The recognition of CMV as a medically important virus goes back to early 1930s when cytomegalic inclusion disease, a severe form of congenital CMV disease with an owl's eye appearance of inclusion bodies in cells from multiple organs of the infants, was observed. By 1970s, the pathogenic organ disease and HCMV link was well established, and HCMV-like viruses were isolated from other mammals. Due to the high social and medical cost of congenital CMV disease (i.e., sensorineural hearing loss and other severe neurological injury), vaccine development is a high public health priority (Plotkin, 2004; Arvin et al., 2004). HCMV continued to draw increasing medical attention as an opportunistic infection in immunocompromised individuals receiving organ transplants and the elderly. Moreover, persistent HCMV infection has been demonstrated to accelerate immunosenescence also known as human immune aging (Koch et al., 2006; Koch et al., 2007; Pawelec et al., 2009; Wistuba-Hamprecht et al., 2013; Pawelec, 2014). The onset of the HIV epidemic and the concomitant increase in AIDS-related CMV infections led to the development of several antiviral drugs (Plotkin, 2004; Griffiths and Boeckh, 2007; Kotton, 2013; Shin et al., 2014; Vora et al., 2018). However, currently there is no protective vaccination, and viral resistance against available antiviral drugs necessitates continuing research and investment in better understanding of CMV pathogenesis (Plotkin, 2002; Schleiss et al., 2006; Heineman, 2007; Griffiths and Boeckh, 2007; Plotkin and Boppana, 2018).

Most reviews in CMV literature focus on the viral and immune response aspects of the pathogenesis. However, host genetics of viral infection and pathogenesis can identify biological pathways that may lead to novel therapeutics. This review takes a different approach and aims to cover the current cumulative state of the knowledge in the host genetics of CMV pathogenesis in different risk groups. Different phenotypic outcomes of HCMV susceptibility are presented in the following sections. The details of genetic associations such as cohorts, odds ratios, P-values, and sample size are presented in **Table 1**. A summary figure of interactions between host genes and HCMV in different phenotypic outcomes based on literature reports is presented in **Figure 1**.

# HOST GENETICS OF HUMORAL IMMUNITY TO HCMV

HCMV immune human sera contain neutralizing antibodies against principal CMV envelope proteins (such as gB), tegument phosphoprotein pp150 (UL32), and nonstructural DNA binding phosphoprotein pp52 (UL44) (Landini, 1993). Humoral immunity to CMV can be protective against blood-borne spread of virus, transplacental transmission, and CMV acquisition and disease (Jonjic et al., 1994; Plotkin et al., 1994; Schoppel et al., 1998; Fields et al., 2001; Schleiss et al., 2004). There is differential response to CMV exposure, and not everyone exposed to HCMV develops a CMV-related disease, suggesting a possible role for host genetic variation in antibody response to HCMV.

Immunoglobulins, also known as antibodies, constitute a critical part of the humoral immune response by specifically recognizing and binding to particular antigens. Immunoglobulin G is the most common type of antibody in circulation. Variation in genes that code for immunoglobulin (Ig) GM (gamma marker) creates several alleles (also referred as allotypes), (i.e., GM 3 and GM 17) with different binding affinities to antigens such as HCMV glycoprotein B (gB). The effect of genetic variation in humoral immunity on susceptibility to HCMV disease has been suggested by the studies that focus on association between immunoglobulin (Ig) GM allotype variation and HCMV antibody response. Pandey et al. reported a significant effect of immunoglobulin GM genotypes on antibody responsiveness to HCMV glycoprotein B (gB) (Pandey, 2014a). The study showed significant differences in antibody response to HCMV between GM 3 and GM 17 alleles. HCMV codes for a Fc gamma receptor (FcgR)-like protein (coded by the HCMV *RL13* gene) that can bind to the anti-HCMV IgG antibody, thus reducing the number of free anti-HCMV antibodies in circulation, and giving survival advantage to the virus. The GM 3 allele has higher affinity to HCMV FcgR-like protein (through bipolar bridging) compared to the GM 17 allele, leaving lower concentration of free anti-HCMV gB antibodies circulating in the system. They also drew attention to B-cell-mediated antigen

CMV Pathogenesis Genetics

*(Continued)*

Frontiers in Genetics

 |

www.frontiersin.org

TABLE 1 | Continued

*(Continued)*

CMV Pathogenesis Genetics

*(Continued)*

CMV Pathogenesis Genetics

TABLE 1 | Continued

*(Continued)*

CMV Pathogenesis Genetics

*CVD-Finns: Cardiovascular risks in young Finns study.*

Sezgin et al. CMV Pathogenesis Genetics

processing/presentation pathway as an alternative mechanism underlying GM allotypes' differential responsiveness to HCMV gB. One of the strategies that HCMV has evolved for evading host immunosurveillance involves generating proteins with similar functional properties to the Fcγ receptor for IgG (FcγR). FcγR interferes with the anti-HCMV IgG antibody's binding to the virus, thus giving survival advantage to HCMV against antibody-dependent cellular cytotoxicity, antibody-dependent cellular phagocytosis, and antibody-dependent complementdependent cytotoxicity (Atalay et al., 2002; Namboodiri and Pandey, 2011).

A major issue in genetic epidemiology studies of antibody variation is that most of the genetic variation is ethnic and population specific. For example, GM 3 is rare among people of African descent. Moreover, the genetic background influencing overall immune response will be different between races and populations. Therefore replication and translation of results from one study to another is not always possible. Ethnic and population-specific genetic variation can also lead to hidden population stratification even in the same country, which is major factor confounding the genetic association results. Given the complex genetic nature of humoral immune response to HCMV, much larger studies with more balanced case and control groups are needed to test the GM associations with HCMV response.

### HOST GENETICS OF HCMV IN CANCERS

HCMV is not considered an oncogenic virus; however, HCMV viral DNA, RNA, and protein have been frequently found in neoplastic tissues including gliomas, breast cancer, and neuroblastoma (Cobbs et al., 2002; Harkins et al., 2010; Cobbs, 2011; Taher et al., 2013; Wolmer-Solberg et al., 2013). Moreover, HCMV infection leads to changes in cell physiology, tumor microenvironment, inhibition of apoptosis, and evasion from immune detection that are characteristics of cancer development (Hanahan and Weinberg, 2011). Not all HCMVinfected individuals develop cancers, suggesting that host genetics of HCMV response may influence HCMV-mediated cancer risk. Indeed, studies with glioma patient cohorts showed a modulating effect of GM alleles on the risk of gliomas, where the IgGM 3 homozygotes were over twice, and the GM 3/17 heterozygotes were over three times as likely to develop glioma (Pandey, 2014a; Pandey et al., 2014b). The magnitude of antibody responsiveness to HCMV glycoprotein B (gB) has also been implicated in breast cancer susceptibility. The GM 3 allele of IgG1 was reported to be significantly associated with increased susceptibility to breast cancer in Caucasian subjects from Brazil; however, the association was not significant in other population groups (Pandey et al., 2012). In a follow-up study, breast cancerfree individuals had significantly higher levels of anti-gB IgG antibodies than patients with breast cancer; however, there was interindividual and interethnic variability in the magnitude of antibody response, and interactions with other genes of the immune system were apparent (Pandey et al., 2016). Functional studies indicate that the binding of HCMV FcgR-like protein to

TABLE 1 |

Continued

includes results from solid organ and stem cell transplantation studies. "HCMV disease in HIV infection" category includes results from HIV-infected patients.

GM 17 allele expressing IgG antibodies was significantly higher than GM 3 expressing antibodies, providing possible mechanistic insights for increased breast cancer risk in some HCMV-infected patients (Pandey et al., 2017).

Significant association of rare GM genotypes with neuroblastoma, a rare extracranial solid tumor, has been reported (Morell et al., 1977), but the mechanism underlying this association is still not clear. These uncommon GM genotypes include the GM 3, the allele with high affinity to HCMV TRL11/IRL11-encoded FcγR. Reports documenting early and late HCMV protein expression in primary neuroblastomas and neuroblastoma xenografts suggest either infection and transformation of neuroblastoma progenitor cells or direct infection of neuroblastoma cells and disturbance of intracellular pathways leading to neoplasms (Wolmer-Solberg et al., 2013). The mechanisms underlying the increased HCMV associated cancer risk with the GM 3 allele may also be involved in neuroblastoma cases as well.

Independent cohort and functional studies make a case for significant influence of host genetic variation in humoral immunity on response to HCMV disease (**Table 1**, **Figure 1**). However, increased cancer risk associated with increased HCMV susceptibility is still a hypothesis to be tested. Clearly, larger multi-ethnic, multi-cohort host genetic, and comprehensive functional studies are needed to uncover the host genetics of humoral immunity to HCMV and HCMV associated cancers.

### HOST GENETICS OF HCMV DISEASE IN TRANSPLANT PATIENTS

HCMV is a common opportunistic infection among immunocompromised individuals. Individuals are maximally immunocompromised due to use of immunosuppressants during solid organ or HSCT procedures and thus are prone to HCMV reactivation (of the latent virus), primary infection, and reinfection. HCMV infections can cause severe morbidity and transplant failure, which frequently results in extended hospital stay and substantially higher cost of care (Falagas et al., 1997; Kim et al., 2000; Ljungman et al., 2002; Ramanan and Razonable, 2013). Transplantations from a seropositive individual to a seronegative individual (R-/D+) pose the greatest risk for HCMV-associated disease in the transplant recipient patients (Cope et al., 1997; Lowance et al., 1999). Therefore, determining the serologic status of the recipient and donor is important in assessing the risk of HCMV-associated disease. However, it can be hard to find serostatus matched donor and recipients, and even serostatus matching does not completely eliminate HCMVassociated morbidity.

Coordinated innate and adaptive immune response is crucial for control of HCMV infection in immunocompromised transplant recipients. Whereas innate interferon (IFN) and natural killer (NK) cell responses are important in immediate control of CMV infection, adaptive T cell immune responses are important in both active infection and reactivation control phases (Crough and Khanna, 2009; Zelini et al., 2010; Reddehase, 2013; Muntasell et al., 2013). To reduce the number of HCMV-associated adverse outcomes and better identify transplant patients for HCMV prophylaxis, several candidate innate and adaptive immune-related gene studies have been conducted (**Table 1**).

### Solid Transplantation Studies

A family of transmembrane proteins, the Toll-like receptors (TLRs), are part of the innate immune system and play crucial roles in the activation of the immune system by regulating the production of antiviral peptides and inflammatory cytokines against viral replication. The detection of CMV envelope glycoproteins B (gB) and H (gH) by TLR2 leads to nuclear factor-kB (NF-kB) activation and cytokine secretion against CMV (Boehme et al., 2006). Clinical studies showed that polymorphisms in TLR-2 (Kijpittayarit et al., 2007; Kang et al., 2012), TLR-4, TLR-9 (Fernandez-Ruiz et al., 2015), and mannose binding lectin (Cervera et al., 2007; Manuel et al., 2007) can be associated with increased risk of HCMV infection and disease after transplantation.

Genetic variants of MICA (major histocompatibility complex class I chain-related protein A) and its activating receptor NKG2D (natural killer group 2 member D) receptor may be associated with HCMV disease risk among kidney transplant patients. A candidate gene association study identified a regulatory MICA variant (rs2596538) in the kidney donors that can be a protective prognostic determinant for CMV disease. This functional variant was able to predict the development of CMV infection and disease during the first year after kidney transplantation (**Table 1**: Rohn et al., 2018). Membrane-associated molecule PD-1 (programmed death-1) regulates immune responses by inhibiting T cell receptor signaling, cytokine production in effector T cells, and expression on regulatory T cells (Sharpe et al., 2007; Franceschini et al., 2009). PD-1's expression also correlates with CMV viremia in transplant patients (Sester et al., 2008). An upstream regulatory region variant (rs11568821) that impairs the function of PD-1 (also called PD-1.3) has been investigated in HCMV infection in kidney and lung graft recipients. The PD-1.3 variant has been shown to be associated with higher risk of HCMV infection (Hoffmann et al., 2010) and lung allograft survival in recipients from HCMV-positive donors (Forconi et al., 2017). Dendritic cell-specific ICAM 3-grabbing nonintegrin (DC-SIGN) variants were also reported to be associated with higher incidence of HCMV infection in kidney transplant patients (Fernandez-Ruiz et al., 2015).

Cytokines, signaling molecules of the immune system, regulate pro-inflammatory and anti-inflammatory responses, and play important roles in antiviral response. Cytokines also play a role in HCMV infection, reactivation, and disease (Asanuma et al., 1995; Zeevi et al., 1999; Faist et al., 2010; van de Berg et al., 2010; Biron and Tarrio, 2015; Nabekura and Lanier, 2016). Studies of functional gene polymorphisms in pro-inflammatory and antiinflammatory cytokines with HCMV disease identified IFNG (interferon-gamma) +874 A/T polymorphism as a risk factor for HCMV disease in kidney and lung transplant patients, where the +874 A allele, a low IFNG producer (reduced gene expression), is associated with increased risk for HCMV infection and disease after organ transplantation (Mitsani et al., 2011; Vu et al., 2014). In a Finnish renal transplant cohort, the donor interleukin-10 (IL-10) gene polymorphism −1082AA was observed to influence HCMV infection risk. Recipient IL-10, IL-6, and IFNG polymorphisms also show significant associations with HCMV reactivation and disease risk (Alakulppi et al., 2006). A possible association between IL-12p40 gene polymorphisms in the recipient and high risk of HCMV infection was also reported after kidney transplantation (Hoffmann et al., 2008).

Type III interferon, also called interferon lambda (INFL3 or formerly IL-28B), has gained much attention as an important viral response element in recent years (Kotenko, 2011; Hayes et al., 2012). In a cohort of solid organ transplant patients from Alberta, a functional single nucleotide polymorphism (SNP) (rs8099917) associated with lower INFL3 (IL-28B) expression during CMV infection, but higher IFN-stimulated gene expression showed a protective effect against CMV replication (Egli et al., 2014). A follow-up Swiss Transplant Cohort study compared the cumulative incidence of CMV replication between patients with different TT/-G (rs368234815) genotype in the CpG region upstream of IFNL3. Patients with the –G/–G genotype had higher cumulative incidence of CMV replication. The study suggest that IFNL3 TT/-G (rs368234815) variant can be a CMV replication controller, particularly in patients not receiving antiviral prophylaxis (Manuel et al., 2015). Fernandez-Ruiz et al. (2015) also reported a lower incidence of HCMV infections among kidney transplant patients with IL28B (IFNL3) rs12979860-T allele.

