Investigation of the Association of miRNA-499,miRNA-146a,miRNA-196a2 Loci with Hepatocellular Carcinoma Risk: A Case

Abstract

microRNAs’ (miRNAs) loci may influence hepatocellular carcinoma (HCC) development. Many recent studies have assessed the relationship between miRNA-499, miRNA-146a, and miRNA-196a2 loci and HCC risk. However, the observed results are conflicting. A total of 584 HCC patients and 923 age- and sex-matched controls were recruited. The correlation of miRNA-499 rs3746444, miRNA-146a rs2910164, and miRNA-196a2 rs11614913 with HCC development was assessed. In the <53-year-old subgroup, a correlation of the rs2910164 locus with HCC risk was found (GG/CG vs. CC: adjusted p = 0.011, GG vs. CC: adjusted p = 0.021 and CG vs. CC: adjusted p = 0.027). The association between miRNA-146a rs2910164 and the risk of HCC was also found in the never smoking (GG/CG vs. CC: adjusted p = 0.011 and CG vs. CC: adjusted p = 0.018). Using false-positive report probability method and power value, we identified that miRNA-146a rs2910164 conferred a risk to HCC in the <53-year-old and never-smoking subgroups. In conclusion, this study indicates rs2910164 may be a risk factor for HCC, especially in the <53-year-old and never-smoking subgroups.

Introduction

In China, an estimated 466,100 new liver carcinoma (LC) cases and 422,100 LC-related deaths occurred in 2015, which might rank as the fourth most frequent cancer and the third leading cause of their related death (Chen et al., 2016). Hepatocellular carcinoma (HCC) is regarded as one of the major subtypes of LC. The etiology of HCC is thought to be associated with a prevalence of hepatitis B virus (HBV) in China. However, HCC is a complex disease and a number of hereditary and environmental factors may contribute to the development of HCC.

microRNAs (miRNAs) contain about 22 nucleotides. They are common noncoding RNA molecules. In eukaryotes, miRNAs are of vital importance for regulation of gene expression (Bartel, 2004). Many investigations have suggested that variations in normal functions of cells are associated with miRNAs. Deficiency of miRNAs can result in a number of diseases. It is believed that miRNAs are important for many vital roles (e.g., apoptosis, development, proliferation, differentiation, and carcinogenesis) (Drakaki and Iliopoulos, 2009; Palma et al., 2014; Wang et al., 2016b; Zhao et al., 2017; Kim et al., 2018; Ou et al., 2018). In addition, accumulating evidence highlights that miRNAs may contribute to infection, immune, and inflammatory response (Jovanovic and Hengartner, 2006). As well, the association of miRNAs with the development of cancer was also studied (He et al., 2018; Zhou et al., 2019). It is reported that HCC is associated with infection of HBV or hepatitis C virus (Ghouri et al., 2017; Stewart et al., 2019). Thus, miRNAs may be implicated in the etiology of HCC (Zhang et al., 2012; Fiorino et al., 2016; Hayes and Chayama, 2016; Sadri Nahand et al., 2019).

There are current studies focusing on the correlation of the rs3746444 locus in miRNA-499 with HCC development (Akkiz et al., 2011a; Xiang et al., 2012). Some reports have indicated that the rs3746444 A>G single nucleotide polymorphism (SNP) in miRNA-499 increased the risk of HCC (Xiang et al., 2012; Chu et al., 2014; Ma et al., 2014; Qi et al., 2014). Several publications showed that rs3746444 in miRNA-499 might decrease the risk of HCC (Zou and Zhao, 2013). However, more case–control studies suggested that rs3746444 variants were not associated with HCC risk (Akkiz et al., 2011a; Shan et al., 2013; Yan et al., 2015; Farokhizadeh et al., 2019). Recently, some meta-analyses explored the relationship between this locus and HCC risk and the observations were also controversial. Some meta-analyses suggested that the rs3746444 A>G polymorphism in miRNA-499 contributed to HCC development (Liu et al., 2014b; Ye et al., 2016; Yu et al., 2016, 2017; Qiu et al., 2018; Yang et al., 2018). However, other meta-analyses failed to find an association of the rs3746444 SNP in miRNA-499 with HCC risk (Hu et al., 2013; Wang et al., 2013, 2016a; Xu et al., 2013a, b; Liu et al., 2014a; Zhu et al., 2016b; Zheng et al., 2017). Thus, the association between this SNP and the development of HCC was conflicting.

Khanizadeh et al. (2019) and Al-Qahtani et al. (2017) reported that rs2910164 C>G SNP in miRNA-146a conferred an increased susceptibility to chronic infection by HBV. Thus, this polymorphism may facilitate the development of HCC. Another study also showed that this SNP might influence the development of HCC (Xu et al., 2008). However, other studies suggested that rs2910164 SNP might not play a vital role in HCC development (Akkiz et al., 2011b; Zhang et al., 2011, 2013; Shan et al., 2013; Chu et al., 2014; Qi et al., 2014; Li et al., 2015; Riazalhosseini et al., 2016; Farokhizadeh et al., 2019). Several meta-analyses also observed conflicting findings (He et al., 2012; Wang et al., 2012; Hu et al., 2013; Xu et al., 2013a; Yin et al., 2013; Zhang et al., 2017; Hao et al., 2018). The inconsistent results may be due to multiple gene, social, and environmental factors.

