Unveiling the role of TLR9 promoter variants in susceptibility and clinical features of systemic lupus erythematosus

Abstract

Objective

Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease in which dysregulated nucleic acid sensing and type I interferon responses drive autoantibody production and organ damage. Toll-like receptor 9 (TLR9) regulates these pathways, and promoter variants (rs187084 and rs5743836) may alter TLR9 expression and modulate disease susceptibility and severity. This study evaluated the association of these promoter SNPs and their haplotypes with SLE risk and clinical/laboratory features in an Iranian population.

Methods

In this case–control study, we genotyped TLR9 promoter SNPs rs187084 and rs5743836 in 140 SLE patients and 140 age- and sex-matched healthy controls using the real-time PCR-high resolution melting (PCR-HRM) assay.

Results

Our analysis showed that the CC and CT genotypes and the C allele of the rs5743836 SNP were associated with an increased risk of SLE (P < 0.05). However, there was no association between the rs187084 SNP and the risk of SLE (P > 0.05). The combined rs187084–rs5743836 CC haplotype was associated with increased SLE risk (CC vs TT haplotype, P < 0.001). Furthermore, in the patient group, carriers of the C allele in both promoter variants exhibited earlier disease onset and more active and severe disease, as evidenced by higher levels of C-reactive protein (CRP) and anti-dsDNA, reduced complement C3 and C4, and a higher frequency of renal and neurological complications (P < 0.05).

Conclusion

Our data suggest that promoter variation in TLR9, specifically the rs5743836 C allele and the combined rs187084-rs5743836 CC haplotype, is linked to an increased risk of SLE and more disease activity and severe clinical presentation.

Keywords

TLR9 systemic lupus erythematosus genetic susceptibility clinical manifestation

Introduction

Systemic lupus erythematosus (SLE) is a chronic, relapsing autoimmune disorder characterized by a wide spectrum of clinical manifestations and variable outcomes, ranging from cutaneous and joint issues to life-threatening renal, neurologic, and hematologic involvement.^1,2 The disease is fundamentally multifactorial: environmental exposures, hormonal effects, immune dysregulation, and complex genetic predisposition, which together shape individual risk, the patterns of organ involvement, the course of disease activity, and the extent of accumulated damage.^3,4

Genetic factors significantly influence the susceptibility and characteristics of SLE. Family and twin studies have consistently shown a heritable component, with estimates of heritability ranging from 43% to 66% in different populations. The concordance rate for SLE in monozygotic twins is notably higher, ranging from 25% to 57%, compared to only 2% in dizygotic twins.⁵ Genome-wide association studies (GWAS) have identified multiple susceptibility loci that implicate pathways related to innate and adaptive immunity, complement function, clearance of apoptotic debris, and lymphocyte signaling.^6,7 While GWAS and other genetic studies have identified numerous loci linked to SLE, these genetic variants explain only a fraction of the heritability. These findings highlight the importance of regulatory variation and gene-environment interactions. Variants that influence gene expression or transcriptional regulation are likely to impact immune pathways crucial for the onset and development of the disease.^8,9

Toll-like receptor 9 (TLR9) is a crucial innate immune sensor that detects unmethylated CpG motifs in microbial and endogenous DNA. It plays a significant role in linking nucleic acid detection to the MyD88-dependent type I interferon and proinflammatory cytokine production and activation of B cells.^10,11 TLR9 signaling in plasmacytoid dendritic cells (pDCs) and B cells is involved in promoting interferon responses and the generation of autoantibodies, which are key processes in the development of SLE.^12,13 In SLE and other autoantibody-mediated diseases, the defective clearance of apoptotic debris and the formation of nucleic acid-protein complexes facilitate the delivery of self-DNA to endosomes, which creates feed-forward loops of interferon production, B cell activation, and pathogenic immune complex formation. These loops drive tissue inflammation and organ damage.^14,15

Multiple studies have shown an increase in TLR9 expression in cell types from patients with various autoimmune diseases, including rheumatoid arthritis,¹⁶ Sjögren’s syndrome,¹⁷ autoimmune thyroid diseases,¹⁸ multiple sclerosis,¹⁹ systemic sclerosis,²⁰ and particularly in SLE.^21,22 Numerous studies report higher TLR9 expression in peripheral blood mononuclear cells and CD20+ B cells from SLE patients versus healthy controls, with levels rising further in those with lupus nephritis and correlating positively with SLEDAI and Renal-SLEDAI scores and histologic activity index.^21,23–26 Accumulating functional and in silico evidence suggests that promoter variants in TLR9, specifically rs187084 (−1486T/C) and rs5743836 (−1237T/C), can impact transcription factor binding, promoter activity, and cytokine responses. These effects may play a role in autoimmune processes. These variants are located near NF-κB/ERα regulatory motifs. They create potential c-Rel/NF-κB, Sp-1, and IL-6 responsive sites, making them strong candidates for influencing susceptibility to SLE and its clinical manifestations.^27–30

Given these findings, we investigated the association of rs187084 and rs5743836 with SLE susceptibility and key clinical and laboratory features of the disease in the Iranian population. By integrating genetic association analyses with clinical phenotype correlations, we aim to determine if functional promoter variation in TLR9 contributes to SLE risk or disease heterogeneity, with the potential to identify genetic markers indicative of TLR9-driven immune dysregulation.

