Association Study of IFNL3 and IFNLR1 Gene Polymorphisms with Systemic Lupus Erythematosus in Iraqi Women

Systemic lupus erythematosus (SLE) is a chronic, multisystem autoimmune disorder characterized by dysregulated immune responses, autoantibody production, and systemic inflammation [1]. As a systemic immune disorder, SLE involves numerous organs when symptoms emerge [2]. Research indicates that disease development stems from the intricate interplay of genetic predisposition and environmental factors, which disrupts immune regulation and compromises immunological tolerance. SLE encompasses various autoimmune disorders with a range of clinical manifestations, including serositis, which involves the inflammation of serosal membranes that can lead to conditions like pericarditis, pleuritis, and peritonitis [3, 4]. Known for its relapsing nature, SLE symptoms can vary significantly in severity, from mild to life-threatening. The onset of SLE typically occurs during adolescence and early adulthood, predominantly affecting women aged 15 to 44 [5].

Interferons play a crucial role in SLE. These cytokines, produced in response to infections or inflammatory stimuli, are part of a broader family that possesses strong antiviral properties and is essential for regulating immune cell function. Type III consists of four subtypes and serves distinct immune functions. Notably, recent findings suggest that type III interferons, particularly interferon lambda, may also influence the pathogenesis of autoimmune and chronic inflammatory diseases, complicating the understanding of their roles. Crow [6] highlights SLE pathogenesis, emphasizing genetic, environmental, and immune factors, including interferon pathways, and B/T cell dysregulation, and identifies potential therapeutic targets for personalized treatment.

Interferons (IFNs) are essential cytokines that contribute significantly to effective antiviral defense. They are divided into three primary groups–types I, II, and III–according to their structural features, receptor engagement, and biological activities. While all IFNs are integral to antiviral defense, their specific roles differ significantly. Holicek et al. [7] reviewed type I interferon’s dual role in cancer, detailing its immune-stimulatory effects, tumor suppression, and context-dependent pro-tumor activities, informing therapeutic strategies. A landmark development in IFN research occurred in early 2003 with the discovery and initial characterization of the interferon lambda (IFN-λ) family. This group consists of three genes that encode closely related proteins designated as IFN-λ1, IFN-λ2, and IFN-λ3, which align with interleukin-29 (IL-29), IL-28A, and IL-28B, respectively. Al-Mashhadani et al. [8] reported elevated IL-1β, IFN-γ, and MMP-9 in Iraqi women with breast cancer, suggesting these mediators contribute to tumor progression and inflammatory responses. Consequently, type III IFNs (IFN-λs) exhibit expression patterns and biological actions similar to those of type I IFNs [9]. IFN-λ receptors are predominantly found on epithelial cells. This specificity underscores the prospective clinical importance of IFN-λ as an innovative antiviral treatment. Preliminary studies also indicate that IFN-λ might be advantageous in treating various medical conditions, including certain cancers [10]. Genetically, IFN-λ genes are located together on both murine chromosome 7 (in the 7A3 region) and human chromosome 19 (specifically in the 19q13.13 region) [11, 12].

Interferons drive aberrant immune activation, promoting the generation of autoantibodies and immune complexes that ultimately cause tissue injury. Research has linked SLE with dysregulation of both type I and type III interferons. Several studies, including those by study [13], reported elevated serum levels of IFNλ1 and IFNλ3 in SLE patients compared to healthy individuals. Additionally, the expression of IFNL1 transcripts has been found to increase in peripheral blood mononuclear cells (PBMCs) of SLE patients, while IFNL3 transcripts are elevated in activated CD4⁺ T cells [14, 15]. Significantly, higher serum concentrations of IFNλ are correlated with more severe disease manifestations and specific laboratory findings, such as elevated anti-double-stranded DNA (dsDNA) autoantibody titers and greater SLE Disease Activity Index values [16, 17]. Elevated IFNλ levels are also associated with various disease symptoms, such as arthritis, nephritis, serositis, and skin issues [13].

Volkova et al. [18] reported that a mechanistic QSP model incorporating IFN-I induction, signaling, and gene-signature readouts was used to compare the pharmacodynamics of anifrolumab, sifalimumab, daxdilimab, and litifilimab. This model provided testable predictions regarding the extent of IFN-signature suppression achieved by each therapeutic mechanism. Post-hoc proteomic and biomarker analyses from clinical trials further demonstrated that anifrolumab (anti-IFNAR1) effectively suppresses IFN-driven inflammatory proteins and pathways linked to disease activity, offering direct human evidence that IFN-I signaling causally drives pathogenic networks [19]. Complementary mechanistic dermatology studies and reviews highlight plasmacytoid dendritic cell (pDC) accumulation and IFN-I/MxA footprints in lesional skin, reinforcing the presence of tissue-localized IFN loops that parallel systemic disease [20].

