Abstract
Background
Because of the wide spectrum of clinical manifestations and well-defined immunologic complications, leprosy is a useful disease for studying genetic regulation of the host response to infection. We hypothesized that polymorphisms in NOD2, a cytosolic receptor known to detect mycobacteria, are associated with susceptibility to leprosy and its clinical outcomes.
Methods
We used a case-control study design with 933 patients in Nepal, which included 240 patients with type I (reversal) reaction (RR), and 124 patients with type 2 (erythema nodosum leprosum (ENL)) reactions. We compared 32 common NOD2 gene region polymorphism frequencies between the different clinical types of leprosy as well as 101 controls without leprosy.
Results
Four polymorphisms were associated with leprosy susceptibility when comparing allele frequencies and eight were associated when comparing genotype frequencies with a dominant model. Five polymorphisms were associated with protection from RR in an allelic analysis, and seven were associated with RR with a dominant model. Four polymorphisms were associated with increased susceptibility to ENL in an allelic analysis, while seven of 32 polymorphisms were associated with a dominant model.
Conclusion
These data suggest that NOD2 genetic variants are associated with leprosy susceptibility and the development of leprosy reactive states.
Keywords: Mycobacterium leprae, NOD2, Reversal Reaction, Erythema nodosum leprosum, Genetic polymorphisms, CYLD, SLIC1
Introduction
Leprosy is an infectious disease caused by Mycobacterium leprae that involves the peripheral nerves and skin with a polarized clinical presentation [1-3]. At one end of the spectrum is tuberculoid leprosy (TT), which is characterized by isolated skin lesions with well-formed granulomas, rare intracellular bacilli on biopsy, and a Th1 dominant T cell cytokine response. At the other end of the spectrum, lepromatous leprosy (LL) patients have numerous lesions with poorly formed granulomas rich in foamy macrophages containing abundant intravacuolar bacilli, and a Th2 dominant T cell response. Between the two poles are patients with borderline lepromatous (BL), mid borderline (BB) and borderline tuberculoid (BT) disease that manifest intermediary bacillary loads and cellular immunity to M. leprae and its antigens. Thirty to 50 percent of leprosy patients can also develop one of two reactional states [1]. Type I or reversal reaction (RR) typically occurs in borderline forms of disease (BL or BB) and is associated with a rapid shift of T cell immunity to the tuberculoid pole (or Th1) or less often to the lepromatous (or Th2) pole, both leading to severe tissue damage. Type 2 reactions or erythema nodosum leprosum (ENL) typically occurs in patients with BL or LL leprosy, and is characterized by increased TNF-α serum levels and immune complex-associated vasculitis, panniculitis and uveitis. ENL and RR may manifest during antimicrobial treatment, but often they occur before or even years after treatment. Host factors that control clinical disease course in leprosy remain only partially understood. We hypothesize common genetic variation in innate immune receptors influence the immune response and diverse clinical phenotypes in patients with leprosy.
Many studies suggest that human genetic factors influence the acquisition of leprosy as well as the clinical course and type of disease. The first studies that suggested genetic influence demonstrated that monozygotic twins have a three-fold greater similarity in type of leprosy than dizygotic twins [4]. Linkage studies have identified PARK2 and PACRG as well as chromosomal regions 10p13 and 20q12 as leprosy susceptibility loci [5, 6]. Candidate gene studies have identified polymorphisms in several immune genes associated with leprosy susceptibility including the vitamin D receptor, lymphotoxin-α, TNF-α, IL-10, HLA genes and TAP-2 [7-9]. Since the spectrum of macrophage intracellular replication can be multibacillary in lepromatous disease and paucibacillary in tuberculoid disease [10], focus has turned to gene studies in the innate immune system. To date candidate genes in this area have focused on pathogen receptors located on the surface and intracellular organelles and have identified Toll-like receptor 1 (TLR-1) [11], TLR-4 [12] and mannose binding lectin [13, 14] as important in leprosy disease susceptibility. In addition, we recently identified polymorphisms in TLR-2 and TLR-1 that are associated with susceptibility to RR [15, 16].
In addition to receptors such as TLRs on the cell surface and within phagosomes, the innate immune system has cytosolic receptors to detect intracellular pathogens. Nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) are a diverse set of 22 innate immune receptors involved in cytoplasmic detection of microbes and activation of inflammatory cascades [17, 18]. The association of genetic variation in NLRs and cytosolic receptors with infectious disease susceptibility is poorly understood. Due to M. leprae’s ability to replicate intracellularly, we hypothesized that cytoplasmic receptors may also play an important role in pathogen detection and may be associated with the varied clinical forms of disease. Although the predominant site of M. leprae replication is within the vacuole, there is some evidence that egress of Mycobacteria [19] and/or mycobacterial cell wall lipids and other bacillary components into the cytosol may also occur [20] via a conserved secretion system (ESX-1) dependant process to activate the inflammasome [21, 22]. NOD2 (CARD15) contains leucine rich repeats linked to effector domains (Caspase activation recruitment domains (CARD)) and activates NF-κb nuclear translocation through activation of Rip2 kinase. NOD2 detects the cell wall building block muramyl dipeptide (MDP), and plays a role in the immune response to many pathogens [23].
Human variants of NOD2 have been detected in Crohn’s disease [24, 25], a chronic granulomatous disorder of the gut that appears similar to Johnne’s disease, a granulomatous disorder in cows caused by Mycobacteria paratuberculosis. The association of Crohn’s disease with mycobacterial infection, however, remains controversial [26, 27]. A number of studies have implicated NOD2 directly in mycobacterial disease. Nonsynonomous variants of NOD2 were more frequent in patients with active tuberculosis (TB) in a cohort of patients from Houston [28]. In addition, human and murine macrophages detect M. tuberculosis and M. paratuberculosis in a NOD2-dependent manner [29, 30]. NOD2 also influences TB disease course in the mouse model of infection [31, 32]. The function of NOD2, however, in M. leprae infection has not been addressed. In this paper, we show evidence for allelic and genotypic association of NOD2 genetic variants with leprosy reactive states and leprosy susceptibility.
Materials and Methods
Human subjects
Recruitment and description of the patient population was previously reported [16]. Briefly, 933 study participants were referred to Anandaban Hospital in Katmandu, Nepal for treatment of leprosy. The diagnosis of leprosy in these patients was done on the basis of clinical symptoms, skin smears, and biopsy reports. The Ridley/Jopling classification scheme was used to assign the class of leprosy. Following initiation of treatment, patients were followed for the development of reactive states (RR and ENL) for a minimum of 3 years. The institutional review boards at University of Washington, University of Medicine and Dentistry of New Jersey, Nepal Health Research Council, and Western Institutional Review Boards approved patient protocols as per the US Department of Health and Human Services Guidelines. Written informed consent was obtained from all of the patients. Eight different ethnic and religious groups were included in the study including Brahmin (26.0%), Chetri (24.2%), Tamang (14.7%), Newar (8.7%), Magar (5.2%), Sarki (3.4%), Muslim (3.3%), and Kami (2.7%), with 11.8% having unrecorded ethnicity [16].
Determination of SNP for genotypic analysis
We identified haplotype tagging SNPs from the Han Chinese (CHB) and European (CEU) ancestry from the International HapMap Project database (http://www.hapmap.org). The genomic region adjacent to NOD2 (16q12) also contains the genes for familial Cylindromatosis (CYLD) and selectin ligand interactor cytoplasmic protein - 1 (SLIC1 or SNX-20). We searched a region on chromosome 16q12, 50 kilobases upstream and downstream of genes NOD2 and CYLD for tagged SNPs using an R2 cutoff of 0.8 for linkage disequilibrium and a minor allele frequency cutoff of 10%. Also added were non-synonomous SNPs found in these two populations at frequencies of greater than 5%. Using this search technique we identified 32 unique SNPs to analyze in this region (Figure 1).
Figure 1.
