Abstract
Objective:
Chronic Opisthorchis viverrini (OV) infection is the cause of advanced periductal fibrosis (APF), subsequently leading to cholangiocarcinoma (CCA). Natural killer (NK) cells can kill hepatic stellate cells (HSCs), the initiating cells for fibrosis formation, by using the interaction between the natural killer group 2 member D (NKG2D) receptor and its ligand on the HSCs. This can inhibit the fibrosis formation. Major histocompatibility complex class I chain-related A (MICA) is the ligand of the NKG2D receptor and has highly polymorphic characteristics that are involved in NKG2D binding and NK cell activation. This study aimed to investigate the polymorphism of MICA in OV-induced fibrosis.
Method:
MICA typing was performed by polymerase chain reaction- sequence specific primer (PCR-SSP) and sequencing in two groups: OV infection without fibrosis (N = 99) and with fibrosis (N = 290).
Result:
Six alleles were identified and the MICA*010 allele had the highest frequency in both groups. The MICA*00201-02 allele was a protective factor for fibrosis (OR= 0.508, 95%CI= 0.34-0.76, Pc <0.05), while the MICA*019 allele was suggested to be a risk allele for fibrosis (OR=1.95, 95%CI=1.25-3.03, Pc<0.005). In addition, two motifs, glycine (G) at position 14 and glutamine (Q) at position 251, were negatively associated with fibrosis (G14: OR=0.508, 95%CI=0.34-0.76, Pc <0.05 and Q251: OR=0.586, 95%CI=0.41-0.84, Pc <0.05). Moreover, the distribution of the MICA-129 genotype also showed the protective genotype (Pc<0.05, OR=0.319, 95%CI= 0.12-0.54) for fibrosis. The MICA*00201-02 allele encoded all these motifs, and this suggested that it might lead to strong NK cell activation to kill HSCs, subsequently preventing fibrosis formation.
Conclusion:
This study described initial evidence suggesting that the polymorphism of the MICA gene might be a marker for OV-derived periductal fibrosis.
Key Words: Liver fibrosis, cholangiocarcinoma, MICA-129 methionine, NKG2D receptor, NK cell
Introduction
Opisthorchis viverrini (OV) infection causes opisthorchiasis, which is a major public health problem in various regions of Asian countries, including Thailand (Sithithaworn et al., 2003, Sripa et al., 2011). Most OV infections are asymptomatic, but mild symptoms such as dyspepsia, abdominal pain, constipation, and diarrhea can occur. Chronic infection can result in chronic inflammation of the intrahepatic bile ducts, leading to periductal fibrosis due to repetitive tissue damage (Sripa et al., 2012). The fibrosis can manifest as echogenicity in the periportal area, which can be detected by ultrasonography. More than 20% of chronic infections can progress to advanced periductal fibrosis (APF) (Mairiang et al., 2017). In this case, treatment is very important because APF can serve as a risk factor for the formation of cholangiocarcinoma (CCA) (Hitanant et al., 1987, Sripa et al., 2003, Kaewpitoon et al., 2008, Sripa et., 2012, Mairiang et al., 2021).
Liver fibrosis is a complex process involving many cells. Chronic liver damage initiates the formation of fibrosis. Hepatic stellate cells (HSCs), which are located in the space between hepatocytes and sinusoidal endothelial cells, are the primary source driving the fibrogenic process (Josan et al., 2015). Additionally, natural killer cells (NK cells) are immune cells that participate in the response to liver fibrosis development by engaging their activating receptors, especially the NKG2D receptor (Tosello-Trampont et al., 2017). Previous studies have shown that NK cells have anti-fibrogenic properties by killing HSCs that express NKG2D ligands, such as RAE1 (in mice) (Radeava et al., 2006) and MICA (in humans) (Jin et al., 2017), and NK cell-derived IFN-γ can induce HSC apoptosis (Bansal et al., 2014). Thus, the engagement of NKG2D receptor and its ligand plays an important role in liver fibrosis development.
Major Histocompatibility complex class I chain-related A (MICA) is one of the ligands of the NKG2D receptor, which heat, viral infection, inflammation, and DNA destruction can induce MICA expression (Choy et al., 2010). The MICA gene is found in the classical class I region and is composed of 6 exons. Exons 2-4 encode the extracellular (α1- α3) domain, which is involved in NKG2D binding. The MICA gene is highly polymorphic, with around 100 alleles recognized by the IMGT/HLA database to date. The polymorphic positions, especially in exons 2-4, mainly involve single amino acid substitutions that affect NKG2D binding affinity and NK cell activation (Li et al., 2000, Steinle et al., 2001). Therefore, this study aims to identify the association of MICA gene polymorphism and amino acid substitutions that affect NKG2D binding, subsequently leading to APF in opisthorchiasis patients.