### Hematopoietic Transplantation Studies

Although still few in number, host genetics of HCMV susceptibility among HSCT cases have also been investigated (**Table 1**). Similar to solid organ transplant studies, several candidate innate and adaptive immunity genes have been examined. Results from solid organ transplantation studies stimulated cytokine and interferon research in HCMV disease in stem cell transplant settings. In a comprehensive immunogenetic study, allogeneic stem cell transplant patients with HCMV reactivation (DNAemia), patients with HCMV disease, and patients without HCMV reactivation were examined (Loeffler et al., 2006). Polymorphisms in the CCR5, IL-10, and MCP1 were observed to contribute to HCMV reactivation and disease after allogeneic stem cell transplantation (Loeffler et al., 2006; Corrales et al., 2015). In a follow-up study, this research group extended their investigation and observed a significant association between promoter region variants, which influenced the expression levels of DC-SIGN on dendritic cells, and increased risk of development of HCMV reactivation and disease (Mezger et al., 2008). Protective effects of the INFL3 rs12979860 C/T polymorphism against CMV infection (Bravo et al., 2014; Corrales et al., 2017) and INFL3 rs12979860 IFNL4 rs368234815 compound genotype against HCMV reactivation (Annibali et al., 2018) in the allogeneic stem cell transplant setting were also reported. Killer immunoglobulin-like receptors (KIR) are cell surface receptors found on NK and certain T cells. The activating and inhibitory signals are transmitted to NK cells through KIR proteins, by which NK cells respond quickly to infections. In a Chinese cohort HLA-matched HSCT patients, patients receiving HSCT from donors with heterozygote 2DS4+/1D+ KIR haplotype showed at least 20% less CMV reactivation compared to donors with other haplotypes (Wu et al., 2016). This observation suggests that donor KIR haplotype should be evaluated for HLA-matched HSCT cases. More recently functional genetic variants in *FOXP3* (Piao et al., 2016), *STAT4* (Wun et al., 2017), and *IL-7*(Kielsen et al., 2018) are reported to influence HCMV infection after HSCT in independent cohort studies.

Host genetics of HCMV disease in transplant patients provide hints towards promising genetic markers to predict CMV viremia (**Table 1**, **Figure 1**). However, these studies are complicated due to several factors, including donor and recipient serostatus, type and dose of immunosuppressive drugs used, and ethnicity of the patient cohort. These factors also lead to significant heterogeneity among the studies confounding the efficacy of a meta-analysis of the individual studies to reach a consensus on securely identified markers and causal variants. The transplant community is still far from developing well accepted genetic markers for personalized CMV approaches (such as decisions on prophylactic and preemptive therapies) to be used in the clinic.

## HOST GENETICS OF HCMV DISEASE IN HIV-INFECTED PATIENTS

Patients with HIV infection are another group of immunocompromised individuals that are at high risk for CMV disease. Before the use of ART (antiretroviral therapy), up to 40% of adults with AIDS developed CMV disease (Gallant et al., 1992). Although the incidence of CMV infection has declined dramatically, new cases continue to occur (Sezgin et al., 2018). Among HIV-infected patients the risk of CMV disease is linked to CD4+ T-cell counts. The most common CMV disease among patients with uncontrolled HIV infection is CMV-Retinitis that may develop when CD4+ T-cell counts drop below 50–100 CD4+ cells/µl (Jabs, 1995; Dunn and Jabs, 1995; Heiden et al., 2007). While some patients with low CD4+ T-cell counts remain asymptomatic, others can progress to CMV disease rather quickly. Host genetic variants in genes involved in regulation of innate and adaptive immune responses may have a role in this differential susceptibility to CMV among HIV-infected patients as they have in other immunocompromised groups such as transplant patients.

A comprehensive candidate gene study on host genetics of CMV-Retinitis among HIV-infected patients was conducted in Longitudinal Studies of Ocular Complications of AIDS (LSOCA) cohort (**Table 1**). The study showed that human interleukin-10 receptor (IL-10R1) variants that potentially interfere with IL-10 binding and signal transduction can influence CMV-Retinitis occurrence in European Americans (Sezgin et al., 2010). The same study also suggested a possible role of IL-10 variants on CMV-Retinitis risk among African Americans (Sezgin et al., 2010). In a follow-up study of the same cohort, cytokine and cytokine receptor [*CCR5* and stromal derived factor (*SDF-1*)] genetic variants have been observed to influence retinitis progression (Sezgin et al., 2011). In a different cohort study, *TNF* polymorphisms were also linked to susceptibility to CMV retinitis in white patients, though with rather small sample size (Deghaide et al., 2009). In a large Swiss HIV Cohort Study, the effect of *IFNL3* TT/-G substitution, the variant that increased susceptibility to CMV replication in transplant patients (Manuel et al., 2015), was also shown to be associated with higher risk of CMV retinitis (Bibert et al., 2014).

Although subject to complex confounding factors and high false discovery rates, host candidate gene studies of immunocompromised groups cumulatively indicate possible effects of innate and adaptive immune gene variants on CMV disease (**Table 1**, **Figure 1**). More studies should be designed to replicate and validate these results.

# HOST GENETICS OF VERTICAL HCMV TRANSMISSION

Vertical transmission of HCMV from mother to fetus or newborn is common and plays an important role in maintaining infection in the population (Stagno et al., 1982a; Whitley, 2004). Prenatal infection rates are highest in low income countries or low socioeconomic populations, where risk of maternal seropositivity is also high (Stagno et al., 1982b; Stagno et al., 1982c). Recurrent and primary HCMV infection during pregnancy can cause congenital infection of the newborn and may lead to severe clinical complications such as hearing defects, birth defects, and irreversible neurodevelopmental sequelae (Boppana et al., 1992; Boppana et al., 1999; Gaytant et al., 2002).

Host candidate genetic studies of congenital HCMV infection mainly have focused on innate immune system, such as TLRs and Mannan-binding lectins, and cytokine genes (**Table 1**, **Figure 1**). In children with congenital HCMV disease, the TLR2 1350 T > C variant (rs3804100) was reported to be associated with the infection, although no relationship was established with the course of infection (HCMV disease) (Taniguchi et al., 2013). Eldar-Yedidia et al. (2017) reported a protective effect of TLR2 rs1898830 –GG genotype against HCMV transmission to fetus. A follow-up study investigating the influence of Arg677Trp (rs121917864, 2029 C > T) and Arg753Gln (rs5743708) variants in the TLR2, and Asp299Gly variant in the TLR4 on the risk of CMV infection in infants and adults found that heterozygosity for the TLR2 Arg677Trp was significantly associated with a lower risk of CMV infection in adults but not in infants. The same study also reported TLR4 Asp299Gly association with lower viremia in the adults (Jablonska et al., 2014). In a study of HCMV-infected fetuses and neonates, and controls, Wujcicka et al. (2017a) reported TLR2 2258 G > A SNP (rs5743708) to be associated with increased risk of congenital HCMV infection, but no effect of TLR2 1350 T > C and 2029 C > T variants on HCMV risk was observed. The same group in an independent study evaluated the role of TLR2, TLR4, and TLR9 variants in HCMV infection among pregnant women. Only the TLR9 2848 G > A (rs352140) variant was reported to be associated with HCMV infection risk in pregnant women (Wujcicka et al., 2017b). Increased HCMV infection risk in infants with TLR9 -1486 T > C and TLR9 2848 C > T variants is also reported (Paradowska et al., 2016).

Another important player in the innate immune system is the Mannan-binding lectin (MBL), a pattern recognition molecule and a first line defense antimicrobial factor (Kilpatrick, 2002). Mutations in the promoter region and first exon of *MBL2* were reported to be associated with lower serum MBL concentrations (Madsen et al., 1995). In a Polish study, MBL2 functional gene polymorphisms that influence serum MBL concentrations were examined in prenatal and perinatal CMV infections (Szala et al., 2011). However, no significant influence on susceptibility to prenatal or perinatal HCMV infections was observed (Szala et al., 2011).

HCMV infection during pregnancy can affect the cytokine profile within a HCMV-infected placenta and shift the cytokine expression toward a proinflammatory state with implications for adverse pregnancy outcomes (Hamilton et al., 2012; Scott et al., 2012). As host genetic variants in cytokine-related genes were shown to influence susceptibility to HCMV infection and disease in transplant patients and patients with AIDS, several congenital infection studies also investigated the association of cytokine and cytokine receptor variants on HCMV susceptibility. Kasztelewicz et al. (2017) compared the allelic distribution of 11 candidate SNPs in eight genes (TNF rs1799964 and rs1800629, TNFRSF1A rs4149570, IL-1B rs16944 and rs1143634, IL-10 rs1800896, IL-10RA rs4252279, IL-12B rs3212227, CCL2 rs1024611 and rs13900, CCR5 rs333) between a group of infants (n = 72) with confirmed intrauterine CMV infection and 398 uninfected controls. IL-1B (rs16944) and TNF (rs1799964) variants were significantly associated with intrauterine HCMV infection. Moreover, they identified CCL2 (rs13900) as a genetic risk factor for hearing loss at birth and at 6 months of age (Kasztelewicz et al., 2017). Wujcicka et al. examined the effects of fetal and maternal IL-1A, IL-1B, IL-6, IL-12B, and TNFA gene variants on HCMV infection and disease in neonates and fetuses in two independent Polish cohort studies. In one study, they reported that IL-1A and IL-1B variants increased the risk of congenital HCMV infection in neonates and fetuses, as well as the onset of disease-related symptoms (Wujcicka et al., 2017c). The other study of pregnant women also reported possible effects of IL-1A, IL-1B, and IL-6 on the occurrence and development of HCMV infection in the neonate (Wujcicka et al., 2017d).

Deciphering the contribution of hot genetics to HCMV vertical transmission and related disease outcomes may be the hardest of all HCMV-related disease studies. Firstly, the susceptibility of the pregnant mother to HCMV needs to be considered, where the immune response will be modified due to pregnancy further complicating the interaction between the host and HCMV. Secondly, if the mother cannot clear the infection, and HCMV finds its way to fetus, then the immune response by the infant, which is rather immature and still developing, will be involved with a genetic make-up different than that of the mother. Aforementioned reports should be considered as early attempts of a rather challenging research agenda. Highthroughput genetic and immune profiling methods with much larger cohorts are necessary to understand the genetic and nongenetic factors involved in HCMV vertical transmission.

# GWAS OF HCMV INFECTION

Genome-wide association studies (GWASs) have made significant contributions for discovering genetic factors underlying complex phenotypes and diseases. Unlike traditional hypothesis-driven candidate gene studies, where only a few candidate genes are targeted, in GWAS all human genes become potential candidates for the phenotype of interest. Therefore, GWAS approach can discover genes and their variants that may look irrelevant to the phenotype of interest, which in return can lead to discovery of novel biological pathways involved in development of this phenotype.

The first GWAS was conducted to identify genetic polymorphisms associated with the susceptibility to HCMV and strength of anti-HCMV immunoglobulin G (IgG) response to CMV infection (Kuparinen et al., 2012). The study included 1486 anti-CMV IgG seropositive and 648 seronegative individuals genotyped on an Illumina BeadChip containing 670,000 probes. Although no strong genetic components were observed, the study identified 10 new candidate loci that showed suggestive association with anti-CMV IgG titer (**Table 1**). Annotated genes among these loci suggested a possible role for microtubule network in anti-CMV antibody response (Kuparinen et al., 2012). Another GWAS, aiming to localize the loci influencing serological phenotypes to common viral infections, found suggestive evidence of association for modifying IgG antibody response to HCMV (anti-CMV) on chromosome 14 (Rubicz et al., 2015). A retinol metabolism gene, *DHRS4*, near the associated SNP, was proposed to be a candidate for further evaluation. These two studies show that GWAS approach can be productive in HCMV field; however, one also needs to consider the fact that there was no overlap of identified genes between the two GWASs, although the phenotypes were similar. Curiously, none of the candidate innate and adaptive immune genes examined so far were top hits in these GWASs.

## Challenge and Future Directions

Clinical management of CMV infection is particularly challenging due to the arsenal of host immune evasion strategies encoded by its large genome and its complex interactions with its human host. As we show in this review, with a few exceptions, most of the genetic loci identified to date have not been replicated or validated in sufficiently powered cohort studies, suggesting that only a small fraction of variance in host response is likely due to genetic variation. To address the role of host genetic variation in immune response to HCMV and CMV disease, large prospective studies and genomewide approaches are required to securely identify causal variants involved in immune response and pathophysiological mechanisms leading to CMV disease.

# AUTHOR CONTRIBUTIONS

ES designed the study, conducted literature research, and wrote and edited the manuscript. PA and CW wrote and edited the manuscript.

### REFERENCES

## FUNDING

This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under contract HHSN26120080001E. This research was supported in part by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

transplant infections. *Transplantation* 83 (11), 1493–1500. doi: 10.1097/01. tp.0000264999.71318.2b

after kidney transplantation. *Transplantation* 83 (3), 359–362. doi: 10.1097/01. tp.0000251721.90688.c2

virus. *Am. J. Ophthalmol.* 151 (6), 999–1006 e1004. doi: 10.1016/j. ajo.2010.11.029

predominantly in individuals infected with Cytomegalovirus. *Immun. Ageing* 10 (1), 26. doi: 10.1186/1742-4933-10-26

**Conflict of Interest Statement:** PA and CW are employees of Leidos Biomedical Research, Inc., and declare no competing interest.

The remaining authors declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Copyright © 2019 Sezgin, An and Winkler. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Host Genetic Determinants of Hepatitis B Virus Infection

*Zhenhua Zhang1,2, Changtai Wang3, Zhongping Liu1, Guizhou Zou1, Jun Li2 and Mengji Lu4\**

*1 Department of Infectious Diseases, the Second Affiliated Hospital of Anhui Medical University, Hefei, China, 2 College of Pharmacy, Anhui Medical University, Hefei, China, 3 Department of Infectious Diseases, the Affiliated Anqing Hospital of Anhui Medical University, Anqing, China, 4 Institute of Virology, University Hospital of Duisburg-Essen, Essen, Germany*

Chronic hepatitis B virus (HBV) infection is still a major health problem worldwide. Recently, a great number of genetic studies based on single nucleotide polymorphisms (SNPs) and genome-wide association studies have been performed to search for host determinants of the development of chronic HBV infection, clinical outcomes, therapeutic efficacy, and responses to hepatitis B vaccines, with a focus on human leukocyte antigens (HLA), cytokine genes, and toll-like receptors. In addition to SNPs, gene insertions/deletions and copy number variants are associated with infection. However, conflicting results have been obtained. In the present review, we summarize the current state of research on host genetic factors and chronic HBV infection, its clinical type, therapies, and hepatitis B vaccine responses and classify published results according to their reliability. The potential roles of host genetic determinants of chronic HBV infection identified in these studies and their clinical significance are discussed. In particular, HLAs were relevant for HBV infection and pathogenesis. Finally, we highlight the need for additional studies with large sample sizes, well-matched study designs, appropriate statistical methods, and validation in multiple populations to improve the treatment of HBV infection.