Genetic map and Linkage disequilibrium (D’ and R2) of the single nucleotide polymorphisms used in the region of chromosome 16q21. Arrows represent direction of transcription
Molecular Biology
DNA was obtained from whole blood using Nucleon BACC2 Genomic DNA (Amersham Lifesciences) and High-Pure PCR template preparation extraction kits (Roche) as previously described [16]. Genotyping of DNA was performed using a chip-based MALDI-TOF MassARRAY technique (Sequenom) as previously described [16]. Briefly, SPECTRODE-SIGNER software was used to determine probes to be used for multiplex SNP assays; 5ng of DNA was amplified in a 384-well plate following Sequenom’s specifications. Shrimp alkaline phosphatase was added after PCR to prevent further incorporation of unused dNTPs that might interfere with the primer extension step. Next allelic discrimination reactions were performed by adding a mixture of dNTPs and dideoxy NTPs to each well. MassEXTEND clean resin was added to the mixture to remove extraneous salts that could interfere with the MALDI-TOF analysis. Genotypes were determined by spotting 15 nl of each reaction onto a 386 SpectroCHIP (seqenom), which was subsequently read by the MALDI-TOF mass spectrometer.
Statistics
Univariate analysis was performed on categorical variables using a Pearson Chi-square test, and for continuous variables using a Student’s t test. Multivariate logistic regression was performed using Stata (Intercooled Version 10.1, Statacorp) and adjusted for age groups, sex, and ethnicity when appropriate. Haplotypes were constructed with the program Hapipf in Stata. For each of the NOD2 polymorphisms, significant deviations from the expected genotypic frequencies were determined using the Hardy Weinberg principle with a p value cutoff of p<0.001. All SNPs analyzed were in Hardy Weinberg equilibrium when analyzed in the control group.
Multiple Tests Comparisons
32 polymorphisms were genotyped in our study in three analyses, ENL versus unaffected, RR versus unaffected, and leprosy versus control. If we correct for multiple comparisons with a Bonferroni test (P value × 32), only p values less than 0.00156 remain significant. However, linkage disequilibrium between the 32 polymorphisms, is significant (Figure 1) and suggests that a Bonferroni correction is overly conservative [33]. Since there is no standardized approach for correcting P values for multiple comparisons in candidate gene association studies, we report uncorrected P values throughout the manuscript.
Results
Association of NOD2 SNPs with leprosy acquisition in Nepal
To determine whether NOD2 polymorphisms are associated with leprosy susceptibility, we compared allele and genotype frequencies in 933 leprosy patients and 101 controls without leprosy. Baseline characteristics of these subjects are listed in Table 1. Four polymorphisms were identified as significant (p<0.05) at the allelic level, (rs12448797 (OR 2.18, 95%CI 1.05-4.52, p=0.031), rs2287195 (OR 1.51, 95%CI 1.09-2.10, p=0.013), rs8044354 (OR 1.53, 95%CI 1.12-2.07, p=0.006), and rs1477176 (OR 0.44, 95%CI 0.29-0.68, p=0.0002)) (Table 2). The most significant of these was rs1477176 (OR 0.44, 95%CI 0.29-0.68, p=0.00017). When these genotypes were analyzed with a dominant model, 8 of these SNPs were associated with leprosy susceptibility (Supplemental Table 1). Six of these SNPs (rs2287185, rs8044354, rs8043770, rs13339578, rs4785225, and rs751271) were clustered in the promoter region and within the NOD2 gene itself. The remaining two SNPs (rs12448797 and rs1477176) were located in adjacent genes (selectin ligand interactor cytoplasmic protein (SLIC1) and ubiquitin carboxyl-terminal hydrolase (CYLD - cylindromatosis)).
Table 1.
Population characteristics of Nepalese cohort
| ENL (among BL and LL patients only) |
RR | Leprosy | |||||
|---|---|---|---|---|---|---|---|
| Yes | No | Yes | No | Yes | No | ||
| n= | 124 | 428 | 240 | 693 | 933 | 101 | |
|
| |||||||
| Sex | M | 89 (71.4) | 305 (71.2) | 164 (68.3) | 488 (70.4) | 652 (69.9) | 63 (62.4) |
| F | 35 (28.2) | 123 (28.7) | 76 (31.7) | 205 (29.6) | 281 (30.1) | 38 (37.6) | |
|
| |||||||
| pa | 0.911 | 0.544 | 0.121 | ||||
|
| |||||||
| Ethnicity (not including unassigned) |
Brahmin | 32 (31.4) | 101 (27.6) | 55 (26.6) | 196 (32.2) | 251 (30.3) | 17 (19.1) |
| Chetri | 23 (22.6) | 104 (28.4) | 59 (28.5) | 157 (25.8) | 216 (26.4) | 33 (31.5) | |
| Tamang | 21 (20.6) | 68 (18.6) | 47 (22.7) | 88 (14.5) | 135 (17.0) | 16 (18.0) | |
| Newar | 6 (5.9) | 33 (9.0) | 15 (7.3) | 55 (9.1) | 70 (8.6) | 20 (22.5) | |
| Magar | 9 (8.8) | 22 (6.0) | 11 (5.3) | 40 (6.6) | 51 (6.4) | 3 (3.4) | |
| Muslim | 2 (2.0) | 15 (4.1) | 7 (3.4) | 25 (4.1) | 32 (3.9) | 2 (2.3) | |
| Sarki | 4 (3.9) | 13 (3.6) | 7 (3.4) | 26 (4.3) | 33 (4.2) | 2 (2.3) | |
| Kami | 5 (4.9) | 10 (2.7) | 6 (2.9) | 21 (3.5) | 27 (3.2) | 1 (1.1) | |
|
| |||||||
| pb | 0.578 | 0.190 | <0.01 | ||||
|
| |||||||
| Age ± SD | 37.7±13.6 | 46.0±16.4 | 38.09±15.6 | 46.3±16.1 | 44.2±16.4 | 31.9±12.9 | |
|
| |||||||
| pc | <0.01 | <0.01 | <0.01 | ||||
Statistical probability that frequency of sex is different between cases and controls (ENL, RR, leprosy).
Statistical probability that ethnic frequency is different between cases (ENL, RR, leprosy) versus controls by 2×8 chi square analysis.
Statistical probability that age is different in cases (ENL, RR, leprosy) versus controls by Wilcoxon rank-sum test.
Table 2.
