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Abstract

Objective

This study aimed to investigate the effects of hypoxia-inducible factor-1α (HIF-1α), hypoxia-inducible factor-2α (HIF-2α), and erythroferrone (ERFE) on hepcidin in patients with chronic kidney disease (CKD) stages 3–5 and renal anemia.

Methods

A total of 90 patients with CKD stages 3–5 and renal anemia were selected for the study at the Nephrology Department of Fujian Provincial People’s Hospital and divided into three groups, according to CKD stage, while another 30 healthy subjects who underwent a physical examination at the hospital during the same period were selected as the normal group. The serum levels of hepcidin, HIF-1α, HIF-2α, ERFE, and furin were measured using an avidin biotin peroxidase complex enzyme-linked immunosorbent assay to compare the differences between the groups in the related indicators.

Results

① Serum HIF-2α, HIF-1α, ERFE, and furin levels increased gradually in the patients with CKD stages 3–5 (p < 0.05, p < 0.01). ②Simple correlation analysis:Serum hepcidin was positively correlated with HIF-2α, ERFE, and HIF-1α in the CKD patients (p < 0.01). ③Serum hepcidin was positively correlated with HIF-2α, HIF-1α, and ERFE in the CKD patients injected with erythropoietin (EPO) (p < 0.01), while serum hepcidin was positively correlated with HIF-2α and HIF-1α (p < 0.01) in the patients not injected with EPO. ④ Multivariate linear regression analysis showed that HIF-1α, (β = 4.36, p < 0.01), serum ferritin(SF) (β = 0.13, p < 0.01), and HIF-2α (β = 0.66, p < 0.01) were significantly correlated with hepcidin.

Conclusion

HIF-1α, HIF-2α, and SF are factors which have an effect on hepcidin in patients with CKD stages 3–5 and renal anemia. The increase of HIF-1α, HIF-2α, and ERFE does not seem to inhibit the increase of hepcidin.

Keywords

Renal anemia hepcidin HIF-1α HIF-2α erythroferrone

Introduction

Hypoxia-inducible factor (HIF) is a transcription factor for cellular adaptation to hypoxic conditions, and, in recent years, the determination of serum HIF has been increasingly used in clinical disease prediction and assessment.^1,2 The production of erythropoietin (EPO) and the absorption and utilization of iron can indirectly down-regulate hepcidin.³ Erythroferrone (ERFE) is a newly discovered erythroid regulator for iron metabolism, and EPO can stimulate the production of ERFE, thereby promoting the production of erythrocytes and inhibiting the synthesis of hepcidin by hepatocytes.⁴ Hirokazu et al.⁵ found that ERFE levels were elevated and negatively correlated with hepcidin in patients undergoing hemodialysis, while Hanudel et al.⁶ found that neither hemodialysis nor ERFE in patients diagnosed with CKD was correlated with hepcidin. These conflicting results may be attributed to renal function, demographics with different iron status, different inflammatory status, or sample size.

For patients with CKD and renal anemia, due to a progressive increase in hepcidin, a decrease in serum iron, and a decrease in EPO production, the degree of anemia is more severe, resulting in hypoxia, and the progressive increase of HIF and ERFE expressions inhibits an increase in hepcidin.^5,7 Although HIF cannot directly regulate ERFE,⁴ HIF can indirectly alter ERFE by regulating EPO. This study aims to explore whether various influencing factors in the HIF pathway of iron metabolism in patients diagnosed with CKD may inhibit hepcidin levels.

Patients and Methods

This is a cross-sectional study with a small sample size conducted at a single center in a real-world clinical setting. Patients with CKD stages 3–5 and renal anemia, according to the diagnostic criteria found in the 2012 United States National Kidney Foundation Kidney Disease Outcomes Quality Initiative Clinical Practice Guidelines for Chronic Renal Failure, were included in this study.⁸ The exclusion criteria were as follows: patients on hemodialysis; patients with an infection, surgery, or a tumor within one month of the study; patients with CKD caused by systemic lupus erythematosus, Sjögren’s syndrome, or other connective tissue diseases; patients with acute renal failure; and patients adapting to anti-inflammatory drugs and antioxidants.

