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Table 1 Bivariate analysis of malaria predictors and clinical malaria

From: Evaluating the predictive performance of malaria antibodies and FCGR3B gene polymorphisms on Plasmodium falciparum infection outcome: a prospective cohort study

Predictor

Levels

Protected

Susceptible

Combined

p-value

N = 342

N = 53

N = 395

Age in years

 

5(3,8)

5 (3,7)

5 (3,8)

0.12e

Mosquito net use

No

60% (204)

58% (31)

59% (235)

0.87f

Blood group

A

18% (63)

19% (10)

18% (73)

0.93f

AB

6% (22)

8% (4)

7% (26)

 

B

29% (98)

25% (13)

28% (111)

 

O

46% (159)

49% (26)

47% (185)

 

Sickle cell status

Positive

15% (51)

19% (10)

15% (61)

0.46f

Parasite count(categorized)

positive

7% (25)

4% (2)

7% (27)

0.34f

Haemoglobin at enrollment(gram per dL)

 

12 (11,13)

11 (11,12)

12 (11,13)

0.11e

Additive c.108C>G

CC

29% (100)

26% (14)

29% (114)

0.4f

CG

42% (144)

36% (19)

41% (163)

 

GG

29% (98)

38% (20)

30% (118)

 

Additive c.114T>C

CC

27% (92)

26% (14)

27% (106)

0.82f

CT

43% (147)

47% (25)

44% (172)

 

TT

30% (103)

26% (14)

30% (117)

 

Additive c.233C>A

AA

9% (31)

2% (1)

8% (32)

0:2f

AC

27% (93)

28% (15)

27% (108)

 

CC

64% (218)

70% (37)

65% (255)

 

Additive c.244A>G

GG

31% (106)

32% (17)

31% (123)

0.36f

AG

39% (134)

47% (25)

40% (159)

 

AA

30% (102)

21% (11)

29%(113)

 

Additive c.316A>G

GG

13% (43)

17% (9)

13% (52)

0.65f

AG

32% (109)

32% (17)

32% (126)

 

AA

56% (190)

51% (27)

55% (217)

 

Additive c.194A>G

GG

39% (135)

30% (16)

38% (151)

0.43f

AG

39% (135)

45% (24)

40% (159)

 

AA

21% (72)

25% (13)

22% (85)

 

Dominant c.108C>G

CC vs CG-GG

71% (244)

62% (33)

70%(277)

0:18f

Dominant c.114T>C

TT vs CT-CC

73% (250)

74% (39)

73% (289)

0:94f

Dominant c.194A>G

AA vs AG-GG

61% (207)

70% (37)

62% (244)

0:2f

Dominant c.233C>A

CC vs AC-AA

91% (311)

98% (52)

92% (363)

0:075f

Dominant c.244A>G

AA vs AG-GG

69% (236)

68% (36)

69% (272)

0:87f

Dominant c.316A>G

AA vs AG-GG

87% (299)

83% (44)

87% (343)

0:38f

Recessive c.108C>G

CC-CG vs GG

29%(100)

26% (14)

29% (114)

0:67f

Recessive c.114T>C

TT-CT vs CC

30% (103)

26% (14)

30% (117)

0:58f

Recessive c.194A>G

AA-AG vs GG

21% (72)

25% (13)

22% (85)

0:57f

Recessive c.233C>A

CC-AC vs AA

64% (218)

70% (37)

65% (255)

0:39f

Recessive c.244A>G

AA-AG vs GG

30% (102)

21% (11)

29% (113)

0:17f

Recessive c.316A>G

AA-AG vs GG

56% (190)

51% (27)

55% (217)

0:53f

log.IgG-MSP1

 

2.2 (1.6,3.7)

2.4 (1.6,3.2)

2.3 (1.6,3.6)

0:77e

log.IgG1-MSP1

 

3.2 (2.4,5.4)

3.1 (2.6,4.4)

3.2 (2.4,5.4)

0:6e

log.IgG2-MSP1

 

1.9 (1.6,2.8)

2.0 (1.6,2.7)

1.9 (1.6,2.8)

0:71e

log.IgG3-MSP1

 

3.3 (1.9,6.0)