Genetic studies have further elucidated the connection between genetic variations and the risk of SLE. Certain variants of IFNL3 and IFNL4 are linked to lupus nephritis in Taiwanese patients, while the rs4649203 single-nucleotide polymorphism in IFNLR1 is associated with an increased susceptibility to SLE among individuals from the Chinese Han population [21]. In a case study, serum IFNλ1 levels notably decreased during clinical remission following glucocorticoid and hydroxychloroquine treatment [22, 23]. Additionally, IFNλs have been shown to stimulate keratinocytes to express MHC class I molecules, potentially facilitating pathogenic CD8+ T cell responses [24].

This research sought to explore the potential association between genetic polymorphisms of the IFNL3 (rs12979860) gene and multiple polymorphisms in the IFNLR1 gene (rs4649203, rs72650431, rs72872528, and rs59960858) with systemic lupus erythematosus (SLE) incidence among Iraqi women.

In the present study, the five SNPs were selected due to their roles in interferon signaling and autoimmune disease risk. IFNL3 rs12979860 is a functional haplotype marker influencing interferon-stimulated gene expression and linked to SLE susceptibility [25]. IFNLR1 rs4649203 shows genome-wide association with SLE in the Chinese Han population, while rs59960858 is a lead eQTL regulating IFNLR1 expression and colocalizing with psoriasis risk [26]. To ensure broader haplotype representation, rs72650431 and rs72872528 were chosen as tag variants within IFNLR1, following linkage disequilibrium–based selection strategies.

3.1 PCR-based detection of the IFNL3 gene

Agarose gel electrophoresis (Figure 1) and nanodrop analysis were used to detect the integrity and purity, respectively, of the genomic DNA isolated from the participants. The absorbance ratios of the DNA ranged from 1.8 to 2.0, indicating high purity. In the current study, a PCR reaction was conducted for the patient and control group samples to amplify the IFNL3 gene, and agarose gel electrophoresis was utilized to confirm this amplification for this region. Ethidium bromide staining of PCR amplified products revealed that all samples had a band and a fragment size of 306 bp. Figure 2 illustrates the agarose gel electrophoresis of the IFNL3 gene.

Figure 1. Gel electrophoresis of genomic DNA extracted from blood samples

Lanes 1-16 represent genomic DNA in 1% agarose gel at 70 volts for 60 min.

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Figure 2. Amplification of the rs12979860-specific DNA region to detect the IFNL3 gene

DNA samples were separated on a 1.5% agarose gel pre-stained with ethidium bromide, and the gel picture revealed 306 bp PCR products; M: 100bp ladder marker; Lanes 1-5 resemble 306bp PCR products.

3.2 Association between rs12979860 polymorphism and SLE

Table 2 and Figure 3 present the genotype distribution and allele frequency of the SNP rs12979860. The distribution and allele frequency of the three genotypes, CC, CT, and TT, between SLE patients and control subjects did not differ significantly. The CT genotype functions as a risk factor (more susceptible to disease) because its odds ratio is greater than 1. However, the odds ratio was 0.87, and the CC genotype was significantly different; as a result, the CC genotype serves as a protective factor. In contrast, given that the odds ratio was 1, the TT genotype indicates that there is most likely no difference between the two groups. The odds ratio for the T allele was 1.08, while the odds ratio for the C allele was 0.91, indicating that the T allele could be associated with the susceptibility to the disease, while the C allele may act as a protective allele.

Table 2. Genotypic and allelic distribution of IFNL3 rs12979860 in study groups with Hardy-Weinberg equilibrium assessment

Table 3. Comparative summary of key findings

These findings are supported by several related studies. For instance, it was reported that there was no association between rs12979860 and SLE susceptibility in Mexican individuals, but an increased OASL expression among CC carriers, which is consistent with the present study’s null overall association [27]. The Mexican study included a larger cohort of 439 patients compared with the 60 patients in the present study. Additionally, Beretta et al. [28] associated the CC genotype with pulmonary fibrosis in systemic sclerosis, which may explain the deviation from the Hardy-Weinberg equilibrium in the current patient group if fibrotic complications were present.

