Title: BMI as a determinant for metabolic-related changes in resistant hypertension

Isabella Fagian Pansani a; Ana Paula Cabral de Faria, PharmD, PhD a,
Natália R. Barbaro, PharmD, PhD a, Andréa R. Sabbatini, PharmD, PhD a, Rodrigo
Modolo, MD, PhD a; Heitor Moreno, MD, PhD a,.

aLaboratory of Cardiovascular Pharmacology, Faculty of Medical
Sciences, University of Campinas, Campinas, SP, Brazil.
Place where it was held: Laboratory of Cardiovascular Pharmacology, Faculty of
Medical Sciences, University of Campinas, Campinas, SP, Brazil.

Background and objective
: Obesity is a common feature of resistant hypertension
(RHTN) and it is considered a strong risk factor for the lack of blood pressure control.
Moreover, increased aldosterone levels have been associated with impaired glucose
metabolism and may interact with adipose tissue deregulating inflammatory adipokines
such as leptin. This study aimed to verify the influence of obesity in aldosterone and
leptin plasma levels as well as in markers of glucose metabolism in RHTN subjects.
Patients and methods: Ninety-one resistant hypertensive patients were divided into
two subgroups by the mean BMI: (i) a more obese (OBS, N=41, BMI>31.5 kg/m2) and
(ii) a leaner group (LNR, N=50, BMI<31.5 kg/m2). We determined body composition by
bioimpedance (BIA 450). Fasting glucose, glycated hemoglobin (HbA1c) as well as
aldosterone (radioimmunoassay) and leptin (enzyme immunoassay) levels were also
evaluated. Results: OBS subgroup showed altered glucose metabolism by fasting
glucose (129±48 vs. 107±32 mg/dL, p=0.04) and glycated hemoglobin (7.6±2.3 vs.
6.8±1.9%, p=0.03). Plasma aldosterone (137.9±102.0 vs. 92.6±67.9 pg/ml, p=0.03) as
well as leptin levels (24.4±17.2 vs. 36.4±23.5 ng/ml, p=0.01) were also higher in OBS
compared with LNR group. Multiple linear regression indicated that glucose level is
independently associated with obesity in RHTN patients. Conclusions: Our findings
demonstrated that a greater BMI may be determinant for deregulating glucose
metabolism as well as aldosterone and leptin levels in resistant hypertensive subjects.
Keywords: Refractory hypertension; obesity; diabetes; leptin; aldosterone.
Resistant hypertension (RHTN) was defined to identify subjects at high cardiovascular risk with persistently high blood pressure (BP) and should benefit from special diagnostic and therapeutic conditions Resistant hypertensive patients are those (i) who have BP above the target levels (≥ 140x90mmHg) despite the concurrent use of three or more classes of antihypertensive drugs in optimal doses, one being a diuretic, or (ii) who can achieve BP control with the use of four or more agents According to Framingham cohort study, obesity is one of the main risk factors for the lack of BP control, with great impact on resistance to antihypertensive treatment About one third of obese patients have poor BP control compared to patients with BMI<25 kg/m2 Hence, obesity can be associated with more severe hypertension, with patients requiring more medications to effectively control BP than those who were of normal weight The pathophysiological mechanisms of obesity-induced HTN are complex and not fully elucidated, but have been associated with impaired sodium excretion, increased activity of the sympathetic nervous system and activation of the renin-angiotensin-aldosterone system (RAAS) The hyperaldosteronism, as well as obesity, is associated with clinical and biochemical features of RHTN The aldosterone hormone promotes insulin resistance and participates in deregulation of inflammatory adipokines, such as leptin, from adipose tissue resulting in systemic inflammation and glucose intolerance It is well documented that leptin influences the BP levels and insulin sensitivity by regulating sympathetic nerve activity in both thermogenic brown adipose tissue and
in the kidney, which may result in RAAS stimulation This proinflammatory
adipokine was also related to cardiovascular damage in obese resistant hypertensive
subjects Although emerging data suggest that obesity, aldosterone excess and leptin
levels may interact to have an important role in the pathophysiology of RHTN some
questions are still unknown. This study aimed to verify the influence of obesity in
aldosterone and leptin plasma levels as well as in markers of glucose metabolism in
RHTN subjects.


