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Medical Science Monitor: International Medical Journal of Experimental and Clinical Research logoLink to Medical Science Monitor: International Medical Journal of Experimental and Clinical Research
. 2019 Dec 17;25:9637–9650. doi: 10.12659/MSM.917244

Polymorphisms of the TNF Gene and Three Susceptibility Loci Are Associated with Crohn’s Disease and Perianal Fistula Crohn’s Disease: A Study among the Han Population from South China

Min Zhang 1,2,B,E,F,G,*, Xiaoyan Wang 2,3,A,C,D,F,*, Xiaodong Jiang 1,2,B, Xiangling Yang 2,3,B,C, Chuangyu Wen 2,3,C,D, Min Zhi 1,2,A,C, Xiang Gao 1,2,D,F, Pinjin Hu 1,2,A,G,, Huanliang Liu 2,3,E,G,
PMCID: PMC6929548  PMID: 31844038

Abstract

Background

Although 90 susceptibility loci of Crohn’s disease (CD) have been confirmed in the Asian population, susceptibility genes for perianal fistula of CD (pCD) in this population remain unknown. This study explored susceptibility genes for CD and pCD in the Han population from South China.

Material/Methods

In total, 490 patients diagnosed with CD between July 2012 and June 2016 at the Sixth Affiliated Hospital of Sun Yat-sen University were included and divided into the CD group (n=240) and the pCD group (n=250). The healthy control group was composed of 260 volunteers. Peripheral blood samples were taken, and single nucleotide polymorphism (SNP) locus sequencing was used to screen for susceptibility loci. SNPs were sequenced using matrix-assisted laser desorption ionization time-of-flight mass spectrometry.

Results

Nine SNPs in TNFSF1 on chromosome 9 were associated with CD. Among them, the rs6478106 locus is a risk locus for CD. The distribution frequency of the T allele of the rs6478106 SNP was significantly different between cases and controls (32.49% versus 18.27%, P<0.001). Rs72553867, located in the IRGM gene on chromosome 5, rs4409764, located in the NKX2–3 gene on chromosome 10, and rs3731772, located in the AOX1 gene on chromosome 2, were susceptibility factors for pCD. Nine SNPs located in TNFSF15 on chromosome 9 were related to CD in Han individuals from Southern China.

Conclusions

The rs6478106 T allele is associated with the risk of CD in the investigated population. SNPs rs72553867 (IRGM gene), rs4409764 (NKX2–3 gene), and rs3731772 (AOX1 gene) increase the risk of pCD.

MeSH Keywords: Crohn Disease; Fistula; Genes, vif

Background

Crohn’s disease (CD) is a major component of chronic idiopathic inflammatory disease, which primarily affects the terminal ileum and colon. A prospective, population-based study showed that the incidence rate for CD was as high as 1.09 per 100 000 person-years in China [1]. Although the CD prevalence in China is still lower than that in Western countries, this figure has increased rapidly over the past few decades [2]. The underlying etiology of CD is still undetermined [3], but it has long been thought as a consequence of an inappropriate mucosal immune response to antigenic stimulation from the gut microbiota in a genetically susceptible host [4]. Studies from twins suggested an approximately 50% genetic contribution in CD [5]. Therefore, the identification of the related genetic changes that are implicated in CD susceptibility would provide insights into the etiology of this disorder.

To the best of our knowledge, over 200 single nucleotide polymorphisms (SNPs) in several genes (such as NOD2/CARD15, NOD1/CARD4, and ABCB1) are related to CD in Western populations [69]. However, due to genetic differences, some SNPs failed to show a link to CD in the Asian population [10,11]. For example, mutations within genes from the NOD2/CARD15, ATG16L1, and IL23/Th17 signaling pathways were demonstrated to confer susceptibility to CD only in Western patients and not in Chinese and Japanese patients [1215]. In addition, studies in the Asian population have revealed some unique SNPs, e.g., c.374T>C of the DLG1 gene in Chinese patients [16], ATG16L2 and/or FCHSD2 in Chinese and South Korean patients [17,18], and SNPs in the TNFSF15 gene in East Asians [19]. These differences emphasize the importance of identifying population-specific gene variants.

Perianal fistula CD (pCD) is a subtype of CD with poor prognosis and low quality of life. According to population-based studies, the proportion of pCD ranges from 12% to 40% among CD patients, and this prevalence varies according to disease location and disease duration [20]. A European project has revealed that perianal fistula formation in CD patients might be attributed to genes including IL23R, LOC441108, PRDM1, and NOD2 [21]. Another study in the Italian population suggested an association of the SNP rs4958847 in the IRGM gene with the susceptibility to pCD [22]. Studies in Dutch, German, and Norwegian populations found an association between rs2165047 in the DLG5 gene and the NOD2 haplotype with perianal development [23,24]. Furthermore, rs72796353 in NOD2 was also reported to be significantly associated with perianal fistula development in cases devoid of SNPs rs2066844, rs2066845, and rs2066847 [25]. Among the Asian population, only 2 studies have screened potentially pathogenic SNPs in CD patients and explored their associations with perianal fistula formation. One recent study was conducted in a Japanese population and found that the AT haplotype in the TNFRSF1B gene might promote fistula development [26], while another study in a Korean population revealed the association of the rs4574921 CC genotype within the TNFSF15 gene with perianal fistula formation [27]. However, susceptibility genes and SNPs have never been assessed in the Chinese population. In addition, to reveal the unique gene variants predisposing patients to pCD, it is important to identify the differences in susceptibility genes and SNPs between non-perianal CD (npCD) patients and pCD patients, which have yet to be evaluated.

Here, we extended previous findings in the Asian population by assessing the association between the CD susceptibility loci reported in Asians to Southern Chinese CD patients to clarify the specificity of CD susceptibility genes in the Chinese population and further compare the frequencies of those loci between pCD and npCD patients to explore the SNPs conferring susceptibility to pCD in the Chinese population.

Material and Methods

Patients

In total, data pertaining to 490 CD patients diagnosed between July 2012 and June 2016 were collected from the Inflammatory Bowel Disease (IBD) Center in the Sixth Affiliated Hospital of Sun Yat-sen University, including 250 patients with perianal fistula and 240 with non-perianal fistula. The CD diagnostic criteria were based on the Expert Consensus Document of IBD diagnosis and treatment in China, 2012 [28]. Demographic and clinical information, such as age, sex, race, year of diagnosis, disease location and disease behavior, were collected from all patients. CD behavior includes B1 (non-stricturing, non-penetrating), B2 (stricturing), and B3 (penetrating). In total, 260 healthy volunteers were also recruited from Guangzhou Blood Center.

All included patients and controls were of Han ethnicity and were born in Southern China, including the provinces of Guangdong, Guangxi, Fujian, Jiangxi, Jiangsu, Zhejiang, Hunan, Hubei, Sichuan, Chongqing, Yunnan, Hainan, Taiwan, Hongkong, and Macao.

This study obtained approval from the institutional Review Board of the Sixth Affiliated Hospital, Sun Yat-sen University (IRB number: 2017ZSLYEC-017). Written informed consent was obtained from each participant.

Sample collection

Approximately 2 mL of peripheral venous blood was taken from each patient after fasting. The blood sample was centrifuged at 1000 rpm for 10 minutes. After serum removal, the sample was stored at −80°C.

Candidate locus determination

We searched the MEDLINE, EMBASE and China National Knowledge Infrastructure (CNKI) databases to identify studies reporting the candidate loci and genes implicated in Asian CD patients. Finally, 90 loci were identified as risk loci candidates for screening among CD patients (Supplementary Table 1).

DNA extraction

DNA was extracted from the peripheral blood leucocytes by standard procedures with a Blood Genomic DNA Isolation Kit (Tiangen, Beijing, China; batch no., DP335). The DNA concentration was determined and then the sample was stored at −20°C.

SNP locus sequencing

Genotyping was performed with matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) [29] on the MassARRAY platform (BGI Tech, Beijing, China).

