{"paper_id":"15096866-c073-438e-8f74-68adc13a06eb","body_text":"Sex Differences in Clinical Manifestations and Serum CXCR4/CXCL12 Levels in Patients with Type 2 Diabetes and Primary Aldosteronism | 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 Sex Differences in Clinical Manifestations and Serum CXCR4/CXCL12 Levels in Patients with Type 2 Diabetes and Primary Aldosteronism wei liu, Juanjuan Zhou, Shanyu Yi, Meiyu Shen, Zaizhao Li, Xin Su This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3939206/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Type 2 diabetes mellitus (T2DM) and hypertension are prevalent chronic diseases in modern society. Primary hyperaldosteronism (PA) is the most common cause of secondary hypertension. Our study examined the clinical characteristics of T2DM patients afflicted with PA. We enrolled a total of 213 T2DM patients with hypertension and observed a 22.1% prevalence of PA within this group. Sex disparities in clinical presentations were observed. Among male PA patients, the incidence of obesity significantly exceeded that of the essential hypertension (EH) group (40% vs. 4.5%, χ2 = 4.172, p = 0.041), with the plasma aldosterone concentration (PAC) demonstrating a positive correlation with body mass index (BMI) (correlation coefficient = 0.318, p = 0.001). In contrast, among female PA patients, the prevalence of proteinuria was notably greater than that in the EH group (54.5% vs. 24.7%, p < 0.05), and the PAC was positively correlated with proteinuria (correlation coefficient = 0.213, p = 0.032). Significant sex differences emerged in the serum concentrations of brain natriuretic peptide (BNP), atrial natriuretic peptide (ANP), C-X-C motif chemokine receptor 4 (CXCR4), C-X-C motif chemokine ligand 12 (CXCL12), adiponectin, and leptin. The serum levels of BNP, ANP, CXCR4, CXCL12, and leptin were significantly correlated with BMI. In female patients, the PAC was significantly positively correlated with CXCR4 (correlation coefficient = 0.322, p = 0.004) and CXCL12 (correlation coefficient = 0.248, p = 0.029). Our findings highlight sex-specific differences in the clinical manifestations of T2DM patients with PA. Notably, the serum BNP, ANP, leptin, adiponectin, CXCR4, and CXCL12 levels exhibited significant sex differences and correlated significantly with BMI. In female patients, the PAC was positively correlated with CXCR4 and CXCL12 levels. type 2 diabetes primary aldosteronism CXCR4 CXCL12 BNP ANP leptin adiponectin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Type 2 diabetes mellitus (T2DM) and hypertension are the most prevalent chronic diseases in contemporary society and contribute significantly to various complications, notably cardiovascular diseases and chronic renal dysfunction. In Chinese adults, the prevalence of T2DM is 11.2% [ 1 ], while hypertension affects 23.2% of the population. The concomitant prevalence of hypertension in Chinese adults with diabetes soared to 45.2%. Notably, primary hyperaldosteronism (PA) has emerged as the leading cause of secondary hypertension, afflicting up to 20% of individuals with refractory hypertension[ 2 ]. The deleterious impact of excessive aldosterone on cardiovascular and renal health is partially independent of blood pressure. Are these manifestations distinct from those in T2DM patients with essential hypertension (EH)? Addressing this question holds crucial implications for our understanding of the clinical landscape when these two common chronic diseases coincide. Furthermore, do differences exist in the serum levels of atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP), the lipid metabolism markers leptin and adiponectin, and CXCR4 and its ligand CXCL12 between EH and PA patients? To answer these questions, we conducted a cross-sectional study by recruiting T2DM patients with hypertension to evaluate the function of the renin-angiotensin-aldosterone system (RAAS) and analyze relevant clinical data; in addition, we quantified the concentrations of serum leptin, adiponectin, ANP, BNP, CXCR4, and CXCL12. 2. Materials and Methods We conducted this study at the Diabetes Clinic of the Second Xiangya Hospital of Central South University (Changsha, Hunan, China), and data were collected every Friday throughout the study period. From January 2020 to December 2021, a total of 213 T2DM outpatients with hypertension were enrolled (Fig. 1). All included patients underwent a physical examination, including height, weight, and BP measurements, and blood was collected for the measurement of the RAAS score and leptin, adiponectin, ANP, BNP, CXCR4 and CXCL12 levels. Diabetes was diagnosed according to the World Health Organization (WHO) criteria. Hypertension was defined as a systolic blood pressure of at least 140 mmHg and/or diastolic blood pressure of at least 90 mmHg or the reported use of hypertension medications. Obesity was defined as a BMI ≥ 28 kg/m2. Hypokalemia was defined as a serum potassium concentration < 3.5 mmol/l. Microalbuminuria was defined by a spot urinary albumin-to-creatinine ratio (UACR) of 30 to 300 mg/g. CV events identified from hospital records at baseline included myocardial infarction; unstable angina pectoris requiring angioplasty; stroke; or transient ischemic attack. The exclusion criteria for individuals were as follows: (1) women who were pregnant or nursing; (2) patients with secondary hypertension caused by other underlying diseases, such as pheochromocytoma, Cushing's syndrome, or renal artery stenosis; (3) patients with serious heart, kidney or liver diseases; (4) patients who were taking diuretic drugs or had stopped using diuretic drugs for less than 4 weeks; and (5) patients with other serious diseases (not suitable for screening). This study was approved by the Ethics Committee of the Second Xiangya Hospital of Central South University, and all patients provided informed consent before participating in the study. Figure 1. Study Flow Chart 2.1. Clinical evaluation The diagnosis of PA followed the criteria of the Endocrine Society[ 1 , 2 ]. Prior to screening, patients discontinued the use of all antihypertensive drugs except for dihydropyridine calcium channel blockers and alpha-adrenergic blockers. Specifically, spironolactone, eplerenone, diuretics, and licorice-containing Chinese medicines were stopped for at least 4 weeks, while beta-blockers, angiotensin-converting enzyme inhibitors, and angiotensin-receptor antagonists were stopped for at least 2 weeks. Evaluation of the RAAS included determination of the PAC and plasma renin activity (PRA) and calculation of the aldosterone-renin ratio (ARR). Patients with a PAC ≥ 15 ng/dl and an ARR ≥ 30 ng/dl/ng/ml/h were further tested with the captopril challenge test (CCT) and/or saline infusion test (SIT). The diagnostic criteria were as follows. After CCT, patients who met all the following criteria were diagnosed with PA: (1) PAC decreased by < 30%, (2) ARR remained ≥ 30 ng/dl/ng/ml/h, and (3) PAC ≥ 11 ng/dl. After SIT, patients with postinfusion plasma aldosterone levels > 10 ng/dl were diagnosed with PA. The serum concentrations of leptin, adiponectin, ANP, BNP, CXCR4 and CXCL12 were measured using appropriate ELISA kits (Jianglai Biotechnology, Shanghai, China) following the manufacturer’s instructions. All tests were conducted in the biochemical laboratory of the Second Xiangya Hospital, Central South University. PAC was determined by chemiluminescence (Maglumi 2000 Plus, China). The intragroup CV of the PAC was ≤ 5%, and the intergroup CV was ≤ 10%. PRA was also measured by chemiluminescence (Maglumi 2000 Plus, China). The intra-assay CV of PRA detection was less than 15%, and the inter-assay CV was less than 10%. 2.2. Statistical analysis Statistical Package for Social Sciences (SPSS) version 23.0 for Windows and GraphPad Prism 5.0 (GraphPad Prism Software, Inc.) were used to analyze the results. Descriptive statistics are reported as mean ± SD or median (interquartile range [IQR]). Categorical variables are expressed as numbers and percentages. Normality tests were used to determine the distribution of variables. ANOVA was used for between-group comparisons of normally distributed variables. The nonparametric Friedman test was used for between-group comparisons of nonnormally distributed variables. p < 0.05 was considered to indicate statistical significance. 3. Results 3.1. Clinical features A total of 213 patients participated in the study, 86 (40%) of whom were initially flagged for altered RAAS activity and subsequently underwent confirmation via CCT. Among these patients, 49 exhibited uninhibited aldosterone levels and reduced renin activity, leading to a PA diagnosis. The overall prevalence of PA among T2DM patients with hypertension was 22.1% (49/213), with no significant sex difference observed. Table 1 displays the clinical characteristics and biochemical data of all the study participants. Patients with PA had a higher PAC and ARR and lower PRA than patients in the EH group did. Patients with PA had lower serum potassium levels (p < 0.001), and the proportion of patients with hypokalemia was much greater in the PA group (26%) than in the EH group (3%) (p < 0.001). Table 1 Clinical characteristics of the subjects Total PA EH χ2/Z p Number (n, %) 213 47(22.1%) 166(77.9%) Sex (n, %) M 110(51.6%) 25(22.7%) 85(77.3%) 0.058 0.779 F 103(48.4%) 22(21.4%) 81(78.6%) Age (y) 56(49,61) 56(51,60) 55(48,61) -0.747 0.455 BMI (kg/m2) 25.26(23.25,27.35) 25.60(23.67,27.47) 24.99(23.08,27.28) -1.316 0.188 PAC (ng/dl) 15.7(11.6,22.7) 24.9(15.9,33.4) 14.4(10.3,19.3) 55.65 < 0.001 PRA (ng/ml/h) 0.31(0.12,1.01) 0.1(0.04,0.19) 0.47(0.17,1.19) 18.65 < 0.001 ARR 46.5(15.2,161.3) 214(121.4,771.3) 30(11,80) 42.84 < 0.001 Microalbuminuria (n, %) 54(25.4%) 17(36.2%) 37(22.3%) 3.726 0.053 CV events (n, %) 36(16.9%) 11(23.4%) 25(15.1%) 1.816 0.178 Serum Na (mmol/l) * 139.84 ± 2.35 140.71 ± 2.64 139.59 ± 2.21 -2.92 0.004 Serum K (mmol/l) * 4.08(3.81,4.28) 3.88(3.48,4.14) 4.12(3.90,4.34) -4.444 < 0.001 Hypokalemia (n, %) 17(8%) 12(26%) 5(3%) 25.294 < 0.001 Serum Cl (mmol/l) * 103(101.05,105.4) 104.6(102,106.5) 102.6(100.8,104.73) -2.755 0.006 Serum Ca (mmol/l) * 2.27 ± 0.12 2.23 ± 0.12 2.28 ± 0.12 2.37 0.019 Serum P (mmol/l) 1.06(0.955,1.18) 1.03(0.92,1.16) 1.07(0.96,1.18) -0.53 0.60 Serum Mg (mmol/l) 0.87 ± 0.09 0.87 ± 0.09 0.87 ± 0.09 0.19 0.85 CO2CP (mmol/l) 24.74 ± 2.59 25.02 ± 2.77 24.66 ± 2.54 -0.83 0.408 HOMA2IR 1.26(0.90,1.7) 1.29(0.73,1.7) 1.26(0.91,1.69) -0.319 0.75 HbA1C (%) 7.76(6.8,9.35) 7.83(6.8,9.4) 7.6(6.8,9.33) -0.119 0.905 SBP (mmHg) 152 ± 21 156 ± 20 150 ± 22 -1.73 0.085 DBP (mmHg) 90(82,99) 90(79,98) 90.5(82,99) -0.463 0.644 TG (mmol/l) 1.77(1.24,2.46) 1.82(1.28,2.43) 1.76(1.23,2.51) -0.268 0.789 TC (mmol/l) 4.39(3.73,5.29) 4.38(3.68,4.85) 4.45(3.73,5.38) -0.916 0.36 HDL (mmol/l) * 1.07(0.91,1.27) 0.99(0.8,1.14) 1.1(0.93,1.28) -2.63 0.009 LDL (mmol/l) 2.76(2.19,3.39) 2.84(2.09,3.39) 2.74(2.19,3.45) -0.304 0.761 ALT(U/l) 20.2(14.65,29.85) 17.8(13.8,31.2) 20.4(14.8,29.78) -0.645 0.519 TBIL (umol/l) 11.2(8.4,15.2) 10.2(8.2,14) 11.65(8.88,15.43) -1.834 0.067 SCr (umol/l) 70(55.95,86.55) 73(60,94.3) 69(55,84.78) -1.351 0.177 UA (umol/l) 338(278.8,384.4) 344.9(265,384.9) 335.35(280.08,384.4) -0.208 0.835 eGFR (ml/min/1.73 m2) 93.63(68.42,116.02) 85.95(67.78,121.67) 94.42(68.56,115.80) -0.635 0.525 BNP (pg/mL) 33.53(22.31,53.43) 34.27(23.51,53.01) 33.34(22.06,55.24) -0.189 0.85 ANP (pg/mL) 14.11(8.85,29.31) 15.26(8.61,26.83) 14.11(8.85,30.30) -0.471 0.638 CXCR4 (ng/mL) 174(97,245) 190(106,284) 171(95.5,234.5) -1.106 0.269 CXCL12 (ng/mL) 1512(734,2450) 1456(780,2656) 1525(718,2330.5) -0.666 0.505 Adiponectin (ng/mL) 88.36(46.03,152.38) 88.36(49.56,150.66) 88.33(44.66,154.22) -0.07 0.944 Leptin (ng/mL) 4.62(1.98,11.14) 4.80(2.11,11.78) 4.50(1.94,10.93) -0.745 0.456 *p < 0.05 was considered to indicate statistical significance; M = male; F = female; BMI = body mass index; CV events = cardiovascular events; CO2CP = carbon dioxide combining power; HOMA2IR = homeostatic model assessment for insulin resistance; HbA1C = hemoglobin A1c; SBP = systolic blood pressure; DBP = diastolic blood pressure; TG = triglyceride; TC = total cholesterol; HDL = high-density lipoprotein; LDL = low-density lipoprotein; ALT = alanine amino transferase; TBIL = total bilirubin; SCr = serum creatinine; UA = uric acid; eGFR = estimated glomerular filtration rate; BNP = brain natriuretic peptide; ANP = atrial natriuretic peptide; CXCR4 = C-X-C motif chemokine receptor 4; CXCL12 = C-X-C motif chemokine ligand 12 3.2༎Sex differences in clinical manifestations 3.2.1. Among male patients, the proportion of obese individuals in the PA group was significantly greater than that in the EH group (Fig. 2). In China, overweight is defined as a BMI ≥ 24 kg/m2, while obesity is defined as a BMI ≥ 28 kg/m2[ 3 ]. Our study used these criteria to define obesity. The prevalence of obesity in male PA patients was significantly greater than that in the EH group (40% vs. 4.5%, χ2 4.172, p = 0.041), but there was no statistically significant difference in the prevalence of obesity among female patients. Figure 2. Patients were divided into a nonobese group (BMI 18.5, 27.9) and an obese group (BMI > 28) according to their BMI. BMI = body mass index In male PA patients, the PAC was positively correlated with BMI (correlation coefficient 0.318, p = 0.001) and duration of hypertension (correlation coefficient 0.219, p = 0.02). The PAC was negatively correlated with age of onset of hypertension (correlation coefficient − 0.221, p = 0.02) and blood potassium concentration (correlation coefficient − 0.457, p < 0.001) (Table 2 ). There was no association with diabetes duration, proteinuria, or renal function. Table 2 Associations of the PAC with BMI, duration of hypertension, age of onset of hypertension, and blood potassium in male PA patients Variable Plasma aldosterone concentration Correlation coefficient p value BMI 0.318 0.001 Course of hypertension 0.219 0.02 Age of onset of hypertension -0.221 0.02 Serum potassium -0.457 < 0.001 3.2.2. Among females, the proportion of proteinuria-positivity in the PA group was greater than that in the EH group (54.5% vs. 24.7%, p < 0.05). There was no difference among the males (Fig. 3). After adjusting for the course of diabetes and hypertension, aldosterone was positively correlated with albuminuria in women (correlation coefficient = 0.213, p = 0.032). Figure 3. Among females, the proportion of proteinuria-positivity in the PA group was significantly greater than that in the EH group (54.5% vs. 24.7%, p < 0.05). There was no difference among males. 