Fatores determinantes da concentração de hepcidina sérica em pacientes com anemia falciforme sem sobrecarga de ferro

Abstract

Introduction: Sickle cell disease is a group of hematological genetic diseases, which leads to a mutation in the β-globin gene, in a new type of hemoglobin, hemoglobin S (HbS). The sickle-cell anemia (SCA; HbSS) genotype is the greatest severity form of the disease. The formation of hemoglobin polymers and structural changes in the red blood cells lead to chronic hemolysis and vaso-occlusive episodes.Hepcidin is the key hormone in the regulation of iron metabolism and acts to reduce iron absorption and bioavailability. Hemolysis, anemia, hypoxia, and increased erythropoiesis can reduce the transcription of the hepcidin gene, constituting a counter-regulatory mechanism to increase iron absorption. In contrast, situations of iron overload, inflammation and obesity, are able to increase the transcription of the hepcidin gene, which may lead to lower iron absorption. Studies have linked hepcidin to iron overload. However, most patients with SCA do not present iron overload. Objective: evaluate the predictive factors of plasma hepcidin concentration in individuals with SCA without iron overload. Methods: A database was analyzed with data collected between 2014 and 2016, composed of 101 adult participants (19-59 years old), divided into: group with non-iron overload (serum ferritin <1000 ng / mL) (n = 58); and control group without the disease (n = 43). Hemoglobin (Hb), red blood cells (RBC), hematocrit (Ht), total iron binding capacity (TIBC) and serum iron (Fe) were used as indicators of anemia / hypoxia; growth differentiation factor 15 (GDF-15) and reticulocytes as indicators of erythropoietic activity; lactate dehydrogenase (LDH) as an indicator of hemolysis; ferritin (Ft) and transferrin saturation index (TSI) as indicators of iron loading; interleukin-6 (IL-6) and leukocytes as indicators of inflammation; body mass index (BMI) as an indicator of obesity. To determine the relationship between the variables, multiple linear regression was performed by the backward method, considering hepcidin as a dependent variable. Results: The median serum hepcidin concentration was lower in the SCA group (4.2 ng / mL; Interquartile Interval, IQI: 2.20-7.77 ng / mL) when compared to the control group (7.2 ng / mL;IQI: 5.60-11.60 ng / mL). The determinant variables for serum hepcidin concentration in people with SCA were: Ft (p = 0.0001, β = 0.430), LDH (p = 0.0001, β = -0.634) and reticulocytes (p = 0.002, β = -0.351). For individuals without the disease, the determinants were: Ft (p = 0.018, β = 0.220) and Ht (p = 0.034, β = 1.976). When regression analysis was done with another cutoff for serum ferritin (> 300 ng / mL for males or> 200 ng / mL females), the determinants of hepcidin were: Ft (p = 0.0001, β = 0.457), reticulocytes (p = 0.0001, β = -0.410)and LDH ( p = 0.0001; β = -0.709) in the high ferritin subgroup. In the subgroup with normal serum ferritin, the determinants of hepcidin were:Ft (p = 0.0001, β = 0.458), reticulocytes(p = 0.001, β = -0.481) and LDH (p = 0.001; β = -0.659). Conclusion: Hemolysis seems to explain the lower concentration of serum hepcidin in individuals with SCA without iron overload. At the same time, indicators of iron status correlate with hepcidin concentrations, both in healthy people and people with SCA.