- Email: [email protected]
The influence of gene-chronic hepatitis C virus infection on hepatic fibrosis and steatosis
Journal Pre-proof The influence of gene-chronic hepatitis C virus infection on hepatic fibrosis and steatosis
Mariana Cavalheiro Magri, Caroline Manchiero, Thamiris Vaz Gago Prata, Arielle Karen da Silva Nunes, José Santos de Oliveira Junior, Bianca Peixoto Dantas, Fátima Mitiko Tengan PII:
S0732-8893(19)31018-1
DOI:
https://doi.org/10.1016/j.diagmicrobio.2020.115025
Reference:
DMB 115025
To appear in:
Diagnostic Microbiology & Infectious Disease
Received date:
10 October 2019
Revised date:
24 January 2020
Accepted date:
14 February 2020
Please cite this article as: M.C. Magri, C. Manchiero, T.V.G. Prata, et al., The influence of gene-chronic hepatitis C virus infection on hepatic fibrosis and steatosis, Diagnostic Microbiology & Infectious Disease(2020), https://doi.org/10.1016/ j.diagmicrobio.2020.115025
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2020 Published by Elsevier.
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The influence of gene-chronic hepatitis C virus infection on hepatic fibrosis and steatosis
Word count of the abstract: 149 Word count of the text: 3235
Mariana Cavalheiro Magri a, Caroline Manchieroa, Thamiris Vaz Gago Prataa,
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Arielle Karen da Silva Nunesa, José Santos de Oliveira Junior a, Bianca Peixoto
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Dantasa, Fátima Mitiko Tengana,b
a
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Laboratorio de Investigacao Medica em Hepatologia por Virus (LIM-47),
Paulo, Sao Paulo, SP, BR.
Pr
Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao
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Address: Av. Dr. Eneas de Carvalho Aguiar, 470 - Instituto de Medicina
b
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05403-000.
rn
Tropical - Predio 2. Bairro Cerqueira César. Sao Paulo, SP, Brazil. CEP
Departamento de Molestias Infecciosas e Parasitarias, Faculdade de
Medicina, Universidade de Sao Paulo, Sao Paulo, SP, BR. Address: Av. Dr. Eneas de Carvalho Aguiar, 470 - Instituto de Medicina Tropical - Predio 1. Bairro Cerqueira Cesar. Sao Paulo, SP, Brazil. CEP 05403-000.
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Email: Mariana Cavalheiro Magri - [email protected] Caroline Manchiero - [email protected] Thamiris Vaz Gago Prata - [email protected] Arielle Karen da Silva Nunes - [email protected] José Santos de Oliveira Junior - [email protected] Bianca Peixoto Dantas - [email protected]
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Fátima Mitiko Tengan - [email protected]
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Corresponding author
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Mariana Cavalheiro Magri
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Laboratorio de Investigacao Medica em Hepatologia por Virus (LIM-47), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao
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Paulo, Sao Paulo, SP, Brazil.
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Address: Av. Dr. Eneas de Carvalho Aguiar, 470 - Instituto de Medicina Tropical
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- Predio 2. Bairro Cerqueira Cesar. Sao Paulo, SP, Brazil. CEP 05403-000. Phone: +55 11 30617031 Fax: +55 11 30851601 E-mail: [email protected]
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Abstract Host single nucleotide polymorphisms (SNPs) in different genes can play a role in chronic hepatitis C virus (HCV) infection, and influence the presence of hepatic fibrosis and comorbidities such as hepatic steatosis. We assessed the combined effect of SNPs in the PNPLA3, MTTP, TM6SF2 and IFNL3/IFNL4 genes in 288 Brazilian patients who were chronically infected with HCV. Hepatic fibrosis was observed in 246 (85.4%) patients and hepatic steatosis in 141
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(49.0%) patients. PNPLA3 rs738409 (CG/GG) (p=0.044) and TM6SF2 rs58542926 (CT) (p=0.004) were alone associated with fibrosis, and PNPLA3
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rs738409 (p<0.05, in distinct genetic models) was associated with steatosis.
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Multiple logistic regression of each SNP combined with HCV genotype 3
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infection showed that MTTP rs1800591 (GT/TT) combined with HCV genotype 3 was associated with a 6.72-fold increased chance of hepatic steatosis
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(p=0.013). In the analysis of SNPs combined two by two, no influence on
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hepatic fibrosis or steatosis was observed.
Keywords: hepatitis C, single nucleotide polymorphisms (SNPs), interferon lambda 3 and 4 (IFNL3/IFNL4), microsomal triglyceride transfer protein (MTTP), patatin-like phospholipase domain containing 3 (PNPLA3), transmembrane six superfamily member 2 (TM6SF2).
Abbreviations:
ALT,
alanine
aminotransferase;
AST,
aspartate
aminotransferase; BMI, body mass index; CHC, chronic hepatitis C; CI, confidence interval; DAAs, direct acting antivirals; GGT, gamma glutamyl transpeptidase; HCV, hepatitis C virus; HCC, hepatocellular carcinoma; HOMA-
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IR, homeostasis model assessment of insulin resistance; IFNL3/IFNL4, interferon lambda 3 and 4; IL28, interleukin-28B; MTTP, microsomal triglyceride transfer protein; NAFLD, non-alcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; OR, odds ratio; PCR-RFLP, polymerase chain reactionrestriction fragment length polymorphism; PNPLA3, patatin-like phospholipase domain containing 3; SNPs, single nucleotide polymorphisms; TM6SF2,
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transmembrane six superfamily member 2; WHO, World Health Organization.
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1. Introduction
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The study of single nucleotide polymorphisms (SNPs) in different genes
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has been increasingly relevant in the clinical field, as they can play an important role in the development of various diseases in different population groups [1,2].
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Recent studies have evaluated the role of SNPs related to patients with chronic
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hepatitis C virus (HCV) infection, as this infection affects approximately 71
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million individuals worldwide and its evolution over the years, is characterized by persistent and progressive inflammation in the liver, and may lead to hepatocellular carcinoma (HCC) if proper treatment is not administered [3]. Several studies have described associations of SNPs with the development of chronic hepatitis C (CHC) and have evaluated their influence on the presence of hepatic fibrosis, hepatic steatosis, and with spontaneous viral clearance [4-9]. Recent data have shown that the development and progression of hepatic fibrosis in CHC is multifactorial and that host factors may influence it. Relevant host factors include age; gender; behavioural aspects such as alcoholism and smoking; metabolic aspects such as hepatic steatosis, insulin
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resistance, diabetes and obesity; and, importantly, host SNPs [10,11]. SNPs in interferon lambda 3 and 4 (IFNL3/IFNL4), initially christened interleukin-28B (IL28B), appear to worsen the natural course of disease in patients with CHC [12]. Although a study with 2,335 chronically HCV-infected patients associated IFNL3/IFNL4 rs8099917 with slower fibrosis progression [9]. SNPs in other genes, such as patatin-like phospholipase domain containing 3 (PNPLA3) and the transmembrane six superfamily member 2 (TM6SF2), have been associated
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with advanced hepatic fibrosis [6,7]. Chronic HCV infection is also known to cause some comorbidities, such as hepatic steatosis, present in approximately
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half of these patients. Moreover, the presence of hepatic steatosis due to
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metabolic syndrome is associated with accelerated hepatic fibrosis progression
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and risk for HCC [10,13]. SNPs in genes such as PNPLA3, TM6SF2 and microsomal triglyceride transfer protein (MTTP) have been shown to impact
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lipoprotein and lipid secretion and predispose individuals with and without HCV
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infection to hepatocyte triglyceride accumulation, the hepatic steatosis [5,7,13-
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16]. A recent review mentioned genetic factors that contributes to development and progression of non-alcoholic fatty liver disease (NAFLD), a growing epidemic disease ranging from isolated hepatic steatosis to HCC, summarized that the NAFLD development is related with several relevant SNPs in genes such as PNPLA3, TM6SF2, glucokinase regulator (GCKR), oacyltransferase domain-containing 7 (MBOAT7), hydroxysteroid 17-beta dehydrogenase 13 (HSD17B13), among others [17]. The HSD17B13 rs72613567 SNP, for example, has also been associated with protection against hepatic fibrosis in HCV infected patients [18].
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Many of the associations described above are not yet fully established, and some SNPs may not have independent roles. In 2016, Trépo et al. [19], considering liver disease in clinical practice, discussed that evaluating a single SNP alone may have a limited predictive value. However, few studies have evaluated combined effect of SNPs [20-22]. A significant association between SNPs could possibly represent a protective effect or a higher chance for development of clinical consequences, such as hepatic fibrosis and steatosis, in
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some cases. Therefore, the present study was conducted to evaluate the potential combined effect of six selected SNPs in the PNPLA3, MTTP, TM6SF2
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and IFNL3/IFNL4 genes in hepatic steatosis and hepatic fibrosis associated
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2.1. Study subjects
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2. Materials and Methods
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with CHC patients.
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A total of 288 patients chronically infected with HCV were evaluated at the HCFMUSP from January 2010 to December 2015. Eligibility criteria were age ≥ 18 years, positive anti-HCV antibody, HCV-RNA presence for more than 6 months and having undergone liver biopsy prior to specific antiviral therapy. The exclusion criteria were hepatitis B virus (HBV) or human immunodeficiency virus (HIV) coinfection and other etiologies in the liver.
2.2. Data collection The epidemiological factors collected included age, gender, body mass index (BMI) (calculated as weight divided by height squared) and alcohol
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consumption. The serum biochemical tests collected to better describe the study population were gamma glutamyl transpeptidase (GGT), alanine aminotransferase (ALT), aspartate aminotransferase (AST), insulin and glucose. Based on data from the insulin secretion and fasting glucose of the patients, the HOMA-IR index (homeostasis model assessment of insulin resistance) was calculated. The HCV genotypes were also collected. Histological assessment of liver fragments was performed as follows:
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hepatic steatosis was assessed and graded on a scale from 0 to 3 as described by Kleiner et al. [23]. The hepatic fibrosis stage and inflammatory activity of the
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liver were scored using the Metavir system [24]. Histological examination was
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performed by two experienced pathologists.
2.3. SNP genotyping
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The polymorphisms rs738409 of the PNPLA3 gene and rs1800591 of the
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MTTP gene were genotyped by polymerase chain reaction-restriction fragment
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length polymorphism (PCR-RFLP) as described in previous studies of our group [25,26]. The polymorphisms rs2294918 of PNPLA3, rs58542926 of TM6SF2, rs8099917 and rs12979860of IFNL3/IFNL4 were genotyped by real-time PCR using the TaqMan genotyping assay system on a Step One Plus Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). The TaqMan genotyping
assays
performed
rs58542926
assay
ID
C_89463510_10,
rs2294918 assay ID C_2520500_10, rs8099917 assay ID C_11710096_10 and rs12979860 assay ID C_7820464_10 (Applied Biosystems, Foster City, CA, USA). The interpretation of genotypes is presented in Table 1.