This study aimed to verify the influence of obesity in aldosterone and leptin plasma levels as well as in markers of glucose metabolism in RHTN subjects.
Study Population
Ninety-one patients followed at Outpatient Resistant Hypertension Clinic Hospital of the Faculty of Medical Sciences, University of Campinas (FCM/UNICAMP, Campinas, Brazil) were included and categorized into two subgroups by the mean BMI: (i) a more obese group with BMI>31.5 kg/m2 (OBS, N=41) and (ii) a leaner group with BMI<31.5 kg/m2 (LNR, N=50). The inclusion of patients was performed only after a six-month period of clinical follow-up, and exclusion of secondary causes of hypertension (pheochromocytoma, coarctation of aorta, primary aldosteronism, Cushing's syndrome and renal artery stenosis) and pseudoresistance by ambulatory BP monitoring (ABPM) and pill count assessment (screening for white coat hypertension and non-drug adherence, respectively). The inclusion criteria were subjects older than 35 years diagnosed with "true" RHTN according to the Guidelines of the American Heart Association Patients with symptomatic ischemic heart, liver or renal diseases or history of stroke or peripheral vascular disease were excluded. This cross-sectional study was approved by the Research Ethics Committee of FCM/UNICAMP (approval no. 222/2011) and it was conducted in accordance with the Declaration of Helsinki. All patients signed an informed consent before participation in the study. Office Blood Pressure Measurement The office systolic (SBP) and diastolic (DBP) blood pressures were measured in the right arm using a validated digital sphygmomanometer (HEM-907XL, Omron Heathcare Inc., Japan). Ambulatory Blood Pressure Monitoring (ABPM) The ABPM is essential for the diagnosis of true resistant hypertension, since it avoids misleading diagnoses of white coat hypertension. The measures of SBP and DBP were obtained by SPACELABS 24h-ABPM monitoring (Washington, USA) according to the Guidelines of the European Society of Hypertension. Patients were instructed to keep their routine activities and write symptoms in a personal diary. Biochemical Tests The routine biochemical exams such as fasting glucose and glycated hemoglobin (HbA1c) were assessed. Plasma aldosterone levels were determined by radioimmunoassay (RIA) and plasma leptin by enzyme immunoassay kit (ELISA). The intra- and interassay coefficients of variation were below 4.8% for leptin kits. Bioimpedance Variables fat-free mass (FFM), fat mass (FM), total body water (TBW) and basal metabolic rate (BMR) were determined by the device Bioimpedance Analyser 450 (Biodynamics Corporation, Seattle, USA). Briefly, the method is based on tetrapolar bioelectrical impedance (electrodes on feet and hands) to assess body composition (mass and body fluids). The measurements were performed according to the manufacturer's instructions with the patient after overnight fasting, instructed to avoid the practice of physical activity and smoking prior to the exam. Statistical analyses The variables were expressed as mean and standard deviation and compared using the Student's t-test or Mann-Whitney test, according to the data distribution.
Correlation analyses (by Pearson or Spearman tests) and a multiple linear regression
analysis were performed to evaluate the association of the variables of interest to the
presence of obesity. The level of significance accepted was α=0.05.


The general characteristics of the subgroups according to BMI categorization are listed in table 1. There were no differences regarding age, gender and race among the studied subgroups. Still, office BP and ABPM levels were similar, except for diastolic ABPM, which was lower in the OBS subgroup. Bioimpedance body composition variables were in agreement with categorization of subgroups by BMI as shown in figure 1. The subgroups did not differ the use of antihypertensive drugs (table 2). Furthermore, the proportion of statin therapy (45.8% vs. 55.6%), glucose-lowering drugs (33.3% vs. 55.6%) and insulin use (10.4% vs. 20.0%) did not differ among subjects in the leaner group and the obese group, respectively. The patients in the OBS subgroup showed altered glucose metabolism, determined by higher levels of fasting glucose (129±48 vs. 107±32 mg/dL, p=0.04,
figure 2A) and glycated hemoglobin (7.6±2.3 vs. 6.8±1.9%, p=0.03, figure 2B). Plasma
aldosterone (137.9±102.0 vs. 92.6±67.9 pg/ml, p=0.03, figure 2C) as well as leptin
levels (24.4±17.2 vs. 36.4±23.5 ng/ml, p=0.01, figure 2D) were also higher in OBS
when compared to LNR subgroup. Correlation analyses demonstrated that BMI
(r=0.33, p=0.006; r=0.29, p=0.01; r=0.32, p=0.002) and FM (r=0.32, p=0.03; r=0.26,
p=0.04; r=0.40, p=0.003) were positively associated with fasting glucose, glycated
hemoglobin and leptin levels, respectively. Finally, as shown in table 3, multiple linear
regression indicated that only glucose level is independently associated with obesity in
RHTN patients, adjusted for age, gender and race.