3.1 (2.0,6.0)

3.3 (1.9,6.0)

0:83e

log.IgG4-MSP1

 

1.6 (1.4,2.0)

1.6 (1.3,1.9)

1.6 (1.4,2.0)

0:64e

log.IgG-MSP3

 

3.2 (2.5,4.6)

3.2 (2.5,4.8)

3.2 (2.5,4.6)

0:66e

log.IgG-1MSP3

 

3.2 (2.6,4.7)

2.9 (2.6,4.2)

3.2 (2.6,4.7)

0:36e

log.IgG-2MSP3

 

1.8 (1.6,2.2)

1.8 (1.5,2.1)

1.8 (1.6,2.2)

0:52e

log.IgG-3MSP3

 

2.7 (1.8,4.5)

2.6 (2.0,4.1)

2.7 (1.8,4.5)

0:89e

log.IgG-4MSP3

 

1.7 (1.4,2.1)

1.7 (1.5,2.1)

1.7(1.4,2.1)

0:82e

log.IgG-GLURPR0

 

3.4 (2.4,4.7)

3.8 (2.6,4.8)

3.4 (2.4,4.7)

0:36e

log.IgG1-GLURPR0

 

3.4 (2.5,4.9)

3.7 (2.7,5.1)

3.4 (2.5,4.9)

0:40e

log.IgG2-GLURPR0

 

1.9(1.6,2.3)

1.8(1.6,2.9)

1.9 (1.6,2.4)

0:61e

log.IgG3-GLURPR0

 

2.1 (1.6,3.4)

2.0 (1.7,2.7)

2.1 (1.6,3.4)

0:78e

log.IgG4-GLURPR0

 

1.5 (1.3,1.7)

1.5 (1.2,1.7)

1.5 (1.3,1.7)

0:44e

log.IgG-GLURPR2

 

3.9 (2.2,5.9)

4.2 (2.8,6.0)

4.0 (2.2,5.9)

0:26e

log.IgG1-GLURPR2

 

5.8 (3.8,8.0)

5.8 (4.3,7.5)

5.8 (3.9,8.0)

0:93e

log.IgG2-GLURPR2

 

3.2 (2.1,6.3)

2.9 (2.1,6.4)

3.1 (2.1,6.3)

0:56e

log.IgG3-GLURPR2

 

5.9 (3.5,7.8)

6.1 (4.1,7.3)

5.9 (3.5,7.6)

0:96e

log.IgG4-GLURPR2

 

2.1 (1.8,3.1)

2.1 (1.8,2.4)

2.1 (1.8,2.9)

0:62e

log.igG-AMA1

 

6.2 (3.6,9.2)

6.4 (4.5,8.4)

6.7 (3.8,9.1)

0:45e

log.IgG1-AMA1

 

9.5 (6.2,10.2)

8.9 (6.6,10.0)

9.4 (6.3,10.2)

0:61e

log.IgG2-AMA1

 

3.2 (2.1,4.5)

2.9 (2.1,4.2)

3.2 (2.1,4.4)

0:57e

log.IgG3-AMA1

 

4.7 (3.1,6.4)

4.8 (3.2,6.8)

4.7 (3.2,6.5)

0:54e

log.igG4-AMA1

 

4.0 (2.5,5.1)

3.6 (2.9,4.7)

3.9 (2.6,5.1)

0:62e

  1. a (b, c), represent the median, lower quartile, and the upper quartile for continuous variables.\( e \)-Wilcoxon Ranksum test, \( f \)-Fishers Exact Test. Numbers after percents are frequencies. Additive model: assumes the risk associated with an allele is increased r-fold for heterozygotes and 2r-fold for homozygote; Dominant model: assumes risk association with the dominant allele and compares homozygous wild type with a combination of the heterozygous and homozygous for the variant; Recessive model: assesses risk association with the recessive allele and compares homozygous variant type with a combination of the heterozygous and homozygous for the wild type. Tests used: Wilcoxon test; Pearson test, MSP: Merozoite surface protein, GLURP: Glutamate Rich Protein, AMA: Apical membrane antigen. Note: natural log transformation was used
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Malaria Journal

ISSN: 1475-2875

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