The mean age of the participants was 49.7 (± 15.8) years and there was an almost equal proportion of male (49.4%, n= 245/496) and female (50.6%, n=251/496) participants. The prevalence of anaemia among CKD cases was about three times that of controls, 33.0% (95%CI: 27.99% – 38.45%) vs 9.78% (95%CI: 6.22 % - 15.05%) respectively (Table 1).
Table 1: Socio-demographic, haematological and biochemical characteristics of participants by iron-deficiency-anaemia status
Characteristics
|
CKD (n= 312)
|
Controls (n=184)
|
|
IDA
n= 103 (%)
|
Non-anaemic n=209 (%)
|
P-value
|
IDA
n=18 (%)
|
Non-anaemic
n=166 (%)
|
P-value
|
Hepcidin (ng/ml)
(median, IQR)
|
8.4
(4-45.5)
|
6.8
(3.9 -33.6)
|
0.2790
|
3.1
(2.3 – 7.9)
|
3.1
(2.1- 10.9)
|
0.836
|
GDF-15 (pg/ml)(median, IQR)
|
1256.8 (919.1 -1618)
|
700
(335.1-1327.8)
|
<0.0001
|
1175.9 (708.9 -1267.1)
|
397.95 (183.2-1101)
|
0.016
|
Age (mean ±SD) years
|
54.5 ± 15.2
|
54.3 ± 14.2
|
0.9340
|
45.2± 17.5
|
41.3 ±13.6
|
0.255
|
<40
|
15 (14.6)
|
37 (17.7)
|
0.484
|
8 (44.4)
|
79 (47.6)
|
0.800
|
≥40
|
88 (82.3)
|
172 (85.4)
|
|
10 (55.6)
|
87 (52.4)
|
|
Race
|
Blacks
|
95 (92.2)
|
165 (79.0)
|
0.003
|
12 (66.7)
|
133 (80.1)
|
0.185
|
Whites
|
8 (7.8)
|
44 (21.1)
|
|
6 (33.3)
|
33 (19.9)
|
|
Gender
|
Male
|
41 (39.8)
|
126 (60.3)
|
0.001
|
7 (38.9)
|
71 (42.8)
|
0.752
|
Female
|
62 (60.2)
|
83 (39.7)
|
|
11 (61.1)
|
95 (57.2)
|
|
Systolic Blood Pressure (median, IQR) (mmHg)
|
139
(125 – 157)
|
140
(130 - 160)
|
0.1994
|
132
(120 – 140)
|
132
(130 - 140)
|
0.998
|
Diastolic Blood Pressure (median, IQR) (mmHg)
|
80
(70- 91)
|
80
(70 – 90)
|
0.6234
|
81
(70 -90)
|
80
(72 – 90)
|
0.7707
|
Serum Urea (median, IQR)
(mmol/L)
|
17.1
(9.8 - 25.7)
|
11
(7.1 – 15.9)
|
0.0001
|
4
(3-4.9)
|
4.35
(3.6 – 5.2)
|
0.4486
|
Serum Creatinine
(median, IQR),
mmol /L
|
265(158- 520)
|
171(120 – 255)
|
<0.0001
|
70.5(64 – 78)
|
78.5 69 – 91)
|
<0.0001
|
eGFR (median, IQR), mls/min/1.73m2
|
27.0(12.6 – 27.0)
|
43.6 (27.7 – 66.0
|
<0.0001
|
129.8(96.3 - 139.5)
|
114.4(96.8 – 133.0)
|
0.3490
|
Table 1 also showed that the median levels of serum GDF-15 [1024.5 (429.4 - 1489.5pg/ml) vs. 447.25 (188.25 - 1192.3pg/ml), P-value<0.0001] and hepcidin [7.1 (3.9 - 36.2) vs 3.1(2.1 – 10.9), P-value <0.0001], were more than doubled among the CKD participants as compared to the controls. Among the CKD participants, the median GDF-15 level was higher among the anaemic as compared to the non-anaemic participants (P-value <0.0001, Table 1). Similarly, median GDF-15 levels were higher among the anaemic controls as compared to the non-anaemic controls (P= 0.0155). In contrast, there was no difference in the serum levels of hepcidin by anaemia status among the CKD participants (P-value =0.2790) and the controls (P-value = 0.8357).
