CC BY-NC-ND 4.0 · Avicenna J Med 2022; 12(02): 045-053
DOI: 10.1055/s-0042-1749612
Review Article

Zinc, Magnesium, and Copper Levels in Patients with Sickle Cell Disease: A Systematic Review and Meta-analysis

1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
,
Shahd S. Ali
1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
,
Waad K. Ali
1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
,
Hind R. Madani
1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
,
Rawya A. Basheir
1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
,
Rayan M. Altayeb
1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
,
Rayan H. S. Shazali
1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
,
Safaa Fadlelmoula
1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
,
Wisal M. Eltayeb
1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
,
Zeina I. Omar
1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
,
Mahmoud Elnil
1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
,
1   Department of Pathology, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
› Author Affiliations
Funding None.
 

Abstract

Background Sickle cell disease (SCD) is associated with oxidative stress due to an imbalance between production and elimination of the reactive oxygen species. It has been reported that SCD patients are at risk of multiple micronutrients' deficiencies, including several trace elements involved in the antioxidation mechanisms. We aimed to assess the status of these micronutrients in SCD patients.

Methods This study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The databases of MedLine, Embase, and PsycInfo were used for the systematic search from time the databases existed until April 2021. A total of 36 studies fulfilled the eligibility criteria. We calculated the pooled standardized mean difference (SMD) of serum zinc, magnesium, or copper levels among patients with SCD and their healthy controls.

Results SCD patients had significantly lower zinc (SMD = −1.27 [95% CI: 1.67−0.87, p 0.001]) and magnesium levels (SMD = −0.53 [95% CI: 1.0−0.06, p 0.026] than their controls. Copper level was found to be significantly higher in SCD patients, with SMD = 0.68 (95% CI: 0.05−1.32, p 0.004).

Conclusion This review showed that SCD patients may potentially prompt to have lower zinc and magnesium levels and higher copper levels compared with those without the disease. Future research need to be directed to investigate clinical outcome of nutritional difficiencies in patients with SCD, as well as the possibility of implementing nutritional supplement programs which may help minimizing the harmful effects of the disease on human body.


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Introduction

Sickle cell disease (SCD) is an inherited red blood cell disorder that leads to forming the mutated hemoglobin S, resulting in a wide range of signs and symptoms, including chronic hemolytic anemia, sequestration crisis, susceptibility to repeated infections, and periodic episodes of pain mostly due to vasoocclusive phenomena.[1] [2] [3] SCD also presents with long-term effects such as cerebrovascular accidents, sickle nephropathy, pulmonary complications, renal impairment, cardiomyopathy, delayed puberty, and reduced growth.[1] [2] [3] [4] [5] [6] [7]

The sickling and ischemic reperfusion injury associated with SCD lead to a state of oxidative stress due to an imbalance between production and elimination of the reactive oxygen species.[8] [9] Furthermore, hemoglobin S has a high autoxidation rate which contributes to the oxidative stress in SCD patients.[8] [9] As a result of the high-energy expenditure associated with the high rate of red cell turnover, SCD patients are at risk of multiple micronutrients deficiencies that could have an impact on SCD severity.[8] [9] [10] [11] It has been reported that the concentrations of multiple micronutrients and trace elements tend to be low in patients with SCD.[8] [9] [10] [11]

Many of these micronutrients are involved in antioxidation mechanisms which are further compromised as a result of high oxidative stress in the sickled erythrocytes.[8] [9] Of these trace elements, zinc, copper, and magnesium and their roles have been widely described in the literature.[8] [9] Zinc and copper are essential cofactors for the optimal performance of superoxide dismutase, a scavengering enzyme responsible for detoxifying anion superoxide to hydrogen peroxide. However, copper could act as a prooxidant and promotes free radicals when it presents in high concentration in the state of impaired zinc bioavailability, a condition that has been previously described in various diseases, including SCD.[8] [9] [12] [13] Also, magnesium has a role in the modulation of endothelial inflammation, besides its roles in regulating heart rhythm, immune system functions, and bone metabolism.[14]

Several studies provided data on the status of these micronutrients in SCD but these data require further summary and analyses for better accuracy. This review aimed to provide a quantitative, comprehensive view of the status and extent of zinc, copper, and magnesium levels and deficiencies in SCD patients.


