Genetic variants in STAT4 and their interactions with environmental factors for the incidence of hepatocellular carcinoma

Abstract

BACKGROUND:

A recent genome-wide association study (GWAS) has posed STAT4 as a promising susceptibility gene for hepatocellular carcinoma (HCC). However, the most significant variant in this GWAS, rs7574865, yielded inconsistent results.

OBJECTIVE:

This study, in a Southern Chinese population, was aimed to clarify the roles in HCC incidence of the rs7574865 and other two potentially functional variants, rs897200 and rs1031507 in STAT4.

METHODS:

This study enrolled 631 new HCC cases and 631 cancer-free controls. The genetic association was estimated using the multivariate logistic regression model. The pairwise gene-environment interactions were assessed using the multiplicative term in regression model and the “Delta” method for the additive scale.

RESULTS:

In the multivariate analysis, the rs7574865 TT genotype conferred a decreased risk of HCC compared to the GG genotype (adjusted OR $=$ 0.62, 95%CI $=$ 0.38 $\sim$ 0.99). The significant association of rs7574865 was also observed under the additive genetic model, with an adjusted OR of 0.81 (95%CI $=$ 0.65 $\sim$ 0.99). Nevertheless, other two variants alone showed no significant association, as well as the haplotypes and genetic risk scores. Further analysis indicated a potential interaction between the rs897200 and alcohol drinking ( $P=$ 0.048 and 0.072 for additive and multiplicative interactions, respectively). Drinkers with the rs897200 CT+CC genotypes presented an increased disease-risk, as compared with non-drinkers carrying the TT genotype (adjusted OR $=$ 1.68, 95%CI $=$ 1.11 $\sim$ 2.54).

CONCLUSIONS:

The variant in STAT4, rs7574865, serves as a potential marker for predicting incidence of HCC. The rs897200 variant possibly interplays with alcohol drinking to alter HCC risk in the Southern Chinese, but warrants further investigation.

Keywords

Hepatocellular carcinoma (HCC)signal transducer and activator of transcription 4 (STAT4)genetic variant genotype gene-environment interaction

1. Introduction

Hepatocellular carcinoma (HCC), the major histological type of primary liver cancer, is the sixth most common cancer. Moreover, it is the fourth leading cause of cancer death worldwide, with almost 800,000 deaths annually [1, 2]. The development of HCC is a stepwise process involving the confluence of multiple etiological factors. Several dominant risk factors, including chronic infection of hepatitis B virus (HBV) or hepatitis C virus (HCV) [3], alcohol drinking [3], prolonged aflatoxin exposure [3], and tobacco use [4], have been linked to the incidence of HCC. The observation that most individuals exposed to the well-known risk factors never develop HCC demonstrates that individual susceptibility modulates the process of HCC. Family clustering and incidence variety among different ancestry groups have highlighted the important role of genetic components in HCC susceptibility [5].

The Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signaling pathway plays a key role in regulating a variety of cellular processes such as survival, proliferation, and differentiation [6]. The STAT proteins are critical regulators of anti-viral defense against hepatitis viral infection, inflammation, and tumorigenesis [7]. STAT4, one member of the STAT family, is important for the differentiation of the Type 1 helper cells to promote cell-mediated immune response. Also, STAT4 activates the transcription of various target genes after it is phosphorylated and translocated to the nucleus. Moreover, STAT4 has exhibited complex biological functions in regulating liver injury, liver fibrosis and hepatocarcinogenesis in vivo and in vitro [8]. A three-stage designed genome-wide association study (GWAS), including seven case-control populations, has further identified STAT4 as a promising susceptibility gene for HCC in a Chinese cohort [9]. The most significant variant, rs7574865 in STAT4, was strongly associated with lower levels of STAT4 mRNA in both the HCC tissues and non-tumor tissues. However, this variant was not cross-validated in other GWASs and the following replicated investigations [10]. It could be possible that the rs7574865 might be largely marker correlated to causal variants, showing significant heterogeneity of genetic association in different ethnic groups, because of the distinct genetic architecture and environmental pressures. Therefore, more consolidated studies are warranted to further clarify the role of rs7574865 and detect out the casual variant of STAT4. We herein performed a replicated analysis comprising 631 cases and 631 controls in a Southern Chinese population, to provide more precise estimation of the association between rs7574865 and HCC risk. We further explored the genetic associations of two potential functional variants selected by bioinformatical method, rs897200 and rs1031507, and their interactions with environmental factors on HCC risk.