Materials and methods

Samples

A total of 280 individuals were enrolled in this case–control study, comprising 140 patients with SLE and 140 healthy controls. Cases and controls were matched by age and sex and were drawn from the same population; all participants shared common ancestry and were unrelated. SLE patients were recruited from both inpatient and outpatient rheumatology clinics at Alzahra Hospital in Isfahan and met the 2019 EULAR/ACR classification criteria for SLE. Control subjects were healthy blood donors with no personal or family history of autoimmune or autoinflammatory and immunological diseases. Demographic and clinical information was obtained using a written questionnaire that recorded age, sex, age at disease onset, body mass index, family history of SLE and related disorders, and clinical manifestations. Routine laboratory assessments included serum complement components C3 and C4, anti-double-stranded DNA (anti-dsDNA) antibodies, erythrocyte sedimentation rate (ESR), white blood cell count, and C-reactive protein (CRP). Peripheral blood (5 mL) was collected into EDTA tubes from each participant after obtaining written informed consent and stored at −20°C until analysis. The study protocol and all procedures were approved by the local ethics committee of Isfahan University of Medical Sciences (IR.MUI.MED.REC.1404.168).

SNP genotyping

Genomic DNA was isolated from peripheral blood cells using the AddPrep Genomic DNA Extraction Kit (AddBio Inc., Korea) according to the supplied protocol. DNA yield and purity were assessed by UV–visible spectrophotometry, and integrity was checked by agarose gel electrophoresis. The genotyping of the SNPs was carried out utilizing the polymerase chain reaction high-resolution melting (PCR-HRM) method. The specific forward and reverse primers used to amplify fragments surrounding the variant sequences are: rs5743836 forward: CCTGCTTGCAGTTGACTGTG; rs5743836 reverse: CCCTGTTGAGAGGGTGACAT, and rs187084 forward: AGCTGACTGCTGGGTGTACATA; rs187084 reverse: TTTAACTGCTAGCACACCGGAT. The HRM assay was conducted using HOT FIREPol EvaGreen HRM Mix (without ROX) on a Rotor-Gene 6000 (Corbett Research). The protocol included an initial denaturation at 95°C for 10 min, followed by 40 cycles of 95°C for 20 s, annealing at 57°C for rs5743836 and 59°C for rs187084 for 25 s, and extension at 72°C for 20 s. Subsequently, melt data were collected from 60°C to 95°C with a ramp rate of 0.1°C/s and continuous fluorescence monitoring to generate high-resolution melting curves. Polymorphisms were identified by comparing the melting curve shapes of samples and normalized difference plots to reference genotypes previously confirmed by Sanger sequencing. Each run included three DNA samples with known genotypes as controls. To validate HRM results, 10% of the study samples were randomly chosen for confirmatory sequencing, and concordant results were used to confirm the assay performance.

Statistical analyses

All statistical analyses were conducted using IBM SPSS Statistics version 25 (Armonk, NY: IBM Corp). Continuous variables are reported as mean ± standard deviation, while categorical variables are presented as percentages. Genotype distributions in cases and controls were evaluated for deviation from Hardy–Weinberg equilibrium (HWE) using the chi-square (χ2) test. Differences in demographic and laboratory continuous variables between groups were assessed using the independent Student’s t-test. Comparisons of categorical variables, such as genotype and allele frequencies, were conducted using the Pearson chi-square test. Logistic regression was employed to assess the relationship between genotypes and case-control status, and to calculate odds ratios (ORs) with 95% confidence intervals (CIs) and corresponding P-values. Statistical significance was set at a two-sided P-value <0.05.

Results

Demographic, clinical, and laboratory profile

In this case-control study, 140 patients with SLE (43 males, 97 females) and 140 age- and sex-matched control subjects (33 males, 107 females) were included. The mean age at disease onset among patients was 24.61 ± 9.43 years. Compared with controls, SLE patients had significantly higher body mass index (P < 0.001), systolic blood pressure (P < 0.001), and diastolic blood pressure (P = 0.002). Several disease-related features were observed exclusively in the patient group: positive family history (22.1%), neurological symptoms (25.7%), skin manifestations (62.9%), hematological manifestations (47.9%), oral ulcers (71.4%), arthritis (69.3%), and renal involvement (41.4%). Baseline characteristics are summarized in Table 1.

Table 1.

Baseline characteristics of SLE patients and control subjects who participated in the study.