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Methods

Search Strategy and Eligibility Criteria

This systematic review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline.[15] [16] A systematic search was performed in April 2021 through Medline, Embase, and PsycInfo databases from data of inception up to specified databases up to April 2021. Databases were queried for the terms ((zinc or magnesium or copper) AND (Sickle cell or Sickler)). Duplicate records were removed subsequently. We included studies reported sufficient data on the mean levels of zinc, magnesium, or copper among patients with SCD and their healthy controls for evidence synthesis. Neither age restriction nor specific population criteria were implemented. Studies with insufficient data, case reports, conference presentations, editorials, proposals, and abstracts were excluded.

The titles and abstracts of retrieved articles were screened by two independent reviewers for potential inclusion. Any discrepancy between the reviewers was resolved by consensus with a third reviewer. Full-text screening was done by two independent reviewers and any discrepancy between the reviewers was resolved by consensus with a third reviewer. Appraisal of individual study quality was performed by two independent reviewers using the Newcastle–Ottawa scale, a tool that determines the quality based on the selection of the study group, comparability of groups, and ascertainment of the exposure and outcomes.[17] Data extraction was done with a data collection sheet made in a Microsoft Excel Spreadsheet. When data were presented in medians and interquartile range, we transformed them into means and standard deviations.[18]


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Statistical Analysis

The standardized mean difference (SMD) was selected as a measurement tool to estimate the difference in serum levels of the targeted micronutrients. SMD was chosen as the included studies reported the results using different tools and measures. Statistical analysis was performed using R language v.4, using the “meta” and “metafor” packages, through the MARVIS app (Elkhidir, Ibrahim (2022): MARVIS. Figshare software).[19] [20] [21] [22] Random effects models were used to pool the individual estimates and to accommodate for the heterogeneity in the reported pooled effect sizes. The effect size selected for statistical computation is the pooled SMD. Statistical heterogeneity was estimated using I 2 statistics and further assessed using subgroup analysis and metaregression. Publication bias was evaluated by both the Egger test and funnel plot visual analysis.


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Result

Studies Characteristics

The search yielded a total of 986 records. After eliminating duplicate data, 696 studies were included for the title and abstract screening of which 599 were excluded due to irrelevance. Full texts of the remaining 97 records were screened with a subsequent exclusion of 54 records. A total of 36 studies published from 1974 to 2019 met the eligibility criteria and were further included for evidence synthesis; 15 from Africa, 9 from the United States, 8 from Asia, and 4 from Europe.[8] [9] [12] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] Details of the selection process are summarized in ([Fig. 1]).

Zoom Image
Fig. 1 The flow diagram for the process of study selection.

Zinc

Discriptive summary of data for zinc in [Table 1]. The pooled SMD of serum zinc across all included studies was −1.27 (95% confidence interval [CI]: −1.67 to −0.87, p < 0.001) with a prediction interval of (−3.44; 0.90; [Fig. 2]). A substantial heterogeneity across studies was noted (I 2 = 95%, p < 0.001). A potential risk for publication bias was noted on visual examination of funnel plot and the Egger's test = − 2.14; p = 0.042. Subgroup analysis by study location as a grouping variable revealed that the Asian (−1.65), African (−1.63), and American (−0.71) studies have statistically significant SMD, unlike the European studies (−0.82). Year of publication explained approximately 10.34% (R 2) of the total heterogeneity.

Zoom Image
Fig. 2 Pooled SMD of zinc levels among patients with SCD. CI, confidence interval; SCD, sickle cell disease; SD, standard deviation; SMD, standardadized mean difference.
Table 1

Data of zinc between sickle cell disease patient(s) and non–sickle cell disease patient(s)

Study

Location

Design

Sickle cell disease patient(s)

Non–sickle cell disease patient(s)

Mean

SD

n

Mean

SD

n

Akinkugbe and Ette (1987)[37]

Africa

Cross-sectional

53.45

25.19

40

79

61.6

20

Alayash et al (1987)[49]

Asia

Cross-sectional

113

35.9

57

117.43

34.1

45

Al-Naama et al (2016)[51]

Asia

Cross-sectional

62.2

12.6

42

94.2

12.5

50

Antwi-Boasiako et al (2019)