Table 1
The characteristics of cases with HCC and controls

Variables	Cases (%) $N=$ 631	Controls (%) $N=$ 631	$\chi^{2}$	$P$
Age group (years)			0.62	0.431
$\leqslant$ 56	321 (50.87)	307 (48.65)
$>$ 56	310 (49.13)	324 (51.35)
Gender			0.17	0.681
Male	548 (86.85)	543 (86.05)
Female	83 (13.15)	88 (13.95)
Smoking status			18.38	$<$ 0.001
Never	204 (32.33)	278 (44.06)
Ever	427 (67.67)	353 (55.94)
Drinking status			15.53	$<$ 0.001
Never	281 (44.53)	351 (55.63)
Ever	350 (55.47)	280 (44.37)
Chronic HBV infection ${}^{\text{a}}$			411.12	$<$ 0.001
Negative	165 (26.19)	524 (83.04)
Positive	465 (73.81)	107 (16.96)
HCC family history			39.86	$<$ 0.001
No	545 (86.37)	608 (96.35)
Yes	86 (13.63)	23 (3.65)

${}^{\text{a}}$ Missing one observation.

2. Materials and methods

2.1 Study populations

The hospital-based case-control study consisted of 631 newly diagnosed HCC cases and 631 cancer-free controls. The subjects’ enrollment has been described previously [11]. In brief, the cases were confirmed by pathological examination combined with imaging examination. Patients were consecutively recruited from Shunde Hospital of Southern Medical University, Foshan, China, between September 2010 and October 2014. Cancer-free controls were randomly selected from a physical health screening at the same hospital, during the same period of the case enrollment. The controls were frequency matched to cases by gender and age ( $\pm$ 5 years). All participants were genetically unrelated ethnic Han Chinese population from Foshan City and its surrounding areas. The protocol of this study was approved by the institutional review board of Guangdong pharmaceutical university. At recruitment, the written informed consent has been obtained for each subject. Data about demographical characteristics (age, gender), smoking and drinking status, and family history of HCC, was collected by professionally trained interviewers, which detailed definitions have been described previously [11]. The information on serological testing including HBsAg, anti-HBs, HBeAg, anti-HBe, and anti-HBc was obtained from the medical records.

2.2 Genetic variants selection and genotyping

Except for the HCC associated variant (rs7574865) reported by the GWAS [12], the other two potentially functional variants in STAT4, with minor allele frequency (MAF) $>$ 0.05 in Han Chinese, were functionally annotated using multiple bioinformatic tools, including Ensembl genome browser (http://asia.ensembl. org/index.html) [13], HaploReg V4.1 (https://pubs.broadinstitute.org/mammals/haploreg/haploreg.php) [14], and RegulomeDB (http://www.regulomedb.org/). As predicted by HaploReg V4.1, chromatin mark ChIP-seq tracks existed at the location of rs897200 and rs1031507. Expression quantitative trait locus (eQTL) studies [15] revealed that rs897200 and rs1031507 in the lymphocytes for STAT4 expression had $P$ values of 2.46 $\times$ 10 ${}^{-9}$ and 1.02 $\times$ 10 ${}^{-10}$ , respectively. RegulomeDB analysis showed their scores were 1d and 1f, respectively. Considering the potential functional evidence, rs897200 and rs1031507, together with rs7574865, were finally selected for genotyping in this study.

