Abstract
Objective
To examine the impact of a body fat content on the concentration of a serum prohepcidin, iron metabolism parameters and inflammation markers in elderly patients with microcytic or normocytic anemia.
Design
Clinical study with biochemical and anthropometric measurements.
Subjects
Fifty two elderly patients (19 male, 33 female) with anemia, 65–91 years of age.
Measurements
Prohepcidin, ferritin, soluble transferrin receptor, erythropoietin and interleukin-6 were measured using commercially available ELISA kits. Iron, TIBC, transferrin, C-reactive protein and complete blood count were assayed using standard laboratory methods. Body fat content, fat distribution and protein nutrition state parameters were assessed by means of anthropometry.
Results
Mean serum prohepcidin levels were significantly higher in patients with high body fat content in comparison to patients with normal body fat content (224,85 vs 176,6 ng/ml). Prohepcidin levels of the elderly patients with anemia were positively correlated with biceps, subscapular and suprailiac skinfold thickness or body fat mass percentage. In our study serum prohepcidin levels do not correlate with any iron parameters or inflammation markers.
Conclusion
Summing up, the results of this study indicate that increased prohepcidin concentration, observed in obese elderly patients with anemia, may play an important role in iron deficiency development.
Key words: Prohepcidin, obesity, iron metabolism, anemia, elderly
Introduction
Anemia of the elderly is a common medical problem (1). Epidemiological studies have shown that the prevalence of anemia increases with age, with a marked increase after the age of 60 (2). According to NHANES III data, there are three general causes of anemia in the elderly. These are: 1) anemia due to blood loss or nutritional deficiencies, 2) anemia associated with chronic inflammation or chronic renal failure and 3) unexplained anemia (1).
The current knowledge provides substantial evidence in support of a close connection between being overweight or obesity, and iron metabolism disorders (3, 4, 5, 6, 7, 8, 9). According to some authors' opinions there are two different mechanisms of hypoferremia development observed in obese individuals. Firstly, the sideropenia is caused by inadequate levels of iron in the diet. It was noticed that the diet of obese people consists mainly of high carbohydrate and high in fat meals with a low INQ (Index of Nutritional Quality) value for iron (6, 9, 10, 11, 12, 13). Secondly, the hypoferremia could be a consequence of an increased pro-inflammatory cytokine and adipokine production by fatty tissue (3, 11-13). IL-6, leptin, and other inflammatory mediators' secretion to the circulation results in an increased hepcidin gene expression (4, 14). Hepcidin is a small, 25-amino acid peptide, proposed to be a key regulator of iron metabolism (15, 16, 17, 18, 19). Hepcidin is synthesized as an 84-amino acid pre-propeptide, predominantly in the liver by hepatocytes, as well as renal epithelial cells and several other types of tissue (16). Hepatic hepcidin expression is regulated by iron homeostasis, hypoxia and inflammatory stimuli (14, 18-19). According to published study, hepatic hepcidin expression is more responsive to changes in erythropoiesis or iron intake than to changes in body iron stores (20). Hepcidin regulates intestinal iron absorption and affects the release of iron from hepatic stores and macrophages (21, 22, 23). As a result, the increased production of hepcidin may cause iron deficiency (21, 22, 23, 24, 25, 26). The role of hepcidin was shown to be related to its regulation of the ferrous iron trans-membrane transporter, ferroportin (21). Circulating hepcidin appears to bind to ferroportin inducing receptor-ligand internalization and lysosomal degradation (21).
Newest researche by Bekri et al. (3) indicated that fatty tissue adipocytes are a direct source of hepcidin. The authors demonstrated for the first time that the hepcidin concentration and that hepcidin mRNA expression were increased in obese patients (3). There are only few clinical studies that indicate the association between obesity and iron homeostasis (27, 28, 29, 30, 31).
The aim of this study was to assess the impact of a body fat content on the concentration of a serum prohepcidin, iron metabolism parameters and inflammation markers in elderly patients with microcytic or normocytic anemia.