Between March 2019 and December 2019, a total of 30 healthy volunteers were selected as the control group and underwent a detailed physical examination, including routine blood, urine, and stool tests, a biochemical panel, an electrocardiogram, an anteroposterior chest radiography, and a B ultrasound, to ensure a comprehensive assessment and the exclusion of any lesions in the heart, brain, liver, kidney, lung, and endocrine systems.

Between March 2018 and December 2019, 90 patients were randomly selected for the study from the Nephrology Department of Fujian Provincial People’s Hospital (the absence of a sample size estimation is one of the limitations of this study). The general clinical data are shown in Table 1. There were 46 males and 44 females, aged 25–86 years (mean 60.82 ± 16.08 years). Among them, there were 41 patients with chronic glomerulonephritis, 25 patients with diabetic nephropathy, 14 patients with hypertensive nephropathy, 4 patients with hyperuricemic nephropathy, and 6 patients with immunoglobulin A nephropathy. The healthy control group consisted of 14 males and 16 females, aged 50–87 years (mean 60.93 ± 6.38 years). There was no statistical difference in gender and age between the two groups (p > 0.05).

Table 1.

Baseline characteristics in healthy group vs. patients with CKD stages 3–5.

	Normal	Stage 3 CKD	Stage 4CKD	Stage 5CKD
N	30	30	30	30
Age , year	60.93±6.38	62.00 ( 48.00 , 67.00 )	65.00 ( 56.25 , 73.00 )	64.70±13.67
Gender ( male/female )	14/16	13/17	16/14	17/13
EPO(Yes/No)	/	14/16	21/9	26/4
Iron sucrose (Yes/No)	/	3/27	2/28	7/23
BUN (mmol/L)	4.75 ± 0.99	8.60 ± 2.55^a	15.48 ± 4.47^ac	25.29 ± 8.13^ace
SCr (µmol/L)	61.55 ± 10.69	144.98 ± 32.67^a	245.01 ± 45.78^ac	411.98 ± 56.99^ace
eGFR (ml/min/1.73 m²)	108.90 ± 23.65	43.58 ± 9.41^a	22.80 ± 4.53^ac	11.38 ± 0.92^ace
hsCRP ( mg/L )	1.53 ± 0.74	3.06 ± 1.24^a	5.48 ± 2.24^ac	9.04 ± 2.12^ace
RBC (10¹²/L)	4.62 ± 0.43	3.51 ± 0.38^a	3.30 ± 0.46^ab	2.89 ± 0.34^ace
Hb (g/L)	138.37 ± 7.49	100.27 ± 6.11^a	91.63 ± 11.10^ac	85.40 ± 11.97^acd
HCT (I/L)	0.41 ± 0.04	0.30 ± 0.02^a	0.28 ± 0.03^ac	0.26 ± 0.04^acd
Fe³⁺(umol/L)	19.34 ± 3.96	11.56 ± 2.76^a	9.13 ± 2.64^ac	7.82 ± 2.05^ac
SF (ug/L)	93.88 ± 10.81	144.40 ± 16.62^a	186.95 ± 52.01^ac	236.50 ± 79.60^acd
TSAT ( % )	31.56 ± 6.05	17.02 ± 1.84^a	12.70 ± 2.19^ac	10.80 ± 1.57^acd
furin ( pg/mL )	247.34 ± 89.14	489.14 ± 108.16^a	682.68 ± 162.95^ac	1033.24 ± 304.89^ac
Hepcidin (ng/mL)	45.59 ± 13.99	55.41 ± 15.61	93.48 ± 14.00^ac	158.59 ± 29.58^ace
HIF-2α (ng/mL)	29.78 ± 6.23	36.96 ± 6.76^a	42.03 ± 7.40^ac	50.14 ± 9.09^ace
HIF-1α (ng/mL)	12.69 ± 1.69	21.28 ± 2.72^a	30.31 ± 2.11^ac	39.92 ± 2.94^acd
ERFE ( ng/mL)	13.10 ± 4.55	16.47 ± 3.44^a	18.80 ± 3.96^ab	21.54 ± 4.52^acd

EPO=erythropoietin; BUN=blood urea nitrogen; SCr=serum creatinine; eGFR=estimated glomerular filtration rate ; hsCRP=high sensitivity C-reactive protein; RBC=red blood cell; Hb=hemoglobin; HCT= hematocrit; Fe³⁺=Serum iron; SF=serum ferritin; TSAT=transferrin saturation; HIF-2α= hypoxia-inducible factor 2α; HIF-1α=hypoxia-inducible factor-1α; ERFE=Erythroferrone.