MiRNA-196a2 rs11614913 T>C, another common miRNA SNP, was also explored for a relationship to the risk of HCC. Rs11614913 is located in the 3′-UTR of the miRNA-196a2 precursor. This SNP alters the transcription of mature miRNA-196a (Hoffman et al., 2009) and rs11614913 might be involved in HBV infection and its related liver complications (Al-Qahtani et al., 2017). In a meta-analysis, the miRNA-196a2 rs11614913 C allele was found to be associated with an increased risk of HCC (Liu et al., 2018). However, most of the previous studies included had small sample sizes and the observation may not be accurate.

In this study, we included 1507 participants and assessed the relationship of miRNA-499 rs3746444, miRNA-146a rs2910164, and miRNA-196a2 rs11614913 with HCC risk.

Materials and Methods

Subjects

In total, 525 male and 59 female patients with HCC were recruited from the Fujian Medical University Union Hospital (Fuzhou City, China) and No. 900 Hospital of Chinese People's Liberation Army (Fuzhou City, China) between 2002 and 2016. In this study, each patient had surgery and was pathologically confirmed with HCC. The control group constituted 923 subjects (835 male and 88 female) without any cancer history. Each participant signed a written informed consent. By using a questionnaire, we collected the following information: drinking, age, sex, and tobacco consumption. By using biochemical examination, we evaluated the status of chronic HBV infection in each subject. This investigation was approved by the Ethics Committee of Changzhou No. 3 People's Hospital (Approval No. 2018-04).

Polymorphisms selection

To determine the role of miRNA polymorphisms in the development of HCC, we selected miRNA-499 rs3746444, miRNA-146a rs2910164, and miRNA-196a2 rs11614913 SNPs according to some published literatures. In these studies, rs3746444, rs2910164, and rs11614913 were found to be correlated with cancer (Chen et al., 2018; Ahmad et al., 2019; Tang et al., 2019; Yan et al., 2019).

Genotying

We collected 1507 blood samples with an EDTA anticoagulant and they were stored at −80°C. Extracting DNA was carefully carried out from leucocytes. The quality and concentration was measured by NanoDrop ND-1000 microspectrophotometer (Thermo Fisher Scientific, Inc., Waltham, MA). The concentration of genomic DNA was 20–50 ng/μL. The 260/280 nm ratio was 1.8–2.0. Using an ABI 3730XL sequencer, the SNPscan™ method was used to genotype the miRNA-499 rs3746444, miRNA-146a rs2910164, and miRNA-196a2 rs11614913 loci (Chen et al., 2018). A second technician selected 4% DNA samples randomly, and the results indicated that genotypes of the first assay were repeatable.

Statistical analyses

The mean ± standard deviation was used to express the distribution of age. The difference of age was measured with Student's t-test. The categorical variable (e.g., the number of genotypes, alcohol consumption, age, gender, and smoking) between the two groups were compared with a χ ²-test. Odds ratios (ORs) and their confidence intervals (95% CIs) were used to determine the relationship between miRNA-499 rs3746444, miRNA-146a rs2910164, and miRNA-196a2 rs11614913 and HCC risk. An online Hardy–Weinberg equilibrium (HWE) calculation program (http://ihg.gsf.de/cgi-bin/hw/hwa1.pl) was used to determine whether the distribution of miRNA-499 rs3746444, miRNA-146a rs2910164, and miRNA-196a2 rs11614913 genotypes in controls could represent the Chinese Han population (Tang et al., 2016). SAS 9.4 software (SAS Institute, Cary, NC) was used to carry out the statistical analyses. The significance was defined as p < 0.05 (two sided). In the present study, the power value (α = 0.05) was calculated by using Power-Sample software (http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/PowerSampleSize) (Tang et al., 2013, 2019). The false-positive report probability (FPRP) was also harnessed to determine the results (He et al., 2013).

Results

Case–control study

A total of 1507 sex/age-matched participants (584 HCC cases/923 controls) were recruited. No significant difference was found in terms of age (HCC cases vs. controls [mean age]: 53.17 ± 11.76 years vs. 53.72 ± 9.97 years, p = 0.327), and gender (number of cases vs. controls [male/female]: 525/59 vs. 835/88, p = 0.717). The ratio of tobacco consumption was similar between two groups (number of cases vs. controls [never/ever]: 374/210 vs. 596/327, p = 0.834). Differences in the distribution of chronic HBV infection and alcohol drinking were found (chronic HBV infection of HCC cases vs. controls [yes/no]: 412/172 vs. 85/838, p < 0.001; drinking of cases vs. controls [never/ever]: 414/170 vs. 775/148, p < 0.001). In controls, the genotype of the miRNA-499 rs3746444, miRNA-146a rs2910164, and miRNA-196a2 rs11614913 conformed to the HWE. The minor allele frequency (MAF) of miRNA-499 rs3746444, miRNA-146a rs2910164, and miRNA-196a2 was 0.15, 0.38, and 0.43, respectively (Table 1).