3.3. Differences in serum markers 3.3.1. The serum concentrations of BNP, ANP, CXCR4, CXCL12, adiponectin and leptin were significantly different between the sexes. The serum concentrations of BNP, ANP, CXCR4, CXCL12, adiponectin and leptin did not significantly differ between the PA and EH groups. However, the serum concentrations of BNP and ANP were significantly greater in males than in females, while the serum concentrations of CXCR4, CXCL12, adiponectin and leptin were significantly lower in males than in females (Fig. 4, Table 3 ). Table 3 Serum concentrations of BNP, ANP, CXCR4, CXCL12, adiponectin and leptin in patients of different sexes Male Female p value BNP 46.38(32.32,66.61) 24.89(18.15,35.78) < 0.001 ANP 25.80(14.11,43.01) 9.58(6.78,14.40) < 0.001 CXCR4 116(75.5,176.5) 224(176,292) < 0.001 CXCL12 835(500,1550.5) 2274(1496,3254) < 0.001 Leptin 2.33(1.38,4.86) 8.93(4.69,18.90) < 0.001 Adiponectin 74.59(37.2,124.49) 117.88(55.86,179.5) < 0.001 Figure 4. The concentrations of BNP and ANP in male serum were significantly greater than those in female serum, while the concentrations of CXCR4, CXCL12, adiponectin and leptin in male serum were significantly lower than those in female serum. 3.3.2. Serum concentrations of BNP, ANP, CXCR4, CXCL12 and leptin were significantly correlated with BMI. Among the patients included in both the PA and EH groups, sex and ANP were significantly negatively correlated with BMI, while CXCR4, CXCL12 and leptin were significantly positively correlated with BMI (Fig. 5). Figure 5. BNP and ANP were significantly negatively correlated with BMI, while CXCR4, CXCL12 and leptin were significantly positively correlated with BMI. 3.3.3. Correlations of the PAC with BMI and serum biochemical markers in patients of different sexes Among the patients enrolled in both the PA and EH groups, the PAC was positively associated with BMI in men (correlation coefficient = 0.318, p = 0.001). In females, the PAC was significantly associated with the serum concentrations of CXCR4 (correlation coefficient = 0.322, p = 0.004) and CXCL12 (correlation coefficient = 0.248, p = 0.029) (Table 4 ). Table 4 Associations of the PAC with BMI and serum biochemical marker levels in patients of different sexes Variable Plasma aldosterone concentration (PAC) Male Female Correlation coefficient p value Correlation coefficient p value BMI 0.318 ** 0.001 0.161 0.105 Adjusted for BMI BNP (pg/mL) 0.060 0.578 -0.123 0.282 ANP (pg/mL) 0.003 0.977 -0.144 0.207 CXCR4 (ng/mL) -0.032 0.770 0.322 ** 0.004 CXCL12 (ng/mL) -0.080 0.460 0.248 * 0.029 Adiponectin (ng/mL) 0.044 0.683 0.065 0.573 Leptin (ng/mL) -0.077 0.475 0.122 0.288 3.3.4. Serum concentrations of BNP, ANP, CXCR4, CXCL12 and leptin were significantly correlated. In all patients, after sex and BMI correction, the serum concentrations of BNP, ANP, CXCR4, CXCL12 and leptin were significantly correlated with each other (Table 5 ). Table 5 The relationship between serum biochemical markers Variable BNP ANP CXCR4 CXCL12 Leptin Adiponectin Correlation coefficient p Correlation coefficient p Correlation coefficient p Correlation coefficient p Correlation coefficient p Correlation coefficient p BNP 0.891 < 0.001 -0.489 < 0.001 -0.383 < 0.001 -0.323 < 0.001 0.025 0.723 ANP 0.891 < 0.001 -0.514 < 0.001 -0.382 < 0.001 -0.247 < 0.001 0.075 0.281 CXCR4 -0.489 < 0.001 -0.514 < 0.001 0.934 < 0.001 0.749 < 0.001 -0.006 0.928 CXCL12 -0.383 < 0.001 -0.382 < 0.001 0.934 < 0.001 0.728 < 0.001 -0.013 0.847 Leptin -0.323 < 0.001 -0.247 < 0.001 0.749 < 0.001 0.728 < 0.001 0.031 0.650 Adiponectin 0.025 0.723 0.075 0.281 -0.006 0.928 -0.013 0.847 0.031 0.650 4. Discussion In our single-center cross-sectional study, we investigated the prevalence of PA in patients with T2DM and hypertension. Additionally, we observed clinical manifestations in both the PA group and the EH group. Our findings provide valuable insights into the coexistence of these conditions. Our study revealed that the prevalence of PA among T2DM patients with hypertension was 22.1%. This finding aligns with our previous finding of a prevalence of at least 19% in newly diagnosed T2DM patients with hypertension[ 4 ]. A Japanese study also reported a 21.6%[ 5 ] prevalence of diabetes in patients with PA. These findings collectively emphasize the common occurrence of these two diseases and underscore the need for vigilance when dealing with their coexistence. Notably, our research indicated that male PA patients were more likely to develop obesity, and the PAC was positively correlated with BMI in this subgroup. The World Health Organization (WHO) defines overweight as a BMI ≥ 25 kg/m2 and obesity as a BMI ≥ 30 kg/m2. However, Asian individuals, even those with a BMI ≤ 25 kg/m2, have an increased risk of diabetes and cardiovascular diseases. Therefore, in China, overweight is defined as a BMI ≥ 24 kg/m2, while obesity is defined as a BMI ≥ 28 kg/m2[ 3 ]. Our study used these criteria to define obesity. The relationship between sex and the RAAS has been inconsistent across various studies. Visceral obesity and insulin resistance have been associated with an elevated PAC in normotensive women[ 6 ], while male PA patients are more prone to obesity and obesity-related metabolic disorders[ 7 – 10 ]. This intricate connection between aldosterone and visceral obesity involves adipose tissue-secreted factors stimulating aldosterone production. Moreover, mineralocorticoid receptor (MR) expression increases during white adipocyte differentiation, contributing to adipose tissue inflammation, oxidative stress, fibrosis, and insulin resistance[ 11 ]. Therefore, obese male T2DM patients with hypertension should be closely monitored for the possibility of PA. Our study revealed that female T2DM patients with PA had a greater incidence of proteinuria, which was positively correlated with the PAC. Previous research has indicated a positive correlation between the PAC and left ventricular wall thickness in premenopausal women[ 12 ]. Additionally, aldosterone blockers such as eplerenone have been demonstrated to be effective at reducing cardiac remodeling in female mice[ 13 ]. Diabetes mellitus (DM) independently predicts renal function decline in female PA patients treated with spironolactone[ 14 ], underscoring the clinical significance of addressing this comorbidity. PA combined with DM has been associated with poorer clinical outcomes and increased all-cause mortality[ 15 ]. Importantly, the RAAS plays a role in the development of diabetic renal complications[ 16 , 17 ], with MR expression and transcriptional activity increasing under high-glucose conditions[ 18 ]. In conclusion, early detection and treatment of PA in female patients hold promise for improving long-term renal outcomes. Our study also revealed significant sex differences in the serum levels of BNP, ANP, leptin, adiponectin, CXCR4 and CXCL12. These serum biochemical markers were found to be correlated with BMI. Importantly, in female patients, the PAC was positively correlated with the serum concentrations of CXCR4 and CXCL12. These findings suggest that distinct pathophysiological mechanisms may be involved in patients with PA of different sexes. BNP and ANP, which are members of the natriuretic peptide (NP) family, serve as common markers of cardiac volume. NPs have diuretic, natriuretic, and vascular relaxation effects and play pivotal roles in cardiovascular, endocrine, renal, and vascular homeostasis[ 19 – 21 ]. The NP family is the target of the novel antihypertensive agent sacubitril/valsartan. Notably, circulating NP levels tend to be lower in patients with obesity and diabetes [ 22 ] but are elevated in those with PA. Our study indicated no significant difference between BNP and ANP in patients with PA combined with T2DM. Leptin, which is produced primarily by adipose tissue, is present at higher serum levels in obese individuals than in nonobese individuals[ 23 ]. Elevated circulating leptin levels are associated with increased renal sympathetic tone in overweight individuals and are involved in insulin secretion and peripheral tissue sensitivity[ 24 – 26 ]. Leptin is also associated with hypertension, atherosclerosis[ 27 ], and decreased kidney function[ 28 ]. Importantly, our results showed that a higher BMI in females corresponded to significantly elevated leptin levels, suggesting a potential avenue for the treatment of hypertension-related complications in women through modulation of the leptin-aldosterone axis. CXCL12, an agonist of the G protein-coupled receptor CXCR4, is widely expressed and influences angiogenesis and leukocytes, playing roles in various pathologies, including cancer and autoimmune and inflammatory disorders[ 29 ]. The expression patterns of CXCR4 and aldosterone synthetase in the adrenal cortex have led to the use of 68Ga-Pentixafor-PET/CT for subtype diagnosis of PA[ 30 ]. However, to the best of our knowledge, there is limited research on the expression of CXCL12 and CXCR4 in the serum of PA patients. Our study revealed a positive correlation between serum CXCR4/CXCL12 concentrations and the PAC in female patients, indicating the potential role of CXCL12/CXCR4 in both local adrenal aldosterone synthetase expression and systemic regulation. Previous research has shown that increased serum CXCL12 levels are associated with major adverse cardiovascular events[ 31 , 32 ]. Additionally, the CXCL12/CXCR4 axis has implications for diabetic nephropathy, with increased CXCR4 expression observed in renal biopsy tissues of diabetic nephropathy patients[ 33 ]. Our findings suggest that the high expression of CXCR4/CXCL12 in women may be associated with sex-specific kidney damage in PA patients. Activation of the NOD-like receptor protein 3 inflammasome (NLRP3) pathway by CXCR4 has been shown to induce neuronal inflammation[ 34 ], while the MR antagonist eplerenone inhibits chronic inflammation development by blocking NLRP3 inflammasome activation signals in adipose tissue and the liver of high-fat diet mice[ 11 ]. Currently, there is limited research on the correlation between PA and immune regulation, suggesting that further investigation into the involvement of CXCR4/CXCL12 in kidney damage related to PA combined with T2DM is worthwhile. Future studies may explore sex-specific antihypertensive drug efficacy, revealing the clinical significance of this drug for the treatment of PA. 5. Conclusions In summary, our study yielded several key findings: 1. The prevalence of PA among T2DM patients with hypertension was 22.1%, emphasizing the common coexistence of these conditions. 2. Sex differences were prominent in the clinical manifestations of patients with PA. Male PA patients were more prone to obesity, and the PAC was positively correlated with BMI. Female PA patients exhibited a higher incidence of proteinuria, and the PAC was positively correlated with this renal complication. Early detection and management of PA in female patients may yield favorable long-term renal outcomes. 