Methods
The study group consisted of 52 elderly patients (19 male, 33 female, between 65 to 91 years of age and a mean age of 78,38±8,39) with recognized de novo microcytic or normocytic anemia (WHO criteria) (32, 33). All the persons who had taken any vitamin and mineral supplements were excluded from the research.
Peripheral blood samples were taken after the diagnosis had been made, but prior to treatment being provided.
Prohepcidin concentration in the blood serum was determined by a stable ELISA (DRG Instruments GmbH, Germany). Serum ferritin was measured using DRG Ferritin kit (EIA-1872, DRG International, Inc., USA) and soluble transferrin receptor (sTfR) concentrations were examined by an enzyme-linked immunosorbent assay (sTfR ELISA, BioVendor Laboratory Medicine, Inc., Czech Republic). Serum erythropoietin was determined by the EPO ELISA kit (Roche Diagnostics GmbH, Mannheim, Germany). Interleukin-6 concentration in the serum was quantified by a commercial enzyme-linked immunosorbent assay (human IL-6, firma Bender MedSystem).
Iron and TIBC concentration was measured on Architect c8000 System (Abbott Laboratories, IL, USA). Transferrin and C-reactive protein concentration in the serum was determined using BNTMII Systems (Dade Behring). The complete blood count was analyzed in the routine diagnostic using Sysmex XE-2100.
Nutritional status was carried out on the basis of the measurements of body mass (kg), body height (cm), circumference (cm): arm, hip, waist, thickness of four skinfolds (mm), i.e. over biceps (BSF) and triceps (TSF), subscapular (SCSF) and suprailiac (SISF) (29, 30). The body mass measurement was carried out using a Radwag physician scale, with an electronic reading scale and a measurement accuracy of 0,01 kg. Body height was stated using a height-meter, and the skinfolds' thickness using a skinfold caliper produced by the Siber Hegner & Co. Ltd (measurement accuracy of 0,1 cm). Arm, hip and waist circumference were measured using a tape with a measurement accuracy of 0,1 cm. From these weight and height values, the body mass index (BMI, kg/m2) was assigned to each individual. The arm muscles' circumference (AMC, cm) were calculated according to the Frisancho formula (34). Fat-free body mass (FFM, kg), fat mass (FM, kg) and fat mass percentage in the body (%FM, %) were calculated on the basis of weight measurements and the sum of four skinfold's thickness, according to the Durnin and Wormsley formula (35, 36).
The values of somatic parameters were interpreted for each person individually according to sex with reference (37, 38). High body fat content (obesity) was defined as a fat mass percentage %FM=25% in men and =33% in women (37). Men with a %FM=17-25% and women with a %FM=22-33% were classified as representing normal body fat content.
All procedures in the study were approved by the Local Ethics Committee. Informed written consent was obtained after the purpose, nature, and potential risks were explained to the subjects.
All statistics were conducted using StatSoft STATISTICA software, version 6.0. The normal distribution of the variables was evaluated using the W-Shapiro-Wilk test. Parametric data was expressed as mean, standard deviation, minimum and maximum. Non-parametric parameters were presented by median and percentile values. An independent sample t test for parametric continuous variables and the Mann Whitney U test for non-parametric continuous variables were used to compare the difference between the two subject groups. Correlations were tested with the Spearman rank correlation test. A value of p<0,05 was considered statistically significant.
Results
A total of 19 elderly men with anemia and 33 elderly women with anemia were studied. Overall, women were found to have higher mean values of triceps skinfold thickness and fat mass percentage then men (table 1). As expected, men in comparison to women had higher body mass, arm muscle circumference and waist hip ratio (table 1). The mean values of BMI, BSF, SCSF, SISF and FM were similar in elderly patients with anemia of both sexes. Moreover, there were no significant differences in levels of hematological and biochemical parameters between men and women (table 2).
Table 1.
