesterol) TBI: toe brachial index T1D: type 1 diabetes uACR: urine albumin/creatinine ratio Declarations Funding/acknowledgement : This work was supported by the Ministry of Health of the Czech Republic, grant No. NU20-01-00083 and by the project National Institute for Research of Metabolic and Cardiovascular Diseases [Programme EXCELES, ID Project No. LX22NPO5104] - Funded by the European Union – Next Generation EU and by Ministry of Health of the Czech Republic, Grant [No.NU22-A-125]. All rights reserved. Ethics approval and consent to participate This study conformed to the provisions of the Declaration of Helsinki and was approved by Ethical commitee under No. NU20-01-0008. Informed consent was obtained for all participants involved in this study. Author Contribution PP did all clinical measurements, collected the data and prepared draft of the manuscript, mainly methods, MC did all statistical analyses and prepared Figures 1-3, JH and DD were responsible for genetic analysis and interpretation of genetic data. MK contributed to design of the study and participated in data and funding acquisition JP conceived and designed the study and finally wrote the main manuscript. All authors reviewed the manuscript and contributed to its final version.All authors have reviewed and agree to the published version of the manuscript. Funding organization had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. 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Abbreviations: GGT – gama-glutamyl transferase; HbA1c - glycated hemoglobin, HOMA-IR - Homeostatic Model Assessment for Insulin Resistance, Connexin37 gene CC - CC homozygotes Cite Share Download PDF Status: Published Journal Publication published 22 Aug, 2024 Read the published version in Cardiovascular Diabetology → Version 1 posted Editorial decision: Revision requested 25 Jun, 2024 Reviews received at journal 24 Jun, 2024 Reviewers agreed at journal 03 Jun, 2024 Reviewers agreed at journal 02 Jun, 2024 Reviews received at journal 02 Jun, 2024 Reviewers agreed at journal 02 Jun, 2024 Reviewers agreed at journal 02 Jun, 2024 Reviewers invited by journal 01 Jun, 2024 Editor assigned by journal 01 Jun, 2024 Submission checks completed at journal 01 Jun, 2024 First submitted to journal 01 Jun, 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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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-4512208","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":313889326,"identity":"626188a5-15a9-4675-80cc-43b858a7463a","order_by":0,"name":"Pavlina Pithova","email":"","orcid":"","institution":"2nd Medical Faculty Motol, Prague","correspondingAuthor":false,"prefix":"","firstName":"Pavlina","middleName":"","lastName":"Pithova","suffix":""},{"id":313889327,"identity":"587648c7-b692-4ad5-a671-ae6eab74a266","order_by":1,"name":"Michaela Cichrova","email":"","orcid":"","institution":"Faculty of Mathematics and Physics, Charles University in Prague","correspondingAuthor":false,"prefix":"","firstName":"Michaela","middleName":"","lastName":"Cichrova","suffix":""},{"id":313889328,"identity":"bf0fe36e-3559-4745-bf11-48cfaf4b8490","order_by":2,"name":"Milan Kvapil","email":"","orcid":"","institution":"2nd Medical Faculty Motol, Prague","correspondingAuthor":false,"prefix":"","firstName":"Milan","middleName":"","lastName":"Kvapil","suffix":""},{"id":313889329,"identity":"2aae63b2-b59f-4945-96f4-412c67932800","order_by":3,"name":"Jaroslav Hubacek","email":"","orcid":"","institution":"Institute of Clinical and Experimental Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jaroslav","middleName":"","lastName":"Hubacek","suffix":""},{"id":313889330,"identity":"1700fdb5-942b-4b78-b0ff-91376f28a997","order_by":4,"name":"Dana Dlouha","email":"","orcid":"","institution":"Institute of Clinical and Experimental Medicine","correspondingAuthor":false,"prefix":"","firstName":"Dana","middleName":"","lastName":"Dlouha","suffix":""},{"id":313889331,"identity":"c8c500fe-d7e1-4a00-b505-9c891604ebe7","order_by":5,"name":"Jan Pitha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAApklEQVRIiWNgGAWjYBACxgYGhgMfDBJI1HJwBklaQICZh4EULcztZw8etilIk9NtYH78gTiH9eQlHM4xyDE2O8BmYECcloYcA6CWisRtB4h1HmP/G4PDFgYV9SAtB4jTMgNoC4NBToLZAR5Q6BGl5V3CwR6DNMNth9mMidLBYNife/jDjz/J8mbHm4kMMcMGHiiLmTg7GBjkGXgIKxoFo2AUjIIRDgDx+i/d4O9BVgAAAABJRU5ErkJggg==","orcid":"","institution":"Institute of Clinical and Experimental Medicine","correspondingAuthor":true,"prefix":"","firstName":"Jan","middleName":"","lastName":"Pitha","suffix":""}],"badges":[],"createdAt":"2024-06-01 06:23:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4512208/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4512208/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12933-024-02401-0","type":"published","date":"2024-08-22T15:57:22+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":58387037,"identity":"67eae9e3-66cc-4562-82a9-52ff130fd86c","added_by":"auto","created_at":"2024-06-14 18:46:47","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":123368,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDeterminants of Ankle brachial index (a) and Toe brachial index (b) in type 1 diabetes (\u003c/strong\u003ex axis\u003cstrong\u003e - \u003c/strong\u003elogarithmic transformation of p-value/ p values depicted as inverse logarithm: longer bars correspond to lower p-value; black bars indicate significant association and/or modification by sex or connexin37 gene polymorphism; gray bars: no association and no interaction; minus/plus signs at the basis of the bars means positive or inverse association). Abbreviations: FIB-4- Fibrosis-4 Liver Index; GGT – gama-glutamyl transferase; HbA1c - glycated hemoglobin, HOMA-IR - Homeostatic Model Assessment for Insulin Resistance; Connexin37 gene CC - CC homozygotes\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4512208/v1/95452bf3467db0b88d5d62ff.jpg"},{"id":58387675,"identity":"8896a565-4ea3-45d7-af56-ef79ec3f5182","added_by":"auto","created_at":"2024-06-14 18:54:47","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":124477,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDeterminants of Belcaro score of carotid (a) and femoral (b) arteries in type 1 diabetes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003ex axis:\u003cstrong\u003e \u003c/strong\u003ep values depicted as inverse logarithm: longer bars correspond to lower p-value; black bars indicate significant association and/or modification by sex or connexin37 gene polymorphism; gray bars: no association and no interaction; minus/plus signs at the basis of the bars means positive or inverse association). Abbreviations: FIB-4- Fibrosis-4 Liver Index ; GGT – gama-glutamyl transferase; HbA1c - glycated hemoglobin, HOMA-IR - Homeostatic Model Assessment for Insulin Resistance, Connexin37 gene CC - CC homozygotes\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4512208/v1/23fe4aa718eb6a45663591f9.jpg"},{"id":58387038,"identity":"f347f54a-b94d-4fd6-96e1-7b3396474e02","added_by":"auto","created_at":"2024-06-14 18:46:47","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":118174,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDeterminants of urine albumin/ creatinine ratio (a) and Oliva Roztocil index (b) in type 1 diabetes\u003c/strong\u003e \u003cstrong\u003e(\u003c/strong\u003ex axis\u003cstrong\u003e - \u003c/strong\u003elogarithmic transformation of p-value/ p values depicted as inverse logarithm: longer bars correspond to lower p-value; black bars indicate significant association and/or modification by sex or connexin37 gene polymorphism; gray bars: no association and no interaction; minus/plus signs at the basis of the bars means positive or inverse association) Abbreviations: FIB-4- Fibrosis-4 Liver Index, GGT – gama-glutamyl transferase; HbA1c - glycated hemoglobin, HOMA-IR - Homeostatic Model Assessment for Insulin Resistance, ORI – Oliva Roztocil Index, Connexin37 gene CC - CC homozygotes\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4512208/v1/fb4b15d18107982ceae44e0e.jpg"},{"id":63300642,"identity":"7cb40450-886e-4892-a006-4dee3920d5ec","added_by":"auto","created_at":"2024-08-26 16:16:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1222945,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4512208/v1/943ec4e5-371c-4d9a-84a5-3592688b4037.pdf"},{"id":58387674,"identity":"74d40929-72eb-4bf5-aced-b4abae8b34f8","added_by":"auto","created_at":"2024-06-14 18:54:47","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15630,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4512208/v1/bf78c7c887c89ba7ba919bce.docx"},{"id":58387041,"identity":"24ba9bd9-27c2-435e-9735-913ad50d1b18","added_by":"auto","created_at":"2024-06-14 18:46:47","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":179203,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical Abstract\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLegend: (\u003c/strong\u003ex axis:\u003cstrong\u003e \u003c/strong\u003ep values depicted as inverse logarithm: longer bars correspond to lower p-value; black bars indicate significant association and/or modification by sex or connexin37 gene polymorphism; gray bars: no association and no interaction; minus/plus signs at the basis of the bars means positive or inverse association). Abbreviations: GGT – gama-glutamyl transferase; HbA1c - glycated hemoglobin, HOMA-IR - Homeostatic Model Assessment for Insulin Resistance, Connexin37 gene CC - CC homozygotes\u003c/p\u003e","description":"","filename":"graphicalabstract.