Compared with the normal group: ^ap<0.01; Compared with CKD stage 3: ^bp<0.05, ^cp <0.01; Compared with CKD stage 4: ^dp<0.05, ^ep<0.01.

All the patients with CKD received conventional treatment before and after enrollment; the general treatment included the correction of water and electrolyte acid–base disorders and a high-quality low-protein diet with a high-calorie intake, supplemented with compound α-Ketoacid tablets, four tablets/three times a day (tid) (Beijing Fresenius Kabi Pharmaceutical Co., Ltd., H20041442) and oral alfacalcidol, 0.5 µg/day (Kunming Baker Norton Pharmaceutical Co., Ltd., J20171090) to regulate calcium and phosphate metabolism. In addition to the general treatment, the patients with hypertensive nephropathy received antihypertensive drugs to maintain their blood pressure within 140–160 mmHg. The patients with serum creatinine (SCr) <265 µmol/L were given the following antihypertensive drugs: angiotensin-converting enzyme inhibitors, namely, perindopril tert-butylamine tablets, 4 mg every day (qd) (Servier [Tianjin] Pharmaceutical Co., Ltd., H20034053) or angiotensin receptor blockers, namely, candesartan cilexetil tablets, 4 mg qd (Takeda Pharmaceutical Company Limited, Osaka Plant, J20110011), while the patients with SCr >265 µmol/L were given calcium channel blocker antihypertensive drugs, namely, nifedipine controlled-release tablets, 30–60 mg qd (Bayer AG, J20130115). Patients with high serum phosphorus (P³⁺) were given calcium-containing phosphorus binders; patients with a serum calcium <2.40 mmol/L were administered calcium acetate, 2–4 0.667 g/tablets/tid (Guizhou Weikang Zifan Pharmaceutical Co., Ltd., H20103772); and those with high P³⁺, hypercalcemia, and a serum calcium >2.40 mmol/L were provided with non-calcium-containing phosphorus binders, namely, sevelamer carbonate tablets (Genzyme Europe B.V, J20130160). Patients with diabetic nephropathy were treated with hypoglycemic agents and insulin to maintain hemoglobin (Hb)A1c at 7%–8%. The anemia treatment was as follows: iron therapy, consisting of an iron sucrose injection (Nanjing Hencer Pharmaceutical Co., Ltd., H20046043) 100 mg/three times a week, was used when transferrin saturation was ≤20% or/and ferritin was ≤200 μg/L, and the target of ferritin was controlled at 200–400 μg/L. The EPO treatment, comprising a recombinant human erythropoietin injection (Harbin Pharmaceutical Group Bioengineering Co., Ltd., S20050090) 10,000 U/week subcutaneously, was started with an Hb <100 g/L or a hematocrit (HCT) <33%. The Hb target was controlled at 110–130 g/L. Blood samples were taken from the subjects for testing after two weeks of iron and EPO treatment.

