Association between human African trypanosomiasis and the IL6 gene in a Congolese population

Infection, Genetics and Evolution 7 (2007) 60–68 www.elsevier.com/locate/meegid

Association between human African trypanosomiasis and the IL6 gene in a Congolese population David Courtin a,*, Jacqueline Milet a, Vincent Jamonneau b, Claude Sese Yeminanga c, Victor Kande Betu Kumeso c, Constantin Miaka Mia Bilengue d, Christine Betard e, Andre´ Garcia f a

Institut de Recherche pour le De´veloppement (IRD), Unite´ de recherche 010: Sante´ de la me`re et de l’enfant en milieu tropical, Faculte´ de pharmacie, 4 Avenue de l’observatoire, 75270 Paris, France b Institut de Recherche pour le De´veloppement (IRD), Unite´ de recherche 177: relations hoˆtes vecteurs parasites dans les trypanosomoses, Campus International de Baillarguet, TA207/G, 34398 Montpellier Cedex 5, France c Programme National de Lutte contre la Trypanosomiase Humaine Africaine, s/c Ministe`re de la Sante´, Boulevard du 30 juin no. 4310, Commune de la Gombe, BP 3088, Kinshasa, Re´publique De´mocratique du Congo d Ministe`re de la Sante´, Boulevard du 30 juin no. 4310, Commune de la Gombe, BP 3088, Kinshasa, Re´publique De´mocratique du Congo e Centre National de Ge´notypage, 2 rue Gaston Cre´mieux, BP 5721, 91057 Evry, France f Institut de Recherche pour le De´veloppement (IRD), Unite´ de recherche 010: Sante´ de la me`re et de l’enfant en milieu tropical, 08 BP 841 Cotonou, Benin Received 9 January 2006; received in revised form 31 March 2006; accepted 1 April 2006 Available online 23 May 2006

Abstract Despite the importance of behavioural and environmental risk factors, there are arguments consistent with the existence of a genetic susceptibility to human African trypanosomiasis (HAT). A candidate gene association study was conducted in the Democratic Republic of Congo using a family-based sample which included a total of 353 subjects (86 trios; one case and parents (n = 258) and 23 families with more than one case and parents (n = 95)). Polymorphisms located on the IL1a, IL4, IL6, IL8, IL10, TNFa and IFNg genes were genotyped after re-sequencing of the genes for extensive SNP search. The T allele of the IL64339 SNP was significantly associated with a decreased risk of developing the disease ( p = 0.0006) and a suggestive association was observed for the IL1a5417 T SNP and an increased risk of developing the disease. These results suggest that genetic variability of the IL6 and to a lesser extent the IL1a gene are involved in the development of HAT. For the TNFa and IL10 gene polymorphisms, association results obtained here were different from those we observed in another population living under different epidemiologic conditions. This underlines the complexity of the interactions existing between host genetic polymorphisms, parasite diversity and behavioural and environmental risk factors in HAT. # 2006 Elsevier B.V. All rights reserved. Keywords: Association study; FBAT; Interleukin; Trypanosoma brucei gambiense; Human African trypanosomiasis; Human genetics; Human susceptibility

1. Introduction Human African trypanosomiasis (HAT), or sleeping sickness, occurs in two classical forms: the chronic form caused by Trypanosoma brucei gambiense (Tbg) in western and central Africa and the acute form caused by Trypanosoma brucei rhodesiense (Tbr) in eastern Africa. Chronic infection classically lasts for years, whilst acute infection lasts only for weeks or months. After inoculation, parasites first grow in

* Corresponding author. Tel.: +33 1 53 73 96 21; fax: +33 1 53 73 96 17. E-mail address: [email protected] (D. Courtin). 1567-1348/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.meegid.2006.04.001

blood and lymph (the first period or haemolymphatic stage), and then cross the blood–brain barrier (BBB) to reach the central nervous system (CNS) (the second period or meningoencephalitic stage). Without treatment, the disease outcome is fatal. HAT diagnosis cannot be based only on clinical presentation and imply the detection of the parasite by means of biological methods. A first group of methods (serological tests) is based on the detection of antibodies against trypanosomes in peripheral blood and is completed by a second group of methods (parasitological tests) relying on the finding of trypanosomes in blood, lymphatic juice or cerebrospinal fluid (CSF). Only subjects with positive serology and parasitology are diagnosed as HAT cases and treated