Materials and Methods
Patient samples
The DNA samples used in this study were the leftover specimen that were approved by the Ethics Committee of Khon Kaen University, Khon Kaen, Thailand (HE641133) under the umbellar of ethic number HE480528. In brief, subjects were recruited from seven villages in Khon Kaen, Thailand, where OV transmission was high along the Chi River Basin. Opisthorchiasis patients were identified by microscopic fecal examination for OV infection which detailed description in previous report (Mairiang et a 2012, Saichua et al 2012). Then, the abdominal ultrasound examination previously described by Mairiang et al. was used to classify APF (Mairiang et al. 2012, 2021). Patients with grade 0 and grade 1 fibrosis (no echoes and echoes in one segment of liver) were classified into the APF negative group, and those with grade 2 and grade 3 fibrosis (echoes in 2, 3 and more segments of liver) were classified into the APF positive group. The patients were then divided into two groups: OV positive (OV+) and APF negative, and OV+ and APF positive. DNA was extracted from white blood cells from 99 OV+ and APF (-) samples and 290 OV+ and APF (+) samples. Finally, all patients were referred for treatment at local state hospitals.
PCR-SSP tying and sequencing for MICA polymorphisms
To identify MICA polymorphisms, a modified PCR-SSP method from a previous publication (Jumnainsong et al., 2007) was performed. In brief, 12 primer mixtures were used to identify MICA alleles with polymorphism positions in exon 2-4. These primer mixtures were specific to six MICA alleles, which are the most commonly occurring alleles in the Northeast Thai population and cover 86.8% of the population (Romphruk et al., 2001). The primer sequences for the 12 primer mixtures and primer checkerboard were shown in Table 1 and 2, respectively. Internal control primers, 439 base pairs (bp) human growth hormone (HGH), were also used to check PCR reactions. The HGH forward primer (5’-CAgTgCCTTCCCAACCATTCCCTTA-3’) and HGH reverse primer (5’-ATCCACTCACGgATTTCTg TTgTgTTTg-3’) were used. However, this primer set had some limitations as it cannot identify polymorphisms in the transmembrane region and some rare groups of alleles.
Table 1.
Twelve Primer Mixes and Primer Sequences for MICA Genotyping
| Mix No. | Name and primer sequences (5’- 3’) | Exon | Positon | Target allele |
|---|---|---|---|---|
| 1 | 2; ACCTCACggTgCTgTCCg | 2 | 22-40 | 00201-02, 011, 015,017, 030, 034, 035, 041 |
| 14.2: CCCAgCATTTCTACTACgATA | 3 | 319-340 | ||
| 2’: CTCAggACTACgCCggATTT | 3 | 517-537 | ||
| 2 | 8: ACggCgATATCTAgAATCCg | 3 | 503-523 | 00801-03, 035, 037, 039, 042 |
| 8’: TCCTgACgCCTggTCAgTA | 4 | 638-657 | ||
| 3 | 10: CAgAgCCCCACAgTCTTCC | 2 | 1-17 | 10 |
| 13’: TCTggAggACTggggCAAC | 3 | 385-403 | ||
| 4 | 20: TACggCgATATCTAgAATCCA | 3 | 502-523 | 010, 016, 019, 022, 033 |
| 8’: TCCTgACgCCTggTCAgTA | 4 | 638-657 | ||
| 5 | 4.2: TCAgCCCTTCCTgCgCTA 2’: CTCAggACTACgCCggATTT |
2 3 |
89-107 517-537 |
001, 00201-02, 00701-02, 011, 01201-02, 015, 017, 01801-02, 021, 029, 030, 034, 035, 037-039, 041, 043, 045 |
| 6 | 16: CATgggACAgAgAgACCAgA | 2 | 174-192 | 001, 01201-02, 01801-02, 021 |
| 2’: CTCAggACTACgCCggATTT | 3 | 517-537 | ||
| 7 | 4: gTCAgCCCTTCCTgCgCTA | 2 | 90-107 | 004-006, 00801-03, 00901-02, 010, 016, 019, 024, 025, 028, 031, 033, 042, 044 |