Africa

Cross-sectional

66.5

5.8

34

101.4

9.4

50

Bashir (1995)[55]

Asia

Cross-sectional

85.6

10.3

15

107.2

11.7

25

Canellas et al (2012)[43]

The United States

Cross-sectional

60

10

43

80

20

60

Emokpae et al (2019)[59]

Africa

Case control

46.26

1.986

74

54.6

1.237

50

Hasanato et al (2019)[9]

Asia

Cross-sectional

65.5

22.5926

33

94

13.75

33

Karayalcin et al (1979)[23]

The United States

Cross-sectional

114.9

22.2

46

133.63

24.36

46

Karayalcin-zinc et al (1974)[24]

The United States

Cross-sectional

116

33

50

177

49

50

Kehinde et al (2011)[25]

Africa

Cross-sectional

70

6

20

70

7

20

Kilinç et al (1991)[28]

Europe

Case control

58

18.6529

20

96.4

22.8

20

Kudirat et al (2019)[30]

Africa

Descriptive longitidual

23.4

7.4

70

48.9

14.4

70

Kuvibidila et al (2006)[31]

The United States

Case control

96.1

20.5

90

95.1

46.1

82

Olaniyi et al (2010)[36]

Africa

Case control

1320

230

59

1170

200

35

Oliveira et al (2001)[56]

The United States

Case control

85.15

32.18

34

108.45

22.89

20

Onukwuli et al (2018)[39]

Africa

Cross-sectional, case control

58.01

10.58

81

68.37

8.67

81

Oztas et al (2012)[40]

Europe

Case control

158.3

13.8

15

154.1

22.4

10

Phebus et al (1988)[41]

The United States

Case control

76.3

8.9

56

82.2

9.8

44

Prasad et al (1976)

The United States

Case control

104

10.5

84

113

13.6

70

Smith et al (2019)[42]

Africa

Cross-sectional

101

13.4683

80

105.7

11.5

80

Wasnik et al (2017)[44]

Asia

Cross-sectional

83.09

9.26

33

104.06

6.27

33

Yousif et al (2018)[45]

Asia

Case control

67.25

17.78

87

90.34

16.38

90

Yuzbasiyan et al (1989)[46]

The United States

Case control

87

17

7

83

17

8

Arinola et al (2008)[50]

Africa

Case control

11.2545

5.66609

44

15.94

5.51066

50

Arcasoy et al (2001)[48]

Europe

Case control

77.3

15.74

10

90.04

13.83

20

Durosinmi et al (1993)[57]

Africa

Case control

2.89

0.73

18

5.21

1.97

27

Sungu et al (2018)[8]

Africa

Case control

0.27

0.58

76

1.64

0.14

76


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Magnesium

Discriptive summary of data for magnesium in [Table 2]. The pooled SMD of serum magnesium across all included studies was −0.53 (95% CI: −1.0 to −0.06, p < 0.026) with a prediction interval of (−1.0; 1.25; [Fig. 3]). A substantial heterogeneity across studies was noted (I 2 = 92%, p < 0.01). No potential risk for publication bias was noted visual examination of the funnel plot and the Egger's test was 0.964, p = 0.36. Subgroup analysis by study location as a grouping variable revealed that SMD was only significant among American studies. Both location and year explained 17.20% (R 2) of the total heterogeneity. Testing for residual heterogeneity was significant (QE [df = 6] = 98.3528, p < 0.001), indicating that there are other factors not included in the model that significantly contributing to the high heterogeneity.

Table 2

Data of magnesium between sickle cell disease patient(s) and non–sickle cell disease patient(s)

Study

Location

Design

Sickle cell disease patient(s)

Non–sickle cell disease patient(s)

Mean

SD

n

Mean

SD

n

Antwi-Boasiako et al (2019)

Africa

Case control

0.79

0.25

79

0.90

0.11

48

Elshal et al (2012)[58]

Asia

Case control

0.79

0.13

60

0.85

0.17

20

Khan (2003)[27]

Asia

Case control

0.84

0.09

51

0.78

0.05

29

Kontessis et al (1992)[29]

Europe

Case control

0.77

0.10

8

0.85

0.10

14

Olaniyi et al (2010)[36]

Africa

Case control

0.39

0.09

59

0.38

0.08

35

Olukoga et al (1993)[38]