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2.4. Statistical analysis Patient characteristics were evaluated according to the genotypes of each SNP. Qualitative characteristics were described using absolute and relative frequencies and the association was verified using of χ2 test or exact tests (Fisher's exact test or likelihood ratio test). Quantitative characteristics were described as the mean and standard deviation and compared using tStudent tests [27]. Hardy-Weinberg equilibrium between expected and
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observed genotype distributions of each SNP was estimated by the χ2 test. The association of each SNP with the occurrence of hepatic fibrosis and
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steatosis was estimated by odds ratio (OR) and 95% confidence interval (CI)
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and bivariate tests using simple logistic regression [28]. Each SNP was
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analysed with the co-dominant, dominant and recessive genetic models. The co-dominant model considers the three genotypes separated. The dominant
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model considers the homozygous wild-type vs. the heterozygous and
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homozygous mutated-type together, and the recessive model considers the
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homozygous wild-type and heterozygous together vs. the homozygous mutated-type. Significance in any of the three genetic models was considered as a possible association of the SNPs with hepatic fibrosis or hepatic steatosis in CHC.
A multiple logistic regression model adjusted for the potential confounders age, gender, BMI and alcohol consumption was used to analyse of each SNP (dominant model) combined with HCV genotype 3 infection, and the combined effect of independent SNPs (two by two) on the presence of hepatic fibrosis and steatosis [28]. The multiple logistic regressions were also adjusted for PNPLA3 rs738409 (genotype CG/GG), whose risk of hepatic steatosis is
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better established. The significance level was considered less than 0.05 (p<0.05) for all analyses. Data were analysed with IBM-SPSS for Windows v.20.0.
3. Results
3.1 Characteristics of the study subjects
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The mean age of all 288 participating patients chronically infected with HCV was 54.9 years, 56.9% were female, and 37.2% of the patients were
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underweight. The mean liver enzyme serum levels were 83.4 ± 92.3 U/L for
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GGT, 62.3 ± 49.5 U/L for ALT and 49.7 ± 38.2 U/L for AST. The mean serum
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levels of glucose were 91.5 ± 39.5 mg/dL, insulin was 15.2 ± 32.3 µU/mL, and the calculated HOMA-IR was 3.4 ± 6.4. Regarding the characteristics of the
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anatomopathological study of the liver fragment, we highlight that inflammatory
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activity was observed in 285 (98.9%) of the patients, fibrosis in 246 (85.4%),
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and steatosis in 141 (49.0%). HCV genotype 1 was present in 78.9% of CHC patients, followed by genotype 3 in 15.8% of CHC patients and other genotypes in only 5.2% of CHC patients (Table S1, supplementary material).
3.2 SNPs All samples from patients with CHC included in the study were genotyped for the six SNPs as shown in Table 1, with the exception of PNPLA3 rs2294918 in which it was possible to only genotype 270 instead of 288. The frequencies of the mutated alleles of each SNP were calculated and the frequency for PNPLA3 rs738409 was 0.43, PNPLA3 rs2294918 was 0.09, MTTP rs1800591 was 0.33,
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TM6SF2 rs58542926 was 0.05, IFNL3/IFNL4 rs8099917 was 0.34, and IFNL3/IFNL4 rs12979860 was 0.57. The genotype distributions of the SNP MTTP rs1800591 and TM6SF2 rs58542926 in the study population were in Hardy-Weinberg equilibrium with values of p=0.859 and p=0.368, respectively. The other SNP distributions deviated from the expected counts according to Hardy-Weinberg equilibrium (p≤0.05) (Table 1). The characteristic of the study population were stratified by the six
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evaluated SNPs genotypes to perform exploratory analyzes. It was observed that few characteristics differed statistically among the SNPs genotypes.
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However, the mean value of BMI differed according to the genotypes of the
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TM6SF2 rs58542926 (p=0.004) and IFNL3/IFNL4 rs12979860 (p=0.034); the
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mean glucose differed according to the genotypes of the MTTP rs1800591 (p=0.034) and the IFNL3/IFNL4 rs8099917 (p=0.046); and the mean GGT also
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differed according to the genotypes of the IFNL3/IFNL4 rs8099917 (p=0.010).
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Advanced fibrosis was statistically associated with the TM6SF2 rs58542926
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genotype CT (p=0.002), while steatosis presence was associated with the PNPLA3 rs738409 genotype CG/GG (p=0.006) (Table S1, Supplementary material).
Furthermore, the association of each SNP alone with the occurrence of hepatic fibrosis was estimated using the co-dominant, dominant and recessive genetic models and is presented in Table 2. Two SNPs were associated with its occurrence: PNPLA3 rs738409 (p=0.044) and TM6SF2 rs58542926 (p=0.004). In relation to the hepatic steatosis, the presence of at least one mutated allele of PNPLA3 rs738409 was associated with steatosis (p<0,05) in the three distinct genetic models (Table 3).
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The occurrence of fibrosis and steatosis was also evaluated by each SNP combined with HCV genotype 3 infection (Table 4). The presence of MTTP rs1800591 (GT/TT genotype) combined with the presence of the HCV genotype 3 was associated with a 6.72-fold increased chance of hepatic steatosis regardless of some patient characteristics (adjusted for age, gender, BMI and alcohol consumption) (p=0.013) and after adjusting also for the PNPLA3 rs738409 the chance of hepatic steatosis increased in patients with
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CHC (odds ratio=8.34; p=0.007).
Finally, the results of multiple logistic regression of the SNPs combined
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two by two that could influence the presence of hepatic fibrosis and steatosis
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are detailed in Table 5. None of the combined SNPs were statistically
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significant regardless of patient characteristics (adjusted for age, gender, BMI
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4. Discussion
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and alcohol consumption) (p>0.05).
In this study, six SNPs (PNPLA3 rs738409, PNPLA3 rs2294918, MTTP rs1800591, TM6SF2 rs58542926, IFNL3/IFNL4 rs8099917 and IFNL3/IFNL4 rs12979860) were evaluated in 288 Brazilian patients with CHC in three distinct genetic models, thus making use of the information available on all genotypes. Subsequently, the combined effects of each SNP with HCV genotype 3 and of the SNPs two by two were analysed in relation to the presence of histologically determined hepatic fibrosis and steatosis. Initially, despite the efficiency of treatment with HCV direct acting antivirals (DAAs), the circulation and transmission of this virus and the progression of hepatic disease continue to
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occur. The World Health Organization (WHO) considers chronic HCV infection a public health issue that affects individuals of all ages, genders and ethnicities, and it leads to approximately 399,000 deaths annually [3]. Thus, the evaluation of genetic factors such as SNPs, which may help us understand the pathogenesis of liver disease and may predict a higher risk of an individual with CHC developing hepatic fibrosis and steatosis, is relevant. Regarding the presence of hepatic fibrosis, in the evaluation of
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independent SNPs in the distinct genetic models, associations of SNPs in the gene PNPLA3 rs738409 (CG/GG genotype) and TM6SF2 rs58542926 (CT
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genotype) with hepatic fibrosis were observed. These findings are in
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accordance with the data of a study that recruited 1,077 CHC patients and
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observed that the PNPLA3 rs738409 (CG/GG genotype) was a factor predictive of advanced hepatic fibrosis [29]. A meta-analysis performed in 2016 comprised
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2,037 CHC patients and revealed that the recessive genetic model of the
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PNPLA3 rs738409 (GG genotype) was significantly associated with higher
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severity of hepatic fibrosis in Caucasians but not Asian populations [6]. A newsworthy Spanish retrospective study evaluated repeated measures of hepatic fibrosis among CHC patients and observed that the G allele of the SNP in PNPLA3 rs738409 was associated with higher hepatic fibrosis progression during a mean follow-up of 49.7 months [30]. The association of the TM6SF2 SNP with advanced hepatic fibrosis was also described in a meta-analysis with 4,325 CHC patients, in which the risk of histologically determined clinically significant fibrosis was increased in carriers of the TM6SF2 rs58542926 (E167K) mutated allele [7]. Similarly, in an Italian cohort with of 815 CHC patients the TM6SF2 rs58542926 was associated with cirrhosis, and in 645
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Swiss/German patients was associated with fibrosis stage F2-F4 [31]. In contrast, Eslam et al. [16] found only a marginal association of the TM6SF2 rs58542926 with fibrosis in CHC patients from the International Liver Disease Genetics Consortium database, and Huang et al. [20] found no independent association of the PNPLA3 rs738409 SNP with hepatic fibrosis in Asian CHC patients. On the other hand, as in the present study, they also found no association between IFNL3/IFNL4 rs8099917 and rs12979860 SNPs with
frequency
of
IFNL3/IFNL4 rs12979860
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fibrosis. Noureddin et al. [32] reported that there was no difference in the genotypes
on
hepatic
fibrosis
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progression between CHC patients. However, Eslam et al. [8] in a study with a
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large cohort including 3,129 CHC patients in which 49.4% had significant
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fibrosis and 73% were infected with HCV genotype 1, the IFNL3/IFNL4 rs12979860 (CC genotype) was strongly associated with hepatic fibrosis. Then,
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in a later study by this same group of researchers the IFNL3/IFNL4 rs12979860
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SNP was used as one of the variables to the development of a fibrosis non-
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invasive prediction model called FibroGENE-DT. This model was even significantly superior to APRI in prediction of cirrhosis and superior to FIB-4 in prediction of fibrosis progression rate [33]. Briefly, other variants in IFNL3/IFNL4 have also been associated with hepatic fibrosis, such as rs4803217 and rs368234815, with similar results to those for the SNP rs12979860 [34]. Therefore, despite the lack of association observed in the present study, SNPs in IFNL3/IFNL4 and interferon (IFN)-λ3 levels seems to be determinants of hepatic fibrosis in CHC patients and also in others non-viral liver diseases [35]. Nevertheless, in accordance with our findings, Petit et al. [36] analysed 86 CHC
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patients and reported that the MTTP functional SNP rs1800591 (-493G/T) in the MTTP gene had no influence on the development of hepatic fibrosis. In the evaluation of the combined effects of each SNP with HCV genotype 3 infection, and of the combined effects independent SNPs (dominant model), no association with the presence of hepatic fibrosis was observed. However, an interesting study was conducted among 416 NAFLD patients without HCV infection who underwent liver biopsy. The PNPLA3 rs738409 and
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TM6SF2 rs58542926 mutated alleles additively increased the risk of nonalcoholic steatohepatitis (NASH) by 2.03-fold and increased the risk of
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significant hepatic fibrosis by 1.61-fold [21]. Recently, Youssef et al. [37]
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evaluated the association of IFNL3/IFNL4 rs8099917 (GG genotype) in
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combination with PNPLA3 rs738409 (GG genotype) on susceptibility and hepatic fibrosis progression in CHC patients infected with HCV genotype 4, and
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considered this combination of mutated genotypes a high-risk signature for
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advanced stage of fibrosis.