Keywords: hepatitis B virus, genetic determinants, human leukocyte antigen, susceptibility gene, single nucleotide polymorphism, genome-wide association study

## INTRODUCTION

With 292 million people infected and a global prevalence of 3.9%, hepatitis B virus (HBV) infection is still a major global public health problem (Polaris Observatory Collaborators, 2018). The outcomes of HBV infection are highly diverse, including acute hepatitis, self-limiting recovery, chronic hepatitis, cirrhosis, liver cancer, and liver failure (**Figure 1**) (European Association For The Study Of The Liver, 2017). In the natural history of HBV infection, there is substantial variation in the course of disease development and clinical outcomes depending on the transmission pattern, timing of infection, sex, immune status, host genetic factors, and underlying diseases in infected individuals. The disease outcome is related to viral, environmental, and host factors (Ganem and Prince, 2004; Rehermann and Bertoletti, 2015). With respect to host factors, in addition to age, gender, alcohol, obesity, diabetes, and renal failure, host gene variants may also affect the clinical course of HBV infection (Laskus et al., 1992; He et al., 2006; Thursz et al., 2011; Yano et al., 2013; Matsuura et al., 2016). Since the implementation of the Human Genome Project, great progress has been made in genetic and disease-related research, providing a basis for advances in precision medicine. Host genetic polymorphisms mainly include single nucleotide polymorphisms (SNPs),

#### *Edited by:*

*Cheryl Ann Winkler, Frederick National Laboratory for Cancer Research (NIH), United States*

#### *Reviewed by:*

*Michael Scheurer, Baylor College of Medicine, United States Guangwen Cao, Second Military Medical University, China*

> *\*Correspondence: Mengji Lu<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Applied Genetic Epidemiology, a section of the journal Frontiers in Genetics*

*Received: 07 November 2018 Accepted: 03 July 2019 Published: 13 August 2019*

#### *Citation:*

*Zhang Z, Wang C, Liu Z, Zou G, Li J and Lu M (2019) Host Genetic Determinants of Hepatitis B Virus Infection. Front. Genet. 10:696. doi: 10.3389/fgene.2019.00696*

progression are variable, indicating that host genetic determinants play an important role in HBV infection.

insertions/deletions, and copy number variations (CNVs). Owing to technological limitations, current research mainly focuses on the relationships between SNPs and susceptibility to diseases.

Two approaches are frequently used to screen susceptibility genes for HBV-related diseases and outcomes. First, genomewide association study (GWAS) have become a common tool for genetic association research focused on complex diseases (Hardy and Singleton, 2009), including HBV infection. In the first stage of GWAS, patient samples are typically used to screen a large number of candidate SNP loci using TaqMan probes, SNPstream genotyping technology, SNaPshot genotyping, SNP chips, and other methods, with several rounds of validation to finally identify SNPs. Second, the traditional approach is the selection of candidate genes predicted to play a role in HBV-related diseases or treatment responses based on theory and previous analyses, followed by verification by comparisons of SNP genotype frequencies in patient and control groups.

 Hepatitis B vaccines are widely used and effective for the prevention of new HBV infections. However, the overall success rate of hepatitis B vaccination is about 90% (Bruce et al., 2016; Hu et al., 2018). The outcome of HBV infection can vary dramatically, depending on both host and viral factors. A major part of patients do not experience clinically relevant symptoms during the acute infection phase while others have acute illness with symptoms that last several weeks. Without any intervention, about 95% of intrauterine or perinatal HBV infections but only about 5% in adults develop into chronic infections (Stevens et al., 1975; Wright and Lau, 1993; Petrova and Kamburov, 2010). HBV persistence is a major risk for developing chronic hepatitis B, cirrhosis, hepatocellular carcinoma, or acute liver failure (Wright and Lau, 1993; Zhang et al., 2013a). A small number of patients develop occult HBV infection (OBI) without detectable serum HBsAg but HBV DNA in the serum or liver (Torbenson and Thomas, 2002; Raimondo et al., 2008; Raimondo et al., 2019; Seed et al., 2019). Interferon-alpha (IFN-α) and nucleos(t)ide analogs (NUCs) have been approved and are widely used for the treatment of chronic hepatitis B (European Association For The Study Of The Liver, 2017). Regimens such as antiviral treatment with tenofovir and entecavir provide results in viral suppression in around 95% of patients, have limited associated resistance, and prevent liver disease progression, cirrhosis, and HCC. However, these treatments do not regularly achieve clinical cure or HBsAg clearance and the incidence of cirrhosis or HCC is still significantly higher in treated patients than those without HBV infection (**Figure 1**). Many studies have shown that host genetic polymorphisms may influence HBV infection, including hepatitis B vaccine responses, chronic HBV infection (CHI), intrauterine transmission (IT), OBI, liver cirrhosis (LC), hepatocellular carcinoma (HCC), liver transplantation (LT), and the antiviral efficacy of IFNs and NUCs (Kamatani et al., 2009; Davila et al., 2010; Li et al., 2012b; Chang et al., 2014). These studies have demonstrated that host genetics play an important role in HBV infection and pathogenesis (**Figure 2**). Yet, many contradictory or ambiguous findings have been reported.

In this review, we summarize the current state of research on the role of host genetic determinants of CHI, its clinical type, therapeutic responses, and responses to hepatitis B vaccines (**Tables S2–7**). More than 500 publications varying in quality have focused on this topic. Thus, we assessed the reliability of these studies according to the sample size, type of technology, and analysis methods. Note that for great many genes related to HBI or vaccine efficacy, only a single study was available. For intrauterine infections, OBI, drug efficacy, and other factors, all published papers were included owing to the small sample size. We also considered whether there are valid contradictions among studies. We classified studies into three categories: very relevant (I), possibly relevant (II), and unable to confirm (III) (**Table 1**; **Table S1**), as a guide for readers. The topic of host genetics and end-stage liver diseases, including HCC, is reviewed by An et al. (An et al., 2018) in this special issue and therefore is not included in our review.

# CHRONIC HBV INFECTION

Early epidemiological data showed that chronic HBV infection is very frequently established in infants born to HBV carrier mothers or in young children (Stevens et al., 1975; Li et al., 2015) and shows a strong gender disparity with significantly higher susceptibility of male patients (Lee et al., 1999; Su et al., 2007; Liaw et al., 2009; Wang et al., 2015). Adequate

TABLE 1 | Classification of host genetic determinants associated with hepatitis B virus (HBV)-related liver diseases and responses to HBV vaccines.

*1. The total sample size refers to the sample size of a single study, including the experimental and control group.*

*2. The study groups of intrauterine infection, OBI, IFN-*α*, and NUCs were changed to 200 and 500 (500 and 1,000 for CHI and HBV vaccine groups, respectively), and the other assessment criteria remain the same.*

host immune responses to HBV are essential for sustained viral control (Bertoletti and Gehring, 2006). HBV control is associated with vigorous, multi-specific T cell responses in the host. In chimpanzees, T cell depletion prevents HBV clearance (Thimme et al., 2003; Asabe et al., 2009; Hoogeveen et al., 2018), demonstrating the essential role of cellular immunity in HBV control. Chronic HBV infection is associated with impaired immune responses (Guidotti et al., 2015; Lebosse et al., 2017). Thus, great efforts have been made to identify associations between host immunogenetics and chronic HBV infection. A number of host genetic variants, such as mutations in human leukocyte antigens (HLAs), cytokine and chemokine genes, tolllike receptor (TLRs), microRNAs, vitamin D–related genes, and HBV receptor sodium taurocholate cotransporting polypeptide (NTCP), have been found to influence the outcome of HBV infection (**Table 2**; **Tables S1**, **S2**). The SNPs loci of genes very relevant or possibly relevant with chronic HBV infection are listed in **Table 2**. Other SNPs loci of genes that are still unable to confirm are listed in **Tables S1** and **S2**.

HLA is the human major histocompatibility complex (MHC) and a central element of antiviral immune defense (Shiina et al., 2009). HLA genes are classified as class I (HLA-A, B, C, E, F, and G) and II (HLA-DP, DQ, DR, DM, and DO) (Koller et al., 1989; van Lith et al., 2010). When a pathogen enters the body, it is engulfed by antigen-presenting cells (APCs) and the pathogen proteins are digested into small pieces and loaded onto HLA antigens. They are then displayed by APCs to T cells, which produce a variety of effector molecules to eliminate the pathogen. Therefore, HLAs can affect the outcome of infectious diseases (Singh et al., 2007; Goulder and Walker, 2012; Wang et al., 2016). Genetic polymorphisms, especially in HLA class II genes, are significantly associated with HBV infection and pathogenesis according to many studies (Kamatani et al., 2009; Zhang et al., 2014b; He et al., 2015; Wasityastuti et al., 2016; Trinks et al., 2017). Kamatani et al. (Kamatani et al., 2009) performed a GWAS of chronic HBV infection using 786 cases and 2,201 HBsAg seronegative controls in the Japanese population, followed by a replication study of three additional Japanese and Thai cohorts consisting of 1,300 cases and 2,100 controls. HLA-DPA1 rs3077 and HLA-DPB1 rs9277535 were significantly associated with chronic HBV infection in the Asian population (combined OR [95% CI] = 0.56 [0.51–0.61], *P* = 2.31 × 10–38; OR [95% CI] = 0.57 [0.52–0.62], *P* = 6.34 × 10–39, respectively). They also identified four associated haplotypes: HLA-DPA1\*0202-DPB1\*0501 and HLA-DPA1\*0202-DPB1\*0301 were associated with susceptibility to chronic hepatitis B and HLA-DPA1\*0103-DPB1\*0402 and HLA-DPA1\*0103- DPB1\*0401 showed a protective effect. Several GWAS of Asian populations have also shown that SNPs in HLA regions, such as HLA-DP (rs9277535, rs3077, rs9366816, and rs9277542), HLA-DQ (rs2856718, rs7453920, rs9276370, rs7756516, and rs7453920), HLA-DPB1 (positions 84–87), HLA-C (Leu-15, rs3130542, and rs2853953), HLA-DRB1\*13, HLA-J (rs400488), and HLA-DOA (rs378352), are associated with chronic HBV infection (Mbarek et al., 2011; Nishida et al., 2012; Hu et al., 2013; Kim et al., 2013; Chang et al., 2014; Jiang et al., 2015; Zhu et al., 2016b). Many studies have provided evidence based on case–control samples and conventional PCR-based detection methods that HLA molecules may be crucial determinants of the outcomes of HBV infection in Asian, European, African-American, Saudi Arabian, and Caucasian populations (Thomas et al., 2012; Al-Qahtani et al., 2014; Trinks et al., 2017). However, some studies have reported contradictory results. A study of the Chinese Zhuang population found no association between HLA-DPA1 rs3077 and chronic HBV infection (Wang et al., 2011). Akgöllü et al. (Akgöllü et al., 2017) suggested that HLA-DP rs3077 is not associated with HBV infection in the Turkish population. Vermehren et al. (Vermehren et al., 2012) failed to confirm an association of HLA-DPB1 rs9277535 with hepatitis B in Caucasians. A comprehensive meta-analysis suggested that HLA-DP/DQ (rs3077, rs9277535, rs9275572, rs9275319, rs2856718, and rs7453920) is associated with susceptibility to HBV or the clearance of HBV infection (Zhang et al., 2013e; Yu et al., 2015; Xu et al., 2017b; Xu et al., 2018). A meta-analysis by Huang et al. (Huang et al., 2016) suggested that HLA-DQB1\*0201, DQB1\*0301, and DQB1\*0502 are associated with an increased risk of CHB (chronic hepatitis B), while HLA-DQB1\*0303 and DQB1\*0604 are associated with a decreased risk of CHB.

#### TABLE 2 | Host genetic factors associated with chronic HBV infection.

*(Continued)*

#### TABLE 2 | Contiued

#### *Haplotypes*

*1G-A-G-A-T-T, rs9277535-rs10484569-rs3128917-rs2281388-rs3117222-rs9380343; 2G-G-G-G-T-C, rs9277535-rs10484569-rs3128917-rs2281388-rs3117222-rs9380343; 3A-A, rs3077-rs9277535; 4A-A, rs2395309-rs9277535; 5T-A-T, rs3077-rs9277378-rs3128917; 6C-A-T, rs3077-rs9277378-rs3128917; 7A-A-C-T, rs2395309-rs3077 rs2301220-rs9277341; 8A-A-C-C//A-G-T-G-C-C, rs2395309-rs3077-rs2301220-rs9277341//rs9277535-rs10484569-rs3128917 -rs2281388-rs3117222-rs9380343; 9A-A-C-T//A-G-T-G-C-C, rs2395309-rs3077-rs2301220-rs9277341//rs9277535-rs10484569-rs3128917 -rs2281388-rs3117222-rs9380343; 10G-G-T-C//A-G-T-G-C-C, rs2395309-rs3077-rs2301220-rs9277341//rs9277535-rs10484569-rs3128917 -rs2281388-rs3117222-rs9380343; 11T-T-G-A-T, rs9276370-rs7756516-rs7453920 rs9277535-rs9366816; 12T-T-G-G-T, rs9276370-rs7756516-rs7453920-rs9277535-rs9366816; 13G-A, rs2856718- rs9275572; 14A-G, rs2856718- rs9275572; 15A-A, rs2856718 rs9275572; 16T-C-C-G-G-G, -1031/-863/-857/-308/-238/-163; 17C-A-C-G-G-G, -1031/-863/-857/-308/-238/-163; 18A-T-G-T-T-T-T-C-T, +88344/+102906/+103432/+103437/ +103461/+104261/+104802/+106151/+106318; 19T-C, rs12375841-rs17803780; 20C-A-C, rs421446-rs107822-rs213210; 21T-G-T, rs421446-rs107822-rs213210; 22C-A-C-C-G, -1722/-1661/-658/-319/+49; 23T/C-A-C-C-G, -1722/-1661/-658/-319/+49; 24T-A-C-C-A, -1722/-1661/-658/-319/+49; 25A-T-A, rs17401966-rs12734551-rs3748578; 26C-C, rs111033850-rs12953258; 27T-T-C-T-A, -1800/-1627/+4645/+5806/+6139; 28C-T-C-T-T, rs8179673-rs7574865-rs4274624-rs11889341-rs10168266; 29G-G-A, rs3757328-rs6940552-rs9261204.*

Another meta-analysis indicated that HLA B\*07 and B\*58 protect against chronic HBV infection (Seshasubramanian et al., 2018). Recent studies have shown that non-classical HLA-class I molecules, including HLA-E may also be related to hepatitis B virus infection (Zidi et al., 2016). Available data are consistent with the fact that cellular immunity is a major determinant for

HBV control. However, it is not clear how the identified genetic variation influences immune functions in the host and specific immune responses to HBV. These critical questions need to be answered in future studies.