D. Courtin et al. / Infection, Genetics and Evolution 7 (2007) 60–68

(WHO, 1998). Apart from the Tbg classical form, diversity in clinical progression has been observed, from very chronic and asymptomatic forms (Jamonneau et al., 2000) to acute forms (Truc et al., 1997). The respective roles of either the virulence of the parasite or the host susceptibility in this clinical diversity remain unclear (Jamonneau et al., 2002). Experimental models of infection in mice indicate that African trypanosomes trigger potent inflammatory responses, and it has been suggested that survival is determined by the ability of different inbred strains to regulate inflammatory pathology (Namangala et al., 2001). Genetic factors implicated in the control of immunity could be involved in both the control of infection levels and the mortality rates, as clearly shown for Trypanosoma congolense infections in experimental models (Kemp et al., 1997; Iraqi et al., 2000). In these studies, the authors identified chromosomal regions determining resistance to T. congolense infection on murine chromosomes 1, 5 and 17. The interleukin (IL)10 and tumor necrosis factor (TNF)a genes are located within two of these three identified chromosomal regions, respectively, on chromosomes 1 and 17 of the mouse. Considering the involvement of both TNFa and IL10 in the physiopathology of HAT (cf. bellow), this result represents an additional argument consistent with the importance of these genes and making them possible candidate genes for the control of trypanosome infections. In humans, indirect arguments exist for individual susceptibility such as familial aggregation, although the role of a shared environment has been put forward (Okia et al., 1994; Khonde et al., 1995). More recently, epidemiological observations have allowed us to suggest the potential role of genetic factors involved in the control of immunity, in the diversity of clinical presentations and the progression of HAT (Jamonneau et al., 2000; Garcia et al., 2000, 2002). Indirect arguments also come from immunological studies conducted in human populations. Among the effectors of the immune responses that are likely to play an important role in the pathogenesis of the disease, cytokines such as IL6, IL8, IL10, TNFa and interferon (IFN)g have already been described (OkomoAssoumou et al., 1995; Rhind et al., 1997; MacLean et al., 2001, 2004; Lejon et al., 2002; Courtin et al., 2006a). Concerning IL6, IL8 and IL10, the effect of HAT treatment on their levels in both CSF and plasma strengthen their importance, although their roles remain unclear (Lejon et al., 2002). Chronic exposure to the disease seems to disrupt the normal physiologic equilibrium between TNFa and IL10, consistent with the fact that TNFa and IL10 seem to be either beneficial or detrimental (for a review, see Dumas et al., 1999). Concerning IFNg MacLean et al. (2004) have shown that in plasma, IFNg levels significantly decreased during the second period of the disease. The crossing of the BBB and the invasion of CNS by trypanosomes is a complex phenomenon involving IL1, IL6 and TNFa (De Vries et al., 1996; Lejon et al., 2002; Girard et al., 2005). There is now cumulative evidence that polymorphisms of genes involved in the control of immune response could play a role in HAT (MacLean et al., 2004; Courtin et al., 2006b).

