Genetic studies of human susceptibility to Schistosoma (blood fluke) infections have previously identified a genetic locus determining infection intensity with the African species, Schistosoma mansoni, in the 5q31–33 region of the human genome that is known to contain the Th2 immune response cluster, including the genes encoding the IL-4, IL-5, and IL-13 cytokines. These cytokines are key players in inflammatory immune responses and have previously been implicated in human susceptibility to infection with the Asian species, S. japonicum. In a nested case control study, we genotyped 30 HapMap tagging single nucleotide polymorphisms (SNPs) across these three genes in 159 individuals identified as putatively susceptible to reinfection with S. japonicum and in 133 putatively resistant individuals. A third group comprising 113 individuals demonstrating symptomatic infection was also included. The results provided no significant association at a global level between reinfection predisposition and any of the individual SNPs or haplotype blocks. However, two tagging SNPs in IL-5 demonstrated globally significant association with susceptibility to symptomatic infection. They were in strong linkage disequilibrium with each other and were found to belong to the same haplotype block that also provided a significant association after permutation testing. This haplotype was located in the 3′-untranslated region of IL-5, suggesting that variants in this region of IL-5 may modulate the immune response in these individuals with symptomatic infection.

The digenetic trematode (blood fluke) Schistosoma japonicum, transmitted by the amphibious fresh water snail Oncomelania, causes intestinal and hepatosplenic schistosomiasis in China, the Philippines, and Indonesia. Currently, ∼880,000 individuals are estimated to be infected in China, predominantly in the Yangtze River basin and the lake regions of Hunan and Jiangxi provinces (1). The overdistribution of fecal egg counts commonly observed in endemic populations is indicative of an innate susceptibility to S. japonicum infection in a minority of individuals. Individuals have been identified as being putatively susceptible or resistant to reinfection in both Chinese (2) and Filipino (3) populations. Variance component analyses have demonstrated significant clustering of infection and infection intensities in families for both S. japonicum (4) and the African species, Schistosoma mansoni (5, 6), and strong heritable factors were estimated to contribute to the control of human infection. Genetic studies have investigated infection intensity levels in S. mansoni-infected families and identified a codominant major gene playing a role in human susceptibility (7). The SM1 locus was subsequently linked to the 5q31–33 region of the human genome (8, 9, 10), a region known to contain the Th2 gene cluster encoding the IL-4, IL-5, and IL-13 cytokines. Many immunological studies have demonstrated the role of these cytokines in the immunomodulation of several helminth, including schistosome, infections in murine models (11, 12) and in humans (13, 14, 15, 16, 17). Other studies have shown a marked increase in the levels of IL-5 and IL-13 in individuals identified as being resistant to schistosome infection (18, 19). Furthermore, two polymorphisms in the IL-13 gene promoter region have been shown to be associated with S. hematobium infections (20). These findings led us to undertake a nested case-control study to investigate human susceptibility to S. japonicum reinfection targeting IL-4, IL-5, and IL-13 as candidate genes for single nucleotide polymorphism (SNP)3 typing and association analysis.

The participants in this study were selected from eight administrative villages, Aiguo, Dingshan, Fuqian, Xindong, Yufeng, Caojia, Hexi, and Tangmei from the Poyang Lake region, Jiangxi province, China which is highly endemic for S. japonicum. The total number of subjects from all eight villages who undertook an interview was 5,794. Each administrative village was comprised of 4–8 “natural villages.” Each individual was allocated a personal identification code comprised of their administrative village code, natural village code, household, and household member code. Demographic data were collected as well as water contact and schistosomiasis history using a validated questionnaire (21).

A cohort of 779 individuals was selected from the study based on exposure to infection and S. japonicum infection history. To ensure that all cohort members had similar water exposure, only full-time residents of the village were included who were over the age of 25 and had regular water contact. A questionnaire was constructed to assess schistosomiasis history with respect to previous diagnosed infection, previous treatment (following diagnosis) with the highly effective drug praziquantel, previous treatment as part of a control program, and symptomatic infection (see below for definition). All individuals were also interviewed regarding their occupation, whether the occupation involved water contact, the length of time in their current occupation, and previous water contact. At the time of interview, participants were asked to provide a saliva sample using a commercially available collection kit (Oragene; DNA Genotek). In accordance with the protocol, individuals were given a cup of water to rinse their mouths. Donors were then instructed to provide at least 2 ml of saliva in a vial labeled with their personal identification code, name, and sex. Of the 779 cohort individuals, 192 were lost to follow-up and 587 individuals were interviewed, of which two refused to provide a saliva sample.

All individuals included in the phenotype groups had to have significant occupational water exposure. Susceptibility/resistance to infection was examined using the questionnaire data. Susceptibility to infection/reinfection was defined as an individual having had 10 or more diagnosed schistosome infections in his/her lifetime. Individuals susceptible to symptomatic infection were defined as those who had been diagnosed (by fecal egg count) with a S. japonicum infection that was accompanied by three of the following symptoms: high fever, weakness, loss of appetite, headaches, and dizziness. Resistant individuals were categorized as having had fewer than five known infections and fewer than five treatments. All resistant subjects had to have been in their occupation for at least 15 years to ensure adequate exposure. The lengths of time in occupation, ages, and average numbers of infections per year for each group are shown in Table I. There were 159 individuals who were identified as susceptible to infection/reinfection, 113 who demonstrated symptomatic infection, and 133 who were categorized as resistant to infection/reinfection. The remaining individuals were omitted from the analysis as they could not be definitively classified into one of the three defined phenotypes.

Table I.

Characteristics of the different phenotype groups

Phenotype GroupNNo. of Infections (Range)Age (Range)Length of Time in Occupation (Range)No of Infections/Year in Occupation (95% CI)
Resistant 133 1.71 (0–5) 48.81 (30–76) 28.88 (15–60) 0.067 (0.056–0.077) 
Susceptible to reinfection 159 30.63 (10–70) 50.69 (27–86) 29.27 (5–60) 1.234 (1.071–1.398) 
Susceptible to symptomatic infection 113 17.71 (1–70) 49.63 (29–82) 29.28 (2–58) 0.649 (0.491–0.808) 
Phenotype GroupNNo. of Infections (Range)Age (Range)Length of Time in Occupation (Range)No of Infections/Year in Occupation (95% CI)
Resistant 133 1.71 (0–5) 48.81 (30–76) 28.88 (15–60) 0.067 (0.056–0.077) 
Susceptible to reinfection 159 30.63 (10–70) 50.69 (27–86) 29.27 (5–60) 1.234 (1.071–1.398) 
Susceptible to symptomatic infection 113 17.71 (1–70) 49.63 (29–82) 29.28 (2–58) 0.649 (0.491–0.808) 

DNA was purified from the saliva samples according to the manufacturer’s instructions (Oragene; DNA Genotek). DNA concentration was measured by spectrophotometry. Aliquots of all samples were taken and subsequently adjusted to provide standard stock solutions of 20 ng/μl. The A280/A260 ratio was estimated to provide an indication of the quality of the sample. Low ratios (<1.6) may indicate possible salt or ethanol contaminants, whereas high values may suggest the presence of fragmented DNA, RNA, or bacterial DNA. Only samples that provided a yield >20 ng/μl and a A280/A260 ratio >1.6 and <1.95 were included for genotyping analysis.