Characteristics	Patients	Controls	P
Total number	140	140
Age at now (mean ± SD)	39.59 ± 11.04	41.49 ± 10.80	0.130
Gender n (%)
Male	43 (30.71%)	33 (23.57%)	0.226
Female	97 (69.29%)	107 (76.43%)
Age of onset (mean ± SD)	24.61 ± 9.43	—	—
BMI (mean ± SD)	26.31 ± 2.15	24.16 ± 3.46	<0.001*
SBP (mean ± SD)	127.26 ± 16.01	120.36 ± 9.61	<0.001*
DBP (mean ± SD)	82.21 ± 6.71	79.29 ± 8.56	0.002*
Positive family history n (%)	31 (22.14%)	0	—
Neurological symptoms n (%)	36 (25.71%)	0	—
Skin manifestations n (%)	88 (62.86%)	0	—
Hematological manifestations n (%)	67 (47.86%)	0	—
Oral ulcers n (%)	100 (71.43%)	0	—
Arthritis n (%)	97 (69.29%)	0	—
Renal involvement n (%)	58 (41.43%)	0	—

*P value <0.05. SLE = Systemic lupus erythematosus; SD = Standard deviation; BMI = Body mass index; SBP = Systolic blood pressure; DBP = Diastolic blood pressure.

SLE patients also showed significantly elevated inflammatory and disease-specific markers, including ESR, CRP, and anti-dsDNA (P < 0.001 for all), while complement levels were markedly lower: C3 and C4 (P < 0.001 for both). Renal-related measures such as creatinine (P < 0.001) and blood urea nitrogen (BUN) (P = 0.007) were elevated in patients. Hematologic differences included lower hemoglobin (P < 0.001) and a slightly lower platelet count (P = 0.013). White blood cell count, fasting blood sugar (FBS), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglycerides did not differ significantly between groups (P > 0.05 for all). Details of laboratory data are presented in Table 2.

Table 2.

Laboratory characteristics of patients with SLE and the control group.

Characteristics	Patients (140)	Controls (140)	P
ESR (mm/h)	40.44 ± 17.14	15.65 ± 6.88	<0.001*
CRP (mg/l)	18.63 ± 9.97	3.81 ± 2.09	<0.001*
White blood cell (10⁹/1)	6.55 ± 1.58	6.48 ± 1.45	0.696
Hemoglobin	11.61 ± 1.52	14.14 ± 1.45	<0.001*
PLT (10⁹/1)	225.41 ± 57.92	244.24 ± 67.31	0.013*
Creatinine (mg/dL)	1.46 ± 0.77	0.87 ± 0.20	<0.001*
BUN	18.26 ± 8.15	16.09 ± 4.65	0.007
FBS	88.54 ± 14.06	91.63 ± 21.23	0.153
HDL	49.42 ± 7.19	49.87 ± 11.66	0.698
LDL	109.80 ± 29.88	107.09 ± 36.39	0.497
TG	160.70 ± 46.46	153.89 ± 62.87	0.304
Anti-dsDNA (IU/ml)	212.15 ± 171.91	10.79 ± 4.67	<0.001*
C3 level (mg/dl)	47.87 ± 34.61	143.65 ± 36.29	<0.001*
C4 level (mg/dl)	9.84 ± 6.70	20.80 ± 5.87	<0.001*

*P value <0.05. SLE = Systemic lupus erythematosus; SD = Standard deviation; ESR = Erythrocyte sedimentation rate; CRP = C-reactive protein; BUN = Blood urea nitrogen; PLT = Platelet; HDL = High-density lipoprotein; LDL = Low-density lipoprotein; TG = Triglyceride; FBS = Fasting blood sugar; dsDNA = Double-stranded DNA; C3 = Complement component 3; C4 = Complement component 4.

rs5743836 (−1237T/C): Frequencies and correlations

Table 3 demonstrates a significant difference in TC (34.29% vs 21.43%, OR = 2.09; 95% CI [1.182–3.752]; P = 0.007) and CC (8.57% vs 3.57%, OR = 3.13; 95% CI [0.978–11.82]; P = 0.040) genotypes between the SLE and healthy subject groups. Under a dominant model (TC + CC vs TT), carriers of the C allele had a significantly increased risk (OR 2.24; 95% CI [1.31–3.87]; P = 0.002). The C allele frequency was higher in patients than controls (25.7% vs 14.3%), corresponding to an allele-based OR of 2.07 (95% CI [1.33–3.28]; P < 0.001). The recessive model (CC vs TT + TC) did not reach statistical significance (P = 0.131). The genotype distribution of the rs5743836 polymorphism in the case and control groups conformed to Hardy–Weinberg equilibrium (HWE). Patients carrying the C allele (TC + CC) had an earlier age of onset compared to patients with the TT genotype (21.60 ± 7.68 vs 26.88 ± 10.02 years; P < 0.001). Inflammatory and serologic markers showed higher CRP levels (P = 0.021) and markedly higher anti-dsDNA levels (P < 0.001) in TC + CC carriers. Complement levels were notably lower in TC + CC patients for both C3 (P < 0.001) and C4 (P = 0.009). Neurological manifestations were more prevalent in TC + CC patients (36.7% vs 17.5%; P = 0.012), and renal disease was also more common (53.3% vs 32.5%; P = 0.016). Other clinical manifestations and laboratory findings did not show significant differences between genotype groups (P > 0.05) (Table 4).