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Genetic investigation of cytokine genes could then provide a better understanding of the underlying immunological mechanisms involved in HAT pathogenesis, leading ultimately to more effective therapeutic and prophylactic control modalities. Recently, we conducted an association study in Coˆte d’Ivoire (IC) showing that TNFa308 G/A single nucleotide polymorphism (SNP) was associated with a higher risk of developing the disease, whereas the IL10592 C/A SNP was associated with a lower risk (Courtin et al., 2006b). In the investigation reported herein, our aim was to study the role of single nucleotide polymorphisms of TNFa, IL10, IL1a, IL4, IL6, IL8 and IFNg genes on susceptibility/resistance to HAT by means of a family-based association study conducted on a different population (all individuals were native from the area and belonged to the same ethnic group in the present study) living under different exposure conditions (prevalence of HAT around 1% in IC (Laveissie`re et al., 2003)) and around 15% in some villages of the Bandundu focus (National Control Program, personal communication). 2. Materials and methods 2.1. Population and study design The study took place in Bandundu province of the Democratic Republic of Congo (DRC). All patients enrolled in this study signed an informed consent form and the protocol was approved by local traditional authorities (chief and village committee) and by the local ethical committee of DRC (Public Health Ministry). HAT patients included in the study were diagnosed during active and passive surveys conducted by the National Control Programme (NCP), using their classical detection protocol. For serology, the Card Agglutination Test for Trypanosomiasis (CATT) (Magnus et al., 1978) was performed on whole blood, and trypanosomes were detected in positive CATT individuals, using direct microscopic examination of blood or lymphatic juice when swollen lymph nodes were present. Cases are defined as subjects presenting both serological and parasitological positive tests. Basically, an association study compares the frequencies of genetic polymorphisms between cases and controls. To avoid population admixture that can lead to false associations, familybased association methods have been developed such as the transmission disequilibrium test (TDT) (Spielman et al., 1993). The sampling units in these methods consist of an affected child and his parents or unaffected siblings. Extensions are now available which able to include a larger type of sample units including nuclear family with several affected children. Our population study consisted in 353 individuals, 135 HAT cases and 218 related controls. This group of 353 individuals was constituted by 86 trios composed of one case and parents (n = 258), 20 nuclear families with two cases and parents (n = 80) and 3 nuclear families with three cases and parents (n = 15). All individuals, from the Yansi ethnic group, were born in the area and had been exposed to the risk of infection since their birth.

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Table 1 Primers and probes used in the TaqMan PCR assay SNP