Table 1.

Primary Information for miR-146a rs2910164 C>G, miR-196a2 rs11614913 T > C and miR-499 rs3746444 A>G Polymorphisms

Genotyped SNPs	miR-146a rs2910164 C > G	miR-196a2 rs11614913 T > C	miR-499 rs3746444 A>G
Chromosome	5	12	20
Function	nc-transcript-variant	nc-transcript-variant	nc-transcript-variant
Chr Pos (NCBI Build 38)	160485411	53991815	3499048
MAF for Chinese in database	0.35	0.34	0.15
MAF in our controls (n = 923)	0.38	0.43	0.15
p Value for HWE test in our controls	0.998	0.125	0.673
Genotyping method	SNPscan	SNPscan	SNPscan
% Genotyping value	99.27%	99.27%	99.27%

HWE, Hardy–Weinberg equilibrium; MAF, minor allele frequency; SNP, single nucleotide polymorphism.

Relationship of miRNA SNPs with HCC

The genotype of the miRNA SNPs are summarized in the Supplementary Data. Table 2 lists the frequency of rs3746444 variants in miRNA-499. MiRNA-499 rs3746444 AA, AG, and GG variant frequencies were 71.13% (409), 26.78% (154), and 2.09% (12) in HCC patients and 72.64% (669), 24.97% (230), and 2.39% (22) in controls. In the included controls, MAF of rs3746444 in miRNA-499 was similar to the HapMap-CHB database (MAF = 0.15). We identified a null association between rs3746444 in miRNA-499 and the development of HCC (AG vs. AA: p = 0.454; GG vs. AA: p = 0.754, AG/GG vs. AA: p = 0.527; GG vs. AA/AG: p = 0.704). With adjustments for age, sex, HBsAg, smoking, and drinking, we also found that there was no association between rs3746444 in miRNA-499 and HCC risk (AG vs. AA: p = 0.331; GG vs. AA: p = 0.845, AG/GG vs. AA: p = 0.332; GG vs. AA/AG: p = 0.912).

Table 2.

The Relationship of miRNA Polymorphisms with Hepatocellular Carcinoma

Genotype	Cases (n = 584)		Controls (n = 923)		Crude OR (95% CI)	p	Adjusted OR ^a (95% CI)	p
Genotype	n	%	N	%	Crude OR (95% CI)	p	Adjusted OR ^a (95% CI)	p
miRNA-499 rs3746444
AA	409	71.13	669	72.64	1.00		1.00
AG	154	26.78	230	24.97	1.10 (0.86–1.39)	0.454	1.17 (0.86–1.59)	0.331
GG	12	2.09	22	2.39	0.89 (0.44–1.82)	0.754	1.10 (0.43–2.81)	0.845
AG+GG	166	28.87	252	27.36	1.08 (0.86–1.36)	0.527	1.16 (0.86–1.57)	0.332
AA+AG	563	97.91	899	97.61	1.00		1.00
GG	12	2.09	22	2.39	0.87 (0.43–1.77)	0.704	1.05 (0.41–2.68)	0.912
G allele	178	15.48	274	14.88
miR-146a rs2910164
CC	194	33.74	359	38.98	1.00		1.00
CG	297	51.65	432	46.91	1.27 (1.01–1.60)	0.039	1.34 (0.99–1.81)	0.057
GG	84	14.61	130	14.12	1.20 (0.86–1.66)	0.281	1.36 (0.89–2.08)	0.154
CG+GG	381	66.26	562	61.02	1.26 (1.01–1.56)	0.041	1.35 (1.01–1.79)	0.043
CC+CG	491	85.39	791	85.88	1.00		1.00
GG	84	14.61	130	14.12	1.04 (0.77–1.40)	0.790	1.15 (0.78–1.68)	0.481
G allele	465	40.43	692	37.57
miR-196a2 rs11614913
TT	181	31.48	289	31.38	1.00		1.00
TC	281	48.87	474	51.47	0.95 (0.75–1.20)	0.650	0.96 (0.70–1.31)	0.772
CC	113	19.65	158	17.16	1.14 (0.84–1.55)	0.393	1.21 (0.82–1.80)	0.343
TC+CC	394	68.52	632	68.62	1.00 (0.80–1.25)	0.968	1.02 (0.76–1.37)	0.896
TT+TC	462	80.35	763	82.84	1.00		1.00
CC	113	19.65	158	17.16	1.18 (0.90–1.54)	0.223	1.25 (0.88–1.76)	0.214
C allele	507	44.09	790	42.89

Bold values are statistically significant (p < 0.05).

Adjusted for age, sex, smoking, status of chronic HBV infection, and drinking.

CI, confidence interval; HBV, hepatitis B virus; miRNAs, microRNAs; OR, odds ratio.