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4512208/v1/0d0fc76289da273987e912e3.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Determinants of Vascular Impairment in Type 1 Diabetes; Impact of Sex and Connexin 37 Gene Polymorphism, Cross-sectional study.","fulltext":[{"header":"Background","content":"\u003cp\u003eType 2 diabetes (T2D) but also type 1 diabetes (T1D) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] ranks among the most deleterious cardiovascular risk factors. While in T2D the mechanisms of vascular disease are relatively well described [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], the association of T1D with vascular impairment seems to be more complex and different from T2D [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Moreover, despite documented decrease of cardiovascular mortality in T1D in some countries [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] this mortality in T1D is till several times higher than in general population [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, cardiovascular prevention in T1D should not be based only on data from T2D. This presumption is supported also by our previous work in diabetic women in which preclinical atherosclerosis expressed as intima-media thickness of common carotid and femoral arteries measured by high resolution ultrasound was in T1D women strongly associated with factors reflecting body fat and its distribution whereas in T2D women it was associated with factors reflecting mainly glucose and lipid disorders [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. It is important to stress that in T1D the process of vascular changes starts insidiously at a young age, they clinically manifest later in life and wide range of metabolic and hemodynamic abnormalities directly but also indirectly associated with diabetic status could be responsible for vascular dysfunction and clinical events [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, identifying major predictors of vascular abnormalities in their early stages could lead to better prevention. Regarding predictors of cardiovascular events, metabolic control in T1D is proved to be critical in prevention of cardiovascular disease [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Nevertheless, correction of other risk factors including dyslipidemia, hypertension, nephropathy and, potentially, other factors, seem to be also of high importance. Therefore, better identification of additional non-glycemic predictors of cardiovascular disease might substantially improve therapeutic strategies in T1D subjects. Macro- and microvascular disease can be detected by history and physical examination, however, more sophisticated methods of detection of vascular changes by various non-invasive methodologies are available [\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], some exploited also in assessment of vascular status in diabetic patients [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] including early vascular changes in young patients suffering from T1D [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRegarding predictors of cardiovascular events in T1D, genetic factors could play important role. For example, as shown in the Joslin Diabetes Center 50-Year Medalist Study [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] approximately 30\u0026ndash;35% patients with T1D do not manifest significant microvascular complications for 50 years, regardless of their glycated hemoglobin (HbA1c) levels and traditional cardiovascular risk factors. This indicates that T1D patients may possess genetic factors that accelerate or diminish the adverse effects of metabolic and hemodynamic factors. In this respect, the role of connexin 37(cx37) gene polymorphism as a potential candidate gene has been evaluated; C1019T polymorphism in the human gene encoding connexin 37 (CX37, encoded by GJA4) has been reported to be associated with coronary artery disease [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and its association with cardiovascular events seems to be strongly modified by the presence of T2D [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]; however, no data are available for T1D. Another obvious and robust non-modifiable factor associated with cardiovascular disease is sex. Data from large metanalysis indicate that females with T1D are at higher risk for fatal events than men [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and sex differences in cardiovascular risk profile were already detected in adolescents and children [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBased on these facts, we evaluated associations between traditional and several novel cardiovascular risk factors with vascular parameters obtained by measurement in several territories in middle aged T1D patients. In addition, we evaluated potential modifications of those associations by sex and by gene cx37 polymorphism.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign of the study:\u003c/h2\u003e \u003cp\u003eThe study was designed as a cross-sectional observational one in unselected patients with T1D followed in one center. Independent variables were traditional and novel cardiovascular risk factors and dependent variables were macro- and microvascular parameters.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy population and procedures:\u003c/h2\u003e \u003cp\u003eAll consecutive women and men with T1D in one center were examined. The Institutional Review Board approved the study, and all participants signed informed consent. The investigation conformed to the principles outlined in the Declaration of Helsinki. The inclusion criteria were willingness to sign informed consent and age younger than 65 years. Before they were included in the study and after receiving comprehensive information, all participants provided informed consent. History was obtained with standardized questionnaire focused on the presence of cardiovascular disease of atherosclerotic origin, microvascular disease, and cardiovascular risk factors. Physical examination was focused on measurement of anthropometric parameters and blood pressure. Fasting venous blood samples and urine were taken in the morning before examination and were processed by certified local laboratory.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCardiovascular risk factors, renovascular and genetic parameters:\u003c/h2\u003e \u003cp\u003eDuration of diabetes was established by history and confirmed by medical reports. Patients who reported current or past regular smoking were defined as smokers. Hypertension and dyslipidemia were defined by current or previous treatment irrespectively on actual values of blood pressure and lipid concentration. Waist circumference was measured 5 cm above the umbilicus by paper tape in standing position. The total body fat in % was measured by Omron BF306 (Omron Healthcare Co., Ltd., Matsusaka, Japan) hand held body fat monitor. The blood pressure and heart rate were obtained by three measurements obtained by mercury sphygmomanometer in an interval of 1 minute in sitting position at right upper extremity and we included pulse pressure (difference between mean systolic and mean diastolic blood pressure obtained from last two measurements) into subsequent analyses. HbA1c was used as parameter of metabolic control and as parameter of insulin resistance Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) was calculated ((plasma fasting glucose (mmol/l) *concentration of insulin (IU)/22.5)) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Lipid parameters including plasma non-HDL cholesterol (total cholesterol-HDL cholesterol), remnant cholesterol (RLPC) (total \u0026ndash; LDL-HDL cholesterol), atherogenic index of plasma (AIP) ((log (triglycerides/HDL cholesterol)) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and lipoprotein(a) ((Lp(a)) were measured by standard laboratory methods. Similarly, laboratory parameters as total leukocyte, neutrophil, lymphocyte, platelet counts, C-reactive protein measured by highly sensitive method (hsCRP), cystatin C clearance and liver tests including gama-glutamyl transferase (GGT) were obtained in the local laboratory by routine laboratory measurements. Fibrosis-4 Liver Index (FIB-4) was estimated as follows (age in years, ALT and AST in \u0026micro;kat/l, and platelet count in 10\u003csup\u003e9\u003c/sup\u003e/L): (age *AST)/(platelet count* \u0026radic;\u003csup\u003e2\u003c/sup\u003eALT). Plasma vitamin D was measured by chromatography. Urine albumin/creatinine ratio (uACR) was measured from spot urine samples which were collected during the study visits in the local laboratory.