A1/A2 Primer name

Primer

RD

IL1a 889

C/T

IL1a 2097

Probe

RQ

IL1a 889F IL1a 889R

GGCCACAGGAATTATAAAAGCTGAGA GGGAGAAAGGAAGGCATGGATTTT

VIC CCTTCAATGGTGTTGCC FAM CCTTCAATGATGTTGCC

NFQ NFQ

C/T

IL1a 2097F IL1a 2097R

CGCTTCACCAGGTGTCTGT TCTAACCTCTGATGCTGGTGTCA

VIC AACACATCACGTTAGGAG FAM AACACATCACATTAGGAG

NFQ NFQ

IL1a 4716

A/C

IL1a 4716F IL1a 4716R

TGGGTGATTTCACTTCTCTTTGCTT CACAGTCTAGTACAAACAGGGAAAATAGT

VIC TCTGGATTGGAATATT FAM ATCTGGATTGGCATATT

NFQ NFQ

IL1a 5417

C/T

IL1a 5417F IL1a 5417R

AGTCTGTTGATCAAACTCACAAGTAACA GGAGGTTTTGCCTCACAAATATGTT

VIC ATAAAGATCTTCCTGGTTTGG FAM ATAAAGATCTTCCTAGTTTGG

NFQ NFQ

IL4 33

T/C

IL4 33F IL4 33R

ATTGCATCGTTAGCTTCTCCTGAT ACCCATTAATAGGTGTCGATTTGCA

VIC ACAATGTGAGACAATTA FAM ACAATGTGAGGCAATTA

NFQ NFQ

IL4 110

A/G

IL4 110F IL4 110R

GTCTCACCTCCCAACTGCTT CTGTAAGGTGATATCGCACTTGTGT

VIC TTCCTGCTAGCATGTG FAM CCTGCTGGCATGTG

NFQ NFQ

IL4 8492

C/A

IL4 8492F IL4 8492R

AGTGCCACAGTAGGCTTGATC CTCTGGTTGGCTTCCTTCACA

VIC TCTGCAAAAGAAACATT FAM TTCTGCAAAATAAACATT

NFQ NFQ

IL6 320

C/T

IL6 320F IL6 320R

GGGCTGCTCCTGGTGTT GGCGGCTACATCTTTGGAATCTT

VIC CCCAGTACCCCCAGGAG FAM CCCAGTACCCTCAGGAG

NFQ NFQ

IL6 1890

G/T

IL6 1890F IL6 1890R

GTCAAATGTTTAAAACTCCCACAGGTT GCAGCCAGAGAGGGAAAAGG

VIC CCCTGCGAGTACCTT FAM CCCTGAGAGTACCTT

NFQ NFQ

IL6 4339

C/T

IL6 4339F IL6 4339R

TCATCTCATTCTGCGCAGCTTTA CCATGCTACATTTGCCGAAGAG

VIC CTGCAGGAACTCCT FAM CTGCAGAAACTCCT

NFQ NFQ

IL8 251

A/T

IL8 251F IL8 251R

TCTGTCACATGGTACTATGATAAAGTTATCTAGAAAT CGGAGTATGACGAAAGTTTTCTTTGATC

VIC AAGCATACAATTGATAATT FAM AGCATACATTTGATAATT

NFQ NFQ

IL8 102

T/C

IL8 102F IL8 102R

GACAAGAGCCAGGAAGAAACCA CAGGAAGGCTGCCAAGAGA

VIC CTTGGAAGTCATATTTACA FAM TTGGAAGTCATGTTTACA

NFQ NFQ

IL8 396

G/T

IL8 396F IL8 396R

CACTTAGGAAAGTATAAAGGTTTGATCAATATAGATATTCTG VIC AAATATATGCATGCTACCTGGTAT NFQ ACCGTGGTTCTCAATAGGACATACTA FAM ATGCATGCTACATGGTAT NFQ

IL10 592

C/A

IL10 592F IL10 592R

GGTAAAGGAGCCTGGAACACATC GCCCTTCCATTTTACTTTCCAGAGA

VIC CCCGCCTGTCCTGTAG FAM CCGCCTGTACTGTAG

NFQ NFQ

IL10 435

C/T

IL10 435F IL10 435R

ATGATACAGTAAATGTGCAGGAAACCT CGCCAGCAGGATCTTATAAGTTTCT

VIC CACGAGAGAGAACG FAM CACGAGAAAGAACG

NFQ NFQ

TNFa 863 C/A

TNFa 863F GTAGGAGAATGTCCAGGGCTATG TNFa 863R CCCTCTACATGGCCCTGTCT

VIC ACCCCCCCTTAACG FAM CCCCCACTTAACG

NFQ NFQ

TNFa 376 G/A

TNFa 376F CCCCTCCCAGTTCTAGTTCTATCTT TNFa 376R CCTCAAAACCTATTGCCTCCATTTC

VIC CTGTCTGGAAGTTAGAAG FAM CTGTCTGGAAATTAGAAG

NFQ NFQ

TNFa 308 G/A

TNFa 308F CCAAAAGAAATGGAGGCAATAGGTT TNFa 308R GGACCCTGGAGGCTGAAC

VIC CCCGTCCCCATGCC FAM CCCGTCCTCATGCC

NFQ NFQ

IFNg 183

G/T

IFNg 183F IFNg 183R

GGGCATAATGGGTCTGTCTCAT GGCATTTGGGTGTTGTAGTTAGAGT

VIC CTTGGGTCCTTTGACG FAM TTGGGTCATTTGACG

NFQ NFQ

IFNg 4565

C/T

IFNg 4565F IFNg 4565R

GACTCATCAATCAAATAAGTATTTATAATAGCAACTTTTGT CACATAGCCTTGCCTAATTAGTCAGA

VIC ACAGTCACAGGATATAG FAM CAGTCACAAGATATAG

NFQ NFQ

IFNg 5003

C/T

IFNg 5003F IFNg 5003R

ACAACTACTTATGCTGTGTTGGACTT GAAGACTCCCCTCCCTACTAATTCA

VIC TCACTCCAGGTCTCAC FAM CACTCCAGATCTCAC

NFQ NFQ

IFNg 5295

A/G

IFNg 5295F IFNg 5295R

TTCTAGCCCCTTCTCCACCTT AGCATTGGATGAGGGAGAGGAA

VIC CTCCTTCATTTCAGAATC FAM CCTTCGTTTCAGAATC

NFQ NFQ

A1/A2, allele 1/allele2. RD, reporter dye at the 50 end of each probe (VIC dye is linked to the allele 1 probe and FAM dye linked to the allele 2 probe). RQ, reporter quencher at the 30 end of the probe; NFQ, non-fluorescent quencher.