Table 3.

Association of TLR9 promoter polymorphisms with SLE risk.

Genotype group	Patients (n = 140)n (%)	Controls (n = 140)n (%)	OR (95% CI)	P value
rs5743836
TT	80 (57.14%)	105 (75.00%)	Reference	—
TC	48 (34.29%)	30 (21.43%)	2.09 (1.182–3.752)	0.007*
CC	12 (8.57%)	5 (3.57%)	3.13 (0.978–11.82)	0.040*
Dominant inheritance
TT	80 (57.14%)	105 (75.00%)	Reference	—
TC + CC	60 (42.86%)	35 (25.00%)	2.24 (1.314–3.872)	0.002*
Recessive inheritance
CC	12 (8.57%)	5 (3.57%)	Reference	—
TT + TC	128 (91.43%)	135 (96.43 %)	0.39 (0.106–1.250)	0.131
Allele
T	208 (74.29%)	240 (85.71%)	Reference	—
C	72 (25.71%)	40 (14.29%)	2.07 (1.326–3.278)	<0.001*
rs187084
TT	44 (31.43%)	55 (39.29%)	Reference	—
TC	75 (53.57%)	68 (48.57%)	1.38 (0.798–2.384)	0.240
CC	21 (15.00%)	17 (12.14%)	1.53 (0.680–3.523)	0.339
Dominant inheritance
TT	44 (31.43%)	55 (39.29%)	Reference	—
TC + CC	96 (68.57%)	85 (60.71%)	1.41 (0.838–2.381)	0.211
Recessive inheritance
CC	21 (15.00%)	17 (12.14%)	Reference	—
TC + TT	119 (85.00%)	123 (87.86%)	0.78 (0.369–1.646)	0.601
Allele
T	163 (58.21%)	178 (63.57%)	Reference	—
C	117 (41.79%)	102 (36.43%)	1.25 (0.879–1.786)	0.225
rs187084_5743836
Haplotype
TT	144 (51.43%)	156 (55.71%)	Reference
TC	19 (6.79%)	22 (7.86%)	0.94 (0.458–1.896)	0.869
CT	64 (22.86%)	84 (30.00%)	0.83 (0.544–1.250)	0.366
CC	53 (18.92%)	18 (6.43%)	3.18 (1.737–6.054)	<0.001*

*P value <0.05.

Table 4.

Association of TLR9 (rs5743836) polymorphism with various parameters of SLE.

Parameter mean ± SD or n (%)	TT (n = 80)	TC + CC (n = 60)	P value
Age of onset	26.88 ± 10.02	21.60 ± 7.68	<0.001*
ESR (mm/h)	38.21 ± 16.78	43.42 ± 17.29	0.075
CRP (mg/l)	16.95 ± 8.77	20.87 ± 11.06	0.021*
C3 level (mg/dl)	58.93 ± 36.18	33.12 ± 26.09	<0.001*
C4 level (mg/dl)	11.11 ± 6.37	8.14 ± 6.81	0.009*
Anti-dsDNA (IU/mL)	132.65 ± 150.03	318.15 ± 139.62	<0.001*
Creatinine (mg/dL)	1.38 ± 0.76	1.55 ± 0.77	0.222
Hemoglobin	11.51 ± 1.44	11.71 ± 1.58	0.054
Neurological symptoms n (%)	14 (17.50%)	22 (36.67%)	0.012*
Skin manifestations n (%)	48 (60.00%)	40 (66.66%)	0.214
Hematological manifestations n (%)	37 (46.25%)	30 (50.00%)	0.367
Oral ulcers n (%)	56 (70.00%)	44 (73.33%)	0.709
Arthritis n (%)	53 (66.25%)	44 (73.33%)	0.460
Renal involvement n (%)	26 (32.50%)	32 (53.33%)	0.016*

*P value <0.05. SLE = Systemic lupus erythematosus; SD = Standard deviation; ESR: Erythrocyte sedimentation rate; CRP:C-reactive protein; C3 = Complement component 3; C4 = Complement component 4; dsDNA = Double-stranded DNA.

rs187084 (‐1486T/C): Frequencies and correlations

The genotype frequencies in the case and control groups conformed to the Hardy-Weinberg equilibrium (HWE). The rs187084 genotype and allele distributions did not differ significantly between patients and controls. Genotype frequencies for TT, TC, and CC genotypes in SLE patients were 31.43%, 53.57%, and 15.00%, respectively, compared to 39.29%, 48.57%, and 12.14% in the control group. Our analysis of different inheritance models for the rs187084 polymorphism showed no increased or decreased risk for SLE under both dominant and recessive models (P > 0.05). The allele frequencies for T and C in SLE patients were 58.21% and 41.79%, respectively, while in non-SLE subjects, they were 63.57% and 36.43%. Overall, no statistically significant association with SLE was found for rs187084.