\u003c/p\u003e \u003cp\u003eCx37 gene polymorphism (rs1764391) was established as previously described [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In short, DNA was isolated from frozen EDTA blood [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. To genotype the C1019\u0026thinsp;\u0026gt;\u0026thinsp;T (Pro319\u0026thinsp;\u0026gt;\u0026thinsp;Ser) variant within Cx37 gene, oligonucleotides 5` CTGGACCCACCCCCTCAGAATGGCCAAAGA and 5` AGGAAGCCGTAGTGCCTGGTGG and restriction enzyme AasI (Fermentas, Lithuania) were used to distinguish the T (fragments of 240 bp and 35 bp) and C (275 bp) alleles. A set of 24 samples was analyzed three times within 3 weeks with 100% confirmity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eVascular parameters:\u003c/h2\u003e \u003cp\u003ePresence of cardiovascular disease was defined as by study participants reported cardiovascular disease of atherosclerotic origin (ischemic heart disease, ischemic stroke and manifest peripheral artery disease), microcirculatory disease (retinopathy, nephropathy) and diabetic foot. The directly measured vascular parameters were represented by ankle-brachial (ABI) and toe-brachial (TBI) indexes obtained as ratio of pressures at ankles and toes obtained by sphygmomanometer using the photoplethysmographic probe (Hadeco Smartdop 50) for signal detection divided by pressures at upper extremities measured with regular sphygmomanometer; ABI and TBI were then automatically calculated by the software. Oliva-Roztocil interbranch index (ORI) was calculated from photoplethysmographic curve by software obtained by the same photoplethysmographic probe. ORI was already used in several studies [\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], in short, its calculation is based on the range measured between ascending and descending arm of pulse wave contour at two thirds of signal amplitude and is also standardized for heart rate period (\u003cb\u003eGraphical Abstract\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eMacrovascular changes were represented by carotid intima media thickness (CIMT) at the far walls of common carotid arteries two times on both sides at 1 cm distance from the bulb; mean value calculated from two values on both sides was used for subsequent analysis. In addition to CIMT, we used semiquantitative method based on detection of focal changes called Belcaro score of carotid arteries (BSCar) and femoral bifurcation (BSFem) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This classification defines the degree of preclinical atherosclerosis based on four ultrasound criteria. Class I represents normal three ultrasonic layers (intima media, adventitia, and periadventitia) clearly separated with no disruption of lumen-intima interface for at least 3.0 cm, and/or initial alterations (lumen-intima interface disruption at intervals of \u0026lt;\u0026thinsp;0.5 cm). Class II represents intima-media granulation, granular echogenicity of deep, normally anechoic intimal-medial layer and/or increased intima-media thickness (\u0026gt;\u0026thinsp;1 mm). Class III represents plaque without hemodynamic disturbance, localized wall thickening and increased density involving all ultrasonic layers, intima-media thickness\u0026thinsp;\u0026gt;\u0026thinsp;2 mm. Finally, class IV represents plaque as in Class III, but with stenosis on duplex scanning indicating stenosis\u0026thinsp;\u0026gt;\u0026thinsp;50%. CIMT and Belcaro scores were measured by duplex ultrasound device (Toshiba Nemio MX, Japan) with Toshiba PLN-805AT linear array ultrasound transducer probe (frequency range of 6.0 to 12.0 MHz). All vascular measurements were accomplished after at least 5 minutes of rest in supine position by single experienced investigator (PP) during one session in quite room with stable temperature approximately 21 degrees of Celsius.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses:\u003c/h2\u003e \u003cp\u003eThe statistical analysis was conducted using two different types of regression models, selected according to the characteristics of the dependent variables: linear regression models based on ordinary least squares [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] were used for ABI, TBI, ORI, CIMT, Cystatin C clearance and uACR, and ordinal logistic regression through a cumulative link model [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] was used for Belcaro scores (3 groups were compared; in BSCar I vs. II vs. III-IV, in BSFem I, II vs. III vs. IV). The final models were built in a backward stepwise manner; the initial models incorporated all variables under study, along with their interactions with sex and cx37 gene polymorphism (CT/TT vs. CC). Through model comparisons and exploratory analyses, several continuous independent variables were transformed to more accurately represent their potential effects on the dependent variables, for example, in all models, hsCRP was categorized into intervals (0.5, 0.5\u0026ndash;1.5, 1.5\u0026ndash;2.5, and \u0026gt;\u0026thinsp;2.5 mg/l). Other transformations of continuous independent variables and details are listed in Supplement. The dependent variable uACR was log-transformed. For the final model, we evaluated both the overall effect of the independent variables (simultaneously testing all coefficients corresponding to the independent variables \u0026ndash; main effects and interactions) and, specifically for ABI, TBI, ORI, uACR, BSCar and BSFem, the main effects and interactions separately, the corresponding p-values are listed and displayed graphically as inverse logarithms (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003eand Graphical Abstrac\u003c/b\u003et). For the linear regression models, submodel F-tests with heteroscedasticity-consistent standard errors [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] were used in the model-building process and for testing the final model. For the ordinal logistic regression, p-values for the model coefficients were calculated using Wald tests and likelihood ratio tests were used during the model development. The population differences for males and females were assessed using t-tests and proportion tests. All statistical analyses were conducted using the R software [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] at a 5% significance level, and no adjustments were made to account for multiple testing. More detailed description of transformations of particular continuous independent variables and more detailed analyses for individual variables are listed in Supplement. Finally, because of multiple testing we consider associations and interactions as strong if p\u0026thinsp;\u0026le;\u0026thinsp;0.01 and as moderate if p\u0026thinsp;\u0026gt;\u0026thinsp;0.01.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBasic characteristics of the study population and sex differences\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eIn total, 260 women and 260 men younger than 65 years with T1D were included. Complete data for the purpose of this study were obtained from 227 men and 235 women (mean age 43.6 \u0026plusmn; 13.6 years; mean duration of diabetes 22.1 \u0026plusmn; 11.3 years). As shown in \u003cstrong\u003eTable 1\u003c/strong\u003e, women and men did not differ in the mean age and mean duration of the diabetes but women had higher HbA1c than men while men had higher HOMA-IR than women. Men reported more often smoking and history of hypertension than women. Women and men reported similar frequency of dyslipidemia and cardiovascular and microvascular disease. No differences between women and men were found for prevalence of polymorphism of the gene for cx37. Body mass index and waist circumference were higher in men, whereas total body fat content was higher in women. Women and men did not differ in pulse pressure and lipid parameters with the exception of AIP which was higher (i.e. less favorable) in men. Men had higher values of vitamin D and GGT than women and no differences were detected for hsCRP and FIB-4. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding vascular parameters, women had lower ABI, TBI and higher ORI (less favorable value) than men, while men had higher CIMT, BSCar, BSFem, uACR and lower cystatin C clearance than women. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eDemographics and history data (all data are means \u0026plusmn; SD, if not stated differently)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"619\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003cp\u003e(n=227)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003eMen\u003c/p\u003e\n \u003cp\u003e(n=235)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e43.8 \u0026plusmn; 12.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e43.3 \u0026plusmn; 14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003eDuration of diabetes (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e21.7 \u0026plusmn; 10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e22.5 \u0026plusmn; 12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.448\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003ePrevalence of smoking (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e31.9 %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e43 %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003ePrevalence of hypertension (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e37.9 %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e49.8 %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003ePrevalence of dyslipidemia (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e30.1 %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e34.9 %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.275\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003eGene for connexin 37 n (%)\u0026nbsp;TT/CT/CC genotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e21/104/102 (9.3/45.8/44.