2.2. SNP discovery SNP discovery using re-sequencing (Vasilescu et al., 2003) was performed to detect IL1a, IL4, IL6, IL8, IL10, TNFa and

IFNg gene polymorphisms in 16 healthy individuals and 16 affected individuals, randomly selected, among those included in our study. DNAs from the coding sequence, exon flanking regions and promoter regions of these genes were amplified by

D. Courtin et al. / Infection, Genetics and Evolution 7 (2007) 60–68

PCR. The PCRs were carried out in a 15 ml reaction mixture containing 25 ng of DNA. The list of each gene’s primer is available on the web site of the Centre National de Ge´notypage (CNG), France (www.cng.fr). DNA amplified fragments were purified with Bio-Gel P-100 (Bio-Rad1) and sequencing reactions were achieved using BigDye Terminator Mix (Applied Biosystems1). The reaction solutions were purified using G50 Sephadex resin (Amersham Pharmacia Biotech AB) and subsequently analysed using an ABI PRISM 3700 DNA Analyser (Applied Biosystems1). We compared sequences using Genalys software developed by CNG (Takahashi et al., 2002) in order to identify SNPs and estimate their frequency in our study population. 2.3. SNP genotyping SNPs were genotyped using TaqMan primers and probes (Applied Biosystems1). The allelic discrimination was based on the design of two TaqMan probes, specific for the wildtype allele and the mutant allele. One allelic probe was labelled with the FAM dye and the other with the fluorescent VIC dye. The sequences of the primers and allele-specific probes used in the TaqMan assays are shown in Table 1. The TaqMan PCR reactions were done according to the instructions provided with the kit using 3 ng of genomic DNA and were analysed in a 7900HT Sequence Detection System (Applied Biosystems1) with Applied Biosystems1 Genotyper software (SDS system, Version 2.0).

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3. Results The mean age (range) of HAT cases in the population study was 14.69 (2–39) years. The sex ratio (male:female) was 0.65 (53/82). Ninety-nine SNPs were identified after re-sequencing the candidate genes in individuals from the Congolese population: 32 in IL1a, 5 in IL4, 17 in IL6, 10 in IL8, 9 in IL10, 16 in TNFa and 10 in IFNg (Fig. 1). Among these 99 SNPs, 22 were selected for larger-scale genotyping based on location (SNPs in promotor and exons were preferred), linkage disequilibrium (SNPs that were not in complete LD with each other were selected), and allele frequencies greater than 5% except for TNFa308 G/A (Fig. 1). For this last SNP, the allele frequency was 3%, but its potential involvement in susceptibility/ resistance to the disease argued for keeping it in the analysis. Information on selected SNPs is shown in Table 2. Statistical analysis revealed that all studied polymorphisms were in Hardy–Weinberg equilibrium in our population sample. The family-based association study results are shown in Table 3. Nominal p-values (not adjusted for multiple testing) <0.05 were found for three SNPs: IL64339 C/T, IL1a5417 C/T and IL10592 C/A. Under a dominant model, the IL64339 T allele was less transmitted from heterozygote parents to affected offspring ( p = 0.0006), consistent with a protective effect. The IL1a5417 C/T polymorphism showed an excess transmission ( p = 0.009) of the rare allele from parents to affected offspring, suggesting an increased risk of developing the disease. A weak trend ( p = 0.043) was observed for an association between the

2.4. Statistical analysis The Spearman Chi-square test was used to compare the frequencies of observed and expected genotypes under Hardy– Weinberg equilibrium, using STATA software (StataCorp 1999, Release 6.0). Haplotypes and their frequencies were estimated with the EM algorithm (Laird, 1993). We tested for an association of individual SNPs with HAT using the family-based association test (FBAT) programme (Horvath et al., 2001), and for haplotypes, using the haplotype extension (HBAT) of the FBAT programme (Horvath et al., 2004). The bi-allelic mode was used to test each haplotype (specific haplotype) and the multiallelic mode was used to test the global haplotype. The global haplotype tests all haplotypes simultaneously and computes a large sample Chi-square statistic. To ensure its validity as a test of association in the pedigree, the FBAT statistic was calculated using empirical variance (the – e option) in single-locus and haplotype analyses. As we have no information about the relevant genetic model, the three possible genetic models were used for analysis: additive, dominant and recessive (only results for the model with the lowest p-value was presented here). Then, we took into account for the adjustment of the significance level the fact that we tested three models for each polymorphism. As 22 polymorphisms were tested, adjusting for multiple testing by Bonferroni correction means that the association for a single marker has to be significant at a = 0.05/(22  3) = 0.0008 to achieve an overall significance of 0.05.