| 12’: CTgCATGCATAgCgTgATAgT | 3 | 467-488 | ||
| 8 | 4: gTCAgCCCTTCCTgCgCTA | 2 | 90-107 | 004, 006, 00901-02, 010, 016, 019, 031, 033, 044 |
| 25’: gTTCTCCTCAggACTACgCT | 3 | 523-543 | ||
| 9 | 573FT: ATggTgAATggT5CACCCgCAgT | 4 | 552-573 | 45 |
| 752RC: gAACCTCTgCTCCTCTCCTTC | 4 | 752-773 | ||
| 10 | 4.2: TCAgCCCTTCCTgCgCTA 373R: TggggCAttgTCCATTCCTC |
2 3 |
89-107 373-393 |
00201, 00701-02, 011, 01201-02, 013-015, 017, 01801-02, 021, 022, 029, 030, 034-039, 041, 043, 045 |
| 11 | 272F: CAggCTTgCATTCCCTCCA | 3 | 253-272 | 001, 00201-02, 005, 00701-02, 011, 01201-02, 013-015, 01801-02, 021, 022, 029, 030, 034-039, 041, 043, 045 |
| 19’: AgCCCTgCATgTCACggTA | 4 | 594-613 | ||
| 12 | 86FG: CAgAgCCCCACAgTCTTCg | 2 | 1-17 | All except 010 |
| 13’:TCTggAggACTggggCAAC | 3 | 385-403 |
Table 2.
A Primer set of MICA Typing Consisting of 12 Primer Mixes
| MICA allele | Primer mixture number | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | |
| *00201-02 | ||||||||||||
| *00801-03 | ||||||||||||
| *010 | ||||||||||||
| *019 | ||||||||||||
| *01801-02 | ||||||||||||
| *045 | ||||||||||||
Shaded boxes are positive reactions; All of these alleles were the common alleles in Northeast Thai population and covered around 86.8% of the population.
One hundred ng/µL of genomic DNA template was required for PCR. The PCR mixture was consisted of 1 mM dNTP, 25 mM MgCl2, 10X PCR buffer, 5 U Taq DNA polymerase enzyme (all from Vivantis, USA), 0.25 µM of each specific primer, and 0.1 µM of control primers. For PCR, the Veriti 96-well Thermal cycler (Applied Biosystem, USA) was used. The following series of thermal cycling conditions were programmed: initial denaturation at 96°C for 2 minutes; 5 cycles of denaturation at 96°Celsius (°C) for 30 second (s), annealing at 68°C for 60 s, and extension at 72°C for 40 s; 21 cycles of denaturation at 96°C for 30 s, annealing at 65°C for 60 s, and extention at 72°C for 40 s; 4 cycles of denaturation at 96°C for 30 s, annealing at 55°C for 75 s, and extension at 72°C for 120 s, and final extension at 72°C for 10 minutes. Gel electrophoresis was used to confirm the 13 µl amplification product. A 1.5% agarose gel (Vivantis, Malaysia) was stained with ethidium bromide and visualized using an ultraviolet (UV) transilluminator (Shimadzu, Japan).
If the samples could not be fully identified by the 12-primer mixture set, the sequencing method was applied to solve the issue. MICA exon 2-3 was amplified with the primers MICA 2-3F (5’ TGAAATCCTCTTCTTGTCCCTTTGC 3’) and MICA 2-3R (5’ AGGGTCCTCTACTTGCCCTGATTAC 3’) before sequencing (Toledo-Stuardo et al., 2021). There were 21 samples which showed only one allele by PCR-SSP. These samples were amplified for the sequencing, and the result of MICA typing by PCR-SSP and sequencing was the same (table S1).
Amino acid substitution selection
The amino acid sequence in α1- α3 domain of common 6 MICA alleles in the population was aligned to identify the amino acid position that difference among 6 alleles. This demonstrated 13 non-synonymous amino acid substitutions in these domains (table S2). Since α1- α3 domain of MICA are the extracellular domain that bind to NKG2D receptor, these amino acid substitutions can affect NKG2D binding and NK cell activation.
