Published online May 27, 2026. doi: 10.4254/wjh.v18.i5.116995
Revised: January 23, 2026
Accepted: March 4, 2026
Published online: May 27, 2026
Processing time: 181 Days and 15.9 Hours
Chronic hepatitis C (CHC) infection remains a significant global health burden often progressing to hepatic fibrosis and cirrhosis, which may ultimately result in hepatocellular carcinoma. Liver fibrosis development is governed by complex host-pathogen interaction, including genetic susceptibility and immune dysregulation. IFI16 and AIM2 inflammasomes serve as critical modulators of inflammation and pathogen pathways.
To determine the association of variants IFI16 (rs1057028) and AIM2 (rs2814770) with hepatic fibrosis progression in Pakistani CHC patients.
This study recruited 378 CHC patients from Lahore General Hospital (tertiary care hospital). Study participants were selected based on hepatitis C virus (HCV)-RNA positivity and transient elastography confirmed hepatic fibrosis. A total of 378 CHC patients for IFI16 genetic variant and 140 CHC patients for AIM2 variant were genotyped using amplification refractory mutation system assays. χ2 test, t-test, Mann-Whitney U test, combined genotype effect, and logistic regression analysis was performed determine association between target single nucleotide polymorphisms and progression of HCV-related fibrosis and cirrhosis.
Results of our study showed that only AIM2 rs2841770 variant genotype TT shows significant association with a higher risk of advanced stage of liver fibrosis (OR = 4.83, P = 0.05). Combined genotype analysis had shown that CHC patients having A allele of rs1057028 and T allele of rs2814770 are significantly associated with increased risk of hepatic fibrosis (OR = 2.6, 95%CI: 1.16-5.86, P = 0.022). Our findings also revealed a significant trend of increasing frequency of liver fibrosis with an increased number of risk alleles of IFI16 rs1057028 and AIM2 rs2814770. In univariate regression analysis, body mass index and alanine aminotransferase levels significantly associated with increased risk of liver fibrosis.
This study suggests that AIM2 rs2814770 and its combined effect with IFI16 rs1057028 may be increase susceptibility to hepatic fibrosis in CHC patients, highlighting immunogenetic modulation, warranting further research for predictive biomarkers.
Core Tip: Hepatic fibrosis progression in chronic hepatitis C (CHC) is influenced by complex immunogenetic factors. This study demonstrates that the AIM2 (rs2814770) TT genotype and combined carriage of variants rs1057028 (A allele) of IFI16 and rs2814770 (T allele) of AIM2 significantly increases the risk of advanced liver fibrosis in Pakistani CHC patients. A dose-dependent rise in fibrosis severity with increasing risk alleles further supports their pathogenic relevance. These findings suggest a potential role of IFI16 and AIM2 genetic variants as predictive biomarkers for fibrosis progression, underscoring the need for expanded studies to validate their clinical utility.
- Citation: Arshad I, Majid M, Rauff B, Amar A, Choudhery MS. Genetic polymorphism of IFI16 and AIM2 among Pakistani hepatitis C virus-induced fibrosis patients. World J Hepatol 2026; 18(5): 116995
- URL: https://www.wjgnet.com/1948-5182/full/v18/i5/116995.htm
- DOI: https://dx.doi.org/10.4254/wjh.v18.i5.116995
The liver is an essential organ with multifaceted roles in metabolism, detoxification, synthesis, storage, and immune function. Disruptions in any of these functions whether due to disease or injury can lead to the development of hepatic diseases like hepatitis C and hepatitis B. Chronic hepatitis C (CHC) virus infection represents a global health concern, affecting millions of individuals worldwide and significantly contributing to the liver disease burden. Globally, approximately 57 million people are estimated to suffer from CHC virus infection[1]. Pakistan bears the world’s second-highest burden of hepatitis C virus (HCV) infection, with 9.8 million people living with HCV infection and a national prevalence of 4.1%[2]. The healthcare system of Pakistan is under strain due to high HCV prevalence, necessitating improved diagnostic tools for detecting liver damage progression. Each year, 100000-200000 new cases of HCV-related cirrhosis are reported, emphasizing the need for improved treatment options[3]. HCV does not exhibit symptoms in its early stages. However, it can progress to severe liver diseases/injuries if not treated[4]. Liver fibrosis is a major liver injury that occurs from a prolonged wound-healing response to ongoing liver damage. Different factors, such as chronic HCV and hepatitis B virus (HBV) infections, alcoholic liver disease, metabolic dysfunction, non-alcoholic steatohepatitis, and autoimmune diseases contribute to chronic liver inflammation. Liver fibrosis, marked by excessive or abnormal accumulation of extracellular matrix proteins, is a hallmark of chronic hepatic diseases, including those caused by HCV infection. Liver fibrosis is a multifactorial disease, but genetic factors and an overactive immune response mediated by an imbalance between pro- and inflammatory cytokines are key mediators in the development and severity of liver fibrosis. The uncontrolled activation of inflammasomes and cytokines is a significant contributor in the pathogenesis of HCV-induced liver fibrosis[5]. Genetic variations have been identified in IL28B, interferon lambda-4, interferonλ, and their association with HCV patients has been studied in Pakistan and other ethnicities[6-8]. Previous studies have also highlighted that the activation of AIM2 and IFI16 is up-regulated in acute and chronic hepatitis B infections[9]. The impact of IFI16 has also been identified in different diseases such as periodontitis, aseptic inflammation and viral hepatitis[10].