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Various studies have shown that SNPs may also predispose people with and without HCV infection to hepatic steatosis. Regarding its presence in CHC patients in the present study, an association of the PNPLA3 rs738409 was found in co-dominant, dominant and recessive genetic models with the presence of hepatic steatosis. Huang et al. [20] found that the PNPLA3 rs738409 (GG genotype) was independently associated with hepatic steatosis in CHC patients from Taiwan. However, the same significance was not independently observed in relation to IFNL3/IFNL4 rs8099917 and rs12979860 SNPs, as in our study. A meta-analysis conducted by Fan et al. [6] revealed that among Caucasian populations with CHC, PNPLA3 rs738409 (GG genotype)
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was associated with the risk of hepatic steatosis. In the present study, the other SNPs were not associated with hepatic steatosis in any evaluated genetic model. Akgöllü and Akkız [38] found no association of the MTTP rs1800591 (493G/T) with the presence of hepatic steatosis in Turkish individuals with HCV genotype 1 infection. Otherwise, Milano et al. [31] detected an association of TM6SF2 rs58542926 (E167K) with more severe steatosis in Italian patients, but when stratified by HCV genotype the association remained in patients not
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infected by genotype 3, but not in those infected by HCV genotype 3. Regarding the influence of IFNL3/IFNL4 rs8099917 and rs12979860 SNPs on hepatic
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steatosis, these relationships have controversial results, and Eslam et al. [39]
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discuss that this may be due to different ethnicities, small sample sizes of the
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studies and local other risk factors for hepatic steatosis. In the evaluation of the combined effects of each SNP with HCV
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genotype 3 infection, an association of the MTTP rs1800591 (GT/TT) combined
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with the HCV genotype 3 with the presence of hepatic steatosis was observed.
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The association of these two combined factors increased the chance of steatosis by 6.72-fold. The study by Zampino et al. [40] showed that patients with HCV genotype 3 and carriers of the mutated allele (T) of MTTP rs1800591 (-493G/T) had more advanced hepatic steatosis and fibrosis in relation to those with the wild allele (G). Of note, it has been widely accepted that viral and host factors are likely to contribute to the development of hepatic steatosis, and the HCV genotype 3 can be an important factor for it. In addition, the persistence of steatosis may prevent complete return to health even in patients treated for HCV [13].
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Otherwise, in the two by two combined SNP analyses, no association was found with the presence of hepatic steatosis. However, studies have shown, also using the dominant model, that the proportion of CHC patients with hepatic steatosis was higher in those with the combined presence of the risk alleles of PNPLA3 rs738409 (CG/GG genotype) and IFNL3/IFNL4 rs12979860 (CT/TT genotype) and in those with the risk alleles of PNPLA3 rs738409 (CG/GG genotype) combined with IFNL3/IFNL4 rs8099917 (TG/GG genotype)
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[20]. In contrast, a recent study among Italian CHC patients showed that the presence of hepatic steatosis was not influenced by the additive effect of MTTP
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rs1800591 (GT/TT genotype) on PNPLA3 rs738409 (GG genotype), but
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PNPLA3 rs738409 alone was associated with steatosis [22].
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Of note, Brazil has a heterogeneous population with diverse patterns of admixture observed by a study of ancestry informative SNPs [41], which may be
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a limitation of the present study and reinforces the need to evaluate the
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frequency and possible associations of each SNP genotype in different
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geographical regions of the world. Additionally, we cannot exclude the possibility that other SNPs in these genes or in other genes may be driving some of the results observed. Nevertheless, to our knowledge, this is the first investigation to explorer the combined effect of these six specific SNPs. Despite the lack of statistically significant association, we believe that in several cases accessing genetic information could help identify patients who might be at risk for liver diseases development.
5. Conclusion
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In conclusion, our findings indicate that PNPLA3 rs738409 and TM6SF2 rs58542926 were alone associated with hepatic fibrosis, and PNPLA3 rs738409 with hepatic steatosis. MTTP rs1800591 combined with HCV genotype 3 robustly increased chance of hepatic steatosis. Otherwise, the combined effect between the SNPs had no influence on hepatic fibrosis and steatosis in a genetic context of Brazilian CHC patients. Additional exploratory researches to test the combined effects of different SNPs are needed to better understand
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their contributions to liver disease.
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Funding
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None.
Conflict of Interest Declaration
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Ethical approval
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None declared.
The study was conducted according to the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the Ethics Committee (Ethics Committee for Research Projects Analysis - CAPPesq) of the Clinical Hospital of the School of Medicine, University of Sao Paulo (HCFMUSP), Brazil, numbers 448.527 and 1.310.147, and written informed consent was obtained from patients participating in the study.
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Table 1. Genotype interpretation for the PNPLA3, MTTP, TM6SF2 and IFNL3/IFNL4 genes. Gene PNPLA3 MTTP TM6SF2 IFNL3/IFNL4
SNP ID number rs738409 rs2294918 rs1800591 rs58542926 rs8099917 rs12979860
Homozygous wild-type (n/%) CC (143/46.5) GG (226/83.7) GG (128/44.4) CC (259/89.9) TT (146/50.7) CC (2/0.7)
Heterozygous (n/%) CG (61/21.2) GA (37/13.7) GT (129/44.8) CT (29/10.1) TG (86/29.9) CT (246/85.4)
Homozygous mutated-type (n/%) GG (93/32.3) AA (7/2.6) TT (31/10.8) TT (0/0) GG (56/19.4) TT (40/13.9)
MAF 0.43 0.09 0.33 0.05 0.34 0.57
HWE, Hardy-Weinberg equilibrium; ID, identification; MAF, minor allele
oo
f
frequency; SNP, single nucleotide polymorphism; p≤0.05 not consistent with
Jo u
rn
al
Pr
e-
pr
HWE
HWE p value* 0.000 0.001 0.859 0.368 0.000 0.000
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29
Table 2. Association of the SNPs in the PNPLA3, MTTP, TM6SF2 and IFNL3/IFNL4 genes and the risk of hepatic fibrosis among patients with chronic hepatitis C in distinct genetic models. Fibrosis SNP genotype
Absent (n=231)
Present (n=58)
OR
Low
Upper
p
0.123 1.00 1.70 1.95
182 (80.2) 45 (19.8) 31 (83.8) 6 (16.2) 6 (85.7) 1 (14.3)
1.00 0.78 0.67
oo
pr
1.00 1.49 0.49
214 (82.3) 46 (17.7) 17 (58.6) 12 (41.4)
1.00 3.28
120 (81.6) 27 (18.4) 68 (79.1) 18 (20.9) 43 (76.8) 13 (23.2)
1.00 1.18 1.34
Pr
e-
105 (82.0) 23 (18.0) 98 (75.4) 32 (24.6) 28 (90.3) 3 (9.7)
al
Jo u
0.79 1.01
3.64 3.80 0.829
f
114 (85.1) 20 (14.9) 47 (77.0) 14 (23.0) 70 (74.5) 24 (25.5)
rn
Co-dominant model PNPLA3 rs738409 CC CG GG PNPLA3 rs2294918 GG GA AA MTTP rs1800591 GG GT TT TM6SF2 rs58542926* CC CT IFNL3/IFNL4 rs8099917 TT TG GG IFNL3/IFNL4 rs12979860 CC CT TT Dominant model PNPLA3 rs738409 CC CG/GG PNPLA3 rs2294918 GG GA/AA MTTP rs1800591 GG GT/TT IFNL3/IFNL4 rs8099917 TT TG/GG IFNL3/IFNL4 rs12979860 CC CT/TT Recessive model PNPLA3 rs738409
95% CI
0.31 0.08
1.99 5.74 0.140
0.82 0.14
2.72 1.75 0.004
1.47
7.34 0.723
0.60 0.64
2.29 2.84 0.999
2 (100.0) 0 (0.0) 197 (79.8) 50 (20.2) 32 (80) 8 (20)
1.00 & &
114 (85.1) 20 (14.9) 117 (75.5) 38 (24.5)
1.00 1.85
182 (80.2) 45 (19.8) 37 (84.1) 7 (15.9)
1.00 0.77
105 (82.0) 23 (18.0) 126 (78.3) 35 (21.7)
1.00 1.27
120 (81.6) 27 (18.4) 111 (78.2) 31 (21.8)
1.00 1.24
2 (100.0) 0 (0.0) 229 (79.8) 58 (20.2)
1.00 &
0.044 1.02
3.37 0.547
0.32
1.83 0.427
0.71
2.28 0.463
0.70
2.21 0.999
0.109
Journal Pre-proof CC/CG GG PNPLA3 rs2294918 GG/GA AA MTTP rs1800591 GG/GT TT IFNL3/IFNL4 rs8099917 TT/TG GG IFNL3/IFNL4 rs12979860 CC/CT TT
161 (82.6) 34 (17.4) 70 (74.5) 24 (25.5)
30 1.00 1.62
0.90
2.94 0.740
213 (80.7) 51 (19.3) 6 (85.7) 1 (14.3)
1.00 0.70
0.08
5.91 0.138
203 (78.7) 55 (21.3) 28 (90.3) 3 (9.7)
1.00 0.40
0.12
1.35 0.513
188 (80.7) 45 (19.3) 43 (76.8) 13 (23.2)
1.00 1.26
0.63
2.55 0.991
199 (79.9) 50 (20.1) 32 (80.0) 8 (20.0)
1.00 1.00
0.43
2.29
oo
f
SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval. Bivariate tests; *The presence of the TM6SF2 rs58542926 mutated genotype
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rn
al
Pr
e-
pr
was not detected.