Allelic Association of NOD2 Single Nucleotide Polymorphisms with Leprosy Disease Acquisition
| Allele | Genotype | Allelic Comparisons | ||||||
|---|---|---|---|---|---|---|---|---|
| SNP,group | Gene | 0 | 1 | 00 | 01 | 11 | OR (95%CI) | PA |
| SNP type | ||||||||
| rs7186262 | ||||||||
| No Leprosy | 100 (0.510) | 96 (0.490) | 25 (0.255) | 50 (0.510) | 23 (0.235) | |||
| Leprosy | 876 (0.519) | 812 (0.481) | 219 (0.259) | 438 (0.519) | 187 (0.222) | 0.97 (0.71-1.31) | 0.816 | |
| rs1109863 | ||||||||
| No Leprosy | 105 (0.520) | 97 (0.480) | 27 (0.276) | 51 (0.520) | 23 (0.235) | |||
| Leprosy | 816 (0.474) | 906 (0.526) | 186 (0.220) | 444 (0.526) | 231 (0.274) | 1.20 (0.89-1.63) | 0.216 | |
| rs12448797 | ||||||||
| No Leprosy | 188 (0.959) | 8 (0.041) | 91 (0.929) | 6 (0.061) | 1 (0.010) | |||
| Leprosy | 1583 (0.915) | 147 (0.085) | 727 (0.861) | 129 (0.153) | 9 (0.011) | 2.18 (1.06-5.23) | 0.031 | |
| rs8059649 | ||||||||
| No Leprosy | 194 (0.980) | 4 (0.020) | 95 (0.969) | 4 (0.041) | 0 (0.000) | |||
| Leprosy | 1682 (0.959) | 72 (0.041) | 807 (0.956) | 68 (0.081) | 2 (0.002) | 2.08 (0.76-7.91) | 0.151 | |
| rs12443880 | ||||||||
| No Leprosy | 194 (0.990) | 2 (0.010) | 96 (0.980) | 2 (0.020) | 0 (0.000) | |||
| Leprosy | 1677 (0.967) | 57 (0.033) | 813 (0.963) | 51 (0.060) | 3 (0.004) | 3.30 (0.86-28.08) | 0.081 | |
| rs6596 | ||||||||
| No Leprosy | SLIC1 | 197 (0.995) | 1 (0.005) | 98 (1.000) | 1 (0.010) | 0 (0.000) | ||
| Leprosy | Syn | 1748 (0.984) | 28 (0.016) | 861 (1.020) | 26 (0.031) | 1 (0.001) | 3.16 (0.52-129.66) | 0.235 |
| rs1131716 | ||||||||
| No Leprosy | SLIC1 | 193 (0.985) | 3 (0.015) | 95 (0.969) | 3 (0.031) | 0 (0.000) | ||
| Leprosy | NSyn | 1681 (0.957) | 75 (0.043) | 805 (0.954) | 71 (0.084) | 2 (0.002) | 2.87 (0.93-14.36) | 0.063 |
| rs2287195 | ||||||||
| No Leprosy | SLIC1 | 144 (0.727) | 54 (0.273) | 55 (0.561) | 34 (0.347) | 10 (0.102) | ||
| Leprosy | Intron | 1053 (0.638) | 597 (0.362) | 333 (0.395) | 387 (0.459) | 105 (0.124) | 1.51 (1.08-2.14) | 0.013 |
| rs8044354 | ||||||||
| No Leprosy | 128 (0.646) | 70 (0.354) | 46 (0.469) | 36 (0.367) | 17 (0.173) | |||
| Leprosy | 956 (0.545) | 798 (0.455) | 259 (0.307) | 438 (0.519) | 180 (0.213) | 1.53 (1.11-2.10) | 0.006 | |
| rs8043770 | ||||||||
| No Leprosy | 148 (0.763) | 46 (0.237) | 61 (0.622) | 26 (0.265) | 10 (0.102) | |||
| Leprosy | 1235 (0.706) | 515 (0.294) | 439 (0.520) | 357 (0.423) | 79 (0.094) | 1.34 (0.94-1.94) | 0.095 | |
| rs10459815 | ||||||||
| No Leprosy | 192 (0.970) | 6 (0.030) | 93 (0.949) | 6 (0.061) | 0 (0.000) | |||
| Leprosy | 1632 (0.936) | 112 (0.064) | 766 (0.908) | 100 (0.118) | 6 (0.007) | 2.20 (0.96-6.19) | 0.058 | |
| rs7194886 | ||||||||
| No Leprosy | 160 (0.808) | 38 (0.192) | 68 (0.694) | 24 (0.245) | 7 (0.071) | |||
| Leprosy | 1415 (0.800) | 353 (0.200) | 568 (0.673) | 279 (0.331) | 37 (0.044) | 1.05 (0.72-1.57) | 0.796 | |
| rs2067085 | ||||||||
| No Leprosy | NOD2 | 165 (0.825) | 35 (0.175) | 72 (0.735) | 21 (0.214) | 7 (0.071) | ||
| Leprosy | Syn | 1463 (0.838) | 283 (0.162) | 616 (0.730) | 231 (0.274) | 26 (0.031) | 0.91 (0.61-1.38) | 0.640 |
| rs6500328 | ||||||||
| No Leprosy | NOD2 | 151 (0.770) | 45 (0.230) | 63 (0.643) | 25 (0.255) | 10 (0.102) | ||
| Leprosy | Intron | 1325 (0.769) | 397 (0.231) | 503 (0.596) | 319 (0.378) | 39 (0.046) | 1.01 (0.70-1.46) | 0.976 |
| rs13339578 | ||||||||
| No Leprosy | NOD2 | 145 (0.732) | 53 (0.268) | 58 (0.592) | 29 (0.296) | 12 (0.122) | ||
| Leprosy | Intron | 1154 (0.683) | 536 (0.317) | 382 (0.453) | 390 (0.462) | 73 (0.086) | 1.27 (0.90-1.80) | 0.155 |
| rs17312836 | ||||||||
| No Leprosy | NOD2 | 153 (0.773) | 45 (0.227) | 64 (0.653) | 25 (0.255) | 10 (0.102) | ||
| Leprosy | Intron | 1380 (0.789) | 370 (0.211) | 539 (0.639) | 302 (0.358) | 34 (0.040) | 0.91 (0.64-1.33) | 0.606 |
| rs1861759 | ||||||||
| No Leprosy | NOD2 | 154 (0.778) | 44 (0.222) | 65 (0.663) | 24 (0.245) | 10 (0.102) | ||
| Leprosy | Syn | 1403 (0.789) | 375 (0.211) | 547 (0.648) | 309 (0.366) | 33 (0.039) | 0.94 (0.65-1.37) | 0.712 |
| rs4785225 | ||||||||
| No Leprosy | NOD2 | 145 (0.732) | 53 (0.268) | 58 (0.592) | 29 (0.296) | 12 (0.122) | ||
| Leprosy | Intron | 1227 (0.685) | 563 (0.315) | 411 (0.487) | 405 (0.480) | 79 (0.094) | 1.26 (0.89-1.78) | 0.176 |
| rs17313265 | ||||||||
| No Leprosy | NOD2 | 183 (0.915) | 17 (0.085) | 84 (0.857) | 15 (0.153) | 1 (0.010) | ||
| Leprosy | Intron | 1532 (0.894) | 182 (0.106) | 691 (0.819) | 150 (0.178) | 16 (0.019) | 1.28 (0.75-2.30) | 0.353 |
| rs751271 | ||||||||
| No Leprosy | NOD2 | 147 (0.735) | 53 (0.265) | 59 (0.602) | 29 (0.296) | 12 (0.122) | ||
| Leprosy | Intron | 1227 (0.688) | 557 (0.312) | 415 (0.492) | 397 (0.470) | 80 (0.095) | 1.26 (0.90-1.79) | 0.170 |
| rs1861758 | ||||||||
| No Leprosy | NOD2 | 152 (0.784) | 42 (0.216) | 65 (0.663) | 22 (0.224) | 10 (0.102) | ||
| Leprosy | Intron | 1323 (0.777) | 379 (0.223) | 506 (0.600) | 311 (0.368) | 34 (0.040) | 1.04 (0.72-1.52) | 0.844 |
| rs5743289 | ||||||||
| No Leprosy | NOD2 | 195 (0.995) | 1 (0.005) | 97 (0.990) | 1 (0.010) | 0 (0.000) | ||
| Leprosy | Intron | 1731 (0.982) | 31 (0.018) | 851 (1.008) | 29 (0.034) | 1 (0.001) | 3.49 (0.58-143.02) | 0.191 |
| rs5743291 | ||||||||
| No Leprosy | NOD2 | 192 (0.980) | 4 (0.020) | 94 (0.959) | 4 (0.041) | 0 (0.000) | ||
| Leprosy | NSyn | 1679 (0.982) | 31 (0.018) | 825 (0.977) | 29 (0.034) | 1 (0.001) | 0.89 (0.31-3.49) | 0.822 |
| rs3135499 | ||||||||
| No Leprosy | NOD2 | 155 (0.783) | 43 (0.217) | 66 (0.673) | 23 (0.235) | 10 (0.102) | ||
| Leprosy | 3′UTR | 1351 (0.762) | 421 (0.238) | 505 (0.598) | 341 (0.404) | 40 (0.047) | 1.12 (0.78-1.64) | 0.521 |
| rs3135500 | ||||||||
| No Leprosy | NOD2 | 155 (0.783) | 43 (0.217) | 66 (0.673) | 23 (0.235) | 10 (0.102) | ||
| Leprosy | 3′UTR | 1311 (0.773) | 385 (0.227) | 502 (0.595) | 307 (0.364) | 39 (0.046) | 1.06 (0.74-1.55) | 0.754 |
| rs8056611 | ||||||||
| No Leprosy | 119 (0.601) | 79 (0.399) | 40 (0.408) | 39 (0.398) | 20 (0.204) | |||
