Table 1.
Bivariate analysis of malaria predictors and clinical malaria
| 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 |
a (b, c), represent the median, lower quartile, and the upper quartile for continuous variables.-Wilcoxon Ranksum test, -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