This present study showed that obese resistant hypertensive patients (BMI>31.5 kg/m²) had higher fasting glucose as well as HbA1c levels, which may reflect the impact of obesity in deregulation of glucose metabolism in these individuals. In addition, fasting blood glucose was strongly and independently associated with obesity - represented by increased BMI. In fact, obesity is a strong predisposing factor for the development of type 2 diabThis relationship may be explained by the association of obesity with low-grade inflammation, characterized by higher levels of circulating proinflammatory cytokines and fatty acids, which induces insulin resistance by interfering in the normal insulin function and causing β-cell dysfunction Indeed, the β-cell failure may be partly due to genetic factors and partly due to acquired factors. Among the acquired factors, the prolonged exposure of pancreatic β-cells to high levels of glucose and lipids may contribute to oxidative stress and high rates of β-cells apoptosis The OBS subgroup showed greater hormonal change due to the higher plasma levels of aldosterone and leptin when compared to the counterparts. The effects of aldosterone are mediated by the mineralocorticoid receptor (MR), which acts on the salt homeostasis and BP regulation in epithelial target tissues. Those receptors have also been identified stimulating non-classical signaling pathways of aldosterone, particularly on the adipose tissue, which mediate the adipogenesis and proinflammatory process In this context, MR activation may arise as a causative factor in several pathological conditions, including insulin resistance and obesity Obesity and increased aldosterone may be linked, because adipose tissue releases soluble factors that stimulate adrenal aldosterone secretion In turn, active MR on adipocytes promotes proinflammatory cytokines expression, which causes reduced insulin receptor expression and impaired insulin-induced glucose uptake Moreover, improvement in insulin sensitivity has been closely associated with decreases in skeletal muscle NADPH oxidase activity – as well as the levels of reactive oxygen species – and with greater mitochondrial structure integrity Thus, the MR antagonists, besides the current use in treatment of RHTN, emerge as a potential pharmacological strategy to reverse metabolic adverse outcomes involved in RHTN diseaseand downregulate proinflammatory adipokines, such as lepti In addition, leptin – secreted from the peripheral adipose tissue – reaching the brain can activate neural pathways that increase the renal sympathetic nervous system. This will result in RAAS stimulation leading to increases in sodium retention, volume expansion and BP levels As obesity may result in chronic hyperleptinemia, it is possible to associated leptin levels with the RHTN pathophysiology Finally, the parameters of bioimpedance in agreement with the literature demonstrated that obese individuals have higher FFM, FM, BMR and TBW. A recent study has showed that the FFM and FM contribute almost equally to the BMI variation, being this contribution caused by common genetic as well as shared environmental and metabolic factorsBMI is an index current used in clinical practice as an easy indirect parameter of obesity. Although the parameters of bioimpedance may offer a better description of adiposity of an individual the BMI categorization has been associated with metabolic changes in our subjects, supporting the measurement of this parameter of great interest. On the other hand, the bioelectrical impedance method can be more appreciated in the clinical management of RHTN population, since it may better predict cardiovascular ris Some limitations to our study should be mentioned. This study enrolled a small number of RHTN patients. The 24-hour urinary aldosterone excretion rate test was not performed, although this assay could help assess patients with changes in aldosterone physiology. Some antihypertensive drugs may reduce expression of proinflammatory factors reversing obesity-related changesDespite that, those possible sources of interferences did not affect our findings, since subgroups had similar proportion of antihypertensive agents use. Furthermore, due to ethical issues RHTN individuals must not be assessed withdrawing the antihypertensive drugs. Because this study was cross-sectional, causal inferences cannot be made. However, our findings support a possible link of metabolic diseases such as obesity, diabetes and resistant hypertension. In conclusion, our findings showed that higher BMI may be determinant in deregulating glucose metabolism as well as aldosterone and leptin levels in resistant
hypertensive subjects. Those outcomes support that an intensive lifestyle change is
crucial trying to revert metabolic disorders and achieve BP control Moreover,
optimization of therapy in RHTN-related disorders such as diabetesmust also be
focused. Indeed, this may reflect a worse prognosis of those obese subjects, although
this hypothesis should be tested using prospective studies with a larger RHTN