3. Significant sex differences were observed in the serum concentrations of BNP, ANP, leptin, adiponectin, CXCR4, and CXCL12. These markers are also correlated with BMI, highlighting the intricate relationship between obesity and hormonal regulation in these patients. In females, the PAC was positively correlated with the serum levels of CXCR4 and CXCL12, suggesting sex differences in the pathophysiological mechanisms underlying PA. Our study paves the way for future research into the complex interactions between sex, hormones, and metabolic factors in patients with PA and T2DM. Understanding these dynamics may lead to more tailored and effective treatment strategies for these comorbid conditions. Declarations Author Contribution Author Contributions: Conceptualization, Xin Su; methodology, Wei Liu; software, Juanjuan Zhou; validation, Shanyu Yi and Meiyu Shen; data curation, Zaizhao Li; writ-ing—original draft preparation, Wei Liu; writing—review and editing, Xin Su; funding acquisition, Xin Su and Wei Liu. All the authors have read and agreed to the published version of the manuscript. References Society, C.D. Guideline for the prevention and treatment of type 2 diabetes mellitus in China(2020 edition). Chinese Journal of Practical Internal Medicine August 2021, Vol.41 No.8 . Endocrinology, C.S.o. Expert Consensus on the Diagnosis and Treatment of Primary hyperaldosteronism (2020 edition). Chinese Journal of Endocrinology and Metabolism 2020, 36 . Obesity Group, S.o.E., Chinese Medical Association. Consensus of Chinese adult obesity prevention experts. ChinJ Endocrinol Metab 2011, Vol.27, No.2 , 711–717. Hu, Y.; Zhang, J.; Liu, W.; Su, X. Determining the Prevalence of Primary Aldosteronism in Patients With New-Onset Type 2 Diabetes and Hypertension. J Clin Endocrinol Metab 2020, 105 , doi: 10.1210/clinem/dgz293 . Akehi, Y.; Yanase, T.; Motonaga, R.; Umakoshi, H.; Tsuiki, M.; Takeda, Y.; Yoneda, T.; Kurihara, I.; Itoh, H.; Katabami, T.; et al. High Prevalence of Diabetes in Patients With Primary Aldosteronism (PA) Associated With Subclinical Hypercortisolism and Prediabetes More Prevalent in Bilateral Than Unilateral PA: A Large, Multicenter Cohort Study in Japan. Diabetes Care 2019, 42 , 938–945, doi: 10.2337/dc18-1293 . Goodfriend, T.L.; Egan, B.M.; Kelley, D.E. Plasma aldosterone, plasma lipoproteins, obesity and insulin resistance in humans. Prostaglandins Leukot Essent Fatty Acids 1999, 60 , 401–405, doi: 10.1016/s0952-3278(99)80020-9 . Heizhati, M.; Aierken, X.; Gan, L.; Lin, M.; Luo, Q.; Wang, M.; Hu, J.; Maimaiti, N.; Duiyimuhan, G.; Yang, W.; et al. Prevalence of primary aldosteronism in patients with concomitant hypertension and obstructive sleep apnea, baseline data of a cohort. Hypertens Res 2023, doi: 10.1038/s41440-023-01226-w . Hatano, Y.; Sawayama, N.; Miyashita, H.; Kurashina, T.; Okada, K.; Takahashi, M.; Matsumoto, M.; Hoshide, S.; Sasaki, T.; Nagashima, S.; et al. Sex-specific Association of Primary Aldosteronism With Visceral Adiposity. J Endocr Soc 2022, 6 , bvac098, doi: 10.1210/jendso/bvac098 . Bu, X.; Sun, F.; Zhang, H.; Liu, X.; Zhao, Z.; He, H.; Li, Y.; Yan, Z.; Zhu, Z. Clinical Characteristics of Target Organ Damage in Primary Aldosteronism with or without Metabolic Syndrome. J Diabetes Res 2022, 2022 , 8932133, doi: 10.1155/2022/8932133 . Gershuni, V.M.; Herman, D.S.; Kelz, R.R.; Roses, R.E.; Cohen, D.L.; Trerotola, S.O.; Fraker, D.L.; Wachtel, H. Challenges in obesity and primary aldosteronism: Diagnosis and treatment. Surgery 2020, 167 , 204–210, doi: 10.1016/j.surg.2019.03.036 . Wada, T.; Ishikawa, A.; Watanabe, E.; Nakamura, Y.; Aruga, Y.; Hasegawa, H.; Onogi, Y.; Honda, H.; Nagai, Y.; Takatsu, K.; et al. Eplerenone prevented obesity-induced inflammasome activation and glucose intolerance. J Endocrinol 2017, 235 , 179–191, doi: 10.1530/JOE-17-0351 . Vasan, R.S.; Evans, J.C.; Benjamin, E.J.; Levy, D.; Larson, M.G.; Sundstrom, J.; Murabito, J.M.; Sam, F.; Colucci, W.S.; Wilson, P.W. Relations of serum aldosterone to cardiac structure: gender-related differences in the Framingham Heart Study. Hypertension 2004, 43 , 957–962, doi: 10.1161/01.HYP.0000124251.06056.8e . Kanashiro-Takeuchi, R.M.; Heidecker, B.; Lamirault, G.; Dharamsi, J.W.; Hare, J.M. Sex-specific impact of aldosterone receptor antagonism on ventricular remodeling and gene expression after myocardial infarction. Clin Transl Sci 2009, 2 , 134–142, doi: 10.1111/j.1752-8062.2009.00094.x . Nakamaru, R.; Yamamoto, K.; Akasaka, H.; Rakugi, H.; Kurihara, I.; Yoneda, T.; Ichijo, T.; Katabami, T.; Tsuiki, M.; Wada, N.; et al. Sex Differences in Renal Outcomes After Medical Treatment for Bilateral Primary Aldosteronism. Hypertension 2021, 77 , 537–545, doi: 10.1161/HYPERTENSIONAHA.120.16449 . Reincke, M.; Fischer, E.; Gerum, S.; Merkle, K.; Schulz, S.; Pallauf, A.; Quinkler, M.; Hanslik, G.; Lang, K.; Hahner, S.; et al. Observational study mortality in treated primary aldosteronism: the German Conn's registry. Hypertension 2012, 60 , 618–624, doi: 10.1161/HYPERTENSIONAHA.112.197111 . J.Deinum, B.R.n., E.Mathiesen, F.H.M.Derkx, W.C.J.Hop, M.A.D.H. Schalekamp. Increase in serum prorenin precedes onset of microalbuminuria in patients with insulin-dependent diabetes mellitus. Diabetologia 1999, 42 , 1006–1010. Visniauskas, B.; Arita, D.Y.; Rosales, C.B.; Feroz, M.A.; Luffman, C.; Accavitti, M.J.; Dawkins, G.; Hong, J.; Curnow, A.C.; Thethi, T.K.; et al. Sex differences in soluble prorenin receptor in patients with type 2 diabetes. Biol Sex Differ 2021, 12 , 33, doi: 10.1186/s13293-021-00374-3 . Jo, R.; Shibata, H.; Kurihara, I.; Yokota, K.; Kobayashi, S.; Murai-Takeda, A.; Mitsuishi, Y.; Hayashi, T.; Nakamura, T.; Itoh, H. Mechanisms of mineralocorticoid receptor-associated hypertension in diabetes mellitus: the role of O-GlcNAc modification. Hypertens Res 2023, 46 , 19–31, doi: 10.1038/s41440-022-01036-6 . Pandey, K.N. Molecular Signaling Mechanisms and Function of Natriuretic Peptide Receptor-A in the Pathophysiology of Cardiovascular Homeostasis. Front Physiol 2021, 12 , 693099, doi: 10.3389/fphys.2021.693099 . Okamoto, R.; Ali, Y.; Hashizume, R.; Suzuki, N.; Ito, M. BNP as a Major Player in the Heart-Kidney Connection. Int J Mol Sci 2019, 20 , doi: 10.3390/ijms20143581 . YAU-JIUNN LEE, S.-R.L., SHYI-JANG SHIN, YUNG-HSIUNG LAI, YOUNG-TSO LIN, AND JUEI-HSIUNG TSAI. rain Natriuretic Peptide Is Synthesized in the Human Adrenal Medulla and Its Messenger Ribonucleic Acid Expression along with That of Atria1 Natriuretic Peptide Are Enhanced in Patients with Primary Aldosteronism. Journal of Clinical Endocrinology and Metabolism 1994, 79 . Wang, T.J.; Larson, M.G.; Levy, D.; Benjamin, E.J.; Leip, E.P.; Wilson, P.W.; Vasan, R.S. Impact of obesity on plasma natriuretic peptide levels. Circulation 2004, 109 , 594–600, doi: 10.1161/01.CIR.0000112582.16683.EA . Izquierdo, A.G.; Crujeiras, A.B.; Casanueva, F.F.; Carreira, M.C. Leptin, Obesity, and Leptin Resistance: Where Are We 25 Years Later? Nutrients 2019, 11 , doi: 10.3390/nu11112704 . Amitani, M.; Asakawa, A.; Amitani, H.; Inui, A. The role of leptin in the control of insulin-glucose axis. Front Neurosci 2013, 7 , 51, doi: 10.3389/fnins.2013.00051 . Choi, J.R.; Kim, J.Y.; Huh, J.H.; Kim, S.H.; Koh, S.B. Contribution of obesity as an effect regulator to an association between serum leptin and incident metabolic syndrome. Clin Chim Acta 2018, 487 , 275–280, doi: 10.1016/j.cca.2018.09.038 . da Silva, A.A.; do Carmo, J.M.; Hall, J.E. Role of leptin and central nervous system melanocortins in obesity hypertension. Curr Opin Nephrol Hypertens 2013, 22 , 135–140, doi: 10.1097/MNH.0b013e32835d0c05 . Ghantous, C.M.; Azrak, Z.; Hanache, S.; Abou-Kheir, W.; Zeidan, A. Differential Role of Leptin and Adiponectin in Cardiovascular System. Int J Endocrinol 2015, 2015 , 534320, doi: 10.1155/2015/534320 . Shih, Y.L.; Shih, C.C.; Chen, S.Y.; Chen, J.Y. Elevated serum leptin levels are associated with lower renal function among middle-aged and elderly adults in Taiwan, a community-based, cross-sectional study. Front Endocrinol (Lausanne) 2022, 13 , 1047731, doi: 10.3389/fendo.2022.1047731 . He, X.; Li, C.; Yin, H.; Tan, X.; Yi, J.; Tian, S.; Wang, Y.; Liu, J. Mesenchymal stem cells inhibited the apoptosis of alveolar epithelial cells caused by ARDS through CXCL12/CXCR4 axis. Bioengineered 2022, 13 , 9060–9070, doi: 10.1080/21655979.2022.2052652 . Ding, J.; Tong, A.; Hacker, M.; Feng, M.; Huo, L.; Li, X. Usefulness of 68 Ga-Pentixafor PET/CT on Diagnosis and Management of Cushing Syndrome. Clin Nucl Med 2022, 47 , 669–676, doi: 10.1097/RLU.0000000000004244 . Zhang, S.; Ding, Y.; Feng, F.; Gao, Y. The role of blood CXCL12 level in prognosis of coronary artery disease: A meta-analysis. Frontiers in Cardiovascular Medicine 2022, 9 , doi: 10.3389/fcvm.2022.938540 . Sjaarda, J.; Gerstein, H.; Chong, M.; Yusuf, S.; Meyre, D.; Anand, S.S.; Hess, S.; Pare, G. Blood CSF1 and CXCL12 as Causal Mediators of Coronary Artery Disease. J Am Coll Cardiol 2018, 72 , 300–310, doi: 10.1016/j.jacc.2018.04.067 . Siddiqi, F.S.; Chen, L.H.; Advani, S.L.; Thai, K.; Batchu, S.N.; Alghamdi, T.A.; White, K.E.; Sood, M.M.; Gibson, I.W.; Connelly, K.A.; et al. CXCR4 promotes renal tubular cell survival in male diabetic rats: implications for ligand inactivation in the human kidney. Endocrinology 2015, 156 , 1121–1132, doi: 10.1210/en.2014-1650 . Li, W.; Liang, J.; Li, S.; Jiang, S.; Song, M.; Xu, S.; Wang, L.; Meng, H.; Zhai, D.; Tang, L.; et al. The CXCL12-CXCR4-NLRP3 axis promotes Schwann cell pyroptosis and sciatic nerve demyelination in rats. Clin Exp Immunol 2023, doi: 10.1093/cei/uxad081 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3939206\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":271745826,\"identity\":\"7ad67cc7-ce14-4f4e-8198-eadcb26564d4\",\"order_by\":0,\"name\":\"wei liu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"National Clinical Research Center for Metabolic Diseases, Institute of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"wei\",\"middleName\":\"\",\"lastName\":\"liu\",\"suffix\":\"\"},{\"id\":271745827,\"identity\":\"c2316725-e606-47b0-9817-fd10b4074faf\",\"order_by\":1,\"name\":\"Juanjuan Zhou\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"National Clinical Research Center for Metabolic Diseases, Institute of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Juanjuan\",\"middleName\":\"\",\"lastName\":\"Zhou\",\"suffix\":\"\"},{\"id\":271745828,\"identity\":\"0adc02c6-4f77-474d-b454-488fc3c03380\",\"order_by\":2,\"name\":\"Shanyu Yi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"National Clinical Research Center for Metabolic Diseases, Institute of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Shanyu\",\"middleName\":\"\",\"lastName\":\"Yi\",\"suffix\":\"\"},{\"id\":271745829,\"identity\":\"f9c05de0-4d27-409e-a66b-030868a82bb6\",\"order_by\":3,\"name\":\"Meiyu Shen\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Medical College of Hunan Normal University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Meiyu\",\"middleName\":\"\",\"lastName\":\"Shen\",\"suffix\":\"\"},{\"id\":271745830,\"identity\":\"a9ea5a75-69c6-45eb-924d-327d3ff2a8c5\",\"order_by\":4,\"name\":\"Zaizhao Li\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"National Clinical Research Center for Metabolic Diseases, Institute of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Zaizhao\",\"middleName\":\"\",\"lastName\":\"Li\",\"suffix\":\"\"},{\"id\":271745831,\"identity\":\"1abf73a2-5201-4100-bc8f-ecdb172b4623\",\"order_by\":5,\"name\":\"Xin Su\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYJCCA4z/JOQgTDZitTCwWRiTpgWosiKxgWgt8jNyDA8X8Eik9/efMWD4UHaYgX92A34tBjfSEg7PkJDInXEjx4BxxrnDDBJ3DhDQIpF84DCPgUTuBgkeA2betsNAkQRCDktsOMyTIJFuwH/GgPkvMVoYboBsOSCRYMCQY8DMSIwWgzPPEg7zNkgYzriRVnCw51w6j8QNQg5rzzH+zNtQJ8/ff3jjgx9l1nL8Mwg5DBkcAGIeEtSPglEwCkbBKMAFAOEWPt2QrXc/AAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"National Clinical Research Center for Metabolic Diseases, Institute of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Xin\",\"middleName\":\"\",\"lastName\":\"Su\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-02-08 07:59:54\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-3939206/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-3939206/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":51018020,\"identity\":\"a7995752-1308-4b5f-bd25-bb2e8a42e45c\",\"added_by\":\"auto\",\"created_at\":\"2024-02-12 19:20:10\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":191126,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eStudy Flow Chart\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig.1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3939206/v1/65e26bcd021027a449ec3f90.png\"},{\"id\":51018015,\"identity\":\"091d9f1b-a0cf-4541-9fce-a34991f54a48\",\"added_by\":\"auto\",\"created_at\":\"2024-02-12 19:20:09\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":42249,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePatients were divided into a nonobese group (BMI 18.5, 27.9) and an obese group (BMI \\u0026gt;28) according to their BMI. BMI =body mass index\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig.2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3939206/v1/efb44d564d4a51ccbd3acb2c.png\"},{\"id\":51018018,\"identity\":\"5a5a0978-c653-4c3d-afe2-52e2c6eadb50\",\"added_by\":\"auto\",\"created_at\":\"2024-02-12 19:20:10\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":105565,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eAmong females, the proportion of proteinuria-positivity in the PA group was significantly greater than that in the EH group (54.5% vs. 24.7%, p\\u0026lt;0.05). There was no difference among males.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig.3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3939206/v1/2c75a74041b5e5d74a870c13.png\"},{\"id\":51018019,\"identity\":\"e00ca1fd-cbda-4ca3-86b1-505f9247eb97\",\"added_by\":\"auto\",\"created_at\":\"2024-02-12 19:20:10\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":292225,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe concentrations of BNP and ANP in male serum were significantly greater than those in female serum, while the concentrations of CXCR4, CXCL12, adiponectin and leptin in male serum were significantly lower than those in female serum.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig.4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3939206/v1/2cd2bd0bdd912a7101ee2142.png\"},{\"id\":51018016,\"identity\":\"85df1a4e-7465-4bf8-8fd2-07fbcb7f94c4\",\"added_by\":\"auto\",\"created_at\":\"2024-02-12 19:20:09\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":71972,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eBNP and ANP were significantly negatively correlated with BMI, while CXCR4, CXCL12 and leptin were significantly positively correlated with BMI.