Interferon-inducible protein 16 (IFI16) is a nuclear and cytoplasmic DNA sensor that plays a critical determinant in the innate immune response to viral and microbial infections. It is a member of the pyrin and HIN domain-containing, protein family and is transcribed by the IFI16 gene. The IFI16 gene significantly contributes to the innate immune response against viruses by detecting foreign DNA in a cell and modulating the inflammatory response against double-stranded DNA (dsDNA)[11]. This activation triggers a range of immune pathways that results in the release of type I interferons and pro-inflammatory cytokines, inflammasome formation, regulation of gene expression, and induction of apoptosis and cellular senescence[10,12]. Over activation of the IFI16 gene contributes to the prolonged activation of inflammatory cytokines that induce liver pathology by aberrant activation of hepatic stellate cells, subsequently driving to aberrant extracellular matrix production and fibrosis[13].
AIM2 gene transcribes a cytosolic innate immune sensor that recognizes the dsDNA within the cell. AIM2 gene plays a key role in host defense, inflammation, and immune responses[14]. Liver Kupffer cells exhibit high expression of AIM2 in both protein and mRNA levels and secrete substantial amount of interleukin-1 beta (IL-1β) upon AIM2 activation[15].
Activation of IFI16 and AIM2 is also upregulated in acute and chronic hepatitis B infections[9]. The impact of IFI16 dysregulation has been identified in different diseases such as periodontitis, aseptic inflammation and viral hepatitis[10]. Different single nucleotide polymorphisms (SNPs) in the AIM2 gene and IFI16 genes have been found as a possible biomarker for a variety of infectious and chronic inflammatory diseases[16]. Understanding how genetic variations of IFI16 and AIM2 genes influence the development and progression of liver fibrosis and cirrhosis could provide crucial insights for more effective management and treatment strategies. The present research seeks to bridge existing knowledge gaps and provide new perspectives on the genetic underpinnings of liver disease associated with chronic HCV infection. For this purpose, this study evaluated the role of AIM2 (rs2814770) and IFI16 (rs1057028) SNPs as potential biomarkers for liver disease progression in a cohort of Pakistani CHC patients, with liver fibrosis staged using transient elastography.
The current study and procedures were approved by the Undergraduate Ethical Review Committee of University of Health Sciences, Lahore (Approval No. UHS/UERC-25/SEC/03 and No. UHS/UERC-25/SEC/04), following the ethical standards outlined in the Declaration of Helsinki. A total of 378 CHC patients presenting at a tertiary care hospital in Lahore (Lahore General Hospital) that receives patients from Lahore as well as multiple districts of Punjab, were recruited in this study. Although the study cohort is hospital-based but broad referral catchment area likely reflects the heterogeneity of regional population beyond a single locality. All participants gave written informed consent prior to enrollment. This study included all CHC patients who tested positive for HCV-RNA in their bloodstream using PCR, had liver fibrosis, underwent transient elastography (Fibroscan®), were treatment-naïve, and consented to provide blood samples for genetic analysis. Exclusion criteria for the current study included alcoholism, autoimmune hepatitis, coinfection with other viruses that may impact the health of the liver (such as HBV, hepatitis D virus, and alpha1-antitrypsin deficiency, human immunodeficiency virus), Wilson’s disease, and previous or current liver injury and evidence of non-CHC hepatic pathologies by standard clinical and laboratory examination. Each selected patient provided demographic and clinical data, including age, gender, body mass index (BMI), ethnicity, HCV virus load, and regular liver function tests. BMI (kg/m2) was computed by dividing the body weight (kilogram) by the square of height (meters).
Cirrhosis and hepatic fibrosis in CHC patients were assessed by imaging analysis using probes SN77561 and SN94171, with specifically transient elastography using Fibroscan® (Echosens, Waltham, and North America). The highest sensitivity and specificity, as reported earlier[6,17], were obtained by defining Metavir fibrosis stages (F0-F3) and cirrhosis (F4) using Ziol transient elastography cut-offs. Metavir fibrosis stages were used to identify hepatic cirrhosis as F4, advanced hepatic fibrosis as > F3, and significant hepatic fibrosis as ≥ F2.