Cytokines are key antiviral and immunomodulatory molecules produced by immune cells and certain non-immune cells; they are involved in host defense against HBV infection and pathogenesis (Koziel, 1999; Shin et al., 2016). The antiviral and immunomodulatory functions of a number of cytokines, like type I and II IFNs, TNF-α, IL-10, and IL-21, play essential roles in the direct suppression of HBV replication in hepatocytes (Phillips et al., 2010), mediating the antiviral functions of T cells (Freeman et al., 2012), and the modulation of adaptive immune responses to HBV (Lin and Young, 2014; Gehring and Protzer, 2019). IFN-γ and TNF-α are major antiviral mediators of specific CD8+T cells and are required for HBV control in primary HBV infections (Phillips et al., 2010; Bertoletti and Ferrari, 2013). IL-10 may contribute to negative regulation of host immune responses and thereby plays a role in viral persistence (Saraiva and O'Garra, 2010). IL-18 is a cytokine that belongs to the IL-1 superfamily and is produced by macrophages and other cells (Mavragani and Moutsopoulos, 2014). Recently, IL-21 has drawn attention in the field of HBV research owing to its potential association with viral control *via* follicular helper T cell functions (Johnson and Jameson, 2009).  Clinical researches have revealed correlations between IL-18 -607C/A and -137G/C (rs1946519 and rs187238) polymorphisms and the risk of HBV infection (Karra et al., 2015). The study of a Indian population by Karra et al. involving 271 patients with hepatitis B–related liver diseases, including 109 with spontaneous recovery, 162 patients with persistent HBV infection, and 280 healthy volunteers, indicated that the −607A allele in the promoter region of the IL-18 gene may protect against HBV infection (healthy controls *vs*. cases, OR [95% CI] = 0.711 [0.559–0.904], *P* = 0.005). The AA genotype was associated with spontaneous clearance (spontaneous recovery *vs*. persistent HBV infection, OR [95% CI] = 2.765 [1.582–4.832], *P* = 0.0002), while the CC genotype was associated with HBV infection (persistent HBV infection *vs*. spontaneous recovery, OR [95% CI] = 0.318 [0.151–0.67], *P* = 0.001). Moreover, the -137C allele (cases *vs*. healthy controls, OR [95% CI] = 1.355 [1.037–1.771], *P* = 0.025) and the GC genotype (cases *vs*. healthy controls, OR [95% CI] = 1.558 [1.11–2.185], *P* = 0.01) were associated with persistent HBV infections. SNPs (−1,082, −592) within the IL-10 gene have been reported to be associated with susceptibility or the clearance of HBV infection (Cheong et al., 2006; Talaat et al., 2014). Further studies are needed to determine the functions of these cytokines in HBV infection and thereby to explain these conflicting results.

IL-28B SNPs are major determinants of HCV clearance and the efficacy of IFN therapy (Ge et al., 2009; Prokunina-Olsson et al., 2013). This locus encodes a cytokine that is distantly related to type I interferons and the IL-10 family and is induced by viral infection (Sheppard et al., 2003). A systematic review by Lee et al. (Lee et al., 2014) including 4,028 patients with chronic hepatitis B and 2,327 spontaneously recovered controls from 11 case–control studies indicated that there is no significant association between IL28B SNPs (rs12979860, rs12980275, and rs8099917) and spontaneous HBV clearance. These findings are not surprising, as the mechanisms underlying HBV control may differ substantially from those underlying HCV infection.

Interferon gamma (IFN-γ) is a type II interferon and is critical for innate and adaptive immunity against viral, bacterial, and protozoal infections (Schoenborn and Wilson, 2007). Cellular responses to IFN-γ are activated by its interaction with a heterodimeric receptor consisting of IFN-γ receptor 1 (IFN-γR1) and IFN-γ receptor 2 (IFN-γR2) (Robek et al., 2004). Previous studies have reported that several polymorphisms in IFN-γ, IFN-γR1, and IFN-γR2 are associated with the natural history of HBV infection (Liu et al., 2006; Khanizadeh et al., 2012). In a study by Liu et al. (Liu et al., 2006) including 181 patients with HBV infection and 272 gender, age-matched healthy controls, the A allele frequency of IFN-γ +874 (OR [95% CI] = 2.25 [1.69– 2.99], *P* < 0.0001), and the AG haplotype (+874A and +2109G) (*P* < 0.0001) were found to significantly influence susceptibility to HBV infection in the Chinese population. A meta-analysis by Sun et al. (Sun et al., 2015) suggested that the IFN-γ +874T/A polymorphism contributes to an increased risk of HBV-related diseases, especially in Asians.

Chemokines are a family of small cytokines found in all vertebrates, some viruses, and some bacteria; they guide cells of the innate and adaptive immune systems. Some chemokines are involved in the control of immune cells during immune surveillance, directing lymphocytes to lymph nodes, to screen for pathogen invasion *via* interactions with APCs residing in these tissues (Kehrl, 2006; Mélik-Parsadaniantz and Rostène, 2008).

To date, studies of cytokine and chemokine genes have evaluated limited numbers of SNPs with small sample sizes, and rather inconsistent results have been obtained. Therefore, future large-scale and multi-center studies are needed to establish the relationship between the genetic control of cytokine- and chemokine-related functions and chronic HBV infection, given the importance of cytokines in anti-HBV immune responses.

TLRs play key roles as pattern recognition receptors; they activate the innate immune system (Chang, 2010; Kondo et al., 2011) and are required for efficient host defense against viral infection. Deficiencies in TLR or TLR-related signaling greatly reduce host-specific T cell responses to HBV and may contribute to HBV persistence (Ma et al., 2017). Thus, genetic variation in TLRs is expected to impact the susceptibility to chronic HBV infection (Al-Qahtani et al., 2012a; He et al., 2015; Huang et al., 2015; Zhu et al., 2017). Multiple SNPs in TLR genes (TLR3 rs1879026, rs3775290, and rs3775291, TLR7 rs179010, and TLR9 rs352140) have been examined for their association with the risk of HBV infection (He et al., 2015; Huang et al., 2015; Zhu et al., 2017). SNPs in TLR3 may be associated with an increased risk of chronic HBV infection. Al-Qahtani et al. (Al-Qahtani et al., 2012a) investigated SNPs in the TLR3 gene in Saudi Arabian patients chronically infected with HBV, including 707 patients and 600 uninfected controls. Only TLR3 rs1879026 (OR [95% CI] = 0.809 [0.655–0.999], *P* = 0.0480) and the GCGA haplotype (rs1879026, rs5743313, rs5743314, and rs5743315) (*P* = 0.0339) potentially contribute to the risk of HBV infection. Huang et al. (Huang et al., 2015) indicated that the TT genotype of TLR3 rs3775290 is closely correlated with a decreased risk of CHB. A meta-analysis by Geng et al. (Geng et al., 2016) demonstrated a significant effect of TLR3 rs3775291 and HBV-related diseases.

MicroRNAs (miRNAs) are a group of endogenous, highly conserved, small noncoding RNAs that modulate various cellular processes and play key roles in host–virus interactions and the pathogenesis of viral diseases (Qureshi et al., 2014). HBV replication is also regulated by miRNAs *via* their cellular targets (Zhang et al., 2011a; Zhang et al., 2013d; Lin et al., 2017). Hundreds of SNPs in miRNAs have been reported. Recent studies have shown that some miRNAs may play a role in anti-HBV defense (Su et al., 2011). In addition, miRNA polymorphisms are related to hepatitis B infection (Bae et al., 2012; Cheong et al., 2013; Al-Qahtani et al., 2017). A study of a Saudi Arabian population including 1,352 HBV-infected patients and 600 uninfected healthy individuals found that SNPs in different microRNA genes, including miR-149 (rs2292832), miR-146a (rs2910164), miR-196a-2 (rs11614913), and miR-30a (rs1358379), were associated with hepatitis B infection, while other SNPs in microRNA genes, including miR-423 (rs6505162), miR-492 (rs2289030), miR-146a (rs2910164), miR-196a-2 (rs11614913), and miR-30a (rs1358379) were associated with HBV clearance (Al-Qahtani et al., 2017). A meta-analysis (Zhou et al., 2015) has shown that the carriers of miR-196a-2\*T (rs11614913), miR-122\*del (rs3783553), miR-106b-25\*A (rs999885), and miR-let-7c\*del (rs6147150) alleles in the Asian population have an increased risk of chronic HBV infection.

Cytotoxic T-lymphocyte-associated protein 4 (CTLA4) is expressed by T lymphocytes and plays a key role as a negative regulator of T-cell responses (Buchbinder and Hodi, 2015). Several studies have evaluated the association between CTLA4 polymorphisms and chronic HBV infection. In particular, the + 49A/G polymorphism (rs231775) of CTLA4 may influence susceptibility to HBV infection in the Chinese population (Chen et al., 2010). Mohammad et al. (Mohammad et al., 2006) found that CTLA-4 -318 polymorphisms (rs5742909), but not +49 and −1,172 polymorphisms (rs733618) are significantly associated with susceptibility to chronic HBV infection in the Iranian population (OR = 0.49, 95% = 0.206–1.162, *P =* 0.012). Another study also showed that the CTLA4 –318C > T, but not +49G > A, is associated with chronic HBV infection (Schott et al., 2007). A meta-analysis (Xu et al., 2013) suggested that the A allele of the CTLA4 +49 polymorphism is significantly associated with an increased risk of persistent HBV infection, whereas the G allele may influence viral clearance. Another meta-analysis also suggested that the CTLA-4 +49A/G polymorphism is significantly correlated with persistent HBV infection in the Asian population (Huang et al., 2013).

NTCP encoded by the solute carrier family 10 member 1 (SLC10A1) gene is mainly expressed in hepatocytes and a functional receptor for HBV and hepatitis D virus (Hagenbuch and Meier, 1994; Yan et al., 2012a). NTCP rs2296651 (S267F) has been found to be related to HBV susceptibility in the Asian population (Hu et al., 2016; Yang et al., 2016a; Nfor et al., 2018; Wu et al., 2018a). In a larger cohort of Taiwanese patients, including 3,801 with chronic HBV infection and 3,801 matched HBsAg seronegative controls, the AA genotype of the S267F

variant (rs2296651) was associated with resistance to chronic HBV infection (OR = 0.13, 95% CI = 0.05–0.34, *P* < 0.001), but there were no significant associations with serological outcomes, including HBV DNA detectability and HBeAg and HBsAg seroclearance (Hu et al., 2016). However, the S267F variant is absent in the Moroccan population (Ezzikouri et al., 2017). A large cohort study did not confirm the association between the common and rare alleles or CNVs in the SLC10A1 gene with the risk of persistent HBV infection in a population from Southern China (Zhang et al., 2017). A meta-analysis including 14,591 chronically HBV-infected patients and 12,396 healthy controls suggested that the A allele and GA genotypes of rs2296651 are inversely correlated with chronic HBV infection. They also reported that NTCP rs4646287, rs7154439, and rs4646296 show no significant correlation with HBV infection (Wang et al., 2017a).

The signal transducer and activator of transcription (STAT) protein family mediates many aspects of cellular immunity, proliferation, apoptosis, and differentiation (Miklossy et al., 2013). STAT proteins are involved in the development and function of the immune system and play a role in maintaining immune tolerance (Singh et al., 2009). In HBV infection, polymorphisms in STAT4 are related to the clinical outcome of HBV infection (Lu et al., 2015b; Jiang et al., 2016b). A case– control study including 1,610 Chinese patients with chronic HBV infection and 1,423 uninfected control subjects showed that the STAT4 SNPs rs7574865, rs10168266, rs11889341, and rs8179673 are significantly associated with the risk of HBV infection and inversely related to HBV clearance. They also found that the CTCTT haplotype, formed by the SNPs rs8179673, rs7574865, rs4274624, rs11889341, and rs10168266, is related to HBV infection susceptibility and clearance in the Chinese Han population. A meta-analysis including 8,944 chronically HBVinfected patients, 8,451 healthy individuals, and 2,081 subjects with HBV clearance demonstrated that STAT4 rs7574865 is significantly associated with HBV infection (OR [95% CI] = 1.14 [1.07–1.21]; *P =* 3.8 × 10−5) and clearance (OR [95% CI] = 1.20 [1.07–1.35], *P =* 0.002) (Jiang et al., 2016b). Lu et al. (Lu et al., 2015b) showed that STAT4 minor alleles (rs7574865, rs7582694, rs11889341, and rs8179673) are associated with spontaneous HBV clearance. Another meta-analysis by Liao et al. (Liao et al., 2014) did not confirm the correlation between STAT4 rs7574865 and HBV susceptibility or clearance. Thus, the association of STAT4 polymorphisms with HBV infection requires further verification.

Signal transducer and activator of transcription 3 (STAT3) and nuclear factor-kappaB (NF-κB) pathways may play a significant role in chronic HBV infection. A Chinese Han population study showed that STAT3 rs1053004 and rs1053005 polymorphisms and haplotypes formed by rs1053004 and rs1053005 might contribute to the susceptibility to chronic HBV infection (Li et al., 2018). Another Chinese study also found that the SNPs rs2233406 (CT versus CC) and rs3138053 (AG or AG+GG versus AA) in the promoter region of NFKBIA were significantly associated with decreased risk of HBV persistence, especially in genotype B HBV-infected subjects (Zhang et al., 2014a). Unfortunately, related research is still not sufficient and mainly focused on HCC. Their role of HBV infection needs to be better defined by future research.

Vitamin D has the ability to activate the innate immune system and dampen the adaptive immune system (Hewison, 2011). A vitamin D deficiency is associated with an increased risk or severity of viral infections (Beard et al., 2011). Vitamin D has both anti-inflammatory and anti-microbial effects and may play an active role in HBV infection (Bellamy et al., 1999; Beard et al., 2011; Gao et al., 2017). Vitamin D–related genes include 1-α-hydroxylase (CYP27B1), cytochrome P450 family 2 subfamily R polypeptide 1 (CYP2R1), vitamin D–binding protein (GC), VDR, 7-dehydrocholesterol reductase (DHCR7), sterol 27-hydroxylase (CYP27A1), and cytochrome P450 family 24 subfamily A member 1 (CYP24A1). Vitamin D–related genes have recently been found to play an important role in HBV susceptibility (Chatzidaki et al., 2012; Gao et al., 2017). The majority of these studies have focused on four SNPs in VDR: ApaI (rs7975232), TaqI (rs731236), FokI (rs10735810), and BsmI (rs1544410). Chatzidaki et al. (Chatzidaki et al., 2012) found that the joint haplotype of the VDR ApaI α allele and TaqI T allele is related to the outcome of HBV infection in children in the context of mother-to-child transmission (RR [95% CI] = 1.74 [0.97–3.13], *P =* 0.049). A meta-analysis (He et al., 2018) has reported that the genotypes FF, Ff, and allele F of FokI in VDR increase the risk of HBV infection. However, no associations were found between VDR ApaI and BsmI polymorphisms and HBV infection.