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3939206/v1/5dd8af95aa7a62f40fb6a693.png\"},{\"id\":51157773,\"identity\":\"b8b60295-0882-4cc9-9d30-2547ce6c2076\",\"added_by\":\"auto\",\"created_at\":\"2024-02-15 06:22:49\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":998168,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3939206/v1/1d773501-283a-4f97-93ae-0dab07a2c2c7.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Sex Differences in Clinical Manifestations and Serum CXCR4/CXCL12 Levels in Patients with Type 2 Diabetes and Primary Aldosteronism\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003eType 2 diabetes mellitus (T2DM) and hypertension are the most prevalent chronic diseases in contemporary society and contribute significantly to various complications, notably cardiovascular diseases and chronic renal dysfunction. In Chinese adults, the prevalence of T2DM is 11.2% [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e], while hypertension affects 23.2% of the population. The concomitant prevalence of hypertension in Chinese adults with diabetes soared to 45.2%. Notably, primary hyperaldosteronism (PA) has emerged as the leading cause of secondary hypertension, afflicting up to 20% of individuals with refractory hypertension[\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. The deleterious impact of excessive aldosterone on cardiovascular and renal health is partially independent of blood pressure. Are these manifestations distinct from those in T2DM patients with essential hypertension (EH)? Addressing this question holds crucial implications for our understanding of the clinical landscape when these two common chronic diseases coincide. Furthermore, do differences exist in the serum levels of atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP), the lipid metabolism markers leptin and adiponectin, and CXCR4 and its ligand CXCL12 between EH and PA patients? To answer these questions, we conducted a cross-sectional study by recruiting T2DM patients with hypertension to evaluate the function of the renin-angiotensin-aldosterone system (RAAS) and analyze relevant clinical data; in addition, we quantified the concentrations of serum leptin, adiponectin, ANP, BNP, CXCR4, and CXCL12.\\u003c/p\\u003e\"},{\"header\":\"2. Materials and Methods\",\"content\":\"\\u003cp\\u003e\\u003cdiv class=\\\"BlockQuote\\\"\\u003e\\u003cp\\u003eWe conducted this study at the Diabetes Clinic of the Second Xiangya Hospital of Central South University (Changsha, Hunan, China), and data were collected every Friday throughout the study period. From January 2020 to December 2021, a total of 213 T2DM outpatients with hypertension were enrolled (Fig.\\u0026nbsp;1). All included patients underwent a physical examination, including height, weight, and BP measurements, and blood was collected for the measurement of the RAAS score and leptin, adiponectin, ANP, BNP, CXCR4 and CXCL12 levels.\\u003c/p\\u003e\\u003cp\\u003eDiabetes was diagnosed according to the World Health Organization (WHO) criteria. Hypertension was defined as a systolic blood pressure of at least 140 mmHg and/or diastolic blood pressure of at least 90 mmHg or the reported use of hypertension medications. Obesity was defined as a BMI\\u0026thinsp;\\u0026ge;\\u0026thinsp;28 kg/m2. Hypokalemia was defined as a serum potassium concentration\\u0026thinsp;\\u0026lt;\\u0026thinsp;3.5 mmol/l. Microalbuminuria was defined by a spot urinary albumin-to-creatinine ratio (UACR) of 30 to 300 mg/g. CV events identified from hospital records at baseline included myocardial infarction; unstable angina pectoris requiring angioplasty; stroke; or transient ischemic attack. The exclusion criteria for individuals were as follows: (1) women who were pregnant or nursing; (2) patients with secondary hypertension caused by other underlying diseases, such as pheochromocytoma, Cushing's syndrome, or renal artery stenosis; (3) patients with serious heart, kidney or liver diseases; (4) patients who were taking diuretic drugs or had stopped using diuretic drugs for less than 4 weeks; and (5) patients with other serious diseases (not suitable for screening). This study was approved by the Ethics Committee of the Second Xiangya Hospital of Central South University, and all patients provided informed consent before participating in the study.\\u003c/p\\u003e\\u003cp\\u003e\\u003cb\\u003eFigure 1.\\u003c/b\\u003e Study Flow Chart\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/p\\u003e \\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1. Clinical evaluation\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eThe diagnosis of PA followed the criteria of the Endocrine Society[\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. Prior to screening, patients discontinued the use of all antihypertensive drugs except for dihydropyridine calcium channel blockers and alpha-adrenergic blockers. Specifically, spironolactone, eplerenone, diuretics, and licorice-containing Chinese medicines were stopped for at least 4 weeks, while beta-blockers, angiotensin-converting enzyme inhibitors, and angiotensin-receptor antagonists were stopped for at least 2 weeks.\\u003c/p\\u003e \\u003cp\\u003eEvaluation of the RAAS included determination of the PAC and plasma renin activity (PRA) and calculation of the aldosterone-renin ratio (ARR). Patients with a PAC\\u0026thinsp;\\u0026ge;\\u0026thinsp;15 ng/dl and an ARR\\u0026thinsp;\\u0026ge;\\u0026thinsp;30 ng/dl/ng/ml/h were further tested with the captopril challenge test (CCT) and/or saline infusion test (SIT). The diagnostic criteria were as follows. After CCT, patients who met all the following criteria were diagnosed with PA: (1) PAC decreased by \\u0026lt;\\u0026thinsp;30%, (2) ARR remained\\u0026thinsp;\\u0026ge;\\u0026thinsp;30 ng/dl/ng/ml/h, and (3) PAC\\u0026thinsp;\\u0026ge;\\u0026thinsp;11 ng/dl. After SIT, patients with postinfusion plasma aldosterone levels\\u0026thinsp;\\u0026gt;\\u0026thinsp;10 ng/dl were diagnosed with PA.\\u003c/p\\u003e \\u003cp\\u003eThe serum concentrations of leptin, adiponectin, ANP, BNP, CXCR4 and CXCL12 were measured using appropriate ELISA kits (Jianglai Biotechnology, Shanghai, China) following the manufacturer\\u0026rsquo;s instructions.\\u003c/p\\u003e \\u003cp\\u003eAll tests were conducted in the biochemical laboratory of the Second Xiangya Hospital, Central South University. PAC was determined by chemiluminescence (Maglumi 2000 Plus, China). The intragroup CV of the PAC was \\u0026le;\\u0026thinsp;5%, and the intergroup CV was \\u0026le;\\u0026thinsp;10%. PRA was also measured by chemiluminescence (Maglumi 2000 Plus, China). The intra-assay CV of PRA detection was less than 15%, and the inter-assay CV was less than 10%.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2. Statistical analysis\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eStatistical Package for Social Sciences (SPSS) version 23.0 for Windows and GraphPad Prism 5.0 (GraphPad Prism Software, Inc.) were used to analyze the results. Descriptive statistics are reported as mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD or median (interquartile range [IQR]). Categorical variables are expressed as numbers and percentages. Normality tests were used to determine the distribution of variables. ANOVA was used for between-group comparisons of normally distributed variables. The nonparametric Friedman test was used for between-group comparisons of nonnormally distributed variables. p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 was considered to indicate statistical significance.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1. Clinical features\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eA total of 213 patients participated in the study, 86 (40%) of whom were initially flagged for altered RAAS activity and subsequently underwent confirmation via CCT. Among these patients, 49 exhibited uninhibited aldosterone levels and reduced renin activity, leading to a PA diagnosis. The overall prevalence of PA among T2DM patients with hypertension was 22.1% (49/213), with no significant sex difference observed. Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e displays the clinical characteristics and biochemical data of all the study participants. Patients with PA had a higher PAC and ARR and lower PRA than patients in the EH group did. Patients with PA had lower serum potassium levels (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), and the proportion of patients with hypokalemia was much greater in the PA group (26%) than in the EH group (3%) (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001).\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eClinical characteristics of the subjects\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"7\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003ePA\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eEH\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e χ2/Z\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ep\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNumber (n, %)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e213\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e47(22.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e166(77.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eSex (n, %)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eM\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e110(51.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e25(22.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e85(77.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e0.058\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e0.779\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e103(48.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e22(21.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e81(78.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge (y)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e56(49,61)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e56(51,60)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e55(48,61)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.747\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.455\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBMI (kg/m2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e25.26(23.25,27.35)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e25.60(23.67,27.47)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e24.99(23.08,27.28)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-1.316\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.188\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePAC (ng/dl)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e15.7(11.6,22.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e24.9(15.9,33.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e14.4(10.3,19.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e55.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePRA (ng/ml/h)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.31(0.12,1.01)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.1(0.04,0.19)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.47(0.17,1.19)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e18.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eARR\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e46.5(15.2,161.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e214(121.4,771.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e30(11,80)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e42.84\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMicroalbuminuria (n, %)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e54(25.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e17(36.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e37(22.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3.726\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.053\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCV events (n, %)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e36(16.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e11(23.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e25(15.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1.816\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.178\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSerum Na (mmol/l) *\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e139.84\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e140.71\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.64\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e139.59\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.21\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-2.92\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.004\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSerum K (mmol/l) *\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.08(3.81,4.28)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.88(3.48,4.14)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e4.12(3.90,4.34)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-4.444\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHypokalemia (n, %)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e17(8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e12(26%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e5(3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e25.294\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSerum Cl (mmol/l) *\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e103(101.05,105.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e104.6(102,106.