Table 2 Results of SNP discovery and information on the SNPs selected for testing association Genes

Chromosome location

Detected SNPs

Selected SNPs

SNPs location

Amino acid change

IL1a

2q14

32

889 2097 4716 5417

Promotor Intron 3 Intron 4 Intron 5

– – – –

IL4

5q31.1

5

33 110 8492

Exon 1 Exon 1 Intron 3

50 UTR Leu15Leu –

IL6

7p21

17

320 1890 4339

Exon 2 Intron 3 Exon 5

Ser32Pro – Phe201Phe

IL8

4q12-q13

10

251 102 396

Promotor Exon 1 Intron 1

– 50 UTR –

IL10

1q31-q32

9

592 435

Promotor Intron 1

– –

TNFa

6p21.3

16

863 376 308

Promotor Promotor Promotor

– – –

IFNg

12q14

10

183 4565 5003 5295

Promotor Exon 4 Intron 4 Intron 4

– 30 UTR – –

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Fig. 1. Gene maps and haplotypes of the seven cytokine genes investigated in the study. Coding exons are marked by black blocks, and 50 and 30 UTRs by white blocks. Asterisks indicate polymorphisms genotyped in a larger population. The regions that have been sequenced are shown by a horizontal line below each gene. Haplotypes with frequencies >0.05 (excepted for TNFa) are shown for all SNPs. A1 and A2 corresponded to the frequent and rare allele, respectively.

D. Courtin et al. / Infection, Genetics and Evolution 7 (2007) 60–68

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Table 3 Family-based association test results Gene

SNP

Alleles

Fq

No. of familiesa

Modelb

Observed valuec

Expected valued

IL1a

889

T C

0.413 0.587

37

d

30.000

28.000

0.603

0.546

2097

T C

0.373 0.627

50

d

31.000

33.056

0.543

0.587

4716

C A

0.295 0.705

42

d

24.000

25.917

0.529

0.596

5417

T C

0.194 0.806

37

d

35.000

25.333

2.612

0.009

33

C T

0.515 0.485

44

a

54.000

50.000

0.929

0.353

110

G A

0.169 0.831

35

a

29.000

22.500

1.786

0.074

8492

A C

0.439 0.561

47

a

45.000

50.000

1.211

0.226

320

T C

0.066 0.934

20

d

16.000

12.500

1.460

0.144

1890

T G

0.318 0.682

55

d

34.000

38.658

1.160

0.245

4339

T C

0.143 0.857

34

d

10.000

20.750

3.410

0.0006

251

T A

0.159 0.841

4

r

2.000

1.778

0.183

0.855

102

T C

0.242 0.758

19

r

16.000

18.167

0.686

0.492

396

T G

0.508 0.492

34

r

28.000

23.000

1.873

0.061

592

A C

0.451 0.549

45

d

41.000

33.444

2.021

0.043

435

T C

0.293 0.707

41

d

29.000

28.778

0.065

0.948

863

A C

0.098 0.902

24

a

14.000

18.333

1.363

0.173

376

A G

0.047 0.953

9

a

5.000

6.500

0.655

0.512

308

A G

0.154 0.846

25

a

19.000

18.167

0.288

0.773

183

T G

0.040 0.960

7

a

3.000

4.000

0.632

0.527

4565

T C

0.085 0.915

20

a

9.000

11.500

0.928

0.353

5003

T C

0.051 0.949

11

a

7.000

6.500

0.243

0.808

5295

G A

0.140 0.860

32

a

22.000

24.667

0.783

0.433

IL4

IL6

IL8

IL10

TNFa

IFNg

a

pe

Z

Number of informative families (i.e. families with at least one heterozygous parent). Genetic model (a = additive, d = dominant and r = recessive). The three genetic models were tested for each SNPs, only the more relevant one was presented. c Number of transmitted alleles observed. d Expected value of transmitted alleles under the null hypothesis. e Nominal p-value; in bold = p-value remaining significant after Bonferroni correction; significance level retained after correction (66 tests (22 SNPs  3 models)): 0.0008. b