Africa

Case control

0.76

0.10

25

0.83

0.15

25

Prasad et al (1976)

The United States

Case control

0.78

0.10

29

0.82

0.08

38

Sungu et al (2018)[8]

Africa

Case control

0.13

0.02

76

0.42

0.21

76

Yousif et al (2018)[45]

Asia

Case control

0.55

0.19

87

0.77

0.11

90

Zehtabchi et al (2004)

The United States

Case control

0.79

0.09

74

0.81

0.07

32

Zoom Image
Fig. 3 Pooled SMD of magnesium levels among patients with SCD. CI, confidence interval; SCD, sickle cell disease; SD, standard deviation; SMD, standardadized mean difference.

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Copper

Discriptive summary of data for copper in [Table 3]. The pooled SMD of serum copper across all included studies was 0.68 (95% CI: 0.05–1.32, p < 0.004), with a prediction interval of (−2.29; 3.66; [Fig. 4]). A substantial heterogeneity across studies was noted (I 2 = 97%, p < 0.001). On visual examination of funnel plot, no potential risk for publication bias was noted and the Egger's test statistics was 0.561, p = 0.58. Subgroup analysis by study location as a grouping variable, revealed that SMD was only significant among Asian studies. Between group difference is significant (Q = 12.01865, df = 3, p = 0.007). Mixed model of study location and year of publication explained approximately 21.77% (R 2) of the total heterogeneity. Testing for residual heterogeneity was significant (QE [df = 5] = 242.2145, p < 0.001), indicating that there are other factors not included in the model that significantly contributing to the high heterogeneity.

Table 3

Data of copper between sickle cell disease patient(s) and non–sickle cell disease patient(s)

Study

Location

Design

Sickle cell disease patient(s)

Non–sickle cell disease patient(s)

Mean

SD

n

Mean.c

SD

n

Akinkugbe and Ette (1987)[37]

Africa

Cross-sectional

70.40

42.62

40

89.30

61.30

20

Alayash et al (1987)[49]

Asia

Cross-sectional

144.93

44.09

57

148.40

44.40

45

Al-Naama et al, (2016)[51]

Asia

Cross-sectional

145.50

14.30

42

100.90

13.50

50

Antwi-Boasiako et al, 2019

Africa

Cross-sectional

220.90

27.80

34

114.00

16.30

50

Bashir (1995)[55]

Asia

Cross-sectional

131.30

11.50

15

109.00

15.10

25

Canellas et al (2012)[43]

The United States

Cross-sectional

120.00

10.00

43

100.00

10.00

60

Emokpae et al (2019)[59]

Africa

Case control

105.80

2.46

74

102.60

1.59

50

Erhabor et al (2019)[60]

Africa

Case control

40.40

9.66

45

75.60

6.50

25

Hasanato et al (2019)[9]

Asia

Cross-sectional

131.67

15.56

33

88.00

10.50

33

kehinde et al (2011)[25]

Africa

Cross-sectional

6.00

2.00

20

7.00

3.00

20

Kilinç et al (1991)[28]

Europe

Case control

133.80

64.67

20

168.70

39.30

20

Mukuku et al (2018)[33]

Africa

Case control

172.00

15.00

76

189.00

20.00

76

Olaniyi et al (2010)[36]

Africa

Case control

67.00

10.10

59

68.50

10.00

35

Oztas et al (2012)[40]

Europe

Case control

95.90

9.90

15

96.30

9.10

10

Prasad et al, 1976

The United States

Case control

126.00

25.00

41

116.00

19.00

60

Smith et al (2019)[42]

Africa

Cross-sectional

144.00

17.09

80

116.00

27.70

80

Yousif et al (2018)[45]

Asia

Case control

142.35

49.92

87

109.66

24.42

90

Zoom Image
Fig. 4 Pooled SMD of copper levels among patients with SCD. CI, confidence interval; SCD, sickle cell disease; SD, standard deviation; SMD, standardadized mean difference.