| Leprosy | 993 (0.573) | 741 (0.427) | 293 (0.347) | 407 (0.482) | 167 (0.198) | 1.12 (0.82-1.54) | 0.445 | |
| rs751919 | ||||||||
| No Leprosy | 148 (0.755) | 48 (0.245) | 60 (0.612) | 28 (0.286) | 10 (0.102) | |||
| Leprosy | 1291 (0.759) | 411 (0.241) | 487 (0.577) | 317 (0.376) | 47 (0.056) | 0.98 (0.69-1.42) | 0.916 | |
| rs11862720 | ||||||||
| No Leprosy | CYLD | 164 (0.854) | 28 (0.146) | 71 (0.724) | 22 (0.224) | 3 (0.031) | ||
| Leprosy | Intron | 1347 (0.809) | 319 (0.191) | 544 (0.645) | 259 (0.307) | 30 (0.036) | 1.39 (0.91-2.19) | 0.124 |
| rs1477176 | ||||||||
| No Leprosy | CYLD | 169 (0.854) | 29 (0.146) | 73 (0.745) | 23 (0.235) | 3 (0.031) | ||
| Leprosy | Intron | 1571 (0.930) | 119 (0.070) | 733 (0.868) | 105 (0.124) | 7 (0.008) | 0.44 (0.28-0.71) | 0.000 |
| rs9925070 | ||||||||
| No Leprosy | CYLD | 151 (0.763) | 47 (0.237) | 62 (0.633) | 27 (0.276) | 10 (0.102) | ||
| Leprosy | Intron | 1363 (0.779) | 387 (0.221) | 527 (0.624) | 309 (0.366) | 39 (0.046) | 0.91 (0.64-1.32) | 0.603 |
| rs1420872 | ||||||||
| No Leprosy | CYLD | 151 (0.786) | 41 (0.214) | 63 (0.643) | 25 (0.255) | 8 (0.082) | ||
| Leprosy | Intron | 1311 (0.785) | 359 (0.215) | 508 (0.602) | 295 (0.350) | 32 (0.038) | 1.01 (0.69-1.49) | 0.964 |
| rs2302759 | ||||||||
| No Leprosy | CYLD | 130 (0.663) | 66 (0.337) | 46 (0.469) | 38 (0.388) | 14 (0.143) | ||
| Leprosy | Intron | 1141 (0.654) | 603 (0.346) | 382 (0.453) | 377 (0.447) | 113 (0.134) | 1.04 (0.75-1.45) | 0.801 |
P values in bold are less than 0.05 for the allelic analyses
We next examined whether population admixture could confound our results as some differences were seen in the ethnic frequencies between control individuals and the leprosy patients. There are greater than eight ethnic groups in Nepal, and the majority (approximately 70%) are present in 4 groups (Brahmin, Chetri, Tamang and Newar). We used a multivariate logistic regression model to adjust the analysis for ethnicity (with the 8 prevalent ethnic groups, excluding uncategorized), age and sex when comparing genotype frequencies in a dominant model. When adjusted for ethnicity, sex, and age, eight out of eight polymorphisms (rs12448797 (OR 3.20, 95%CI 1.24-8.26, p=0.016), rs2287195 (OR 2.29, 95%CI 1.43-3.68, p=0.001), rs8044354 (OR 2.17, 95%CI 1.36-3.46, p=0.001), rs8043770 (OR 2.05, 95%CI 1.25-3.34, p=0.004), rs13339578 (OR 2.19, 95%CI 1.37-3.52, p=0.001), rs4785225 (OR 2.00, 95%CI 1.25-3.21, p=0.004), rs751271 (OR 1.95, 95%CI 1.22-3.13, p=0.005), and rs1477176 (OR 0.43, 95%CI 0.25-0.76, p=0.003)) remained significantly associated with leprosy susceptibility. Together, these results suggest that several NOD2 SNPs are associated with leprosy susceptibility.
Lack of association of NOD2 with Leprosy Type
Of the 933 patients enrolled in the study, 582 had lepromatous leprosy (including LL, BL, or BB), and 342 had tuberculoid leprosy (including BT and TT leprosy). We analyzed the frequency of NOD2 SNPs to associate with type of leprosy. Only one SNP (rs1131716) was associated with predisposition to the lepromatous pole (OR 2.01, 95%CI 1.12-3.76, p=0.013). All other SNPs did not show association with leprosy type (data not shown).
Association of NOD2 SNPs with RR in leprosy
Among 933 leprosy subjects in Nepal, 240 individuals had type 1 RR over a three-year period of regular visits to the leprosy clinic. Of these, only 2 were identified as also having ENL.
We compared the minor allele frequency of those with and without RR and identified five SNPs (Table 3), (rs2287195 Odds Ratio (OR) 1.34, p=0.013, rs8044354 OR 1.36, p=0.005, rs8043770, OR 1.36, p=0.012, rs7194886 OR 1.36, p=0.032, and rs1861759, OR 1.33, p=0.041) with significant association. We also found one SNP with borderline significance (rs4785225, OR 1.25, p=0.064) (Table 3). The most significant association was with SNP rs8044354 (OR 1.36 (95%CI 1.09-1.70), p=0.005). The polymorphisms were clustered in the gene regions located between the NOD2 and SLIC1 genes (Figure 1).
Table 3.
Allelic and Genotypic Association of NOD2 Single Nucleotide Polymorphisms with Type 1 Reversal Reaction in Leprosy
| Allele | Genotype | Allelic Comparisons | Genotypic Comparisons |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|
| SNP,group | Gene | 0 | 1 | 00 | 01 | 11 | OR (95%CI) | PA | c2 (2df) | P |
| SNP type | ||||||||||
| rs7186262 | ||||||||||
| No RR | 640 (0.508) | 620 (0.492) | 154 (0.244) | 332 (0.527) | 144 (0.229) | |||||
| RR | 236 (0.551) | 192 (0.449) | 65 (0.304) | 106 (0.495) | 43 (0.201) | 1.19 (0.95-1.49) | 0.120 | 3.024 | 0.221 | |
| rs1109863 | ||||||||||
| No RR | 664 (0.516) | 622 (0.484) | 163 (0.259) | 338 (0.537) | 142 (0.225) | |||||
| RR | 242 (0.555) | 194 (0.445) | 68 (0.318) | 106 (0.495) | 44 (0.206) | 1.17 (0.93-1.46) | 0.162 | 2.834 | 0.242 | |
| rs12448797 | ||||||||||
| No RR | 1169 (0.912) | 113 (0.088) | 534 (0.848) | 101 (0.160) | 6 (0.010) | |||||
| RR | 414 (0.924) | 34 (0.076) | 193 (0.902) | 28 (0.131) | 3 (0.014) | 1.18 (0.78-1.81) | 0.423 | 1.601 | 0.449 | |
| rs8059649 | ||||||||||
| No RR | 1248 (0.960) | 52 (0.040) | 600 (0.952) | 48 (0.076) | 2 (0.003) | |||||
| RR | 434 (0.956) | 20 (0.044) | 207 (0.967) | 20 (0.093) | 0 (0.000) | 0.90 (0.52-1.62) | 0.708 | 1.163 | 0.559 | |
| rs12443880 | ||||||||||
| No RR | 1246 (0.967) | 42 (0.033) | 604 (0.959) | 38 (0.060) | 2 (0.003) | |||||
| RR | 431 (0.966) | 15 (0.034) | 209 (0.977) | 13 (0.061) | 1 (0.005) | 0.97 (0.52-1.90) | 0.917 | 0.092 | 0.955 | |
| rs6596 | ||||||||||
| No RR | SLIC1 | 1292 (0.983) | 22 (0.017) | 636 (1.010) | 20 (0.032) | 1 (0.002) | ||||
| RR | Syn | 456 (0.987) | 6 (0.013) | 225 (1.051) | 6 (0.028) | 0 (0.000) | 1.29 (0.50-3.93) | 0.577 | 0.474 | 0.789 |
| rs1131716 | ||||||||||
| No RR | SLIC1 | 1251 (0.958) | 55 (0.042) | 600 (0.952) | 51 (0.081) | 2 (0.003) | ||||
| RR | NSyn | 430 (0.956) | 20 (0.044) | 205 (0.958) | 20 (0.093) | 0 (0.000) | 0.95 (0.55-1.68) | 0.833 | 0.941 | 0.625 |
| rs2287195 | ||||||||||