The reference values (5% - 95% range) among the non-anaemic controls of this study for hepcidin and GDF-15 were 1.5 - 28.1 ng/ml and 108.2 – 2833 pg/ml, respectively. Furthermore, the reference range (5th – 95th percentile) of hepcidin among apparently healthy female participants was 1.4 – 38.8 ng/ml while the reference range for males was 1.6 – 28.1ng/ml. There was a significant negative linear relationship between hepcidin and GDF-15 among anaemic CKD patients (r= -0.28, P-value = 0.0037), supplementary Table 1.
Serum ferritin (r= 0.5, P-value <0.0001), and serum creatinine levels (r= 0.21, P-value = 0.0368) were positively correlated with hepcidin, while GFR (r= - 0.19, P-value = 0.0493) was negatively correlated with hepcidin among the participants with CKD, supplementary table 1. GDF-15 was negatively correlated with serum ferritin and haemoglobin levels, while TSAT level correlated with GDF-15, especially among the anaemic CKD cases (supplementary table 2).
For every ng/ml increase in serum ferritin level among CKD patients, log hepcidin increased by 0.00389 (β=0.00389, P-value<0.001). In other words, hepcidin levels increased by 100.00389 units for every ng/ml increase in serum ferritin.
logGDF-15 decreased with every unit increase of MCHC (β= -0.0618, P-value=0.005). On average, the white racial group and those participants with late CKD stage (IV-V) had a higher log GDF-15 as compared to the black racial group (β=0.343, P-value = 0.018) and early CKD stage (I-III) (β=0.476, P-value < 0.001); Table 2.
Table 2: Multiple linear predictors of log Hepcidin and logGDF-15 among CKD patients
Variable
|
Log Hepcidin
|
Log GDF-15
|
Coefficient
|
SE
|
P-value
|
Coefficient
|
SE
|
P-value
|
Ferritin
|
0.00389
|
0.00064
|
< 0.0001
|
-0.00038
|
0.00039
|
0.328
|
Age
|
0.0017
|
0.00581
|
0.766
|
0.0016
|
0.0036
|
0.648
|
Race
|
|
|
|
|
|
|
Blacks
|
Reference
|
Reference
|
Reference
|
Reference
|
Reference
|
Reference
|
Whites
|
-0.2301
|
0.2239
|
0.303
|
0.3429
|
0.1443
|
0.018
|
Gender
|
|
|
|
|
|
|
Male
|
Reference
|
Reference
|
Reference
|
Reference
|
Reference
|
Reference
|
Female
|
-0.2336
|
0.1572
|
0.138
|
0.1688
|
0.1041
|
0.106
|
MCHC
|
-0.0393
|
0.0376
|
0.298
|
-0.0618
|
0.0220
|
0.005
|
MCV
|
0.0082
|
0.0124
|
0.506
|
-0.0136
|
0.0073
|
0.066
|
CKD Stage
|
|
|
|
|
|
|
Early(I-III)
|
Reference
|
Reference
|
Reference
|
Reference
|
Reference
|
Reference
|
Late (IV – V)
|
-0.0223
|
0.1656
|
0.893
|
0.4761
|
0.0993
|
< 0.0001
|
The predictive value of GDF-15 and hepcidin for diagnosing IDA among CKD participants was 77.27% (95%CI: 71.98% – 82.56%) and 77.01% (95%CI: 71.64% – 82.38%), respectively (table 3, Figure 1A). There was no statistically significant difference between the AUC of the ROC curves of GDF-15 and that of hepcidin (P-value = 0.8369); (Figure 1A). A combination of the two parameters did not improve the diagnostic value of either of the two tests, as the AUC of the ROC of the model with the combination was 78.27%, 95%CI: 73.08% – 83.47%; P-value = 0.1809 Figure 1B.
Using the non-covariate analysis and Younden’s index, the optimum cut-off value among CKD participants for GDF-15 was 1,030 pg/ml (at a sensitivity of 72.8% and specificity of 61.24%). Similarly, the optimum cut-off for hepcidin was 22.5ng/ml (at a sensitivity of 38.8% and specificity of 70.8%); (Data not shown).
Table 3: Relationship between iron deficiency anaemia and Hepcidin or GDF-15 as primary biomarker among CKD participants
Variable
|
1Multivariable logistic regression analysis with Hepcidin as the primary factor
|
2Multivariable logistic regression analysis with GFD15 as the primary factor
|
Adjusted Odds ratio
|
95%CI
|
P-value
|
Adjusted Odds ratio
|
95%CI
|
P-value
|
Hepcidin
|
1.0030
|
1.0004 – 1.0055
|
0.023
|
-
|
-
|
-
|
GDF-15
|
|
-
|
-
|
1.0003
|
1.0001 -1.0005
|
0.017
|
1Multivariable logistic regression of the model of the relationship between Hepcidin and iron deficiency anaemia
2Multivariable logistic regression of model of the relationship between GDF-15 and iron deficiency anaemia.