A 4-μL reaction system consisted of PCR buffer with 1.5 mM MgCl2 (0.625 μL), 25 mM MgCl2 (0.325 μL), 25 mM dNTPs (0.1 μL), 500 nM Primer Mix (1.0 μL), 5 U/μL HotStar Taq (0.1 μL), and HPLC grade water (1.85 μL). The system was applied to a 384-well plate. Template DNA at 20 ng/μL (1 μL) was added, and a 1-minute centrifugation at 1000 rpm was performed. The amplification conditions included 94°C for 5 minutes, followed by 45 cycles of 94°C for 20 seconds, 56°C for 30 seconds, 72°C for 1 minute, and 72°C for 3 minutes, with a final holding at 4°C.

Shrimp alkaline phosphatase (SAP) mix at 2.0 μL was prepared, which contained 1.53 μL of HPLC grade water, 0.17 μL of SAP buffer (10x), and 0.3 μL of SAP enzyme (1 U/μL). Excess dNTPs were removed from the reaction system by incubating 5 μL of the reaction with the SAP mix at 37°C for 20 minutes followed by incubating it at 85°C for 5 minutes and then at 4°C until used.

Single-based extension liquid was prepared in a final volume of 2 μL, containing 0.2 μL of iPLEX Buffer Plus (0.222×), 0.2 μL of iPLEX Termination Mix (1×), 0.94 μL of Primer Mix (7 μM: 14 μM), and 0.619 μL of HPLC grade water. The liquid was used to produce 9 μL of the single-based extension reaction system. The system was subsequently subjected to 40 cycles of 94°C for 30 seconds and 94°C for 5 seconds, 5 cycles of 52°C for 5 seconds, 45 cycles of 80°C for 5 seconds and 72°C for 3 minutes, and a final holding step at 4°C. Resin purification was performed. After centrifugation, the products were sampled onto a 384-well SpectroChip (Sequenom, USA) for MALDI-TOF MS. The obtained data were analyzed with TYPER4.0.

Statistical analysis

All analyses were performed with SPSS version 20.0 (SPSS Inc., Chicago, IL, USA). Comparisons of characteristics among cases with and without perianal fistula and controls were made with one-way analysis of variance (ANOVA) or the chi-squared test whichever applicable; post hoc multiple comparisons were performed by Bonferroni correction analyses. Assessment of the genetic equilibrium of two comparison sets (CD patients versus controls; CD patients with or without perianal fistula) was made using the Hardy-Weinberg equilibrium test. Genotype frequency comparisons between the aforementioned sets were performed with the chi-squared test and are presented as odds ratios (ORs) and 95% confidence intervals (CIs). Haploview 4.2 was utilized for the linkage disequilibrium analysis. All tests were 2-sided, and P<0.05 was considered significant. The genome-wide association study (GWAS) involved statistical comparisons of hundreds of thousands of SNPs. To maintain a significance level of 0.05, the level of inspection for each comparison must be controlled to a certain extent, and we set a significance level for SNP comparisons at P<10−7.

Results

Characteristics

Generally, CD patients were older than the controls. The patients with pCD were older than those with npCD (Table 1). The majority of cases were male in all 3 groups. In addition, higher percentages of patients with npCD than of those with pCD were single and had penetrating CD.

Table 1.

Clinical characteristics of CD patients and healthy controls.

Characteristics CD with perianal fistula (n=250) CD without perianal fistula (n=240) Controls (n=260) F/χ2 value P value
Age (years) 32.61±13.32 28.51±9.72 24.34±3.96 52.66 <0.001
Male (n, %) 156 (62.4) 186 (77.5) 174 (66.9) 12.931 0.002
Location (n, %) 2.72 0.26
 Ileal±upper 17 (6.8) 26 (10.8) NA
 Colonic±upper 26 (10.4) 27 (11.3) NA
 Ileocolonic±upper 207 (82.8) 187 (77.9) NA
Behavior (n, %) 58.956 <0.001
 B1 63 (25.2) 35 (14.6) NA
 B2 72 (28.8) 39 (16.3) NA
 B3 115 (46.0) 176 (73.3) NA

CD – Crohn’s disease; B1 – non-stricturing, non-penetrating; B2 – structuring; B3 – penetrating; NA – not applicable.

Risk genetic loci screening

In total, 90 genetic loci among 750 patients were identified (Supplementary Table 1). SNPs satisfying a detection rate >90%, MAF >5 and Hardy-Weinberg equilibrium were further screened, and 70 were obtained for further analysis (Supplementary Table 2).

Correlation analysis of genotypes in CD patients

Single SNP association analysis

The frequency comparison between risk loci in CD patients and controls (Supplementary Table 3) indicated that 9 SNPs (rs10114470, rs3810936, rs6478109, rs6478108, rs4263839, rs7848647, rs4246905, rs457492, and rs6478106) were significantly related to CD (all with P<10−7 in Bonferroni multiplex analysis; Table 2). Among those SNPs, 5 were C>T mutations, 2 were G>A mutations, and the remaining 2 were T>C mutations. All those variants were located in the TNFSF15 gene on chromosome 9. Rs6478106 was the only SNP that presented correlation with the pathogenicity of CD (OR=2.15, 95% CI 1.94–3.26), while the remaining SNP exhibited protective roles against CD.

Table 2.

CD-related SNPs.

Chromosome no. dbSNP Gene Major allele Risk allele Frequency among CD group Frequency among controls Allelic test P-value OR 95% CI
9 rs10114470 TNFSF15 C T 0.283 0.566 1.41E-11 0.477 (0.385, 0.593)
9 rs3810936 TNFSF15 C T 0.383 0.565 2.40E-11 0.477 (0.384, 0.594)
9 rs6478109 TNFSF15 G A 0.370 0.539 3.55E-10 0.504 (0.406, 0.625)
9 rs6478108 TNFSF15 T C 0.274 0.543 3.71E-10 0.504 (0.406, 0.625)
9 rs4263839 TNFSF15 G A 0.373 0.541 5.08E-10 0.506 (0.407, 0.628)
9 rs7848647 TNFSF15 C T 0.371 0.539 5.11E-10 0.506 (0.408, 0.628)
9 rs4246905 TNFSF15 C T 0.265 0.429 1.18E-09 0.499 (0.398, 0.625)
9 rs457492 TNFSF15 T C 0.266 0.419 1.55E-09 0.502 (0.400, 0.628)
9 rs6478106 TNFSF15 C T 0.325 0.183 4.29E-09 2.153 (1.939, 3.257)

We further assessed the genotype distribution of rs6478106 among different age and gender groups. The results indicated that there were no associations of rs6478106 with age (≤30 vs. >30, χ2=0.386, P=0.824) or sex (male versus female, χ2=2.096, P=0.351) (Table 3).

Table 3.

Distribution of rs6478106 genotypes in different ages and sexes.

Genotypes (n) χ2 P value
CC CT TT
Age (years) ≤30 112 106 24 0.386 0.824
>30 108 115 25
Sex Male 77 64 14 2.096 0.351
Female 143 157 35

Haplotype analysis

Five SNPs (rs4574921, rs6478106, rs10114470, rs3810936, and rs4246905) were found in a 14-kb linkage disequilibrium region (block 1) on chromosome 9, while another 5 SNPs (rs4263839, rs6478108, rs6478109, rs7865494, and rs7848647) were found in a 17-kb linkage disequilibrium region (block 2) on chromosome 9. Haploview analysis showed that the haplotypes CCTTT, TTCCC, CCTCT and TCCTC in block 1 significantly increased the risk of CD (P<0.05).