There is a marked difference in HBV infection rates between populations in East/Southeast Asia and Western world. For instance, the prevalence of HBsAg was as high as 10% in the Chinese population prior to the initiation of the HBV vaccination program but less than 1% in the Caucasian population (Fattovich et al., 2008; Yin et al., 2010). The reason for this difference is not completely clear. The role of host genetic determinants is also not well-established. Li et al. (Li et al., 2015) summarized multiple studies and found that some genetic loci with rare alleles include rs3138053 (NFKBIA), rs2856718, rs7453920, and rs9275319 (HLA-DQ), and rs9277378, rs2395309, rs2301220, and rs9277341 (HLA-DP) are significantly associated with decreased risks of development of chronic HBV infection. These loci are different between the Chinese Han and European populations, indicating that the Chinese Han patients may be inherently more prone to develop chronic infection once exposed to HBV, whereas Europeans tend to recover from HBV infection spontaneously (Li et al., 2015). A study including Chinese Han and Uyghur populations reported that there are some differences in HLA-DP/ DQ polymorphisms that affect susceptibility and resistance to HBV infection (Xiang et al., 2016). A meta-analysis by Geng et al. (2016) demonstrated that TNF-α-238 increases the risk in the European population but not in an Asian population in all genetic

models. Therefore, the genetic determinants may contribute the different rates of chronic HBV infection in Asian and European populations. However, future global multicenter research is needed to precisely define such host genetic determinants.

HBV infection often occurs in families. If a mother is chronically HBV infected, infants have an extremely high chance of establishing a chronic HBV infection in the absence of medical interventions (Stevens et al., 1975; Chen et al., 2018; Dionne-Odom et al., 2018). HBV exposure during infancy or early childhood is more prone to the development of chronic infection and HBV infection-related diseases (Lai and Yuen, 2007). Studies have shown that spontaneous HBsAg clearance is most likely to occur in patients born to mothers of non-HBsAg carriers (Chiu et al., 2014). Globally, a total of 42.1% of infants naturally born to HBsAg carrier mothers but only 2.9% of infants with HBV passive–active immunoprophylaxis acquired HBV infection perinatally (Li et al., 2015). The rate of vertical HBV infection had stayed constant (approximately 0.3%) until immunoprophylaxis of mother-to-infant transmission was implemented in 1986 in Japan. In contrast, horizontal HBV transmission decreased from 1.43 to 0.10% in men and from 0.95 to 0.03% in women over years. The decrease of horizontal transmission of HBV may be due to many factors, including improved socioeconomic environments, advanced medical maneuvers and equipment, and careful vaccination procedures (Sato et al., 2014). However, the current studies on host genetic and chronic HBV infection did not separate vertical from horizontal transmission, nor did they stratify the age at the time of infection. The role of environmental exposure including early exposure of HBV in the childhood when immune function is immature, and their interaction with the genetic predisposition is still not clarified.

In studies of associations between host genetic determinants and chronic HBV infection to date, reported OR values for significant associations typically range from 1 to 2. Thus, these determinants have much less influence than the HBV infection status of the mother or the age of the HBV infection. Nevertheless, some genetic variants, like mutations in NTCP, may play a decisive role in HBV infection. NTCP variation could prevent the binding of the HBV virion to receptors on hepatocytes and therefore limit viral infection (Yan et al., 2012a). Such findings may provide mechanistic insights into the viral life cycle and new targets for drug development. Many genetic determinants (HLA, TLR, IL) may modulate host innate and adaptive immunity and significantly influence the course and outcome HBV infection (Kamatani et al., 2009; Mbarek et al., 2011; Kim et al., 2013; Jiang et al., 2015; Geng et al., 2016) (**Table 2**; **Table S2**). It will be useful to identify the functional relevance of these genetic polymorphisms in cellular signaling and other processes, with the goal of identifying new targets. Many factors contribute to the development of chronic HBV infection, such as the mode of transmission (vertical or horizontal transmission), age at the time of infection, the presence of underlying diseases involving other organs, and the use of immune inhibitors (Pawlowska et al., 2016; Chien et al., 2019). The majority of studies do not including subgroup analyses of these factors, which may have a significant impact on the reliability of the results. Furthermore, there are substantial variations among studies from different countries and regions due to differences in the study populations, genetic background, and polymorphisms. Therefore, it may be necessary to conduct stratified analyses of HBV infection time, ethnicity, host immune status, and mode of transmission to further determine the impact of HLA-DP, DQ, and DR on chronic hepatitis B or clearance. Nevertheless, the available information suggests that genetic variation in host immune-related genes has substantial contribution to the outcome of HBV infection. Future research is necessary to uncover the mechanisms underlying these associations.

### INTRAUTERINE TRANSMISSION

Mother-to-child transmission is the major route of HBV infection in developing countries (Stevens et al., 1975; Shao et al., 2007; Li et al., 2015). Intrauterine transmission is the main explanation for mother-to-child transmission, since the implementation of effective measures against HBV infection, such as antiviral treatment, vaccination, and the application of hepatitis B immunoglobulins (Gu et al., 2004; Brown et al., 2016; Ren et al., 2016). Therefore, blocking intrauterine HBV transmission is an important part of the eradication of HBV infection in the general population (Peng et al., 2019). Unfortunately, the incidence of intrauterine HBV infection remains high (Han et al., 2011). The exact mechanism underlying intrauterine infection with HBV has not been fully elucidated (Xu et al., 2008). Previous studies have shown that genetic factors could play an important role in determining the outcome of HBV intrauterine infection (Yu et al., 2006; Xu et al., 2008; Gao et al., 2015b; Liu et al., 2018d). Based on twin and family study, host genetic factors are critical for the development of chronic HBV infection (Lin et al., 1989). Up to date, SNPs in the host genes IFN-γ, TNF-α, CXCL13, PDCD1, TLR3, and TLR9 were found to be relevant for intrauterine transmission (Yu et al., 2006; Gao et al., 2015b; Wan et al., 2016; Liu et al., 2018c; Gao et al., 2015b) (**Table S3**).

A number of host genes may play important roles in HBV intrauterine infection (**Table 3**, **Tables S1**, **S3**). Yu et al. (Yu et al., 2006) showed that a SNP (+874) in IFN-γ is associated with HBV intrauterine infection (both *P* < 0.05). Wan et al. (Wan et al., 2016) investigated associations between candidate genes (SLC10A1, HLA-DP, HLA-C, CXCR5, CXCL13, TLR-3, TLR-4, TLR-9, and UBE2L3) and HBV intrauterine infection in a sample of 44 neonates with HBV intrauterine infection and 662 neonatal controls. They demonstrated that only the rs355687 CT genotype of CXCL13 was associated with susceptibility to

TABLE 3 | Host genetic factors associated with intrauterine hepatitis B infection or response to interferon-alpha (IFN-α) or nucleos(t)ide analog (NUC).

*1A-C, rs12980275-rs12979860; 2G-T-G-A, rs3177979-rs1293747-rs4767043-rs10849829; 3C-C-T-A, rs2285934-rs2072138-rs2072136-rs10849829; 4C-C-C-A, rs2285934 rs2072138-rs2072136-rs10849829; 5A-C-T-A, rs2285934-rs2072138-rs2072136-rs10849829.*

HBV intrauterine infection (OR [95% CI] = 0.25 [0.08–0.82], *P =* 0.022).

A case–control study of the Chinese population including 69 HBsAg-positive mother–newborn pairs with intrauterine infection and 138 mother–newborn pairs without intrauterine infection assessed the involvement of the LTβR/APOBEC3B signaling pathway and PD-1/PD-L1 signaling pathway genes, including LTA, LTBR, TNFSF14, PDCD1, APOBEC3B, CD274, CD40, and CD40LG, in HBV intrauterine transmission. They found that the maternal rs2227981 TT genotype of the PDCD1 gene is associated with a decreased risk of intrauterine HBV infection (OR 0.11, 95% CI = 0.01–0.95, *P =* 0.045). There was no significant correlation between the remaining genes and the risk of intrauterine HBV infection (Liu et al., 2018c). Only a few studies have evaluated genetic susceptibility to intrauterine transmission. It is often difficult to distinguish whether a child acquired an HBV infection by the intrauterine or intra-natal route. HBV infection by intrauterine transmission is mainly identified by a blood test at birth. However, this approach may result in false positives due to maternal blood contamination during birth, especially when sensitive PCR methods for HBV DNA detection are used. Moreover, the sample sizes of existing studies are not large enough; thus, the reliability of studies could be questioned. Further research is needed to improve the diagnostic accuracy of intrauterine HBV infection and explore the relationship between HBV intrauterine infection and susceptibility genes as well as other risk factors associated with HBV intrauterine infection.

There is no effective intervention available to prevent intrauterine HBV infection. Neither antiviral treatment during the late phase of pregnancy nor perinatal vaccination/hyperimmunoglobulin application changed the rate of intrauterine HBV infection (Pan et al., 2012a; Brown et al., 2016). Therefore, the identification of relevant genetic determinants could be very helpful.

## OCCULT HBV INFECTION

OBI is defined by serum HBV DNA positivity but negative serum HBsAg detection (Torbenson and Thomas, 2002; Raimondo et al., 2008; Raimondo et al., 2019; Seed et al., 2019). If blood from patients with OBI is transfused to other persons, posttransfusion hepatitis may occur (Seo et al., 2011). OBI may also be associated with hepatitis B vaccination failure, vertical HBV transmission, organ transplant failure, cirrhosis, and liver cancer (Raimondo et al., 2013).

The mechanisms underlying OBI have yet to be elucidated and may be related to HBV mutations in the pre-S/S genomic region or antigen–antibody cycle immune complex formation (Zhang et al., 2011b; Samal et al., 2012). Some investigators have suggested that host genetic factors, especially immune-related factors including HLAs, IL10, CXCL12, and VDR, may play a role in the occurrence of OBI (Arababadi et al., 2010; Hassanshahi et al., 2010; Mardian et al., 2017; Wang et al., 2017b) (**Tables S1**, **S4**). Wang et al. (Wang et al., 2017b) performed a case–control study with 107 patients with OBI and 280 healthy individuals to assess

associations of SNPs in HLA loci, including HLA-A, -B, -C, -DRB1, and -DQB1, in Chinese patients. They found that HLA-B\*44:03 (OR = 2.146, 95% CI = 1.070–4.306, *P =* 0.028), C\*07:01 (OR = 4.693, 95% CI = 1.822–12.086, *P =* 0.000), DQB1\*02:02 (OR = 1.919, 95% CI = 1.188–3.101, *P =* 0.007), and DRB1\*07:01 (OR = 2.012, 95% CI = 1.303–3.107, *P =* 0.001) were strongly associated with susceptibility to OBI, while DRB1\*08:03 (OR = 0.395, 95% CI = 0.152–1.027, *P =* 0.049), DRB1\*15:01 (OR = 0.495, 95% CI = 0.261–0.940, *P =* 0.029), and DQB1\*06:02 (OR = 0.500, 95% CI = 0.249–1.005, *P =* 0.048) alleles were more prevalent in the healthy control group. Mardian et al. (Mardian et al., 2017) found a significant association between the minor allele "T" of HLA-DP (rs3077) and the TGA haplotype (rs3077– rs3135021–rs9277535) and OBI in Indonesian blood donors. Therefore, HLA polymorphisms are an important factor in OBI infection and additional studies are needed to validate these findings. Iranian researchers have shown that the genotypes and alleles of IL-10 (-592) (Ahmadabadi et al., 2012), the +801 region of CXCL12 (Hassanshahi et al., 2010), and the T/T allele of exon 9 of VDR (Arababadi et al., 2010) may be associated with OBI.

Owing to the low frequency of OBI, the accumulation of cases is difficult and time-consuming. Thus, the number of cases included in studies is always small (generally less than 100 cases). In addition, the occurrence of OBI is also related to HBV mutations (Samal et al., 2012). OBI diagnostic criteria are not uniform among studies. Both viral and host factors need to be considered in future analyses. Patients with OBI are positive for HBV DNA but negative for HBsAg. Thus, there could be specific mechanisms for the control of HBsAg production without affecting HBV DNA synthesis. Recently, Lin et al. found that autophagy and related genes (e.g., Rab7) may determine HBsAg production (Lin et al., 2017; Lin et al., 2019), but further studies are needed to evaluate this.

# ANTIVIRAL EFFICACY OF INTERFERON-**α** OR NUCLEOS(T)IDE ANALOGUES

IFN-α and NUCs have been approved and are widely used for the treatment of chronic hepatitis B and slow down liver disease progression, cirrhosis, and HCC (Lee and Keeffe, 2011; European Association For The Study Of The Liver, 2017). However, NUCs and IFN-α alone or combined treatment are rare to achieve functional cure (Reijnders et al., 2010; Zoulim and Locarnini, 2012; Terrault et al., 2016; Revill et al., 2019). Extensive studies have identified host genetic genes, alanine aminotransferase (ALT) levels, HBV genotype, and HBV DNA, anti-HBc, and HBsAg levels as important predictors of treatment efficacy (Brouwer et al., 2014; Fan et al., 2016b; Zhu et al., 2016a). Accumulating evidence suggests that host genetics play an important role in the patient response to IFN-α or NUCs (**Table 3**; **Tables S1**, **S5**, **S6**).

IFN-α is a cytokine with a broad-spectrum effect against viruses and tumors. It is able to inhibit cell growth and exerts immunomodulatory effects. IFN-α exerts antiviral activity mainly *via* the Janus-activated kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway and interferon-stimulating genes (ISGs) (Levy and Darnell, 2002). IFN-α binds to type I IFN receptor (IFN-αR1) on the surface of target cells and induces the synthesis of antiviral proteins, such as MxA, 2',5'-oligoadenylate synthetase (OAS), protein kinase (PKR), and adenosine deaminases acting on RNA (ADAR) (Samuel, 2001). In addition, IFN-α upregulates HLAs and thereby modulates adaptive immunity. Thus, host genetic polymorphisms, particularly those associated with IFN signaling pathways, may potentially alter the responsiveness to IFN-α therapy. Many studies have evaluated the relationship between the outcome of IFN-α treatment for CHB and host genetics and identified the potential relevance of HLAs, STAT4, vitamin D– related genes, and some ISGs (Tseng et al., 2011; Brouwer et al., 2014; Wu et al., 2014; Jiang et al., 2016a; Thanapirom et al., 2017; Brouwer et al., 2019) (**Table S5**).