Table 2 summarizes the frequency of rs2910164 variants in miRNA-146a. The CC, CG, and GG variant frequencies were 33.74% (194), 51.65% (297), and 14.61% (84) in HCC patients and 38.98% (359), 46.91% (432), and 14.12% (130) in controls. In controls, the MAF of miRNA-146a rs2910164 was similar to the HapMap-CHB database (MAF = 0.35). We found that miRNA-146a CG or CG/GG increased the risk of HCC (CG vs. CC: p = 0.039 and CG/GG vs. CC: p = 0.041). With adjustments for age, sex, HBsAg, smoking, and drinking, we also found that there was an association between miRNA-146a rs2910164 and HCC susceptibility (CG/GG vs. CC: p = 0.043).

miRNA-196a2 rs11614913 TT, TC, and CC variant frequencies were 31.48% (181), 48.87% (281), and 19.65% (113) in HCC patients and 31.38% (289), 51.47% (474), and 17.16% (158) in controls. In controls, the MAF of miRNA-196a2 rs11614913 was 0.43. We did not identify any association between rs11614913 in miRNA-196a2 and development of HCC (TC vs. TT: p = 0.650; CC vs. TT: p = 0.393, CT/CC vs. TT: p = 0.968; CC vs. TT/TC: p = 0.223). With adjustments for age, sex, HBsAg, smoking, and drinking, we also found that there was no correlation between rs11614913 in miRNA-196a2 and HCC (TC vs. TT: p = 0.772; CC vs. TT: p = 0.343, CT/CC vs. TT: p = 0.896; CC vs. TT/TC: p = 0.214).

Stratification analysis

Table 3 lists the number of miRNA-146a rs2910164 variants in different subgroups. In the <53-year-old subgroup, a correlation of the rs2910164 locus with HCC risk was found (GG/CG vs. CC: adjusted p = 0.011, GG vs. CC: adjusted p = 0.021 and CG vs. CC: adjusted p = 0.027). The association between miRNA-146a rs2910164 and the risk of HCC was also found in the never-smoking and never-drinking subgroups (never-smoking subgroup: GG/CG vs. CC: adjusted p = 0.011 and CG vs. CC: adjusted p = 0.018; never-drinking subgroup: GG/CG vs. CC: adjusted p = 0.042 and CG vs. CC: adjusted p = 0.039). When we conducted stratification analysis by the status of chronic HBV infection, we identified that miRNA-146a rs2910164 conferred a risk to HCC in individuals with chronic HBV infection (GG/CG vs. CC: adjusted p = 0.035 and CG vs. CC: adjusted p = 0.028). However, a null association was found in other subgroups.

Table 3.

Stratified Analyses Between miRNA-146a rs2910164 C > G Polymorphism and Hepatocellular Carcinoma Risk by Sex, Age, Chronic Hepatitis B Virus Infection, Smoking Status, and Alcohol Consumption

Variable	miRNA-146a rs2910164 C > G (case/control)^a			Adjusted OR ^b (95% CI); p
Variable	CC	CG	GG	CG vs. CC	GG vs. CC	GG/CG vs. CC	GG vs. CC/CG
Sex
Male	177/329	269/388	71/116	1.31 (0.94–1.83); 0.109	1.35 (0.84–2.15); 0.211	1.32 (0.96–1.81); 0.085	1.15 (0.75–1.76); 0.513
Female	17/30	28/44	13/14	1.88 (0.75–4.68); 0.177	2.31 (0.76–7.04); 0.142	2.00 (0.84–4.73); 0.117	1.56 (0.61–4.02); 0.355
Age
<53	81/157	136/185	43/51	1.69 (1.06–2.69); 0.027	2.13 (1.13–4.03); 0.021	1.78 (1.15–2.77); 0.011	1.56 (0.88–2.76); 0.127
≥53	113/202	161/247	41/79	1.11 (0.74–1.66); 0.607	0.93 (0.52–1.66); 0.809	1.07 (0.73–1.56); 0.736	0.88 (0.52–1.49); 0.626
Smoking status
Never	115/229	194/277	59/88	1.57 (1.08–2.26); 0.018	1.61 (0.98–2.65); 0.061	1.58 (1.11–2.24); 0.011	1.24 (0.79–1.93); 0.349
Ever	79/130	103/155	25/42	1.09 (0.62–1.89); 0.773	0.99 (0.43–2.28); 0.979	1.06 (0.63–1.81); 0.817	0.94 (0.44–2.04); 0.884
Alcohol consumption
Never	141/309	208/354	59/110	1.43 (1.02–2.00); 0.039	1.29 (0.80–2.07); 0.294	1.39 (1.01–1.92); 0.042	1.06 (0.68–1.63); 0.810
Ever	53/50	89/78	25/20	0.96 (0.47–1.96); 0.918	1.71 (0.67–4.35); 0.260	1.11 (0.57–2.16); 0.763	1.75 (0.76–4.02); 0.188
Chronic HBV infection
Yes	137/40	213/32	54/13	1.83 (1.07–3.15); 0.028	1.42 (0.67–3.01); 0.362	1.72 (1.04–2.85); 0.035	1.03 (0.51–2.08); 0.931
No	57/319	84/400	30/117	1.11 (0.77–1.62); 0.569	1.35 (0.82–2.22); 0.236	1.17 (0.82–1.66); 0.387	1.27 (0.81–1.98); 0.297

Bold values are statistically significant (p < 0.05).

For miRNA-146a rs2910164 C>G, the genotyping was successful in 575 (98.46%) HCC cases, and 921 (99.78%) controls.