Genomic DNA was purified from EDTA-anticoagulated whole blood samples using the DNeasy Blood Kit (QIAGEN, Germany) by mixing anticoagulated blood with proteinase K, PBS, and Buffer AL, followed by applying mixture to DNeasy spin column. Spin column was then washed to remove impurities and the DNA was eluted in the elution buffer. Genotyping of target IFI16 rs1057028 and AIM2 rs2814770 SNPs was performed using custom-designed amplification refractory mutation system (ARMS) based genotyping assays. Tetra primers were designed using primer 1 (https://primer1.soton.ac.uk/primer1.html) for ARMS-PCR and validated using different Insilico tools, including the University of California Santa Cruz genome browser (https://genome.ucsc.edu/cgi-bin/hgBlat), IDT oligoanalyzer (https://www.idtdna.com/pages/tools/oligoanalyzer), OligoCalc (https://mcb.berkeley.edu/Labs/krantz/tools/oligocalc.html). Primer details for both genes are presented in Supplementary Tables 1 and 2. Genomic DNA was amplified by preparing 15 µL reaction mixture using specific set of four primers (outer forward, outer reverse inner forward and inner reverse). Amplification conditions for both genes are shown in Supplementary Figures 1 and 2. Respective genotypes for each sample were interpreted after analyzing the ARMS amplification products on 2% agarose gels, and the product size for interpretation of genotypes of IFI16 rs1057028 and AIM2 rs2814770 are shown in Supplementary Table 3.
Representative gel images are shown in Supplementary Figure 3 for IFI16 rs1057028 and Supplementary Figure 4 for AIM2 rs2814770.
Data were analyzed statistically using GraphPad Prism, SPSS software, and SNPStat online tool (https://www.snpstats.net/start.htm) for analyzing SNP data in genetic association studies, including genotype distribution, Hardy-Weinberg test, and model-based evaluation of SNP effect, combined genotype analysis, and regression with covariates.
Descriptive statistics were used to demonstrate the qualitative features of liver fibrosis patients [age, gender, BMI, metavir stage, HCV-RNA load, alanine aminotransferase (ALT), aspartate aminotransferase (AST), and total bilirubin]. A normality test (Shapiro-Wilk test) was applied to determine the normal distribution status of quantitative variables for descriptive analysis of CHC patients’ baseline data. Quantitative variables with normal distribution were estimated as mean ± SD, whereas those deviating from normal distribution were estimated as median (interquartile range). χ2 test was performed using the SNPStat tool to evaluated the association between the severity of liver fibrosis and the IFI16 rs1057028 and AIM2 rs2814770 SNPs. Dominant and recessive genetic models were also employed to investigate the impact of the IFI16 rs1057028 and AIM2 rs2814770 SNP polymorphisms on the progression of hepatic fibrosis and cirrhosis. Model selection was guided by the Akaike Information Criterion (AIC), where the model with lowest AIC value was considered the best-fit. ORs accompanied by 95%CIs and corresponding P values were calculated to evaluate the strength and statistical significance of association between the IFI16 rs1057028 and AIM2 rs2814770 SNP polymorphisms and the severity of liver fibrosis for each model. A combined genotyping analysis was also performed using the SNPStat online tool to evaluate the association of different combinations of alleles with the risk of liver damage in CHC patients. Allelic and genotypic frequencies were described as n (%). Quantitative data were compared between groups using the Student’s t-test or, when appropriate, non-parametric Mann-Whitney U or Kruskal-Wallis tests. Categorical data and group associations were analyzed using Fisher’s exact test or the χ2 test as applicable. Pooled analysis of both SNPs was also performed to examine the effect of the combination of polymorphism of variant alleles in liver enzymes using the Kruskal-Wallis test with GraphPad Prism software. The impact of age, gender, BMI, HCV-RNA, ALT, AST, total bilirubin, and IFI16 (TT) genotype on liver fibrosis progression was assessed using logistic regression with results presented as OR and 95%CI. Functional annotation of IFI16 rs1057028 and AIM2 rs2814770 variants was initially performed using ReguolmeDB to assess predicted regulatory features, transcription factor binding and chromatin state https://regulomedb.org/regulome-search/. Subsequently, the Genotype-Tissue-Expression (GTEx) database was queried to assess the genotype-specific effects of IFI16 rs1057028 and AIM2 rs2814770 variants on tissue-specific gene expression profiles. The GTEx project is an online database that provides publicly available expression quantitative trait loci (eQTL) data across multiple healthy human tissue, available at GTEx portal https://www.gtexportal.org/. This analysis aimed to determine whether these variants confer loss-of-function consequences or exhibit cis-regulatory eQTL activity, thereby elucidating their potential functional significance. Furthermore, to elucidate possible interaction and interplay of IFI16 and AIM2 in modulating inflammatory pathways potentially involved in immunomolecular pa
This study enrolled 378 patients with chronic HCV infection (CHC), representing a spectrum from no/minimal fibrosis to advanced fibrosis and cirrhosis. The baseline characteristics including demographic, clinical, and laboratory parameters of the study participants are shown in Table 1. The median age was 40 (32-50) years, with 189 (50%) of females. The median BMI was 26.8 (24-30) kg/m2, indicating that most patients were in the overweight range, and the median of HCV RNA load was log10 4.58 (3.75-5.41) IU/mL. Liver function tests showed elevated levels of ALT and AST with a median of 59 (41-88) IU/L and 55 (39.2-89.5) IU/L, respectively. Total bilirubin was in the normal range with a median of 0.8 mg/dL. According to Metavir staging, 223 (59.5%) of patients had no/minimal fibrosis (F0-F1), 17 (4.5%) had significant fibrosis (F2), 59 (15.7%) had advanced fibrosis (F3), and 76 (20.3%) presented with cirrhosis (F4). Frequency distribution of all variables was statistically significant with P < 0.05 as shown in Table 1. In the whole sample set, genotype analysis of IFI16 rs1057028 (n = 378) showed that AA 209 (55.3%) genotype was most frequent, followed by AT 100 (26.5%), and TT 69 (18.3%), with allele frequencies of A = 518 (69%) and T = 238 (31%). For AIM2 rs2814770 (n = 140), genotype distribution was: CC 41(29.3%), CT 60 (42.9%), and TT 39 (27.9%), with allele frequencies of C = 142 (51%) and T = 138 (49%).