| No RR | SLIC1 | 760 (0.621) | 464 (0.379) | 233 (0.370) | 294 (0.467) | 85 (0.135) | ||||
| RR | Intron | 293 (0.688) | 133 (0.312) | 100 (0.467) | 93 (0.435) | 20 (0.093) | 1.34 (1.06-1.72) | 0.013 | 6.243 | 0.044 |
| rs8044354 | ||||||||||
| No RR | 682 (0.525) | 616 (0.475) | 178 (0.283) | 326 (0.517) | 145 (0.230) | |||||
| RR | 274 (0.601) | 182 (0.399) | 81 (0.379) | 112 (0.523) | 35 (0.164) | 1.36 (1.09-1.70) | 0.005 | 7.807 | 0.020 | |
| rs8043770 | ||||||||||
| No RR | 898 (0.690) | 404 (0.310) | 310 (0.492) | 278 (0.441) | 63 (0.100) | |||||
| RR | 337 (0.752) | 111 (0.248) | 129 (0.603) | 79 (0.369) | 16 (0.075) | 1.37 (1.06-1.76) | 0.012 | 6.746 | 0.034 | |
| rs10459815 | ||||||||||
| No RR | 1215 (0.938) | 81 (0.063) | 572 (0.908) | 71 (0.113) | 5 (0.008) | |||||
| RR | 417 (0.931) | 31 (0.069) | 194 (0.907) | 29 (0.136) | 1 (0.005) | 0.90 (0.58-1.43) | 0.618 | 0.883 | 0.643 | |
| rs7194886 | ||||||||||
| No RR | 1031 (0.788) | 277 (0.212) | 406 (0.644) | 219 (0.348) | 29 (0.046) | |||||
| RR | 384 (0.835) | 76 (0.165) | 162 (0.757) | 60 (0.280) | 8 (0.037) | 1.36 (1.02-1.82) | 0.032 | 5.172 | 0.075 | |
| rs2067085 | ||||||||||
| No RR | NOD2 | 1073 (0.829) | 221 (0.171) | 445 (0.706) | 183 (0.290) | 19 (0.030) | ||||
| RR | Syn | 390 (0.863) | 62 (0.137) | 171 (0.799) | 48 (0.224) | 7 (0.033) | 1.30 (0.95-1.79) | 0.095 | 4.282 | 0.118 |
| rs6500328 | ||||||||||
| No RR | NOD2 | 973 (0.761) | 305 (0.239) | 362 (0.575) | 249 (0.395) | 28 (0.044) | ||||
| RR | Intron | 352 (0.793) | 92 (0.207) | 141 (0.659) | 70 (0.327) | 11 (0.051) | 1.20 (0.92-1.58) | 0.175 | 3.906 | 0.142 |
| rs13339578 | ||||||||||
| No RR | NOD2 | 849 (0.673) | 413 (0.327) | 275 (0.437) | 299 (0.475) | 57 (0.090) | ||||
| RR | Intron | 305 (0.713) | 123 (0.287) | 107 (0.500) | 91 (0.425) | 16 (0.075) | 1.21 (0.94-1.55) | 0.126 | 2.723 | 0.256 |
| rs17312836 | ||||||||||
| No RR | NOD2 | 1009 (0.780) | 285 (0.220) | 388 (0.616) | 233 (0.370) | 26 (0.041) | ||||
| RR | Intron | 371 (0.814) | 85 (0.186) | 151 (0.706) | 69 (0.322) | 8 (0.037) | 1.23 (0.94-1.63) | 0.128 | 2.799 | 0.247 |
| rs1861759 | ||||||||||
| No RR | NOD2 | 1023 (0.777) | 293 (0.223) | 390 (0.619) | 243 (0.386) | 25 (0.040) | ||||
| RR | Syn | 380 (0.823) | 82 (0.177) | 157 (0.734) | 66 (0.308) | 8 (0.037) | 1.33 (1.01-1.76) | 0.041 | 5.590 | 0.061 |
| rs4785225 | ||||||||||
| No RR | NOD2 | 893 (0.673) | 433 (0.327) | 290 (0.460) | 313 (0.497) | 60 (0.095) | ||||
| RR | Intron | 334 (0.720) | 130 (0.280) | 121 (0.565) | 92 (0.430) | 19 (0.089) | 1.25 (0.98-1.59) | 0.064 | 4.961 | 0.084 |
| rs17313265 | ||||||||||
| No RR | NOD2 | 1141 (0.893) | 137 (0.107) | 515 (0.817) | 111 (0.176) | 13 (0.021) | ||||
| RR | Intron | 391 (0.897) | 45 (0.103) | 176 (0.822) | 39 (0.182) | 3 (0.014) | 1.04 (0.72-1.53) | 0.815 | 0.403 | 0.818 |
| rs751271 | ||||||||||
| No RR | NOD2 | 892 (0.677) | 426 (0.323) | 293 (0.465) | 306 (0.486) | 60 (0.095) | ||||
| RR | Intron | 335 (0.719) | 131 (0.281) | 122 (0.570) | 91 (0.425) | 20 (0.093) | 1.22 (0.96-1.55) | 0.092 | 4.466 | 0.107 |
| rs1861758 | ||||||||||
| No RR | NOD2 | 981 (0.769) | 295 (0.231) | 369 (0.586) | 243 (0.386) | 26 (0.041) | ||||
| RR | Intron | 342 (0.803) | 84 (0.197) | 137 (0.640) | 68 (0.318) | 8 (0.037) | 1.22 (0.93-1.63) | 0.144 | 2.829 | 0.243 |
| rs5743289 | ||||||||||
| No RR | NOD2 | 1286 (0.982) | 24 (0.018) | 632 (1.003) | 22 (0.035) | 1 (0.002) | ||||
| RR | Intron | 445 (0.985) | 7 (0.015) | 219 (1.023) | 7 (0.033) | 0 (0.000) | 1.19 (0.49-3.28) | 0.693 | 0.383 | 0.826 |
| rs5743291 | ||||||||||
| No RR | NOD2 | 1255 (0.980) | 25 (0.020) | 616 (0.978) | 23 (0.037) | 1 (0.002) | ||||
| RR | NSyn | 424 (0.986) | 6 (0.014) | 209 (0.977) | 6 (0.028) | 0 (0.000) | 1.41 (0.56-4.22) | 0.453 | 0.657 | 0.720 |
| rs3135499 | ||||||||||
| No RR | NOD2 | 988 (0.754) | 322 (0.246) | 362 (0.575) | 264 (0.419) | 29 (0.046) | ||||
| RR | 3′UTR | 363 (0.786) | 99 (0.214) | 143 (0.668) | 77 (0.360) | 11 (0.051) | 1.20 (0.92-1.56) | 0.171 | 3.519 | 0.172 |
| rs3135500 | ||||||||||
| No RR | NOD2 | 972 (0.769) | 292 (0.231) | 368 (0.584) | 236 (0.375) | 28 (0.044) | ||||
| RR | 3′UTR | 339 (0.785) | 93 (0.215) | 134 (0.626) | 71 (0.332) | 11 (0.051) | 1.10 (0.84-1.44) | 0.500 | 1.437 | 0.487 |
| rs8056611 | ||||||||||
| No RR | 726 (0.562) | 566 (0.438) | 210 (0.333) | 306 (0.486) | 130 (0.206) | |||||
| RR | 267 (0.604) | 175 (0.396) | 83 (0.388) | 101 (0.472) | 37 (0.173) | 1.19 (0.95-1.49) | 0.122 | 2.317 | 0.314 | |
| rs751919 | ||||||||||
| No RR | 949 (0.752) | 313 (0.248) | 353 (0.560) | 243 (0.386) | 35 (0.056) | |||||
| RR | 342 (0.777) | 98 (0.223) | 134 (0.626) | 74 (0.346) | 12 (0.056) | 1.15 (0.88-1.51) | 0.286 | 1.746 | 0.418 | |
| rs11862720 | ||||||||||
| No RR | CYLD | 997 (0.805) | 241 (0.195) | 401 (0.637) | 195 (0.310) | 23 (0.037) | ||||
| RR | Intron | 350 (0.818) | 78 (0.182) | 143 (0.668) | 64 (0.299) | 7 (0.033) | 1.08 (0.81-1.46) | 0.573 | 0.319 | 0.853 |
| rs1477176 | ||||||||||
| No RR | CYLD | 1173 (0.929) | 89 (0.071) | 548 (0.870) | 77 (0.122) | 6 (0.010) | ||||
| RR | Intron | 398 (0.930) | 30 (0.070) | 185 (0.864) | 28 (0.131) | 1 (0.005) | 1.01 (0.65-1.60) | 0.976 | 0.554 | 0.758 |
| rs9925070 | ||||||||||
| No RR | CYLD | 997 (0.770) | 297 (0.230) | 381 (0.605) | 235 (0.373) | 31 (0.049) | ||||
| RR | Intron | 366 (0.803) | 90 (0.197) | 146 (0.682) | 74 (0.346) | 8 (0.037) | 1.21 (0.92-1.60) | 0.155 | 2.077 | 0.354 |
| rs1420872 | ||||||||||
| No RR | CYLD | 971 (0.781) | 273 (0.219) | 375 (0.595) | 221 (0.351) | 26 (0.041) | ||||
| RR | Intron | 340 (0.798) | 86 (0.202) | 133 (0.621) | 74 (0.346) | 6 (0.028) | 1.11 (0.84-1.48) | 0.446 | 0.918 | 0.632 |
| rs2302759 | ||||||||||
| No RR | CYLD | 860 (0.663) | 438 (0.337) | 292 (0.463) | 276 (0.438) | 81 (0.129) | ||||
| RR | Intron | 281 (0.630) | 165 (0.370) | 90 (0.421) | 101 (0.472) | 32 (0.150) | 0.87 (0.69-1.09) | 0.213 | 1.554 | 0.460 |
SNPs are arranged by order that they are located on the chromosome.