Statistical analysis
The MICA allele frequencies were calculated by direct counting. Statistical analysis was performed using IBM Statistics SPSS software (version 26). To determine the significance of the association between groups, they were compared using the Pearson chi-square method, and p-values and corrected p-values were calculated. To determine the disease risk in carriers of specific alleles, odds ratios (OR) and 95% confidence intervals (95%CI) were calculated using Woolf’s method. Bonferroni’s multiple correction (corrected p-value, Pc) was obtained by multiplying the p-value with the number of tests performed, and a Pc value <0.05 was considered statistically significant.
Results
Clinicopathological features of subjects
According to the abdominal ultrasound examination in opisthorchiasis patients, they were classified into fibrosis and non-fibrosis groups. In the fibrosis group, males were more prevalent than females (62.8% and 37.2%, respectively). The occurrence of non-fibrosis by sex was nearly the same. The average age was 45.5 years in the non-fibrosis group and 48.1 years in the fibrosis group. In addition, other factors involving liver fibrosis; smoking and alcohol drinking were not significant difference (Table 3).
Table 3.
Clinicopathological Features of the Subjects
| Characteristics | No-fibrosis Patients | Fibrosis Patients | Total | P-value |
|---|---|---|---|---|
| Number(N) | 99 | 290 | 389 | |
| Gender (%) | ns | |||
| Male | 49 (49.5) | 182 (62.8) | 231 | |
| Female | 50 (50.5) | 108 (37.2) | 158 | |
| Age (years) | ns | |||
| Range | 20-59 | 21-60 | ||
| Average | 45.5 | 48.1 | ||
| Intervals | ||||
| ≤30 | 3 (3.0) | 26 (9.0) | 29 | |
| 31-40 | 10 (10.0) | 64 (22.1) | 74 | |
| 41-50 | 47 (47.5) | 92 (31.7) | 139 | |
| ≥51 | 39 (39.5) | 108 (37.2) | 147 | |
| Smoking (%) | ns | |||
| Non-smoking | 57 (57.6) | 102 (35.2) | 169 | |
| Smoking | 31 (31.3) | 147 (50.7) | 178 | |
| No information | 11 (11.1) | 41 (14.1) | 52 | |
| Alcohol drinking (%) | ns | |||
| Never/ Occasional | 72 (71.7) | 155 (53.5) | 227 | |
| Regular | 16 (16.2) | 94 (32.4) | 110 | |
| No information | 11 (11.1) | 41 (14.1) | 52 | |
ns, not significant
Association of MICA phenotypes in non-fibrosis and fibrosis groups of opisthorchiasis
In both groups, six alleles were identified, and MICA*010 was the most common allele. The association between MICA phenotypes in the non-fibrosis and fibrosis groups was calculated using the Pearson chi-square test. These p-values were further corrected by multiplying them by the number of alleles detected and tested in this population. According to Table 4, the distribution frequency of the MICA*00201-02 allele was significantly lower in fibrosis patients than in non-fibrosis patients. This suggested that MICA*00201-02 was a protective factor against fibrosis (24.8% vs. 14.3%, OR=0.51, 95%CI=0.34-0.76, Pc < 0.05). Another allele, the MICA*019 allele, was suggested as a risk allele because it was significantly higher in OV-induced fibrosis than in non-fibrosis OV patients (14.1% vs. 24.3%, OR=1.95, 95%CI=1.25-3.03, Pc<0.005).
Table 4.
MICA Allele Frequencies in Non Fibrosis (99) and Fibrosis (290) of Opisthorchiasis Groups
| MICA alleles | OV (+), Fib (-) | OV (+), Fib (+) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Number | % AF | Number | % AF | Chi square | P -value | Pc | Odds ratio | 95%CI | |
| 2n=198 | 2n=580 | ||||||||
| *00201-02 | 49 | 24.8 | 83 | 14.3 | 11.414 | 0.0007 | 0.004 | 0.508 | 0.34-0.76 |
| *00801-03 | 36 | 18.2 | 109 | 18.8 | 1.899 | 0.168 | NS | 1.041 | 0.68-1.58 |
| *010 | 55 | 27.8 | 153 | 26.4 | 0.147 | 0.701 | NS | 0.932 | 0.65-1.34 |
| *01801-02 | 17 | 8.59 | 48 | 8.28 | 0.019 | 0.892 | NS | 0.961 | 0.54-1.71 |
| *019 | 28 | 14.1 | 141 | 24.3 | 8.977 | 0.0027 | 0.016 | 1.95 | 1.25-3.03 |
| *045 | 13 | 6.57 | 46 | 7.93 | 0.393 | 0.531 | NS | 1.226 | 0.65-2.32 |
NS, not significant; Significant difference, Pc<0.05
Association of MICA genotypes in non-fibrosis and fibrosis groups of opisthorchiasis
As shown in Table 5, the distribution frequency of MICA*00201-02 homozygotes were significantly higher in the non-fibrosis group than in the fibrosis group, which may be a protective genotype against fibrosis. Similarly, MICA*010 homozygous alleles also had a negative association.