| Characteristics | CHC patients (n = 378) |
| Age (years) | 40 (32-50) |
| BMI (kg/m2) | 26.8 (24-30) |
| HCV-RNA log10 (IU/mL) | 4.58 (3.75-5.41) |
| ALT (IU/L) | 59 (41-88) |
| AST (IU/L) | 55 (39.2-89.5) |
| Bilirubin (mg/dL) | 0.8 (0.7-0.9) |
| Metavir staging | |
| F0-F1 | 223 (59.5) |
| F2 | 17 (4.5) |
| F3 | 59 (15.7) |
| F4 | 76 (20.3) |
| IFI16 rs1057028 (n = 378) | |
| AA | 209 (55.3) |
| AT | 100 (26.5) |
| TT | 69 (18.3) |
| A | 518 (69) |
| T | 238 (31) |
| AIM2 rs2814770 (n = 140) | |
| CC | 41 (29.3) |
| CT | 60 (42.9) |
| TT | 39 (27.9) |
| C | 142 (51) |
| T | 138 (49) |
IFI16 rs1057028 polymorphism has been analyzed to determine its potential role in liver fibrosis progression by comparing allele and genotype distribution between patients having early stage (F0-F1) and advanced stage (F2-F4) fibrosis. The distribution of IFI16 rs1057028 genotypes in the control group was almost conferred with Hardy-Weinberg equilibrium (HWE; P = 0.05). In advanced fibrosis, comparison of homozygous variant genotype T/T of IFI16 rs1057028 revealed a higher proportion of T/T genotype among patients with advanced fibrosis (F2-F4) 22.7% compared to those with mild fibrosis (F0-F1) 16.1%, however, this association was not statistically significant (P = 0.14). The variant allele T of IFI16 rs1057028 non-significantly increases the risk of advanced fibrosis among CHC patients (OR = 1.24, P = 0.91). The distribution of genotypic and allelic frequencies of IFI16 rs1057028 considering the advanced fibrosis ≥ F2 is shown in Table 2.
| SNP | Model | Genotype | CHC patients | OR (95%CI) | P value | AIC | |
| Fibrosis grade (F0-F1), | Fibrosis grade (F2-F4), | ||||||
| IFI16 (rs1057028) | Genotypic | A/A | 125 (57.3) | 76 (50.7) | 1.00 | 0.14 | 463.7 |
| A/T | 58 (26.6) | 40 (26.7) | 1.20 (0.71-2.03) | ||||
| T/T | 35 (16.1) | 34 (22.7) | 1.81 (1.01-3.23) | ||||
| Allelic | A | 316 (71) | 196 (64) | 1.00 | 0.91 | NA | |
| T | 130 (29) | 108 (36) | 1.24 (0.91-0.68) | ||||
| Dominant | A/A | 125 (57.3) | 76 (50.7) | 1.00 | 0.12 | 463.2 | |
| A/T-T/T | 93 (42.7) | 74 (49.3) | 1.43 (0.91-2.22) | ||||
| Recessive | A/A-A/T | 183 (83.9) | 116 (77.3) | 1.00 | 0.06 | 462.1 | |
| T/T | 35 (16.1) | 34 (22.7) | 1.70 (0.98-2.96) | ||||
Analysis of AIM2 rs2814770 polymorphism in association with the progression of liver fibrosis revealed distinct genotype distribution between patients with no/minimal fibrosis (F0-F1) and advanced fibrosis (F2). The allelic and genotypic frequencies of distribution of AIM2 rs2814770 were in accordance to HWE in the control group (P > 0.05) as shown in Table 2. Under the genotypic model, the AIM2 rs2814770 variant genotype, in homozygous T/T or heterozygous C/T form, increases the risk of significant liver fibrosis among CHC patients (OR = 4.86 and 2.00, respectively; P = 0.05). Similarly, a highly significant association was found under the recessive model with a three-fold increased risk of advanced fibrosis among CHC patients having T/T genotype (OR = 3.13 and P = 0.03). However, no significant allelic or dominant model associations were detected (all P > 0.05). The distribution of genotypic and allelic frequencies of AIM2 rs2814770 considering the advanced fibrosis ≥ F2 are shown in Table 3.