We selected tagging SNPs across the IL-4/IL-13 and IL-5 genes based on data from the public databases including the International HapMap Project (http://www.hapmap.org/) and NCBI (http://www.ncbi.nlm.nih.gov/). SNPs were selected beginning 20 kb upstream and extending 20 kb downstream for each gene. IL-4 and IL-13 were only 12.5 kb apart and thus were treated as one region. SNPs identified in the region that had frequency information in HapMap (for Chinese populations) were used to identify tag SNPs. A total of 20 tag SNPs were selected in these three genes, selecting from phase I and II HapMap data so that other SNPs within the interval were in strong linkage disequilibrium (r2 coefficient ≥ 0.8) with one of the tag SNPs. An additional 10 SNPs were selected from the literature with evidence of previous associations with atopic conditions, malaria, and Schistosoma hematobium infections and were included in the study (20, 22, 23, 24, 25, 26).

Assays were designed to type 30 SNPs across the 5q31–33 locus using the Sequenom MassARRAY assay design software (version 3.0). A MALDI-TOF mass spectrometer (Sequenom) was used to type the SNPs using iPLEX chemistry. PCRs were conducted in 2.5-μl reactions in standard 384-well plates. PCR was performed using ∼12.5 ng of genomic DNA for each sample, 0.5 U of Taq polymerase (HotStarTaq; Qiagen), 500 μmol of each dNTP, and 100 nmol of each PCR primer. PCR thermal cycling in an ABI 9700 instrument was 15 min at 94°C followed by 45 cycles of 20 s at 94°C, 30 s at 56°C, and 60 s at 72°C. To the completed PCR, 1 μl of shrimp alkaline phosphatase master mix was added and incubated for 30 min at 37°C followed by inactivation for 5 min at 85°C. After adjusting the concentrations of the extension primers to equilibrate signal-to-noise ratios, the post-PCR primer extension reaction of the iPLEX assay was performed in a final 5 μl of the extension reaction containing 0.1 μl of termination mix, 0.02 μl of DNA polymerase (Sequenom), and 600-1200 nM extension primers. A two-step 200 short cycles program was used for the iPLEX reaction; initial denaturation was 30 s at 94°C followed by 5 cycles of 5 s at 52°C and 5 s at 80°C. Forty additional annealing and extension cycles were then looped back to 5 s at 94°C, 5 s at 52°C, and 5 s at 80°C. A final extension was done at 72°C for 3 min and then the sample was cooled to 20°C. The iPLEX reaction products were desalted by diluting samples with 15 μl of water and 3 μl of resin to optimize mass spectrometric analysis and then spotted on a SpectroChip (Sequenom), processed, and analyzed in a compact mass spectrometer by MassARRAY workstation (version 3.3) software (Sequenom).

Genotype frequencies for all SNP variants were examined and the results were tested for departures from the Hardy-Weinberg equilibrium separately for both the susceptible groups and the resistant group. This was achieved using the Haploview program (27). Genotypes for all but one marker (rs2243250) were consistent with the Hardy-Weinberg equilibrium and no obvious genotyping errors were apparent; thus, the data for this marker were excluded from further analysis. Three markers were found to have no allelic variation in this population (rs2069743, rs2243231, and rs2243240).

Haplotype blocks were determined using the default method of Gabriel et al. (28) and are displayed schematically with their population frequencies and interblock connections based on the Haploview output (see Fig. 2). Linkage disequilibrium (LD) plots were also obtained and illustrate the estimated LD between SNPs, where dark grey regions depict strong LD (1.0) with strong confidence (logarithm of odds (LOD), >2.0), and pale grey and white regions represent low LD (<1.0) and state the LD value within the box.

The Haploview program was also used to test for association between the phenotypes and individual markers or combinations of markers (haplotypes). The p values were then corrected for multiple testing of all the SNPs and haplotypes within the region through 10,000 permutations. This adjusts the p values derived from multiple statistical tests to correct for the occurrence of false positives and provides region-wide empirical p values for each marker. “Local” significance therefore can be described as the probability that an association for a particular SNP marker is due to chance and concerns a single test of the null hypothesis of no linkage, whereas a “global” significance level is the probability that an association is detected within a given set of SNPs and involves sampling over a large number of tests to find the most significant result. This is achieved in Haploview by maintaining the individual genotype as a whole while the individual’s status is shuffled. The method preserves the correlation between SNPs (linkage disequilibrium) while breaking the relation between status and the genotypes. For each replicate or permutation, each SNP was tested for association and the most significant p value was stored. To assess the potential effect of each significant SNP on the risk of disease, logistic regression was performed to obtain odds ratios and 95% confidence intervals (CI). These compared the carriers of the minor allele to homozygous carriers of the major allele for each significant SNP.

Written ethical approval for this study was obtained at the national, provincial, and village levels within China, and approval for the study was granted by the ethics committees of the Jiangxi Provincial Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention and the Queensland Institute of Medical Research, before commencement. Study participants identified as stool egg-positive for schistosomiasis were treated with 40 mg/kg praziquantel, the current dosage recommended by the World Health Organization. Oral informed consent was obtained from all adults.