Stratification analysis revealed that among SLE patients, those carrying the C allele (TC + CC) had an earlier age of onset (23.21 ± 8.34 vs 27.68 ± 10.94 years; P = 0.019). Serum levels of CRP (P = 0.015) and anti-dsDNA (P = 0.001) were significantly higher in carriers of the C allele compared to patients with the TT genotype. Complement levels were significantly lower in TC + CC patients for both C3 (P = 0.001) and C4 (P = 0.005). Creatinine was higher in carriers of the C allele (P = 0.029), and renal involvement was significantly more common (47.9% vs 27.3%; P = 0.027) among TC + CC carriers. Neurological manifestations were substantially more frequent in these patients (35.4% vs 4.6%; P < 0.001). Other clinical manifestations and laboratory findings showed no significant differences between genotype groups (P > 0.05) (Table 5).

Table 5.

Association of TLR9 (rs187084) polymorphism with various parameters of SLE.

Parameter mean ± SD or n (%)	TT (n = 44)	TC + CC (n = 96)	P value
Age of onset	27.68 ± 10.94	23.21 ± 8.34	0.019*
ESR (mm/h)	38.77 ± 16.88	41.21 ± 17.29	0.437
CRP (mg/l)	15.93 ± 7.69	19.86 ± 10.67	0.015*
C3 level (mg/dl)	61.69 ± 30.96	41.54 ± 34.48	0.001*
C4 level (mg/dl)	12.17 ± 6.69	8.77 ± 6.47	0.005*
Anti-dsDNA (IU/mL)	143.22 ± 148.05	243.74 ± 173.53	0.001*
Creatinine (mg/dL)	1.25 ± 0.65	1.55 ± 0.80	0.029*
Hemoglobin	11.71 ± 1.33	11.54 ± 1.55	0.122
Neurological symptoms n (%)	2 (4.55%)	34 (35.42%)	<0.001*
Skin manifestations n (%)	26 (59.09%)	62 (64.58%)	0.124
Hematological manifestations n (%)	21 (47.73%)	46 (47.92%)	0.99
Oral ulcers n (%)	30 (68.18%)	70 (72.92%)	0.687
Arthritis n (%)	31 (70.45%)	66 (68.75%)	0.99
Renal involvement n (%)	12 (27.27%)	46 (47.92%)	0.027*

P value <0.05. SLE = Systemic lupus erythematosus; SD = Standard deviation; ESR: Erythrocyte sedimentation rate; CRP:C-reactive protein; C3 = Complement component 3; C4 = Complement component 4; dsDNA = Double-stranded DNA.

rs187084–rs5743836 haplotype association with SLE

The promoter haplotype at positions −1486T/C and −1237T/C showed that the CC haplotype was significantly more frequent in SLE patients (8.92%) than in controls (6.43%). Compared to the TT haplotype, the CC haplotype was associated with an increased risk of SLE (OR 3.18; 95% CI [1.74–6.05]; P < 0.001) (Table 3).

Discussion

Activation of TLR9 initiates MyD88-dependent signaling, leading to the activation of NF-κB and IRF transcription factors. This results in the production of proinflammatory cytokines such as TNF-α, IL-6, and type I interferons. In B cells, TLR9 signaling plays a role in activation, class switching, and differentiation into plasmablasts. Dysregulated TLR9 activity serves as a crucial link between nucleic acid sensing and the breakdown of tolerance, which is particularly relevant to the development of SLE.^12,31,32 A wide range of experimental and clinical evidence suggests that TLR9 plays a significant role in the pathogenesis, disease activity, and organ-specific severity of SLE. Studies in lupus-prone mouse models have shown that genetic deletion of TLR9 greatly reduces or eliminates the production of spontaneous anti-dsDNA and antichromatin autoantibodies, indicating that TLR9 is essential for the development of anti-DNA autoreactivity. However, other autoreactive specificities, such as anti-RNA/Sm antibodies, persisted or even increased in the absence of TLR9.³³ In humans, multiple studies have reported increased TLR9 expression in various samples from SLE patients. Higher TLR9 levels are correlated with SLEDAI scores and markers of poor prognosis. Tissue analyses have shown increased TLR9 transcripts and protein in lupus nephritis biopsies, demonstrating robust proximal tubular TLR9 expression that parallels proteinuria and worsens glomerular injury. These observations implicate tubular TLR9 in the amplification of intrarenal inflammation and injury, suggesting that therapeutic strategies aimed at preventing or suppressing intrarenal TLR9 expression may mitigate renal damage in SLE.^34,35 Clinically, persistently high TLR9 mRNA in whole blood is associated with poor prognosis and sustained disease activity over follow-up. Conversely, decreases in TLR9 expression are linked to favorable outcomes. These findings support a role for TLR9 as both a mediator of renal pathology and a potential biomarker of disease activity and severity in SLE.³⁶ Beyond SLE, TLR9 overexpression has also been observed in other autoimmune diseases, such as systemic sclerosis, specifically in CD3 + T lymphocyte cells. Notably, particularly high levels of TLR9 are found in the diffuse cutaneous subtype, correlating with skin fibrosis and increased disease severity. This suggests that TLR9 may play a role as a consistent amplifier of autoimmunity and tissue fibrotic processes, making it a potential marker for disease severity.³⁷