P values in bold are less than 0.05 for the allelic and genotypic analyses.
We next analyzed the distribution of genotype frequencies (Table 3). We found 3 polymorphisms with significantly different genotype frequencies (rs2287195, rs8044354, and rs8043770) in those with RR versus no RR (Table 2). Next, we examined whether these genotypic associations were consistent with a recessive (00 + 01 vs 11) or dominant (00 vs 01 + 11) model. We found that seven NOD2 polymorphisms had significant associations (P value <0.05) with protection from RR assuming a dominant inheritance model (Supplemental Table 1). Of these 7 SNPs, two polymorphisms (rs4785225 and rs752171) were noted to be in significant linkage disequilibrium with an R2 value of greater than 0.8 in this population.
We next evaluated whether the associations were affected by population admixture. No significant difference in ethnicity (p=0.319) or sex (p=0.710) was observed between people affected with RR and those not affected (Table 1). Those affected with RR tended to be significantly younger at the time of sample collection (36.7 years old versus 45.9 years old) than those unaffected (p<0.01) (Table 1). In an adjusted analysis (for age, sex, and ethnicity), SNP rs2287195 (OR 0.70, 95%CI 0.49-1.00, p=0.049), rs8043770 (OR 0.68, 95%CI 0.48-0.96, p=0.028), rs7194886 (OR 0.63, 95%CI 0.44-0.92, p=0.018), and rs1861759 (OR 0.66, 95%CI 0.47-0.95, p=0.027) remained associated with protection from RR. In contrast, three other SNPs (rs8044354, rs4785225, and rs751271) when adjusted for age, sex and ethnicity did not remain associated with RR. Together, these results suggest that several SNPs in NOD2 may be associated with protection from RR.
Association of NOD2 SNPs with ENL in leprosy
We next examined whether polymorphisms in the NOD2 gene region were associated with erythema nodosum leprosum (ENL) reaction in leprosy. A total of 124 patients identified with ENL were compared to 428 patients with lepromatous or borderline lepromatous leprosy (LL or BL) without ENL (Table 1). No significant differences in ethnicity were seen between leprosy patients who were affected with ENL versus those who were not (p=0.578). At the allelic level there were 4 SNPs which had significant associations (rs8044354 (OR 0.74, p=0.046), rs17312836, (OR 0.70, p=0.039), rs1861759 (OR 0.70, p=0.037), and rs1861758 (OR 0.71, p=0.047)) with p values less then 0.05 (Table 4), and 2 SNPs with borderline significance (rs6500328 (OR 0.73, p=0.066), and rs7194886 (OR 0.72, p=0.057)).
Table 4.
Allelic and Genotypic Association of NOD2 Single Nucleotide Polymorphisms with Erythema Nodosum Leprosum
| Allele | Genotype | Allelic Comparisons | Genotypic Comparisons |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|
| SNP,group | Gene | 0 | 1 | 00 | 01 | 11 | OR (95%CI) | PA | c2 (2df) | P |
| SNP type |
||||||||||
| rs7186262 | ||||||||||
| No RR | 394 (0.520) | 364 (0.480) | 99 (0.261) | 196 (0.517) | 84 (0.222) | |||||
| RR | 115 (0.513) | 109 (0.487) | 30 (0.268) | 55 (0.491) | 27 (0.241) | 0.97 (0.72-1.33) | 0.866 | 0.274 | 0.872 | |
| rs1109863 | ||||||||||
| No RR | 395 (0.506) | 385 (0.494) | 99 (0.261) | 197 (0.520) | 94 (0.248) | |||||
| RR | 124 (0.539) | 106 (0.461) | 35 (0.313) | 54 (0.482) | 26 (0.232) | 1.14 (0.84-1.55) | 0.383 | 1.163 | 0.559 | |
| rs12448797 | ||||||||||
| No RR | 719 (0.908) | 73 (0.092) | 331 (0.873) | 57 (0.150) | 8 (0.021) | |||||
| RR | 211 (0.894) | 25 (0.106) | 93 (0.830) | 25 (0.223) | 0 (0.000) | 0.86 (0.52-1.45) | 0.528 | 5.264 | 0.072 | |
| rs8059649 | ||||||||||
| No RR | 774 (0.965) | 28 (0.035) | 373 (0.984) | 28 (0.074) | 0 (0.000) | |||||
| RR | 224 (0.941) | 14 (0.059) | 105 (0.938) | 14 (0.125) | 0 (0.000) | 0.58 (0.29-1.21) | 0.100 | 2.827 | 0.093 | |
| rs12443880 | ||||||||||
| No RR | 763 (0.961) | 31 (0.039) | 368 (0.971) | 27 (0.071) | 2 (0.005) | |||||
| RR | 222 (0.965) | 8 (0.035) | 107 (0.955) | 8 (0.071) | 0 (0.000) | 1.13 (0.50-2.88) | 0.766 | 0.584 | 0.747 | |
| rs6596 | ||||||||||
| No RR | SLIC1 | 805 (0.984) | 13 (0.016) | 396 (1.045) | 13 (0.034) | 0 (0.000) | ||||
| RR | Syn | 237 (0.988) | 3 (0.013) | 117 (1.045) | 3 (0.027) | 0 (0.000) | 1.28 (0.35-7.03) | 0.705 | 0.146 | 0.703 |
| rs1131716 | ||||||||||
| No RR | SLIC1 | 765 (0.949) | 41 (0.051) | 363 (0.958) | 39 (0.103) | 1 (0.003) | ||||
| RR | NSyn | 223 (0.945) | 13 (0.055) | 105 (0.938) | 13 (0.116) | 0 (0.000) | 0.92 (0.47-1.90) | 0.797 | 0.469 | 0.791 |
| rs2287195 | ||||||||||
| No RR | SLIC1 | 466 (0.635) | 268 (0.365) | 154 (0.406) | 158 (0.417) | 55 (0.145) | ||||
| RR | Intron | 128 (0.587) | 90 (0.413) | 31 (0.277) | 66 (0.589) | 12 (0.107) | 0.82 (0.59-1.13) | 0.202 | 10.366 | 0.006 |
| rs8044354 | ||||||||||
| No RR | 443 (0.548) | 365 (0.452) | 125 (0.330) | 193 (0.509) | 86 (0.227) | |||||
| RR | 111 (0.474) | 123 (0.526) | 20 (0.179) | 71 (0.634) | 26 (0.232) | 0.74 (0.55-1.01) | 0.046 | 9.272 | 0.010 | |
| rs8043770 | ||||||||||
| No RR | 569 (0.706) | 237 (0.294) | 205 (0.541) | 159 (0.420) | 39 (0.103) | |||||
| RR | 158 (0.675) | 76 (0.325) | 50 (0.446) | 58 (0.518) | 9 (0.080) | 0.87 (0.63-1.20) | 0.367 | 3.835 | 0.147 | |
| rs10459815 | ||||||||||
| No RR | 746 (0.933) | 54 (0.068) | 350 (0.923) | 46 (0.121) | 4 (0.011) | |||||
| RR | 215 (0.919) | 19 (0.081) | 98 (0.875) | 19 (0.170) | 0 (0.000) | 0.82 (0.47-1.50) | 0.472 | 2.933 | 0.231 | |
| rs7194886 | ||||||||||
| No RR | 663 (0.813) | 153 (0.188) | 275 (0.726) | 113 (0.298) | 20 (0.053) | |||||
| RR | 180 (0.756) | 58 (0.244) | 66 (0.589) | 48 (0.429) | 5 (0.045) | 0.72 (0.50-1.03) | 0.057 | 6.943 | 0.031 | |
| rs2067085 | ||||||||||
| No RR | NOD2 | 674 (0.845) | 124 (0.155) | 289 (0.763) | 96 (0.253) | 14 (0.037) | ||||