With regard to the measurement indicators, blood samples were collected from the antecubital vein after 10 hours of overnight fasting. These blood samples were centrifuged at 3,000 rpm for 10 minutes within 30 minutes or stored in a −80°C refrigerator if not tested in time after the sample collection. ①Hepcidin, HIF-1α, HIF-2α, and ERFE levels were uniformly detected using avidin biotin peroxidase complex enzyme-linked immunosorbent assay (ELISA), using hepcidin, HIF-1α, HIF-2α, and furin ELISA kits (batch Nos.: MB-19123007, MB-19123033, MB-19123015, and MB-19123006, Jiangsu Meibiao Biotechnology Co., Ltd.). With respect to accuracy, the correlation coefficient R, between the standard linear regression and the expected concentration, was ≥0.9900, and in terms of sensitivity, the minimal concentration of detection was less than 1.0 pg/mL. With respect to the ERFE ELISA kit (batch No.: MB-19123030), the accuracy was R ≥ 0.9900, and, for sensitivity, the minimal concentration of detection was less than 0.1 ng/mL. When measured, the intra-plate and inter-plate coefficients of variation were less than 15%. ②The Hb, red blood cell counts, and HCT were measured using a Beckman Coulter hematology analyzer; ③the SCr, blood urea nitrogen (BUN), and other biochemical indicators were measured using a Beckman-C800 biochemical analyzer (United States); ④serum iron was detected using a BH5300 serum multi-element analyzer (Beijing Bohui Innovation Biotechnology), and serum ferritin was determined using immunoradiometric assay. The glomerular filtration rate (eGFR) was calculated from the SCr concentration according to age and gender.

Statistical Analysis

The statistical calculations were performed using SPSS 20.0 software, and the measurement data that conformed to the normal distribution were expressed as the mean ± standard deviation ( $\bar{x}$ ± s). The measurement data that were not normally distributed were expressed as the median and quartile. For the comparison of multiple indicators in the same group, the measurement data conforming to the normal distribution were tested for homogeneity of variance; the homogeneity of variance was tested using Fisher’s least significant difference test, and the heterogeneity of variance was tested using the Games–Howell test. A multivariate rank–sum test was selected for the non-normal distribution data. For the correlation analysis, a linear correlation Spearman’s test was used for the analysis of the normal distribution. Enumeration data were subjected to a Chi-square test with an R × C table.

Results

The serum indicators of the healthy group and the patients with CKD stages 3–5 are presented in Table 1.

Comparison of erythropoietin and iron therapy in patients with chronic kidney disease stages 3–5

Hepcidin, HIF-2α, ERFE, and HIF-1α levels were higher in the patients who had been given EPO (p < 0.01), whereas the levels in those who received iron showed little change (p > 0.05). See Table 2 and Table 3 for details.

Table 2.

Comparison between Groups with or without EPO in terms of indicators.

	YES	NO	F	p
N	61	29
Hepcidin (ng/mL)	113.75 ± 46.61	78.81 ± 41.02	2.24	<0.01
HIF-2α (ng/mL)	45.21 ± 8.84	38.49 ± 9.24	0.08	<0.01
ERFE ( ng/mL)	20.67 ± 4.12	15.30 ± 2.62	4.55	<0.01
HIF-1α (ng/mL)	32.61 ± 2.62	26.84 ± 7.46	0.04	<0.01

EPO=erythropoietin; HIF-2α= hypoxia-inducible factor 2α; ERFE=Erythroferrone.

HIF-1α=hypoxia-inducible factor-1α.

Table 3.

Comparison between groups with or without Iron in terms of indicators.

	YES	NO	F	p
N	12	78
Hepcidin (ng/mL)	111.66 ± 53.69	101.08 ± 46.79	1.23	0.48
HIF-2α (ng/mL)	45.76 ± 12.36	42.62 ± 8.96	1.44	0.29
ERFE ( ng/mL)	19.57 ± 4.93	18.84 ± 4.42	0.60	0.60
HIF-1α (ng/mL)	30.93 ± 8.20	30.64 ± 7.88	0.32	0.91

HIF-2α= hypoxia-inducible factor 2α, ERFE=Erythroferrone.

HIF-1α=hypoxia-inducible factor-1α.

Analysis of the correlation between serum hepcidin and each indicator

Serum hepcidin was positively correlated with BUN, SCr, hsCRP, SF, HIF-2α, ERFE, and HIF-1α (p < 0.01) and negatively correlated with eGFR, RBC, Hb, HCT, Fe³⁺, and TSAT (p < 0.01) in the CKD patients. See Table 4 for details.

Table 4.

Analysis on correlation between Hepcidin and each indicator.