In total, 30 SNPs were genotyped spanning a region of 20 kb across the IL5 locus and a 24-kb region across the IL13 and IL4 genes (an average spacing of one SNP every 3.03 and 1.51 kb, respectively; Fig. 1). Genotypes were obtained for most individuals with a mean completion rate of 95.45%. The minor allele frequencies of the SNPs ranged from 0.011 to 0.477 (Tables I and II). In our study, we have investigated the 5q31–33 region of the human genome, more specifically, the IL-4, IL-5, and IL-13 genes. Across these loci we found little evidence of linkage disequilibrium between markers at different ends of the genes (Fig. 2). We chose SNPs across the 5q31–33 region using a SNP tagging strategy where representative SNPs were genotyped that had a high correlation (r2 > 0.8) with other known SNPs in these genes. Common variants increasing the risk of S. japonicum infection or symptomatic infection would be expected to show evidence of association with one or more of the tagging SNPs genotyped. We found evidence for association between S. japonicum infection and individual tagging SNPs in both IL-5 and IL-13 for allelic association tests. Tests of association between S. japonicum infection and haplotypes or combinations of SNPs also showed evidence for IL-5 variation contributing to risk of S. japonicum infection. However, all associations found with S. japonicum infection were not found to be significant when tested for global significance.

FIGURE 1.

Human IL5, IL-4, and IL-13 and the genomic structure of each gene showing the location of the tag SNPs genotyped.

FIGURE 1.

Human IL5, IL-4, and IL-13 and the genomic structure of each gene showing the location of the tag SNPs genotyped.

Close modal
Table II.

SNPs genotyped across the 5q31–33 region and associations with infection with S. japonicum

No.dbSNP IDaPositionGeneRoleAllelesFrequencyAssociation (χ2)p Value
rs4143832 131890876 IL-5  A/C 0.151 0.224 0.0926 
rs11739623 131892051 IL-5  C/T 0.38 0.426 0.2934 
rs2079103 131892405 IL-5  G/T 0.403 2.824 0.0197 
rs2706399 131895601 IL-5 3′-UTR A/G 0.153 4.251 0.0281 
rs17690122 131895734 IL-5 3′-UTR A/G 0.151 0.132 0.1156 
rs743562 131900282 IL-5 3′-UTR C/T 0.477 0.122 0.9351 
rs739718 131900972 IL-5 3′-UTR A/G 0.249 2.706 0.109 
rs2069812 131907815 IL-5 Promoter C/T 0.332 1.74 0.3275 
rs2057687 131915144 IL-5 Promoter A/G 0.144 2.611 0.0911 
10 rs1881457 132020308 IL-13 Promoter A/C 0.231 0.307 0.3118 
11 rs1800925 132020708 IL-13 Promoter C/T 0.167 0.047 0.4883 
12 rs2069744 132022568 IL-13 Intron C/T 0.096 0.641 0.1945 
13 rs1295686 132023742 IL-13 Intron (boundary) A/G 0.191 4.793 0.035 
14 rs20541 132023863 IL-13 Exon C/T 0.339 2.23 0.2745 
15 rs2069757 132026312 IL-13 Intron A/G 0.127 1.337 0.109 
16 rs1295683 132026775 IL-13 3′-UTR C/T 0.338 1.136 0.4566 
17 rs2243208 132029050 IL-13 3′-UTR A/G 0.141 1.438 0.0678 
18 rs2243211 132029321 IL-13 3′-UTR A/C 0.036 0.116 0.4634 
19 rs2243218 132029923 IL-13 3′-UTR A/G 0.041 0.263 0.4025 
20 rs2243300 132031985 IL-13 3′-UTR G/T 0.039 0.493 0.2784 
21 rs762534 132032655 IL-4 Promoter A/C/T 0.051 2.51 0.0667 
22 rs2243248 132036543 IL-4 Promoter G/T 0.057 0.064 0.6994 
23 rs17772853 132037489 IL-4 Exon C/T 0.012 0.107 0.6223 
24 rs2070874 132037609 IL-4 Exon C/T 0.188 0.245 0.899 
25 rs2227284 132040624 IL-4 Intron A/C 0.134 0.026 0.6849 
26 rs2243283 132044492 IL-4 Intron C/G 0.244 0.382 0.8302 
No.dbSNP IDaPositionGeneRoleAllelesFrequencyAssociation (χ2)p Value
rs4143832 131890876 IL-5  A/C 0.151 0.224 0.0926 
rs11739623 131892051 IL-5  C/T 0.38 0.426 0.2934 
rs2079103 131892405 IL-5  G/T 0.403 2.824 0.0197 
rs2706399 131895601 IL-5 3′-UTR A/G 0.153 4.251 0.0281 
rs17690122 131895734 IL-5 3′-UTR A/G 0.151 0.132 0.1156 
rs743562 131900282 IL-5 3′-UTR C/T 0.477 0.122 0.9351 
rs739718 131900972 IL-5 3′-UTR A/G 0.249 2.706 0.109 
rs2069812 131907815 IL-5 Promoter C/T 0.332 1.74 0.3275 
rs2057687 131915144 IL-5 Promoter A/G 0.144 2.611 0.0911 
10 rs1881457 132020308 IL-13 Promoter A/C 0.231 0.307 0.3118 
11 rs1800925 132020708 IL-13 Promoter C/T 0.167 0.047 0.4883 
12 rs2069744 132022568 IL-13 Intron C/T 0.096 0.641 0.1945 
13 rs1295686 132023742 IL-13 Intron (boundary) A/G 0.191 4.793 0.035 
14 rs20541 132023863 IL-13 Exon C/T 0.339 2.23 0.2745 
15 rs2069757 132026312 IL-13 Intron A/G 0.127 1.337 0.109 
16 rs1295683 132026775 IL-13 3′-UTR C/T 0.338 1.136 0.4566 
17 rs2243208 132029050 IL-13 3′-UTR A/G 0.141 1.438 0.0678 
18 rs2243211 132029321 IL-13 3′-UTR A/C 0.036 0.116 0.4634 
19 rs2243218 132029923 IL-13 3′-UTR A/G 0.041 0.263 0.4025 
20 rs2243300 132031985 IL-13 3′-UTR G/T 0.039 0.493 0.2784 
21 rs762534 132032655 IL-4 Promoter A/C/T 0.051 2.51 0.0667 
22 rs2243248 132036543 IL-4 Promoter G/T 0.057 0.064 0.6994 
23 rs17772853 132037489 IL-4 Exon C/T 0.012 0.107 0.6223 
24 rs2070874 132037609 IL-4 Exon C/T 0.188 0.245 0.899 
25 rs2227284 132040624 IL-4 Intron A/C 0.134 0.026 0.6849 
26 rs2243283 132044492 IL-4 Intron C/G 0.244 0.382 0.8302 
a

SNP database identifier.

FIGURE 2.