Genomic DNA was extracted from 5 ml peripheral blood sample with the TIANamp Blood DNA Kit (Tiangen, Beijing, China) following the manufacturer’s instructions. Candidate variants were genotyped by TaqMan real-time polymerase chain reaction (PCR) assay (Applied Biosystems, Foster city, CA) without knowledge of the case or control status. PCR was performed in a 5 $\mu$ l reaction volume. The reaction cycling conditions were 95 ${}^{\circ}$ C for 10 min, followed by 40 cycles of 95 ${}^{\circ}$ C for 15 sec and 60 ${}^{\circ}$ C for 1 min. The ABI Prism 7900HT Sequence Detection System (Applied Biosystems, Carlsbad, CA, United States) was used to analyze the endpoint fluorescence. Quality control was monitored by including a 5% duplicate and negative control, with a 100% concurrence rate of the duplicate sets. Moreover, the average call rates for the three variants genotyped were all $>$ 99%.

Table 2
Association analysis of three genetic variants in STAT4 and the risk of HCC

Variants	Case (%) $N=$ 631	Controls (%) $N=$ 631	$\chi^{2}$	$P$	Crude OR (95%CI)	Adjusted OR (95%CI) ${}^{\text{b}}$
rs7574865 ${}^{\text{a}}$			5.37	0.068
GG	301 (47.78)	267 (42.38)			1.00	1.00
GT	272 (42.17)	286 (45.40)			0.84 (0.67 $\sim$ 1.07)	0.85 (0.63 $\sim$ 1.13)
TT	57 (9.05)	77 (12.22)			0.66 (0.45 $\sim$ 0.96)	0.62 (0.38 $\sim$ 0.99)
Dominant model	–	–			0.80 (0.64 $\sim$ 1.00)	0.80 (0.60 $\sim$ 1.05)
Recessive model	–	–			0.71 (0.50 $\sim$ 1.03)	0.67 (0.43 $\sim$ 1.05)
Additive model	–	–			0.82 (0.70 $\sim$ 0.97)	0.81 (0.65 $\sim$ 0.99)
rs897200			2.40	0.302
TT	264 (41.97)	276 (43.74)			1.00	1.00
CT	286 (45.47)	293 (46.43)			1.02 (0.81 $\sim$ 1.29)	1.01 (0.76 $\sim$ 1.35)
CC	79 (12.56)	62 (9.83)			1.33 (0.92 $\sim$ 1.93)	1.19 (0.75 $\sim$ 1.90)
Dominant model	–	–			1.08 (0.86 $\sim$ 1.34)	1.04 (0.79 $\sim$ 1.38)
Recessive model	–	–			1.32 (0.93 $\sim$ 1.88)	1.19 (0.76 $\sim$ 1.84)
Additive model	–	–			1.11 (0.94 $\sim$ 1.31)	1.06 (0.86 $\sim$ 1.31)
rs1031507			2.67	0.263
AA	266 (42.29)	277 (43.90)			1.00	1.00
AC	284 (45.15)	293 (46.43)			1.01 (0.80 $\sim$ 1.28)	0.99 (0.74 $\sim$ 1.33)
CC	79 (12.56)	61 (9.67)			1.35 (0.93 $\sim$ 1.96)	1.24 (0.78 $\sim$ 1.98)
Dominant model	–	–			1.07 (0.85 $\sim$ 1.34)	1.04 (0.78 $\sim$ 1.37)
Recessive model	–	–			1.34 (0.94 $\sim$ 1.91)	1.24 (0.80 $\sim$ 1.93)
Additive model	–	–			1.11 (0.94 $\sim$ 1.31)	1.07 (0.87 $\sim$ 1.32)

OR, Odds ratio; 95% CI, 95% confidence interval. ${}^{\text{a}}$ One case and one control were not successfully genotyped for rs7574865. ${}^{\text{b}}$ Adjusting for age, gender, smoking, drinking, chronic HBV infection, and family history of HCC.