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e102.6(100.8,104.73)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-2.755\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.006\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSerum Ca (mmol/l) *\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.27\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.23\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.28\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2.37\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.019\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSerum P (mmol/l)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.06(0.955,1.18)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.03(0.92,1.16)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.07(0.96,1.18)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.53\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.60\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSerum Mg (mmol/l)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.87\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.09\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.87\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.09\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.87\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.09\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.19\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.85\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCO2CP (mmol/l)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e24.74\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.59\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e25.02\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.77\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e24.66\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.54\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.83\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.408\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHOMA2IR\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.26(0.90,1.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.29(0.73,1.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.26(0.91,1.69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.319\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.75\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHbA1C (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7.76(6.8,9.35)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e7.83(6.8,9.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e7.6(6.8,9.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.119\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.905\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSBP (mmHg)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e152\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;21\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e156\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;20\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e150\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-1.73\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.085\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDBP (mmHg)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e90(82,99)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e90(79,98)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e90.5(82,99)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.463\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.644\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTG (mmol/l)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.77(1.24,2.46)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.82(1.28,2.43)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.76(1.23,2.51)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.268\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.789\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTC (mmol/l)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.39(3.73,5.29)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.38(3.68,4.85)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e4.45(3.73,5.38)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.916\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.36\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHDL (mmol/l) *\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.07(0.91,1.27)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.99(0.8,1.14)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.1(0.93,1.28)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-2.63\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.009\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLDL (mmol/l)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.76(2.19,3.39)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.84(2.09,3.39)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.74(2.19,3.45)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.304\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.761\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eALT(U/l)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e20.2(14.65,29.85)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e17.8(13.8,31.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e20.4(14.8,29.78)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.645\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.519\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTBIL (umol/l)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e11.2(8.4,15.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e10.2(8.2,14)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e11.65(8.88,15.43)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-1.834\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.067\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSCr (umol/l)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e70(55.95,86.55)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e73(60,94.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e69(55,84.78)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-1.351\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.177\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eUA (umol/l)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e338(278.8,384.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e344.9(265,384.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e335.35(280.08,384.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.208\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.835\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eeGFR (ml/min/1.73 m2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e93.63(68.42,116.02)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e85.95(67.78,121.67)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e94.42(68.56,115.80)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.635\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.525\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBNP (pg/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e33.53(22.31,53.43)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e34.27(23.51,53.01)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e33.34(22.06,55.24)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.189\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.85\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eANP (pg/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.11(8.85,29.31)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e15.26(8.61,26.83)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e14.11(8.85,30.30)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.471\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.638\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCXCR4 (ng/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e174(97,245)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e190(106,284)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e171(95.5,234.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-1.106\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.269\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCXCL12 (ng/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1512(734,2450)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1456(780,2656)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1525(718,2330.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.666\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.505\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAdiponectin (ng/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e88.36(46.03,152.38)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e88.36(49.56,150.66)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e88.33(44.66,154.22)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.07\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.944\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLeptin (ng/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.62(1.98,11.14)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.80(2.11,11.78)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e4.50(1.94,10.93)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.745\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.456\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"7\\\"\\u003e*p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 was considered to indicate statistical significance; M\\u0026thinsp;=\\u0026thinsp;male; F\\u0026thinsp;=\\u0026thinsp;female; BMI\\u0026thinsp;=\\u0026thinsp;body mass index; CV events\\u0026thinsp;=\\u0026thinsp;cardiovascular events; CO2CP\\u0026thinsp;=\\u0026thinsp;carbon dioxide combining power; HOMA2IR\\u0026thinsp;=\\u0026thinsp;homeostatic model assessment for insulin resistance; HbA1C\\u0026thinsp;=\\u0026thinsp;hemoglobin A1c; SBP\\u0026thinsp;=\\u0026thinsp;systolic blood pressure; DBP\\u0026thinsp;=\\u0026thinsp;diastolic blood pressure; TG\\u0026thinsp;=\\u0026thinsp;triglyceride; TC\\u0026thinsp;=\\u0026thinsp;total cholesterol; HDL\\u0026thinsp;=\\u0026thinsp;high-density lipoprotein; LDL\\u0026thinsp;=\\u0026thinsp;low-density lipoprotein; ALT\\u0026thinsp;=\\u0026thinsp;alanine amino transferase; TBIL\\u0026thinsp;=\\u0026thinsp;total bilirubin; SCr\\u0026thinsp;=\\u0026thinsp;serum creatinine; UA\\u0026thinsp;=\\u0026thinsp;uric acid; eGFR\\u0026thinsp;=\\u0026thinsp;estimated glomerular filtration rate; BNP\\u0026thinsp;=\\u0026thinsp;brain natriuretic peptide; ANP\\u0026thinsp;=\\u0026thinsp;atrial natriuretic peptide; CXCR4\\u0026thinsp;=\\u0026thinsp;C-X-C motif chemokine receptor 4; CXCL12\\u0026thinsp;=\\u0026thinsp;C-X-C motif chemokine ligand 12\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2༎Sex differences in clinical manifestations\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003e3.2.1. Among male patients, the proportion of obese individuals in the PA group was significantly greater than that in the EH group (Fig.\\u0026nbsp;2).\\u003c/p\\u003e \\u003cp\\u003eIn China, overweight is defined as a BMI\\u0026thinsp;\\u0026ge;\\u0026thinsp;24 kg/m2, while obesity is defined as a BMI\\u0026thinsp;\\u0026ge;\\u0026thinsp;28 kg/m2[\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. Our study used these criteria to define obesity. The prevalence of obesity in male PA patients was significantly greater than that in the EH group (40% vs. 4.5%, χ2 4.172, p\\u0026thinsp;=\\u0026thinsp;0.041), but there was no statistically significant difference in the prevalence of obesity among female patients.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eFigure 2.\\u003c/b\\u003e Patients were divided into a nonobese group (BMI 18.5, 27.9) and an obese group (BMI\\u0026thinsp;\\u0026gt;\\u0026thinsp;28) according to their BMI. BMI\\u0026thinsp;=\\u0026thinsp;body mass index\\u003c/p\\u003e \\u003cp\\u003eIn male PA patients, the PAC was positively correlated with BMI (correlation coefficient 0.318, p\\u0026thinsp;=\\u0026thinsp;0.001) and duration of hypertension (correlation coefficient 0.219, p\\u0026thinsp;=\\u0026thinsp;0.02). The PAC was negatively correlated with age of onset of hypertension (correlation coefficient \\u0026minus;\\u0026thinsp;0.221, p\\u0026thinsp;=\\u0026thinsp;0.02) and blood potassium concentration (correlation coefficient \\u0026minus;\\u0026thinsp;0.457, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). There was no association with diabetes duration, proteinuria, or renal function.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eAssociations of the PAC with BMI, duration of hypertension, age of onset of hypertension, and blood potassium in male PA patients\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eVariable\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003ePlasma aldosterone concentration\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCorrelation coefficient\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ep value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBMI\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.318\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCourse of hypertension\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.219\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.02\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge of onset of hypertension\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.221\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.02\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSerum potassium\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.457\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e3.2.2. Among females, the proportion of proteinuria-positivity in the PA group was greater than that in the EH group (54.5% vs. 24.7%, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). There was no difference among the males (Fig.