Haplotype blocks identified in each gene and LD plot of SNP estimated as r2 using Haploview for IL-5. SNP codes are provided in order of location along each gene; dark grey squares depict strong LD (1.0) with strong confidence (LOD > 2.0), pale grey and white regions represent low LD (<1.0), and the LD value is provided within each box. Plots based on Haploview output.

FIGURE 2.

Haplotype blocks identified in each gene and LD plot of SNP estimated as r2 using Haploview for IL-5. SNP codes are provided in order of location along each gene; dark grey squares depict strong LD (1.0) with strong confidence (LOD > 2.0), pale grey and white regions represent low LD (<1.0), and the LD value is provided within each box. Plots based on Haploview output.

Close modal

Investigation of allelic associations between symptomatic infection and individual tagging SNPs detected five significant SNPs: one in IL-13 and four in IL-5 (Table II), all of which belonged to the same haplotype block (Fig. 2). Of these, two SNPs in IL-5 (rs4143832 and rs17690122) remained significant after permutation tests (p = 0.025 and p = 0.019, respectively) and were in strong LD with each other (Fig. 2). Logistic regression provided an odds ratio of 2.3 (p = 0.004; CI = 1.30–4.01) and 2.25 (p = 0.005; CI = 1.27–4.00) for each SNP marker, respectively. Haplotype association tests also detected two significant haplotypes associated with symptomatic infection (Table III). Permutation tests showed a p value of 0.019 for one haplotype (Table IV).

Table III.

SNPs genotyped across the 5q31–33 region and associations with symptomatic S. japonicum infection

No.dbSNP IDaPositionGeneRoleAllelesFrequencyAssociation (χ2)p Value
rs4143832 131890876 IL-5  A/C 0.159 7.107 0.0014b 
rs11739623 131892051 IL-5  C/T 0.388 0.432 0.3621 
rs2079103 131892405 IL-5  G/T 0.402 2.292 0.0176 
rs2706399 131895601 IL-5 3′-UTR A/G 0.141 1.597 0.0237 
rs17690122 131895734 IL-5 3′-UTR A/G 0.16 8.073 0.0011b 
rs743562 131900282 IL-5 3′-UTR C/T 0.463 0.563 0.3908 
rs739718 131900972 IL-5 3′-UTR A/G 0.239 0.358 0.3587 
rs2069812 131907815 IL-5 Promoter C/T 0.328 1.744 0.6754 
rs2057687 131915144 IL-5 Promoter A/G 0.13 0.225 0.3338 
10 rs1881457 132020308 IL-13 Promoter A/C 0.251 0.569 0.0926 
11 rs1800925 132020708 IL-13 Promoter C/T 0.178 1.257 0.1183 
12 rs2069744 132022568 IL-13 Intron C/T 0.1 0.968 0.1092 
13 rs1295686 132023742 IL-13 Intron (boundary) A/G 0.337 0.019 0.1677 
14 rs20541 132023863 IL-13 Exon C/T 0.336 0.004 0.706 
15 rs2069757 132026312 IL-13 Intron A/G 0.14 0.1546 
16 rs1295683 132026775 IL-13 3′-UTR C/T 0.187 0.227 0.7437 
17 rs2243208 132029050 IL-13 3′-UTR A/G 0.151 0.935 0.0366 
18 rs2243211 132029321 IL-13 3′-UTR A/C 0.038 0.023 0.5867 
19 rs2243218 132029923 IL-13 3′-UTR A/G 0.042 0.07 0.4294 
20 rs2243300 132031985 IL-13 3′-UTR G/T 0.04 0.215 0.2961 
21 rs762534 132032655 IL-4 Promoter A/C/T 0.044 2.355 0.0978 
22 rs2243248 132036543 IL-4 Promoter G/T 0.059 0.119 0.5717 
23 rs17772853 132037489 IL-4 Exon C/T 0.011 1.015 0.3123 
24 rs2070874 132037609 IL-4 Exon C/T 0.193 1.135 0.3878 
25 rs2227284 132040624 IL-4 Intron A/C 0.136 1.13 0.3334 
26 rs2243283 132044492 IL-4 Intron C/G 0.232 2.401 0.5494 
No.dbSNP IDaPositionGeneRoleAllelesFrequencyAssociation (χ2)p Value
rs4143832 131890876 IL-5  A/C 0.159 7.107 0.0014b 
rs11739623 131892051 IL-5  C/T 0.388 0.432 0.3621 
rs2079103 131892405 IL-5  G/T 0.402 2.292 0.0176 
rs2706399 131895601 IL-5 3′-UTR A/G 0.141 1.597 0.0237 
rs17690122 131895734 IL-5 3′-UTR A/G 0.16 8.073 0.0011b 
rs743562 131900282 IL-5 3′-UTR C/T 0.463 0.563 0.3908 
rs739718 131900972 IL-5 3′-UTR A/G 0.239 0.358 0.3587 
rs2069812 131907815 IL-5 Promoter C/T 0.328 1.744 0.6754 
rs2057687 131915144 IL-5 Promoter A/G 0.13 0.225 0.3338 
10 rs1881457 132020308 IL-13 Promoter A/C 0.251 0.569 0.0926 
11 rs1800925 132020708 IL-13 Promoter C/T 0.178 1.257 0.1183 
12 rs2069744 132022568 IL-13 Intron C/T 0.1 0.968 0.1092 
13 rs1295686 132023742 IL-13 Intron (boundary) A/G 0.337 0.019 0.1677 
14 rs20541 132023863 IL-13 Exon C/T 0.336 0.004 0.706 
15 rs2069757 132026312 IL-13 Intron A/G 0.14 0.1546 
16 rs1295683 132026775 IL-13 3′-UTR C/T 0.187 0.227 0.7437 
17 rs2243208 132029050 IL-13 3′-UTR A/G 0.151 0.935 0.0366 
18 rs2243211 132029321 IL-13 3′-UTR A/C 0.038 0.023 0.5867 
19 rs2243218 132029923 IL-13 3′-UTR A/G 0.042 0.07 0.4294 
20 rs2243300 132031985 IL-13 3′-UTR G/T 0.04 0.215 0.2961 
21 rs762534 132032655 IL-4 Promoter A/C/T 0.044 2.355 0.0978 
22 rs2243248 132036543 IL-4 Promoter G/T 0.059 0.119 0.5717 
23 rs17772853 132037489 IL-4 Exon C/T 0.011 1.015 0.3123 
24 rs2070874 132037609 IL-4 Exon C/T 0.193 1.135 0.3878 
25 rs2227284 132040624 IL-4 Intron A/C 0.136 1.13 0.3334 
26 rs2243283 132044492 IL-4 Intron C/G 0.232 2.401 0.5494 
a

SNP database identifier.

b

Still significant after permutation test at a p < 0.05 level.