Table 5.
MICA Genotypes Frequencies in Non-Fibrosis (99) and Fibrosis (290) of Opisthorchiasis Groups
| MICA alleles | OV (+), Fib (-) | OV (+), Fib (+) | Chi square | P value | Pc value | Odds ratio | 95%CI | ||
|---|---|---|---|---|---|---|---|---|---|
| Number N=99 |
% AF | Number n=290 |
% AF | ||||||
| *00201-02/*00201-02 | 5 | 5.05 | 1 | 0.34 | 10.762 | 0.001 | 0.021 | 0.065 | 0.008-0.56 |
| *00201-02/*00801-03 | 7 | 7.07 | 13 | 4.48 | 1.014 | 0.314 | NS | 0.617 | 0.24-1.59 |
| *00201-02/*010 | 15 | 15.15 | 33 | 11.38 | 0.971 | 0.324 | NS | 0.719 | 0.37-1.39 |
| *00201-02/*019 | 9 | 9.09 | 25 | 8.62 | 0.02 | 0.886 | NS | 0.943 | 0.42-2.10 |
| *00201-02/*01801-02 | 5 | 5.05 | 4 | 1.38 | 4.324 | 0.038 | NS | 0.266 | 0.07-1.00 |
| *00201-02/*045 | 3 | 3.03 | 6 | 2.07 | 0.302 | 0.583 | NS | 0.676 | 0.17-2.76 |
| *00801-03/*00801-03 | 1 | 1.01 | 1 | 0.34 | 0.639 | 0.424 | NS | 0.339 | 0.02-5.47 |
| *00801-03/*010 | 10 | 10.1 | 44 | 14.83 | 2.097 | 0.148 | NS | 1.741 | 0.82-3.71 |
| *00801-03/*019 | 5 | 5.05 | 37 | 12.41 | 7.204 | 0.0073 | NS | 4.535 | 1.36-15.07 |
| *00801-03/*01801-02 | 4 | 4.04 | 5 | 1.72 | 0.625 | 0.429 | NS | 0.561 | 0.13-2.39 |
| *00801-03/*045 | 3 | 2.02 | 6 | 2.07 | 0.001 | 0.976 | NS | 1.025 | 0.20-5.16 |
| *010/*010 | 9 | 9.09 | 4 | 1.38 | 13.588 | 0.0002 | 0.004 | 0.14 | 0.04-0.47 |
| *010/*019 | 4 | 4.04 | 37 | 12.76 | 1.579 | 0.209 | NS | 1.664 | 0.75-3.71 |
| *010/*01801-02 | 4 | 4.04 | 16 | 5.52 | 0.983 | 0.322 | NS | 1.869 | 0.53-6.55 |
| *010/*045 | 3 | 3.03 | 16 | 5.52 | 2.045 | 0.153 | NS | 2.832 | 0.64-12.54 |
| *019/*019 | 2 | 2.02 | 7 | 2.76 | 0.161 | 0.689 | NS | 1.376 | 0.29-6.59 |
| *019/*01801-02 | 3 | 3.03 | 16 | 5.17 | 1.755 | 0.185 | NS | 2.645 | 0.59-11.78 |
| *019/*045 | 3 | 3.03 | 12 | 4.14 | 0.954 | 0.329 | NS | 2.094 | 0.46-9.52 |
| *01801-02/*01801-02 | 1 | 1.01 | 1 | 0.34 | 0.639 | 0.424 | NS | 0.339 | 0.02-5.47 |
| *01801-02/*045 | 2 | 2.02 | 5 | 1.72 | 0.2 | 0.655 | NS | 0.678 | 0.12-3.76 |
| *045/*045 | 1 | 1.01 | 1 | 0.34 | 0.639 | 0.424 | NS | 0.339 | 0.02-5.47 |
NS, not significant; Significant difference, Pc<0.05
Association of MICA amino acids substitutions in non-fibrosis and fibrosis groups of opisthorchiasis patients
Since amino acid substitutions are involved in NKG2D binding affinity and lead to the activation of immune cells, we analysed 13 positions of non-synonymous amino acid substitutions in exons 2-4 of 6 MICA alleles in this population (Table S2). Two positions, Glycine-14 and glutamine-251, were negatively associated with fibrosis (Pc = 0.004 and 0.044, respectively, Table 6). Additionally, a previous study showed that amino acid position 129, which is either methionine or valine, was an important position because it affected NKG2D affinity [14]. Although the association of the allele frequency of position 129 was not significant (Table 6), the distribution of MICA-129 genotypes indicated that the MICA-129 Met/Met homozygous genotype had a negative association and may be assumed as a protective genotype (Pc < 0.05, OR = 0.319, 95%CI = 0.16-0.65) for fibrosis (Table 7).