Anthropometrical parameters in elderly men and women
| Parameter | Men (N=19) | Women (N=33) | p | ||
|---|---|---|---|---|---|
| x±SD | min – max | x±SD | min - max | ||
| Body mass (kg) | 77,48±13,02 | 62,80-103,30 | 67,84±12,89 | 49,70-107,00 | 0,0126 |
| BMI (kg/m2) | 27,68±4,34 | 22,49-37,49 | 28,19±5,60 | 21,25-45,71 | NS |
| AMC (cm) | 23,44±1,88 | 20,89-27,42 | 21,61±2,55 | 15,68-26,93 | 0,0088 |
| WHR | 0,98±0,06 | 0,88-1,08 | 0,90±0,08 | 0,74-1,10 | 0,0013 |
| BSF (mm) | 10,57±6,01 | 3,80-24,40 | 12,77±6,92 | 5,60-38,80 | NS |
| TSF (mm) | 14,27±7,46 | 5,40-32,20 | 19,28±6,76 | 4,20-33,00 | 0,0167 |
| SCSF (mm) | 20,19±7,55 | 10,30-35,20 | 18,14±7,57 | 6,60-41,40 | NS |
| SISF (mm) | 14,96±8,19 | 5,20-32,20 | 17,77±9,31 | 3,80-38,00 | NS |
| FM (kg) | 22,36±8,66 | 11,04-40,32 | 25,10±7,63 | 12,64-47,34 | NS |
| FFM (kg) | 55,12±5,49 | 46,81-65,13 | 42,74±6,42 | 32,42-59,66 | <0,0001 |
| %FM (%) | 28,00±6,57 | 17,58-39,03 | 36,40±5,33 | 25,43-44,78 | <0,0001 |
BMI – body mass index, AMC - arm muscle circumference, WHR - waist hip ratio, BSF – biceps skinfold, TSF – triceps skinfold, SCSF – subscapular skinfold, SISF- suprailiac skinfold, FM - fat mass in the body, FFM - fat-free body mass, %FM - fat mass percentage, N - sample size, x – mean value, SD – standard deviation, p - significance level, NS -differences not significant statistically.
Table 2.
Hematological and biochemical parameters in elderly men and women
| Parameter | Men (N=19) | Women (N=33) | p | ||
|---|---|---|---|---|---|
| x±SD Me | min – max Q1; Q3 | x±SD | min - max | ||
| HGB (g/dl) | 10,72±1,82 | 7,10-12,90 | 10,37±1,49 | 7,00-12,00 | NS |
| HCT (%) | 33,83±5,59 | 20,90-41,40 | 32,90±4,78 | 21,50-41,70 | NS |
| MCV (fl) | 89,58±8,14 | 68,70-99,70 | 89,25±7,33 | 69,90-109,10 | NS |
| RBC · 106/_l | 3,79±0,63 | 2,23-5,19 | 3,69±0,66 | 1,97-5,21 | NS |
| WBC · 103/_l | 7,69±2,74 | 2,79-14,24 | 8,37±3,19 | 2,90-14,96 | NS |
| Prohepcidin (ng/ml) | 231,10 | 197,9; 241,7 | 198,39 | 161,0; 230,6 | NS |
| Iron (μg/dl) | 33,00 | 20,00; 58,00 | 31,80 | 21,00; 62,80 | NS |
| sTfR (μg/ml) | 1,64 | 0,47; 5,13 | 1,91 | 0,52; 2,79 | NS |
| Transferrin (g/l) | 2,13 | 1,62; 2,57 | 2,11 | 1,68; 2,22 | NS |
| TIBC (μ/dl) | 254,10 | 179,6; 289,5 | 227,20 | 194,7; 265,4 | NS |
| Ferritin (ng/ml) | 52,87 | 19,99; 77,90 | 67,71 | 14,16; 154,28 | NS |
| EPO (U/l) | 7,71 | 5,62; 11,39 | 8,37 | 5,45; 15,91 | NS |
| CRP (mg/l) | 8,10 | 4,85; 21,10 | 18,20 | 7,63; 51,10 | NS |
| IL-6 (pg/ml) | 2,38 | 0,34; 4,32 | 2,47 | 0,34; 12,77 | NS |
HGB – hemoglobin, HCT – hematocrit, MCV - mean corpuscular volume, RBC – erythrocyte count, WBC – leukocyte count, sTfR – soluble transferrin receptor, TIBC -total iron-binding capacity, EPO – erythropoietin, CRP – C-reactive protein, IL-6 – interleukin-6, N - sample size, x – mean value, SD – standard deviation, Me – median, Q1 and Q3 – 25th and 75th percentiles, p - significance level, NS - differences not significant statistically
High body fat content was observed in 36 (69,2%) elderly patients with anemia and normal body fat content was observed in 16 (30,8%) elderly patients with anemia. As expected, obese patients in comparison to the patient with normal body fat content had significantly higher values of the following parameters: body mass, body mass index, waist-hip index, BSF, TSF, SCSF, SISF and body fat mass (table 3). However, protein nutrition status parameters (AMC, FFM) were similar across all subjects, independent of body fat percentage (table 3).