Table IV.

Haplotype blocks in the 5q31–33 region and associations with symptomatic S. japonicum infection

BlockHaplotypeCase Ratio; Control Ratioχ2 Valuep Value
Block 1     
 GTCTT 0.389 81.0:141.0; 105.0:151.0 1.028 0.3105 
 GCATT 0.226 49.0:173.0; 59.0:197.0 0.065 0.7983 
 TCATC 0.159 48.0:174.0; 28.0:228.0 10.15 0.0014a 
 GCCCT 0.157 25.0:197.0; 50.1:205.9 6.208 0.0127 
 GCCTT 0.065 17.0:205.0; 13.9:242.1 0.986 0.3206 
     
Block 2     
 AA 0.533 121.4:100.6; 133.1:122.9 0.345 0.5569 
 GA 0.232 44.1:177.9; 66.9:189.1 2.62 0.1055 
 GG 0.23 54.2:167.8; 55.8:200.2 0.469 0.4933 
     
Block 3     
 TG 0.645 141.0:81.0; 167.5:88.5 0.193 0.6603 
 CG 0.198 50.0:172.0; 44.5:211.5 1.99 0.1583 
 CA 0.157 31.0:191.0; 44.0:212.0 0.934 0.3338 
     
Block 4     
 AC 0.763 162.0:60.0; 202.9:53.1 2.608 0.1063 
 CT 0.174 45.0:177.0; 38.0:218.0 2.44 0.1183 
 CC 0.063 15.0:207.0; 15.1:240.9 0.152 0.6968 
     
Block 5     
 GG 0.652 147.0:75.0; 164.7:91.3 0.182 0.6694 
 AG 0.231 44.0:178.0; 66.3:189.7 2.463 0.1165 
 AA 0.117 31.0:191.0; 25.0:231.0 2.026 0.1546 
     
Block 6     
 TTTA 0.795 172.0:50.0; 208.0:48.0 1.037 0.3085 
 CCGG 0.145 33.7:188.3; 35.7:220.3 0.149 0.6996 
 CCTG 0.049 13.3:208.7; 10.2:245.8 0.985 0.321 
BlockHaplotypeCase Ratio; Control Ratioχ2 Valuep Value
Block 1     
 GTCTT 0.389 81.0:141.0; 105.0:151.0 1.028 0.3105 
 GCATT 0.226 49.0:173.0; 59.0:197.0 0.065 0.7983 
 TCATC 0.159 48.0:174.0; 28.0:228.0 10.15 0.0014a 
 GCCCT 0.157 25.0:197.0; 50.1:205.9 6.208 0.0127 
 GCCTT 0.065 17.0:205.0; 13.9:242.1 0.986 0.3206 
     
Block 2     
 AA 0.533 121.4:100.6; 133.1:122.9 0.345 0.5569 
 GA 0.232 44.1:177.9; 66.9:189.1 2.62 0.1055 
 GG 0.23 54.2:167.8; 55.8:200.2 0.469 0.4933 
     
Block 3     
 TG 0.645 141.0:81.0; 167.5:88.5 0.193 0.6603 
 CG 0.198 50.0:172.0; 44.5:211.5 1.99 0.1583 
 CA 0.157 31.0:191.0; 44.0:212.0 0.934 0.3338 
     
Block 4     
 AC 0.763 162.0:60.0; 202.9:53.1 2.608 0.1063 
 CT 0.174 45.0:177.0; 38.0:218.0 2.44 0.1183 
 CC 0.063 15.0:207.0; 15.1:240.9 0.152 0.6968 
     
Block 5     
 GG 0.652 147.0:75.0; 164.7:91.3 0.182 0.6694 
 AG 0.231 44.0:178.0; 66.3:189.7 2.463 0.1165 
 AA 0.117 31.0:191.0; 25.0:231.0 2.026 0.1546 
     
Block 6     
 TTTA 0.795 172.0:50.0; 208.0:48.0 1.037 0.3085 
 CCGG 0.145 33.7:188.3; 35.7:220.3 0.149 0.6996 
 CCTG 0.049 13.3:208.7; 10.2:245.8 0.985 0.321 
a

Still significant after permutation test at a p < 0.05 level.

The 5q31–33 region of the human genome contains genes encoding the IL-4, IL-5, and IL-13 cytokines that are known players in the Th2-type immune response. These have been shown to have prominent roles in human susceptibility to infection with several parasitic helminths including Ascaris, Trichuris, and hookworm (13, 14, 15, 16, 17). Moreover, combined segregation and linkage analysis identified this region to contain a susceptibility locus (SM1) controlling S. mansoni infection intensity, and polymorphisms in IL-13 have also been associated with infection susceptibility to S. hematobium (20) and susceptibility to severe malaria in Thailand (24). These cytokines act together to produce a proinflammatory response to schistosome infection characterized by increased eosinophil and IgE production (29, 30, 31) Such responses are typical of reactions to allergens and, as such, are commonly observed with asthma and allergy (32, 33, 34). Polymorphisms in these genes have also been associated with asthma and atopic dermatitis (34, 35, 36, 37, 38).

In this study, we investigated the relationship between this region of the genome and infection with S. japonicum. We detected two SNPs, one in IL-5 and one in IL-13, with allelic associations to infection susceptibility, but both associations did not withstand permutation testing, thus indicating that the associations could be due to chance. A major challenge underlying this study was that of precise phenotype definition; given the extensive levels of schistosomiasis control in China, it is becoming increasingly difficult to accurately determine the number of previous praziquantel drug treatments and infection diagnoses in schistosome-endemic communities. Consequently, we applied highly stringent criteria to identify putatively susceptible and resistant individuals as accurately as possible. This resulted in a relatively low number of susceptible and resistant individuals that limited the power of the study to detect discrete genetic associations with infection. The SNP identified in IL-5, however, belongs to the same haplotype block as the two SNPs that are associated with symptomatic S. japonicum infection and are in strong linkage disequilibrium with each other. The SNP detected in IL-13 has also been implicated in asthma and associated elevated IgE levels (39, 40). Further work to increase the sample size and investigate the potential biological implications of these SNPs on IL-5 and IL-13 expression would provide more insight into the potential role of these mutations in susceptibility to schistosome infection.