Adjusted for age, sex, smoking, drinking, chronic HBV infection (besides stratified factors accordingly) in a multiple logistic regression model.

HCC, hepatocellular carcinoma.

For miRNA-499 rs3746444 and miRNA-196a2 rs11614913, we did not find any association between these SNPs and HCC risk (Tables 4 and 5).

Table 4.

Stratified Analyses Between miRNA-196a2 rs11614913 T > C Polymorphism and Hepatocellular Carcinoma Risk by Sex, Age, Chronic Hepatitis B Virus Infection, Smoking Status, and Alcohol Consumption

Variable	miR-196a2 rs11614913 T > C (case/control)^a			Adjusted OR ^b (95% CI); p
Variable	TT	TC	CC	TC vs. TT	CC vs. TT	CC/TC vs. TT	CC vs. TT/TC
Sex
Male	163/263	253/428	101/142	1.00 (0.71–1.41); 0.989	1.22 (0.79–1.87); 0.379	1.05 (0.76–1.46); 0.750	1.22 (0.83–1.78); 0.311
Female	18/26	28/46	12/16	0.71 (0.31–1.67); 0.438	0.79 (0.26–2.44); 0.687	0.73 (0.33–1.64); 0.451	0.97 (0.36–2.65); 0.958
Age
<53	78/130	129/197	53/66	1.12 (0.70–1.79); 0.649	1.26 (0.69–2.30); 0.459	1.15 (0.74–1.80); 0.534	1.18 (0.69–2.00); 0.551
≥53	103/159	152/277	60/92	0.85 (0.56–1.29); 0.448	1.23 (0.72–2.08); 0.445	0.94 (0.64–1.40); 0.764	1.36 (0.85–2.16); 0.199
Smoking status
Never	118/192	180/296	70/106	0.99 (0.68–1.43); 0.939	1.23 (0.76–1.97); 0.398	1.05 (0.74–1.49); 0.795	1.24 (0.82–1.88); 0.317
Ever	63/97	101/178	43/52	0.86 (0.48–1.55); 0.620	0.97 (0.46–2.07); 0.944	0.89 (0.51–1.55); 0.682	1.07 (0.55–2.07); 0.842
Alcohol consumption
Never	133/241	196/402	79/130	0.89 (0.63–1.25); 0.496	1.10 (0.71–1.72); 0.667	0.94 (0.68–1.30); 0.710	1.19 (0.80–1.76); 0.393
Ever	48/48	85/72	34/28	1.26 (0.60–2.67); 0.546	1.99 (0.83–4.79); 0.126	1.46 (0.73–2.94); 0.289	1.73 (0.82–3.64); 0.151
Chronic HBV infection
Yes	133/22	192/52	79/11	0.59 (0.33–1.05); 0.073	1.24 (0.55–2.79); 0.598	0.70 (0.40–1.23); 0.215	1.75 (0.86–3.55); 0.124
No	48/267	89/422	34/147	1.20 (0.82–1.77); 0.348	1.23 (0.75–2.00); 0.408	1.21 (0.84–1.75); 0.309	1.09 (0.72–1.67); 0.675

For miR-196a2 rs11614913 T>C, the genotyping was successful in 575 (98.46%) HCC cases, and 921 (99.78%) controls.

Adjusted for age, sex, smoking, drinking, chronic HBV infection (besides stratified factors accordingly) in a multiple logistic regression model.

Table 5.

Stratified Analyses Between miRNA-499 rs3746444 A>G Polymorphism and Hepatocellular Carcinoma Risk by Sex, Age, Chronic Hepatitis B Virus Infection, Smoking Status, and Alcohol Consumption

Variable	miRNA-499 rs3746444 A>G (case/control)^a			Adjusted OR ^b (95% CI); p
Variable	AA	AG	GG	AG vs. AA	GG vs. AA	GG/AG vs. AA	GG vs. AA/AG
Sex
Male	362/603	143/210	12/20	1.36 (0.97–1.90); 0.079	1.21 (0.45–3.25); 0.711	1.34 (0.97–1.87); 0.080	1.11 (0.41–2.97); 0.836
Female	47/66	11/20	0/2	0.50 (0.19–1.33); 0.163	—	0.47 (0.18–1.25); 0.132	—
Age
<53	186/284	68/99	6/10	1.02 (0.63–1.64); 0.933	1.89 (0.56–6.40); 0.309	1.08 (0.68–1.71); 0.736	1.88 (0.56–6.32); 0.310
≥53	223/385	86/131	6/12	1.30 (0.86–1.97); 0.209	0.56 (0.14–2.21); 0.405	1.23 (0.82–1.84); 0.314	0.52 (0.13–2.05); 0.349
Smoking status
Never	268/439	92/137	8/18	1.18 (0.81–1.73); 0.391	0.94 (0.33–2.70); 0.906	1.16 (0.80–1.67); 0.439	0.90 (0.31–2.58); 0.843
Ever	141/230	62/93	4/4	1.13 (0.65–1.99); 0.664	1.77 (0.22–14.38); 0.595	1.16 (0.67–2.01); 0.609	1.70 (0.21–13.72); 0.620
Alcohol consumption
Never	298/569	102/184	8/20	1.19 (0.83–1.69); 0.339	0.95 (0.34–2.68); 0.919	1.17 (0.83–1.64); 0.380	0.91 (0.32–2.55); 0.853
Ever	111/100	52/46	4/2	1.15 (0.59–2.26); 0.679	1.65 (0.16–17.34); 0.679	1.17 (0.61–2.27); 0.634	1.57 (0.15–16.37); 0.706
Chronic HBV infection
Yes	291/66	105/18	8/1	1.30 (0.71–2.38); 0.388	1.13 (0.13–9.63); 0.910	1.29 (0.72–2.32); 0.391	1.07 (0.13–9.07); 0.952
No	118/603	49/212	4/21	1.18 (0.81–1.71); 0.388	0.99 (0.33–2.97); 0.988	1.16 (0.81–1.67); 0.418	0.95 (0.32–2.83); 0.925