| SNP | Model | Genotype | CHC patients | OR (95%CI) | P value1 | AIC | |
| Fibrosis grade (F0-F1), n = 70 | Fibrosis grade, (F2-F4), n = 70 | ||||||
| AIM2 rs2841770 | Genotypic | C/C | 24 (34.8) | 17 (24.3) | 1.00 | 0.05 | 125.3 |
| C/T | 26 (37.7) | 33 (47.1) | 2.00 (0.66-6.09) | ||||
| T/T | 19 (27.5) | 20 (28.6) | 4.86 (1.27-18.58) | ||||
| Allelic | C | 75 (54) | 67 (48) | 1.00 | 0.40 | NA | |
| T | 65 (46) | 73 (52) | 1.12 (0.79-2.01) | ||||
| Dominant | C/C | 24 (34.8) | 17 (24.3) | 1.00 | 0.058 | 125.5 | |
| C/T-T/T | 45 (65.2) | 53 (75.7) | 2.66 (0.94-7.50) | ||||
| Recessive | C/C-C/T | 50 (72.5) | 50 (71.4) | 1.00 | 0.038 | 124.8 | |
| T/T | 19 (27.5) | 20 (28.6) | 3.13 (1.03-9.56) | ||||
The combined genotype analysis was performed to determine any potential effect of allelic combinations of IFI16 rs1057028 and AIM2 rs2814770 genetic variants among no/minimal fibrosis (F0-F1) and advanced fibrosis (F2-F3) with 140 samples set for each. The results have shown that CHC patients having the A allele of rs1057028 and the T allele of rs2814770 are significantly presented with a higher risk of hepatic fibrosis (OR = 2.6, 95%CI: 1.16-5.86, P = 0.022). A variant allele T in both SNPs suggests a slightly significant association of risk of advanced stage (F2-F3) of hepatic fibrosis (OR = 2.41, 95%CI: 0.98-5.91, P = 0.057). These results are shown in Table 4.
| Combined genotypes rs1057028 A/T, rs2814770 C/T | Frequency | Case, control ratios | OR (95%CI interval) | P value corrected1 |
| A-C | 0.3673 | 0.2595, 0.4703 | 1.00 | - |
| A-T | 0.2874 | 0.2905, 0.294 | 2.60 (1.16-5.86) | 0.022 |
| T-T | 0.2054 | 0.231, 0.1703 | 2.41 (0.98-5.91) | 0.057 |
| T-C | 0.1399 | 0.219, 0.0654 | 2.40 (0.74-7.82) | 0.15 |
We also evaluated the association of IFI16 rs1057028 and AIM2 rs2814770 polymorphism with baseline clinical and laboratory features of HCV patients. There were no significant associations seen with baseline characteristics, including liver function test (ALT, AST, and total bilirubin) for IFI16 rs1057028 (all P > 0.05) as represented in Table 5. Similarly, there was no significant association between AIM2 rs2814770 genotype under recessive model and any of the clinical variables, including gender, age, HCV RNA levels, liver enzymes (ALT and AST), and total bilirubin, except BMI (Table 6). Genetic association analysis of IFI16 (rs1057028) and AIM2 (rs2814770) with significant hepatic fibrosis after stratification of CHC patients into obese and non-obese groups based on BMI status, below 40 years and above 40 years groups of age and ALT levels of threshold of 60 IU/mL was carried out. None of these analyses gave a statistically significant association with any group (Figure 1).