This study was supported by the State of São Paulo
Research Foundation (FAPESP) and National Council for Scientific and Technological
Development (CNPq), Brazil.
Calhoun DA, Jones D, Textor S, Goff DC, Murphy TP, Toto RD, et al. Resistant hypertension: diagnosis, evaluation, and treatment. A scientific statement from the American Heart Association Professional Education Committee of the Council for High Blood Pressure Research. Hypertension. 2008;51:1403-19. Lloyd-Jones DM, Evans JC, Larson MG, and Levy D. Treatment and control of hypertension in the community: a prospective analysis. Hypertension. 2002;40:640-6. Reisin E, Graves JW, Yamal JM, Barzilay JI, Pressel SL, Einhorn PT, et al. Blood pressure control and cardiovascular outcomes in normal-weight, overweight, and obese hypertensive patients treated with three different antihypertensives in ALLHAT. J Hypertens. 2014;32:1503-13. Bramlage P, Pittrow D, Wittchen HU, Kirch W, Boehler S, Lehnert H, et al. Hypertension in overweight and obese primary care patients is highly prevalent and poorly controlled. Am J Hypertens. 2004;17:904-10. Hall JE. The kidney, hypertension, and obesity. Hypertension. 2003;41:625-33. Nishizaka MK, Pratt-Ubunama M, Zaman MA, Cofield S, and Calhoun DA. Validity of plasma aldosterone-to-renin activity ratio in African American and white subjects with resistant hypertension. Am J Hypertens. 2005;18:805-12. Martins LC, Figueiredo VN, Quinaglia T, Boer-Martins L, Yugar-Toledo JC, Martin JF, et al. Characteristics of resistant hypertension: ageing, body mass index, hyperaldosteronism, cardiac hypertrophy and vascular stiffness. J Hum Hypertens. 2011;25:532-8. de Haro Moraes C, Figueiredo VN, de Faria AP, Barbaro NR, Sabbatini AR, Quinaglia T, et al. High-circulating leptin levels are associated with increased blood pressure in uncontrolled resistant hypertension. J Hum Hypertens. 2013;27:225-30. de Faria AP, Modolo R, Fontana V, and Moreno H. Adipokines: Novel Players in Resistant Hypertension. J Clin Hypertens (Greenwich). 2014. Muller H, Schweitzer N, Johren O, Dominiak P, and Raasch W. Angiotensin II stimulates the reactivity of the pituitary-adrenal axis in leptin-resistant Zucker rats, thereby influencing the glucose utilization. Am J Physiol Endocrinol Metab. 2007;293:E802-10. Guo C, Ricchiuti V, Lian BQ, Yao TM, Coutinho P, Romero JR, et al. Mineralocorticoid receptor blockade reverses obesity-related changes in expression of adiponectin, peroxisome proliferator-activated receptor-gamma, and proinflammatory adipokines. Circulation. 2008;117:2253-61. da Silva AA, do Carmo J, Dubinion J, and Hall JE. The role of the sympathetic nervous system in obesity-related hypertension. Curr Hypertens Rep. 2009;11:206-11. Matsumura K, Tsuchihashi T, Fujii K, and Iida M. Neural regulation of blood pressure by leptin and the related peptides. Regul Pept. 2003;114:79-86. Dulloo AG, Jacquet J, Solinas G, Montani JP, and Schutz Y. Body composition phenotypes in pathways to obesity and the metabolic syndrome. Int J Obes (Lond). 2010;34 Suppl 2:S4-17. van Greevenbroek MM, Schalkwijk CG, and Stehouwer CD. Obesity-associated low-grade inflammation in type 2 diabetes mellitus: causes and consequences. Neth J Med. 2013;71:174-87. Zick Y. Insulin resistance: a phosphorylation-based uncoupling of insulin signaling. Trends Cell Biol. 2001;11:437-41. Brownlee M. A radical explanation for glucose-induced beta cell dysfunction. J Clin Invest. 2003;112:1788-90. Donath MY, Ehses JA, Maedler K, Schumann DM, Ellingsgaard H, Eppler E, et al. Mechanisms of beta-cell death in type 2 diabetes. Diabetes. 2005;54 Suppl 2:S108-13. Sowers JR, Whaley-Connell A, and Epstein M. Narrative review: the emerging clinical implications of the role of aldosterone in the metabolic syndrome and resistant hypertension. Ann Intern Med. 2009;150:776-83. Feraco A, Armani A, Mammi C, Fabbri A, Rosano GM, and Caprio M. Role of mineralocorticoid receptor and renin-angiotensin-aldosterone system in adipocyte dysfunction and obesity. J Steroid Biochem Mol Biol. 2013;137:99-106. Ehrhart-Bornstein M, Arakelyan K, Krug AW, Scherbaum WA, and Bornstein SR. Fat cells may be the obesity-hypertension link: Human adipogenic factors stimulate aldosterone secretion from adrenocortical cells. Endocrine Research. 