For miRNA-499 rs3746444 A>G, the genotyping was successful in 575 (98.46%) HCC cases, and 921 (99.78%) controls.

Adjusted for age, sex, smoking, drinking, chronic HBV infection (besides stratified factors accordingly) in a multiple logistic regression model.

Combination analysis of miRNA polymorphisms

Table 6 summarized the combined analyses of miRNA polymorphisms. Rs2910164/rs3746444, rs11614913/rs3746444, rs11614913/rs2910164, and rs11614913/rs2910164/rs3746444 combinations were used to analyze the interaction of SNP-SNP with HCC risk (Qiu et al., 2019; Thakur et al., 2019). Compared with rs2910164 CC/rs3746444 AA, we found that rs2910164 CG/rs3746444 AA may confer an increased risk to HCC (OR 1.43, 95% CI 1.09–1.87, p = 0.010).

Table 6.

Combination Analysis of miRNA Loci (rs3746444, rs2910164, and rs11614913) in Hepatocellular Carcinoma Cases and Controls

Genotype	HCC cases		Controls		OR (95% CI)	p
Genotype	n	%	n	%	OR (95% CI)	p
rs11614913/rs2910164
TT/CC	60	10.43	107	11.62	1.00
TT/CG	96	16.70	141	15.31	1.21 (0.81–1.83)	0.352
TT/GG	25	4.35	41	4.45	1.09 (0.60–1.96)	0.871
TC/CC	100	17.39	189	20.52	0.94 (0.63–1.41)	0.775
TC/CG	140	24.35	220	23.89	1.13 (0.78–1.66)	0.515
TC/GG	41	7.13	65	7.06	1.12 (0.68–1.86)	0.646
CC/CC	34	5.91	63	6.84	0.96 (0.57–1.62)	0.886
CC/CG	61	10.61	71	7.71	1.53 (0.96–2.44)	0.072
CC/GG	18	3.13	24	2.61	1.34 (0.67–2.66)	0.407
rs11614913/rs3746444
TT/AA	127	22.09	206	22.37	1.00
TT/AG	50	8.70	78	8.47	1.04 (0.68–1.58)	0.855
TT/GG	4	0.70	5	0.54	1.30 (0.34–4.92)	0.701
TC/AA	202	35.13	350	38.00	0.94 (0.71–1.24)	0.645
TC/AG	72	12.52	113	12.27	1.03 (0.71–1.50)	0.861
TC/GG	7	1.22	11	1.19	1.03 (0.39–2.73)	0.949
CC/AA	80	13.91	113	12.27	1.15 (0.80–1.65)	0.454
CC/AG	32	5.57	39	4.23	1.33 (0.79–2.23)	0.278
CC/GG	1	0.17	6	0.65	0.27 (0.03–2.27)	0.197
rs2910164/rs3746444
CC/AA	133	23.13	268	29.10	1.00
CC/AG	57	9.91	84	9.12	1.37 (0.92–2.03)	0.120
CC/GG	4	0.70	7	0.76	1.15 (0.33–4.00)	0.824
CG/AA	214	37.22	302	32.79	1.43 (1.09–1.87)	0.010
CG/AG	76	13.22	120	13.03	1.28 (0.90–1.82)	0.177
CG/GG	7	1.22	10	1.09	1.41 (0.53–3.79)	0.493
GG/AA	62	10.78	99	10.75	1.26 (0.86–1.84)	0.229
GG/AG	21	3.65	26	2.82	1.63 (0.88–3.00)	0.116
GG/GG	1	0.17	5	0.54	0.40 (0.05–3.49)	0.393
rs11614913/rs2910164/rs3746444
TT/CC/AA	41	7.13	78	8.47	1.00
TT/CC/AG	18	3.13	28	3.04	1.22 (0.61–2.47)	0.574
TT/CC/GG	1	0.17	1	0.11	1.90 (0.12–31.23)	0.647
TT/CG/AA	68	11.83	101	10.97	1.28 (0.79–2.09)	0.319
TT/CG/AG	26	4.52	37	4.02	1.34 (0.71–2.51)	0.364
TT/CG/GG	2	0.35	3	0.33	1.27 (0.20–7.90)	0.799
TT/GG/AA	18	3.13	27	2.93	1.27 (0.63–2.57)	0.509
TT/GG/AG	6	1.04	13	1.41	0.71 (0.26–1.96)	0.512
TT/GG/GG	1	0.17	1	0.11	1.90 (0.12–31.23)	0.647
TC/CC/AA	68	11.83	145	15.74	0.89 (0.55–1.44)	0.638
TC/CC/AG	30	5.22	40	4.34	1.43 (0.78–2.62)	0.249
TC/CC/GG	2	0.35	4	4.71	0.95 (0.17–5.42)	0.955
TC/CG/AA	106	18.43	154	16.72	1.31 (0.83–2.06)	0.242
TC/CG/AG	30	5.22	62	6.73	0.92 (0.52–1.64)	0.779
TC/CG/GG	5	0.87	4	0.43	2.38 (0.61–9.34)	0.203
TC/GG/AA	29	5.04	51	5.54	1.08 (0.60–1.96)	0.795
TC/GG/AG	12	2.09	11	1.19	2.08 (0.84–5.11)	0.108
TC/GG/GG	0	0.0	3	0.33	0.27 (0.01–5.36)	0.212
CC/CC/AA	24	4.17	45	4.89	1.01 (0.54–1.89)	0.964
CC/CC/AG	9	1.57	16	1.74	1.07 (0.44–2.63)	0.883
CC/CC/GG	1	0.17	2	0.22	0.95 (0.08–10.81)	0.968
CC/CG/AA	41	7.13	47	5.10	1.66 (0.94–2.92)	0.078
CC/CG/AG	20	3.48	21	2.28	1.81 (0.88–3.72)	0.103
CC/CG/GG	0	0.0	3	0.33	0.27 (0.01–5.36)	0.212
CC/GG/AA	15	2.61	21	2.28	1.36 (0.63–2.91)	0.430
CC/GG/AG	3	0.52	2	0.22	2.85 (0.46–17.77)	0.242
CC/GG/GG	0	0.0	1	0.11	0.63 (0.03–15.84)	0.469