\\u0026nbsp;3). After adjusting for the course of diabetes and hypertension, aldosterone was positively correlated with albuminuria in women (correlation coefficient\\u0026thinsp;=\\u0026thinsp;0.213, p\\u0026thinsp;=\\u0026thinsp;0.032).\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eFigure 3.\\u003c/b\\u003e Among females, the proportion of proteinuria-positivity in the PA group was significantly greater than that in the EH group (54.5% vs. 24.7%, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). There was no difference among males.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3. Differences in serum markers\\u003c/h2\\u003e \\u003cp\\u003e3.3.1. The serum concentrations of BNP, ANP, CXCR4, CXCL12, adiponectin and leptin were significantly different between the sexes.\\u003c/p\\u003e \\u003cp\\u003eThe serum concentrations of BNP, ANP, CXCR4, CXCL12, adiponectin and leptin did not significantly differ between the PA and EH groups. However, the serum concentrations of BNP and ANP were significantly greater in males than in females, while the serum concentrations of CXCR4, CXCL12, adiponectin and leptin were significantly lower in males than in females (Fig.\\u0026nbsp;4, Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eSerum concentrations of BNP, ANP, CXCR4, CXCL12, adiponectin and leptin in patients of different sexes\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003ep value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBNP\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e46.38(32.32,66.61)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e24.89(18.15,35.78)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eANP\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e25.80(14.11,43.01)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e9.58(6.78,14.40)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCXCR4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e116(75.5,176.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e224(176,292)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCXCL12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e835(500,1550.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2274(1496,3254)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLeptin\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2.33(1.38,4.86)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8.93(4.69,18.90)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAdiponectin\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e74.59(37.2,124.49)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e117.88(55.86,179.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eFigure 4.\\u003c/b\\u003e The concentrations of BNP and ANP in male serum were significantly greater than those in female serum, while the concentrations of CXCR4, CXCL12, adiponectin and leptin in male serum were significantly lower than those in female serum.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.3.2. Serum concentrations of BNP, ANP, CXCR4, CXCL12 and leptin were significantly correlated with BMI.\\u003c/h2\\u003e \\u003cp\\u003eAmong the patients included in both the PA and EH groups, sex and ANP were significantly negatively correlated with BMI, while CXCR4, CXCL12 and leptin were significantly positively correlated with BMI (Fig.\\u0026nbsp;5).\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eFigure 5.\\u003c/b\\u003e BNP and ANP were significantly negatively correlated with BMI, while CXCR4, CXCL12 and leptin were significantly positively correlated with BMI.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.3.3. Correlations of the PAC with BMI and serum biochemical markers in patients of different sexes\\u003c/h2\\u003e \\u003cp\\u003eAmong the patients enrolled in both the PA and EH groups, the PAC was positively associated with BMI in men (correlation coefficient\\u0026thinsp;=\\u0026thinsp;0.318, p\\u0026thinsp;=\\u0026thinsp;0.001). In females, the PAC was significantly associated with the serum concentrations of CXCR4 (correlation coefficient\\u0026thinsp;=\\u0026thinsp;0.322, p\\u0026thinsp;=\\u0026thinsp;0.004) and CXCL12 (correlation coefficient\\u0026thinsp;=\\u0026thinsp;0.248, p\\u0026thinsp;=\\u0026thinsp;0.029) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eAssociations of the PAC with BMI and serum biochemical marker levels in patients of different sexes\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"6\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" morerows=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003eVariable\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c6\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003ePlasma aldosterone concentration (PAC)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eCorrelation coefficient\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003ep value\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eCorrelation coefficient\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003ep value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eBMI\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.318\\u003c/b\\u003e\\u003csup\\u003e\\u003cb\\u003e**\\u003c/b\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.161\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.105\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e \\u003cp\\u003eAdjusted for BMI\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eBNP (pg/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.060\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.578\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-0.123\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.282\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eANP (pg/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.003\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.977\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-0.144\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.207\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCXCR4 (ng/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e-0.032\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.770\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.322\\u003c/b\\u003e\\u003csup\\u003e\\u003cb\\u003e**\\u003c/b\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.004\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCXCL12 (ng/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e-0.080\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.460\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.248\\u003c/b\\u003e\\u003csup\\u003e\\u003cb\\u003e*\\u003c/b\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.029\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eAdiponectin (ng/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.044\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.683\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.065\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.573\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eLeptin (ng/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e-0.077\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.475\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.122\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.288\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.3.4. Serum concentrations of BNP, ANP, CXCR4, CXCL12 and leptin were significantly correlated.\\u003c/h2\\u003e \\u003cp\\u003eIn all patients, after sex and BMI correction, the serum concentrations of BNP, ANP, CXCR4, CXCL12 and leptin were significantly correlated with each other (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eThe relationship between serum biochemical markers\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"13\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c11\\\" colnum=\\\"11\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c12\\\" colnum=\\\"12\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c13\\\" colnum=\\\"13\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVariable\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eBNP\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003eANP\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c7\\\" namest=\\\"c6\\\"\\u003e \\u003cp\\u003eCXCR4\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c9\\\" namest=\\\"c8\\\"\\u003e \\u003cp\\u003eCXCL12\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c11\\\" namest=\\\"c10\\\"\\u003e \\u003cp\\u003eLeptin\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c13\\\" namest=\\\"c12\\\"\\u003e \\u003cp\\u003eAdiponectin\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCorrelation coefficient\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ep\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eCorrelation coefficient\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eCorrelation coefficient\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003ep\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eCorrelation coefficient\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003ep\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003eCorrelation coefficient\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003ep\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003eCorrelation coefficient\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003ep\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBNP\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.891\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.489\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e-0.383\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e-0.323\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.025\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.723\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eANP\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.891\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.514\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e-0.382\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e-0.247\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.075\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.281\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCXCR4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.489\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-0.514\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.934\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e-0.006\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.928\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCXCL12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.383\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-0.382\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.934\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.728\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e-0.013\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.847\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLeptin\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.323\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-0.247\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.728\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.031\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.650\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAdiponectin\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.025\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.723\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.075\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.281\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-0.006\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.928\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e-0.013\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.847\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.031\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.650\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cp\\u003eIn our single-center cross-sectional study, we investigated the prevalence of PA in patients with T2DM and hypertension. Additionally, we observed clinical manifestations in both the PA group and the EH group. Our findings provide valuable insights into the coexistence of these conditions.\\u003c/p\\u003e \\u003cp\\u003eOur study revealed that the prevalence of PA among T2DM patients with hypertension was 22.1%. This finding aligns with our previous finding of a prevalence of at least 19% in newly diagnosed T2DM patients with hypertension[\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. A Japanese study also reported a 21.6%[\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e] prevalence of diabetes in patients with PA. These findings collectively emphasize the common occurrence of these two diseases and underscore the need for vigilance when dealing with their coexistence.