Symptomatic infection was also investigated in this study. This outcome of infection is typically seen in individuals experiencing their first schistosome infection, although symptoms can be present in those who have a sudden heavy exposure to the parasite and also among chronically infected individuals. There are many symptoms and variations in the clinical presentation of schistosome infection and disease, ranging from fever and eosinophilia to diffuse abdominal pain and hepatomegaly (2). The difference between infection and disease is frequently confused and often requires clarification. In this study we investigated symptomatic infection that we define as the manifestation of a hyperallergenic response to infection with S. japonicum diagnosed by a local doctor (who made a parasitological examination) and characterized by at least three of the following symptoms: high fever, weakness, loss of appetite, headache, and dizziness. We identified 113 individuals who had previously experienced symptoms associated with schistosome infection and were diagnosed by a local doctor at that time. Two SNPs within 15 kb downstream from IL-5 (one in the 3′-untranslated region (UTR)) were found to be globally significant (p < 0.05). They were in strong linkage disequilibrium with each other and belonged to the same haplotype block identified in Haploview (Fig. 2). The haplotype also showed an association after testing for global significance (p = 0.019), suggesting that variants in IL-5 could be contributing to the risk of symptomatic infection. Odds ratios and CI values obtained for both SNPs were similar, reflecting the high level of LD between the two markers and indicating that homozygous genotypes of the major allele are associated with a 2-fold decrease in the risk of having a symptomatic reaction if infected with S. japonicum. It has been shown previously in this population that symptomatic infection is strongly associated with reinfection (data not shown), indicating that those who had previously experienced a symptomatic reaction in response to infection were twice as likely to be reinfected (4).

Marked elevated levels of circulating serum IL-5 have been observed in individuals previously identified as putatively resistant to schistosome infection/reinfection (19, 41, 42), and IL-5-induced eosinophilia has shown to be a common symptom in acute schistosomiasis patients (2, 43, 44). Furthermore, IL-5 contributes to the immune response against various pathogens and infectious agents, including gastrointestinal helminths such as hookworms (16) and Trichuris (45). It is important to note, however, that the phenotype in this study could also be reflecting a genetic predisposition to hyperallergenic reactions and inflammatory responses that are associated with acute and chronic infection rather than susceptibility to schistosome infection per se. Other allergies, asthma, and other atopic syndromes may also be associated with these individuals predisposed to a symptomatic response to infection, and this merits further investigation.

It is noteworthy also that the two significant SNPs detected in this study may not be the cause of the association and that possible neighboring SNPs in strong LD with each other could be accounting for the association observed with symptomatic infection. However, the strong LD of these SNPs with each other and their location in the same haplotype block would suggest that the true infection-predisposing variant does lie in the 3′-UTR region of IL-5. Previous functional studies have shown that mutations in the 3′-UTR region can have an effect on mRNA stability or translational efficiency by interfering with the mRNA binding protein interaction (46, 47, 48).

This is the first study to investigate the genetics underlying susceptibility to S. japonicum infection. Despite the restricted sample size of this investigation, a significant association was observed implicating IL-5 with symptomatic infection with S. japonicum. Further work to increase the sample size and to replicate the study in populations in neighboring endemic provinces in China would provide further information on the role of IL-5 variants in determining the risk of S. japonicum infection. Rapid identification of those more predisposed to infection and/or a symptomatic reaction to infection would assist in minimizing the morbidity associated with S. japonicum infection, allow for more targeted treatment of susceptible individuals, and reduce overall costs to the individual and the to health care system in China.

The authors have no financial conflict of interest.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1

This study was supported by the National Institute of Allergy and Infectious Diseases (NIAID) (Tropical Medicine Research Center Grant 1 P 50AI-39461) and a National Health and Medical Research Council of Australia and Wellcome Trust (U.K.) International Collaborative Research Grants Scheme Award.

3

Abbreviations used in this paper: SNP, single nucleotide polymorphism; CI, confidence interval; LD, linkage disequilibrium; LOD, logarithm of odds; UTR, untranslated region.