Table 3.
Anthropometrical parameters of subjects with normal body fat content compared to subjects with high body fat content
| Parameter | Body fat content∗ | p | |||||
|---|---|---|---|---|---|---|---|
| All subjects (N=52) | Normal (N=16) | High (N=36) | |||||
| x±SD | min - max | x±SD | min - max | x±SD | min - max | ||
| Body mass (kg) | 71,36±13,64 | 49,70-107,00 | 64,04±7,51 | 49,70-79,00 | 74,62±14,55 | 50,40-107,0 | 0,0042 |
| BMI (kg/m2) | 28,01±5,14 | 21,25-45,71 | 24,63±1,66 | 22,49-28,33 | 29,51±5,46 | 21,25-45,71 | <0,0001 |
| AMC (cm) | 22,27±2,47 | 15,68-27,42 | 21,93±2,08 | 18,97-27,42 | 22,43±2,64 | 15,68-26,93 | NS |
| WHR | 0,93±0,08 | 0,74-1,10 | 1,55±0,52 | 0,74-1,08 | 1,88±0,33 | 0,79-1,10 | 0,0034 |
| BSF (mm) | 11,97±6,63 | 3,80-38,80 | 6,70±1,99 | 3,80-10,20 | 14,31±6,63 | 6,40-38,80 | <0,0001 |
| TSF (mm) | 17,45±7,37 | 4,20-33,00 | 10,38±3,71 | 4,20-17,60 | 20,39±6,65 | 6,90-33,00 | <0,0001 |
| SCSF (mm) | 18,98±7,65 | 6,60-44,40 | 12,01±2,25 | 7,60-15,80 | 21,95±7,05 | 6,60-41,40 | <0,0001 |
| SISF (mm) | 16,74±8,94 | 3,80-38,80 | 8,82±2,75 | 3,80-13,50 | 20,26±8,47 | 6,80-38,80 | <0,0001 |
| FM (kg) | 24,10±8,05 | 11,04-47,34 | 17,01±4,21 | 11,04-25,51 | 27,25±7,33 | 17,29-47,34 | <0,0001 |
| FFM (kg) | 47,26±8,53 | 32,42-65,13 | 47,02±6,73 | 35,38-58,28 | 47,37±9,31 | 32,42-65,13 | NS |
body fat content was defined as normal: men =17-25% FM, women =22-33%FM, high: men =25%FM, women =33%FM; BMI – body mass index, AMC - arm muscle circumference, WHR - waist hip ratio, BSF – biceps skinfold, TSF – triceps skinfold, SCSF – subscapular skinfold, SISF- suprailiac skinfold, FM - fat mass in the body, FFM - fat-free body mass, %FM - fat mass percentage, N - sample size, x – mean value, SD – standard deviation, p - significance level, NS - differences not significant statistically.
As shown in table 4 complete blood cell count did not differ significantly between elderly patients with high or normal body fat content.
Table 4.