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\"\u003e\n \u003cp\u003e24/101/110\u003c/p\u003e\n \u003cp\u003e(10.2/43.0/46.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.816\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003ePrevalence of known ASCVD n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e21 (9.2)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\"\u003e\n \u003cp\u003e30 (12.7)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003ePrevalence of retinopathy/treatment\u0026nbsp;\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e111/47 (48.8/20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\"\u003e\n \u003cp\u003e115/54 (48.9/23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.000/0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003ePrevalence of nephropathy n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e65 (28.6)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e73 (30.6)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.612\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003ePrevalence of diabetic foot n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e17 (7.4)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e27 (11.5)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003eBody mass index (kg.m\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e25.4 \u0026plusmn; 4.5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e26.9 \u0026plusmn; 4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003eWaist circumference (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e80.2 \u0026plusmn; 10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e92.4 \u0026plusmn; 12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003eTotal body fat (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e27.9 \u0026plusmn; 7.3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e19.29 \u0026plusmn; 7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\"\u003e\n \u003cp\u003ePulse pressure (mm Hg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\"\u003e\n \u003cp\u003e53.2 \u0026plusmn; 13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e55.7 \u0026plusmn; 14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eNon- HDL cholesterol (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e3.18 \u0026plusmn; 0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e3.33 \u0026plusmn; 0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eAtherogenic index of plasma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e-0.27 \u0026plusmn; 0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e-0.09 \u0026plusmn; 0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eRemnant cholesterol (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e0.56 \u0026plusmn; 0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e0.60 \u0026plusmn; 0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eLipoprotein (a) (mg/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e254.1 \u0026plusmn; 369.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e251.2 \u0026plusmn; 332.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003ehsCRP (mg/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e2.21 \u0026plusmn; 2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e2.19 \u0026plusmn; 3.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.939\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eHbA1c (mmol/mol)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e68.1 \u0026plusmn; 14.8\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e62.7 \u0026plusmn; 14.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eHOMA-IR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e0.99 \u0026plusmn; 3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e1.29 \u0026plusmn; 2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003ePlasma vitamin D (nmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e53.39 \u0026plusmn; 27.17 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e58.12 \u0026plusmn; 22.1 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eGama-glutamyl transferase (ukat/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e0.38 \u0026plusmn; 0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e0.63 \u0026plusmn; 0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eFIB-4 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e0.87 \u0026plusmn; 0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e0.98 \u0026plusmn; 0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eAnkle brachial index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e1.04 \u0026plusmn; 0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e1.11 \u0026plusmn; 0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eToe brachial index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e0.8 \u0026plusmn; 0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e0.86 \u0026plusmn; 0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eCIMT (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e0.69 \u0026plusmn; 0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e0.76 \u0026plusmn; 0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eBelcaro score carotid I/II/III/IV n (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e141/79/6/1 (61.7/35.2/2.6/0.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e103/103/27/2\u003c/p\u003e\n \u003cp\u003e(43.8/43.8/11.5/0.008)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eBelcaro score femoral I/II/III/IV n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e166/37/24/0\u003c/p\u003e\n \u003cp\u003e(72.7/16.3/10.6/0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e136/67/31/1\u003c/p\u003e\n \u003cp\u003e(57.9/28.5/13.2/0.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eOliva Roztocil index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e0.27 \u0026plusmn; 0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e0.26 \u0026plusmn; 0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eUrine Albumine/Creatinine (mg/mol creatinine)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e7.82 \u0026plusmn; 37.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e17.3 \u0026plusmn; 62.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.22617124394184%\" valign=\"top\"\u003e\n \u003cp\u003eCystatin C clearance (ml/s/1,73m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.455573505654282%\" valign=\"top\"\u003e\n \u003cp\u003e1.80 \u0026plusmn; 0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.58642972536349%\" valign=\"top\"\u003e\n \u003cp\u003e1.49 \u0026plusmn; 0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.731825525040387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e ASCVD: cardiovascular disease of atherosclerotic origin,\u0026nbsp;CIMT: intima-media thickness of common carotid artery, FIB-4: fibrosis 4 liver index, HOMA-IR: Homeostatic Model Assessment for Insulin Resistance, hsCRP -C-reactive protein measured by high sensitivity method\u003c/p\u003e\n\u003cp\u003eAll patients were treated by intensified insulin therapy, 49% of women and 43% of men used the insulin pump therapy.\u003cem\u003e\u0026nbsp;\u003c/em\u003eIn addition, 25% of women and 31% of men used continuous glucose sensors or flash glucose monitoring during last year regularly. In addition, 8% of women and 6% of men needed additional metformin therapy to improve their insulin sensitivity.\u003cem\u003e\u0026nbsp;\u003c/em\u003eMen were treated by higher mean insulin dose (0.66 \u0026plusmn; 0.19 vs. 0.62 \u0026plusmn; 0.22 IU/kg/day, p\u0026lt; 0.01) and more frequently treated by ACE/ARB1 inhibitors than women (46% vs. 35%, p\u0026lt; 0.01) while no difference was observed for hypolipidemic treatment (24% and 29%). In addition, 30% women reported menopausal status.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeterminants of directly measured vascular and renovascular parameters\u003c/strong\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eABI (\u003cstrong\u003eFigure 1a)\u003c/strong\u003e was positively and strongly associated with age, moderately with waist circumference, with Lp(a) lower than 600 mg/l, and with GGT (p\u0026lt;0.001, p=0.029\u003cem\u003e,\u0026nbsp;\u003c/em\u003ep=0.025, and p=0.026 for GGT equal or more than 0.65 ukat/l, respectively) and it was inversely and strongly associated with female sex, pulse pressure, and inversely and moderately with RLPC (p=0.003, p\u0026lt;0.001, and p=0.022, respectively). No modifying effect of sex was observed. Regarding modifying effect of cx37 gene polymorphism, in CC homozygotes ABI was positively and moderately associated with RLPC (p=0.03) and it was inversely and moderately associated with GGT (p=0.032 for GGT equal or more than 0.65 ukat/l, respectively) and inversely and moderately with Lp(a) (p=0.027).\u003c/p\u003e\n\u003cp\u003eTBI (\u003cstrong\u003eFigure 1b\u003c/strong\u003e) was inversely and strongly associated with age, female sex, pulse pressure, and Lp(a) (p\u0026lt;0.001, p=0.01, p\u0026lt;0.001, and p=0.01, respectively) and it was inversely and moderately associated with hsCRP (p=0.035, with individual coefficients p=0.005-0.49 with the highest predicted values for hsCRP 0.5, followed by 1.5-2.5 and 0.5-1.5, respectively). Regarding modifying effect of sex, in females it was positively and moderately associated with higher body fat and with higher AIP, and inversely and strongly with history of smoking (p=0.029 and p=0.04, and p=0.01, respectively). Regarding modifying effect of cx37 gene, in CC homozygotes TBI was inversely and strongly associated with reported dyslipidemia (p=0.007) and positively and moderately with female sex (p=0.04).