1
Zhou, X. N., Q. W. Jiang, L. P. Sun, T. P. Wang, Q. B. Hong, G. M. Zhao, L. Y. Wen, Z. C. Ying, X. H. Wu, D. D. Lin.
2005
. Control and surveillance of schistosomiasis in China.
Chin. J. Schisto. Contr.
17
:
161
-165.
2
Ross, A. G., D. Vickers, G. R. Olds, S. M. Shah, D. P. McManus.
2007
. Katayama syndrome.
Lancet Infect. Dis.
7
:
218
-224.
3
Acosta, L. P., G. D. Aligui, W. U. Tiu, D. P. McManus, R. M. Olveda.
2002
. Immune correlate study on human Schistosoma japonicum in a well-defined population in Leyte, Philippines, I: assessment of ‘resistance’ versus ‘susceptibility’ to S. japonicum infection.
Acta Trop.
84
:
127
-136.
4
Ellis, M. K., Y. Li, Z. Rong, H. Chen, D. P. McManus.
2006
. Familial aggregation of human infection with Schistosoma japonicum in the Poyang Lake region, China.
Int. J. Parasitol.
36
:
71
-77.
5
Bethony, J., A. Gazzinelli, A. Lopes, W. Pereira, L. Alves-Oliveira, S. Williams-Blangero, J. Blangero, P. Loverde, R. Correa-Oliveira.
2001
. Genetic epidemiology of fecal egg excretion during Schistosoma mansoni infection in an endemic area in Minas Gerais, Brazil.
Mem. Inst. Oswaldo Cruz
96
: (Suppl.):
49
-55.
6
Bethony, J., J. T. Williams, J. Blangero, H. Kloos, A. Gazzinelli, B. Soares-Filho, L. Coelho, L. Alves-Fraga, S. Williams-Blangero, P. T. Loverde, R. Correa-Oliveira.
2002
. Additive host genetic factors influence fecal egg excretion rates during Schistosoma mansoni infection in a rural area in Brazil.
Am. J. Trop. Med. Hyg.
67
:
336
-343.
7
Abel, L., F. Demenais, A. Prata, A. E. Souza, A. Dessein.
1991
. Evidence for the segregation of a major gene in human susceptibility/resistance to infection by Schistosoma mansoni.
Am. J. Hum Genet.
48
:
959
-970.
8
Marquet, S., L. Abel, D. Hillaire, A. Dessein.
1999
. Full results of the genome-wide scan which localises a locus controlling the intensity of infection by Schistosoma mansoni on chromosome 5q31–q33.
Eur. J. Hum. Genet.
7
:
88
-97.
9
Marquet, S., L. Abel, D. Hillaire, H. Dessein, J. Kalil, J. Feingold, J. Weissenbach, A. J. Dessein.
1996
. Genetic localization of a locus controlling the intensity of infection by Schistosoma mansoni on chromosome 5q31–q33.
Nat. Genet.
14
:
181
-184.
10
Muller-Myhsok, B., F. F. Stelma, F. Guisse-Sow, B. Muntau, T. Thye, G. D. Burchard, B. Gryseels, R. D. Horstmann.
1997
. Further evidence suggesting the presence of a locus, on human chromosome 5q31–q33, influencing the intensity of infection with Schistosoma mansoni.
Am. J. Hum. Genet.
61
:
452
-454.
11
Finkelman, F. D., T. Shea-Donohue, J. Goldhill, C. A. Sullivan, S. C. Morris, K. B. Madden, W. C. Gause, J. F. Urban, Jr.
1997
. Cytokine regulation of host defense against parasitic gastrointestinal nematodes: lessons from studies with rodent models.
Annu. Rev. Immunol.
15
:
505
-533.
12
Gause, W. C., J. F. Urban, Jr, M. J. Stadecker.
2003
. The immune response to parasitic helminths: insights from murine models.
Trends Immunol/
24
:
269
-277.
13
Cooper, P. J., M. E. Chico, C. Sandoval, I. Espinel, A. Guevara, M. W. Kennedy, J. F. Urban, Jr, G. E. Griffin, T. B. Nutman.
2000
. Human infection with Ascaris lumbricoides is associated with a polarized cytokine response.
J. Infect. Dis.
182
:
1207
-1213.
14
Jackson, J. A., J. D. Turner, L. Rentoul, H. Faulkner, J. M. Behnke, M. Hoyle, R. K. Grencis, K. J. Else, J. Kamgno, M. Boussinesq, J. E. Bradley.
2004
. T helper cell type 2 responsiveness predicts future susceptibility to gastrointestinal nematodes in humans.
J. Infect. Dis.
190
:
1804
-1811.
15
Jackson, J. A., J. D. Turner, L. Rentoul, H. Faulkner, J. M. Behnke, M. Hoyle, R. K. Grencis, K. J. Else, J. Kamgno, J. E. Bradley, M. Boussinesq.
2004
. Cytokine response profiles predict species-specific infection patterns in human GI nematodes.
Int. J. Parasitol.
34
:
1237
-1244.
16
Quinnell, R. J., D. I. Pritchard, A. Raiko, A. P. Brown, M. A. Shaw.
2004
. Immune responses in human necatoriasis: association between interleukin-5 responses and resistance to reinfection.
J. Infect. Dis.
190
:
430
-438.
17
Turner, J. D., H. Faulkner, J. Kamgno, F. Cormont, J. Van Snick, K. J. Else, R. K. Grencis, J. M. Behnke, M. Boussinesq, J. E. Bradley.
2003
. Th2 cytokines are associated with reduced worm burdens in a human intestinal helminth infection.
J. Infect. Dis.
188
:
1768
-1775.
18
Al-Sherbiny, M., A. Osman, R. Barakat, H. El Morshedy, R. Bergquist, R. Olds.
2003
. In vitro cellular and humoral responses to Schistosoma mansoni vaccine candidate antigens.
Acta Trop.
88
:
117
-130.
19
Leenstra, T., L. P. Acosta, H. W. Wu, G. C. Langdon, J. S. Solomon, D. L. Manalo, L. Su, M. Jiz, B. Jarilla, A. O. Pablo, et al
2006
. T-helper-2 cytokine responses to Sj97 predict resistance to reinfection with Schistosoma japonicum.
Infect. Immun.
74
:
370
-381.
20
Kouriba, B., C. Chevillard, J. H. Bream, L. Argiro, H. Dessein, V. Arnaud, L. Sangare, A. Dabo, A. H. Beavogui, C. Arama, et al
2005
. Analysis of the 5q31–q33 locus shows an association between IL13–1055C/T IL-13–591A/G polymorphisms and Schistosoma haematobium infections.
J. Immunol.
174
:
6274
-6281.
21
Ross, A. G., L. Yuesheng, A. S. Sleigh, L. Yi, G. M. Williams, W. Z. Wu, L. Xinsong, H. Yongkang, D. P. McManus.
1997
. Epidemiologic features of Schistosoma japonicum among fishermen and other occupational groups in the Dongting Lake region (Hunan Province) of China.
Am. J. Trop. Med. Hyg.
57
:
302
-308.
22
Bugawan, T. L., D. B. Mirel, A. M. Valdes, A. Panelo, P. Pozzilli, H. A. Erlich.
2003
. Association and interaction of the IL4R, IL4, and IL13 loci with type 1 diabetes among Filipinos.
Am. J. Hum. Genet.
72
:
1505
-1514.
23
He, J. Q., M. Chan-Yeung, A. B. Becker, H. Dimich-Ward, A. C. Ferguson, J. Manfreda, W. T. Watson, A. J. Sandford.