Table 6.
The Allele Frequency of MICA Aamino-Acids Substitutions in Non-Fibrosis (99) and Fibrosis (290) of Opisthorchiasis Groups
| Positions | OV (+), Fib (-) | OV (+), Fib (+) | Chi square | P- value | Pc | Odds ratio | 95%CI | ||
|---|---|---|---|---|---|---|---|---|---|
| Number 2n=198 |
% AF | Number 2n=580 |
% AF | ||||||
| Proline 6 | 55 | 27.78 | 153 | 26.38 | 0.147 | 0.701 | NS | 0.932 | 0.65-1.34 |
| Arginine 6 | 143 | 72.22 | 427 | 73.62 | 0.147 | 0.701 | NS | 1.073 | 0.75-1.54 |
| Glycine 14 | 49 | 24.75 | 83 | 14.31 | 11.414 | 0.0007 | 0.004 | 0.508 | 0.34-0.76 |
| Tryptophan 14 | 149 | 75.25 | 497 | 85.69 | 11.414 | 0.0007 | 0.004 | 1.969 | 1.32-2.93 |
| Threonine 24 | 17 | 8.59 | 48 | 8.28 | 0.019 | 0.892 | NS | 0.961 | 0.54-1.71 |
| Alanine 24 | 181 | 91.41 | 532 | 91.72 | 0.019 | 0.892 | NS | 1.041 | 0.58-1.86 |
| Cysteine 36 | 79 | 39.9 | 177 | 30.52 | 5.885 | 0.015 | NS | 0.662 | 0.47-0.92 |
| Tyrosine 36 | 119 | 60.1 | 403 | 69.48 | 5.885 | 0.015 | NS | 1.512 | 1.08-2.11 |
| Methionine 129 | 79 | 39.9 | 177 | 30.52 | 5.885 | 0.015 | NS | 0.662 | 0.47-0.92 |
| Valine 129 | 119 | 60.1 | 403 | 69.48 | 5.885 | 0.015 | NS | 1.512 | 1.08-2.11 |
| Lysine 173 | 79 | 39.9 | 177 | 30.52 | 5.885 | 0.015 | NS | 0.662 | 0.47-0.92 |
| Glutamic acid 173 | 119 | 60.1 | 403 | 69.48 | 5.885 | 0.015 | NS | 1.512 | 1.08-2.11 |
| Glycine 175 | 115 | 58.08 | 286 | 49.31 | 4.546 | 0.033 | NS | 0.702 | 0.51-0.97 |
| Serine 175 | 83 | 41.92 | 294 | 50.69 | 4.546 | 0.033 | NS | 1.424 | 1.02-1.97 |
| Glycine 206 | 79 | 39.9 | 177 | 30.52 | 5.885 | 0.015 | NS | 0.662 | 0.47-0.92 |
| Serine 206 | 119 | 60.1 | 403 | 69.48 | 5.885 | 0.015 | NS | 1.512 | 1.08-2.11 |
| Tryptophan 210 | 79 | 39.9 | 177 | 30.52 | 5.885 | 0.015 | NS | 0.662 | 0.47-0.92 |
| Arginine 210 | 119 | 60.1 | 403 | 69.48 | 5.885 | 0.015 | NS | 1.512 | 1.08-2.11 |
| Threonine 213 | 79 | 39.9 | 177 | 30.52 | 5.885 | 0.015 | NS | 0.662 | 0.47-0.92 |
| Isoleucine 213 | 119 | 60.1 | 403 | 69.48 | 5.885 | 0.015 | NS | 1.512 | 1.08-2.11 |
| Serine 215 | 79 | 39.9 | 177 | 30.52 | 5.885 | 0.015 | NS | 0.662 | 0.47-0.92 |
| Threonine 215 | 119 | 60.1 | 403 | 69.48 | 5.885 | 0.015 | NS | 1.512 | 1.08-2.11 |
| Arginine 251 | 119 | 60.1 | 403 | 69.48 | 8.578 | 0.0034 | 0.044 | 1.706 | 1.19-2.44 |
| Glutamine 251 | 66 | 33.33 | 131 | 22.59 | 9.016 | 0.0034 | 0.044 | 0.586 | 0.41-0.84 |
| Glutamic acid 251 | 13 | 6.57 | 46 | 7.93 | 2.799 | 0.094 | NS | 1.783 | 0.90-3.53 |
NS, not significant; Significant difference, Pc<0.05
Table 7.