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31
Table 3. Association of the SNPs in the PNPLA3, MTTP, TM6SF2 and IFNL3/IFNL4 genes and the risk of hepatic steatosis among patients with chronic hepatitis C in distinct genetic models. SNP genotype
OR
80 (59.7) 28 (45.9) 39 (41.5)
1.00 1.75 2.09
95% CI Low
Upper
p
0.018
1.00 1.00 1.74
135 (51.9) 12 (41.4)
125 (48.1) 17 (58.6)
1.00 1.53
82 (55.8) 41 (47.7) 24 (42.9)
65 (44.2) 45 (52.3) 32 (57.1)
1.00 1.39 1.68
2 (100.0) 127 (51.4) 18 (45.0)
0 (0.0) 120 (48.6) 22 (55.0)
1.00 & &
80 (59.7) 67 (43.2)
54 (40.3) 88 (56.8)
1.00 1.95
111 (48.9) 27 (61.4)
116 (51.1) 17 (38.6)
1.00 0.60
67 (52.3) 80 (49.7)
61 (47.7) 81 (50.3)
1.00 1.11
82 (55.8) 65 (45.8)
65 (44.2) 77 (54.2)
1.00 1.49
2 (100.0) 145 (50.5)
0 (0.0) 142 (49.5)
1.00 &
Pr
0.95 1.22
3.22 3.57 0.314
f
61 (47.7) 62 (47.7) 19 (61.3)
al
Jo u
1.00 0.58 0.72
oo
116 (51.1) 14 (37.8) 3 (42.9)
e-
67 (52.3) 68 (52.3) 12 (38.7)
54 (40.3) 33 (54.1) 55 (58.5)
pr
111 (48.9) 23 (62.2) 4 (57.1)
rn
Co-dominant model PNPLA3 rs738409 CC CG GG PNPLA3 rs2294918 GG GA AA MTTP rs1800591 GG GT TT TM6SF2 rs58542926* CC CT IFNL3/IFNL4 rs8099917 TT TG GG IFNL3/IFNL4 rs12979860 CC CT TT Dominant model PNPLA3 rs738409 CC CG/GG PNPLA3 rs2294918 GG GA/AA MTTP rs1800591 GG GT/TT IFNL3/IFNL4 rs8099917 TT TG/GG IFNL3/IFNL4 rs12979860 CC CT/TT Recessive model PNPLA3 rs738409 CC/CG
Steatosis Absent Present (n=147) (n=143)
0.29 0.16
1.19 3.28 0.365
0.61 0.78
1.63 3.88 0.284
0.70
3.33 0.203
0.81 0.90
2.36 3.13 0.754
0.005 1.22
3.11 0.133
0.31
1.17 0.654
0.70
1.77 0.089
0.94
2.38 0.999
0.028 108 (55.4)
87 (44.6)
1.00
Journal Pre-proof GG PNPLA3 rs2294918 GG/GA AA MTTP rs1800591 GG/GT TT IFNL3/IFNL4 rs8099917 TT/TG GG IFNL3/IFNL4 rs12979860 CC/CT TT
39 (41.5)
55 (58.5)
32 1.75
1.06
2.88 0.739
134 (50.8) 4 (57.1)
130 (49.2) 3 (42.9)
1.00 0.77
135 (52.3) 12 (38.7)
123 (47.7) 19 (61.3)
1.00 1.74
123 (52.8) 24 (42.9)
110 (47.2) 32 (57.1)
1.00 1.49
129 (51.8) 18 (45.0)
120 (48.2) 22 (55.0)
1.00 1.31
0.17
3.52 0.156
0.81
3.73 0.183
0.83
2.69 0.425
0.67
2.57
f
SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval.
oo
Bivariate tests; *The presence of the TM6SF2 rs58542926 mutated genotype
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rn
al
Pr
e-
pr
was not detected.
Journal Pre-proof
33
Table 4. Analysis of each SNP (dominant model) combined with HCV genotype 3 infection in the presence of hepatic steatosis and fibrosis in patients with chronic hepatitis C. 95% CI Low Upper
1.66 0.61 0.22 2.61 2.17 3.58
0.32 0.12 0.03 0.14 0.42 0.33
1.32 6.72 0.99 1.50 0.61 0.39
0.31 1.51 0.15 0.14 0.15 0.04
p
OR*
95% CI Low Upper
0.546 0.548 0.155 0.526 0.354 0.294
0.66 0.29 2.99 2.10 3.99
0.13 0.03 0.16 0.40 0.36
3.34 2.47 56.27 10.95 43.93
0.614 0.258 0.464 0.379 0.258
8.34 1.38 1.84 0.55 0.40
1.78 0.21 0.17 0.13 0.04
39.13 9.22 20.59 2.34 3.87
0.007 0.741 0.620 0.414 0.431
oo
f
8.64 3.07 1.76 50.38 11.09 38.57 5.72 29.98 6.33 15.68 2.50 3.58
pr
Fibrosis HCV-3 by PNPLA3 rs738409 HCV-3 by MTTP rs1800591 a HCV-3 by TM6SF2 rs58542926 HCV-3 by PNPLA3 rs2294918 HCV-3 by IFNL3/IFNL4 rs8099917 b HCV-3 by IFNL3/IFNL4 rs12979860 Steatosis HCV-3 by PNPLA3 rs738409 HCV-3 by MTTP rs1800591 HCV-3 by TM6SF2 rs58542926a HCV-3 by PNPLA3 rs2294918 HCV-3 by IFNL3/IFNL4 rs8099917 HCV-3 by IFNL3/IFNL4 rs12979860b
OR
e-
Variable
0.708 0.013 0.989 0.733 0.487 0.405
Pr
HCV-3, HCV genotype 3; SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval.
al
Logistic regression adjusted for age, gender, BMI, alcohol consumption; * Model
(genotype CG/GG)
The presence of the TM6SF2 rs58542926 mutated genotype (TT) was not
Jo u
a
rn
adjusted for all variables from previous model plus PNPLA3 rs738409
detected, because of that was analysed as CC x CT instead of the dominant model. b
The presence of the IFNL3/IFNL4 rs12979860 wild genotype (CC) was not
detected in patients with steatosis or fibrosis because of that was analysed as CT x TT instead of the dominant model.
p
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Table 5. Analysis of the combined effect of independent SNPs (dominant model) in the presence of hepatic steatosis and fibrosis in patients with chronic hepatitis C. 95% CI Variable
95% CI
OR
p
OR*
p
Low
Upper
Low
Upper
0.32
19.58 0.387
Fibrosis a
TM6SF2 rs58542926 x MTTP rs1800591
2.77
0.38
20.26 0.316 2.49
PNPLA3 rs738409 x MTTP rs1800591
1.13
0.29
4.31
MTTP rs1800591 x PNPLA3 rs2294918
3.34
0.28
39.65 0.340 2.73
0.23
31.84 0.422
0.42
0.11
1.56
0.10
1.42
0.148
0.20
8.00
0.799
b
f
1.11
0.18
6.91
a
TM6SF2 rs58542926 x PNPLA3 rs738409
5.91
0.58
60.21 0.134
a
2.52
0.20
32.26 0.477 2.41
0.17
33.42 0.513
1.93
0.29
12.66 0.493 2.04
0.29
14.39 0.474
1.81
0.15
22.00 0.640 1.99
0.16
24.30 0.590
2.01
0.26
15.41 0.503
0.55
0.15
2.08
0.380
0.64
0.09
4.32
0.643
0.26
0.03
1.96
0.191 0.21
0.03
1.66
2.54
0.24
27.02 0.440 1.49
0.13
16.63 0.744
0.18
0.03
1.16
0.072 0.19
0.03
1.22
0.079
TM6SF2 rs58542926a x MTTP rs1800591
0.51
0.10
2.64
0.418 0.40
0.07
2.15
0.284
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MTTP rs1800591 x IFNL3/IFNL4 rs12979860
0.192 0.37
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MTTP rs1800591 x IFNL3/IFNL4 rs8099917
0.863
PNPLA3 rs738409 x MTTP rs1800591
2.45
0.87
6.92
0.091
MTTP rs1800591 x PNPLA3 rs2294918
0.69
0.15
3.18
0.636 0.64
0.14
2.96
0.566
0.99
0.36
2.75
0.983 0.96
0.34
2.70
0.934
0.20
3.60
0.820
pr
TM6SF2 rs58542926 x PNPLA3 rs2294918 a
TM6SF2 rs58542926 x IFNL3/IFNL4 rs8099917 TM6SF2 rs58542926 x IFNL3/IFNL4 rs12979860
b
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a
PNPLA3 rs738409 x IFNL3/IFNL4 rs8099917
Pr
PNPLA3 rs738409 x PNPLA3 rs2294918 b
PNPLA3 rs738409 x IFNL3/IFNL4 rs12979860 IFNL3/IFNL4 rs8099917 x PNPLA3 rs2294918 b
al
IFNL3/IFNL4 rs12979860 x PNPLA3 rs2294918 b
rn
IFNL3/IFNL4 rs12979860 x IFNL3/IFNL4 rs8099917 Steatosis
MTTP rs1800591 x IFNL3/IFNL4 rs8099917 b
MTTP rs1800591 x IFNL3/IFNL4 rs12979860
0.910 1.27
0.140
0.73
0.18
3.02
0.665 0.85
a
TM6SF2 rs58542926 x PNPLA3 rs738409
1.00
0.16
6.21
0.997
a
1.09
0.12
10.09 0.942 1.02
0.11
9.58
0.984
1.59
0.30
8.35
0.587 1.57
0.29
8.43
0.598
0.21
0.02
1.85
0.160 0.21
0.02
1.86
0.160
2.25
0.50
10.23 0.292
0.78
0.28
2.17
0.632
PNPLA3 rs738409 x by IFNL3/IFNL4 rs12979860
0.56
0.13
2.39
0.430
IFNL3/IFNL4 rs8099917 x PNPLA3 rs2294918
TM6SF2 rs58542926 x PNPLA3 rs2294918 a
TM6SF2 rs58542926 x IFNL3/IFNL4 rs8099917 a
TM6SF2 rs58542926 x IFNL3/IFNL4 rs12979860
b
PNPLA3 rs738409 x PNPLA3 rs2294918 PNPLA3 rs738409 x IFNL3/IFNL4 rs8099917 b
0.64
0.15
2.73
0.547 0.60
0.14
2.58
0.488
b
0.95
0.15
6.01
0.957 0.58
0.09
3.87
0.571
b
0.83
0.20
3.45
0.796 0.82
0.19
3.52
0.794
IFNL3/IFNL4 rs12979860 x PNPLA3 rs2294918 IFNL3/IFNL4 rs12979860 x IFNL3/IFNL4 rs8099917
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SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval. Logistic regression adjusted for age, gender, BMI, alcohol consumption; * Model adjusted for all variables from previous model plus PNPLA3 rs738409 (genotype CG/GG) a
The presence of the TM6SF2 rs58542926 mutated genotype (TT) was not
detected, because of that was analysed as CC x CT instead of the dominant model.
f
The presence of the IFNL3/IFNL4 rs12979860 wild genotype (CC) was not
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b
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rn
al
Pr
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CT x TT instead of the dominant model.
pr
detected in patients with steatosis or fibrosis because of that was analysed as
Mariana Cavalheiro Magri, Caroline Manchiero, Thamiris Vaz Gago Prata, Arielle Karen da Silva Nunes, José Santos de Oliveira Junior, Bianca Peixoto Dantas, Fátima Mitiko Tengan PII:
S0732-8893(19)31018-1
DOI:
https://doi.org/10.1016/j.diagmicrobio.2020.115025
Reference:
DMB 115025
To appear in:
Diagnostic Microbiology & Infectious Disease
Received date:
10 October 2019
Revised date:
24 January 2020
Accepted date:
14 February 2020
Please cite this article as: M.C. Magri, C. Manchiero, T.V.G. Prata, et al., The influence of gene-chronic hepatitis C virus infection on hepatic fibrosis and steatosis, Diagnostic Microbiology & Infectious Disease(2020), https://doi.org/10.1016/ j.diagmicrobio.2020.115025
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2020 Published by Elsevier.