Correlation analysis between genotype distribution and perianal fistula of CD

Correlation analysis between single SNP and perianal fistula of CD

The comparison analysis between pCD and npCD patients (Supplementary Table 4) indicated that rs72553867, rs4958847, rs4409764, rs888208, rs3731772, and rs1292053 were candidate SNPs for susceptibility to CD perianal fistula (adjusted P<0.05, according to the Bonferroni test). Rs72553867, rs4958847, rs4409764, rs888208, rs3731772, and rs1292053 are located on chromosomes 5, 5, 10, 2, and 17, respectively. Among these candidates, rs72553867 (OR=1.685, 95% CI 1.188–2.390) and rs4958847 (OR=1.365, 95% CI 1.047–1.778) were found to be located in an IRGM coding region on chromosome 5. Rs4409764 (OR=1.329, 95 CI% 1.033–1.709) and rs888208 (OR=1.338, 95% CI 1.032–1.735) were found to be located in the NKX2–3 gene. Rs3731772 is in the AOX1 gene (OR=1.335, 95% CI 1.025–1.740), and rs1292053 was in the coding region of TUBD1 (OR=1.300, 95% CI 1.010–1.674) (Table 4).

Table 4.

Perianal fistula of CD-associated SNP loci.

Name Chr. no Gene or locus Major/minor allele Risk allele pCD group RAF CD group RAF OR (95% CI) P allele
rs72553867 chr5 IRGM C/A A 0.194 0.125 1.685 (1.188–2.390) 0.003
rs4958847 chr5 IRGM A/G A 0.688 0.617 1.365 (1.047–1.778) 0.021
rs4409764 chr10 NKX2–3 G/T T 0.558 0.487 1.329 (1.033–1.709) 0.027
rs888208 chr10 NKX2–3 A/G A 0.656 0.588 1.338 (1.032–1.735) 0.028
rs3731772 chr2 AOX1 T/C T 0.681 0.615 1.335 (1.025–1.740) 0.032
rs1292053 chr17 TUBD1 G/A A 0.482 0.417 1.300 (1.010–1.674) 0.041

Chr. – chromosome; RAF – risk allele frequency.

Adjusted analysis between single SNPs and perianal fistula of CD

We further added age and gender as covariates to the analysis (Supplementary Table 5) and found that rs72553867 located in the IRGM gene on chromosome 5 (OR=1.770, 95% CI 1.151–2.723), rs4409764 located in the NKX2–3 gene on chromosome 10 (OR=1.886, 95% CI 1.181–3.012) and rs3731772 located in the AOX1 gene on chromosome 2 (OR=2.131, 95% CI 1.150–3.949) were SNPs that conferred susceptibility to pCD.

Haplotype analysis

Haplotype analysis revealed a 54-kb monomer block in chromosome 5 that contained 4 haplotypes, namely, CTCTAG, TCCCGA, TCACAA, and CTCTAA. Compared with the CTCTAG and CTCTAA haplotypes, haplotypes TCCCGA and TCACAA were associated with pCD (P<0.05).

Discussion

This study showed that 9 SNPs (rs10114470, rs3810936, rs6478109, rs6478108, rs4263839, rs7848647, rs4246905, rs4574921, and rs6478106) located in TNFSF15 on chromosome 9 are related to CD in the Han population from Southern China. Rs6478106 is the only risk SNP associated with CD. Further analysis revealed that rs72553867 (located in IRGM on chromosome 5), rs4409764 (located in NKX2–3 on chromosome 10) and rs3731772 (located in AOX1 on chromosome 2) increase the risk of pCD.

TNFSF15 is mainly expressed in endothelial cells and can be induced in myeloid cells after the ligation of TLR and FcR by IgG ICs and the co-stimulation of T cells through the receptor DR3 [30]. Studies have confirmed the upregulated mRNA and protein levels of TNFSF15 in macrophages and CD4+/CD8+ lymphocytes in the intestinal lamina propria of CD patients [31]. TNFSF15 can bind to death domain receptor 3 and provide co-stimulatory signals that activate lymphocytes, inducing IFN-γ secretion and prompting participation in inflammatory responses [32,33]. Therefore, excessive expression of TNFSF15 can initiate and aggravate mucosal inflammation in CD patients. In European populations, the association of the TNFSF15 polymorphism with CD susceptibility has been widely reported [34,35]. Rs4979462 and rs7848647 in TNFSF15 were reported to be related with CD in Korean and Japanese populations [18,27,36]. In China, only 1 study was conducted on the association between TNFSF15 and CD, and the authors found that the 3 SNPs in TNFSF15 (rs3810936, rs6478109, rs7848647) were not significantly associated with CD genetic susceptibility and clinical subtypes in the Han population [37], which contrasts with our results that found 9 SNPs (rs10114470, rs3810936, rs6478109, rs6478108, rs4263839, rs7848647, rs4246905, rs4574921, and rs6478106) in TNFSF15 were related to CD. However, this study had a small sample size (42 CD patients and 49 healthy), which might lead to a limited power to discover significant associations [37]. Consistent with the results in the Japanese population [38], our analyses also indicated that rs6478106 was a susceptibility SNP for CD. Our analysis further revealed that this association had no relationship with age or sex. Therefore, we propose that the genetic variation of TNFSF15, especially rs6478106T, is related to an increased risk for CD in China. The genetic variations of TNFSF15 in this study may provide evidence regarding the etiology of the disease and information that may be important for the development of treatments.

IRGM is widely expressed in various human cells and plays an important regulatory role in intracellular pathogen-associated immunity. IFN-γ can induce the expression of the IRGM mouse homologue LRG-47 and produce auto lysosomes, while the lack of LRG-47 results in an increased susceptibility to infection [39]. The rs13361189 and rs4958847 loci of IRGM were confirmed to be related to CD susceptibility in a large-scale clinical trial [40]. An Italian study showed that the polymorphisms rs1000113 and rs4958847 in the autophagy gene IRGM might participate in the pathogenesis of CD and that the polymorphism of rs4958847 was related to fistula behavior [22]. Another study among the Korean population suggested that rs10065172 and rs72553867 are protective factors against the development of CD [41]. Although increasing efforts have been devoted to focusing on the associations of IRGM mutations with CD, research on CD susceptibility genes in the Han population remains limited. In the study conducted by Zheng et al., 318 CD patients were examined, but no association between the rs13361189 polymorphism in IRGM and CD was observed for the Chinese population [42], consistent with our result. We also found that in addition to rs4958847, the rs72553867 polymorphism was also closely related to the formation of perianal fistula in the Southern Han population. Our results suggested that IRGM gene polymorphisms might affect IRGM expression and thus alter the severity of intestinal mucositis.

Previous studies indicated the genetic association of NKX2–3 with pCD. Yu et al. analyzed the mRNA expression and protein level of NKX2–3 in American patients with familial IBD and found a significant link of NKX2–3 to CD [43]. Another Japanese study also found that the rs10883365 polymorphism of NKX2–3 was positively correlated with CD [44]. In addition, a Korean study showed that the rs88208 locus in NKX2–3 was also associated with CD, whereas studies in the Chinese population had the opposite conclusion [45,46]. In the southern Han population, our study showed a significant relation between the rs4409764 and rs888208 sites of NKX2–3 and the pathogenesis of pCD. More noteworthy, this study also found that rs3731772 was significantly associated with pCD in the Han population in southern China. The results of our study may provide clues for the function of the AOX1 gene in patients with fistula CD.

Our study suffered from several potential limitations. First, screening for selected candidate loci and genes instead of genome-wide sequencing might lead to missed pathogenic SNPs. However, the selection of our SNP pool was based on multiple related studies that were obtained through a systematic search in MEDLINE and 2 other comprehensive databases in China. Second, we did not perform functional genomics research in this study. Functional analysis is helpful in ascertaining the actual roles of those genes, and our analysis may lay the groundwork for further potential function analyses. Third, although this study is the first confirmative research on susceptibility loci associated with perianal fistula CD in the Chinese population, it is preliminary and suffers from a small sample size based on a single center. Thus, the results of this study need to be validated by future multicenter studies with a large sample.

Conclusions

In the Han population from South China, 9 SNPs in TNFSF15 are related to CD and 3 SNPs located in IRGM, NKX2–3, and AOX1 increase the risk of pCD. This study is the first confirmative study on susceptibility loci associated with perianal fistula CD in this population, and its results are helpful for the exploration of new disease-associated mechanisms in the future.