Bold values are statistically significant (p < 0.05).

Power calculation and FPRP method

For miRNA-146a rs2910164 SNP, the power value was 0.768 in CG/GG versus CC genetic model. In the <53-year-old subgroup, the power values were 0.837 in CG versus CC, 0.875 in GG versus CC, and 0.928 in CG/GG versus CC. In the never-smoking subgroup, the power values were 0.861 in CG versus CC and 0.842 in CG/GG versus CC. In the never-drinking subgroup, the power values were 0.759 in CG versus CC and 0.730 in CG/GG versus CC. In individuals with chronic HBV infection subgroup, the power values were 0.646 in CG versus CC and 0.616 in CG/GG versus CC. In combination analysis of miRNA polymorphisms, compared with rs2910164CC/3746444AA, rs2910164CG/3746444AA could not promote the development of HCC (power = 0.735). Using FPRP method and power value, we found that miRNA-146a rs2910164 conferred a risk to HCC in the <53-year-old and never-smoking subgroups.

Discussion

Accumulating evidence suggests that miRNAs are implicated in a new mechanism in the development of HCC. Recently, several studies have been performed to identify the relationship of miRNA variants with susceptibility to HCC. However, these studies reported conflicting findings. In this study, we included 584 HCC cases and 923 controls and explored the association of miRNAs variants with HCC susceptibility. We found that rs2910164 increased the susceptibility to HCC in the never-smoking and the <53-year-old subgroups.

Currently, more gene-related investigations have focused on the relationship of rs2910164 C>G polymorphism in miRNA-146a with cancer development. However, most of the polymorphisms only make a low penetrance for cancer risk. In this study, we performed a study involving 1507 subjects to conduct an evaluation between rs2910164 variants and HCC susceptibility. Recently, the correlation of the variants in rs2910164 with HCC risk has been extensively studied (Xu et al., 2008; Akkiz et al., 2011b; Zhang et al., 2011, 2013; Shan et al., 2013; Chu et al., 2014; Qi et al., 2014; Li et al., 2015; Riazalhosseini et al., 2016; Farokhizadeh et al., 2019). In addition, two meta-analyses have identified an association between rs2910164 variants in miRNA-146a and the overall susceptibility to cancer (Ma et al., 2013; Nikolic et al., 2015). However, the potential correlation between the variants in rs2910164 and HCC development is conflicting. Xu et al. (2008) reported that rs2910164 SNP might influence a risk of HCC. However, other investigations suggested that rs2910164 C>G polymorphism in miRNA-146a was not associated with the risk of HCC (Akkiz et al., 2011b; Zhang et al., 2011, 2013; Shan et al., 2013; Chu et al., 2014; Qi et al., 2014; Li et al., 2015; Riazalhosseini et al., 2016; Farokhizadeh et al., 2019).