	Hepcidin
	R	p
SCr	0.871	<0.01
BUN	0.760	<0.01
eGFR	−0.848	<0.01
hsCRP	0.710	<0.01
Hb	−0.51	<0.01
RBC	−0.573	<0.01
HCT	−0.552	<0.01
Fe³⁺	−0.471	<0.01
SF	0.69	<0.01
TSAT	−0.704	<0.01
HIF-2α	0.565	<0.01
ERFE	0.468	<0.01
HIF-1α	0.907	<0.01

BUN=blood urea nitrogen; SCr=serum creatinine; eGFR=estimated glomerular filtration rate ; hsCRP=high sensitivity C-reactive protein; RBC=red blood cell; Hb=hemoglobin; HCT= hematocrit; Fe³⁺=Serum iron;SF=serum ferritin; TSAT=transferrin saturation; HIF-2α= hypoxia-inducible factor 2α; HIF-1α=hypoxia-inducible factor-1α; ERFE=Erythroferrone.

Analysis of the correlation between hepcidin and various indexes in the different subgroups of chronic kidney disease stages 3–5

Serum hepcidin was positively correlated with HIF-2α, ERFE, and HIF-1α in the patients with CKD that were injected with EPO (p < 0.01), while serum hepcidin was positively correlated with HIF-2α and HIF-1α (p < 0.01) but not with ERFE (p> 0.05) in the patients who were not injected with EPO. See Table 5 for details.

Table 5.

Analysis on correlation between serum Hepcidin and each indicator in CKD stages 3–5.

	Hepcidin
EPO injection	YES		NO
	R	p	R	p
HIF-2α	0.45	<0.01	0.64	<0.01
ERFE	0.49	<0.01	0.05	0.78
HIF-1α	0.90	<0.01	0.89	<0.01

EPO=erythropoietin; HIF-2α= hypoxia-inducible factor 2α; ERFE=Erythroferrone.

HIF-1α=hypoxia-inducible factor-1α.

Multiple linear regression analysis

Taking serum hepcidin as the dependent variable, and eGFR, SCr, BUN, hsCRP, Hb, RBC, HCT, Fe³⁺, SF, TSAT, HIF-2a, ERFE, and HIF-1a as the independent variables, the results showed that HIF-1α, SF, and HIF-2α were the factors that affected hepcidin. The results of the multivariate linear regression analysis are presented in Table 6.

Table 6.

Multifactor analysis of factors affecting Hepcidin.

Factor	β	Std. error	β standardized	t value	p value
Constant	−84.62	9.76		−8.67	0.000
HIF-1α	4.36	0.35	0.72	12.41	0.000
SF	0.13	0.04	0.19	3.55	0.001
HIF-2α	0.66	0.24	0.13	2.73	0.008

HIF-1α=hypoxia-inducible factor-1α; SF=serum ferritin; HIF-2α= hypoxia-inducible factor 2α.

Discussion

Jolanta et al.⁹ showed that hepcidin levels could increase in the early stages of CKD and were gradually up-regulated as the CKD advanced. As renal function declined, eGFR decreased and hepcidin excretion was blocked, so hepcidin remained in the body; the worse the renal function, the more severe the hepcidin accumulation, causing serum iron deficiency or intracellular iron overload, followed by renal anemia. It is known that most patients with CKD are in a state of microinflammation, and inflammation stimulates elevated hepcidin, triggering impaired iron absorption and utilization in patients, and the inflammatory state can aggravate the accumulation of hepcidin.¹⁰ In the present study, the serum hepcidin levels were increased in CKD stage 3 compared with the normal group, with no statistical significance. However, serum hepcidin levels were further increased in CKD stages 4 and 5 (p < 0.01). Hepcidin was negatively correlated with eGFR (r = −0.848, p < 0.01) and positively correlated with SCr, BUN, SF, and high-sensitivity C-reactive protein (r = 0.871, 0.76, 0.69, and 0.71, respectively, p< 0.01). As eGFR decreases, hsCRP increases gradually. Note that SF increased gradually, but TSAT was always lower than 20%, indicating microinflammation. In the multiple regression analysis, SF was seen to be a factor related to hepcidin, which is consistent with previous studies.¹¹ Thus, it can be concluded that microinflammation is a factor that has an impact on hepcidin.