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The influence of gene-chronic hepatitis C virus infection on hepatic fibrosis and steatosis
Word count of the abstract: 149 Word count of the text: 3235
Mariana Cavalheiro Magri a, Caroline Manchieroa, Thamiris Vaz Gago Prataa,
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Arielle Karen da Silva Nunesa, José Santos de Oliveira Junior a, Bianca Peixoto
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Dantasa, Fátima Mitiko Tengana,b
a
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Laboratorio de Investigacao Medica em Hepatologia por Virus (LIM-47),
Paulo, Sao Paulo, SP, BR.
Pr
Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao
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Address: Av. Dr. Eneas de Carvalho Aguiar, 470 - Instituto de Medicina
b
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05403-000.
rn
Tropical - Predio 2. Bairro Cerqueira César. Sao Paulo, SP, Brazil. CEP
Departamento de Molestias Infecciosas e Parasitarias, Faculdade de
Medicina, Universidade de Sao Paulo, Sao Paulo, SP, BR. Address: Av. Dr. Eneas de Carvalho Aguiar, 470 - Instituto de Medicina Tropical - Predio 1. Bairro Cerqueira Cesar. Sao Paulo, SP, Brazil. CEP 05403-000.
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Email: Mariana Cavalheiro Magri - [email protected] Caroline Manchiero - [email protected] Thamiris Vaz Gago Prata - [email protected] Arielle Karen da Silva Nunes - [email protected] José Santos de Oliveira Junior - [email protected] Bianca Peixoto Dantas - [email protected]
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f
Fátima Mitiko Tengan - [email protected]
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Corresponding author
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Mariana Cavalheiro Magri
Pr
Laboratorio de Investigacao Medica em Hepatologia por Virus (LIM-47), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao
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Paulo, Sao Paulo, SP, Brazil.
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Address: Av. Dr. Eneas de Carvalho Aguiar, 470 - Instituto de Medicina Tropical
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- Predio 2. Bairro Cerqueira Cesar. Sao Paulo, SP, Brazil. CEP 05403-000. Phone: +55 11 30617031 Fax: +55 11 30851601 E-mail: [email protected]
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Abstract Host single nucleotide polymorphisms (SNPs) in different genes can play a role in chronic hepatitis C virus (HCV) infection, and influence the presence of hepatic fibrosis and comorbidities such as hepatic steatosis. We assessed the combined effect of SNPs in the PNPLA3, MTTP, TM6SF2 and IFNL3/IFNL4 genes in 288 Brazilian patients who were chronically infected with HCV. Hepatic fibrosis was observed in 246 (85.4%) patients and hepatic steatosis in 141
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(49.0%) patients. PNPLA3 rs738409 (CG/GG) (p=0.044) and TM6SF2 rs58542926 (CT) (p=0.004) were alone associated with fibrosis, and PNPLA3
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rs738409 (p<0.05, in distinct genetic models) was associated with steatosis.
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Multiple logistic regression of each SNP combined with HCV genotype 3
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infection showed that MTTP rs1800591 (GT/TT) combined with HCV genotype 3 was associated with a 6.72-fold increased chance of hepatic steatosis
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(p=0.013). In the analysis of SNPs combined two by two, no influence on
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hepatic fibrosis or steatosis was observed.
Keywords: hepatitis C, single nucleotide polymorphisms (SNPs), interferon lambda 3 and 4 (IFNL3/IFNL4), microsomal triglyceride transfer protein (MTTP), patatin-like phospholipase domain containing 3 (PNPLA3), transmembrane six superfamily member 2 (TM6SF2).
Abbreviations:
ALT,
alanine
aminotransferase;
AST,
aspartate
aminotransferase; BMI, body mass index; CHC, chronic hepatitis C; CI, confidence interval; DAAs, direct acting antivirals; GGT, gamma glutamyl transpeptidase; HCV, hepatitis C virus; HCC, hepatocellular carcinoma; HOMA-
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IR, homeostasis model assessment of insulin resistance; IFNL3/IFNL4, interferon lambda 3 and 4; IL28, interleukin-28B; MTTP, microsomal triglyceride transfer protein; NAFLD, non-alcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; OR, odds ratio; PCR-RFLP, polymerase chain reactionrestriction fragment length polymorphism; PNPLA3, patatin-like phospholipase domain containing 3; SNPs, single nucleotide polymorphisms; TM6SF2,
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transmembrane six superfamily member 2; WHO, World Health Organization.
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1. Introduction
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The study of single nucleotide polymorphisms (SNPs) in different genes
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has been increasingly relevant in the clinical field, as they can play an important role in the development of various diseases in different population groups [1,2].
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Recent studies have evaluated the role of SNPs related to patients with chronic
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hepatitis C virus (HCV) infection, as this infection affects approximately 71
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million individuals worldwide and its evolution over the years, is characterized by persistent and progressive inflammation in the liver, and may lead to hepatocellular carcinoma (HCC) if proper treatment is not administered [3]. Several studies have described associations of SNPs with the development of chronic hepatitis C (CHC) and have evaluated their influence on the presence of hepatic fibrosis, hepatic steatosis, and with spontaneous viral clearance [4-9]. Recent data have shown that the development and progression of hepatic fibrosis in CHC is multifactorial and that host factors may influence it. Relevant host factors include age; gender; behavioural aspects such as alcoholism and smoking; metabolic aspects such as hepatic steatosis, insulin
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resistance, diabetes and obesity; and, importantly, host SNPs [10,11]. SNPs in interferon lambda 3 and 4 (IFNL3/IFNL4), initially christened interleukin-28B (IL28B), appear to worsen the natural course of disease in patients with CHC [12]. Although a study with 2,335 chronically HCV-infected patients associated IFNL3/IFNL4 rs8099917 with slower fibrosis progression [9]. SNPs in other genes, such as patatin-like phospholipase domain containing 3 (PNPLA3) and the transmembrane six superfamily member 2 (TM6SF2), have been associated
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f
with advanced hepatic fibrosis [6,7]. Chronic HCV infection is also known to cause some comorbidities, such as hepatic steatosis, present in approximately
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half of these patients. Moreover, the presence of hepatic steatosis due to
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metabolic syndrome is associated with accelerated hepatic fibrosis progression
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and risk for HCC [10,13]. SNPs in genes such as PNPLA3, TM6SF2 and microsomal triglyceride transfer protein (MTTP) have been shown to impact
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lipoprotein and lipid secretion and predispose individuals with and without HCV
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infection to hepatocyte triglyceride accumulation, the hepatic steatosis [5,7,13-
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16]. A recent review mentioned genetic factors that contributes to development and progression of non-alcoholic fatty liver disease (NAFLD), a growing epidemic disease ranging from isolated hepatic steatosis to HCC, summarized that the NAFLD development is related with several relevant SNPs in genes such as PNPLA3, TM6SF2, glucokinase regulator (GCKR), oacyltransferase domain-containing 7 (MBOAT7), hydroxysteroid 17-beta dehydrogenase 13 (HSD17B13), among others [17]. The HSD17B13 rs72613567 SNP, for example, has also been associated with protection against hepatic fibrosis in HCV infected patients [18].
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Many of the associations described above are not yet fully established, and some SNPs may not have independent roles. In 2016, Trépo et al. [19], considering liver disease in clinical practice, discussed that evaluating a single SNP alone may have a limited predictive value. However, few studies have evaluated combined effect of SNPs [20-22]. A significant association between SNPs could possibly represent a protective effect or a higher chance for development of clinical consequences, such as hepatic fibrosis and steatosis, in
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some cases. Therefore, the present study was conducted to evaluate the potential combined effect of six selected SNPs in the PNPLA3, MTTP, TM6SF2
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and IFNL3/IFNL4 genes in hepatic steatosis and hepatic fibrosis associated
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2.1. Study subjects
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2. Materials and Methods
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with CHC patients.
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A total of 288 patients chronically infected with HCV were evaluated at the HCFMUSP from January 2010 to December 2015. Eligibility criteria were age ≥ 18 years, positive anti-HCV antibody, HCV-RNA presence for more than 6 months and having undergone liver biopsy prior to specific antiviral therapy. The exclusion criteria were hepatitis B virus (HBV) or human immunodeficiency virus (HIV) coinfection and other etiologies in the liver.
2.2. Data collection The epidemiological factors collected included age, gender, body mass index (BMI) (calculated as weight divided by height squared) and alcohol
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consumption. The serum biochemical tests collected to better describe the study population were gamma glutamyl transpeptidase (GGT), alanine aminotransferase (ALT), aspartate aminotransferase (AST), insulin and glucose. Based on data from the insulin secretion and fasting glucose of the patients, the HOMA-IR index (homeostasis model assessment of insulin resistance) was calculated. The HCV genotypes were also collected. Histological assessment of liver fragments was performed as follows:
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hepatic steatosis was assessed and graded on a scale from 0 to 3 as described by Kleiner et al. [23]. The hepatic fibrosis stage and inflammatory activity of the
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liver were scored using the Metavir system [24]. Histological examination was
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performed by two experienced pathologists.
2.3. SNP genotyping
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The polymorphisms rs738409 of the PNPLA3 gene and rs1800591 of the
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MTTP gene were genotyped by polymerase chain reaction-restriction fragment
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length polymorphism (PCR-RFLP) as described in previous studies of our group [25,26]. The polymorphisms rs2294918 of PNPLA3, rs58542926 of TM6SF2, rs8099917 and rs12979860of IFNL3/IFNL4 were genotyped by real-time PCR using the TaqMan genotyping assay system on a Step One Plus Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). The TaqMan genotyping
assays
performed
rs58542926
assay
ID
C_89463510_10,
rs2294918 assay ID C_2520500_10, rs8099917 assay ID C_11710096_10 and rs12979860 assay ID C_7820464_10 (Applied Biosystems, Foster City, CA, USA). The interpretation of genotypes is presented in Table 1.