Supplementary Data

Supplementary Table 1.

Risk locus candidates for screening among CD patients.

Gene SNP Chr G-position Allele Functional consequence
4p14 rs1487630 4 38335823 C>T Intron variant
ATG16L1 rs2241880 2 234183368 A>G Missense
ATG16L2 rs11235604 11 72533536 C>T Missense
ATG16L2-FCHSD2 rs11235667 11 72863697 A>G
BTNL2 rs28362680 6 32370816 G>A Intron variant
CARD9 rs200735402 9 139265120 C>T Missense
CDKAL1 rs6908425 6 20728731 T>C Intron variant
DEFB1 rs2978880 8 6724306 G>A Upstream variant 2KB
DNAH12 rs4462937 3 57414434 A>G Missense
DR4 rs13278062 8 23082971 G>T Upstream variant 2KB
DR4 rs20575 8 23059324 C>G Missense
DR5 rs1047266 8 22900701 G>A Intron variant
DLG1 rs527829647 3 197194534 A>G Missense
DLG1 rs1134986 3 197138371 C>T Missense
FUT3 rs28362459 19 5844781 A>C Missense
FUT3 rs3745635 19 5844332 C>T Missense
FUT3 rs3894326 19 5843773 A>T Missense
GPR35 rs3749172 2 241570249 A>C Missense
HLA-DQA2 rs3208181 6 32713030 T>C Synonymous codon
IL-23R rs11209026 1 67705958 G>A Missense
IL-23R rs6588248 1 67652984 T>G Intron variant
IL-23R rs7517847 1 67681669 T>G Intron variant
IL-23R rs1004819 1 67670213 G>A Intron variant
IL-23R rs76418789 1 67648596 G>A Missense
IL-23R rs11209032 1 67740092 G>A
IL-27 rs153109 16 28507775 T>C Intron variant
IRF5 rs2004640 7 128578301 G>T Intron variant
IRF5 rs3807306 7 128580680 G>T Intron variant
IRGM rs10065172 5 150848436 C>T Synonymous codon
IRGM rs11741861 5 150898347 A>G Intron variant
IRGM rs12654043 5 150846533 A>G Utr variant 5 prime
IRGM rs13361189 5 150843825 T>C
IRGM rs4958847 5 150860025 G>A Intron variant
IRGM rs72553867 5 150848404 C>A Missense
IRGM rs9637870 5 150848053 G>A Utr variant 5 prime
IRGM rs9637876 5 150847863 C>T Utr variant 5 prime
MHC rs7765379 6 32680928 T>G
MHC rs9271366 6 32619077 G>A
BTNL2 rs10947261 6 32405455 G>T Intron variant
NFKBIA rs2273650 14 35870798 C>T Utr variant 3 prime
NKX2–3 rs10883365 10 101287764 G>A Nc transcript variant
NKX2–3 rs4409764 10 101284237 T>G
NKX2–3 rs888208 10 101284237 T>G
NOTCH4 rs422951 6 32188383 T>C Missense
PPP5C rs4802307 19 46346549 G>T Upstream variant 2KB
PTPN2 rs514000 18 12854073 C>T Intron variant
PUS10 rs13003464 2 61186829 A>G Intron variant
PUS10 rs7608910 2 60977721 A>G Intron variant
RNASET2 rs2149085 6 167371110 T>C Upstream variant 2KB
SLC22A4 rs1050152 5 132340627 C>T Intron variant
SLC25A15-ELF1-WBP4 rs7329174 13 41558110 A>G Intron variant
SMNDC1-DUSP5 rs11195128 10 112186148 C>T
SOX11 rs11894081 2 5664008 G>T
STAT3 rs1053004 17 40466092 G>A Utr variant 3 prime
STAT3 rs9891119 17 40507980 A>C Intron variant
STAT4 rs7574865 2 191964633 T>G Intron variant
TBC1D1-KLF3 rs6856616 4 38325036 T>C
TNF-α rs1799964 6 31542308 T>C Downstream variant 500B
TNF-α rs1800630 6 31542476 C>A Downstream variant 500B
TUBD1 rs1292053 17 59886176 A>G Intron variant
TNFSF15 rs10114470 9 117547772 T>C Utr variant 3 prime
TNFSF15 rs3810936 9 117552885 T>C Synonymous codon
TNFSF15 rs4263839 9 117566440 A>G Intron variant
TNFSF15 rs4574921 9 117538334 C>T
TNFSF15 rs6478106 9 117545666 C>T
TNFSF15 rs6478108 9 117558703 C>T Intron variant
TNFSF15 rs6478109 9 117568766 A>G Upstream variant 2KB
TNFSF15 rs7848647 9 117569046 T>C Upstream variant 2KB
TNFSF15 rs7865494 9 117576479 C>T
TNFSF15 rs4246905 9 114790969 T>C Intron variant
TNFSF8 rs3181374 9 117665187 A>G Intron variant
USP25 rs2823256 21 16784706 G>A Intron variant
ZMIZ1 rs1250569 10 81045207 T>C Intron variant
ZMIZ1 rs1250546 10 79272775 A>G Intron variant
ZNF365 rs224143 10 64477836 G>A
rs1145816 6 91663151 C>T
LOC105370520 rs1495465 14 58016414 C>A Upstream variant 2KB
rs10761659 10 64445564 A>G
LOC105379031 rs7702331 5 73255307 A>G Intron variant
rs1819333 6 166960059 T>G
LOC105377139 rs7282490 21 44195858 G>A Upstream variant 2KB
NDUT15 rs186364861 13 48611934 G>A Missense
ABCC4 rs3765534 13 95815415 C>T Missense
AOX1 rs3731772 2 12739259 T>C
ITPA rs1127354 20 3193842 C>A Intron variant, missense
MTHFR rs1801133 1 11856378 G>A Missense
GSTP1 rs1695 11 67585218 A>G Missense
RANTES/CCL5 rs2107538 17 34207780 C>T Intron variant
CCR5 rs1799987 3 46411935 A>G Intron variant
CCR5 rs3181036 3 46412559 C>T Intron variant

Supplementary Table 2.

SNPs selected for analysis.

No. SNP No. SNP No. SNP No. SNP
1 rs1004819 19 rs3765534 37 rs6478108 55 rs1801133
2 rs10065172 20 rs3810936 38 rs7608910 56 rs10883365
3 rs10114470 21 rs514000 39 rs2107538 57 rs1127354
4 rs1053004 22 rs6478109 40 rs3181374 58 rs1250546
5 rs10761659 23 rs2149085 41 rs3894326 59 rs1819333
6 rs11195128 24 rs3749172 42 rs4462937 60 rs2823256
7 rs11741861 25 rs422951 43 rs4958847 61 rs3731772
8 rs13361189 26 rs7282490 44 rs6478106 62 rs4246905
9 rs1799964 27 rs7574865 45 rs7517847 63 rs4574921
10 rs2004640 28 rs888208 46 rs7848647 64 rs72553867
11 rs2241880 29 rs11209032 47 rs7865494 65 rs7702331
12 rs3208181 30 rs11235667 48 rs11235604 66 rs1487630
13 rs3807306 31 rs1292053 49 rs1250569 67 rs1695
14 rs4409764 32 rs1799987 50 rs153109 68 rs1800630
15 rs2273650 33 rs4263839 51 rs3181036 69 rs1047266
16 rs3745635 34 rs6588248 52 rs11894081 70 rs10947261
17 rs7329174 35 rs6908425 53 rs13003464
18 rs7765379 36 rs9637876 54 rs1134986

Supplementary Table 3.

Analysis results for 70 SNPs related to CD.