The first GWAS published to date did not find any candidate gene associated with the efficacy of IFN-α treatment. This may be explained by an insufficient sample size, with only 43 patients (Chang et al., 2014). Recently, Brouwer et al. (Brouwer et al., 2019) published a GWAS on the efficacy prediction of PEG-IFN in the treatment of CHB, including 1,058 patients from 21 centers from Europe, Asia, and North America. A SNP rs78900671 GC allele (TRAPPC9, COL22A1) had been identified to have the strongest association with response to PEG-IFN treatment (*P =* 6.43×10-7). Another SNP PRELID2 rs371991 (*P =* 3.44×10-6) was associated with the primary response to PEG-IFN treatment in HBeAg-positive patients while G3BP2 rs3821977 (*P =* 2.46×10-6) was associated with response in HBeAg-negative patients. Yet the correlation between these SNP loci and the efficacy of interferon treatment needs confirmation by future studies.

HLA molecules play an important role in the recognition of viral proteins and regulation of adaptive immunity. Adaptive immunity is upregulated by IFN-α treatment and essential for sustained responses and HBV control (Bengsch and Thimme, 2018; Ma et al., 2018b). Thus, HLAs may be an important genetic marker for the prediction of IFN-α efficacy. Many studies have analyzed the relationship between HLA genes and the IFN-α response (Tseng et al., 2011; Zhu et al., 2011; Brouwer et al., 2014; Tangkijvanich et al., 2016). A study of a Taiwan population by Tseng et al. (Tseng et al., 2011) including 115 HBeAg-positive patients with CHB who received peginterferon (PEG-IFN) therapy showed that the HLA-DPA1 rs3077 GG genotype (OR [95% CI] = 3.49 [1.12–10.84], *P =* 0.031) is associated with HBeAg seroconversion at 6 months of therapy. Brouwer et al. (Brouwer et al., 2014) evaluated 262 Caucasian patients with chronic HBV infection who were treated with PEG-IFN for 1 year and found that the HLA-DPB1 (rs9277535) G-allele and haplotype block GG combining HLA-DPB1 (rs9277535) and HLA-DPA1 (rs3077) are strongly associated with virological (HBV DNA <2,000 IU/ml at 6 months post-treatment) and serological responses (HBeAg seroconversion combined with HBV DNA <2,000 IU/ml at 6 months post-treatment) to PEG-IFN therapy. Zhu et al. (Zhu et al., 2011) reported that the HLA-DQB1\*0303 or DRB1\*08 alleles and the \*1101-\*4601-\*0102 (HLA-A, B, C) or \*0302-\*0303-\*09 (HLA-DQA1, DQB1, DRB1) haplotypes are associated with the efficacy of IFN therapy in the Chinese population. However, some studies have failed to observe a relationship between HLA variants and the response to IFN-α- or PEG IFN-based treatment (Limothai et al., 2016).

IFN-λ3 is encoded by the IL-28B gene, which regulates the immune system by activating the JAK-STAT signaling pathway, thereby exerting an antiviral effect (Liu et al., 2012a). Recent GWAS has revealed that IL28B is associated with the efficacy of anti-HCV treatment (Ge et al., 2009). In a large international collaborative study of 205 HBeAg-positive patients with CHB who received PEG-IFN-α-2a or PEG-IFN-α-2b, IL28B rs12979860 and rs12980275 were independent predictors of HBeAg seroconversion in response to PEG-IFN (Sonneveld et al., 2012). Boglione et al. (Boglione et al., 2014) examined the effect of the IL28B gene polymorphisms rs12979860, rs8099917, and rs12980275 on the response to PEG-IFN in 190 chronically HBVinfected, HBeAg-negative patients and showed that rs12979860 CC, rs8099917 TT, and rs12980275 AA are significantly associated with HBV-DNA < 2,000 IU/ml post-treatment, while rs12979860 CC and rs12980275 AA are significantly associated with qHBsAg > 1 log during therapy. Many other research teams worldwide have indicated that IL-28B is involved in the efficacy of IFN-α therapy (Lampertico et al., 2013; Wu et al., 2015a; Cusato et al., 2017). However, variable and inconclusive results have been obtained (Cheng et al., 2014; Tangkijvanich et al., 2016). A study in Taiwan showed that IL28B rs12979860 is not associated with the virological response to PEG-IFN alpha-2b with or without entecavir in patients with HBeAg-negative CHB (Tangkijvanich et al., 2016). A Chinese study also suggested that IL28B (rs12979860 and rs8099917) has no significant association with the response to IFN-α or PEG IFN (Cheng et al., 2014). To determine whether IL28B polymorphisms play a role in the response to interferons, further large-scale cohort studies of homogenous patient populations are necessary.

Vitamin D has important immunomodulatory effects on innate and adaptive immune responses (Hewison, 2011). Vitamin D enhances the IFN-α-mediated activation of the JAK-STAT pathway, increases the expression levels of antiviral proteins, and improves the overall antiviral ability (Lange et al., 2014). Vitamin D–related genes, including VDR (Cusato et al., 2017), CYP27B1 (Cusato et al., 2017), CYP24A1 (Cusato et al., 2017), CYP2R1 (Thanapirom et al., 2017), DHCR7 (Thanapirom et al., 2017), and DBP/GC (Cusato et al., 2017; Thanapirom et al., 2017), have been evaluated for potential associations with the outcome of IFN-α therapy in patients with CHB. Several studies in China, Thailand, and Italy have shown that polymorphisms in the rs4646536 and rs10877012 loci of CYP27B1 may be related to the efficacy of IFN-α in patients with CHB; OR values reported in studies of Italy (Cusato et al., 2017), Thailand (Limothai et al., 2017), and Italy (Boglione et al., 2015) were 2.87, 3.13, and 3.13 for the rs4646536 locus (all P < 0.01); and the OR values for studies of Italy (Cusato et al., 2017) was 3.13 for the rs10877012 locus (both P < 0.001). Therefore, the TT (rs4646536) and GG (rs10877012) genotypes may be predictors of sustained HBeAg seroconversion in HBeAg-positive patients treated with IFN-α. Cusato et al. (Cusato et al., 2017) evaluated SNPs in vitamin D pathway genes in HBeAg-negative patients with CHB treated with PEG-IFN-α, suggesting that VDR (rs7975232 [ApaI], rs11568820 [Cdx2], rs10735810 [FokI]), CYP27B1 (rs4646536 [+2838], rs10877012 [−1260]), VDBP (rs7041), and CYP24A1 (rs2248359) are correlated with the clinical outcomes of PEG-IFN-α treatment. Thanapirom et al. (Thanapirom et al., 2017) showed that the CYP2R1 (rs12794714) TT genotype is a predictor of sustained HBeAg seroconversion in HBeAgpositive patients treated with Peg-IFN-α (OR [95% CI] = 4.53 [1.51–13.61], *P =* 0.01), whereas SNPs in DHCR7 (rs12785878), CYP27B1 (rs10877012), CYP2R1 (rs2060793), GC (rs4588, rs7041, rs222020, and rs2282679), and VDR (FokI, BsmI, Tru9I, ApaI, TaqI) are not related to HBeAg seroconversion. Several studies have investigated the role of other SNPs in vitamin D pathway genes in predicting the outcome of IFN-α therapy, but their predictive value remains controversial (Thanapirom et al., 2017). Differences among studies could be explained by several factors, such as differences in study design, sample size, ethnicity, and genotyping methods.

SNPs in JAK-STAT pathway genes and ISGs may contribute to the antiviral effects of IFN-based therapy (Kong et al., 2007; Ren et al., 2011; Wu et al., 2014; Jiang et al., 2016a). OAS3, MxA-88, and STAT4 genes in the IFN signaling pathway may have predictive value for the efficacy of interferons, but further studies are needed to verify this.

NUCs (e.g., lamivudine [LAM], adefovir [ADV], telbivudine [LdT], entecavir [ETV], and tenofovir [TDF]) inhibit HBV replication mainly by inhibiting HBV DNA polymerase. They bind competitively to HBV DNA polymerase and are incorporated into the DNA chain, resulting in the termination of DNA synthesis and inhibition of HBV replication (Lok et al., 2007; European Association For The Study Of The Liver, 2017). As the direct effect of NUCs on HBV does not require host functions and may not be directly related to host genetics, few studies have evaluated the correlation between host gene SNPs and drug efficacy, and these have generally yielded negative results (**Table 3**; **Tables S1**, **S6**).

There were significant differences in the patterns of HBsAg decline, and seroclearance during LAM therapy in Japanese patients with HBeAg-positive CHB was associated with HLA-DPA1 (rs3077), HLA-DPB1 (rs9277535), and A alleles at rs3077 and rs9277535 (Hosaka et al., 2015). A GWAS (Chang et al., 2014) with small sample sizes (LAM group, *n* = 119; ETV group, *n* = 64) of male Taiwanese individuals revealed that the TT genotype of rs9276370 (HLA-DQA2) is highly associated with a non-sustained response in the LAM group (OR [95% CI] = 5.41 [1.73–16.95], *P =* 0.0037), but not in the ETV group (OR [95% CI] = 0.68 [0.16–2.86], *P =* 0.5954). Zhang et al. (Zhang et al., 2014b) reported that the HLA-DQ (rs9275572) A allele is associated with viral and biochemical responses to LAM treatment in Chinese patients.

Using a small sample size (*n* = 76), our team evaluated the virological responses associated with the ESR1 PvuII T/C genotype in nucleoside-naive patients with chronic hepatitis B treated with ETV after 48 and 96 weeks of treatment; we did not detect associations between XbaI polymorphisms and virological response (Zhang et al., 2013c). Another study also found that CTLA4 (rs231775) and HLA-DPA1 (rs3077) are associated with predictors of relapse and outcomes after discontinuing TDF and ETV therapy in Taiwan patients with CHB (Su et al., 2018). However, the sample sizes of these studies are insufficient.

The main issues with studies of the efficacy of IFN/NUCs are as follows. 1) ALT, HBsAg, HBeAg, anti-HBc, HBV DNA, and HBV genotype may affect the efficacy of IFN/NUCs, and it is difficult to control for these confounding factors. 2) Some studies do not distinguish between HBeAg-positive or -negative patients, resulting in the inconsistent use of drugs as well as differences in treatment duration. 3) The criteria for determining efficacy and time points for evaluations are often inconsistent. 4) Many studies include small sample sizes and a lack of secondary verification. 5) Different and even contradictory results have been reported. Despite studies showing that several SNP sites in IL28B are closely related to the efficacy of IFN-α for the treatment of HCV infection, it is difficult to confirm that any host genetic determinant is significantly related to the efficacy of IFN-α or NUCs in chronic HBV infection without resolving these issues. It is necessary to clarify whether host genetic factors determine the efficacy of antiviral therapies. Currently, available antiviral treatments based on IFN-α/NUCs are not effective to clear HBV covalently closed circular DNA (cccDNA). Information about the involvement of host factors in antiviral activity may be helpful to optimize treatment approaches.

Attempts to improve the response by administering two different NUCs or a combination of NUCs and IFN-α failed to increase the rate of "functional cure." New drug candidates targeting different steps of HBV life cycle including entry, cccDNA formation, viral transcription, capsid assembly, and secretion of viral envelope proteins were developed and partly tested in clinical trials (Qazi et al., 2018; Tu and Urban, 2018; Yang and Lu, 2018; Yang et al., 2019). Immunotherapeutic approaches to enhance antiviral immunity using IL-15, TLR agonists, retinoic acid inducible gene I (RIG-I) agonist, stimulator of IFN genes (STING) agonist or based on engineered T cells are also under investigation (Ma et al., 2015; Zhang and Lu, 2015; Guo et al., 2017; Koh et al., 2018). A new drug targeting cIAPs has being now tested in a clinical trial phase I (Liu et al., 2018a). Checkpoint inhibitors like anti-PD1 are able to stimulate host adaptive immunity and considered as potential drug candidates to treat chronic HBV infection (Liu et al., 2014a; Liu et al., 2018b). Such innovative drugs, Along with current available therapies, will offer the prospect of a markedly improved response to treatments and an increased rate of functional cure (Ko et al., 2015; Blank et al., 2016; Di Scala et al., 2016; Zhu et al., 2019). Those new drug candidates, especially for immunotherapies, may exert the antiviral actions in dependence on host genetic background. Some genetic determinants found in the previous studies like SNPs in HLA loci may reappear again in such studies. Their efficacy in anti-HBV treatment related to human genetics remains to be a topic for future studies.

## RESPONSE TO HEPATITIS B VACCINATION

Hepatitis B vaccines are widely used for the prevention of new HBV infections and are the most effective way to prevent HBV transmission (Kew, 1995; Ni et al., 2012; Bruce et al., 2016). The overall success rate of vaccination is about 90%. Several factors, such as age, gender, body mass index (BMI), immunosuppression, vaccine escape mutations, and premature birth, are associated with a failure to respond to hepatitis B vaccination (Zuckerman, 2006; Kang et al., 2014; Yang et al., 2016b). A twin study indicated that the immune response to hepatitis B vaccination has a high heritability (77%) (Newport et al., 2004). Yan et al. investigate the overall contribution of genetic and environmental effects on poor response to HBV vaccination in Chinese infants. They found that the HBV vaccine response in infants is dominantly determined by genetic effect by 91%, compared with perinatal environmental factors (Yan et al., 2013). Genetic factors may have important roles in the immune response to hepatitis B vaccination, and many studies have focused on the identification of these genes including HLAs and IL4 (Png et al., 2011; Cui et al., 2013; Li et al., 2013b; Nishida et al., 2018) (**Table 4**; **Tables S1**, **S7**).