Several studies have demonstrated that the CC genotype favors viral clearance, which contrasts with its potential protective role in SLE, highlighting the pleiotropic effects of this variant [29, 30]. Furthermore, Hamdi et al. [31] suggested that CC enhances the expression of proinflammatory cytokines, potentially linking to the elevated OASL expression. The deviation from the Hardy-Weinberg equilibrium in patients may be attributed to factors such as selection bias (e.g., inclusion of patients with severe phenotypes), population stratification, or genetic drift. The control group being in HWE suggests no genotyping errors. The elevated CC frequency observed in both Iraqi groups (56-60%) contrasts with global patterns. While lower frequencies were reported in Mexican populations, Taiwanese studies identified associations with nephritis, underscoring the population-specific effects of this variant, as presented in Table 3 [27].

3.3 Polymerase chain reaction-detection of IFNLR1 gene

In this study, PCR was carried out on samples from both patient and control groups to amplify the IFNLR1 gene. The amplification was verified through agarose gel electrophoresis, as illustrated in Figure 4. The electrophoresis, performed with ethidium bromide staining, revealed a fragment size of 1007 bp, confirming successful amplification in all samples.

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3.4 Association between rs4649203 polymorphism and SLE

As presented in Figure 5 and Table 4, the genotype distribution and allele frequency of SNP rs4649203 showed no significant differences among the three genotypes (GG, GA, and AA) between SLE patients and controls. The odds ratios for the GA and AA genotypes were 0.76 and 0.87, respectively, suggesting a potential protective effect of both genotypes. Notably, the GG genotype was absent in the control group. The odds ratio for the G allele was 1.41, whereas that for the A allele was 0.71, suggesting that the G allele may confer susceptibility to the disease, while the A allele may serve as a protective factor. Additionally, the outcomes in Table 4 show that the control group concurs with the HWE. There were no appreciable variations between the expected and observed genotypic frequencies. The HWE is compatible with both groups. Given that the total observed for both groups was 46, GA recorded a total of 38, and GG recorded a total of 6, indicating that the AA genotype may be regarded as a common genotype in the Iraqi female population.

Table 4. Genotypic and allelic distribution of IFNLR1 rs4649203 in study groups with Hardy-Weinberg equilibrium assessment

As presented in Figure 6 and Table 5, the genotype distribution and allele frequency of SNP 72650431 showed no significant differences among the three genotypes (AA, AG, and GG) between SLE patients and controls. The odds ratio for the AG genotype was 0.72, indicating a possible protective effect, whereas the AA genotype showed no difference between the two groups, with an odds ratio of 1. Notably, the GG genotype was absent in the control group. The odds ratio for the G allele was 1.27, whereas that for the A allele was 0.78, suggesting that the G allele may be associated with increased disease susceptibility, while the A allele may function as a protective factor. The outcomes of the control groups agree with the HWE, as shown in Table 5. There were no appreciable variations between the expected and observed genotype frequencies. However, the HWE at p ≤ 0.007 was incompatible with the patient group. Other factors, such as selection for certain genotypes (i.e., the association signal itself) by the disease under study (SLE). Deviations from HWE in the control group, on the other hand, typically indicate population confounding or genotyping errors. Given that the total observed for both groups was 78, whereas AG recorded a total of 10 and GG recorded a total of 2, the results indicated that the AA genotype may be regarded as a common genotype in the Iraqi female population.

Table 5. Genotypic and allelic distribution of IFNLR1 72650431 in study groups with Hardy-Weinberg equilibrium assessment

3.6 Association between rs72872528 polymorphism and SLE

The genotypic distribution and allelic frequency for the SNP 72872528 are shown in Table 6 and Figure 7. The distribution of the three genotypes (GG, GT, and TT) and the frequency of each allele did not differ significantly between SLE patients and controls. The GG genotype had an odds ratio of 0.46. The GG genotype thus serves as a protective factor. But because the GT genotype has an odds ratio greater than 1 (1.55), it is a risk factor (more prone to disease). Conversely, the odds ratio for the TT genotype that was absent from the control group was (0). However, the odds ratio for the G allele was 0.37, and the odds ratio for the T allele was 2.63, suggesting that the T allele may be more likely to be linked to the illness. G, however, might serve as a protective allele. The Hardy-Weinberg equilibrium is supported by the results in Table 6 for the control groups. There were no appreciable variations between the expected and observed genotypic frequencies. The HWE was incompatible with the patient group. Other factors, such as selection for certain genotypes (i.e., the association signal itself) by the disease under study (SLE), could be the cause of this. Given that the total observed for both groups was 80, while GT recorded a total of 8 and TT recorded 2, the overall observed results imply that the GG genotype may be regarded as a common genotype in the Iraqi female population.