SNP Chr. Gene Frequency among the CD group Frequency among controls Allelic test P-value OR 95% CI
rs10114470 9 TNFSF15 0.3834 0.5656 1.41E-11 0.4774 (0.3847, 0.5925)
rs3810936 9 TNFSF15 0.3826 0.565 2.40E-11 0.4772 (0.3835, 0.5938)
rs6478109 9 TNFSF15 0.3702 0.5386 3.55E-10 0.5035 (0.4058, 0.6247)
rs6478108 9 TNFSF15 0.374 0.5425 3.71E-10 0.5039 (0.4061, 0.6252)
rs4263839 9 TNFSF15 0.3729 0.5405 5.08E-10 0.5055 (0.4072, 0.6277)
rs7848647 9 TNFSF15 0.3714 0.5388 5.11E-10 0.5059 (0.4075, 0.628)
rs4246905 9 TNFSF15 0.2645 0.4189 1.18E-09 0.4989 (0.3981, 0.6252)
rs4574921 9 TNFSF15 0.2656 0.4189 1.55E-09 0.5015 (0.4003, 0.6285)
rs6478106 9 TNFSF15 0.3249 0.1827 4.29E-09 2.153 (1.661, 2.79)
rs11209032 1 IL-23R 0.4451 0.5598 2.35E-05 0.6307 (0.5091, 0.7814)
rs6588248 1 IL23R 0.3119 0.4066 0.0002632 0.6613 (0.5293, 0.8263)
rs7329174 13 ELF1 0.2758 0.1988 0.001074 1.535 (1.186, 1.986)
rs422951 6 NOTCH4 0.146 0.2115 0.00125 0.6374 (0.4843, 0.8391)
rs7517847 1 IL23R 0.3831 0.4692 0.001257 0.7025 (0.5667, 0.871)
rs13361189 5 IRGM 0.5031 0.4205 0.0024 1.395 (1.125, 1.73)
rs10065172 5 IRGM 0.5 0.4186 0.002739 1.389 (1.12, 1.722)
rs11235604 11 ATG16L2 0.1374 0.08687 0.004163 1.674 (1.173, 2.388)
rs888208 10 NKX2–3 0.3776 0.4537 0.004294 0.7304 (0.5886, 0.9064)
rs1487630 4 4p14 0.2789 0.2115 0.004379 1.442 (1.12, 1.855)
rs4958847 5 IRGM 0.3459 0.4187 0.006374 0.7342 (0.5879, 0.917)
rs9637876 5 IRGM 0.4918 0.4189 0.007165 1.342 (1.083, 1.664)
rs11235667 11 ATG16L2-FCHSD2 0.1381 0.09073 0.007553 1.606 (1.132, 2.278)
rs11741861 5 ZNF300 0.4706 0.4 0.00879 1.333 (1.075, 1.654)
rs1004819 1 IL23R 0.3842 0.4514 0.01217 0.7584 (0.6109, 0.9416)
rs10883365 10 LINC01475 0.5228 0.4554 0.01347 1.31 (1.057, 1.623)
rs3745635 19 FUT3 0.1701 0.1236 0.01765 1.454 (1.066, 1.982)
rs1799987 3 CCR5 0.3499 0.4115 0.01857 0.7696 (0.6187, 0.9573)
rs11195128 10 SMNDC1-DUSP5 0.1724 0.1269 0.02095 1.433 (1.055, 1.947)
rs514000 18 PTPN2 0.4168 0.3546 0.02101 1.301 (1.04, 1.627)
rs4409764 10 NKX2–3 0.4765 0.5388 0.02207 0.7792 (0.6292, 0.9649)
rs10947261 6 BTNL2 0.335 0.281 0.03279 1.289 (1.021, 1.628)
rs3749172 2 GPR35 0.3641 0.3105 0.04015 1.271 (1.011, 1.599)
rs153109 16 IL27 0.4074 0.3533 0.04123 1.259 (1.009, 1.57)
rs7765379 6 MHC 0.1068 0.07529 0.04907 1.469 (0.9997, 2.159)
rs3181374 10 TNFSF8 0.425 0.4764 0.06347 0.8124 (0.6523, 1.012)
rs3181036 3 CCR5 0.168 0.2066 0.0651 0.7757 (0.592, 1.016)
rs1053004 17 STAT3 0.3476 0.3923 0.08707 0.8255 (0.6626, 1.028)
rs6908425 6 CDKAL1 0.1476 0.1815 0.0897 0.7811 (0.587, 1.039)
rs7865494 9 TNFSF15 0.2879 0.249 0.109 1.219 (0.9566, 1.554)
rs7574865 2 STAT4 0.3398 0.3813 0.1108 0.835 (0.669, 1.042)
rs13003464 2 PUS10 0.05215 0.03475 0.1269 1.528 (0.8833, 2.644)
rs2004640 7 IRF5 0.2945 0.2577 0.1319 1.202 (0.9459, 1.528)
rs7282490 21 LOC105377139 0.449 0.4884 0.1463 0.8536 (0.6894, 1.057)
rs1250546 10 ZMIZ1 0.4213 0.4593 0.16 0.8571 (0.6912, 1.063)
rs1292053 17 TUBD1 0.4483 0.4826 0.2055 0.8712 (0.7038, 1.079)
rs10761659 10 LOC105370520 0.2162 0.2442 0.2187 0.8537 (0.6635, 1.099)
rs7608910 2 PUS10 0.05263 0.03846 0.22 1.389 (0.82, 2.353)
rs2273650 14 NFKBIA 0.2684 0.2934 0.3062 0.8835 (0.6968, 1.12)
rs11894081 2 SOX11 0.4214 0.3944 0.3205 1.118 (0.897, 1.394)
rs1250569 10 ZMIZ1 0.4287 0.4535 0.3584 0.9044 (0.7298, 1.121)
rs2823256 21 LOC101927745 0.3126 0.3359 0.3598 0.8992 (0.7162, 1.129)
rs2241880 2 ATG16L1 0.3742 0.3514 0.3813 1.104 (0.8845, 1.378)
rs3807306 7 IRF5 0.1829 0.166 0.4147 1.125 (0.848, 1.491)
rs72553867 5 IRGM 0.1596 0.1757 0.4237 0.8908 (0.671, 1.183)
rs7702331 5 LOC105379031 0.1154 0.1293 0.431 0.878 (0.635, 1.214)
rs1134986 3 DLG1 0.06302 0.05405 0.4878 1.177 (0.7425, 1.866)
rs1801133 1 MTHFR 0.2957 0.2791 0.5012 1.085 (0.8561, 1.374)
rs3894326 19 FUT3 0.1447 0.1564 0.5467 0.913 (0.6791, 1.228)
rs2107538 17 CCL5 0.3418 0.3295 0.6314 1.057 (0.8432, 1.325)
rs1799964 6 LTA 0.1752 0.1846 0.6486 0.9379 (0.7117, 1.236)
rs1800630 6 LTA 0.1586 0.1673 0.6617 0.938 (0.7043, 1.249)
rs2149085 6 RNASET2 0.3929 0.3833 0.7181 1.041 (0.8362, 1.296)
rs1047266 8 TNFRSF10B 0.277 0.2857 0.7208 0.9577 (0.7555, 1.214)
rs3731772 2 AOX1 0.3508 0.3417 0.7247 1.041 (0.8319, 1.303)
rs4462937 3 DNAH12 0.3931 0.4023 0.7281 0.962 (0.7735, 1.197)
rs1819333 6 LOC105379031 0.3909 0.3822 0.7426 1.037 (0.8333, 1.292)
rs1127354 20 ITPA 0.1711 0.1647 0.7537 1.047 (0.7862, 1.394)
rs3208181 6 HLA-DQA2 0.1245 0.1192 0.7671 1.05 (0.7585, 1.455)
rs1695 11 GSTP1 0.1765 0.1712 0.7941 1.038 (0.7837, 1.375)
rs3765534 13 ABCC4 0.05183 0.05385 0.8676 0.9605 (0.5981, 1.543)

SNPs are ordered according to P values. Chr – chromosome.

Supplementary Table 4.

Analysis results for SNPs related to pCD.