2.3 Statistical analysis

Differences in the distribution of demographic characteristics and genotypes between cases and controls were evaluated by the Pearson’s $\chi^{2}$ test. Departure from the Hardy-Weinberg equilibrium (HWE) in controls was examined by the goodness-of-fit $\chi^{2}$ test. Unconditional multivariate logistic regression analysis was performed to evaluate the genetic associations with HCC risk. The odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated adjusting for age (as a categorical variable), gender, smoking, drinking, chronic HBV infection, and family history of HCC. To avoid the assumption of genetic models, three other models (dominant, recessive, and additive) were also employed [16]. Haplotype construction was performed using the Phase V2.1 program. A simple count genetic risk score (GRS) was constructed, by summing the risk alleles of the candidate variants for each subject [17]. Based on the crossover analysis, the multiplicative interaction term and the “Delta” method, under the dominant model, were used to evaluate the multiplicative and additive interactions between genetic and environmental factors, respectively. False positive report probability (FPRP) analysis was conducted to assess the noteworthiness of significant findings [18]. FPRP threshold was set to 0.5 assigned a prior probability of 0.1 and detect an OR of 0.67/1.50 (protective/risk effects) for an association with genotypes under investigation. The significant result with an FPRP value less than 0.5 was considered a noteworthy finding. A two-tailed $P$ value $<$ 0.05 was considered as significant. All statistical analyses were performed by SAS V9.4 software (SAS Institute, Cary, NC, USA).

3. Results

3.1 Subject characteristics

The characteristics distributions for the 631 cases and 631 controls are described in Table 1. The cases and controls were matched well by gender ( $P=$ 0.681) and age ( $P=$ 0.431). The cases had significantly higher rate of chronic HBV infection than that of controls (73.81% Versus 16.96%, $P<$ 0.001). Chronic HBV infection was the most predominant risk factor for HCC, with an adjusted OR of 14.41 (95%CI $=$ 10.80 $\sim$ 19.24; Supplement Table 1). In addition, smoking, drinking and family history of HCC were also associated with increased risk of HCC (Supplement Table 1). Hence, age, gender, chronic HBV infection, smoking and drinking, and family history of HCC were included as covariates in the subsequent multivariate analysis of genetic association.

3.2 Association between variants in STAT4 and HCC risk

The genotypic distributions of the candidate variants, rs7574865, rs897200, and rs1031507, are presented in Table 2. All variants were in agreement with Hardy – Weinberg equilibrium in controls(Supplement Table 2). The GG genotype of rs7574865 is in association with a decreased risk of HCC, compared with the TT genotype (crude OR $=$ 0.66, 95%CI $=$ 0.45 $\sim$ 0.96, $P=$ 0.030; Table 2). After adjusting the age, sex, and other covariates, this association remained significant (adjusted OR $=$ 0.62, 95%CI $=$ 0.38 $\sim$ 0.99, $P=$ 0.046). Under the additive model, a significant genetic association of rs7574865 was also observed, with an adjusted OR of 0.81 (adjusted 95%CI $=$ 0.65 $\sim$ 0.99, $P=$ 0.044). At the prior probability of 0.1 and FPRP cut-off value of 0.5, the association of rs7574865 with HCC risk was verified to be noteworthy (FPRP for GG vs. TT $=$ 0.316). The statistical power is 0.975 for detecting the genetic association of rs7574865 (MAF $=$ 0.35). Nevertheless, no evidence of significant association was seen between the other two variants and HCC risk.

In the haplotype analysis, three common haplotypes (frequency $>$ 5%) were observed, and no significant association were seen with the HCC risk(Supplement Table 3). Also, no significant associations of GRS with HCC were detected (Supplement Table 6).