Hypoxia-inducible factors primarily consist of three subgroups, namely, HIF-1α, HIF-2α, and HIF-3α. HIF-1α is widely expressed in tissues, mainly in tubular cells in the kidney. HIF-2α is mainly expressed in the endothelial system, and its expression is mainly seen in renal interstitial cells, endothelial cells, and glomeruli. These two have different target genes; HIF-1α primarily regulates general cell survival-related physiological functions, whereas HIF-2α mainly regulates fat metabolism and EPO generation.¹² Hypoxia regulates hepcidin in both an EPO-dependent and EPO-independent manner. However, whether it directly affects the down-regulation of hepcidin, or whether it indirectly affects hepcidin through the up-regulation of the tmprss6 gene, degradation of the hemojuvelin (HJV)-bone morphogenetic protein 6 (BMP6)/SMAD signal pathway, and the activation of erythropoiesis, is still a controversial issue.¹³

With regard to the EPO-dependent manner, HIF-2α can promote EPO expression and secretion as well as increase duodenal cytochrome B and divalent metal transporter 1 transcription in intestinal epithelial cells, increasing iron content in the body.¹⁴ Therefore, HIF-2α can improve anemia by positively regulating erythropoiesis and iron homeostasis. This study showed that HIF-2α levels were higher in patients with CKD stages 3–5 than in the normal group, that they increased with the decrease of eGFR, and that they were positively correlated with hepcidin (r = 0.565, p < 0.01). Therefore, with the progression of CKD, eGFR decreased, and the increase of hepcidin aggravated renal anemia. During hypoxia, the activity of the prolyl hydroxylase domain decreased, stimulating the increase of HIF-2α levels. It has been shown that HIF-2α indirectly regulates the regulation of hepcidin by stimulating ERFE through EPO, but it does not directly participate in the inhibition of hepcidin.¹⁵ In the multiple regression analysis, HIF-2α was indicated to be a factor affecting hepcidin. However, although HIF-2α may affect hepcidin by promoting the expression of EPO, the concentration of EPO was not detected in this study.

With respect to the EPO-independent manner, there are negative regulatory targets of the HIF/hypoxic response element signaling pathway in the promoter region of hepcidin; the HIF signaling pathway is directly or indirectly involved in the regulation of hepcidin expression through upstream mediators, and HIF-1α is a negative regulator of hepcidin. The down-regulation of hepcidin is related to the HIF-1α target gene.¹⁶ The promoter of the FURIN gene contains a hypoxia-responsive element and is a binding site for the HIF-1α transcription complex, and hypoxia can significantly increase the level of the furin messenger ribonucleic acid. A region was found in the promoter of the FURIN gene that can regulate furin transcription during hypoxia through the activity of HIF-1a.¹⁷ In this study, HIF-1α gradually increased with the decrease in eGFR (p < 0.05) (a possible adaptive response of the kidney to improve the hypoxia state). HIF-1α was positively correlated with furin (r = 0.717, p < 0.01), and HIF-1α was positively correlated with hepcidin (r = 0.907, p < 0.01); thus, hypoxia may stimulate a negative feedback increase in HIF-1α by promoting the activity of furin. In the multiple regression analysis, HIF-1α was a factor related to the levels of hepcidin, which is consistent with previous studies.