Given the central role of transcriptional regulation in TLR9 expression, promoter polymorphisms that alter transcription factor binding may influence TLR9 levels and, consequently, autoimmunity. Two functional variants in the TLR9 promoter, rs187084 and rs5743836, have been identified. In vitro promoter activation and luciferase reporter assays show increased activity for specific alleles of these SNPs compared to the wild-type sequence. Bioinformatic analyses indicate that the rs5743836 (C allele) creates or enhances binding motifs for transcription factors such as c-Rel/NF-κB, a site responsive to IL-6, and estrogen receptor α (ERα). In contrast, rs187084 is predicted to introduce or enhance a Sp1 binding site.^27–29 Functional stimulation studies provide further evidence: PBMCs carrying the rs187084 C allele exhibit increased TLR9 transcriptional induction after microbial stimulation,³⁸ and PBMCs with the rs5743836 TC genotype show elevated TLR9 and IL-6 expression along with increased B cell proliferation in response to CpG, which depends on IL-6 signaling.³⁹ The proximity of rs5743836 to an NF-κB/ERα regulatory motif suggests a mechanism linking inflammatory and hormonal regulation of TLR9 expression. However, cell-type and allele-specific variability is observed; for example, some assays report higher activity with the T allele at position −1237. These findings underscore that the net effect of these SNPs depends on cellular context, stimuli, and regulatory factors.³⁰

Our study found that the rs5743836 C allele was associated with an increased risk of SLE and is consistent with prior reports of this allele’s association with upregulated TLR9 expression. Importantly, carriers of the C allele (TC + CC) in our cohort also presented with earlier disease onset and more active, severe disease, manifested by higher CRP and anti-dsDNA levels, reduced complement C3 and C4, and greater frequencies of renal and neurological complications. These results support the hypothesis that heightened TLR9 signaling contributes to elevated autoantibody production, inflammation, and organ damage in SLE. However, the literature on rs5743836 is heterogeneous. Santos et al. reported an increased SLE risk (OR = 1.59) and higher anti-SSa/Ro frequency for the C allele in a Southern Brazilian, primarily European-derived female sample.⁴⁰ Conversely, several large meta-analyses and population studies did not find a consistent association. Pooled analyses failed to show a risk for rs5743836 across Asian, European, Latin American, American, and African populations.^41,42 Studies in Omani and some Caucasian (UK and US) cohorts likewise reported no overall SLE association.^43–45 The Omani study linked rs5743836 to anti-cardiolipin IgM levels, a marker that in some reports correlates with disease activity.^43,46,47 These discrepant results point to ancestry-specific effects, variable allele frequencies, and possible differences in linkage disequilibrium or environmental modifiers across populations.

Although rs187084 was not associated with overall SLE susceptibility in our cohort, carriers of the rs187084 C allele (TC + CC) exhibited phenotypes resembling those of rs5743836 C allele carriers: earlier age of onset, greater disease activity, increased frequency of renal involvement (including higher creatinine), and more neurological presentations. These findings support the hypothesis that the rs187084 C allele may modulate TLR9 expression or signaling, contributing to disease severity even if it does not independently increase population-level risk. This view aligns with a complex and partially inconsistent body of evidence, where ethnicity and study design influence observed associations. For example, a 2023 meta-analysis reported that the rs187084 T allele was associated with SLE in Asians but not in Arabs.⁴¹ A Taiwanese study found the T allele linked to increased SLE risk but observed no genotype-phenotype correlations.⁴⁸ Other meta-analyses reported an overall association for rs187084 that disappeared upon ethnic stratification, and comprehensive reviews have failed to demonstrate a clear association across ancestries.^42,49 Together, these data suggest that rs187084 may function more consistently as a modifier of clinical expression or via linkage with other regulatory variants in certain genetic backgrounds; accordingly, our findings demonstrate that the rs187084_rs5743836 CC haplotype correlates with increased risk of SLE.