Table 3
Gene-environment interaction analysis of rs897200 for the risk of HCC

Environmental factors	Genotypes	Cases/ controls	Adjusted OR (95%CI) ${}^{\text{a}}$	$P^{\text{a, b}}$	$P^{\text{a,c}}$
Smoking status				0.466	0.406
Never	TT	83/118	1.00
Never	CT $+$ CC	119/160	0.91 (0.58 $\sim$ 1.44)
Ever	TT	181/158	1.44 (0.89 $\sim$ 2.33)
Ever	CT $+$ CC	246/195	1.63 (1.03 $\sim$ 2.57)
Drinking status				0.072	0.048
Never	TT	125/146	1.00
Never	CT $+$ CC	155/205	0.80 (0.54 $\sim$ 1.20)
Ever	TT	139/130	1.25 (0.80 $\sim$ 1.95)
Ever	CT $+$ CC	210/150	1.68 (1.11 $\sim$ 2.54)
Chronic HBV infection				0.825	0.720
Negative	TT	72/230	1.00
Negative	CT $+$ CC	93/294	1.02 (0.71 $\sim$ 1.46)
Positive	TT	192/46	13.79 (8.94 $\sim$ 21.26)
Positive	CT $+$ CC	271/61	14.94 (10.03 $\sim$ 22.26)
HCC Family history				0.378	0.458
No	TT	225/268	1.00
No	CT $+$ CC	318/340	1.08 (0.81 $\sim$ 1.44)
Yes	TT	39/8	4.30 (1.75 $\sim$ 10.61)
Yes	CT $+$ CC	47/15	2.77 (1.35 $\sim$ 5.68)

OR, Odds ratio; 95% CI, 95% confidence interval. ${}^{\text{a}}$ Adjusting for age, gender, smoking, drinking, chronic HBV infection, and HCC family history. ${}^{\text{b}}$ $P$ values for interaction were calculated using the multiplicative scale. ${}^{\text{c}}$ $P$ values for interaction were calculated using the additive scale.

3.3 Gene-environment interactions analysis

We further performed the crossover analysis to explore the potential gene-environment interaction under the dominant model. The alcohol drinkers with the rs897200 CT and CC genotypes had an increased risk of HCC comparing with the non-drinkers carrying the TT genotype (adjusted OR $=$ 1.68, 95%CI $=$ 1.11 $\sim$ 2.54, $P=$ 0.014; Table 3). It’s worth noting that the additive and multiplicative interactions of gene-drinking for rs897200 were considered to indicate statistical significance ( $P=$ 0.048 and 0.072, respectively). Compared to the rs897200 TT genotype carriers negative for HBV, the adjusted OR was 13.79 (95%CI $=$ 8.94 $\sim$ 21.26) for chronic HBV infection individuals with the TT genotype, while the adjusted OR of 14.94 (95%CI $=$ 10.03 $\sim$ 22.26) for chronic HBV infection individuals with the CT $+$ CC genotypes. Similar results were observed for the other two variants and HBV infection in crossover analysis. Nevertheless, no significant results were observed for other gene-environment interactions on either additive or multiplicative scale(Supplement Table 4 and 5).

4. Discussion

Here we conducted a case-control study to explore the role of three potentially functional variants in STAT4, rs7574865, rs897200, and rs1031507, in HCC susceptibility. This study suggested that the rs7574865 confers a decreased risk of HCC. Intriguingly, the rs897200 shows an interaction effect with alcohol drinking to modulate the risk of HCC.

STAT4 has attracted a lot of attention for its considerable functions in a variety of cancers and autoimmune diseases. In HCC development, STAT4 has been showed to act as cancerocidal-gene. Wang et al. found that downregulation of STAT4 could enhance the proliferation of liver L02 cells [19], consistent with the effect of STAT4 siRNA that promoted growth and suppressed apoptosis of HepG2 cells [20]. Data from STAT4 knockout mice suggested the role of STAT4 in protecting against acute T-cell hepatitis [21]. Furthermore, the level of STAT4 expression was lower in HCC tissues than that in noncancerous liver tissues [20]. Aside from HCC, cryptotanshinone, the STAT inhibitor, regulated cytotoxic CD4 ${}^{+}$ T cells and inhibiting breast tumor growth through upregulated Janus kinase 2 (JAK2) and STAT4 [22]. These abundant evidence demonstrated that STAT4 exerts an important suppressive effect on the development of HCC and other cancers.