| Measure | IFI16 (rs1057028) recessive model | P value | |
| A/A + A/T (n = 309) | T/T (n = 69) | ||
| Age (years) | 40 (32-50) | 40 (33-45) | 0.87 |
| Gender | |||
| Female | 153 (80.95) | 36 (19.05) | 0.7 |
| Male | 155 (82.45) | 33 (17.55) | |
| BMI (kg/m2) | 26.85 (24-30) | 26.8 (24-30.7) | 0.68 |
| HCV-RNA log10 (IU/mL) | 4.57 (3.7-5.4) | 4.75 (5.4-3.7) | 0.86 |
| ALT (IU/L) | 60 (39-88) | 57 (42-94.5) | 0.69 |
| AST (IU/L) | 56 (40-83) | 51 (38.5-83.5) | 0.63 |
| Bilirubin (mg/dL) | 0.8 (0.7-0.9) | 0.8 (0.7-0.95) | 0.22 |
| Measure | AIM2 (rs2814770) recessive model | P value1 | |
| C/C + C/T (n = 101) | T/T (n = 39) | ||
| Age (years) | 38 (31-48.7) | 40 (30-48) | 0.54 |
| Gender | |||
| Female | 54 (77.1) | 16 (22.9) | 0.18 |
| Male | 47 (67.1) | 23 (32.9) | |
| BMI (kg/m2) | 27.2 (23.8-30.9) | 24.5 (22.4-29.4) | 0.05 |
| HCV-RNA log10 (IU/mL) | 4.7 (3.8-5.3) | 4.67 (3.9-5.4) | 0.89 |
| ALT (IU/L) | 57 (37-89.5) | 61 (42-98) | 0.21 |
| AST (IU/L) | 53 (40.2-80.7) | 62.5 (35-86.2) | 0.37 |
| Bilirubin (mg/dL) | 0.8 (0.7-0.9) | 0.8 (0.7-0.95) | 0.45 |
We performed a pooled analysis of IFI16 rs1057028 and AIM2 rs2814770 polymorphic variants to see their effect on liver enzymes. There was no significant increase in liver enzymes (ALT and AST) of hepatic injury with the presence of an increased number of risk alleles of either SNP as shown in Figure 2.
We also evaluated the 140 patients for the association of an increasing trend of liver fibrosis with an increasing number of risk alleles. Results have shown a statistically significant increasing trend of liver fibrosis with a higher number of risk alleles of IFI16 rs1057028 and AIM2 rs2814770. The proportion of significant/advanced in CHC patients across an increasing number of risk alleles is shown in Figure 3.
Logistic regression analysis was conducted to examine the independent effects of demographic, clinical, and genetic factors in relation to disease progression. Among these factors with significant predictive ability, age, BMI, and ALT were identified. Thus, an additional year in age increases the odds of disease by 6% (OR = 1.06; 95%CI: 1.03-1.08; P < 0.001), signifying that older patients are at greater risk. In the same manner, an increase in BMI associated with an increase in disease risk was represented by a 7% increase in odds per 1-unit increase (OR = 1.07; 95%CI: 1.01-1.13; P = 0.017), highlighting the potential contribution of body weight in disease progression. Furthermore, increased levels of ALT were significantly associated with the disease (OR = 1.007; 95%CI: 1.00-1.01; P = 0.017), representing possible liver injury or ongoing inflammation. In contrast, gender, HCV-RNA viral load, AST, total bilirubin, and the IFI16 rs1057028 TT genotype were not found to be statistically significantly associated with disease progression (all P > 0.05). Results of logistic regression are presented in Table 7.
According to RegulomeDB, both rs1057028 and rs2841770 have a score of 1f, indicating eQTL evidence for regulatory function but lacking direct transcription factor binding or chromatin accessibility support. Variant rs1057028 has a rank of 0.55, indicating moderate-to-low regulatory likelihood, and rs2814770 has a rank of 0.195, indicating a moderate probability of regulatory function. This suggests that both rs1057028 and rs2814770 may influence gene expression through indirect regulatory mechanisms (Supplementary Table 4).
We further explored the tissue-specific functional significance of the analyzed genetic variants using the GTEx database. We did not find any eQTL/splicing quantitative trait loci data for the tissue-based functional significance of IFI16 rs1057028 and AIM2 rs2814770 in the liver. However, these target SNPs were evident as significant eQTLs modulating genotype-specific target gene expression of IFI16 and AIM2 in skin, mucosa, spleen, and whole blood (Supplementary Table 5 and 6).
STRING database-based protein-protein interaction network analysis results showed direct potential interactions of IFI16 and AIM2 with each other and also with other inflammatory response as well as cellular apoptosis mediators/regulators. These included PYCARD, CASP1, MEFV and NLRC4 (common for both IFI16 and AIM2), as well as STING1 (specific for IFI16) and NLRP1, NLRP3, NLRP6, NLRP12, CASP5 and NAIP (specific for AIM2) as reflected in Figure 4. These pro-inflammatory and apoptotic proteins potentially play key roles in immune mediated fibrosis development and progression in hepatic tissues seen in liver fibrosis patients. Therefore, functional genetic polymorphisms of IFI16 and AIM2 genes (especially IFI16 rs1057028 and AIM2 rs2814770) can influence their expression, which in turn can modulate the expression of interacting inflammatory response proteins, ultimately leading to altered risk and progression in liver fibrosis.