2003
. Genetic variants of the IL13 and IL4 genes and atopic diseases in at-risk children.
Genes Immun.
4
:
385
-389.
24
Ohashi, J., I. Naka, J. Patarapotikul, H. Hananantachai, S. Looareesuwan, K. Tokunaga.
2003
. A single-nucleotide substitution from C to T at position−1055 in the IL-13 promoter is associated with protection from severe malaria in Thailand.
Genes Immun.
4
:
528
-531.
25
Wang, M., Z. M. Xing, C. Lu, Y. X. Ma, D. L. Yu, Z. Yan, S. W. Wang, L. S. Yu.
2003
. A common IL-13 Arg130Gln single nucleotide polymorphism among Chinese atopy patients with allergic rhinitis.
Hum. Genet.
113
:
387
-390.
26
Wei, C. L., W. Cheung, C. K. Heng, N. Arty, S. S. Chong, B. W. Lee, K. L. Puah, H. K. Yap.
2005
. Interleukin-13 genetic polymorphisms in Singapore Chinese children correlate with long-term outcome of minimal-change disease.
Nephrol. Dial. Transplant.
20
:
728
-734.
27
Barrett, J. C., B. Fry, J. Maller, M. J. Daly.
2005
. Haploview: analysis and visualization of LD and haplotype maps.
Bioinformatics
21
:
263
-265.
28
Gabriel, S. B., S. F. Schaffner, H. Nguyen, J. M. Moore, J. Roy, B. Blumenstiel, J. Higgins, M. DeFelice, A. Lochner, M. Faggart, et al
2002
. The structure of haplotype blocks in the human genome.
Science
296
:
2225
-2229.
29
Dutra, W. O., R. Correa-Oliveira, D. Dunne, L. F. Cecchini, L. Fraga, M. Roberts, A. M. Soares-Silveira, M. Webster, H. Yssel, K. J. Gollob.
2002
. Polarized Th2 like cells, in the absence of Th0 cells, are responsible for lymphocyte produced IL-4 in high IgE-producer schistosomiasis patients.
BMC Immunol.
3
:
8
30
Fitzsimmons, C. M., T. J. Stewart, K. F. Hoffmann, J. L. Grogan, M. Yazdanbakhsh, D. W. Dunne.
2004
. Human IgE response to the Schistosoma haematobium 22.6 kDa antigen.
Parasite Immunol.
26
:
371
-376.
31
McKenzie, G. J., P. G. Fallon, C. L. Emson, R. K. Grencis, A. N. McKenzie.
1999
. Simultaneous disruption of interleukin (IL)-4 and IL-13 defines individual roles in T helper cell type 2-mediated responses.
J. Exp. Med.
189
:
1565
-1572.
32
Balzar, S., M. Strand, D. Rhodes, S. E. Wenzel.
2007
. IgE expression pattern in lung: relation to systemic IgE and asthma phenotypes.
J. Allergy Clin. Immunol.
119
:
855
-862.
33
Holgate, S. T..
1999
. The epidemic of allergy and asthma.
Nature
402
:
B2
-B4.
34
Kabesch, M., M. Depner, I. Dahmen, S. K. Weiland, C. Vogelberg, B. Niggemann, S. Lau, T. Illig, N. Klopp, U. Wahn, et al
2007
. Polymorphisms in eosinophil pathway genes, asthma and atopy.
Allergy
62
:
423
-428.
35
Chiang, C. H., Y. C. Tang, M. W. Lin, M. Y. Chung.
2007
. Association between the IL-4 promoter polymorphisms and asthma or severity of hyperresponsiveness in Taiwanese.
Respirology
12
:
42
-48.
36
Hosseini-Farahabadi, S., J. Tavakkol-Afshari, H. Rafatpanah, R. Farid Hosseini, M. Khaje Daluei.
2007
. Association between the polymorphisms of IL-4 gene promoter (−590C>T), IL-13 coding region (R130Q) and IL-16 gene promoter (−295T>C) and allergic asthma.
Iran J. Allergy Asthma Immunol.
6
:
9
-14.
37
Nagarkatti, R., R. Kumar, S. K. Sharma, B. Ghosh.
2004
. Association of IL4 gene polymorphisms with asthma in North Indians.
Int. Arch. Allergy Immunol.
134
:
206
-212.
38
Noguchi, E., M. Shibasaki, T. Arinami, K. Takeda, Y. Yokouchi, T. Kawashima, H. Yanagi, A. Matsui, H. Hamaguchi.
1998
. Association of asthma and the interleukin-4 promoter gene in Japanese.
Clin. Exp. Allergy
28
:
449
-453.
39
Maier, L. M., J. M. Howson, N. Walker, G. P. Spickett, R. W. Jones, S. M. Ring, W. L. McArdle, C. E. Lowe, R. Bailey, F. Payne, et al
2006
. Association of IL13 with total IgE: evidence against an inverse association of atopy and diabetes.
J. Allergy Clin. Immunol.
117
:
1306
-1313.
40
Sadeghnejad, A., W. Karmaus, S. Hasan Arshad, S. Ewart.
2007
. IL13 gene polymorphism association with cord serum immunoglobulin E.
Pediatr. Allergy Immunol.
18
:
288
-292.
41
Medhat, A., M. Shehata, K. Bucci, S. Mohamed, A. D. Dief, S. Badary, H. Galal, M. Nafeh, C. L. King.
1998
. Increased interleukin-4 and interleukin-5 production in response to Schistosoma haematobium adult worm antigens correlates with lack of reinfection after treatment.
J. Infect. Dis.
178
:
512
-519.
42
Rodrigues, V., Jr, K. Piper, P. Couissinier-Paris, O. Bacelar, H. Dessein, A. J. Dessein.
1999
. Genetic control of schistosome infections by the SM1 locus of the 5q31–q33 region is linked to differentiation of type 2 helper T lymphocytes.
Infect. Immun.
67
:
4689
-4692.
43
Bierman, W. F., J. C. Wetsteyn, T. van Gool.
2005
. Presentation and diagnosis of imported schistosomiasis: relevance of eosinophilia, microscopy for OVA, and serology.
J. Travel Med.
12
:
9
-13.
44
de Jesus, A. R., A. Silva, L. B. Santana, A. Magalhaes, A. A. de Jesus, R. P. de Almeida, M. A. Rego, M. N. Burattini, E. J. Pearce, E. M. Carvalho.
2002
. Clinical and immunologic evaluation of 31 patients with acute Schistosomiasis mansoni.
J. Infect. Dis.
185
:
98
-105.
45
Bradley, J. E., J. A. Jackson.
2004
. Immunity, immunoregulation and the ecology of trichuriasis and ascariasis.
Parasite Immunol.
26
:
429
-441.
46
Akagawa, H., A. Tajima, Y. Sakamoto, B. Krischek, T. Yoneyama, H. Kasuya, H. Onda, T. Hori, M. Kubota, T. Machida, et al
2006
. A haplotype spanning two genes. ELN and LIMK1, decreases their transcripts and confers susceptibility to intracranial aneurysms.
Hum. Mol. Genet.
15
:
1722
-1734.
47
Bertram, L., M. Parkinson, M. B. McQueen, K. Mullin, M. Hsiao, R. Menon, T. J. Moscarillo, D. Blacker, R. E. Tanzi.
2005
. Further evidence for LBP-1c/CP2/LSF association in Alzheimer’s disease families.
J. Med. Genet.
42
:
857
-862.
48
Day, D. A., M. F. Tuite.
1998
. Post-transcriptional gene regulatory mechanisms in eukaryotes: an overview.
J. Endocrinol.
157
:
361
-371.