\\u003c/p\\u003e \\u003cp\\u003eNotably, our research indicated that male PA patients were more likely to develop obesity, and the PAC was positively correlated with BMI in this subgroup. The World Health Organization (WHO) defines overweight as a BMI\\u0026thinsp;\\u0026ge;\\u0026thinsp;25 kg/m2 and obesity as a BMI\\u0026thinsp;\\u0026ge;\\u0026thinsp;30 kg/m2. However, Asian individuals, even those with a BMI\\u0026thinsp;\\u0026le;\\u0026thinsp;25 kg/m2, have an increased risk of diabetes and cardiovascular diseases. Therefore, in China, overweight is defined as a BMI\\u0026thinsp;\\u0026ge;\\u0026thinsp;24 kg/m2, while obesity is defined as a BMI\\u0026thinsp;\\u0026ge;\\u0026thinsp;28 kg/m2[\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. Our study used these criteria to define obesity. The relationship between sex and the RAAS has been inconsistent across various studies. Visceral obesity and insulin resistance have been associated with an elevated PAC in normotensive women[\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e], while male PA patients are more prone to obesity and obesity-related metabolic disorders[\\u003cspan additionalcitationids=\\\"CR8 CR9\\\" citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. This intricate connection between aldosterone and visceral obesity involves adipose tissue-secreted factors stimulating aldosterone production. Moreover, mineralocorticoid receptor (MR) expression increases during white adipocyte differentiation, contributing to adipose tissue inflammation, oxidative stress, fibrosis, and insulin resistance[\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. Therefore, obese male T2DM patients with hypertension should be closely monitored for the possibility of PA.\\u003c/p\\u003e \\u003cp\\u003eOur study revealed that female T2DM patients with PA had a greater incidence of proteinuria, which was positively correlated with the PAC. Previous research has indicated a positive correlation between the PAC and left ventricular wall thickness in premenopausal women[\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e]. Additionally, aldosterone blockers such as eplerenone have been demonstrated to be effective at reducing cardiac remodeling in female mice[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Diabetes mellitus (DM) independently predicts renal function decline in female PA patients treated with spironolactone[\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e], underscoring the clinical significance of addressing this comorbidity. PA combined with DM has been associated with poorer clinical outcomes and increased all-cause mortality[\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. Importantly, the RAAS plays a role in the development of diabetic renal complications[\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e], with MR expression and transcriptional activity increasing under high-glucose conditions[\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]. In conclusion, early detection and treatment of PA in female patients hold promise for improving long-term renal outcomes.\\u003c/p\\u003e \\u003cp\\u003eOur study also revealed significant sex differences in the serum levels of BNP, ANP, leptin, adiponectin, CXCR4 and CXCL12. These serum biochemical markers were found to be correlated with BMI. Importantly, in female patients, the PAC was positively correlated with the serum concentrations of CXCR4 and CXCL12. These findings suggest that distinct pathophysiological mechanisms may be involved in patients with PA of different sexes. BNP and ANP, which are members of the natriuretic peptide (NP) family, serve as common markers of cardiac volume. NPs have diuretic, natriuretic, and vascular relaxation effects and play pivotal roles in cardiovascular, endocrine, renal, and vascular homeostasis[\\u003cspan additionalcitationids=\\\"CR20\\\" citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. The NP family is the target of the novel antihypertensive agent sacubitril/valsartan. Notably, circulating NP levels tend to be lower in patients with obesity and diabetes [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e] but are elevated in those with PA. Our study indicated no significant difference between BNP and ANP in patients with PA combined with T2DM. Leptin, which is produced primarily by adipose tissue, is present at higher serum levels in obese individuals than in nonobese individuals[\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. Elevated circulating leptin levels are associated with increased renal sympathetic tone in overweight individuals and are involved in insulin secretion and peripheral tissue sensitivity[\\u003cspan additionalcitationids=\\\"CR25\\\" citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. Leptin is also associated with hypertension, atherosclerosis[\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e], and decreased kidney function[\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. Importantly, our results showed that a higher BMI in females corresponded to significantly elevated leptin levels, suggesting a potential avenue for the treatment of hypertension-related complications in women through modulation of the leptin-aldosterone axis. CXCL12, an agonist of the G protein-coupled receptor CXCR4, is widely expressed and influences angiogenesis and leukocytes, playing roles in various pathologies, including cancer and autoimmune and inflammatory disorders[\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e]. The expression patterns of CXCR4 and aldosterone synthetase in the adrenal cortex have led to the use of 68Ga-Pentixafor-PET/CT for subtype diagnosis of PA[\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e]. However, to the best of our knowledge, there is limited research on the expression of CXCL12 and CXCR4 in the serum of PA patients. Our study revealed a positive correlation between serum CXCR4/CXCL12 concentrations and the PAC in female patients, indicating the potential role of CXCL12/CXCR4 in both local adrenal aldosterone synthetase expression and systemic regulation. Previous research has shown that increased serum CXCL12 levels are associated with major adverse cardiovascular events[\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. Additionally, the CXCL12/CXCR4 axis has implications for diabetic nephropathy, with increased CXCR4 expression observed in renal biopsy tissues of diabetic nephropathy patients[\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. Our findings suggest that the high expression of CXCR4/CXCL12 in women may be associated with sex-specific kidney damage in PA patients. Activation of the NOD-like receptor protein 3 inflammasome (NLRP3) pathway by CXCR4 has been shown to induce neuronal inflammation[\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e], while the MR antagonist eplerenone inhibits chronic inflammation development by blocking NLRP3 inflammasome activation signals in adipose tissue and the liver of high-fat diet mice[\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. Currently, there is limited research on the correlation between PA and immune regulation, suggesting that further investigation into the involvement of CXCR4/CXCL12 in kidney damage related to PA combined with T2DM is worthwhile. Future studies may explore sex-specific antihypertensive drug efficacy, revealing the clinical significance of this drug for the treatment of PA.\\u003c/p\\u003e\"},{\"header\":\"5. Conclusions\",\"content\":\"\\u003cp\\u003eIn summary, our study yielded several key findings:\\u003c/p\\u003e\\n\\u003cp\\u003e1. The prevalence of PA among T2DM patients with hypertension was 22.1%, emphasizing the common coexistence of these conditions.\\u003c/p\\u003e\\n\\u003cp\\u003e2. Sex differences were prominent in the clinical manifestations of patients with PA. Male PA patients were more prone to obesity, and the PAC was positively correlated with BMI. Female PA patients exhibited a higher incidence of proteinuria, and the PAC was positively correlated with this renal complication. Early detection and management of PA in female patients may yield favorable long-term renal outcomes.\\u003c/p\\u003e\\n\\u003cp\\u003e3. Significant sex differences were observed in the serum concentrations of BNP, ANP, leptin, adiponectin, CXCR4, and CXCL12. These markers are also correlated with BMI, highlighting the intricate relationship between obesity and hormonal regulation in these patients. In females, the PAC was positively correlated with the serum levels of CXCR4 and CXCL12, suggesting sex differences in the pathophysiological mechanisms underlying PA.\\u003c/p\\u003e\\n\\u003cp\\u003eOur study paves the way for future research into the complex interactions between sex, hormones, and metabolic factors in patients with PA and T2DM. Understanding these dynamics may lead to more tailored and effective treatment strategies for these comorbid conditions.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eAuthor Contributions: Conceptualization, Xin Su; methodology, Wei Liu; software, Juanjuan Zhou; validation, Shanyu Yi and Meiyu Shen; data curation, Zaizhao Li; writ-ing\\u0026mdash;original draft preparation, Wei Liu; writing\\u0026mdash;review and editing, Xin Su; funding acquisition, Xin Su and Wei Liu. All the authors have read and agreed to the published version of the manuscript.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eSociety, C.D. Guideline for the prevention and treatment of type 2 diabetes mellitus in China(2020 edition). \\u003cem\\u003eChinese Journal of Practical Internal Medicine\\u003c/em\\u003e August 2021, \\u003cem\\u003eVol.41 No.8\\u003c/em\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eEndocrinology, C.S.o. Expert Consensus on the Diagnosis and Treatment of Primary hyperaldosteronism (2020 edition). Chinese Journal of Endocrinology and Metabolism 2020, \\u003cem\\u003e36\\u003c/em\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eObesity Group, S.o.E., Chinese Medical Association. Consensus of Chinese adult obesity prevention experts. ChinJ Endocrinol Metab 2011, \\u003cem\\u003eVol.27, No.2\\u003c/em\\u003e, 711\\u0026ndash;717.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHu, Y.; Zhang, J.; Liu, W.; Su, X. Determining the Prevalence of Primary Aldosteronism in Patients With New-Onset Type 2 Diabetes and Hypertension. J Clin Endocrinol Metab 2020, \\u003cem\\u003e105\\u003c/em\\u003e, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1210/clinem/dgz293\\u003c/span\\u003e\\u003cspan address=\\\"10.1210/clinem/dgz293\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAkehi, Y.; Yanase, T.; Motonaga, R.; Umakoshi, H.; Tsuiki, M.; Takeda, Y.; Yoneda, T.; Kurihara, I.; Itoh, H.; Katabami, T.; et al. High Prevalence of Diabetes in Patients With Primary Aldosteronism (PA) Associated With Subclinical Hypercortisolism and Prediabetes More Prevalent in Bilateral Than Unilateral PA: A Large, Multicenter Cohort Study in Japan. Diabetes Care 2019, \\u003cem\\u003e42\\u003c/em\\u003e, 938\\u0026ndash;945, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.2337/dc18-1293\\u003c/span\\u003e\\u003cspan address=\\\"10.2337/dc18-1293\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGoodfriend, T.L.; Egan, B.M.; Kelley, D.E. Plasma aldosterone, plasma lipoproteins, obesity and insulin resistance in humans. Prostaglandins Leukot Essent Fatty Acids 1999, \\u003cem\\u003e60\\u003c/em\\u003e, 401\\u0026ndash;405, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1016/s0952-3278(99)80020-9\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/s0952-3278(99)80020-9\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHeizhati, M.; Aierken, X.; Gan, L.; Lin, M.; Luo, Q.; Wang, M.; Hu, J.; Maimaiti, N.; Duiyimuhan, G.; Yang, W.; et al. Prevalence of primary aldosteronism in patients with concomitant hypertension and obstructive sleep apnea, baseline data of a cohort. Hypertens Res 2023, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1038/s41440-023-01226-w\\u003c/span\\u003e\\u003cspan address=\\\"10.1038/s41440-023-01226-w\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHatano, Y.; Sawayama, N.; Miyashita, H.; Kurashina, T.; Okada, K.; Takahashi, M.; Matsumoto, M.; Hoshide, S.; Sasaki, T.; Nagashima, S.; et al. Sex-specific Association of Primary Aldosteronism With Visceral Adiposity. J Endocr Soc 2022, \\u003cem\\u003e6\\u003c/em\\u003e, bvac098, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1210/jendso/bvac098\\u003c/span\\u003e\\u003cspan address=\\\"10.1210/jendso/bvac098\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBu, X.; Sun, F.; Zhang, H.; Liu, X.; Zhao, Z.; He, H.; Li, Y.; Yan, Z.; Zhu, Z. Clinical Characteristics of Target Organ Damage in Primary Aldosteronism with or without Metabolic Syndrome. \\u003cem\\u003eJ Diabetes Res\\u003c/em\\u003e 2022, \\u003cem\\u003e2022\\u003c/em\\u003e, 8932133, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1155/2022/8932133\\u003c/span\\u003e\\u003cspan address=\\\"10.1155/2022/8932133\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGershuni, V.M.; Herman, D.S.; Kelz, R.R.; Roses, R.E.; Cohen, D.L.; Trerotola, S.O.; Fraker, D.L.; Wachtel, H. Challenges in obesity and primary aldosteronism: Diagnosis and treatment. Surgery 2020, \\u003cem\\u003e167\\u003c/em\\u003e, 204\\u0026ndash;210, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1016/j.surg.2019.03.036\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.surg.2019.03.036\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWada, T.; Ishikawa, A.; Watanabe, E.; Nakamura, Y.; Aruga, Y.; Hasegawa, H.; Onogi, Y.; Honda, H.; Nagai, Y.; Takatsu, K.; et al. Eplerenone prevented obesity-induced inflammasome activation and glucose intolerance. J Endocrinol 2017, \\u003cem\\u003e235\\u003c/em\\u003e, 179\\u0026ndash;191, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1530/JOE-17-0351\\u003c/span\\u003e\\u003cspan