Association of IFI16 rs1057028 and AIM2 rs2814770 genetic polymorphisms with the progression of hepatic fibrosis were evaluated in a Pakistani cohort of CHC patients. We genotyped a total of 378 liver fibrosis patients for IFI16 rs1057028 and 140 patients for AIM2 rs2814770, staged fibrosis by transient elastography and tested multiple genetic models. Our findings indicate a significant association between the AIM2 rs2814770 variant and increased risk of advanced hepatic fibrosis, while no such association was observed for IFI16 rs1057028. A combined-genotype analysis suggested a higher fibrosis risk for carriers of IFI16-AIM2 A-T combined genotype. BMI, age, and ALT were identified as independent clinical modifiers of hepatic fibrosis severity. Findings of a recent study reveal that the overexpression of the IFI16 gene is significantly associated with increased levels of liver enzymes ALT and AST in HBV-infected patients[13]. A comparative study has also revealed that AST, ALT, and total bilirubin levels were increased in viral hepatitis patients[18]. Older age was associated with increased risk, consistent with recent literature that defined age as the key factor for liver disease progression[19-21]. BMI has been recognized as an independent indicator of decomposition in cirrhotic patients from the United States and European ethnicities[22]. A Japanese study also revealed that overweight and obesity were inde
Findings of this study provide a contributory role of AIM2-related innate immune pathways in HCV-associated fibrogenesis in this population. AIM2 encodes an innate immune sensor involved in inflammasome formation and the secretion of pro-inflammatory cytokines, which are implicated in fibrotic processes. Previous studies have linked AIM2 overexpression with the progression of liver fibrosis, cirrhosis, and hepatocellular carcinoma[26,27]. However, no significant correlation was found between AIM2 polymorphism and clinical variables, except BMI, suggesting a genotype-specific effect on fibrosis progression.
In contrast, the IFI16 rs1057028 missense variant did not show a significant association with fibrosis severity, and its functional relevance in hepatic disease remains uncertain. However, IFI16 rs1057028, considering severe fibrosis and cirrhosis was also analyzed, which did not show a strong significant association in modulating liver fibrosis in CHC patients. This finding aligns with a recent study that emphasized the fundamental role of IFI16 in metabolic dysfunction-associated steatotic liver disease (MASLD), which suggests that the IFI16 rs6940 variant (A>T) confers conformational changes in the DNA binding domain and enhances the HINb domain stability, increases its dsDNA binding affinity, and potentially enhances the inflammatory responses[28]. Genome-wide association studies (GWAS) also revealed that the missense IFI16 rs1057028 (A>T) SNP is significantly associated with periodontal disease and showed significant association with increased pocket depth (PD), bleeding on probing (BOP), elevated gingival crevicular fluid IL-1β levels, greater periodontal pathogen loads, and higher frequency of severe periodontal disease[29]. IFI16 is a key DNA-sensor protein localized in the nucleus that activates type I interferons and pro-inflammatory cytokines upon foreign DNA recognition. A most recent study revealed that IFI16 regulates hepatic inflammation via STING-TBK-IRF3 signaling cascade. Dysregulation and over-expression of the IFI16 gene promote the upregulation of STING-TBK1-IRF3 signaling cascade, contributing to HBV-induced hepatic inflammation[13]. Presence of variant rs1057028 (A>T) induces three-dimensional conformational changes to the IFI16 protein structure, which alter its function[29]. IFI16’s role has also been described in periodontal disease and metabolic liver disease[28]. However, its contribution to hepatic fibrosis in CHC patients remains unclear. The mechanism by which IFI16 particularly the rs1057028 variant, influences hepatic inflammation and fibrosis is not completely understood; however, its mechanism has been partially elucidated in the context of increased susceptibility of severe periodontal disease.
Inheritance of polymorphism in TGF-β1 and angiotensinogen has been identified with liver fibrosis progression in HCV patients[30]. According to a genetic analysis study, the polymorphism of the IFNL3-IFNL4 rs12979860 genetic variations may also serve as a significant predictor of cirrhosis and liver fibrosis in patients with CHC from Pakistan[6]. In Pakistani HCV patients, the TGF-β1 rs1800469 gene polymorphism was also linked to the pathogenesis of cirrhosis and hepatocellular carcinoma[31]. There are a number of studies that highlight the role of multiple genetic polymorphisms in the progression of hepatic fibrosis. However, the IFI16 and AIM genetic polymorphism is still not properly clear.