Hematological indices of subjects with normal body fat content compared to subjects with high body body fat content
| Parameter | Body fat content∗ | p | |||||
|---|---|---|---|---|---|---|---|
| All subjects (N=52) | Normal (N=16) | High (N=36) | |||||
| x±SD | min - max | x±SD | min – max | x±SD | min - max | ||
| HGB (g/dl) | 10,49±1,61 | 7,00-12,90 | 9,78±1,68 | 7,00-12,00 | 10,81±1,49 | 7,10-12,90 | NS |
| HCT (%) | 33,24±5,06 | 20,90-41,70 | 31,10±5,11 | 21,50-38,60 | 34,19±4,80 | 20,90-41,70 | NS |
| MCV (fl) | 89,38±7,56 | 68,70-109,1 | 89,01±10,33 | 68,70-109,1 | 89,54±6,12 | 77,90-100,0 | NS |
| RBC · 106/μl | 3,72±0,64 | 1,97-5,21 | 3,47±0,65 | 1,97-4,36 | 3,84±0,61 | 2,23-5,21 | NS |
| WBC · 103/μl | 8,12±3,03 | 2,79-14,96 | 8,54±3,44 | 2,90-14,24 | 7,93±2,86 | 2,79-14,96 | NS |
body fat content was defined as normal: men =17-25% FM, women =22-33%FM, high: men =25%FM, women =33%FM; HGB – hemoglobin, HCT – hematocrit, MCV - mean corpuscular volume, RBC – erythrocyte count, WBC – leukocyte count, N - sample size, x – mean value, SD – standard deviation, p - significance level, NS - differences not significant statistically.
The studies showed that patients with high body fat content had significantly higher prohepcidin levels compared to the subjects with normal body fat content (224,85 vs 176,6 ng/ml) despite similar parameters of iron status including: serum iron, sTfR, transferrin, TIBC, ferritin and erythropoietin (table 5). In addition, measurements of inflammation status (CRP and IL-6) were also similar (p> 0,05) between both groups (table 5).
Table 5.
Prohepcidin, iron status parameters and inflammation markers of subjects with normal body fat content compared to subjects with high body fat content
| Parameter | Body fat content∗ | p | |||||
|---|---|---|---|---|---|---|---|
| All subjects (N=52) | Normal (N=16) | High (N=36) | |||||
| Me | Q1; Q3 | Me | Q1; Q3 | Me | Q1; Q3 | ||
| Prohepcidin (ng/ml) | 213,32 | 176,6; 239,4 | 185,07 | 160,8; 222,2 | 224,85 | 188,7; 240,4 | 0,0490 |
| Iron (μg/dl) | 32,55 | 20,50; 62,70 | 22,65 | 17,55; 68,25 | 35,00 | 22,25; 62,70 | NS |
| sTfR (μg/ml) | 1,86 | 0,50; 3,18 | 2,35 | 1,48; 5,03 | 1,54 | 0,47; 2,67 | NS |
| Transferrin (g/l) | 2,11 | 1,62; 2,43 | 2,13 | 1,48; 2,80 | 2,08 | 1,72; 2,36 | NS |
| TIBC (μg/dl) | 230,0 | 184,0; 275,3 | 229,35 | 171,4; 275,2 | 241,21 | 197,0; 277,6 | NS |
| Ferritin (ng/ml) | 61,16 | 19,60; 133,4 | 69,34 | 13,18; 92,47 | 57,48 | 19,60; 134,6 | NS |
| EPO (U/l) | 8,37 | 5,53; 14,49 | 8,28 | 5,89; 24,95 | 8,95 | 5,36; 13,87 | NS |
| CRP (mg/l) | 10,85 | 6,50; 43,50 | 21,20 | 10,60; 51,10 | 8,85 | 5,50; 41,90 | NS |
| IL-6 (pg/ml) | 2,38 | 0,34; 7,26 | 3,71 | 2,04; 13,80 | 1,43 | 0,00; 8,69 | NS |
body fat content was defined as normal: men =17-25% FM, women =22-33%FM, high: men =25%FM, women =33%FM; sTfR – soluble transferrin receptor, TIBC - total iron-binding capacity, EPO – erythropoietin, CRP – C-reactive protein, IL-6 – interleukin-6, N - sample size, Me – median, Q1 and Q3 – 25th and 75th percentiles, p - significance level, NS -differences not significant statistically
Correlations between serum prohepcidin and anthropometric parameters are presented in table 6. When all elderly patients with anemia were examined, serum prohepcidin was positively correlated with biceps skinfold thickness (r = 0,27; p = 0,0486), subscapular skinfold thickness (r = 0,32; p = 0,0244), suprailiac skinfold thickness (r = 0,26; p = 0,0370) and percentage of fat mass (r = 0,37; p = 0,0182). When the elderly women with anemia were assessed separately, prohepcidin was not correlated with any anthropometric parameters. Among the elderly men with anemia, we observed statistically significant positive correlations between serum prohepcidin and BSF (r = 0,47; p = 0,0223), TSF (r = 046; p = 0,0281), SCSF (r = 0,52; p = 0,0112), FM (r = 0,42; p = 0,0449) and %FM (r = 0,46; p = 0,0268).