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1: \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeterminants of Ankle brachial index (a) and Toe brachial index (b) in type 1 diabetes (\u003c/strong\u003ex axis\u003cstrong\u003e\u0026nbsp;-\u0026nbsp;\u003c/strong\u003elogarithmic transformation of p-value/ p values depicted as inverse logarithm: longer bars correspond to lower p-value; black bars indicate significant association and/or modification by sex or connexin37 gene polymorphism; gray bars: no association and no interaction; minus/plus signs at the basis of the bars means positive or inverse association). Abbreviations: FIB-4- Fibrosis-4 Liver Index; GGT \u0026ndash; gama-glutamyl transferase; HbA1c - glycated hemoglobin, HOMA-IR - Homeostatic Model Assessment for Insulin Resistance; Connexin37 gene CC \u0026nbsp;- CC homozygotes\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBSCar (\u003cstrong\u003eFigure 2a\u003c/strong\u003e) was strongly and positively associated with age, CC homozygosity, HbA1c, history of smoking, pulse pressure, and waist circumference (p\u0026lt;0.001, p=0.006, p=0.01, p\u0026lt;0.001, p\u0026lt;0.001, and p=0.002, respectively). No modifying effect of sex was observed. Regarding modifying effect of cx37 gene polymorphism, in CC homozygotes BSCar was inversely and strongly associated with RLPC and positively and moderately with AIP (p=0.01 and p=0.04, respectively).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBSFem (\u003cstrong\u003eFigure 2b\u003c/strong\u003e) was positively and strongly associated with age, HbA1c, smoking and waist circumference and moderately with female sex and pulse pressure (p\u0026lt;0.001, p=0.002, p=0.002, and p\u0026lt;0.001, and p=0.03 and p=0.03, respectively) and it was inversely and strongly associated with body fat (p\u0026lt;0.001). Regarding modifying effect of sex,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ein females\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eBSFem was inversely and strongly associated with non-HDL cholesterol and positively and strongly with diabetes duration (p=0.007 and p=0.002, respectively). Regarding modifying effect of cx37 gene polymorphism, in CC homozygotes BSFem was positively and moderately associated with non-HDL cholesterol (p=0.02)\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 2: Determinants of Belcaro score of carotid (a) and femoral (b) arteries in type 1 diabetes\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003ex axis:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ep values depicted as inverse logarithm: longer bars correspond to lower p-value; black bars indicate significant association and/or modification by sex or connexin37 gene polymorphism; gray bars: no association and no interaction; minus/plus signs at the basis of the bars means positive or inverse association). Abbreviations: FIB-4- Fibrosis-4 Liver Index ; GGT \u0026ndash; gama-glutamyl transferase; HbA1c - glycated hemoglobin, HOMA-IR - Homeostatic Model Assessment for Insulin Resistance, Connexin37 gene CC \u0026nbsp;- CC homozygotes \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCIMT was positively and strongly associated with age and non-HDL cholesterol, and moderately with diabetes duration and HbA1c (p\u0026lt;0.001 and p=0.007, and p=0.02 and p=0.02, respectively) and it was inversely and strongly associated with plasma vitamin D (p=0.009). Regarding modifying effect of sex, in females it was positively and moderately associated with Lp(a) (p=0.03) and inversely and moderately with non-HDL cholesterol (p=0.05). No modifying effect of cx37 gene polymorphism was detected.\u003c/p\u003e\n\u003cp\u003euACR (\u003cstrong\u003eFigure 3a\u003c/strong\u003e)\u0026nbsp;was positively and strongly associated with female sex, duration of diabetes, HbA1c, history of hypertension, pulse pressure,\u0026nbsp;AIP and FIB-4, and\u0026nbsp;moderately with\u0026nbsp;RLPC, Lp(a) and\u0026nbsp;CC homozygosity (p=0.003, p=0.01, p\u0026lt;0.001, p\u0026lt;0.001, p=0.004 p\u0026lt;0.001 and p=0.01, and p=0.02, p=0.02 and p=0.02, respectively) and it was inversely and strongly associated with body fat (p\u0026lt;0.001). Regarding modifying effect of sex, in females\u0026nbsp;uACR\u0026nbsp;was inversely and strongly associated with duration of diabetes (p=0.01). Regarding modifying effect of cx37 gene polymorphism, in CC homozygotes\u0026nbsp;uACR\u0026nbsp;was inversely and strongly associated with HbA1c (p=0.01).\u003c/p\u003e\n\u003cp\u003eORI (\u003cstrong\u003eFigure 3b\u003c/strong\u003e)\u0026nbsp;was positively and strongly associated with age, diabetes duration, smoking, and pulse pressure (p=0.002, p\u0026lt;0.001, p=0.004, and p\u0026lt;0.001, respectively) and it was inversely and moderately associated with female sex and strongly with plasma vitamin D (p=0.02 and p\u0026lt;0.001. respectively). Regarding modifying effect of\u0026nbsp;sex, in females ORI was positively and strongly associated with plasma vitamin D (p=0.003). Regarding modifying effect of\u0026nbsp;cx37 gene, in CC homozygotes ORI was positively and moderately associated with history of hypertension and RLPC (p=0.02 and p=0.02, respectively) and inversely and moderately with female sex (p=0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 3: Determinants of urine albumin/ creatinine ratio \u0026nbsp;(a) and Oliva Roztocil index (b) in type 1 diabetes\u003c/strong\u003e \u003cstrong\u003e(\u003c/strong\u003ex axis\u003cstrong\u003e\u0026nbsp;-\u0026nbsp;\u003c/strong\u003elogarithmic transformation of p-value/ p values depicted as inverse logarithm: longer bars correspond to lower p-value; black bars indicate significant association and/or modification by sex or connexin37 gene polymorphism; gray bars: no association and no interaction; minus/plus signs at the basis of the bars means positive or inverse association) Abbreviations: FIB-4- Fibrosis-4 Liver Index, GGT \u0026ndash; gama-glutamyl transferase; HbA1c - glycated hemoglobin, HOMA-IR - Homeostatic Model Assessment for Insulin Resistance, ORI \u0026ndash; Oliva Roztocil Index, Connexin37 gene CC \u0026nbsp;- CC homozygotes\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCystatin C clearance was inversely and strongly associated with AIP, Lp(a), hypertension, and moderately with pulse pressure and smoking (p\u0026lt;0.001, p=0.01,\u0026nbsp;p=0.01, and p=0.02 and p=0.02, respectively) and it was positively and moderately associated with age (p=0.05). Regarding modifying effect of sex, in females, cystatin C clearance\u0026nbsp;was positively and moderately associated with age (p=0.02). Regarding modifying effect of cx37 gene, in CC homozygotes\u0026nbsp;cystatin C clearance\u0026nbsp;was associated positively and strongly with AIP (p=0.01).\u003c/p\u003e\n\u003cp\u003eFinally, regarding intercorrelations between continuous vascular parameters (ABI, TBI, uACR, ORI), inverse strong linear correlation was found only between TBI and ORI (r= -0.46).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cross-sectional study described associations of traditional and novel cardiovascular risk factors with different vascular parameters in middle-aged population of T1D patients. \u0026nbsp;It also evaluated potential modification of these associations by sex and cx37 gene polymorphism.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSpecific diabetic risk factors and vascular parameters\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main determinants considered to be associated with unfavorable vascular parameters in T1D were age, duration and metabolic control of diabetes, the latter represented by HbA1c. As expected, age was strongly associated with unfavorable values of most of vascular parameters with the exception of albuminuria while duration of diabetes was strongly associated with parameters representing mostly microvascular disease as were albuminuria and ORI but not with macrovascular parameters. Therefore, these data not only confirmed that duration of diabetes rather than chronological age was important for deleterious vascular changes but also indicated that hyperglycemia in T1D firstly affects microcirculatory parameters. This confirms that patients with longer T1D duration should be considered at high or very high cardiovascular risk [\u003cstrong\u003e37\u003c/strong\u003e\u003cstrong\u003e].