A recent GWAS has shown that genetic variants in HLA loci are strongly associated with chronic HBV infection. Difference in host immune responses to HBV antigens are largely explained by HLA alleles (Ovsyannikova et al., 2004). Associations of SNPs in HLA regions, including -A, -B, -DR, and -DQ loci, with the response to hepatitis B vaccines have been identified (Davila et al., 2010; Png et al., 2011; Yoon et al., 2014; Roh et al., 2016). A GWAS of an Indonesian population including 3,614 hepatitis B vaccine recipients suggested that HLA loci, including

HLA-DR (rs3135363) (*P =* 6.53 × 10−22; OR = 1.53, 95% CI = 1.35–1.74), HLA-DP (rs9277535) (*P =* 2.91 ×10−12; OR = 0.72, 95% CI = 0.63–0.81), and HLA class III (rs9267665) (*P =* 1.24 × 10−17; OR = 2.05, CI = 1.64–2.57), are strongly associated with the response to hepatitis B vaccination (Png et al., 2011). Other GWAS have found that HLA-DRB1 (rs477515, rs28366298, and rs13204672), HLA-DP (rs7770370), and multiple HLA-DRB1- DQB1 haplotypes are associated with the response to hepatitis B vaccines (Davila et al., 2010; Wu et al., 2015b). Although similar results have been obtained in several additional studies (Yoon et al., 2014; Roh et al., 2016; Sakai et al., 2017), other studies do not support these associations, likely owing to the sample sizes, statistical methods, or the use of different vaccines (Okada et al., 2017; Xu et al., 2017a). A meta-analysis (Li et al., 2013b) has shown that HLA class II genotypes (HLA-DRB1\*01, DRB1\*1301, DRB1\*15, HLA-DQB1\*05, DQB1\*0501, DQB1\*06, DQB1\*0602) are associated with the antibody response to the hepatitis B vaccine, while the opposite results were found for DRB1\*03 (DRB1\*0301), DRB1\*04, DRB1\*07, DRB1\*1302, and DQB1\*02. Taken together, HLA is an important marker for the response to the hepatitis B vaccine; multicenter studies are needed for verification and to determine the mechanism underlying this association.

Cytokines play key roles in regulating immune responses and may modulate responses to HBV vaccines (Harber et al., 2000; Howe et al., 2005). Among these cytokine genes, IL-4 induces the differentiation of naive helper T cells to Th2 cells

#### TABLE 4 | Host genetic factors associated with response to hepatitis B vaccine.

#### *Haplotypes*

*1A-G-A-G-G, rs5025825-rs6457709-rs35953215-rs3830066-rs7770370; 2A-G, rs3128961-rs9277535; 3A-G-A-G-G-A-G, rs5025825-rs6457709-rs35953215-rs3830066 rs7770370-rs3128961-rs9277535; 4A-A, rs3806156-rs2076530; 5C-G, rs3806156-rs2076530; 6G-T-A-T-C-A-G, rs9268501-rs3763316- rs3763313-rs3763311- rs9268494 rs3806156-rs2076530; 7G-T-A-T-C, rs9268501-rs3763316- rs3763313-rs3763311-rs9268494; 8G-C-A-T-C, rs9268501-rs3763316- rs3763313-rs3763311-rs9268494.*

and is a key regulator of humoral immune responses. Genetic polymorphisms in IL-4 have been reported to be associated with the response to the hepatitis B vaccine in many studies (Chen et al., 2011; Wang et al., 2012), such as IL-4 (rs2070874, rs2243250, rs2227282, rs2243248, rs2227284) (Chen et al., 2011; Wang et al., 2012), IL-4RA (rs1805015) (Chen et al., 2011), IL-12B (rs17860508) (Pan et al., 2012b), and IL-13 (rs1295686) (Chen et al., 2011) that are associated with responses to the hepatitis B vaccine. In a meta-analysis of eight published studies, Cui et al. (Cui et al., 2013) evaluated associations of IL4 genetic polymorphisms, including rs2243250 (C > T), rs2070874 (C > T), rs2227284 (A > C), rs2227282 (C > G), and rs2243248 (G > T), with the response to the hepatitis B vaccine. The analysis suggested that the T allele of rs2243250, the T allele of rs2070874, and the C allele of rs2227284 in IL4 may be useful biomarkers for predicting favorable responses to the hepatitis B vaccine, especially in the Asian population. Relatively few studies have examined other cytokine genes.

Other studies have suggested that polymorphisms in other host genes (BTNL2, FOXP1, LILRB4, TLR2, VDR, etc.) may be related to responses to hepatitis B vaccination (Davila et al., 2010; Chen et al., 2011; Grzegorzewska et al., 2014), but further validation of these results is required.

The overall success rate of vaccination is about 90% (Zuckerman, 2006), and the factors that affect the success of vaccination mainly include 1) the type of vaccine; 2) the dose, mode, and frequency of inoculation; 3) the vaccination schedule; 4) ethnic differences; 5) the age at vaccination; 6) the presence of severe heart, liver, and kidney disease; 7) OBI status; and 8) assessment criteria for successful vaccination. When analyzing the effect of SNPs on the success of vaccination, it is important to match patients with respect to the main factors or perform appropriate statistical analyses to account for these factors. However, at present, correlation analyses are relatively simple. In addition, most subjects are under 20 years of age, and age is related to the rate of antibody production in response to the hepatitis B vaccine. These factors can lead to differences and contradictory results among studies. Further in-depth analyses of host genes may be helpful for understanding the mechanisms underlying the response to hepatitis B vaccination and for exploring new approaches for the development of more effective hepatitis B vaccines. Furthermore, studies should evaluate whether so-called non-responders, who do not produce anti-HBs antibodies after vaccination, may develop chronic HBV infection. It would be useful to determine the genetic factors leading to non-responsiveness to HBV vaccines.

# CONCLUSION

A large number of studies have reported host genetic factors that are associated with chronic HBV infection, clinical type, therapeutic responses, or responses to hepatitis B vaccines (**Figure 2**). Host innate and adaptive immunity represent the major determinants of the outcome of HBV infection. The genetic diversity of many genes related to innate and adaptive immunity

have been found to be relevant for hepatitis B vaccination, HBV infection, and antiviral therapy (**Figure 3**).

HBV vaccines induce specific B cell responses, leading to the production of protective antibodies. The genetic polymorphism in many genes like HLAs and IL-4 has an impact on antigen presentation or cytokine production and thereby on antibody production, resulting in different degrees of responsiveness to vaccination (Png et al., 2011; Wang et al., 2012; Cui et al., 2013; Li et al., 2013b; Akcay et al., 2018; Nishida et al., 2018). The polymorphism in NTCP may determine the process of HBV entry (Yan et al., 2012a; Hu et al., 2016; Yang et al., 2016a; Nfor et al., 2018; Wu et al., 2018a). Many host factors may influence the innate and adaptive immunity including activation and phagocytosis of macrophages, antigen presentation by APCs, and priming and functionality of HBV-specific T cells, influencing HBV clearance and persistence (Bertoletti and Ferrari, 2016; Akcay et al., 2018; Lang et al., 2019; Rehermann and Thimme, 2019). It is well recognized that the recognition and presentation of HBV antigens by DCs to specific T cells initiate specific T cell antibody responses (Schurich et al., 2011; Das et al., 2012; Guidotti et al., 2015; Gehring and Protzer, 2019; Rehermann and Thimme, 2019; Zhu et al., 2019). IFNs and proinflammatory cytokines also contribute to HBV pathogenesis and control (Maini and Gehring, 2016; Hong and Bertoletti, 2017; Lang et al., 2019; Zhu et al., 2019). The genetic polymorphisms in relevant human genes could directly or indirectly determine these immune functions (**Figure 3**). Owing to the complexity of the genetic basis for infection characteristics, it is unlikely that clinical parameters can be attributed to variation in a single genetic factor. Furthermore, contradictory results are not unexpected. As age and mother-to-child transmission of HBV infection have great impacts (Li et al., 2015), host genetic factors are usually not the only determinants for chronic HBV infection, HBV intrauterine infection, its clinical outcome, or antiviral therapies.

Owing to the complexity of the pathogenesis of HBV, future studies should apply strict criteria for patient selection and for the selection of matched controls according to various factors, like age, route of transmission, time of infection, race, and host immune status, to identify relevant host factors. It is also necessary to standardize the diagnosis of HBVrelated diseases. Results should be verified using different ethnic groups and confirmed by future controlled studies with large sample sizes as well as meta-analyses. Importantly, understanding the biological functions of candidate genetic markers is essential to gain mechanistic insight into HBVrelated diseases.

At the moment, genetic markers associated with host responses to HBV infection/vaccines and HBV-related diseases could be classified into three categories according to the quality of studies. Some markers, like human HLAs, are clearly important determinants of HBV pathogenesis and the response to HBV vaccines. However, the precise functions of these loci in HBV infection are unclear. For example, the immunological effects of genetic variation in HLAs are not obvious, though these mutations are likely to contribute to HBV-specific immunity.

Future research should consider interactions between genetic factors and other factors, including viral genotypes/subtypes, population characteristics, other genes, and environmental factors (**Table 1**; **Table S1**). Additional candidate genes that may play a role in the pathogenesis of HBV require confirmation by large-scale, multi-center validation studies. In these future studies, it will be important to stratify populations, match samples, and choose appropriate control groups to improve the reliability of results (**Table 1**; **Table S1**). Additional candidate genes with unconfirmed relevance owing to small samples sizes and studies with different designs should be evaluated by future controlled studies with suitable study subjects and meta-analyses (**Table 1**; **Table S1**).

Recently, our understanding in HBV infection and pathogenesis is fast growing. The knowledge about the molecular and physiological mechanisms of HBV pathogenesis will help us to improve future study design and develop better criteria for patient recruitment. New diagnostic methods like quantitative HBsAg and anti-HBc assays may provide more information to select suitable patient cohorts. The development of genomic and proteomic analysis tools will also enable us to define novel parameters—for example, at the level of single cells or protein chemistry, thereby opening new ways to define genetic determinants for HBV pathogenesis.

# AUTHOR CONTRIBUTIONS

ZZ and CW reviewed the literature. ZZ, CW, ZL, and GZ wrote the manuscript. JL and ML participated in the coordination of the study and manuscript modification. ML conceived the project. All authors contributed, read, and approved the manuscript.

# FUNDING

This work was supported by the Natural Science Foundation of Anhui Province (Grant no. 1608085MH162).

# SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgene.2019.00696/ full#supplementary-material

# REFERENCES

to hepatitis B virus infection: a meta-analysis. *Gene* 525, 35–40. doi: 10.1016/j. gene.2013.04.065

hepatocellular carcinoma in a hyperendemic area for hepatitis B virus infection. *Cancer* 86, 1143–1150. doi: 10.1002/(SICI)1097-0142(19991001)86:7<1143:: AID-CNCR7>3.0.CO;2-Z

PD-L1 blockade in chronic hepadnaviral infection. *PLoS Pathog.* 10, e1003856. doi: 10.1371/journal.ppat.1003856

hepatitis B in a Korean population. *Liver Int.* 37, 354–361. doi: 10.1111/ liv.13245

virus and the risk of chronic infection in a multiethnic population. *Liver Int.* 37, 1476–1487. doi: 10.1111/liv.13405

interferon-alpha treatment in chronic hepatitis B patients. *Antiviral Res.* 83, 252–256. doi: 10.1016/j.antiviral.2009.06.003

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Copyright © 2019 Zhang, Wang, Liu, Zou, Li and Lu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Large-Scale "OMICS" Studies to Explore the Physiopatholgy of HIV-1 Infection

#### *Sigrid Le Clerc1, Sophie Limou2,3,4\* and Jean-François Zagury1\**

*1 Laboratoire GBCM, EA7528, Conservatoire National des Arts et Métiers, HESAM Université, Paris, France, 2 Centre de Recherche en Transplantation et Immunologie UMR1064, INSERM, Université de Nantes, Nantes, France, 3 Institut de Transplantation en Urologie et Néphrologie (ITUN), CHU de Nantes, Nantes, France, 4 Computer Sciences and Mathematics Department, Ecole Centrale de Nantes, Nantes, France*

In this review, we present the main large-scale experimental studies that have been performed in the HIV/AIDS field. These "omics" studies are based on several technologies including genotyping, RNA interference, and transcriptome or epigenome analysis. Due to the direct connection with disease evolution, there has been a large focus on genotyping cohorts of well-characterized patients through genome-wide association studies (GWASs), but there have also been several *in vitro* studies such as small interfering RNA (siRNA) interference or transcriptome analyses of HIV-1–infected cells. After describing the major results obtained with these omics technologies—including some with a high relevance for HIV-1 treatment—we discuss the next steps that the community needs to embrace in order to derive new actionable therapeutic or diagnostic targets. Only integrative approaches that combine all big data results and consider their complex interactions will allow us to capture the global picture of HIV molecular pathogenesis. This novel challenge will require large collaborative efforts and represents a huge open field for innovative bioinformatics approaches.

### *Edited by:*

*Dana C. Crawford, Case Western Reserve University, United States*

#### *Reviewed by:*

*Paul J. McLaren, Public Health Agency of Canada (PHAC), Canada Eric O. Johnson, RTI International, United States*

#### *\*Correspondence:*

*Sophie Limou<EMAIL_ADDRESS>Jean-François Zagury<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Applied Genetic Epidemiology, a section of the journal Frontiers in Genetics*

*Received: 30 January 2019 Accepted: 30 July 2019 Published: 13 September 2019*

#### *Citation:*

*Le Clerc S, Limou S and Zagury J-F (2019) Large-Scale "OMICS" Studies to Explore the Physiopatholgy of HIV-1 Infection. Front. Genet. 10:799. doi: 10.3389/fgene.2019.00799*

Keywords: HIV, genome-wide association study, genomics, omics, big data

# INTRODUCTION

HIV remains a major global public health issue, having claimed more than 35 million lives so far. In 2017, 940,000 people died from HIV-related causes globally (Global AIDS Update, 2016). The active anti-retroviral therapies are efficient and have saved many lives but still present multiple caveats: need for high compliance, permanent treatment, and unwanted side effects and complications (Li et al., 2017). Developing alternative and simple solutions such as immunoprophylactic or immunotherapeutic options remains a public health priority. In line with this, a better understanding of the molecular etiology of disease progression is essential.

Due to the impact of the disease in the Western world, HIV research has been the subject of intense efforts for the past 35 years and has helped in promoting several new research technologies, in particular with high-throughput studies from the "omics" era.

In this review, we will present large-scale studies based on various technologies that have been undertaken to tackle HIV molecular etiology and their main results. These large-scale studies encompass mainly genomics with genome-wide association studies (GWASs) based on genotyping chips and with exome sequencing, transcriptomic studies from SIV and HIV patient

**273**

cells, and small interfering RNA (siRNA) studies in sensitive cell lines. We will also briefly describe the results obtained from proteomics and epigenomics screenings.