Name Chr. No. Gene or locus Major/minor allele Risk allele Case RAF Control RAF OR (95% CI) P value allele P value genotype
rs72553867 chr5 IRGM C/A A 0.194 0.125 1.685 (1.188–2.390) 0.003 0.002a
rs4958847 chr5 IRGM A/G A 0.688 0.617 1.365 (1.047–1.778) 0.021 0.025c
rs4409764 chr10 NKX2–3 G/T T 0.558 0.487 1.329 (1.033–1.709) 0.027 0.007a
rs888208 chr10 NKX2–3 A/G A 0.656 0.588 1.338 (1.032–1.735) 0.028 0.004a
rs3731772 chr2 AOX1 T/C T 0.681 0.615 1.335 (1.025–1.740) 0.032 0.032a
rs1292053 chr17 TUBD1 G/A A 0.482 0.417 1.300 (1.010–1.674) 0.041 0.035c
rs3894326 chr19 FUT3 A/T A 0.880 0.836 1.438 (1.001–2.064) 0.049 0.045c
rs10883365 chr10 NKX2–3 A/G G 0.548 0.496 1.234 (0.957–1.590) 0.105 0.033a
rs3181374 chr9 TNFSF8 A/G A 0.687 0.642 1.226 (0.939–1.600) 0.135 0.069a
rs11235667 chr11 ATG16L2-FCHSD2 A/G A 0.877 0.844 1.314 (0.914–1.887) 0.139 0.148c
rs3749172 chr2 GPR35 C/A A 0.387 0.343 1.209 (0.926–1.577) 0.162 0.055b
rs2241880 chr2 ATG16L1 A/G G 0.394 0.355 1.185 (0.915–1.534) 0.199 0.182b
rs153109 chr16 IL27 T/C T 0.613 0.573 1.181 (0.914–1.526) 0.204 0.094a
rs1800630 chr6 TNF C/A C 0.857 0.828 1.242 (0.881–1.752) 0.216 0.168b
rs11235604 chr11 ATG16L2 C/T C 0.875 0.848 1.256 (0.873–1.805) 0.219 0.225c
rs7282490 chr21 ICOSLG G/A A 0.468 0.429 1.168 (0.907–1.504) 0.228 0.205b
rs2107538 chr17 CCL5 C/T T 0.360 0.325 1.168 (0.897–1.522) 0.249 0.239c
rs10114470 chr9 TNFSF15 C/T C 0.633 0.598 1.160 (0.897–1.500) 0.259 0.128a
rs514000 chr18 PTPN2 T/C T 0.600 0.564 1.160 (0.895–1.501) 0.262 0.106a
rs11209032 chr1 IL23R-IL12RB2 A/G G 0.464 0.429 1.149 (0.893–1.478) 0.281 0.275a

SNPs are ordered according to P values.

a

p value for the dominant model;

b

p value for the regressive model;

c

p value for the additive model.

Chr – chromosome; RAF – risk allele frequency

Supplementary Table 5.

Logistic analysis results for SNPs related to pCD.

Risk allele Univariate Multivariate
OR (95% CI) P value OR (95% CI) P value
rs72553867a AC+AA vs. CC 1.874 (1.246–2.817) 0.003 1.770 (1.151–2.723) 0.009
rs4958847c A vs. G 1.366 (1.045–1.786) 0.023
rs4409764a GT+TT vs. GG 1.780 (1.149–2.758) 0.010 1.886 (1.181–3.012) 0.008
rs888208a AG+AA vs. GG 2.087 (1.205–3.616) 0.009
rs3731772a T C+TT vs. CC 1.941 (1.099–3.428) 0.022 2.131 (1.150–3.949) 0.016
rs1292053a AG+AA vs. GG 1.487 (0.992–2.230) 0.055
rs3894326c A vs. T 1.380 (0.943–2.017) 0.097
Age (year) / / 0.968 (0.951–0.984) <0.001
Male/Female / / 1.608 (1.059–2.442) 0.026
a

Dominant model;

c

additive model.

Acknowledgement

We gratefully acknowledge Yongshui Fu for providing serum samples from healthy controls.

Footnotes

Source of support: This study was supported by the National Natural Science Foundation of China (No. 81600412), the Guangdong Provincial Department of Science and Technology (No. 2017A050501055), the Guangzhou Science and Technology Program projects (No.201604046001, 2016201604030007, 201604020005), the Overseas Excellent Professor Project, the Ministry of Education of China and the National Key Clinical Discipline

Conflicts of interest

None.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Table 1.

Risk locus candidates for screening among CD patients.

Gene SNP Chr G-position Allele Functional consequence
4p14 rs1487630 4 38335823 C>T Intron variant
ATG16L1 rs2241880 2 234183368 A>G Missense
ATG16L2 rs11235604 11 72533536 C>T Missense
ATG16L2-FCHSD2 rs11235667 11 72863697 A>G
BTNL2 rs28362680 6 32370816 G>A Intron variant
CARD9 rs200735402 9 139265120 C>T Missense
CDKAL1 rs6908425 6 20728731 T>C Intron variant
DEFB1 rs2978880 8 6724306 G>A Upstream variant 2KB
DNAH12 rs4462937 3 57414434 A>G Missense
DR4 rs13278062 8 23082971 G>T Upstream variant 2KB
DR4 rs20575 8 23059324 C>G Missense
DR5 rs1047266 8 22900701 G>A Intron variant
DLG1 rs527829647 3 197194534 A>G Missense
DLG1 rs1134986 3 197138371 C>T Missense
FUT3 rs28362459 19 5844781 A>C Missense
FUT3 rs3745635 19 5844332 C>T Missense
FUT3 rs3894326 19 5843773 A>T Missense
GPR35 rs3749172 2 241570249 A>C Missense
HLA-DQA2 rs3208181 6 32713030 T>C Synonymous codon
IL-23R rs11209026 1 67705958 G>A Missense
IL-23R rs6588248 1 67652984 T>G Intron variant
IL-23R rs7517847 1 67681669 T>G Intron variant
IL-23R rs1004819 1 67670213 G>A Intron variant
IL-23R rs76418789 1 67648596 G>A Missense
IL-23R rs11209032 1 67740092 G>A
IL-27 rs153109 16 28507775 T>C Intron variant
IRF5 rs2004640 7 128578301 G>T Intron variant
IRF5 rs3807306 7 128580680 G>T Intron variant
IRGM rs10065172 5 150848436 C>T Synonymous codon
IRGM rs11741861 5 150898347 A>G Intron variant
IRGM rs12654043 5 150846533 A>G Utr variant 5 prime
IRGM rs13361189 5 150843825 T>C
IRGM rs4958847 5 150860025 G>A Intron variant
IRGM rs72553867 5 150848404 C>A Missense
IRGM rs9637870 5 150848053 G>A Utr variant 5 prime
IRGM rs9637876 5 150847863 C>T Utr variant 5 prime
MHC rs7765379 6 32680928 T>G
MHC rs9271366 6 32619077 G>A
BTNL2 rs10947261 6 32405455 G>T Intron variant
NFKBIA rs2273650 14 35870798 C>T Utr variant 3 prime
NKX2–3 rs10883365 10 101287764 G>A Nc transcript variant
NKX2–3 rs4409764 10 101284237 T>G
NKX2–3 rs888208 10 101284237 T>G
NOTCH4 rs422951 6 32188383 T>C Missense
PPP5C rs4802307 19 46346549 G>T Upstream variant 2KB
PTPN2 rs514000 18 12854073 C>T Intron variant
PUS10 rs13003464 2 61186829 A>G Intron variant
PUS10 rs7608910 2 60977721 A>G Intron variant
RNASET2 rs2149085 6 167371110 T>C Upstream variant 2KB
SLC22A4 rs1050152 5 132340627 C>T Intron variant
SLC25A15-ELF1-WBP4 rs7329174 13 41558110 A>G Intron variant
SMNDC1-DUSP5 rs11195128 10 112186148 C>T
SOX11 rs11894081 2 5664008 G>T
STAT3 rs1053004 17 40466092 G>A Utr variant 3 prime
STAT3 rs9891119 17 40507980 A>C Intron variant
STAT4 rs7574865 2 191964633 T>G Intron variant
TBC1D1-KLF3 rs6856616 4 38325036 T>C
TNF-α rs1799964 6 31542308 T>C Downstream variant 500B
TNF-α rs1800630 6 31542476 C>A Downstream variant 500B
TUBD1 rs1292053 17 59886176 A>G Intron variant
TNFSF15 rs10114470 9 117547772 T>C Utr variant 3 prime
TNFSF15 rs3810936 9 117552885 T>C Synonymous codon
TNFSF15 rs4263839 9 117566440 A>G Intron variant
TNFSF15 rs4574921 9 117538334 C>T
TNFSF15 rs6478106 9 117545666 C>T
TNFSF15 rs6478108 9 117558703 C>T Intron variant
TNFSF15 rs6478109 9 117568766 A>G Upstream variant 2KB
TNFSF15 rs7848647 9 117569046 T>C Upstream variant 2KB
TNFSF15 rs7865494 9 117576479 C>T
TNFSF15 rs4246905 9 114790969 T>C Intron variant
TNFSF8 rs3181374 9 117665187 A>G Intron variant
USP25 rs2823256 21 16784706 G>A Intron variant
ZMIZ1 rs1250569 10 81045207 T>C Intron variant
ZMIZ1 rs1250546 10 79272775 A>G Intron variant
ZNF365 rs224143 10 64477836 G>A
rs1145816 6 91663151 C>T
LOC105370520 rs1495465 14 58016414 C>A Upstream variant 2KB
rs10761659 10 64445564 A>G
LOC105379031 rs7702331 5 73255307 A>G Intron variant
rs1819333 6 166960059 T>G
LOC105377139 rs7282490 21 44195858 G>A Upstream variant 2KB
NDUT15 rs186364861 13 48611934 G>A Missense
ABCC4 rs3765534 13 95815415 C>T Missense
AOX1 rs3731772 2 12739259 T>C
ITPA rs1127354 20 3193842 C>A Intron variant, missense
MTHFR rs1801133 1 11856378 G>A Missense
GSTP1 rs1695 11 67585218 A>G Missense
RANTES/CCL5 rs2107538 17 34207780 C>T Intron variant
CCR5 rs1799987 3 46411935 A>G Intron variant
CCR5 rs3181036 3 46412559 C>T Intron variant