| RR | Syn | 186 (0.802) | 46 (0.198) | 74 (0.661) | 38 (0.339) | 4 (0.036) | 0.74 (0.50-1.11) | 0.121 | 3.566 | 0.168 |
| rs6500328 | ||||||||||
| No RR | NOD2 | 607 (0.778) | 173 (0.222) | 239 (0.631) | 129 (0.340) | 22 (0.058) | ||||
| RR | Intron | 170 (0.720) | 66 (0.280) | 57 (0.509) | 56 (0.500) | 5 (0.045) | 0.73 (0.52-1.04) | 0.066 | 8.098 | 0.017 |
| rs13339578 | ||||||||||
| No RR | NOD2 | 520 (0.679) | 246 (0.321) | 173 (0.456) | 174 (0.459) | 36 (0.095) | ||||
| RR | Intron | 146 (0.646) | 80 (0.354) | 41 (0.366) | 64 (0.571) | 8 (0.071) | 0.86 (0.63-1.20) | 0.356 | 4.410 | 0.110 |
| rs17312836 | ||||||||||
| No RR | NOD2 | 640 (0.804) | 156 (0.196) | 260 (0.686) | 120 (0.317) | 18 (0.047) | ||||
| RR | Intron | 172 (0.741) | 60 (0.259) | 61 (0.545) | 50 (0.446) | 5 (0.045) | 0.70 (0.49-1.00) | 0.039 | 6.900 | 0.032 |
| rs1861759 | ||||||||||
| No RR | NOD2 | 650 (0.797) | 166 (0.203) | 261 (0.689) | 128 (0.338) | 19 (0.050) | ||||
| RR | Syn | 176 (0.733) | 64 (0.267) | 60 (0.536) | 56 (0.500) | 4 (0.036) | 0.70 (0.50-1.00) | 0.037 | 9.574 | 0.008 |
| rs4785225 | ||||||||||
| No RR | NOD2 | 564 (0.683) | 262 (0.317) | 190 (0.501) | 184 (0.485) | 39 (0.103) | ||||
| RR | Intron | 157 (0.654) | 83 (0.346) | 45 (0.402) | 67 (0.598) | 8 (0.071) | 0.88 (0.64-1.21) | 0.404 | 4.851 | 0.088 |
| rs17313265 | ||||||||||
| No RR | NOD2 | 676 (0.873) | 98 (0.127) | 299 (0.789) | 78 (0.206) | 10 (0.026) | ||||
| RR | Intron | 211 (0.917) | 19 (0.083) | 96 (0.857) | 19 (0.170) | 0 (0.000) | 1.61 (0.95-2.85) | 0.068 | 4.013 | 0.134 |
| rs751271 | ||||||||||
| No RR | NOD2 | 567 (0.688) | 257 (0.312) | 195 (0.515) | 177 (0.467) | 40 (0.106) | ||||
| RR | Intron | 156 (0.655) | 82 (0.345) | 45 (0.402) | 66 (0.589) | 8 (0.071) | 0.86 (0.63-1.19) | 0.341 | 5.913 | 0.052 |
| rs1861758 | ||||||||||
| No RR | NOD2 | 604 (0.791) | 160 (0.209) | 240 (0.633) | 124 (0.327) | 18 (0.047) | ||||
| RR | Intron | 169 (0.728) | 63 (0.272) | 58 (0.518) | 53 (0.473) | 5 (0.045) | 0.71 (0.50-1.01) | 0.047 | 6.859 | 0.032 |
| rs5743289 | ||||||||||
| No RR | NOD2 | 803 (0.984) | 13 (0.016) | 395 (1.042) | 13 (0.034) | 0 (0.000) | ||||
| RR | Intron | 234 (0.983) | 4 (0.017) | 115 (1.027) | 4 (0.036) | 0 (0.000) | 0.95 (0.29-4.03) | 0.925 | 0.009 | 0.924 |
| rs5743291 | ||||||||||
| No RR | NOD2 | 751 (0.978) | 17 (0.022) | 368 (0.971) | 15 (0.040) | 1 (0.003) | ||||
| RR | NSyn | 230 (0.983) | 4 (0.017) | 113 (1.009) | 4 (0.036) | 0 (0.000) | 1.30 (0.42-5.37) | 0.637 | 0.366 | 0.833 |
| rs3135499 | ||||||||||
| No RR | NOD2 | 627 (0.768) | 189 (0.232) | 240 (0.633) | 147 (0.388) | 21 (0.055) | ||||
| RR | 3′UTR | 171 (0.718) | 67 (0.282) | 58 (0.518) | 55 (0.491) | 6 (0.054) | 0.77 (0.55-1.08) | 0.114 | 4.154 | 0.125 |
| rs3135500 | ||||||||||
| No RR | NOD2 | 588 (0.776) | 170 (0.224) | 230 (0.607) | 128 (0.338) | 21 (0.055) | ||||
| RR | 3′UTR | 166 (0.735) | 60 (0.265) | 59 (0.527) | 48 (0.429) | 6 (0.054) | 0.80 (0.56-1.15) | 0.199 | 2.916 | 0.233 |
| rs8056611 | ||||||||||
| No RR | 450 (0.568) | 342 (0.432) | 137 (0.361) | 176 (0.464) | 83 (0.219) | |||||
| RR | 126 (0.525) | 114 (0.475) | 32 (0.286) | 62 (0.554) | 26 (0.232) | 0.84 (0.62-1.13) | 0.238 | 2.831 | 0.243 | |
| rs751919 | ||||||||||
| No RR | 596 (0.766) | 182 (0.234) | 231 (0.609) | 134 (0.354) | 24 (0.063) | |||||
| RR | 165 (0.730) | 61 (0.270) | 58 (0.518) | 49 (0.438) | 6 (0.054) | 0.83 (0.58-1.18) | 0.266 | 3.005 | 0.223 | |
| rs11862720 | ||||||||||
| No RR | CYLD | 612 (0.799) | 154 (0.201) | 242 (0.639) | 128 (0.338) | 13 (0.034) | ||||
| RR | Intron | 186 (0.809) | 44 (0.191) | 72 (0.643) | 42 (0.375) | 1 (0.009) | 1.06 (0.72-1.58) | 0.745 | 2.259 | 0.323 |
| rs1477176 | ||||||||||
| No RR | CYLD | 704 (0.936) | 48 (0.064) | 329 (0.868) | 46 (0.121) | 1 (0.003) | ||||
| RR | Intron | 219 (0.952) | 11 (0.048) | 104 (0.929) | 11 (0.098) | 0 (0.000) | 1.36 (0.68-2.95) | 0.371 | 0.932 | 0.627 |
| rs9925070 | ||||||||||
| No RR | CYLD | 632 (0.790) | 168 (0.210) | 252 (0.665) | 128 (0.338) | 20 (0.053) | ||||
| RR | Intron | 180 (0.756) | 58 (0.244) | 65 (0.580) | 50 (0.446) | 4 (0.036) | 0.82 (0.58-1.18) | 0.269 | 4.270 | 0.118 |
| rs1420872 | ||||||||||
| No RR | CYLD | 587 (0.789) | 157 (0.211) | 230 (0.607) | 127 (0.335) | 15 (0.040) | ||||
| RR | Intron | 174 (0.770) | 52 (0.230) | 66 (0.589) | 42 (0.375) | 5 (0.045) | 0.89 (0.62-1.31) | 0.541 | 0.427 | 0.808 |
| rs2302759 | ||||||||||
| No RR | CYLD | 521 (0.651) | 279 (0.349) | 180 (0.475) | 161 (0.425) | 59 (0.156) | ||||
| RR | Intron | 156 (0.661) | 80 (0.339) | 50 (0.446) | 56 (0.500) | 12 (0.107) | 1.04 (0.76-1.44) | 0.782 | 2.666 | 0.264 |
P values in bold are less than 0.05 for the allelic and genotypic analyses
Genotypic analysis revealed that these associations with ENL were significant for seven of the SNPs (rs2287195, rs8044354, rs7194886, rs6500328, rs17312836, rs1861759, and rs1861758) (Table 4). We also found that 7 polymorphisms were associated with susceptibility in a dominant model (Supplemental Table 1). The most significant was SNP rs8044354 (OR 2.17 (95%CI 1.26-3.88), p=0.003). Four of these 7 polymorphisms were in linkage disequilibrium in one haplotype block (one group of 4 SNPs (rs6500328, rs17312836, rs1861759, and rs1861758)). When adjusted for ethnicity, sex, and age seven out of seven polymorphisms (rs2287195 (OR 1.93, 95%CI 1.14-3.30, p=0.015), rs8044354 (OR 2.83, 95%CI 1.52-5.28, p=0.001), rs7194886 (OR 1.73, 95%CI 1.07-2.82, p=0.027), rs6500328 (OR 1.90, 95%CI 1.18-3.07, p=0.008), rs17312836 (OR 1.97, 95%CI 1.22-3.19, p=0.005), rs1861759 (OR 2.00, 95%CI 1.25-3.22, p=0.004), and rs1861758 (OR 2.05, 95%CI 1.26-3.33, p=0.004)) remained significantly associated with ENL. Together, these data suggest that several NOD2 SNPs are associated with ENL susceptibility.