# A SHORT RECALL ON HIV-1 INFECTION AND MARKERS

There are three successive stages in HIV infection: the acute primary infection, the asymptomatic stage and symptomatic HIV infection, and acquired immunodeficiency syndrome (AIDS). Depending on the individual, AIDS, the most advanced stage of the infection course, can occur within a few months to several years after HIV infection, with an average of around 8 years in the Western world. This stage has been defined by the Center for Disease Control (CDC) either as a drop of CD4 T-cell count below 200/mm3 or as the appearance of opportunistic infections or some cancers (Center for Disease Control and Prevention, 1992). Quite early, AIDS cohorts were enrolled and prospectively followed, and it became apparent that this infection was exhibiting a considerable phenotypic heterogeneity at different levels: virus acquisition, disease progression, viral load control, and response to treatment (Langlade-Demoyen et al., 1994; Ludlam et al., 1985; Fowke et al., 1996; Pantaleo and Fauci, 1996; Hetherington et al., 2002; Mallal et al., 2002; Saksena et al., 2007). For instance, some individuals, called long-term nonprogressors, are infected but never progress to AIDS; the elite controllers have never exhibited any detectable viral load; and the rapid progressors reach the AIDS stage within a few months following their infection. This phenotypic variability may be attributed to a complex interplay between viral, environmental, and host genetic factors that could be investigated through several types of large-scale studies or omics.

If the CD4 cell count was the major marker to follow HIV-1 infection and immune deficiency in patients in the early 1980s, the progress of molecular biology techniques has made it possible to measure precisely HIV-1 viral load in the blood (i.e., the number of viral particles present in each ml of serum) by the late 1990s. Together with the CD4 cell count, this marker has become very useful to evaluate the status of an infected patient, either a low viral load suggesting a good control of HIV-1 infection or a high viral load suggesting a progressive infection at an early stage of infection or an uncontrolled infection at a late disease stage (AIDS). Most cohorts focus on viral load outcomes (e.g., viral control, viral load at set point), but (slow and rapid) progression phenotypes have also been defined based on the CD4 counts (e.g., the GRIV cohort).

## GENETIC ASSOCIATION STUDIES

Host genes associated with various phenotypes have been extensively explored since the mid-1990s. The concept is as follows: if a particular phenotype (for instance, elite control) is statistically associated with the presence or absence of a genetic variant, the corresponding gene or its product may be involved in the molecular mechanisms of viral infection/ dissemination. Genetic association studies can thus provide new clues on the molecular mechanisms of infection and disease progression and, in the long run, identify new targets for the development of new therapeutic or diagnostic strategies. Initial studies have focused on candidate genes such as *HLA* (Kaslow et al., 1996; Carrington et al., 1999; Hendel et al., 1999), and a large number of host genetic associations with HIV outcomes have been identified. The main confirmed association was a 32-base-pair deletion in the *CCR5* gene (*CCR5-Δ32*) (Dean et al., 1996; Liu et al., 1996; Samson et al., 1996; Rappaport et al., 1997), but other variants closely located in the *CCR5* promoter (Martin et al., 1998; McDermott et al., 1998) or in the nearby *CCR2* gene (Smith et al., 1997) were also influential. This deletion led to the expression of a truncated and non-functional cell surface CCR5 protein that happened to be the major HIV-1 entry co-receptor (Alkhatib et al., 1996; Deng et al., 1996; Liu et al., 1996). Other candidate gene studies pointed to immunityrelated genes (e.g., *KIR*, *IL10*, *IFNγ*) and genes encoding HIV restriction factors (e.g., *CCL5*, *APOBEC3G*, *CUL5*) but were only partially replicated according to the phenotype and cohort tested. The functional interpretation for most of these variants is yet to be discovered, but the detailed account of each candidate gene is beyond the scope of this article and has been covered by previous enlightening reviews (Fellay, 2009; An and Winkler, 2010). Overall, most of the candidate gene associations displayed small to modest effect sizes and, combined all together, account for a small fraction of the phenotype variability (O'Brien and Nelson, 2004).

## GENOME-WIDE ASSOCIATION STUDIES

It was only in 2007 that the first large-scale genetic association studies or GWASs have been published with the seminal publication by Fellay et al. that focused mainly on viral load at set point as the main phenotype of interest (Fellay et al., 2007). These large-scale genomic studies have relied on genotyping chips targeting simultaneously hundreds of thousands to millions of specific genetic markers called single nucleotide polymorphisms (SNPs), the most frequent polymorphisms in the human genome, that can be rapidly and easily genotyped. In contrast to the candidate gene strategy, this approach measures and analyzes gene variants across the whole human genome in an effort to identify common genetic risk factors in the population without any biological hypothesis *a priori*. Since the 2007 publication, GWASs have taken the place of candidate gene studies in AIDS. More than 20 GWASs focusing on various phenotypes and cohorts have been published, and **Table 1** summarizes these studies with their main characteristics (see also (Limou and Zagury, 2013)): date of the publication, origin of the cohort, size of the cohort, phenotype(s) of interest, genotyping chip type, associated SNP(s), best P-value, possible causing gene(s) involved, and publication reference number.

TABLE 1 | GWASs published in the AIDS field since 2007. 5×10−8 is the standard threshold for considering an association as significant in a GWAS, and the significant ones in the table are in bold.

*CTR, controls*

The following major conclusions can be underlined from these GWA studies:

consortium that mainly focused on viral control. Finally, the absence of replication for many other signals presented in **Table 1** does not discount their scientific interest but complicates their biological interpretation.

### NEXT-GENERATION SEQUENCING STUDIES

GWASs rely on common SNPs (typically >1% in the population) and hardly take into account the possible effect of rare variants or other classes of genetic polymorphisms such as indels or copy number variants that can also significantly impact disease outcome. To investigate the impact of such variants, we first focused on low-frequency SNPs (<5%) in our progression GWASs and identified the gene *RICH2* associated with non-progression, which interacts with BST-2, a major known HIV restriction factor (Le Clerc et al., 2011). Later, several studies based on nextgeneration sequencing (NGS) have emerged. Due to the high cost of such studies and to maximize statistical power of detection, these screenings have targeted coding variants (exome) and patients with very specific and extreme disease outcome. To our knowledge, only one publication has emerged from these studies (McLaren et al., 2017), which focused on 1,327 subjects, many of whom were elite and viral controllers. In spite of the significant number of patients studied, only variants in the *HLA* region came out, and this study suggested that exonic variants with large effect sizes are unlikely to have a major contribution to host control of HIV infection (McLaren et al., 2017).

### FUNCTIONAL GENOMIC SCREENINGS

Systematic inactivation of gene expression through siRNA and small hairpin RNA (shRNA) offers a unique chance to identify host genes required for HIV replication. In large-scale studies, authors used siRNAs (Brass et al., 2008; Konig et al., 2008; Zhou et al., 2008) or shRNAs (Yeung et al., 2009) to silence *in vitro* most known genes one by one in HIV permissive cell lines. These screenings identified 273 (Brass et al., 2008), 213 (Konig et al., 2008), 311 (Zhou et al., 2008), and 252 (Yeung et al., 2009) HIV host dependency factors, respectively, for a total of 842 putative candidates. However, the overlap between the different studies was very low, suggesting low reproducibility and/or high false positive, which might not be surprising considering the different experimental models (cell lines, HIV strains, and measurement modes of HIV replication). Overall, these studies still provide an interesting list of candidate cellular factors and pathways potentially implicated in HIV-1 replication that could be considered as relevant targets for drug development.

The development of the CRISPR–Cas9 technology to screen each gene with a library of single-guided RNA offers a greater sensitivity and specificity than interference based-RNA (Wang et al., 2014). A recent report used this technology to screen a CD4 T-cell line and identified five host factors required for HIV replication, including CD4, C-C motif chemokine receptor 5 (CCR5), and activated leukocyte cell adhesion molecule (ALCAM (Park et al., 2017). These factors were further validated in primary human CD4 T-cells and therefore represent major candidates for a therapeutic intervention.

# TRANSCRIPTOMIC STUDIES

The first descriptions of transcriptome analysis by DNA microarrays were in cancer in 2002 (Pomeroy et al., 2002; van 't Veer et al., 2002). In AIDS, the first large-scale transcriptomic study (4,600 transcripts) was published in 2003 (van 't Wout et al., 2003). This study analyzed gene expression in HIVinfected CD4 T-cell lines at different time points and revealed the inhibition of genes involved in cell division, transcription, translation, splicing, and also cholesterol biosynthesis (van 't Wout et al., 2003). An exon transcriptome microarray analysis of purified HIV-infected cells revealed host cell factors required for viral replication and alternative splicing events (Imbeault et al., 2012). A bioinformatic analysis of HIVresistant activated CD4 T-cells (due to CD3/CD28 antibodies' co-stimulation) highlighted a few dozen genes critical for resistance or permissivity (Xu et al., 2013).

Several microarray studies focused on non-human primate models, such as cynomolgus monkeys (Bosinger et al., 2004) and African green monkeys (non-pathogenic model) vs. rhesus macaques (pathogenic model) (Jacquelin et al., 2009). These reports mainly identified a major role for IFN-stimulated genes, as well as a differential expression of some innate genes (such as LPS receptors CD14 and TLR4) and some apoptosis-related genes (Bosinger et al., 2004).

Finally, numerous transcriptome studies explored differential gene expression in HIV-infected individuals. A first report in 2005 claimed to have found (Ockenhouse et al., 2005) a 10-gene signature for HIV-1 serostatus and a 6-gene signature for subjects experiencing a CD4+ T-cell decrease (Ockenhouse et al., 2005). The genes identified were primarily linked with immune response and apoptosis, mitochondrial function, and RNA binding (downregulated in subjects with better prognosis) (Ockenhouse et al., 2005). A study focusing on HIV-1–resistant individuals (Huang et al., 2011) found a set of 185 HIV-1 resistance genes, suggesting a major role for *nef* in disease pathogenesis, and among them pointed out 29 potential targets for AIDS prevention or therapy (Huang et al., 2011). By comparing the complementary DNA (cDNA) profiles of CD3+ T-cells in long-term non-progressors vs. medium progressors (Salgado et al., 2011), 325 genes appeared over-expressed in regular progressors (from DNA replication, cell cycle, and DNA damage pathways), vs. 136 over-expressed genes in long-term non-progressors (from cytokine–cytokine receptor interaction and negative control of apoptosis pathways) (Salgado et al., 2011). The transcriptome comparison of CD4+ T-cells and CD8+ T-cells from rapid progressors, viremic non-progressors, and elite controllers showed a lower expression of IFN-stimulated genes and an upregulation of *CASP1*, *CD38*, *LAG3*, *TNFSF13B*, *SOCS1*, and *EEF1D* genes in viremic non-progressors (Rotger et al., 2011). Finally, a transcriptomic screening also targeted miRNA expression profiles in peripheral blood mononuclear cell (PBMC) from rapid and chronic progressors and identified five downregulated miRNAs in rapid progressors that all converged to the apoptosis pathway (Zhang et al., 2013).

# PROTEOMIC AND EPIGENOMIC STUDIES

Some proteomic studies have also been performed, but they were not very reproducible, as indicated in a recent review by Donnelly and Ciborowski (2016). To our knowledge, few epigenomic studies have been published to date in HIV/AIDS. One Korean group performed two chromatin immunoprecipitation sequencing (ChIPseq) analyses in HIV latently infected CD4 T-cell lines to investigate the impact of H3K4me3 and H3K9ac histone modifications on latency. They revealed several potential candidate genes, including *NFIX*, tumor necrosis factor (TNF) receptor association factor 4 (*TRAF4*), and cell cycle regulating genes such as *CDKN1A* (p21) and *CCND2* (Park et al., 2014; Kim et al., 2017). Finally, the blood DNA methylation signatures of HIV-infected and uninfected subjects were compared through an epigenome-wide association study (EWAS), which highlighted a down-methylation of *NLC5* promoter in HIV-infected subjects (Zhang et al., 2016). This host gene encodes a key regulator of class I *HLA* gene expression and confirms the major role of the *MHC* locus in HIV viral control. Interestingly, *NLC5* promoter and additional *MHC* clusters also appeared differentially methylated in HIV–Hepatitis C virus (HCV) co-infected subjects (Zhang et al., 2017), emphasizing the importance of inflammation-related genes in the course of HIV infection. Overall, these studies are promising and underline the need for additional large-scale epigenetic studies in order to better capture the breadth of host–HIV complex interactions.

# CONCLUSION AND FUTURE DIRECTIONS

In this review, we have presented numerous large-scale genomic and transcriptomic analyses that have taken place in the AIDS field, which are the consequences of the progress in molecular biology and biochemistry technologies. One can see that a huge research effort has been dedicated to genetic association studies, and this is logical since this experimental approach deals with real *in vivo* data, i.e., cohorts of patients and HIV-1 infection *in vivo*. Nevertheless, it was slightly surprising to observe that the main signals found by GWAS, in the *HLA* and *CCR5* loci, had already been identified by previous candidate gene approaches. This apparent limitation could be explained by the yet-unidentified role of other polymorphisms such as copy number variations (CNVs) or interacting gene variants. It could also be explained by the statistical constraints (such as stringent multiple testing corrections) that limit the use of genetic association data (numerous false negatives) and the overall low number of samples at stake (a few thousands) compared to other human diseases such as diabetes or obesity (hundreds of thousands) (Shungin et al., 2015; Fuchsberger et al., 2016). In light of the available biological information provided by the other large-scale studies such as transcriptomic or functional genomic studies presented in this review, it appears important to reanalyze the genomic data by integrating biological information in order to enhance the genetic association results. For instance, our group has successfully implemented such approaches by pre-selecting relevant SNPs defined either by their low frequency (Le Clerc et al., 2011) or by their functional impact as potential expression quantitative trait loci (eQTLs) (Spadoni et al., 2015). More generally, there are several methods for data integration, the first one being to cross-check the results obtained by one method through another, for instance, using GWAS to identify SNPs with low P-values, even nonsignificant, and then using transcriptomics to pick genes that are differentially expressed in a relevant cell type or tissue. By combining two (or more) methods, researchers can zoom in on specific genes of high interest. This has been implemented with the development of PrediScan (Gamazon et al., 2015). Another example of cross-checking is the results obtained by metabolome analysis and GWAS in which the researchers have found that metabolites present at high levels in the blood of some subjects are highly correlated with specific variants present in the genes of enzymes involved in their metabolism (Illig et al., 2010). Other methods of data integration rely on rescuing genes by correlating signals not only at the gene level but also at the pathway level: for instance, one can suspect that if a gene X in a biological pathway is important for a clinical phenotype, the genes present upstream in the biological pathway may impact this gene X expression and, as a consequence, also become targets of interest. One will thus have to look for cross-checks at the level of pathways (Chen et al., 2011). Importantly, it is essential for data integration to perform all these cross-checks in a smart and automated manner. Finally, more sophisticated statistical approaches have recently emerged outside of the HIV field, such as

### REFERENCES

the Bayesian method for data integration (Kichaev et al., 2014; Pickrell, 2014; Finucane et al., 2015; Yang et al., 2017; International Multiple Sclerosis Genetics Consortium, 2019). These new methods are yet to be implemented in the relatively small HIV/AIDS cohorts but might reveal novel underlying physiopathological mechanisms.