MICA Position 129 Genotype Frequency in Non-Fibrosis (99) and Fibrosis (290) of Opisthorchiasis Groups
| OV (+), Fib (-) | OV (+), Fib (+) | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Positions | Number | % F | Number | % F | Chi square | P -value | Pc | Odds ratio | 95%CI |
| n=99 | n=290 | ||||||||
| MICA-129 Met/Met | 17 | 17.2 | 18 | 6.2 | 10.837 | 0.0009 | 0.0027 | 0.319 | 0.16-0.65 |
| MICA-129 Met/Val | 45 | 45.5 | 141 | 48.6 | 0.297 | 0.586 | NS | 1.136 | 0.72-1.79 |
| MICA-129 Val/Val | 37 | 37.4 | 131 | 45.2 | 1.829 | 0.176 | NS | 1.381 | 0.86-2.20 |
NS, not significant; Significant difference, Pc<0.05
Discussion
Chronic OV infection can lead to advanced periductal fibrosis and, ultimately, cholangiocarcinoma (Sripa et al., 2012). Numerous immune cells are involved in the fibrosis mechanism, with NK cells playing a critical role through NKG2D receptor activation, with MICA as an important ligand for this receptor. MICA gene is highly polymorphic, particularly in the extracellular domain region, resulting in amino acid substitutions that affect the affinity of NKG2D binding (Li et al., 2000, Steinle et al., 2001). This is the first report on the association study of extracellular domain polymorphism and periductal fibrosis derived from OV infection. PCR-SSP was the technique in this study and it has some limitations. After PCR-SSP with primer mix number 1 to 11, there were 54 samples that positive with primer mix number 3, 4, 7 and 8. The interpretation of these samples was MICA*010 but cannot exclude MICA*019. To solve this problem, primer mix number 12 was established to identify homozygous MICA*010 and heterozygous MICA*010 and MICA*019. This primer could be positive with all allele except MICA*010. There were 13 samples shown negative with this primer. The interpretation of 13 samples was the homozygous MICA*010. In contrast, 41 samples were positive with this primer. They were the heterozygous MICA*010 and 019. Moreover, another limitation of PCR-SSP was unexpected allele. After PCR-SSP, only one MICA allele was identified in 21 samples. Thus, these samples were confirmed by the sequencing. The sequencing result demonstrated the homozygous allele that was the same result with PCR-SSP. Thus, PCR-SSP was suitable for the screening technique to identify MICA alleles.
There were many factors that may affect to fibrosis, such as smoking and alcohol assumption, these might be the confounding factors in this study. However, when these factors were analyzed, these factors were not significant difference between non fibrosis and fibrosis patient. In addition, there were other factors involving the development of fibrosis that were not analyzed. This was the limitation of this study.
The most common six MICA alleles in the Thai population were identified and analyzed in OV-infected patients with and without fibrosis. The analysis indicated that MICA*00201-02 and MICA*019 alleles showed correlation between the fibrosis group and non-fibrosis group of infected patients. The OV-infected fibrosis group showed that the MICA*019 allele had a significantly higher frequency than that in the no-fibrosis group, making this allele the susceptibility effect for fibrosis. In contrast, the MICA*00201-02 allele was the protective allele for fibrosis, especially in the homozygous MICA*00201-02. These results differed from the association between MICA allele and Schistosoma-derived liver fibrosis (Gong et al., 2012) where MICA alleles were not significantly different between healthy and Schistosoma-derived liver fibrosis. Our results were also different from those of fibrosis derived from fatty liver (Karrar et al., 2020). Furthermore, our results differed from a previous study which showed that MICA*002 was the risk allele for pulmonary fibrosis (Aquino-Galvez et al., 2009), which may be due to distinct ethnic groups and fibrosis mechanisms.