Considering most of these studies had a small sample size, the association of rs2910164 C > G polymorphism to HCC development was still unclear. In this study, 1507 participants were recruited to evaluate a correlation of rs2910164 SNP with HCC risk. In this study, we identified that the rs2910164 C > G locus might increase the susceptibility of HCC, especially in the never-smoking and the <53-year-old subgroups. It is notable that rs2910164 SNP conferred a risk to chronic infection of HBV (Al-Qahtani et al., 2017; Khanizadeh et al., 2019), and the rs2910164 CC variant altered spontaneous viral clearance of HBV (Khanizadeh et al., 2019). It could be explained that the rs2910164 C > G polymorphism might influence the status of chronic HBV infection and subsequently increased the susceptibility of HCC. In addition, the association could be influenced by interaction of gene and environmental factors. Wang et al. (2018) reported miR-146a rs2910164 G allele could increase the risk of HCC in a more recent meta-analysis, which was similar to our findings.

MiR-146a is a negative regulator of immune response. It was suggested that mRNAs might regulate Toll-like receptors (TLRs) by combining with 3′-untranslated regions (O'Neill et al., 2011). What is more, some bioinformatic investigations indicated an interaction of miR-146a and TLR4 (Yang et al., 2011; Li and Shi, 2013). A previous study found that an elevated miR-146a expression might lead to the drug resistance and milieu of immunosuppression (Khorrami et al., 2017). Compared with rs2910164 CC/GC genotype, the mir-146a expression was higher in rs2910164 GG genotype patients with inflammatory bowel disease (Zhu et al., 2016a). Additionally, in never-smoking lung cancer patients, the expression of miR-146a also increased in patients with rs2910164 GG variant than those with rs2910164 CC/CG variants (Jeon et al., 2014). Thus, miR-146a rs2910164 C > G locus may be implicated in the development of HCC by promoting the expression miR-146a.

Combined influence of three miRNA polymorphisms was explored in this study. More and more publications reported that the interaction of gene–gene may confer the susceptibility to complex disorders. Recently, some case–control studies suggested the influence of combined genotypes of these miRNA SNPs to risk of diseases (Rah et al., 2013; Thakur et al., 2019). In the current investigation, rs2910164 CG/rs3746444 AA was found to be associated with a tendency risk to HCC. In a previous study, Rah et al. (2013) reported that rs2910164 CG/rs3746444 AA might decrease the risk of premature ovarian failure. However, in the other study, the association of rs2910164 CG/rs3746444 AA with risk of cervical cancer was not found (Thakur et al., 2019), which was not consistent with our findings. Therefore, the roles of rs2910164 CG/rs3746444 AA might be different in different diseases. The potential association should be verified in future studies.

In this study, some merits should be acknowledged. First, our investigation included larger sample size to detect the correlation between miRNA variants and the development of HCC. Second, the MAFs of miRNA-499 rs3746444, miRNA-146a rs2910164, and miRNA-196a2 rs11614913 were similar to the database for a Chinese population. Third, the distribution of miRNA variants was consistent with the HWE in controls. Finally, we observed that rs2910164 increased a risk of HCC in the chronic HBV infection subgroup. It is assumed that the rs2910164 G allele may influence spontaneous viral clearance of HBV and is implicated in the susceptibility to HCC subsequently.

Additionally, several limitations in the present investigation also should be addressed. First, due to a hospital-based study, bias might not have been avoided. Second, we only included five major risk factors (e.g., age, sex, HBsAg, smoking, and drinking) in this study. Other potential environmental factors should not have been ignored. Third, in some subgroups, the moderate sample size might limit the power of stratification analysis. Fourth, the association of SNPs in miRNAs with the expression and function was not studied. Fifth, the participants were relatively small in some comparisons, and these results might be underpowered. Finally, we only studied the relationship of miRNA-499 rs3746444, miRNA-146a rs2910164, and miRNA-196a2 with HCC risk. Additionally, we did not explore the association of other SNPs in miRNAs with HCC development.

In summary, our study suggests that miRNA-146a rs2910164 C > G SNP increases the risk of HCC. In the future, more studies with detailed environmental factors and large sample sizes should be carried out.

Footnotes

Acknowledgments

The authors appreciate all subjects who participated in this study. They wish to thank Dr. Yan Liu (Genesky Biotechnologies, Inc., Shanghai, China) for technical support.

Author Contributions

Conceived and designed the experiments: Y.C., L.L.; Performed the experiments: S.Z., L.C., Y.W.; Analyzed the data: Y.W., W.T.; Contributed reagents/materials/analysis tools: Y.C., L.L.; Wrote the article: S.Z., L.C.

Disclosure Statement

No competing financial interests exist.

Funding Information

The project was supported by the Application and Basic Research Project of Changzhou City (CJ20180068).

Supplementary Material

Supplementary Data

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Supplementary Material

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Investigation of the Association of miRNA-499,miRNA-146a,miRNA-196a2 Loci with Hepatocellular Carcinoma Risk: A Case–Control Study Involving 1507 Subjects

Abstract

Introduction

Materials and Methods

Subjects

Polymorphisms selection

Genotying

Statistical analyses

Results

Case–control study

Relationship of miRNA SNPs with HCC

Stratification analysis

Combination analysis of miRNA polymorphisms

Power calculation and FPRP method

Discussion

Footnotes

Acknowledgments

Author Contributions

Disclosure Statement

Funding Information

Supplementary Material

References

Supplementary Material