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Table 4 Genetic association between IL6 haplotype and HAT Gene

IL6

Haplotype a

H1: H2: H3: H4:

CGC CTC CTT TGC

Frequencyb

0.636 0.175 0.125 0.064

Global haplotypef FBAT

Specific haplotype FBAT No. of familiesc

Observed valued

Expected valuee

Z

p

x2(d.f.)

p

24 34 31 19

78.000 37.000 15.000 19.000

75.250 32.667 23.167 16.000

1.026 1.371 2.726 1.279

0.305 0.170 0.006 0.201

10.243 (4)

0.036

a These haplotypes correspond to the combination of the SNPs listed in Table 3: 320C/T, 1890G/T, 4339C/T for the IL6 gene. The polymorphism 4339C/T (in bold in haplotype column) is the one previously found significantly associated. b EM estimates haplotype frequency. c Number of informative families (i.e. families with at least one heterozygous parent). d Number of transmitted haplotypes observed. e Expected value of transmitted haplotypes under the null hypothesis. f Global haplotype tests all haplotypes simultaneously and computes a large sample Chi-square statistic.

IL10592 C/A polymorphism and an increased risk of HAT. However, the only association that remained significant after Bonferroni correction concerned the IL64339 C/T SNP. No association between all other polymorphisms and the disease was found, including TNFa308 G/A, which we found associated with a higher risk of developing the disease in IC. Haplotypes were analysed and a statistically significant association was found between IL6 H3 and the disease ( p = 0.034 using a global haplotypic test). This haplotype corresponds to the combination of 320C/T, 1890G/T and 4339C/T for the IL6 gene. Results are summarized in Table 4. The IL6 H3 haplotype presented a frequency of 0.125 and was less transmitted from parents to affected offspring than expected under the null hypothesis of absence of association ( p = 0.006). This haplotype is the only one harbouring the T allele at the IL64339 locus, consistent with the results obtained with the IL64339 T allele alone. For the IL1a, IL4, IL8, IL10, TNFa and IFNg genes, no haplotype was significantly associated with the disease. 4. Discussion In this study, 22 SNPs in seven cytokine genes were investigated to test genetic association with HAT in a Congolese population. Our main finding is that the IL64339 T allele is significantly associated with a lower risk of developing the disease. The trend obtained with the IL1a5417 C/T polymorphism, and to a lesser extent IL10592 C/A, must be considered with interest but needs further confirmation in other populations. The IL64339 C/T polymorphism, located in exon 5 of the IL6 gene is synonymous. However, this polymorphism may be in linkage disequilibrium with another polymorphism located in the part of IL6 gene which was not sequenced or in a nearby gene. This polymorphism can also affect gene function by altering the stability, splicing or location of mRNA (Cartegni et al., 2002; Tabor et al., 2002) and can therefore be considered as an interesting candidate for association (Risch, 2000). The role that IL6 could play in HAT strengthens the pertinence of our finding. A crucial step in HAT is the invasion