Erythroferrone is a protein synthesized and secreted primarily by immature erythrocytes, and it contains a tumor necrosis factor α (TNFα)-like domain at the C-terminus, which is a member of the TNFα/C1q superfamily. Erythropoiesis-stimulating factors can up-regulate the expression of ERFE in bone marrow-nucleated erythrocytes; ERFE promotes erythropoiesis by inhibiting hepatic hepcidin production and increasing the Fe²⁺ release from macrophages to plasma as well as iron absorption by the intestinal epithelium. ⁴ Increases in ERFE were also found in patients with renal anemia, possibly due to the fact that ERFE has a molecular weight of 52 kD. This is higher than the molecular weight cut-off for glomerular filtration (30–50 kD), and, with the decrease of eGFR, ERFE cannot be excreted normally. Thus, both increased ERFE production and/or decreased renal clearance, secondary to EPO stimulation, may contribute to increased ERFE.⁶ The current study showed that the ERFE levels were higher in the patients with CKD stages 3–5 and renal anemia than in the normal group, and they increased with the decrease of renal function, consistent with the previous study. The present study also showed a positive correlation between hepcidin and ERFE (r = 0.468, p < 0.01). In addition, in the subgroup analysis, serum hepcidin was positively correlated with ERFE in the EPO-injected group but not in the non-injected group. Exogenous EPO can also act as an upstream of ERFE to stimulate ERFE production. In a recent prospective study of inflammatory anemia, it was found that ERFE continues to increase during treatment, which is not enough to inhibit hepcidin.¹⁸ The present study also observed the same phenomenon. There was a positive correlation between hepcidin and ERFE in a simple linear correlation. Because the regulation of hepcidin in patients with CKD is complex, the correlation between ERFE and hepcidin may also have been masked by other regulatory mechanisms.

The multiple linear regression analysis showed that HIF-1α, HIF-2α, and SF were the factors affecting hepcidin, and it showed a positive correlation. However, HIF-1α, HIF-2α, and ERFE did not inhibit the level of hepcidin in patients with CKD stages 3–5 and renal anemia, which may be related to the complex pathological state in the end stages of CKD. The regulation of hepcidin in CKD is complex and influenced by many factors, such as renal function, iron status, hypoxia state, and inflammation, so hepcidin remains elevated in patients with renal anemia, and increases in HIF-1α, HIF-2α, and ERFE, and the use of EPO are not enough to inhibit hepcidin. On the contrary, because the level of hepcidin continues to rise, it stimulates their secretion, which shows a statistically positive correlation.The continuous increase of HIF level may also bring many adverse consequences.^19,20 The relationship between them is similar to the “trade-off hypothesis”.²¹ Therefore, inhibiting the increase of hepcidin should be an important means in the treatment of renal anemia.It has been recently discovered that roxadustat can correct renal anemia, and its main mechanisms of action are to inhibit the degradation of HIFs, to increase erythropoietin and receptor sensitivity, and to down-regulate hepcidin levels.²²

This study has several limitations. It is a cross-sectional study with a small sample size conducted at a single center in a real-world clinical setting. In addition, it was not possible to detect the concentration of serum EPO, and there was no assessment of vascular calcification, which may have affected the correlations in some of the data. Larger longitudinal studies are therefore required to more clearly understand the complex causal relationship of various indicators in patients with CKD.

Conclusion

HIF-1α, HIF-2α, and SF are factors affecting levels of hepcidin in patients with CKD stages 3–5 and renal anemia. The increase of HIF-1α, HIF-2α, and ERFE does not seem to inhibit the increase of hepcidin.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical approval

Ethical approval for this study was obtained from the Ethics Committee of the Affiliated People’s Hospital of Fujian University of Traditional Chinese Medicine (2019-050-02).

Informed consent

Written ICF was obtained from all subjects prior to the study.

ORCID iDs

Xiaoying Chen

Yan Yan

Yanyan Hong

Jing Zheng

Trial registration

This randomized clinical trial was not registered as it was an observational clinical study rather than an interventional study.

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The effects of hypoxia-inducible factors-1α and -2α and erythroferrone on hepcidin in patients with chronic kidney disease stages 3–5 and renal anemia

Abstract

Objective

Methods

Results

Conclusion

Keywords

Introduction

Patients and Methods

Statistical Analysis

Results

Comparison of erythropoietin and iron therapy in patients with chronic kidney disease stages 3–5

Analysis of the correlation between serum hepcidin and each indicator

Analysis of the correlation between hepcidin and various indexes in the different subgroups of chronic kidney disease stages 3–5

Multiple linear regression analysis

Discussion

Conclusion

Footnotes

Declaration of conflicting interests

Funding

Ethical approval

Informed consent

ORCID iDs

Trial registration

References