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2.4. Statistical analysis Patient characteristics were evaluated according to the genotypes of each SNP. Qualitative characteristics were described using absolute and relative frequencies and the association was verified using of χ2 test or exact tests (Fisher's exact test or likelihood ratio test). Quantitative characteristics were described as the mean and standard deviation and compared using tStudent tests [27]. Hardy-Weinberg equilibrium between expected and
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observed genotype distributions of each SNP was estimated by the χ2 test. The association of each SNP with the occurrence of hepatic fibrosis and
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steatosis was estimated by odds ratio (OR) and 95% confidence interval (CI)
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and bivariate tests using simple logistic regression [28]. Each SNP was
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analysed with the co-dominant, dominant and recessive genetic models. The co-dominant model considers the three genotypes separated. The dominant
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model considers the homozygous wild-type vs. the heterozygous and
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homozygous mutated-type together, and the recessive model considers the
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homozygous wild-type and heterozygous together vs. the homozygous mutated-type. Significance in any of the three genetic models was considered as a possible association of the SNPs with hepatic fibrosis or hepatic steatosis in CHC.
A multiple logistic regression model adjusted for the potential confounders age, gender, BMI and alcohol consumption was used to analyse of each SNP (dominant model) combined with HCV genotype 3 infection, and the combined effect of independent SNPs (two by two) on the presence of hepatic fibrosis and steatosis [28]. The multiple logistic regressions were also adjusted for PNPLA3 rs738409 (genotype CG/GG), whose risk of hepatic steatosis is
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better established. The significance level was considered less than 0.05 (p<0.05) for all analyses. Data were analysed with IBM-SPSS for Windows v.20.0.
3. Results
3.1 Characteristics of the study subjects
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The mean age of all 288 participating patients chronically infected with HCV was 54.9 years, 56.9% were female, and 37.2% of the patients were
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underweight. The mean liver enzyme serum levels were 83.4 ± 92.3 U/L for
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GGT, 62.3 ± 49.5 U/L for ALT and 49.7 ± 38.2 U/L for AST. The mean serum
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levels of glucose were 91.5 ± 39.5 mg/dL, insulin was 15.2 ± 32.3 µU/mL, and the calculated HOMA-IR was 3.4 ± 6.4. Regarding the characteristics of the
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anatomopathological study of the liver fragment, we highlight that inflammatory
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activity was observed in 285 (98.9%) of the patients, fibrosis in 246 (85.4%),
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and steatosis in 141 (49.0%). HCV genotype 1 was present in 78.9% of CHC patients, followed by genotype 3 in 15.8% of CHC patients and other genotypes in only 5.2% of CHC patients (Table S1, supplementary material).
3.2 SNPs All samples from patients with CHC included in the study were genotyped for the six SNPs as shown in Table 1, with the exception of PNPLA3 rs2294918 in which it was possible to only genotype 270 instead of 288. The frequencies of the mutated alleles of each SNP were calculated and the frequency for PNPLA3 rs738409 was 0.43, PNPLA3 rs2294918 was 0.09, MTTP rs1800591 was 0.33,
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TM6SF2 rs58542926 was 0.05, IFNL3/IFNL4 rs8099917 was 0.34, and IFNL3/IFNL4 rs12979860 was 0.57. The genotype distributions of the SNP MTTP rs1800591 and TM6SF2 rs58542926 in the study population were in Hardy-Weinberg equilibrium with values of p=0.859 and p=0.368, respectively. The other SNP distributions deviated from the expected counts according to Hardy-Weinberg equilibrium (p≤0.05) (Table 1). The characteristic of the study population were stratified by the six
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evaluated SNPs genotypes to perform exploratory analyzes. It was observed that few characteristics differed statistically among the SNPs genotypes.
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However, the mean value of BMI differed according to the genotypes of the
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TM6SF2 rs58542926 (p=0.004) and IFNL3/IFNL4 rs12979860 (p=0.034); the
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mean glucose differed according to the genotypes of the MTTP rs1800591 (p=0.034) and the IFNL3/IFNL4 rs8099917 (p=0.046); and the mean GGT also
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differed according to the genotypes of the IFNL3/IFNL4 rs8099917 (p=0.010).
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Advanced fibrosis was statistically associated with the TM6SF2 rs58542926
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genotype CT (p=0.002), while steatosis presence was associated with the PNPLA3 rs738409 genotype CG/GG (p=0.006) (Table S1, Supplementary material).
Furthermore, the association of each SNP alone with the occurrence of hepatic fibrosis was estimated using the co-dominant, dominant and recessive genetic models and is presented in Table 2. Two SNPs were associated with its occurrence: PNPLA3 rs738409 (p=0.044) and TM6SF2 rs58542926 (p=0.004). In relation to the hepatic steatosis, the presence of at least one mutated allele of PNPLA3 rs738409 was associated with steatosis (p<0,05) in the three distinct genetic models (Table 3).
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The occurrence of fibrosis and steatosis was also evaluated by each SNP combined with HCV genotype 3 infection (Table 4). The presence of MTTP rs1800591 (GT/TT genotype) combined with the presence of the HCV genotype 3 was associated with a 6.72-fold increased chance of hepatic steatosis regardless of some patient characteristics (adjusted for age, gender, BMI and alcohol consumption) (p=0.013) and after adjusting also for the PNPLA3 rs738409 the chance of hepatic steatosis increased in patients with
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CHC (odds ratio=8.34; p=0.007).
Finally, the results of multiple logistic regression of the SNPs combined
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two by two that could influence the presence of hepatic fibrosis and steatosis
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are detailed in Table 5. None of the combined SNPs were statistically
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significant regardless of patient characteristics (adjusted for age, gender, BMI
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4. Discussion
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and alcohol consumption) (p>0.05).
In this study, six SNPs (PNPLA3 rs738409, PNPLA3 rs2294918, MTTP rs1800591, TM6SF2 rs58542926, IFNL3/IFNL4 rs8099917 and IFNL3/IFNL4 rs12979860) were evaluated in 288 Brazilian patients with CHC in three distinct genetic models, thus making use of the information available on all genotypes. Subsequently, the combined effects of each SNP with HCV genotype 3 and of the SNPs two by two were analysed in relation to the presence of histologically determined hepatic fibrosis and steatosis. Initially, despite the efficiency of treatment with HCV direct acting antivirals (DAAs), the circulation and transmission of this virus and the progression of hepatic disease continue to
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occur. The World Health Organization (WHO) considers chronic HCV infection a public health issue that affects individuals of all ages, genders and ethnicities, and it leads to approximately 399,000 deaths annually [3]. Thus, the evaluation of genetic factors such as SNPs, which may help us understand the pathogenesis of liver disease and may predict a higher risk of an individual with CHC developing hepatic fibrosis and steatosis, is relevant. Regarding the presence of hepatic fibrosis, in the evaluation of
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independent SNPs in the distinct genetic models, associations of SNPs in the gene PNPLA3 rs738409 (CG/GG genotype) and TM6SF2 rs58542926 (CT
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genotype) with hepatic fibrosis were observed. These findings are in
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accordance with the data of a study that recruited 1,077 CHC patients and
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observed that the PNPLA3 rs738409 (CG/GG genotype) was a factor predictive of advanced hepatic fibrosis [29]. A meta-analysis performed in 2016 comprised
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2,037 CHC patients and revealed that the recessive genetic model of the
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PNPLA3 rs738409 (GG genotype) was significantly associated with higher
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severity of hepatic fibrosis in Caucasians but not Asian populations [6]. A newsworthy Spanish retrospective study evaluated repeated measures of hepatic fibrosis among CHC patients and observed that the G allele of the SNP in PNPLA3 rs738409 was associated with higher hepatic fibrosis progression during a mean follow-up of 49.7 months [30]. The association of the TM6SF2 SNP with advanced hepatic fibrosis was also described in a meta-analysis with 4,325 CHC patients, in which the risk of histologically determined clinically significant fibrosis was increased in carriers of the TM6SF2 rs58542926 (E167K) mutated allele [7]. Similarly, in an Italian cohort with of 815 CHC patients the TM6SF2 rs58542926 was associated with cirrhosis, and in 645
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Swiss/German patients was associated with fibrosis stage F2-F4 [31]. In contrast, Eslam et al. [16] found only a marginal association of the TM6SF2 rs58542926 with fibrosis in CHC patients from the International Liver Disease Genetics Consortium database, and Huang et al. [20] found no independent association of the PNPLA3 rs738409 SNP with hepatic fibrosis in Asian CHC patients. On the other hand, as in the present study, they also found no association between IFNL3/IFNL4 rs8099917 and rs12979860 SNPs with
frequency
of
IFNL3/IFNL4 rs12979860
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fibrosis. Noureddin et al. [32] reported that there was no difference in the genotypes
on
hepatic
fibrosis
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progression between CHC patients. However, Eslam et al. [8] in a study with a
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large cohort including 3,129 CHC patients in which 49.4% had significant
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fibrosis and 73% were infected with HCV genotype 1, the IFNL3/IFNL4 rs12979860 (CC genotype) was strongly associated with hepatic fibrosis. Then,
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in a later study by this same group of researchers the IFNL3/IFNL4 rs12979860
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SNP was used as one of the variables to the development of a fibrosis non-
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invasive prediction model called FibroGENE-DT. This model was even significantly superior to APRI in prediction of cirrhosis and superior to FIB-4 in prediction of fibrosis progression rate [33]. Briefly, other variants in IFNL3/IFNL4 have also been associated with hepatic fibrosis, such as rs4803217 and rs368234815, with similar results to those for the SNP rs12979860 [34]. Therefore, despite the lack of association observed in the present study, SNPs in IFNL3/IFNL4 and interferon (IFN)-λ3 levels seems to be determinants of hepatic fibrosis in CHC patients and also in others non-viral liver diseases [35]. Nevertheless, in accordance with our findings, Petit et al. [36] analysed 86 CHC
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patients and reported that the MTTP functional SNP rs1800591 (-493G/T) in the MTTP gene had no influence on the development of hepatic fibrosis. In the evaluation of the combined effects of each SNP with HCV genotype 3 infection, and of the combined effects independent SNPs (dominant model), no association with the presence of hepatic fibrosis was observed. However, an interesting study was conducted among 416 NAFLD patients without HCV infection who underwent liver biopsy. The PNPLA3 rs738409 and
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TM6SF2 rs58542926 mutated alleles additively increased the risk of nonalcoholic steatohepatitis (NASH) by 2.03-fold and increased the risk of
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significant hepatic fibrosis by 1.61-fold [21]. Recently, Youssef et al. [37]
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evaluated the association of IFNL3/IFNL4 rs8099917 (GG genotype) in
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combination with PNPLA3 rs738409 (GG genotype) on susceptibility and hepatic fibrosis progression in CHC patients infected with HCV genotype 4, and
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considered this combination of mutated genotypes a high-risk signature for
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advanced stage of fibrosis.