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Discussion

This review aimed to provide an overarching resource about the status of zinc, magnesium, and copper in SCD patients. Most of the studies (28 out of 36) focused on zinc serum level among patients with SCD. The analyses showed that both zinc and magnesium levels were lower in SCD patients, whereas copper level was higher among them. These findings coincide with the known nature of the chronic inflammatory process occurring in SCD associated with ischemia-reperfusion injury, excessive production of free radicals like superoxide, and hydrogen peroxide.[61] [62] Additionally, due to the norable heterogeneity in SMD meta-anaylsis, subgroup analysis was done, and the Asian and African descent had significanly lower values than both American and European. This stress on the importance of race and ethnicity on the clinical outcome in SCD patients which is well established in the literature.[63] The high copper values in these patients may be attributed to the chronic hemolysis state and aggravated by the coexisting zinc deficieny. In two studies by Antwi-Boasiako et al and Osredkar and Sustar et al, they discovered that serum copper is influenced by zinc bioavailability, as they observe that zinc deficiency significantly enhance copper absorption from the gut.[12] [64] Additionally, high copper may promote a prooxidant state as illustrated by Chirico and Pialoux.[65] Although there is noted heterogenity using I 2 statistics, most of included studies for zinc and magnesium had a pattern of consistency across them that nearly 22 studies out of 28 fall below SMD of 0 for zinc, and 10 out of 12 studies for magnesium that fell below a SMD of 0 which, in fact, explained by Borenstein et al which concluded that not to miss such patterns in expense of high heterogeneity.[66]

The differences noted in these trace elements levels between SCD patients and others could be attributed to several peculiar characteristics of SCD such as increased physiological demands due to the fast rate of erythrocytosis and red blood cells turnover in SCD, impact of suboptimal renal function, glomerular injury in SCD, and impaired absorption by the damaged intestinal mucosa as a complication of SCD.[8] [42] [67] There are implications to the reported findings. From a clinical perspective, the SCD patients might have benefited from nutritional supplementations with these elements, as it has been reported by previous studies[13] [68] but nutritional guidelines concerning the performance of these micronutrients in SCD patients are still not broadly available.[13]

From a research perspective, the paucity of data on clinical outcomes of trace elements deficiencies needs to be addressed and could benefit from further studies to give a better understanding of the exact pathogenesis and effects of such deficiencies.


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Limitations

The results of this review need to be considered in the context of some limitations. The protocol of the study was not registered in PROSPERO which is a well-known review registry portal.[69] The inclusion of observational studies published only in English which might compromise representativeness, as well as the notable heterogeneity among studies, which was partially explained by some demographic variables. In addition, despite the paucity of data on the clinical outcomes associated with these trace element deficiencies, it does not mean that the laboratory findings cannot have implications on clinical significance, but the included studies used different tools making using the raw mean difference difficult to implement.


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Conclusion

This review showed that SCD patients may potentially prompt to have lower zinc and magnesium levels and higher copper levels compared with those without the disease. Future research needs to be directed to investigate clinical outcome of nutritional difficiencies in patients with SCD, as well as the possibility of implementing nutritional supplements programs which may help minimizing the harmful effects of the disease on human body.


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Conflict of Interest

None declared.

Authors' Contributions'

S.O.O.M. and I.H.E. conceptualized the research idea and designed the study; R.H.S.S., W.M.E., H.R.M., and R.A.B. undertook articles searching, articles assessment, and review; and S.S.A. and W.K.A.) undertook data extraction and analysis. All authors interpreted the results and drafted the manuscript. All authors revised and approved the final manuscript.


Availability of Data and Material

The dataset generated during this study are available from the corresponding author on reasonable request.



Address for correspondence

Ibrahim H. Elkhidir, MD
Faculty of Medicine, University of Khartoum 11111
Alqasr Avenue, P.O. Box 102, Khartoum
Sudan   

Publication History

Article published online:
02 July 2022

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Zoom Image
Fig. 1 The flow diagram for the process of study selection.
Zoom Image
Fig. 2 Pooled SMD of zinc levels among patients with SCD. CI, confidence interval; SCD, sickle cell disease; SD, standard deviation; SMD, standardadized mean difference.
Zoom Image
Fig. 3 Pooled SMD of magnesium levels among patients with SCD. CI, confidence interval; SCD, sickle cell disease; SD, standard deviation; SMD, standardadized mean difference.
Zoom Image
Fig. 4 Pooled SMD of copper levels among patients with SCD. CI, confidence interval; SCD, sickle cell disease; SD, standard deviation; SMD, standardadized mean difference.