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Ricardo José Tofano,1,2 Leticia Maria Pescinni-Salzedas,1 Eduardo Federighi Baisi Chagas,2 Claudia Rucco Penteado Detregiachi,2 Elen Landgraf Guiguer,1– 3 Adriano Cressoni Araujo,1,2 Marcelo Dib Bechara,1 Claudio José Rubira,1 Sandra Maria Barbalho1– 3 1Department of Biochemistry and Pharmacology, School of Medicine, University of Marília (UNIMAR), Marília, São Paulo, Brazil; 2Postgraduate Program in Structural and Functional Interactions in Rehabilitation, UNIMAR, Marília, São Paulo, Brazil; 3School of Food and Technology of Marilia (FATEC), Marilia, São Paulo, BrazilCorrespondence: Sandra Maria BarbalhoDepartment of Biochemistry and Pharmacology, School of Medicine, University of Marília (UNIMAR), Av. Higino Muzzi Filho 1001, Marília 15525-902, São Paulo, BrazilTel +55 14 99655-3190Email smbarbalho@gmail.comAim: To evaluate the association between parameters of hyperferritinemia (HF) and metabolic syndrome (MS) in patients at cardiovascular risk.Patients and Methods: This is a cross-sectional analytical observational study that included 269 patients who attended a cardiology unit. Biochemical and anthropometric parameters were evaluated to identify the presence of HF and MS. The presence of MS was evaluated according to NCEP ATP III. Biochemical parameters (glycemia, triglycerides, HDL-c) were assessed according to the manufacturer’s protocols. Anthropometric measurements and blood pressure measurements were made by a trained professional. The chi-square (X2) test, odds ratio, normality distribution (verified by the Kolmogorov–Smirnov test), and Levene’s test were used to analyze the variables. To evaluate the effect of MS, HF, and the interaction between MS and HF, two-way analysis of variance (ANOVA) was performed based on the homogeneity of the variances, followed by Bonferroni’s post hoc comparisons. Spearman correlation analysis was performed to evaluate the relationship between quantitative variables. A multiple linear regression model was used to analyze the effect of covariables. A logistic regression model was built to analyze the variables that contribute significantly to predict the outcome (HF) using the backward method.Results: Our results showed that 57% of men and 49.5% of women presented with MS; 44% of men and 11% of women presented with HF. The presence of MS and hypertriglyceridemia increase the probability of having HF by up to 2.1 and 1.88 times, respectively, while for male sex it is increased by 6.2 times. Patients with HF have higher values of C-reactive protein, ferritin, and transferrin saturation, regardless of the presence of MS. The linear regression analysis model indicated that the variables considered in this study explain less than 30% of the variation in ferritin and that the presence of MS in men is responsible for 22% of the variation in the probability of the occurrence of HF.Conclusion: Our results show that hyperferritinemia is closely associated with the components of MS (positive correlation with glycemia, triglycerides levels, blood pressure, and waist circumference, and negative correlation with HDL-c values) in the studied population.Keywords: cardiovascular disease, hyperferritinemia, iron overload syndrome, metabolic syndrome

Background Dyslipidemias are associated with atherosclerosis and cardiovascular diseases. Recently, non-high-density lipoprotein cholesterol (non-HDL-c) has emerged as a new target for assessment and prediction of risk of cardiovascular disease (CVD) and is closely associated with atheroma plaque progression. Objectives To evaluate associations between HDL-c and non-HDL-c levels and anthropometric and biochemical parameters and with the Castelli risk indexes I and II. Methods 300 randomly selected people were subdivided into two groups: patients with normal values for non-HDL-c and patients with altered values for non-HDL-c. These parameters were analyzed for associations with glycemia, total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL-c), Castelli Index I (CI-I), Castelli Index II (CI-II), waist circumference (WC), body mass index (BMI) and presence of metabolic syndrome (MS). Results Glycemia, TC, TG, LDL-c, CI-I, CI-II, WC and BMI were all significantly different between subjects with normal and altered values of HDL-c and non-HDL-c. TC and WC both exhibited significantly higher values among patients with abnormal non-HDL-c when compared to patients with abnormal HDL-c. A significant difference was observed in occurrence of MS among patients with altered values of HDL-c and non-HDL-c. Conclusions Our results show that both HDL-c and non-HDL-c are associated with insulin resistance, dyslipidemia, atherogenic indices, and obesity. There is therefore a need for randomized clinical intervention trials examining the potential role of non-HDL-c as a possible primary therapeutic target. Resumo Contexto A dislipidemia está associada à aterosclerose e às doenças cardiovasculares. Recentemente, a lipoproteína de não alta-densidade de colesterol (não HDL-c) emergiu como um novo alvo para avaliação da predição de risco de doença cardiovascular, intimamente associada à progressão da placa de ateroma. Objetivos Avaliar as associações de níveis de HDL-c e não HDL-c com parâmetros antropométricos e bioquímicos, bem como com índices de Castelli I e II (CI-I e CI-II). Métodos Trezentas pessoas selecionadas aleatoriamente foram divididas em dois grupos: pacientes com valores normais de não HDL-c e pacientes com valores alterados de não HDL-c. Esses parâmetros foram associados a glicemia, colesterol total (CT), triglicerídeos (TG), lipoproteína de baixa densidade (LDL-c), CI-I, CI-II, circunferência de cintura (CC), índice de massa corporal (IMC) e presença de síndrome metabólica (SM). Resultados Glicemia, CT, TG, LDL-c, CI-I, CI-II, CC e IMC exibiram valores significativamente maiores para o não HDL-c quando comparado ao HDL-c. Uma diferença significativa na ocorrência de SM foi encontrada em pacientes com valores alterados de HDL-c e não HDL-c. Conclusões Nossos resultados mostram que tanto o HDL-c quanto o não HDL-c estão associados a resistência à insulina, dislipidemia, índices de aterogênese e obesidade. Assim, há uma necessidade de futuros ensaios randomizados de intervenção clínica examinando o papel potencial do não HDL-c como possível alvo terapêutico primário.