MICA gene polymorphisms lead to amino acid substitutions that are involved in the activation of NK cells via NKG2D binding. The amino acid substitutions among six MICA alleles were analyzed, and the analysis indicated that tryptophan (W) to glycine (G) at codon 14 (W14G) and glutamine (Q) at position 251 (Q251R) were negatively associated with fibrosis. These substitutions were found in extracellular domains 1 and 3 of MICA*00201-02, which might enhance the affinity of NKG2D binding, leading to strong NK cell activation to kill HSCs and subsequently reduce fibrosis. Additionally, a previous study demonstrated that methionine at amino acid position 129 in extracellular domain 2 was involved in a strong affinity for NKG2D binding (Li et al., 2000). We found that the MICA-129 Met/Met genotype was significantly less prevalent in fibrosis patients compared to non-fibrosis patients, implying that the MICA-129 Met/Met genotype might give highly affinity of NKG2D binding and strong NK cell activation to destroy HSCs, thus playing an important role in reducing fibrosis. Since MICA*00201-02 encodes methionine at amino acid position 129, this was another factor supporting the negative association of this allele. Interestingly, a previous study showed that valine at amino acid position 129 showed the opposite result when compared with methionine. It was involved in weak affinity to NKG2D binding (Li et al., 2000). MICA*019 codes for valine at position 129, so MICA*019 may be the weakly affinity allele for NKG2D receptor, leading to less NK cell activation to kill HSCs. This may be a factor supporting the positive association of MICA*019 and promoting fibrosis. IFN-γ-producing NK cells have been demonstrated to inhibit fibrosis by inducing HSC apoptosis (Bansal et al., 2014). MICA*00201-02, which carries 129-methionine, might strongly activate NK cells to produce IFN-γ and enhance HSC apoptosis, subsequently reducing liver fibrosis. The homozygous MICA*010 demonstrated a protective effect on fibrosis which similar with MICA*00201-02. This allele carried MICA*129 Val that was opposite with MICA*00201-02. This might be suggested that another MICA amino acid positions might also affect the NKG2D binding and NK cell activation, especially at amino acid position 6 that MICA*010 was difference from other alleles. However, the exact interaction between NKG2D receptor and MICA in OV-derived liver fibrosis still needs further investigation. MICA allele might be a marker for fibrosis formation, which is an important marker for cholangiocarcinoma.
In conclusions, the MICA*00201-02 allele had a protective effect, while the MICA*019 allele had a susceptibility effect for OV-induced fibrosis. Three amino acid substitutions were found to be negatively associated with fibrosis. According to a previous publication, methionine-129 had a stronger affinity to NKG2D than valine-129. MICA*00201-02 encoded all of the substitutions, especially the 129-methionine substitution. This might be the factor that supported the negative association of this allele, as it could highly activate NK cells to kill HSCs expressing MICA. Therefore, the MICA allele and amino acid substitutions could be markers for OV-induced fibrosis, which is the initiation step of cholangiocarcinoma.
Author Contribution Statement
Initiate the project: Amonrat Jumnainsong, Chanvit Leelayuwat; Collected the data and contributed data analysis: Tay Zar Myo Oo, Prasert Saichua, Paiboon Sithithaworn, Eimorn Mairiang, Banchob Sripa, Amonrat Jumnainsong; Setting the method: Tay Zar Myo Oo, Wisitsak Phoksawat; Wrote the manuscript: Tay Zar Myo Oo, Prasert Saichua, Chanvit Leelayuwat, Amonrat Jumnainsong.
Acknowledgements
The authors are grateful to Mr. Sarawut Kareerat and Dr. Kanda Sornkayasit for their assistance in PCR-SSP amplification. We are also thankful to the fieldwork team of Prof. Banchob Sripa for their support in providing samples for both groups.
Funding statement
This research has been funded by the Centre for Research and Development of Medical Diagnostic Laboratories (CMDL), Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen, Thailand and Cholangiocarcinoma Research Institute, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Ethical Declaration
This study was approved by the Ethics Committee of Khon Kaen University, Khon Kaen, Thailand (HE641133) under the umbellar of ethic number HE480528.
Conflict of Interest
The authors have declared that no conflict of interests.
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