NOD2 haplotypes are associated with ENL and RR
We next constructed haplotypes of the polymorphisms that were significantly associated with RR or ENL. Ten of the 32 polymorphisms were included in the analysis (rs2287195 (0=A,1=G), rs8044354 (0=A,1=G), rs8043770 (0=C,1=G), rs7194886 (0=C,1=T), rs6500328 (0=A,1=G), rs17312836 (0=C,1=G), rs1861759 (0=A,1=C), rs4785225 (0=C,1=G), rs751271 (0=A,1=C), and rs1861758 (0=C,1=T)). We compared whether the haplotype frequencies were significantly different in those who were affected by leprosy reactional states (ENL or RR). For ENL we found one haplotype (1.1.1.1.1.1.1.1.1.1, OR 1.60, 95%CI 1.03-2.48, p=0.035) which conferred significant susceptibility to development of ENL reaction. For RR we found 1 haplotype with significant differences that conferred significant protection to RR (1.1.1.1.1.1.1.1.1.1, OR 0.647, 95%CI 0.45-0.93, p=0.020). These results suggested that haplotype analyses did not reveal greater associations than examination of single polymorphisms.
Together these results indicate that variation in the NOD2 gene region is associated with increased susceptibility to ENL, and conversely are associated with protection from Type 1 RR in leprosy. No association was observed when comparing polar leprosy types (lepromatous versus tuberculoid).
Discussion
In the present study, we used a candidate gene approach to identify an association of the chromosome 16q12 loci with leprosy occurrence and the development of leprosy reactional states in a Nepalese population. We identify several NOD2 polymorphisms that are associated with leprosy susceptibility in the Nepalese population, identifying this gene as an important factor in protection against intracellular pathogens. We also found several polymorphisms are either associated with protection from RR or are associated with increased susceptibility to ENL. To our knowledge, this study is the first to associate variation in the NOD2 region with leprosy reactional states and the first to identify genetic associations with ENL; NOD2 is the third signaling receptor gene to be associated with RR in leprosy; the other two, TLR2 and TLR1, are important in the extracellular detection of organisms [16, 34].
Like many gene association studies, potential limitations of our study may be affected by population admixture and/or a Type I false positive errors due to the problem of multiple comparisons. We adjusted our analysis for ethnicity and the major associations remained significant. In terms of multiple comparisons, there are several possible methods of adjustment. If we used a conservative Bonferroni correction and multiplied the P values by 32 for the number of analyzed SNPs, then only three associations remained significant (rs1477176 allelic association with leprosy susceptibility, and rs1477176 and rs8044354 dominant genotypic associations with leprosy susceptibility). However, because of linkage disequilibrium in genetic association studies, a strict Bonferroni correction is likely too conservative, and may increase Type II errors by falsely rejecting associations [33]. Furthermore, we found associations of multiple SNPs with leprosy (8/32), RR (7/32), and ENL (7/32). The occurrence of multiple SNP associations with these outcomes raises the likelihood that the associations remain statistically significant after adjusting for multiple comparisons. While these data are suggestive of an association between this gene region and leprosy reactive states, these findings will ultimately need to be verified in a separate population.
There are several possible mechanisms by which NOD2 polymorphisms may influence development of reactive states. RR and ENL are immunologic/inflammatory states of leprosy that represent augmented Th1 (RR) or increased Th2/TNF-α (ENL) responses that occur during the course of disease or even years after treatment [35-37]. In animal studies and ex vivo experiments NOD2 stimulation has been shown to augment both Th1 and Th2-dependent responses [38, 39]. Therefore NOD2 may augment Th1 or Th2 responses by direct recognition of M. leprae antigens. Interestingly, M. leprae contains a unique peptidoglycan structure, which may stimulate NOD2 differently and contribute to the unusual immunologic features of leprosy reactions [40]. In addition, others have also shown that NOD2 inhibits TLR2 mediated Th1 responses [41, 42], and we have reported that TLR2/TLR1 stimulation is associated with leprosy RR [16, 43]. Therefore, one effect of NOD2 may be through inhibition of TLR2 signaling.
The polymorphisms examined in this study were clustered in the chromosomal region 16q12 near NOD2 and two other immunologically important genes, SLIC1 and CYLD [44]. SLIC1 may be important in the regulation of P-selection glycoprotein ligand of (PSGL1), a protein involved with macrophage-mediated recruitment of myeloid and activated lymphocytes to tissues [45]. In addition negative regulation of the immune system by CYLD may be important in pneumonia models [46]. The polymorphisms described herein associated with ENL and RR tended to cluster in the region between SLIC1 and NOD2, suggesting that these polymorphisms may influence the expression of either the SLIC1 or NOD2 genes. Further functional studies need to be done to determine exactly which gene (SLIC1, NOD2, or CYLD), is associated with leprosy reactional states.
Several genetic studies have identified the association of NOD2 mutations with Crohn’s disease and Blau’s disease [24, 25, 47] both characterized by altered inflammatory states with granulomatous pathology. However, the association of NOD2 mutations or polymorphisms with infection has not been well studied. A mutation associated with Crohn’s disease (the NOD2-3020insC allele) has been linked to sepsis in infants of very low birth weight [48]. Also, nonsynonomous NOD2 polymorphisms have been associated with active TB in a cohort of African Americans in Houston [28]. These nonsynonomous SNPs were not included in our study due to their absence in the HapMap database Asian populations. Moreover, two previous studies found no association of NOD2 polymorphisms with TB [49, 50]. Although our study suggests an association of NOD2 variation with M. leprae susceptibility, the functional effect of these SNPs on NOD2 signaling is currently not known.
Supplementary Material
Acknowledgements
We would like to thank the staff at Anandaban hospital in Nepal for compilation of the clinical data and the leprosy patients associated with the study. Specifically, Dr. Paul Roche, Mr. Kapil Dev Neupane and Mr. Chaman Ranjit’s involvement in participant recruitment and sample collection was appreciated. We thank Carey Cassidy and Sarah Li for technical assistance.
Funding: Supported by The Heiser Program for Research in Tuberculosis and Leprosy with a grant to TRH and WRB, the National Institutes of Health with grants to GK (AI 22616 and AI 54361), and The Leprosy Mission International to MM and DAH.
Footnotes
Conflicts of interest: No conflicts of interest exist for any of the authors involved.
This work has not been presented at a major meeting.
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