\u003c/strong\u003e The metabolic control of diabetes represented by HbA1c was associated mainly with macrovascular changes represented by plaques in carotid and femoral arteries but also with more subtle vascular and/or renovascular changes as were CIMT and albuminuria. Therefore, in addition to albuminuria also CIMT not recommended for individual risk assessment in recent guidelines [\u003cstrong\u003e38\u003c/strong\u003e\u003cstrong\u003e]\u003c/strong\u003e, could be still valuable tool for vascular risk assessment in specific populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTraditional cardiovascular risk factors and vascular parameters:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs traditional cardiovascular risk factors we analyzed smoking, blood pressure, waist circumference, body fat, HOMA-IR and plasma lipids. Smoking was associated with macrovascular changes represented by focal changes in carotid and femoral arteries and with ORI, the latter representing combination of arterial stiffness and microvascular changes [\u003cstrong\u003e27-28\u003c/strong\u003e\u003cstrong\u003e]\u003c/strong\u003e. Smoking was not associated with albuminuria and, surprisingly, it was not significantly associated with ABI and TBI. However, in women, smoking was strongly associated with lower TBI. This phenomenon in diabetic population was already described [\u003cstrong\u003e39, 40\u003c/strong\u003e\u003cstrong\u003e]\u0026nbsp;\u003c/strong\u003ebut our findings further indicate that\u0026nbsp;this effect is enhanced in T1D women and affects their smaller vessels. More detailed description of the impact of sex on other associations is presented below.\u003c/p\u003e\n\u003cp\u003eVery important and interesting finding was that pulse pressure was strongly associated with less favorable values of almost all macro- and microvascular parameters under study including renovascular parameters with the exception of CIMT. This indicates that in T1D pulse pressure even in the range of physiological values \u003cstrong\u003e(Table 1\u003c/strong\u003e) could be associated with vascular damage at multiple levels. The role of blood pressure in T1D was supported by results of large meta-analysis in which hypertension partly mediated the causal effects of T1D on peripheral and coronary atherosclerosis\u0026nbsp;[\u003cstrong\u003e6\u003c/strong\u003e\u003cstrong\u003e].\u0026nbsp;\u003c/strong\u003e Pathophysiological explanation is that pulse pressure reflects also arterial stiffening in diabetic patients; it was already described to be higher in T1D than in non-diabetic population in a cross-sectional, case-control study of almost 3,000 patients. Moreover, whereas higher pulse pressure in this study was more pronounced in subjects with diabetic nephropathy, it was also found in patients with normal albumin excretion rate compared to controls\u0026nbsp;[\u003cstrong\u003e41\u003c/strong\u003e], in another study, pulse pressure was used as the main endpoint in T1D [\u003cstrong\u003e42\u003c/strong\u003e]. \u0026nbsp;Additionally, the association of pulse pressure with vascular parameters was not modified by sex and cx37 gene polymorphism. Therefore, increased pulse pressure as indicator for future cardiovascular events in older populations [\u003cstrong\u003e43\u003c/strong\u003e] should be considered also\u0026nbsp;in younger T1D patients irrespectively of sex and genetic background.\u003c/p\u003e\n\u003cp\u003eIn contrast to pulse pressure, HOMA-IR as a marker of insulin resistance, was not associated with any vascular parameter. In contrast, waist circumference as simple parameter for insulin resistance was strongly associated with atherosclerotic changes in carotid and femoral arteries. Interesting finding was that amount of body fat was inversely associated with femoral atherosclerosis and albuminuria indicating its potential protective vascular effect in T1D; moreover, in women, this protective effect was observed also for smaller vessels (TBI). However, if this protection applies also for obese diabetic population (patients in this study had normal body mass index) is less probable. In addition to waist circumference, plasma triglycerides and triglycerides rich lipoproteins [\u003cstrong\u003e44, 45\u003c/strong\u003e\u003cstrong\u003e]\u0026nbsp;\u003c/strong\u003ecould be better indicators of insulin resistance than HOMA-IR. In our study, RLPC representing remnant lipoproteins and AIP representing reverse cholesterol transport [\u003cstrong\u003e24, 46\u003c/strong\u003e\u003cstrong\u003e]\u003c/strong\u003e were strongly associated with albuminuria. The association of AIP with lower cystatin C clearance further underlines potential interconnection of particular lipid parameters with renal impairment. Furthermore, the association of RLPC with lower ABI indicates potential greater impact of remnant lipoproteins on lower extremity arteries. In contrast to less frequently used lipid parameters, representant of atherogenic lipoproteins, non-HDL cholesterol was not associated with any vascular parameter under study. Lp(a) as lipid factor emerging recently for interventions [\u003cstrong\u003e47\u003c/strong\u003e\u003cstrong\u003e]\u0026nbsp;\u003c/strong\u003ewas strongly associated with impaired renal parameters but it was positively associated with ABI. In this case we can speculate that Lp(a) could be associated with increased arterial stiffness represented by relatively higher ABI. Moreover, the latter association was moderate (p=0.03) and only chance observation could not be excluded also because of abnormal distribution of Lp(a). Impact of potential insulin resistance on vasculature including renal parameters was in our study associated rather with waist circumference and lipid parameters representing remnant lipoproteins and reverse cholesterol transport rather than with HOMA-IR. Regarding renovascular factors, similar results were obtained for Lp(a) while none effect of atherogenic non-HDL cholesterol was found. These data might indicate potential connection of specific lipid factors with renal impairment. It should be admitted that because of cross-sectional character of the study we cannot exclude reverse associations between lipids and renal parameters.\u0026nbsp;[\u003cstrong\u003e48\u003c/strong\u003e]. Nevertheless, prospectively evaluated effect of traditional cardiovascular risk factors on renal parameters was described in prospective study in almost\u0026nbsp;28,000 children and adolescents with T1D. Risk factors for albuminuria in this study were diabetes duration, HbA1C and blood pressure, but also LDL cholesterol, the latter not confirmed in our study. Difference in assessment of the effect of atherogenic lipids could be attributed to different characteristics of populations under study. In our study older patients were recruited. Moreover, in cross-sectional analysis in this prospective study diabetes duration, HbA1C, dyslipidemia, blood pressure, and male sex, but not lipids were identified as risk factors for nephropathy taking into account other cardiovascular risk factors [\u003cstrong\u003e49\u003c/strong\u003e]\u003cem\u003e.\u0026nbsp;\u003c/em\u003eIn general, the exact role of lipid parameters in T1D is not definitely solved [\u003cstrong\u003e50\u003c/strong\u003e] and one of reasons could be close association of lipids with metabolic control of T1D in contrast to non-diabetic population [\u003cstrong\u003e51\u003c/strong\u003e].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNovel risk factors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNovel risk factors including inflammatory markers represented by plasma vitamin D, hsCRP and markers of liver impairment represented by GGT and FIB-4 did not show robust associations with most of vascular markers under study. Vitamin D concentration was associated with less favorable values of CIMT and ORI and this association was more pronounced in women. Vitamin D deficiency is considered a risk marker for major adverse cardiovascular events in T1D but not for microvascular complications or all-cause mortality [\u003cstrong\u003e52\u003c/strong\u003e]. Based on our data, plasma vitamin D might be associated both with macro- and microvascular changes represented by CIMT and by ORI and this association could be sex dependent at similar plasma levels of vitamin D (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInflammatory factors were already proposed as one of the strongest non-lipid determinants of vascular damage [\u003cstrong\u003e53\u003c/strong\u003e]. Particularly, in patients with T1D inflammatory markers were associated with carotid atherosclerosis in a cross-sectional study from Spain by Mariaca et al. with comparable size and age of study population as in our study [\u003cstrong\u003e54\u003c/strong\u003e]. In contrast to data of Mariaca et al., hsCRP in our study was associated with impairment of smaller vessels represented by lower TBI but not with atherosclerosis in carotid and femoral arteries. The explanation of this difference is that our population was less selected, also patients with duration of T1D less than 10 years were included and less than 3% women and 12% men had detectable carotid plaques (BSCar \u0026gt; II) compared to 41% in the study of Mariaca et al. Revealing association of inflammatory factors with vascular damage is also important because there are data from intervention study using combination of empagliflozin and metformin decreased inflammatory parameters including CRP and improved arterial function in adults with T1D [5\u003cstrong\u003e5\u003c/strong\u003e].