Combined genotype analysis reveals the different combinations of both SNPs with their risk. Interestingly, combined genotype analysis revealed that individuals harboring both the A allele of IFI16 rs1057028 and the T allele of AIM2 rs2814770 had a significantly higher risk of liver fibrosis, suggesting a possible interaction between these genes in regulating inflammatory pathways. IFI16 and AIM2 are key cytosolic DNA sensor in innate immune signaling and inflammasome activation. IFI16 activates the STING-TBK-IRF pathway, leading to the production of type I interferons and pro-inflammatory cytokines as well as apoptosis of infected hepatocytes. AIM2 forms inflammasomes, leading to caspase-1 activation and IL-1β release, particularly in hepatic immune cells. The co-existence of risk alleles in both genes may result in excessive or prolonged inflammasome signaling and increasing the hepatic inflammation. Their combined dysregulation may amplify hepatic inflammation, promote hepatic stellate cell activation, and accelerate extracellular matrix deposition, thereby contributing to fibrosis progression. Chen et al[9] reported upregulation of both IFI16 and AIM2 in acute and chronic hepatitis B infection, highlighting their involvement in virus-induced hepatic inflammation. GWAS revealed that the missense IFI16 rs1057028 (A>T) SNP is significantly associated with periodontal disease and showed significant association with increased PD, BOP, elevated gingival crevicular fluid IL-1β levels, greater periodontal pathogen loads, and higher frequency of severe periodontal disease[26,27]. A recent study emphasized fundamental role of IFI16 in MASLD, where, IFI16 genetic variants notably rs6490 (A<T) variant increases dsDNA binding through stabilization of HINb domain, potentially amplifying inflammation[28]. Fan et al[10] demonstrated the role of IFI16 and AIM2 in regulating inflammasome-driven inflammatory responses in immune-mediated diseases. AIM2 inflammasome activation has been linked to liver inflammation in viral hepatitis models. Several studies reported the dysregulation of both IFI16 and AIM2 in different inflammatory disease. However, IFI16 rs1057028 and AIM2 rs2814770 combined interaction in liver fibrosis has not been studied yet.
We used the GTEx database to determine the effect of IFI16 rs1057028 and AIM2 rs2814770 variants on their specific tissue-based gene expression; however, we did not find any direct evidence of the impact of these variants on hepatic tissue gene expression. Significant eQTL associations of these were found in skin, spleen, whole blood, tibial artery, and esophagus mucosa. Functional annotation through RegulomeDB revealed that both IFI16 rs1057028 and AIM2 rs2841770 variants possess RegulomeDB scores of 1f, suggesting eQTL evidence but no direct transcription factor binding or chromatin accessibility support. The variant rs2841770 exhibited a lower rank of 0.195 compared to rs1057028 of 0.55, indicating a higher predicted probability of regulatory influence. Both loci are positioned within the IFI16/AIM2 regulatory region on chromosome 1q23, which harbors multiple immune-related enhancers active in liver and immune tissues.
Several studies have associated IFI16-region variants (including rs1057028 and nearby haplotypes) with altered inflammatory phenotypes, for example, in periodontal disease and immune-related traits, suggesting that genotype-dependent expression differences are biologically meaningful[29]. Functionally, IFI16 encodes a DNA sensor that activates downstream innate immune pathways (including STING-IRF3) and inflammasome-related responses; dysregulation and overexpression of the IFI16 gene promote the upregulation of STING-TBK1-IRF3 signaling cascade contributing to HBV-induced hepatic inflammation[13,32]. The combination of RegulomeDB annotation (score 1f) plus cross-tissue eQTL evidence strengthens the hypothesis that these SNPs modulate IFI16 (or AIM2) expression in relevant tissues and possibly in disease-context liver, even if direct healthy-liver eQTL data are currently lacking.
This study has certain limitations. The difference in sample sizes between the two SNPs likely reflects variations in DNA quality, genotyping success rates, or sample availability during analysis, leading to incomplete data for one of the loci. The different sample size and analysis of only one SNP per gene may limit the detection of statistically robust associations. We interrogated one SNP per gene; non-genotyped variation, haplotypes, or regulatory variants could carry stronger effects. Additionally, functional validation of these variants and their interaction was not performed. This study focused solely on the HCV infection from the Pakistani population, which while valuable for understanding local genetic architecture, may reduce the generalizability of results across diverse populations. Future studies involving larger, multi-ethnic cohorts and more comprehensive SNP analysis are essential to validate these findings and investigate their potential relevance as prognostic biomarkers for hepatic fibrosis and cirrhosis.
This study provides novel evidence that the AIM2 rs2814770 polymorphism is significantly associated to increased susceptibility of hepatic fibrosis in chronic HCV patients. This association highlights the potential contribution of inflammasome activation in driving hepatic inflammation, immune dysregulation, and progressive tissue remodeling. Although the IFI16 rs1057028 (TT) genotype showed slightly higher odds of advanced fibrosis and cirrhosis, the lack of statistical significance suggests that its role may be more suitable or require larger sample sizes to confirm. In addition to genetic variants, age, BMI, and ALT levels were identified as important clinical predictors of liver fibrosis and cirrhosis, emphasizing the multi-factorial nature of disease progression. Together, these findings strengthen the concept that host genetic susceptibility, in combination with demographic and clinical risk factors, contributes to the heterogeneity of liver disease outcomes in HCV patients. However, further studies with a large sample set from different ethnicities and exploration of other functional SNPs in target genes are needed to elucidate the potential role and prognostic biomarker value of IFI16 and AIM2 genetic testing in mediating liver fibrosis and cirrhosis, making it possible to implement early preventive measures and target-based treatments in the future.
The authors gratefully acknowledge all individuals and institutions whose support, guidance, and resources contributed to the successful completion of this research.
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