2004;30:865-70. Lastra G, Whaley-Connell A, Manrique C, Habibi J, Gutweiler AA, Appesh L, et al. Low-dose spironolactone reduces reactive oxygen species generation and improves insulin-stimulated glucose transport in skeletal muscle in the TG(mRen2)27 rat. American Journal of Physiology-Endocrinology and Metabolism. 2008;295:E110-E6. Ubaid-Girioli S, de Souza LA, Yugar-Toledo JC, Martins LC, Ferreira-Melo S, Coelho OR, et al. Aldosterone Excess or Escape: Treating Resistant Hypertension. Journal of Clinical Hypertension. 2009;11:245-52. de Souza F, Muxfeldt E, Fiszman R, and Salles G. Efficacy of spironolactone therapy in patients with true resistant hypertension. Hypertension. 2010;55:147-52. Moon JR, Smith AE, Tobkin SE, Lockwood CM, Kendall KL, Graef JL, et al. Total body water changes after an exercise intervention tracked using bioimpedance spectroscopy: a deuterium oxide comparison. Clin Nutr. 2009;28:516-25. Krachler B, Volgyi E, Savonen K, Tylavsky FA, Alen M, and Cheng S. BMI and an anthropometry-based estimate of fat mass percentage are both valid discriminators of cardiometabolic risk: a comparison with DXA and bioimpedance. J Obes. 2013;2013:862514. Dosaev T, Prakash J, and Livshits G. Contribution of body composition components and soft-tissue biochemical factors to genetic variation of body mass index (BMI) in an ethnically homogeneous population. Am J Hum Biol. 2014. Kishore Mohan KB and Anburajan M. Multiparametric body composition analysis and anthropometric empirical indicator: obesity based south Indian perspective. J Endocrinol Invest. 2013;36:672-80. Zeng Q, Dong SY, Sun XN, Xie J, and Cui Y. Percent body fat is a better predictor of cardiovascular risk factors than body mass index. Brazilian Journal of Medical and Biological Research. 2012;45:591-600. Nedogoda SV, Ledyaeva AA, Chumachok EV, Tsoma VV, Mazina G, Salasyuk AS, et al. Randomized trial of perindopril, enalapril, losartan and telmisartan in overweight or obese patients with hypertension. Clin Drug Investig. 2013;33:553-61. Engeli S, Bohnke J, Gorzelniak K, Janke J, Schling P, Bader M, et al. Weight loss and the renin-angiotensin-aldosterone system. Hypertension. 2005;45:356-62. Esposito K, Pontillo A, Di Palo C, Giugliano G, Masella M, Marfella R, et al. Effect of weight loss and lifestyle changes on vascular inflammatory markers in obese women: a randomized trial. JAMA. 2003;289:1799-804. Combs TP, Wagner JA, Berger J, Doebber T, Wang WJ, Zhang BB, et al. Induction of adipocyte complement-related protein of 30 kilodaltons by PPARgamma agonists: a potential mechanism of insulin sensitization. Endocrinology. 2002;143:998-1007. Tables
Table 1.
General characteristics of RHTN subgroups
SBP office (mmHg) DBP office (mmHg) PP office (mmHg) Creatinine (mg/dL) Clear Creat (mL/min/1,73m²) Total cholesterol (mg/dL) Triglycerides (mg/dL) Plasma sodium (mEq/L) Plasma potassium (mEq/L) Microalbuminuria (mg/g) Values expressed as mean ± SD. M: male; F: female; BMI: body mass index; SBP:
systolic blood pressure; DBP: diastolic blood pressure; PP: pulse pressure; ABPM:
Ambulatory blood pressure monitoring; Clear Creat: creatinine clearance; HDL-c:
cholesterol high density lipoprotein; LDL-c: cholesterol low density lipoprotein. * p

Table 2.
Proportion of antihypertensive drugs use for the RHTN subgroups
Anti-HT drugs, n (%) Centrally acting-drugs Values expressed as mean±SD. ACE: angiotensin-converting enzyme inhibitors; ARB: angiotensin II receptor antagonists; CCB: calcium channel blockers. Table 3. Multiple linear regression for the presence of obesity in RHTN subgroups*
β coefficient
*Also adjusted for age, gender and race.

Figure legends
Figure 1.
Bioimpedance parameters in RHTN subgroups according to the
categorization of BMI (FFM: fat-free mass; FM: fat mass; BMR: basal metabolic rate;
TBW: total body water).

Figure 2.
Hormonal and metabolic parameters in RHTN subgroups according to the
categorization of BMI (HbA1c: glycated hemoglobin).

CONFLICT OF INTEREST: The authors declare no conflict of interest.


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