Table 6. Genotypic and allelic distribution of IFNLR1 72872528 in study groups with Hardy-Weinberg equilibrium assessment

3.7 Association between rs59960858 polymorphism and SLE

The genotypic distribution and allelic frequency for SNP 59960858 are displayed in Figure 8 and Table 7. The distribution and allelic frequency of the three genotypes (CC, CA, and AA) between SLE patients and controls did not differ significantly. In the CC genotype, the odds ratio was 0.84. As a result, the CC genotype provides protection. On the other hand, the CA genotype acts as a risk factor (more susceptible to disease) because its odds ratio is greater than 1. Meanwhile, the control and patient groups' odds ratio was zero for the AA genotype. The A allele, on the other hand, may be more likely to be linked to the disease, as evidenced by the odds ratio of 1.14 for the A allele and 0.87 for the C allele. C, however, might serve as a protective allele. Additionally, Table 7 shows that the control group is consistent with the HWE. There were no significant variations between the expected and observed genotypic frequencies. The HWE is compatible with both groups. Because the total observed for both groups was 64, whereas CA recorded a total of 26 and GG recorded zero, the total observed results imply that the CC genotype may be regarded as a common genotype in the Iraqi female population.

Table 7. Genotypic and allelic distribution of IFNLR1 59960858 in study groups with Hardy–Weinberg equilibrium assessment

Table 8. Summary of key SNP associations

The results of this study focused on four SNPs (rs4649203, rs72650431, rs72872528, and rs59960858), analyzing their genotype and allele frequencies, odds ratios (ORs), confidence intervals (CIs), p-values, and HWE status (Table 8). For rs4649203, the GA and AA genotypes appeared potentially protective, whereas the G allele may represent a risk factor. In rs72650431, the AA genotype was predominant across both study groups, although a deviation from HWE was observed in the patient cohort. With respect to rs72872528, the GT genotype emerged as a possible risk factor, and the T allele may contribute to pathogenicity. Similarly, for rs59960858, the CA genotype was associated with increased risk, and the A allele was identified as a potential susceptibility factor. When placed in a broader biological context, evidence from recent studies underscores the role of IFNLR1 in antiviral immunity, particularly via activation of the JAK-STAT signaling pathway in epithelial and immune cells [32]. Given that dysregulated immune signaling and aberrant interferon responses are central to the pathogenesis of SLE, these findings suggest that genetic variation in IFNLR1 may have functional implications in disease susceptibility and progression. NCBI records confirm that IFNLR1 is a protein-coding gene expressed in immune-relevant tissues, supporting its potential role in autoimmune processes. Several studies have linked IFNLR1 variants to other immune-related conditions, including the association of rs4649203 with HCV treatment response [33], mutations in IFNLR1 with hearing loss [34], and reported links to pancreatic cancer. These associations reinforce the biological plausibility of the present findings. The findings are comparable with previous studies. In Iranian SLE cohorts, IL-1RN rs315952 shows a protective CT genotype and increased T-allele frequency in patients with hematologic manifestations, though not necessarily deviating from HWE [35]. Jordanian SLE patients exhibit strong associations with HLA-DRB1*0301, *1101, 1102, and DQB10601 alleles and risk haplotypes, which may reflect population stratification rather than technical error [36].

The functional effects of IFNL3/IFNL4 SNPs are well documented. rs12979860, linked to rs368234815, influences IFNL4 expression, affecting interferon-stimulated gene regulation and pro-inflammatory cytokine production, with the C allele enhancing viral clearance and immune activation [37, 38]. Additionally, rs59960858 modulates IFNLR1 expression, influencing autoimmune susceptibility [39].

The observed deviations from the Hardy-Weinberg equilibrium for rs72650431 and rs72872528 in patients may reflect population genetics factors such as consanguinity, which is particularly relevant within the Iraqi cohort. Deviations from the Hardy-Weinberg equilibrium (HWE) in patient groups suggest underlying biological or population processes. Such deviations may indicate selective pressures, genetic drift, inbreeding, or population stratification influencing allele distributions. In SLE, they may reflect disease-associated selection of certain genotypes, highlighting possible genetic susceptibility or resistance factors requiring further mechanistic and population-level investigations. The absence of significant associations may reflect the small sample size, population-specific genetic background, and deviations from the Hardy-Weinberg equilibrium. Additionally, disease heterogeneity, treatment effects, and stronger environmental or epigenetic influences could obscure genetic contributions, underscoring the need for larger, multi-ethnic studies to clarify IFNL3/IFNLR1 roles in SLE susceptibility.