address=\\\"10.1530/JOE-17-0351\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVasan, R.S.; Evans, J.C.; Benjamin, E.J.; Levy, D.; Larson, M.G.; Sundstrom, J.; Murabito, J.M.; Sam, F.; Colucci, W.S.; Wilson, P.W. Relations of serum aldosterone to cardiac structure: gender-related differences in the Framingham Heart Study. Hypertension 2004, \\u003cem\\u003e43\\u003c/em\\u003e, 957\\u0026ndash;962, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1161/01.HYP.0000124251.06056.8e\\u003c/span\\u003e\\u003cspan address=\\\"10.1161/01.HYP.0000124251.06056.8e\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKanashiro-Takeuchi, R.M.; Heidecker, B.; Lamirault, G.; Dharamsi, J.W.; Hare, J.M. Sex-specific impact of aldosterone receptor antagonism on ventricular remodeling and gene expression after myocardial infarction. Clin Transl Sci 2009, \\u003cem\\u003e2\\u003c/em\\u003e, 134\\u0026ndash;142, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1111/j.1752-8062.2009.00094.x\\u003c/span\\u003e\\u003cspan address=\\\"10.1111/j.1752-8062.2009.00094.x\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNakamaru, R.; Yamamoto, K.; Akasaka, H.; Rakugi, H.; Kurihara, I.; Yoneda, T.; Ichijo, T.; Katabami, T.; Tsuiki, M.; Wada, N.; et al. Sex Differences in Renal Outcomes After Medical Treatment for Bilateral Primary Aldosteronism. Hypertension 2021, \\u003cem\\u003e77\\u003c/em\\u003e, 537\\u0026ndash;545, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1161/HYPERTENSIONAHA.120.16449\\u003c/span\\u003e\\u003cspan address=\\\"10.1161/HYPERTENSIONAHA.120.16449\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eReincke, M.; Fischer, E.; Gerum, S.; Merkle, K.; Schulz, S.; Pallauf, A.; Quinkler, M.; Hanslik, G.; Lang, K.; Hahner, S.; et al. Observational study mortality in treated primary aldosteronism: the German Conn's registry. Hypertension 2012, \\u003cem\\u003e60\\u003c/em\\u003e, 618\\u0026ndash;624, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1161/HYPERTENSIONAHA.112.197111\\u003c/span\\u003e\\u003cspan address=\\\"10.1161/HYPERTENSIONAHA.112.197111\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJ.Deinum, B.R.n., E.Mathiesen, F.H.M.Derkx, W.C.J.Hop, M.A.D.H. Schalekamp. Increase in serum prorenin precedes onset of microalbuminuria in patients with insulin-dependent diabetes mellitus. Diabetologia 1999, \\u003cem\\u003e42\\u003c/em\\u003e, 1006\\u0026ndash;1010.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVisniauskas, B.; Arita, D.Y.; Rosales, C.B.; Feroz, M.A.; Luffman, C.; Accavitti, M.J.; Dawkins, G.; Hong, J.; Curnow, A.C.; Thethi, T.K.; et al. Sex differences in soluble prorenin receptor in patients with type 2 diabetes. Biol Sex Differ 2021, \\u003cem\\u003e12\\u003c/em\\u003e, 33, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1186/s13293-021-00374-3\\u003c/span\\u003e\\u003cspan address=\\\"10.1186/s13293-021-00374-3\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJo, R.; Shibata, H.; Kurihara, I.; Yokota, K.; Kobayashi, S.; Murai-Takeda, A.; Mitsuishi, Y.; Hayashi, T.; Nakamura, T.; Itoh, H. Mechanisms of mineralocorticoid receptor-associated hypertension in diabetes mellitus: the role of O-GlcNAc modification. Hypertens Res 2023, \\u003cem\\u003e46\\u003c/em\\u003e, 19\\u0026ndash;31, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1038/s41440-022-01036-6\\u003c/span\\u003e\\u003cspan address=\\\"10.1038/s41440-022-01036-6\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePandey, K.N. Molecular Signaling Mechanisms and Function of Natriuretic Peptide Receptor-A in the Pathophysiology of Cardiovascular Homeostasis. Front Physiol 2021, \\u003cem\\u003e12\\u003c/em\\u003e, 693099, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/fphys.2021.693099\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fphys.2021.693099\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eOkamoto, R.; Ali, Y.; Hashizume, R.; Suzuki, N.; Ito, M. BNP as a Major Player in the Heart-Kidney Connection. Int J Mol Sci 2019, \\u003cem\\u003e20\\u003c/em\\u003e, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3390/ijms20143581\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/ijms20143581\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYAU-JIUNN LEE, S.-R.L., SHYI-JANG SHIN, YUNG-HSIUNG LAI, YOUNG-TSO LIN, AND JUEI-HSIUNG TSAI. rain Natriuretic Peptide Is Synthesized in the Human Adrenal Medulla and Its Messenger Ribonucleic Acid Expression along with That of Atria1 Natriuretic Peptide Are Enhanced in Patients with Primary Aldosteronism. \\u003cem\\u003eJournal of Clinical Endocrinology and Metabolism\\u003c/em\\u003e 1994, \\u003cem\\u003e79\\u003c/em\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWang, T.J.; Larson, M.G.; Levy, D.; Benjamin, E.J.; Leip, E.P.; Wilson, P.W.; Vasan, R.S. Impact of obesity on plasma natriuretic peptide levels. Circulation 2004, \\u003cem\\u003e109\\u003c/em\\u003e, 594\\u0026ndash;600, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1161/01.CIR.0000112582.16683.EA\\u003c/span\\u003e\\u003cspan address=\\\"10.1161/01.CIR.0000112582.16683.EA\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eIzquierdo, A.G.; Crujeiras, A.B.; Casanueva, F.F.; Carreira, M.C. Leptin, Obesity, and Leptin Resistance: Where Are We 25 Years Later? \\u003cem\\u003eNutrients\\u003c/em\\u003e 2019, \\u003cem\\u003e11\\u003c/em\\u003e, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3390/nu11112704\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/nu11112704\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAmitani, M.; Asakawa, A.; Amitani, H.; Inui, A. The role of leptin in the control of insulin-glucose axis. Front Neurosci 2013, \\u003cem\\u003e7\\u003c/em\\u003e, 51, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/fnins.2013.00051\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fnins.2013.00051\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChoi, J.R.; Kim, J.Y.; Huh, J.H.; Kim, S.H.; Koh, S.B. Contribution of obesity as an effect regulator to an association between serum leptin and incident metabolic syndrome. Clin Chim Acta 2018, \\u003cem\\u003e487\\u003c/em\\u003e, 275\\u0026ndash;280, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1016/j.cca.2018.09.038\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.cca.2018.09.038\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eda Silva, A.A.; do Carmo, J.M.; Hall, J.E. Role of leptin and central nervous system melanocortins in obesity hypertension. Curr Opin Nephrol Hypertens 2013, \\u003cem\\u003e22\\u003c/em\\u003e, 135\\u0026ndash;140, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1097/MNH.0b013e32835d0c05\\u003c/span\\u003e\\u003cspan address=\\\"10.1097/MNH.0b013e32835d0c05\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGhantous, C.M.; Azrak, Z.; Hanache, S.; Abou-Kheir, W.; Zeidan, A. Differential Role of Leptin and Adiponectin in Cardiovascular System. \\u003cem\\u003eInt J Endocrinol\\u003c/em\\u003e 2015, \\u003cem\\u003e2015\\u003c/em\\u003e, 534320, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1155/2015/534320\\u003c/span\\u003e\\u003cspan address=\\\"10.1155/2015/534320\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eShih, Y.L.; Shih, C.C.; Chen, S.Y.; Chen, J.Y. Elevated serum leptin levels are associated with lower renal function among middle-aged and elderly adults in Taiwan, a community-based, cross-sectional study. Front Endocrinol (Lausanne) 2022, \\u003cem\\u003e13\\u003c/em\\u003e, 1047731, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/fendo.2022.1047731\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fendo.2022.1047731\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHe, X.; Li, C.; Yin, H.; Tan, X.; Yi, J.; Tian, S.; Wang, Y.; Liu, J. Mesenchymal stem cells inhibited the apoptosis of alveolar epithelial cells caused by ARDS through CXCL12/CXCR4 axis. Bioengineered 2022, \\u003cem\\u003e13\\u003c/em\\u003e, 9060\\u0026ndash;9070, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1080/21655979.2022.2052652\\u003c/span\\u003e\\u003cspan address=\\\"10.1080/21655979.2022.2052652\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDing, J.; Tong, A.; Hacker, M.; Feng, M.; Huo, L.; Li, X. Usefulness of 68 Ga-Pentixafor PET/CT on Diagnosis and Management of Cushing Syndrome. Clin Nucl Med 2022, \\u003cem\\u003e47\\u003c/em\\u003e, 669\\u0026ndash;676, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1097/RLU.0000000000004244\\u003c/span\\u003e\\u003cspan address=\\\"10.1097/RLU.0000000000004244\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhang, S.; Ding, Y.; Feng, F.; Gao, Y. The role of blood CXCL12 level in prognosis of coronary artery disease: A meta-analysis. Frontiers in Cardiovascular Medicine 2022, \\u003cem\\u003e9\\u003c/em\\u003e, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/fcvm.2022.938540\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fcvm.2022.938540\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSjaarda, J.; Gerstein, H.; Chong, M.; Yusuf, S.; Meyre, D.; Anand, S.S.; Hess, S.; Pare, G. Blood CSF1 and CXCL12 as Causal Mediators of Coronary Artery Disease. J Am Coll Cardiol 2018, \\u003cem\\u003e72\\u003c/em\\u003e, 300\\u0026ndash;310, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1016/j.jacc.2018.04.067\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.jacc.2018.04.067\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSiddiqi, F.S.; Chen, L.H.; Advani, S.L.; Thai, K.; Batchu, S.N.; Alghamdi, T.A.; White, K.E.; Sood, M.M.; Gibson, I.W.; Connelly, K.A.; et al. CXCR4 promotes renal tubular cell survival in male diabetic rats: implications for ligand inactivation in the human kidney. Endocrinology 2015, \\u003cem\\u003e156\\u003c/em\\u003e, 1121\\u0026ndash;1132, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1210/en.2014-1650\\u003c/span\\u003e\\u003cspan address=\\\"10.1210/en.2014-1650\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi, W.; Liang, J.; Li, S.; Jiang, S.; Song, M.; Xu, S.; Wang, L.; Meng, H.; Zhai, D.; Tang, L.; et al. The CXCL12-CXCR4-NLRP3 axis promotes Schwann cell pyroptosis and sciatic nerve demyelination in rats. Clin Exp Immunol 2023, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1093/cei/uxad081\\u003c/span\\u003e\\u003cspan address=\\\"10.1093/cei/uxad081\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"type 2 diabetes, primary aldosteronism, CXCR4, CXCL12, BNP, ANP, leptin, adiponectin\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-3939206/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-3939206/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eType 2 diabetes mellitus (T2DM) and hypertension are prevalent chronic diseases in modern society. Primary hyperaldosteronism (PA) is the most common cause of secondary hypertension. Our study examined the clinical characteristics of T2DM patients afflicted with PA. We enrolled a total of 213 T2DM patients with hypertension and observed a 22.1% prevalence of PA within this group. Sex disparities in clinical presentations were observed. Among male PA patients, the incidence of obesity significantly exceeded that of the essential hypertension (EH) group (40% vs. 4.5%, χ2\\u0026thinsp;=\\u0026thinsp;4.172, p\\u0026thinsp;=\\u0026thinsp;0.041), with the plasma aldosterone concentration (PAC) demonstrating a positive correlation with body mass index (BMI) (correlation coefficient\\u0026thinsp;=\\u0026thinsp;0.318, p\\u0026thinsp;=\\u0026thinsp;0.001). In contrast, among female PA patients, the prevalence of proteinuria was notably greater than that in the EH group (54.5% vs. 24.7%, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05), and the PAC was positively correlated with proteinuria (correlation coefficient\\u0026thinsp;=\\u0026thinsp;0.213, p\\u0026thinsp;=\\u0026thinsp;0.032). Significant sex differences emerged in the serum concentrations of brain natriuretic peptide (BNP), atrial natriuretic peptide (ANP), C-X-C motif chemokine receptor 4 (CXCR4), C-X-C motif chemokine ligand 12 (CXCL12), adiponectin, and leptin. The serum levels of BNP, ANP, CXCR4, CXCL12, and leptin were significantly correlated with BMI. In female patients, the PAC was significantly positively correlated with CXCR4 (correlation coefficient\\u0026thinsp;=\\u0026thinsp;0.322, p\\u0026thinsp;=\\u0026thinsp;0.004) and CXCL12 (correlation coefficient\\u0026thinsp;=\\u0026thinsp;0.248, p\\u0026thinsp;=\\u0026thinsp;0.029). Our findings highlight sex-specific differences in the clinical manifestations of T2DM patients with PA. Notably, the serum BNP, ANP, leptin, adiponectin, CXCR4, and CXCL12 levels exhibited significant sex differences and correlated significantly with BMI. In female patients, the PAC was positively correlated with CXCR4 and CXCL12 levels.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Sex Differences in Clinical Manifestations and Serum CXCR4/CXCL12 Levels in Patients with Type 2 Diabetes and Primary Aldosteronism\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-02-12 19:20:04\",\"doi\":\"10.21203/rs.3.rs-3939206/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"2614af0d-4800-44a8-8ced-c7cdb7de653b\",\"owner\":[],\"postedDate\":\"February 12th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-02-15T06:14:40+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-02-12 19:20:04\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-3939206\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-3939206\",\"identity\":\"rs-3939206\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}