Supplementary Table 2.

SNPs selected for analysis.

No. SNP No. SNP No. SNP No. SNP
1 rs1004819 19 rs3765534 37 rs6478108 55 rs1801133
2 rs10065172 20 rs3810936 38 rs7608910 56 rs10883365
3 rs10114470 21 rs514000 39 rs2107538 57 rs1127354
4 rs1053004 22 rs6478109 40 rs3181374 58 rs1250546
5 rs10761659 23 rs2149085 41 rs3894326 59 rs1819333
6 rs11195128 24 rs3749172 42 rs4462937 60 rs2823256
7 rs11741861 25 rs422951 43 rs4958847 61 rs3731772
8 rs13361189 26 rs7282490 44 rs6478106 62 rs4246905
9 rs1799964 27 rs7574865 45 rs7517847 63 rs4574921
10 rs2004640 28 rs888208 46 rs7848647 64 rs72553867
11 rs2241880 29 rs11209032 47 rs7865494 65 rs7702331
12 rs3208181 30 rs11235667 48 rs11235604 66 rs1487630
13 rs3807306 31 rs1292053 49 rs1250569 67 rs1695
14 rs4409764 32 rs1799987 50 rs153109 68 rs1800630
15 rs2273650 33 rs4263839 51 rs3181036 69 rs1047266
16 rs3745635 34 rs6588248 52 rs11894081 70 rs10947261
17 rs7329174 35 rs6908425 53 rs13003464
18 rs7765379 36 rs9637876 54 rs1134986

Supplementary Table 3.

Analysis results for 70 SNPs related to CD.

SNP Chr. Gene Frequency among the CD group Frequency among controls Allelic test P-value OR 95% CI
rs10114470 9 TNFSF15 0.3834 0.5656 1.41E-11 0.4774 (0.3847, 0.5925)
rs3810936 9 TNFSF15 0.3826 0.565 2.40E-11 0.4772 (0.3835, 0.5938)
rs6478109 9 TNFSF15 0.3702 0.5386 3.55E-10 0.5035 (0.4058, 0.6247)
rs6478108 9 TNFSF15 0.374 0.5425 3.71E-10 0.5039 (0.4061, 0.6252)
rs4263839 9 TNFSF15 0.3729 0.5405 5.08E-10 0.5055 (0.4072, 0.6277)
rs7848647 9 TNFSF15 0.3714 0.5388 5.11E-10 0.5059 (0.4075, 0.628)
rs4246905 9 TNFSF15 0.2645 0.4189 1.18E-09 0.4989 (0.3981, 0.6252)
rs4574921 9 TNFSF15 0.2656 0.4189 1.55E-09 0.5015 (0.4003, 0.6285)
rs6478106 9 TNFSF15 0.3249 0.1827 4.29E-09 2.153 (1.661, 2.79)
rs11209032 1 IL-23R 0.4451 0.5598 2.35E-05 0.6307 (0.5091, 0.7814)
rs6588248 1 IL23R 0.3119 0.4066 0.0002632 0.6613 (0.5293, 0.8263)
rs7329174 13 ELF1 0.2758 0.1988 0.001074 1.535 (1.186, 1.986)
rs422951 6 NOTCH4 0.146 0.2115 0.00125 0.6374 (0.4843, 0.8391)
rs7517847 1 IL23R 0.3831 0.4692 0.001257 0.7025 (0.5667, 0.871)
rs13361189 5 IRGM 0.5031 0.4205 0.0024 1.395 (1.125, 1.73)
rs10065172 5 IRGM 0.5 0.4186 0.002739 1.389 (1.12, 1.722)
rs11235604 11 ATG16L2 0.1374 0.08687 0.004163 1.674 (1.173, 2.388)
rs888208 10 NKX2–3 0.3776 0.4537 0.004294 0.7304 (0.5886, 0.9064)
rs1487630 4 4p14 0.2789 0.2115 0.004379 1.442 (1.12, 1.855)
rs4958847 5 IRGM 0.3459 0.4187 0.006374 0.7342 (0.5879, 0.917)
rs9637876 5 IRGM 0.4918 0.4189 0.007165 1.342 (1.083, 1.664)
rs11235667 11 ATG16L2-FCHSD2 0.1381 0.09073 0.007553 1.606 (1.132, 2.278)
rs11741861 5 ZNF300 0.4706 0.4 0.00879 1.333 (1.075, 1.654)
rs1004819 1 IL23R 0.3842 0.4514 0.01217 0.7584 (0.6109, 0.9416)
rs10883365 10 LINC01475 0.5228 0.4554 0.01347 1.31 (1.057, 1.623)
rs3745635 19 FUT3 0.1701 0.1236 0.01765 1.454 (1.066, 1.982)
rs1799987 3 CCR5 0.3499 0.4115 0.01857 0.7696 (0.6187, 0.9573)
rs11195128 10 SMNDC1-DUSP5 0.1724 0.1269 0.02095 1.433 (1.055, 1.947)
rs514000 18 PTPN2 0.4168 0.3546 0.02101 1.301 (1.04, 1.627)
rs4409764 10 NKX2–3 0.4765 0.5388 0.02207 0.7792 (0.6292, 0.9649)
rs10947261 6 BTNL2 0.335 0.281 0.03279 1.289 (1.021, 1.628)
rs3749172 2 GPR35 0.3641 0.3105 0.04015 1.271 (1.011, 1.599)
rs153109 16 IL27 0.4074 0.3533 0.04123 1.259 (1.009, 1.57)
rs7765379 6 MHC 0.1068 0.07529 0.04907 1.469 (0.9997, 2.159)
rs3181374 10 TNFSF8 0.425 0.4764 0.06347 0.8124 (0.6523, 1.012)
rs3181036 3 CCR5 0.168 0.2066 0.0651 0.7757 (0.592, 1.016)
rs1053004 17 STAT3 0.3476 0.3923 0.08707 0.8255 (0.6626, 1.028)
rs6908425 6 CDKAL1 0.1476 0.1815 0.0897 0.7811 (0.587, 1.039)
rs7865494 9 TNFSF15 0.2879 0.249 0.109 1.219 (0.9566, 1.554)
rs7574865 2 STAT4 0.3398 0.3813 0.1108 0.835 (0.669, 1.042)
rs13003464 2 PUS10 0.05215 0.03475 0.1269 1.528 (0.8833, 2.644)
rs2004640 7 IRF5 0.2945 0.2577 0.1319 1.202 (0.9459, 1.528)
rs7282490 21 LOC105377139 0.449 0.4884 0.1463 0.8536 (0.6894, 1.057)
rs1250546 10 ZMIZ1 0.4213 0.4593 0.16 0.8571 (0.6912, 1.063)
rs1292053 17 TUBD1 0.4483 0.4826 0.2055 0.8712 (0.7038, 1.079)
rs10761659 10 LOC105370520 0.2162 0.2442 0.2187 0.8537 (0.6635, 1.099)
rs7608910 2 PUS10 0.05263 0.03846 0.22 1.389 (0.82, 2.353)
rs2273650 14 NFKBIA 0.2684 0.2934 0.3062 0.8835 (0.6968, 1.12)
rs11894081 2 SOX11 0.4214 0.3944 0.3205 1.118 (0.897, 1.394)
rs1250569 10 ZMIZ1 0.4287 0.4535 0.3584 0.9044 (0.7298, 1.121)
rs2823256 21 LOC101927745 0.3126 0.3359 0.3598 0.8992 (0.7162, 1.129)
rs2241880 2 ATG16L1 0.3742 0.3514 0.3813 1.104 (0.8845, 1.378)
rs3807306 7 IRF5 0.1829 0.166 0.4147 1.125 (0.848, 1.491)
rs72553867 5 IRGM 0.1596 0.1757 0.4237 0.8908 (0.671, 1.183)
rs7702331 5 LOC105379031 0.1154 0.1293 0.431 0.878 (0.635, 1.214)
rs1134986 3 DLG1 0.06302 0.05405 0.4878 1.177 (0.7425, 1.866)
rs1801133 1 MTHFR 0.2957 0.2791 0.5012 1.085 (0.8561, 1.374)
rs3894326 19 FUT3 0.1447 0.1564 0.5467 0.913 (0.6791, 1.228)
rs2107538 17 CCL5 0.3418 0.3295 0.6314 1.057 (0.8432, 1.325)
rs1799964 6 LTA 0.1752 0.1846 0.6486 0.9379 (0.7117, 1.236)
rs1800630 6 LTA 0.1586 0.1673 0.6617 0.938 (0.7043, 1.249)
rs2149085 6 RNASET2 0.3929 0.3833 0.7181 1.041 (0.8362, 1.296)
rs1047266 8 TNFRSF10B 0.277 0.2857 0.7208 0.9577 (0.7555, 1.214)
rs3731772 2 AOX1 0.3508 0.3417 0.7247 1.041 (0.8319, 1.303)
rs4462937 3 DNAH12 0.3931 0.4023 0.7281 0.962 (0.7735, 1.197)
rs1819333 6 LOC105379031 0.3909 0.3822 0.7426 1.037 (0.8333, 1.292)
rs1127354 20 ITPA 0.1711 0.1647 0.7537 1.047 (0.7862, 1.394)
rs3208181 6 HLA-DQA2 0.1245 0.1192 0.7671 1.05 (0.7585, 1.455)
rs1695 11 GSTP1 0.1765 0.1712 0.7941 1.038 (0.7837, 1.375)
rs3765534 13 ABCC4 0.05183 0.05385 0.8676 0.9605 (0.5981, 1.543)