The 2 models corrected for gender, age, CKD stage, history of diabetes mellitus, race, C-reactive protein, mean corpuscular volume.
CI: Confidence interval
|
The predictive value of Hepcidin for diagnosing functional IDA among CKD participants was 80.12%. (Table 5, Figure 1C). The predictive value of GDF-15 for diagnosing absolute IDA among CKD participants was 79.66%. (Table 4, Figure 1D). Using the non-covariate analysis and Younden’s index, the optimum cut-off value of GDF-15 for diagnosing absolute IDA among CKD participants was 1129.3 mg/dl(at a sensitivity of 83.64%and specificity of 66.03%) Similarly, the optimum cut-off for hepcidin was 22.5ng/dl(at a sensitivity of 66.7% and specificity of 70.8%); (Supplementary Table 3)
From Supplementary Table 4, we found that although median serum hepcidin level among participants with late stage CKD (IV – V) was more than double the median hepcidin level among participants with early disease (I-III), this relationship did not reach statistical significance among ID (4.7 (Early Vs Late , (3.9 – 32.55) Vs 10.1 (4.1 - 55.8) , P= 0.2583)) and non ID ((6.2(3.9 – 21.6) Vs 14.3(4 – 48), P= 0.1387)) participants. Median GDF-15 levels were also higher among participants with late stage as compared to participants with early stage disease. There was no statistically significant difference in the median hepcidin and median GDF-15 levels across the different aetiologies of CKD.
Further sub-analysis showed that hepcidin was not statistically associated with AID and ID among both early and late stage disease. However, the predictive value of diagnosing FID among late stage CKD disease using hepcidin as a biomarker was about 75.2%, while there was no statistically significant association between hepcidin and FID among patients with early stage CKD; (Supplementary Table 5).
GDF 15 was not associated with FID among both early and late CKD patients. However, the predictive value of GDF-15 for diagnosing AID and ID among early stage disease was about 83.3% and 77.5% respectively. Whereas, there was no statistically significant relationship among GDF and AID or ID among the late stage CKD participants; (Supplementary Table 5).
Among patients with a diagnosis of hypertension, GDF-15 predicted AID and ID anaemia in 81.1% and 81.9% of cases respectively; (Supplementary Table 5).
Table 4: Relationship between absolute iron deficiency anaemia and Hepcidin or GDF-15 as primary biomarker among CKD participants
Variable
|
1Multivariable logistic regression analysis with Hepcidin as the primary factor
|
2Multivariable logistic regression analysis with GFD15 as the primary factor
|
Adjusted Odds ratio
|
95%CI
|
P-value
|
Adjusted Odds ratio
|
95%CI
|
P-value
|
Hepcidin
|
1.0021
|
0.9991 - 1.0051
|
0.176
|
-
|
-
|
-
|
GDF-15
|
-
|
-
|
-
|
1.00038
|
1.0001 -1.0006
|
0.003
|
1Multivariable logistic regression of the model of the relationship between Hepcidin and iron deficiency anaemia
2Multivariable logistic regression of model of the relationship between GDF-15 and iron deficiency anaemia.
The 2 models corrected for gender, age, CKD stage history of Diabetes mellitus, race, C-reactive protein, mean corpuscular volume.
CI: Confidence interval
|
Table 5: Relationship between functional iron deficiency anaemia and Hepcidin or GDF-15 as primary biomarker among CKD participants
Variable
|
1Multivariable logistic regression analysis with Hepcidin as the primary factor
|
2Multivariable logistic regression analysis with GFD15 as the primary factor
|
Adjusted Odds ratio
|
95%CI
|
P-value
|
Adjusted Odds ratio
|
95%CI
|
P-value
|
Hepcidin
|
1.0043
|
1.00041 - 1.00829
|
0.030
|
-
|
-
|
-
|
GDF-15
|
-
|
-
|
-
|
1.00007
|
0.99970 -1.00044
|
0.715
|
1Multivariable logistic regression of the model of the relationship between Hepcidin and iron deficiency anaemia
2Multivariable logistic regression of model of the relationship between GDF-15 and iron deficiency anaemia.
The 2 models corrected for gender, age, CKD stage, history of Diabetes mellitus, race, C-reactive protein, mean corpuscular volume.
CI: Confidence interval
|