In the present study, the TT genotype of rs7574865 yielded a decrease risk of HCC compared to the GG genotype, in accordance with the study in a meta-analysis that also uncovered the association of the rs7574865 with HCC susceptibility [23]. As the annotation by Haploreg V4.1 [14], the rs7574865 may alter the regulatory motif and subsequently affects the binding affinity of the transcription factors, Forkhead Box J2 (Foxj2) and Forkhead box protein 1(Foxp1). The ectopic expression of Foxj2 in HCC cell lines had been shown to inhibit cell migration and invasion [24], while Foxp1 involved in the progression of liver cirrhosis transforming to HCC [25]. More importantly, in Caucasian patients with chronic hepatitis B, the rs7574865 GG genotype conferred the lower levels of STAT4 in liver [26]. Taken together, the rs7574865 variant may contribute to the genetic susceptibility of HCC at least in part via regulating the STAT4 expression.

Notably, an additive interaction between STAT4 rs897200 and drinking was observed associated with HCC risk, although no disease-association solely with rs897200 was seen in this study, possibly due to underpower for the moderate effect of this individual variant. No previous study has examined the interaction between alcohol drinking and rs897200 in relation to HCC. Comprehensive data suggested drinking as an independently risk factors for HCC [3], consistent with our conclusion. The molecular mechanisms underlying the detrimental effect of alcohol on hepatocarcinogenesis involves alternations in expression of cytokine signaling pathway, in particular, changes in the immune system and in inflammation [27, 28]. Pathway analysis using DAVID and GeneGO Metacore tools showed that the most affected pathways in blood cells of alcohol dependent subjects were those related to JAK-STAT signaling [29]. Chronic exposure to alcohol has been further shown to down-regulation of both STAT proteins and important negative regulators of STAT function in vivo [29, 30]. Combined the theories retrieve from above studies, alcohol drinking and STAT4 make a concerted effect to exacerbation of HCC when these conditions coexist. Taken together, it is worth to note that the reducing alcohol consumption in society, especially individuals who carry the mutations of rs897200, will be beneficial in decreasing the risk of HCC.

While we characterized comprehensive analytical strategy to advance our understanding on the genetic etiology of HCC, there were some limitations should be taken into account in this study. Inherent selection bias cannot be completely excluded because this was a hospital-based design. Besides, some detailed unavailable information, including aflatoxin-contaminated food, intensity and duration of smoking and drinking status, are required to further identify. In addition, the present sample size provided insufficient power to detect all significance in interaction test.

In short, this study further highlighted the role of the STAT4 variant, rs7574865, in modulation of the susceptibility to HCC. The variant rs897200 of STAT4 may interplay with alcohol drinking to modify the risk of HCC. Further studies in large sample incorporating with functional experiments of STAT4 variants are warranted to verify these findings.

Supplementary data

The supplementary files are available to download from http://dx.doi.org/10.3233/CBM-203162.

sj-docx-1-cbm-10.3233_CBM-203162.docx - Supplemental material

Supplemental material, sj-docx-1-cbm-10.3233_CBM-203162.docx

Author contributions

Conception: Li Liu, Sidong Chen.

Interpretation or analysis of data: Xuan Zhong, Meihua Luo, Xinfeng Zhou.

Preparation of the manuscript: Xuan Zhong.

Revision for important intellectual content: Li Liu.

Supervision: Li Liu, Meihua Luo, Yanmei Wu, Xinfa Yu, Sidong Chen.

Footnotes

Acknowledgments

This work was supported by the Pearl River Nova Program of Guangzhou Science and Technology Project (201806010103).

Conflict of interest

No potential conflicts of interest were disclosed.

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Genetic variants in STAT4 and their interactions with environmental factors for the incidence of hepatocellular carcinoma

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

Table 1 The characteristics of cases with HCC and controls

2.1 Study populations

2.2 Genetic variants selection and genotyping

Table 2 Association analysis of three genetic variants in STAT4 and the risk of HCC

3. Results

3.1 Subject characteristics

3.2 Association between variants in STAT4 and HCC risk

Table 3 Gene-environment interaction analysis of rs897200 for the risk of HCC

4. Discussion

Supplementary data

sj-docx-1-cbm-10.3233_CBM-203162.docx - Supplemental material

Author contributions

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
The characteristics of cases with HCC and controls

Table 2
Association analysis of three genetic variants in STAT4 and the risk of HCC

Table 3
Gene-environment interaction analysis of rs897200 for the risk of HCC