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Various studies have shown that SNPs may also predispose people with and without HCV infection to hepatic steatosis. Regarding its presence in CHC patients in the present study, an association of the PNPLA3 rs738409 was found in co-dominant, dominant and recessive genetic models with the presence of hepatic steatosis. Huang et al. [20] found that the PNPLA3 rs738409 (GG genotype) was independently associated with hepatic steatosis in CHC patients from Taiwan. However, the same significance was not independently observed in relation to IFNL3/IFNL4 rs8099917 and rs12979860 SNPs, as in our study. A meta-analysis conducted by Fan et al. [6] revealed that among Caucasian populations with CHC, PNPLA3 rs738409 (GG genotype)
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was associated with the risk of hepatic steatosis. In the present study, the other SNPs were not associated with hepatic steatosis in any evaluated genetic model. Akgöllü and Akkız [38] found no association of the MTTP rs1800591 (493G/T) with the presence of hepatic steatosis in Turkish individuals with HCV genotype 1 infection. Otherwise, Milano et al. [31] detected an association of TM6SF2 rs58542926 (E167K) with more severe steatosis in Italian patients, but when stratified by HCV genotype the association remained in patients not
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f
infected by genotype 3, but not in those infected by HCV genotype 3. Regarding the influence of IFNL3/IFNL4 rs8099917 and rs12979860 SNPs on hepatic
pr
steatosis, these relationships have controversial results, and Eslam et al. [39]
e-
discuss that this may be due to different ethnicities, small sample sizes of the
Pr
studies and local other risk factors for hepatic steatosis. In the evaluation of the combined effects of each SNP with HCV
al
genotype 3 infection, an association of the MTTP rs1800591 (GT/TT) combined
rn
with the HCV genotype 3 with the presence of hepatic steatosis was observed.
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The association of these two combined factors increased the chance of steatosis by 6.72-fold. The study by Zampino et al. [40] showed that patients with HCV genotype 3 and carriers of the mutated allele (T) of MTTP rs1800591 (-493G/T) had more advanced hepatic steatosis and fibrosis in relation to those with the wild allele (G). Of note, it has been widely accepted that viral and host factors are likely to contribute to the development of hepatic steatosis, and the HCV genotype 3 can be an important factor for it. In addition, the persistence of steatosis may prevent complete return to health even in patients treated for HCV [13].
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Otherwise, in the two by two combined SNP analyses, no association was found with the presence of hepatic steatosis. However, studies have shown, also using the dominant model, that the proportion of CHC patients with hepatic steatosis was higher in those with the combined presence of the risk alleles of PNPLA3 rs738409 (CG/GG genotype) and IFNL3/IFNL4 rs12979860 (CT/TT genotype) and in those with the risk alleles of PNPLA3 rs738409 (CG/GG genotype) combined with IFNL3/IFNL4 rs8099917 (TG/GG genotype)
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f
[20]. In contrast, a recent study among Italian CHC patients showed that the presence of hepatic steatosis was not influenced by the additive effect of MTTP
pr
rs1800591 (GT/TT genotype) on PNPLA3 rs738409 (GG genotype), but
e-
PNPLA3 rs738409 alone was associated with steatosis [22].
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Of note, Brazil has a heterogeneous population with diverse patterns of admixture observed by a study of ancestry informative SNPs [41], which may be
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a limitation of the present study and reinforces the need to evaluate the
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frequency and possible associations of each SNP genotype in different
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geographical regions of the world. Additionally, we cannot exclude the possibility that other SNPs in these genes or in other genes may be driving some of the results observed. Nevertheless, to our knowledge, this is the first investigation to explorer the combined effect of these six specific SNPs. Despite the lack of statistically significant association, we believe that in several cases accessing genetic information could help identify patients who might be at risk for liver diseases development.
5. Conclusion
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In conclusion, our findings indicate that PNPLA3 rs738409 and TM6SF2 rs58542926 were alone associated with hepatic fibrosis, and PNPLA3 rs738409 with hepatic steatosis. MTTP rs1800591 combined with HCV genotype 3 robustly increased chance of hepatic steatosis. Otherwise, the combined effect between the SNPs had no influence on hepatic fibrosis and steatosis in a genetic context of Brazilian CHC patients. Additional exploratory researches to test the combined effects of different SNPs are needed to better understand
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their contributions to liver disease.
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Funding
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e-
None.
Conflict of Interest Declaration
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Ethical approval
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None declared.
The study was conducted according to the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the Ethics Committee (Ethics Committee for Research Projects Analysis - CAPPesq) of the Clinical Hospital of the School of Medicine, University of Sao Paulo (HCFMUSP), Brazil, numbers 448.527 and 1.310.147, and written informed consent was obtained from patients participating in the study.
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Table 1. Genotype interpretation for the PNPLA3, MTTP, TM6SF2 and IFNL3/IFNL4 genes. Gene PNPLA3 MTTP TM6SF2 IFNL3/IFNL4
SNP ID number rs738409 rs2294918 rs1800591 rs58542926 rs8099917 rs12979860
Homozygous wild-type (n/%) CC (143/46.5) GG (226/83.7) GG (128/44.4) CC (259/89.9) TT (146/50.7) CC (2/0.7)
Heterozygous (n/%) CG (61/21.2) GA (37/13.7) GT (129/44.8) CT (29/10.1) TG (86/29.9) CT (246/85.4)
Homozygous mutated-type (n/%) GG (93/32.3) AA (7/2.6) TT (31/10.8) TT (0/0) GG (56/19.4) TT (40/13.9)
MAF 0.43 0.09 0.33 0.05 0.34 0.57
HWE, Hardy-Weinberg equilibrium; ID, identification; MAF, minor allele
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frequency; SNP, single nucleotide polymorphism; p≤0.05 not consistent with
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al
Pr
e-
pr
HWE
HWE p value* 0.000 0.001 0.859 0.368 0.000 0.000
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Table 2. Association of the SNPs in the PNPLA3, MTTP, TM6SF2 and IFNL3/IFNL4 genes and the risk of hepatic fibrosis among patients with chronic hepatitis C in distinct genetic models. Fibrosis SNP genotype
Absent (n=231)
Present (n=58)
OR
Low
Upper
p
0.123 1.00 1.70 1.95
182 (80.2) 45 (19.8) 31 (83.8) 6 (16.2) 6 (85.7) 1 (14.3)
1.00 0.78 0.67
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pr
1.00 1.49 0.49
214 (82.3) 46 (17.7) 17 (58.6) 12 (41.4)
1.00 3.28
120 (81.6) 27 (18.4) 68 (79.1) 18 (20.9) 43 (76.8) 13 (23.2)
1.00 1.18 1.34
Pr
e-
105 (82.0) 23 (18.0) 98 (75.4) 32 (24.6) 28 (90.3) 3 (9.7)
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0.79 1.01
3.64 3.80 0.829
f
114 (85.1) 20 (14.9) 47 (77.0) 14 (23.0) 70 (74.5) 24 (25.5)
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Co-dominant model PNPLA3 rs738409 CC CG GG PNPLA3 rs2294918 GG GA AA MTTP rs1800591 GG GT TT TM6SF2 rs58542926* CC CT IFNL3/IFNL4 rs8099917 TT TG GG IFNL3/IFNL4 rs12979860 CC CT TT Dominant model PNPLA3 rs738409 CC CG/GG PNPLA3 rs2294918 GG GA/AA MTTP rs1800591 GG GT/TT IFNL3/IFNL4 rs8099917 TT TG/GG IFNL3/IFNL4 rs12979860 CC CT/TT Recessive model PNPLA3 rs738409
95% CI
0.31 0.08
1.99 5.74 0.140
0.82 0.14
2.72 1.75 0.004
1.47
7.34 0.723
0.60 0.64
2.29 2.84 0.999
2 (100.0) 0 (0.0) 197 (79.8) 50 (20.2) 32 (80) 8 (20)
1.00 & &
114 (85.1) 20 (14.9) 117 (75.5) 38 (24.5)
1.00 1.85
182 (80.2) 45 (19.8) 37 (84.1) 7 (15.9)
1.00 0.77
105 (82.0) 23 (18.0) 126 (78.3) 35 (21.7)
1.00 1.27
120 (81.6) 27 (18.4) 111 (78.2) 31 (21.8)
1.00 1.24
2 (100.0) 0 (0.0) 229 (79.8) 58 (20.2)
1.00 &
0.044 1.02
3.37 0.547
0.32
1.83 0.427
0.71
2.28 0.463
0.70
2.21 0.999
0.109
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161 (82.6) 34 (17.4) 70 (74.5) 24 (25.5)
30 1.00 1.62
0.90
2.94 0.740
213 (80.7) 51 (19.3) 6 (85.7) 1 (14.3)
1.00 0.70
0.08
5.91 0.138
203 (78.7) 55 (21.3) 28 (90.3) 3 (9.7)
1.00 0.40
0.12
1.35 0.513
188 (80.7) 45 (19.3) 43 (76.8) 13 (23.2)
1.00 1.26
0.63
2.55 0.991
199 (79.9) 50 (20.1) 32 (80.0) 8 (20.0)
1.00 1.00
0.43
2.29
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SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval. Bivariate tests; *The presence of the TM6SF2 rs58542926 mutated genotype
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Pr
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was not detected.