Table 6.
Spearman correlations of serum prohepcidin with anthropometrical parameters in all subjects and separately by group (normal fattening/high fattening)
| Parameter | Body fat content∗ | |||||
|---|---|---|---|---|---|---|
| All subjects (N=52) | Men(N=16) | Women (N=33) | ||||
| R | P | R | P | R | P | |
| Body mass (kg) | 0,17 | NS | 0,18 | NS | 0,11 | NS |
| BMI (kg/m2) | 0,21 | NS | 0,22 | NS | 0,24 | NS |
| AMC (cm) | 0,29 | NS | 0,33 | NS | 0,03 | NS |
| BSF (mm) | 0,27 | 0,0486 | 0,47 | 0,0223 | 0,20 | NS |
| TSF | 0,10 | NS | 0,46 | 0,0281 | 0,26 | NS |
| SCSF (mm) | 0,32 | 0,0244 | 0,52 | 0,0112 | 0,30 | NS |
| SISF (mm) | 0,26 | 0,0370 | 0,39 | NS | 0,33 | NS |
| FM | 0,14 | NS | 0,42 | 0,0449 | 0,20 | NS |
| FFM | 0,09 | NS | -0,25 | NS | -0,17 | NS |
| %FM (%) | 0,37 | 0,0182 | 0,46 | 0,0268 | 0,34 | NS |
body fat content was defined as normal: men =17-25% FM, women =22-33%FM, high: men =25%FM, women =33%FM; BMI – body mass index, AMC - arm muscle circumference, WHR - waist hip ratio, BSF – biceps skinfold, TSF – triceps skinfold, SCSF – subscapular skinfold, SISF- suprailiac skinfold, FM - fat mass in the body, FFM - fat-free body mass, %FM - fat mass percentage, Spearman R, p - significance level, NS - differences not significant statistically
In our study serum prohepcidin levels do not correlate with any iron parameters or inflammation markers.
Discussion
In the present study we investigated serum prohepcidin concentration in obese elderly patients with normocytic or microcytic anemia. We have demonstrated that prohepcidin concentration was significantly increased in patients with high body fat content in comparison to patients with normal body fat content. Our findings are in agreement with other up-to-date studies in obese children (30, 31) and in obese premenopausal women (28). The results suggest that body fat content has an impact on prohepcidin concentration and thereby also on iron homeostasis. A viable argument in support of this thesis is statistically significant positive correlations between prohepcidin and anthropometric parameters reflecting the fatty tissue's state, such as: biceps, subscapular and suprailiac skinfold thickness or body fat mass percentage. An impact of obesity on prohepcidin level was observed for the first time by Lainé et al. (27), who reported that, in C282Y homozygotes women (classical haemochromatosis), high body mass was commonly associated with a lack of phenotypic expression of the disease, defined as a transferrin saturation ratio <35%. Based on these results, it was suggested that fatty tissue can affect the iron homeostasis (27). This hypothesis had been proven through research conducted by Bekri et al. (3) on the in vitro human adipocytes culture. Authors of this experiment discovered that hepcidin is a pro-inflammatory adipokine of significant importance in the development of iron deficiency in obese patients. They observed an increase of hepcidin mRNA level as well as the increase of hepcidin concentration in fatty tissue (3). Additionally, the mRNA expression was noted to positively correlate with IL-6 and C-reactive protein concentrations (3). A complementary study was performed by Chung et al. (4), which demonstrated that a line of human liver cancer cells (HuH7) treated with leptin, resulted in the increase of hepcidin gene expression depending on both exposition time and the leptin dosage. Leptin, a hormone secreted by white fatty tissue adipocytes, impacted on the hepcidin mRNA level by means of Ob-Rb receptor connected with the JAK/STAT cell signaling pathway (4). This idea has been confirmed in a clinical study in a group of 60 obese children (30). Authors of this study observed statistically significant correlation between hepcidin and leptin levels (r2 = 0.27; p = 0.006) and speculated that leptin can play an important role in stimulating hepcidin secretion in the obese patients (30).