Our primary focus was on SLE, but the functional implications of TLR9 promoter variants extend to broader human health due to the receptor’s universal role in innate immunity. TLR9 plays a crucial role in pathogen recognition by detecting unmethylated CpG motifs, especially in viruses and intracellular bacteria.⁵⁰ Polymorphisms like rs187084 that affect TLR9 expression levels may impact the efficiency of the initial immune response to various infectious challenges. Individuals with high-expression haplotypes may show enhanced clearance of certain pathogens, while those with lower-expression variants could be more susceptible to infections with CpG DNA-utilizing microbes.⁵¹ Additionally, sustained, low-grade activation of this pathway, influenced by promoter variants, is linked to chronic inflammatory conditions beyond autoimmune diseases. The clinical impact observed in SLE likely represents an extreme manifestation of a genetic predisposition that subtly influences immune homeostasis, affecting general health and resistance to infectious diseases.

In conclusion, our data suggest that promoter variation in TLR9, specifically the rs5743836 C allele and the combined rs187084_rs5743836 CC haplotype, is linked to increased risk of SLE and more severe clinical presentation. This includes earlier onset, higher serologic activity, greater complement consumption, and increased renal and neurological involvement. These findings support the idea that heightened TLR9 signaling contributes to elevated autoantibody production, inflammation, and organ damage in SLE. Limitations of our study include a relatively small sample size, which may reduce the power to detect rare genotypes and result in wider confidence intervals. In addition, SLEDAI scores and some important clinical/laboratory manifestations, including nephritis and proteinuria, were not available for all patients due to incomplete clinical records. Therefore, associations between these parameters and TLR9 genotypes could not be comprehensively evaluated. Furthermore, the functional impact of these variants may vary among different ethnic groups due to genetic heterogeneity and environmental influences. Thus, these polymorphisms might reflect population-specific genetic patterns rather than direct causal roles in disease pathogenesis. Additionally, potential residual population stratification and the lack of direct functional or expression data linking the identified genotypes and haplotypes to changes in TLR9 transcription or downstream signaling are important considerations. To overcome these limitations, we recommend replication of our findings in larger, multiethnic cohorts, fine mapping, and evaluation of additional regulatory variants within and near the TLR9 gene. Integrated expression analyses, including mRNA and protein levels, should be conducted to establish genotype-expression correlations and assess the impact of different genotypes and haplotypes on TLR9 activity. This approach would clarify the causal relationship and potential clinical implications of TLR9 variants as prognostic biomarkers or therapeutic targets.

Footnotes

Acknowledgment

We would like to appreciate any support provided by Isfahan university of Medical Sciences.

ORCID iDs

Meysam Mosallaei

Narges Ansari

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

Ameer

Chaudhry

Mushtaq

, et al. An overview of systemic lupus erythematosus (SLE) pathogenesis, classification, and management. Cureus 2022; 14: e30330. https://doi.org/10.7759/cureus.30330

Júnior

VFAJA

Silva

Amaral

, et al. Systemic Lupus Erythematosus (SLE): most common clinical manifestations and renal complications. Brazilian Journal of Implantology and Health Sciences 2024; 6: 647–660. https://doi.org/10.36557/2674-8169.2024v6n9p647-660

Wais

Agrawal

. Systemic lupus erythematous: gene polymorphisms, epigenetics, environmental, hormonal and nutritional factors in the consideration of personalized therapy. Archives of internal medicine research 2024; 7: 331–340. https://doi.org/10.26502/aimr.0188

Alrahimi

Alahmadi

. Understanding the complexities of systemic lupus erythematosus: bridging gaps in epidemiology, environmental triggers, and. Immunology. 2025; 28: 2606–2617.

Demkova

Morris

Vyse

. Genetics of SLE: does this explain susceptibility and severity across racial groups? Rheumatology 2023; 62: i15–i21. https://doi.org/10.1093/rheumatology/keac695

Kwon

Chun

Kim

, et al. Update on the genetics of systemic lupus erythematosus: genome-wide association studies and beyond. Cells 2019; 8: 1180. https://doi.org/10.3390/cells8101180

Saadat

. Enrichment analysis of systemic lupus erythematosus susceptible loci identified by genome-wide association studies. Hum Immunol 2024; 85: 111116. https://doi.org/10.1016/j.humimm.2024.111116

Frangou

Bertsias

Boumpas

. Gene expression and regulation in systemic lupus erythematosus. Eur J Clin Invest 2013; 43: 1084–1096. https://doi.org/10.1111/eci.12130

Jones

Cantsilieris

Fan

, et al. Rare variants in non-coding regulatory regions of the genome that affect gene expression in systemic lupus erythematosus. Sci Rep 2019; 9: 15433. https://doi.org/10.1038/s41598-019-51864-9

10.

Kumagai

Takeuchi

Akira

. TLR9 as a key receptor for the recognition of DNA. Adv Drug Deliv Rev 2008; 60: 795–804. https://doi.org/10.1016/j.addr.2007.12.004

11.

Pandey

Kawai

Akira

. Microbial sensing by toll-like receptors and intracellular nucleic acid sensors. Cold Spring Harbor Perspect Biol 2015; 7: a016246. https://doi.org/10.1101/cshperspect.a016246

12.