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31
Table 3. Association of the SNPs in the PNPLA3, MTTP, TM6SF2 and IFNL3/IFNL4 genes and the risk of hepatic steatosis among patients with chronic hepatitis C in distinct genetic models. SNP genotype
OR
80 (59.7) 28 (45.9) 39 (41.5)
1.00 1.75 2.09
95% CI Low
Upper
p
0.018
1.00 1.00 1.74
135 (51.9) 12 (41.4)
125 (48.1) 17 (58.6)
1.00 1.53
82 (55.8) 41 (47.7) 24 (42.9)
65 (44.2) 45 (52.3) 32 (57.1)
1.00 1.39 1.68
2 (100.0) 127 (51.4) 18 (45.0)
0 (0.0) 120 (48.6) 22 (55.0)
1.00 & &
80 (59.7) 67 (43.2)
54 (40.3) 88 (56.8)
1.00 1.95
111 (48.9) 27 (61.4)
116 (51.1) 17 (38.6)
1.00 0.60
67 (52.3) 80 (49.7)
61 (47.7) 81 (50.3)
1.00 1.11
82 (55.8) 65 (45.8)
65 (44.2) 77 (54.2)
1.00 1.49
2 (100.0) 145 (50.5)
0 (0.0) 142 (49.5)
1.00 &
Pr
0.95 1.22
3.22 3.57 0.314
f
61 (47.7) 62 (47.7) 19 (61.3)
al
Jo u
1.00 0.58 0.72
oo
116 (51.1) 14 (37.8) 3 (42.9)
e-
67 (52.3) 68 (52.3) 12 (38.7)
54 (40.3) 33 (54.1) 55 (58.5)
pr
111 (48.9) 23 (62.2) 4 (57.1)
rn
Co-dominant model PNPLA3 rs738409 CC CG GG PNPLA3 rs2294918 GG GA AA MTTP rs1800591 GG GT TT TM6SF2 rs58542926* CC CT IFNL3/IFNL4 rs8099917 TT TG GG IFNL3/IFNL4 rs12979860 CC CT TT Dominant model PNPLA3 rs738409 CC CG/GG PNPLA3 rs2294918 GG GA/AA MTTP rs1800591 GG GT/TT IFNL3/IFNL4 rs8099917 TT TG/GG IFNL3/IFNL4 rs12979860 CC CT/TT Recessive model PNPLA3 rs738409 CC/CG
Steatosis Absent Present (n=147) (n=143)
0.29 0.16
1.19 3.28 0.365
0.61 0.78
1.63 3.88 0.284
0.70
3.33 0.203
0.81 0.90
2.36 3.13 0.754
0.005 1.22
3.11 0.133
0.31
1.17 0.654
0.70
1.77 0.089
0.94
2.38 0.999
0.028 108 (55.4)
87 (44.6)
1.00
Journal Pre-proof GG PNPLA3 rs2294918 GG/GA AA MTTP rs1800591 GG/GT TT IFNL3/IFNL4 rs8099917 TT/TG GG IFNL3/IFNL4 rs12979860 CC/CT TT
39 (41.5)
55 (58.5)
32 1.75
1.06
2.88 0.739
134 (50.8) 4 (57.1)
130 (49.2) 3 (42.9)
1.00 0.77
135 (52.3) 12 (38.7)
123 (47.7) 19 (61.3)
1.00 1.74
123 (52.8) 24 (42.9)
110 (47.2) 32 (57.1)
1.00 1.49
129 (51.8) 18 (45.0)
120 (48.2) 22 (55.0)
1.00 1.31
0.17
3.52 0.156
0.81
3.73 0.183
0.83
2.69 0.425
0.67
2.57
f
SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval.
oo
Bivariate tests; *The presence of the TM6SF2 rs58542926 mutated genotype
Jo u
rn
al
Pr
e-
pr
was not detected.
Journal Pre-proof
33
Table 4. Analysis of each SNP (dominant model) combined with HCV genotype 3 infection in the presence of hepatic steatosis and fibrosis in patients with chronic hepatitis C. 95% CI Low Upper
1.66 0.61 0.22 2.61 2.17 3.58
0.32 0.12 0.03 0.14 0.42 0.33
1.32 6.72 0.99 1.50 0.61 0.39
0.31 1.51 0.15 0.14 0.15 0.04
p
OR*
95% CI Low Upper
0.546 0.548 0.155 0.526 0.354 0.294
0.66 0.29 2.99 2.10 3.99
0.13 0.03 0.16 0.40 0.36
3.34 2.47 56.27 10.95 43.93
0.614 0.258 0.464 0.379 0.258
8.34 1.38 1.84 0.55 0.40
1.78 0.21 0.17 0.13 0.04
39.13 9.22 20.59 2.34 3.87
0.007 0.741 0.620 0.414 0.431
oo
f
8.64 3.07 1.76 50.38 11.09 38.57 5.72 29.98 6.33 15.68 2.50 3.58
pr
Fibrosis HCV-3 by PNPLA3 rs738409 HCV-3 by MTTP rs1800591 a HCV-3 by TM6SF2 rs58542926 HCV-3 by PNPLA3 rs2294918 HCV-3 by IFNL3/IFNL4 rs8099917 b HCV-3 by IFNL3/IFNL4 rs12979860 Steatosis HCV-3 by PNPLA3 rs738409 HCV-3 by MTTP rs1800591 HCV-3 by TM6SF2 rs58542926a HCV-3 by PNPLA3 rs2294918 HCV-3 by IFNL3/IFNL4 rs8099917 HCV-3 by IFNL3/IFNL4 rs12979860b
OR
e-
Variable
0.708 0.013 0.989 0.733 0.487 0.405
Pr
HCV-3, HCV genotype 3; SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval.
al
Logistic regression adjusted for age, gender, BMI, alcohol consumption; * Model
(genotype CG/GG)
The presence of the TM6SF2 rs58542926 mutated genotype (TT) was not
Jo u
a
rn
adjusted for all variables from previous model plus PNPLA3 rs738409
detected, because of that was analysed as CC x CT instead of the dominant model. b
The presence of the IFNL3/IFNL4 rs12979860 wild genotype (CC) was not
detected in patients with steatosis or fibrosis because of that was analysed as CT x TT instead of the dominant model.
p
Journal Pre-proof
34
Table 5. Analysis of the combined effect of independent SNPs (dominant model) in the presence of hepatic steatosis and fibrosis in patients with chronic hepatitis C. 95% CI Variable
95% CI
OR
p
OR*
p
Low
Upper
Low
Upper
0.32
19.58 0.387
Fibrosis a
TM6SF2 rs58542926 x MTTP rs1800591
2.77
0.38
20.26 0.316 2.49
PNPLA3 rs738409 x MTTP rs1800591
1.13
0.29
4.31
MTTP rs1800591 x PNPLA3 rs2294918
3.34
0.28
39.65 0.340 2.73
0.23
31.84 0.422
0.42
0.11
1.56
0.10
1.42
0.148
0.20
8.00
0.799
b
f
1.11
0.18
6.91
a
TM6SF2 rs58542926 x PNPLA3 rs738409
5.91
0.58
60.21 0.134
a
2.52
0.20
32.26 0.477 2.41
0.17
33.42 0.513
1.93
0.29
12.66 0.493 2.04
0.29
14.39 0.474
1.81
0.15
22.00 0.640 1.99
0.16
24.30 0.590
2.01
0.26
15.41 0.503
0.55
0.15
2.08
0.380
0.64
0.09
4.32
0.643
0.26
0.03
1.96
0.191 0.21
0.03
1.66
2.54
0.24
27.02 0.440 1.49
0.13
16.63 0.744
0.18
0.03
1.16
0.072 0.19
0.03
1.22
0.079
TM6SF2 rs58542926a x MTTP rs1800591
0.51
0.10
2.64
0.418 0.40
0.07
2.15
0.284
Jo u
MTTP rs1800591 x IFNL3/IFNL4 rs12979860
0.192 0.37
oo
MTTP rs1800591 x IFNL3/IFNL4 rs8099917
0.863
PNPLA3 rs738409 x MTTP rs1800591
2.45
0.87
6.92
0.091
MTTP rs1800591 x PNPLA3 rs2294918
0.69
0.15
3.18
0.636 0.64
0.14
2.96
0.566
0.99
0.36
2.75
0.983 0.96
0.34
2.70
0.934
0.20
3.60
0.820
pr
TM6SF2 rs58542926 x PNPLA3 rs2294918 a
TM6SF2 rs58542926 x IFNL3/IFNL4 rs8099917 TM6SF2 rs58542926 x IFNL3/IFNL4 rs12979860
b
e-
a
PNPLA3 rs738409 x IFNL3/IFNL4 rs8099917
Pr
PNPLA3 rs738409 x PNPLA3 rs2294918 b
PNPLA3 rs738409 x IFNL3/IFNL4 rs12979860 IFNL3/IFNL4 rs8099917 x PNPLA3 rs2294918 b
al
IFNL3/IFNL4 rs12979860 x PNPLA3 rs2294918 b
rn
IFNL3/IFNL4 rs12979860 x IFNL3/IFNL4 rs8099917 Steatosis
MTTP rs1800591 x IFNL3/IFNL4 rs8099917 b
MTTP rs1800591 x IFNL3/IFNL4 rs12979860
0.910 1.27
0.140
0.73
0.18
3.02
0.665 0.85
a
TM6SF2 rs58542926 x PNPLA3 rs738409
1.00
0.16
6.21
0.997
a
1.09
0.12
10.09 0.942 1.02
0.11
9.58
0.984
1.59
0.30
8.35
0.587 1.57
0.29
8.43
0.598
0.21
0.02
1.85
0.160 0.21
0.02
1.86
0.160
2.25
0.50
10.23 0.292
0.78
0.28
2.17
0.632
PNPLA3 rs738409 x by IFNL3/IFNL4 rs12979860
0.56
0.13
2.39
0.430
IFNL3/IFNL4 rs8099917 x PNPLA3 rs2294918
TM6SF2 rs58542926 x PNPLA3 rs2294918 a
TM6SF2 rs58542926 x IFNL3/IFNL4 rs8099917 a
TM6SF2 rs58542926 x IFNL3/IFNL4 rs12979860
b
PNPLA3 rs738409 x PNPLA3 rs2294918 PNPLA3 rs738409 x IFNL3/IFNL4 rs8099917 b
0.64
0.15
2.73
0.547 0.60
0.14
2.58
0.488
b
0.95
0.15
6.01
0.957 0.58
0.09
3.87
0.571
b
0.83
0.20
3.45
0.796 0.82
0.19
3.52
0.794
IFNL3/IFNL4 rs12979860 x PNPLA3 rs2294918 IFNL3/IFNL4 rs12979860 x IFNL3/IFNL4 rs8099917
Journal Pre-proof
35
SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval. Logistic regression adjusted for age, gender, BMI, alcohol consumption; * Model adjusted for all variables from previous model plus PNPLA3 rs738409 (genotype CG/GG) a
The presence of the TM6SF2 rs58542926 mutated genotype (TT) was not
detected, because of that was analysed as CC x CT instead of the dominant model.
f
The presence of the IFNL3/IFNL4 rs12979860 wild genotype (CC) was not
oo
b
Jo u
rn
al
Pr
e-
CT x TT instead of the dominant model.
pr
detected in patients with steatosis or fibrosis because of that was analysed as