\u003c/p\u003e\n\u003cp\u003eGGT considered as another risk factor especially for microvascular disease [\u003cstrong\u003e56\u003c/strong\u003e] was in our study associated with lower ABI which means with macrovascular parameter. However, in this case GGT measurement by standard laboratory methods could miss particular GGT iso-enzymes which could play different roles in metabolic diseases [\u003cstrong\u003e57\u003c/strong\u003e\u003cstrong\u003e];\u003c/strong\u003e additionally, substantial non-linear relationship with vascular parameters under study was detected interfering with interpretation of studied relationships as already described in diabetes\u0026nbsp;[\u003cstrong\u003e58\u003c/strong\u003e\u003cstrong\u003e]\u003c/strong\u003e. Finally, FIB-4 as a marker of liver fibrosis, insulin resistance, but also of cardiovascular disease in T1D [\u003cstrong\u003e59\u003c/strong\u003e] was in our study associated mainly with albuminuria. This finding underlines potential role of non-glycemic and non-lipid factors in vascular disease. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSex and cx37 gene polymorphism modifications of observed associations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn women we observed reversed association of diabetes duration with albuminuria whereas the association of diabetes duration with atherosclerosis in femoral arteries was further enhanced. At the same time, in women higher non-HDL cholesterol was associated with less femoral atherosclerosis. This indicates potential protection of renal function and arteries in lower extremities against long lasting glycemia and lipid factors in women. However, the effect of long lasting glycemia on lower extremity arteries could be accelerated in women. In addition, more deleterious effect of smoking on smaller arteries in women was described above.\u0026nbsp;We are not able to reliably propose mechanisms responsible for these findings based on design if this study. In the literature proposed mechanisms of between sex differences are based on psychosocial and biological factors. Psychosocial factors including behavioral patterns and differences in treatment strategies are difficult to exactly characterize. Regarding biological mechanisms it is proposed that sex hormonal disbalance in women with T1D may contribute to more atherogenic lipid profile, insulin resistance, higher inflammation, and loss of vasoprotective effect of female sex seen on epidemiological level in non-diabetic population. However, even in this respect, not unequivocal data are presented. On one hand, in adolescents with T1D lower levels of estradiol were proposed as potential cause of increased risk in women compared to nondiabetic control women [\u003cstrong\u003e60\u003c/strong\u003e\u003cstrong\u003e]\u003c/strong\u003e; furthermore, among premenopausal women with diabetes, hypothalamic hypoestrogenism was more prevalent and associated with coronary artery disease \u003cstrong\u003e[61\u003c/strong\u003e\u003cstrong\u003e].\u003c/strong\u003e On the other hand, in T1D women, higher concentration of estradiol was proposed to be associated with increased vascular damage [\u003cstrong\u003e62\u003c/strong\u003e\u003cstrong\u003e]\u003c/strong\u003e. Sex differences were also highlighted using\u0026nbsp;Steno type 1 risk engine to estimate the 10-year risk of developing cardiovascular events in multicenter, cross-sectional study involving 2,041 middle aged patients with T1D including 45% women. In this study, the 10-year estimated cardiovascular risk was higher in men younger than 55 years than in women of similar age and sex differences disappeared at age equal or more than 55 years. Therefore, age could play also important role in sex differences and as suggested by authors, female sex is no longer protective at certain age, which could correspond to age of menopause.\u0026nbsp;Therefore, in our study attenuation or acceleration of the impact of particular risk factor on different vascular territories could reflect also different hormonal status of T1D women. In addition, interesting in our study was that reported frequency of macro- and microvascular disease was similar in women and men, whereas directly measured vascular parameters have shown marked differences between women and men.\u003c/p\u003e\n\u003cp\u003eRegarding, cx37 gene polymorphism in our study, we observed that CC homozygosity might attenuate or even reverse the effect of metabolic control of diabetes (HbA1c) on albuminuria, while it accelerates the effect of remnant lipoproteins on carotid atherosclerosis. In addition, in CC homozygotes dyslipidemia was associated with lower values of TBI but in the same group, higher values of remnant lipoproteins represented by RLPC were associated with less atherosclerotic changes in carotid arteries. This indicates potential selective effect of CC genotype on risk factors-vascular associations in patients with T1D\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eCarrier\u003cstrong\u003es\u0026nbsp;\u003c/strong\u003eof\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eT or C allele of cx37 gene are reported to be at increased or decreased cardiovascular risk and the main proposed modifying factor making these differences was diabetic status, namely type 2 diabetes. Our data indicate potential modifying effect of this gene also in T1D. From pathophysiological perspective we speculate sensitivity of connexin 37 produced by different gene could be differently affected by glycation affecting is function in gap junctions and affecting intercell communication in the vessel wall [\u003cstrong\u003e63, 64\u003c/strong\u003e\u003cstrong\u003e]\u003c/strong\u003e. However, our study was not designed to answer this question, and, to our knowledge, no data are available to support or discard this presumption. Therefore, potential modification of functionality of cx37 by hyperglycemia remains hypothetical.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main strength of this study is that unselected population of patients with T1D followed in one center in a standard manner were included. Regarding study of traditional and novel cardiovascular risk factors, we exploited several methods of detection of vascular disease including less frequently used parameters. Whereas screening in T1D is not generally recommended [\u003cstrong\u003e65\u003c/strong\u003e], evaluating data obtained from different vascular territories could help in targeting important determinants of vascular disfunction in T1D. In this respect, wide range of hemodynamic, metabolic cardiovascular factors were studied including vitamin D and markers of inflammation and liver fibrosis. Regarding hemodynamic factors, we focused on pulse pressure as indicator of blood pressure because it reflects also arterial stiffness and could be early and simply obtainable parameter for risk assessment in diabetic population. In addition, we focused on the effect of non-LDL lipid parameters on vascular system. In particular we studied non-HDL cholesterol rather than LDL cholesterol, despite we had this parameter (correlation between both parameters was 0.89) and focused rather on representatives of triglyceride rich lipoproteins and on Lp(a), discussed as important risk factors in diabetic population [\u003cstrong\u003e66, 67\u003c/strong\u003e].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe main limitation of our study is its cross-sectional character not allowing us to definitely establish cause and effect relationships. However, because multitude factors and vascular parameters were studied with similar results, we could consider most of observed associations as valid. Another limitation is that our findings are based on\u0026nbsp;preclinical vascular parameters which not always transform to clinical events. But as proved from previous studies, most of studied vascular parameters really reflect future risk of cardiovascular and often fatal events and patients with T1D are not exceptional in this respect. While connexin 37 gene was proposed as candidate gene for ischemic heart disease it represents simple single nucleotide polymorphism and more extensive and sophisticated genetic markers are now studied including genome wide associations. But this particular gene marker was intensively studied and its potential association with ischemic heart disease was repeatedly described including potential modification by diabetes and central obesity [\u003cstrong\u003e19, 20, 25, 63, 64, 68\u003c/strong\u003e]. In addition, this approach also offers some pathophysiological background regarding impaired communication between cells in vascular wall in diabetic patients. Finally, another limitation is that only Caucasian population was studied and we should be cautious to generalize these results to other ethnic groups. \u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis cross-sectional study on one hand confirms already described findings, nevertheless, on the other hand, to the best of our knowledge interesting new associations were revealed regarding blood pressure, lipid parameters and modification of these associations by sex and genetic factors. In particular, we demonstrated that in middle aged T1D patients, pulse pressure was consistently associated with less favorable values in almost all macro- and microvascular parameters independently on sex and cx37 gene polymorphism and that lipid parameters were strongly associated with renal impairment and were modified by sex and cx37 gene polymorphism. Therefore, easily obtainable parameter as pulse pressure should be taken into account in patients with T1D irrespectively of sex and genetic background. Regarding plasma lipids, their association with renal function is more complex and we might detect reverse relationships because of design of our study. Decision whether pulse pressure, remnant lipoproteins, Lp(a) and other determinants of vascular damage should become treatment targets in T1D remains should be based on results of clinical trials.