of CNS by the parasites when they cross the BBB. Although the mechanisms remain unclear, a hypothesis could be that the modification of the BBB permeability stems from the presence of inflammatory mediators, such as IL1, IL6 and TNFa, in blood and/or in CNS (De Vries et al., 1996). Girard et al. (2005) demonstrated in vitro that Tbg induced the synthesis of IL6 by human bone marrow endothelial cells, and Lejon et al. (2002) confirmed the involvement of this cytokine whose level increases in CSF during Tbg infection and decreases after treatment. These findings corroborate with data from Trypanosoma brucei brucei-infected mice, where the detection of IL6 in the brain correlates with astrocyte activation (Hunter et al., 1992) in the choroid plexus (Quan et al., 1999). However, the role of this cytokine could be much more complex and IL6 is certainly involved in other steps than neuropathogenesis during disease progression. In a sub-sample of the same population, we showed that IL6 serum concentrations in HAT cases were higher than in both controls and seropositive individuals without parasitological confirmation (Courtin et al., 2006a). The same differences between cases and controls were shown in serum concentration by Lejon et al. (2002), but in this case, the serum level did not decrease after treatment. All these results emphasize the potential role of this cytokine in the pathogenesis of HAT and the necessity to confirm our results in another population. Unfortunately, the recent events in Coˆte d’Ivoire did not allow us to proceed with this analysis in our previous population for which DNA is no longer available. To our knowledge, the IL1a5417 C/T polymorphism, located in intron 5 of the IL1a gene has not been associated with a functional effect. However, in this case also, this polymorphism may be in linkage disequilibrium with another unidentified coding polymorphism in the gene or in a nearby gene. IL1 participates in macrophage activation during early infection in mice (Sternberg, 2004) and plays a key role in the recruitment of leukocytes into the CNS through the BBB during CNS infection (Borges, 1992; Ching et al., 2005). Its possible association with the HAT variable risk must be confirmed. We showed previously in IC that individuals who are homozygous for the TNFa308 A allele have a higher risk of developing the disease (Courtin et al., 2006b). This effect was

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not found in the present study. The same pattern of discrepant results has already been shown for the same polymorphism and cerebral malaria in different populations (McGuire et al., 1994). The conclusions concerning the role of TNFa308 G/A seemed complex because of the low allele frequencies that make it difficult to assess the effect of homozygosity (Knight et al., 1999). The same pattern of differences in allele frequencies exists between our two populations (i.e. DRC and IC) and could be responsible for the discrepancy observed between our studies. In DRC, only seven subjects (representing 2% of the population) were homozygous for TNFa308 AA genotype, whereas they represented 6% of the population in IC. Although a lack of power could explain the heterogeneity of the results, this difference may result from the complexity of the interactions between environmental and genetic risk factors, as well as of the heterogeneity of genetic control in infections. The result obtained for the IL10592 C/A polymorphism was not significant. However, it is interesting to note that this trend could be consistent with a higher risk of developing the disease, whereas in IC, the same promoter polymorphism was significantly associated with a lower risk of HAT (Courtin et al., 2006b). Although experimental evidence points to a potentially protective role of IL10 in the late stage of the disease by countering the important production of TNFa, excessive down-regulation of TNFa might be deleterious (Blackwell and Christman, 1996). Another explanation could be that the polymorphism studied (i.e. IL10592 C/A) has no effect per se but is in linkage disequilibrium with another unidentified coding polymorphism in the gene in IC. Variation of this linkage disequilibrium across our populations might lead to different findings (Tu and Whittemore, 1999). Heterogeneity of the populations and of the definition of phenotypes must also be taken into account (Palmer and Cookson, 2000). In IC, the prevalence of the disease was lower than 1% and our population lived in a sub-urban area and was composed of 56% migrants from Sudanese areas where HAT was absent. In some villages of the Bandundu area or DRC, the prevalence was greater than 15% (National Control Programme, personal communication) and the entire population studied belonged to the same ethnic group and lived in rural conditions, exposed to the risk of HAT since their birth. Such differences can influence the development of the immune system and can lead to dissimilar interactions between human host and parasites, as already described for HAT (Jamonneau et al., 2002; Garcia et al., 2002) as well as for malaria (Baird, 1995). Phenotypic heterogeneity can be directly related to the complexity of HAT (Jamonneau et al., 2002) and of its progression (Garcia et al., 2000). However, as all individuals harbouring parasites receive an immediate treatment whatever their clinical presentation, the variability in severity of infection cannot be taken into account. The main consequence could be a phenotypic heterogeneity between, but also within, our two populations (i.e. IC and DRC). In conclusion, this study confirms that differing host responses to Trypanosoma infections may result from immune response polymorphisms in host populations (MacLean et al.,

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