According to up-to-date research, the main factors regulating hepcidin expression in the liver are the stimuli signalizing increased erythropoiesis i.e. hypoxia, low transferrin saturation (14, 18, 19, 38). A crucial problematic factor in the research is whether the regulatory mechanism occurs in all cells involved in hepcidin production including adipocytes, or if it is limited solely to hepatocytes. Bekri et al. (3) established the lack of a positive feedback mechanism within fat tissue which controls hepcidin secretion as a reaction to a low transferrin saturation. This mechanism was only observed in liver cells colonies (3). On the other hand, the lack of a restraining impact of hypoxia on hepcidin expression in cardiomyocytes was observed by Merle et al. (39), in the in vivo research in rat hearts. It was also noticed that hypoxia resulted in a significant increase of hepcidin mRNA levels as well as a concentration of hepcidin in the cardiac muscle (39). On the other hand, the liver hepcidin expression decreased as a reaction to hypoxia (39). All the results suggest that factors connected to anemia, such as tissue hypoxia and a decrease of transferrin saturation, have a negative effect on hepcidin production only in the hepatocytes. As a result, we can surmise that regulation of hepcidin gene expression is possibly tissue specific. It is well known that hepcidin expression is more than 100-fold higher in hepatocytes than in adipocytes (16). However, when adipose tissue mass is significantly increased, 'adipose tissue-derived pool of hepcidin' becomes relevant. This observation may have important clinical implications, i.e. obesity accompanied with anemia can result in a negative impact on the course of the latter disease, as well as on effectiveness of pharmaceutical oral iron treatment.
In the present work, we examined also the impact of inflammation status on prohepcidin levels in obese elderly patients with anemia. However, we did not observe any correlations between serum prohepcidin and IL-6 as well as CRP. These findings are in agreement with other data (28) and support the theory, that hepcidin may be regulated by other adipokines, including leptin or lipocalcin-2, commonly elevated in obesity (4, 29, 30).
Moreover, in our study prohepcidin did not correlate with any of iron metabolism parameters. Our findings seem to agree with recent study, which indicate that hepcidin levels were not correlated with iron status parameters in obese premenopausal women (28). These results suggest that prohepcidin detected in obese subjects, is derived, in most part, from the fatty tissue and thus, is not regulated by the iron parameters and inflammation markers.
A potential limitation of our pilot study is the fact that we have measured a prohormone (prohepcidin) of an active, mature peptide (hepcidin). However, no ELISA kit for clinical determination of plasma hepcidin was commercially available at the time this study was conducted. Further studies, assessing serum mature 25aa hepcidin levels are required in order to clarify the relative impact of fatty tissue on circulating hepcidin concentrations. In addition, future studies should be conducted on comparatively larger populations of elderly anemic and non-anemic subjects.
Conclusion
Summing up, the results of this study indicate that increased prohepcidin concentration, observed in obese elderly patients with anemia, may play an important role in iron deficiency development. In conclusion, this preliminary study is the first clinical report relating to serum prohepcidin concentrations in elderly patients with anemia.
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