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eABI: ankle brachial index\u003c/p\u003e\n\u003cp\u003eAIP: atherogenic index of plasma\u003c/p\u003e\n\u003cp\u003eALT: alanine-amino transferase\u003c/p\u003e\n\u003cp\u003eASCVD: cardiovascular disease of atherosclerotic origin\u003c/p\u003e\n\u003cp\u003eAST: aspartate-amino transferase\u003c/p\u003e\n\u003cp\u003eBSCar: Belcaro score carotid\u003c/p\u003e\n\u003cp\u003eBSFem: Belcaro score femoral\u003c/p\u003e\n\u003cp\u003eCx37: connexin 37\u003c/p\u003e\n\u003cp\u003eCIMT: carotid intima media thickness of common carotid artery\u003c/p\u003e\n\u003cp\u003eFIB-4: Fibrosis-4 Liver Index\u003c/p\u003e\n\u003cp\u003eGGT: gama-glutamyl transferase\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHbA1c: glycated hemoglobin\u003c/p\u003e\n\u003cp\u003eHOMA-IR: Homeostatic Model Assessment for Insulin Resistance\u003c/p\u003e\n\u003cp\u003ehsCRP: C-reactive protein measured by high sensitivity method\u003c/p\u003e\n\u003cp\u003eLDL cholesterol: low density cholesterol\u003c/p\u003e\n\u003cp\u003eLp(a): lipoprotein (a)\u003c/p\u003e\n\u003cp\u003eNon-HDL cholesterol: total cholesterol \u0026ndash; HDL cholesterol\u003c/p\u003e\n\u003cp\u003eORI: Oliva-Roztocil interbranch index\u003c/p\u003e\n\u003cp\u003eRLPC: remnant plasma cholesterol (total \u0026ndash; LDL-HDL cholesterol)\u003c/p\u003e\n\u003cp\u003eTBI: toe brachial index\u003c/p\u003e\n\u003cp\u003eT1D: type 1 diabetes\u0026nbsp;\u003c/p\u003e\n\u003cp\u003euACR: urine albumin/creatinine ratio\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding/acknowledgement\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Ministry of Health of the Czech Republic, grant No. NU20-01-00083 and by the project National Institute for Research of Metabolic and Cardiovascular Diseases [Programme EXCELES, ID Project No. LX22NPO5104] - Funded by the European Union \u0026ndash; Next Generation EU and by Ministry of Health of the Czech Republic, Grant [No.NU22-A-125]. All rights reserved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study conformed to the provisions of the Declaration of Helsinki and was approved by Ethical commitee under No. NU20-01-0008. Informed consent was obtained for all participants involved in this study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ePP did all clinical measurements, collected the data and prepared draft of the manuscript, mainly methods, MC did all statistical analyses and prepared Figures 1-3, JH and DD were responsible for genetic analysis and interpretation of genetic data. MK contributed to design of the study and participated in data and funding acquisition JP conceived and designed the study and finally wrote the main manuscript. All authors reviewed the manuscript and contributed to its final version.All authors have reviewed and agree to the published version of the manuscript. Funding organization had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhao Y, Quan E, Zeng T, Huang Z, Luo Y, Peng L, et al. Type 1 diabetes, its complications, and non-ischemic cardiomyopathy: a mendelian randomization study of European ancestry. Cardiovasc Diabetol. 2024;23(1):31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCreager MA, L\u0026uuml;scher TF, Cosentino F, Beckman JA. Diabetes and vascular disease: pathophysiology, clinical consequences, and medical therapy: Part I. Circulation. 2003;108(12):1527\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei J, Tian J, Tang C, Fang X, Miao R et al. 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Cardiovasc Diabetol. 2023;22(1):243.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeens MJ, Pfenniger A, Kwak BR, Delmar M. Regulation of cardiovascular connexins by mechanical forces and junctions. Cardiovasc Res. 2013;99(2):304\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHautefort A, Pfenniger A, Kwak BR. Endothelial connexins in vascular function. Vasc Biol. 2019;1(1):H117\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmer Diabet A. 10. Cardiovascular Disease and Risk Management: Standards of Medical Care in Diabetes-2021. Diabetes Care. 2021;44: S125\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWadstr\u0026ouml;m BN, Pedersen KM, Wulff AB, Nordestgaard BG. Elevated remnant cholesterol and atherosclerotic cardiovascular disease in diabetes: a population-based prospective cohort study. 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Exp Gerontol. 2014;58:203\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":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":"type 1 diabetes mellitus, vascular parameters, cardiovascular risk factors, sex, gene for connexin 37","lastPublishedDoi":"10.21203/rs.3.rs-4512208/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4512208/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePredictors of cardiovascular complications are well established in type 2 diabetes but not in type 1 diabetes (T1D). We analyzed the association between traditional and novel cardiovascular risk factors and macro- and microvascular parameters in T1D patients and modification of these associations by sex and genetic factors.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn a cross-sectional study we analyzed in T1D patients younger than 65 years the association of wide range of cardiovascular risk factors with vascular parameters represented by ankle brachial index (ABI), toe brachial index (TBI), by duplex ultrasound measured presence of plaques in carotid and femoral arteries (Belcaro score) and intima media thickness of carotid arteries (CIMT), by photoplethysmography measured interbranch index expressed as Oliva/Roztocil index (ORI), and renal parameters represented by urine albumin/creatinine ratio (uACR) and cystatin C filtration rate. We evaluated these associations by multivariate regression analysis including interactions with sex and gene for connexin 37 (cx37) polymorphism (rs1764391).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn 235 men and 227 women (mean age 43.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6 years; mean duration of diabetes 22.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3 years) pulse pressure was the strongest predictor of unfavorable values of most of vascular parameters under study (ABI, TBI, Belcaro scores, uACR and ORI) while plasma lipids represented by remnant cholesterol (cholesterol \u0026ndash; LDL-HDL cholesterol), atherogenic index of plasma (log (triglycerides/HDL cholesterol) and Lp(a) were associated mainly with renal impairment (uACR, cystatin C clearance and lipoprotein (a)). Plasma non-HDL cholesterol (total \u0026ndash; HDL cholesterol) was not associated with any vascular parameter under study. In contrast to the pulse pressure, the associations of lipid parameters with renal and vascular parameters were modified by sex and cx37 gene.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePulse pressure was the strongest determinant for macro- and microvascular parameters in T1D and was not influenced by sex and genetic factors while lipid parameters were associated mostly with renal impairment and were modified by sex and genetic factors.\u003c/p\u003e","manuscriptTitle":"Determinants of Vascular Impairment in Type 1 Diabetes; Impact of Sex and Connexin 37 Gene Polymorphism, Cross-sectional study.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-14 18:46:42","doi":"10.21203/rs.3.rs-4512208/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-25T04:12:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-24T21:26:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"91449515233906778476145623788446132699","date":"2024-06-03T21:28:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"339902980044177072036894967409188383046","date":"2024-06-02T18:54:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-02T18:26:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"82307488149304182214276986836816018747","date":"2024-06-02T18:25:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"106446404748619567004918704500419461650","date":"2024-06-02T15:45:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-02T03:39:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-02T03:29:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-01T07:47:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cardiovascular Diabetology","date":"2024-06-01T06:18:13+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":"8790df80-3c97-4729-bb4d-089c48710825","owner":[],"postedDate":"June 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-26T16:08:29+00:00","versionOfRecord":{"articleIdentity":"rs-4512208","link":"https://doi.org/10.1186/s12933-024-02401-0","journal":{"identity":"cardiovascular-diabetology","isVorOnly":false,"title":"Cardiovascular Diabetology"},"publishedOn":"2024-08-22 15:57:22","publishedOnDateReadable":"August 22nd, 2024"},"versionCreatedAt":"2024-06-14 18:46:42","video":"","vorDoi":"10.1186/s12933-024-02401-0","vorDoiUrl":"https://doi.org/10.1186/s12933-024-02401-0","workflowStages":[]},"version":"v1","identity":"rs-4512208","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4512208","identity":"rs-4512208","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}