SNPs are ordered according to P values. Chr – chromosome.

Supplementary Table 4.

Analysis results for SNPs related to pCD.

Name Chr. No. Gene or locus Major/minor allele Risk allele Case RAF Control RAF OR (95% CI) P value allele P value genotype
rs72553867 chr5 IRGM C/A A 0.194 0.125 1.685 (1.188–2.390) 0.003 0.002a
rs4958847 chr5 IRGM A/G A 0.688 0.617 1.365 (1.047–1.778) 0.021 0.025c
rs4409764 chr10 NKX2–3 G/T T 0.558 0.487 1.329 (1.033–1.709) 0.027 0.007a
rs888208 chr10 NKX2–3 A/G A 0.656 0.588 1.338 (1.032–1.735) 0.028 0.004a
rs3731772 chr2 AOX1 T/C T 0.681 0.615 1.335 (1.025–1.740) 0.032 0.032a
rs1292053 chr17 TUBD1 G/A A 0.482 0.417 1.300 (1.010–1.674) 0.041 0.035c
rs3894326 chr19 FUT3 A/T A 0.880 0.836 1.438 (1.001–2.064) 0.049 0.045c
rs10883365 chr10 NKX2–3 A/G G 0.548 0.496 1.234 (0.957–1.590) 0.105 0.033a
rs3181374 chr9 TNFSF8 A/G A 0.687 0.642 1.226 (0.939–1.600) 0.135 0.069a
rs11235667 chr11 ATG16L2-FCHSD2 A/G A 0.877 0.844 1.314 (0.914–1.887) 0.139 0.148c
rs3749172 chr2 GPR35 C/A A 0.387 0.343 1.209 (0.926–1.577) 0.162 0.055b
rs2241880 chr2 ATG16L1 A/G G 0.394 0.355 1.185 (0.915–1.534) 0.199 0.182b
rs153109 chr16 IL27 T/C T 0.613 0.573 1.181 (0.914–1.526) 0.204 0.094a
rs1800630 chr6 TNF C/A C 0.857 0.828 1.242 (0.881–1.752) 0.216 0.168b
rs11235604 chr11 ATG16L2 C/T C 0.875 0.848 1.256 (0.873–1.805) 0.219 0.225c
rs7282490 chr21 ICOSLG G/A A 0.468 0.429 1.168 (0.907–1.504) 0.228 0.205b
rs2107538 chr17 CCL5 C/T T 0.360 0.325 1.168 (0.897–1.522) 0.249 0.239c
rs10114470 chr9 TNFSF15 C/T C 0.633 0.598 1.160 (0.897–1.500) 0.259 0.128a
rs514000 chr18 PTPN2 T/C T 0.600 0.564 1.160 (0.895–1.501) 0.262 0.106a
rs11209032 chr1 IL23R-IL12RB2 A/G G 0.464 0.429 1.149 (0.893–1.478) 0.281 0.275a

SNPs are ordered according to P values.

a

p value for the dominant model;

b

p value for the regressive model;

c

p value for the additive model.

Chr – chromosome; RAF – risk allele frequency

Supplementary Table 5.

Logistic analysis results for SNPs related to pCD.

Risk allele Univariate Multivariate
OR (95% CI) P value OR (95% CI) P value
rs72553867a AC+AA vs. CC 1.874 (1.246–2.817) 0.003 1.770 (1.151–2.723) 0.009
rs4958847c A vs. G 1.366 (1.045–1.786) 0.023
rs4409764a GT+TT vs. GG 1.780 (1.149–2.758) 0.010 1.886 (1.181–3.012) 0.008
rs888208a AG+AA vs. GG 2.087 (1.205–3.616) 0.009
rs3731772a T C+TT vs. CC 1.941 (1.099–3.428) 0.022 2.131 (1.150–3.949) 0.016
rs1292053a AG+AA vs. GG 1.487 (0.992–2.230) 0.055
rs3894326c A vs. T 1.380 (0.943–2.017) 0.097
Age (year) / / 0.968 (0.951–0.984) <0.001
Male/Female / / 1.608 (1.059–2.442) 0.026
a

Dominant model;

c

additive model.


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