Wen

Zhang

, et al. Toll-like receptors 7 and 9 regulate the proliferation and differentiation of B cells in systemic lupus erythematosus. Front Immunol 2023; 14: 1093208. https://doi.org/10.3389/fimmu.2023.1093208

13.

Panda

Kolbeck

Sanjuan

. Plasmacytoid dendritic cells in autoimmunity. Curr Opin Immunol 2017; 44: 20–25. https://doi.org/10.1016/j.coi.2016.10.006

14.

Mahajan

Herrmann

Muñoz

. Clearance deficiency and cell death pathways: a model for the pathogenesis of SLE. Front Immunol 2016; 7: 35. https://doi.org/10.3389/fimmu.2016.00035

15.

Hamilton

Hsu

Mountz

. Role of production of type I interferons by B cells in the mechanisms and pathogenesis of systemic lupus erythematosus. Discov Med 2018; 25: 21–29.

16.

Lacerte

Brunet

Egarnes

, et al. Overexpression of TLR2 and TLR9 on monocyte subsets of active rheumatoid arthritis patients contributes to enhance responsiveness to TLR agonists. Arthritis Res Ther 2016; 18: 10. https://doi.org/10.1186/s13075-015-0901-1

17.

Karlsen

Jakobsen

Jonsson

, et al. Expression of toll‐like receptors in peripheral blood mononuclear cells of patients with primary Sjögren's syndrome. Scand J Immunol 2017; 85: 220–226. https://doi.org/10.1111/sji.12520

18.

Peng

Wang

, et al. Increased toll-like receptors activity and TLR ligands in patients with autoimmune thyroid diseases. Front Immunol 2016; 7: 578. https://doi.org/10.3389/fimmu.2016.00578

19.

Balashov

Aung

Vaknin‐Dembinsky

, et al. Interferon‐β inhibits toll‐like receptor 9 processing in multiple sclerosis. Ann Neurol 2010; 68: 899–906. https://doi.org/10.1002/ana.22136

20.

Fang

Marangoni

Zhou

, et al. Toll‐like receptor 9 signaling is augmented in systemic sclerosis and elicits transforming growth factor β–dependent fibroblast activation. Arthritis Rheumatol 2016; 68: 1989–2002. https://doi.org/10.1002/art.39655

21.

Mortezagholi

Babaloo

Rahimzadeh

, et al. Evaluation of TLR9 expression on PBMCs and CpG ODN-TLR9 ligation on IFN-α production in SLE patients. Immunopharmacol Immunotoxicol 2017; 39: 11–18. https://doi.org/10.1080/08923973.2016.1263859

22.

Celhar

Magalhaes

Fairhurst

. TLR7 and TLR9 in SLE: when sensing self goes wrong. Immunol Res 2012; 53: 58–77. https://doi.org/10.1007/s12026-012-8270-1

23.

Zhang

. Expression level of TLR9, but not hypomethylation, is correlated with SLE disease activity. Physiol Res 2019; 68: 973–980. https://doi.org/10.33549/physiolres.934167

24.

Nakano

Morimoto

Suzuki

, et al. Role of pathogenic auto-antibody production by toll-like receptor 9 of B cells in active systemic lupus erythematosus. Rheumatology 2008; 47: 145–149. https://doi.org/10.1093/rheumatology/kem327

25.

Rao

Zeng

Liang

, et al. Correlation between TLR9 expression and cytokine secretion in the clinical diagnosis of systemic lupus erythematosus. Mediat Inflamm 2015; 2015: 710720. https://doi.org/10.1155/2015/710720

26.

Conti

Spinelli

Truglia

, et al. Kidney expression of toll like receptors in lupus nephritis: quantification and clinicopathological correlations. Mediat Inflamm 2016; 2016: 7697592. https://doi.org/10.1155/2016/7697592

27.

Fischer

Weber

Böhm

, et al. Sex-specific effects of TLR9 promoter variants on spontaneous clearance of HCV infection. Gut 2017; 66: 1829–1837. https://doi.org/10.1136/gutjnl-2015-310239

28.

Mollaki

Georgiadis

Tassidou

, et al. Polymorphisms and haplotypes in TLR9 and MYD88 are associated with the development of Hodgkin's lymphoma: a candidate–gene association study. J Hum Genet 2009; 54: 655–659. https://doi.org/10.1038/jhg.2009.90

29.

Hamann

Glaeser

Hamprecht

, et al. Toll-Like Receptor (TLR)-9 promotor polymorphisms and atherosclerosis. Clin Chim Acta 2006; 364: 303–307. https://doi.org/10.1016/j.cca.2005.07.017

30.

Novak

Bussmann

, et al. Putative association of a TLR9 promoter polymorphism with atopic eczema. Allergy 2007; 62: 766–772. https://doi.org/10.1111/j.1398-9995.2007.01358.x

31.

Yasaka

Yamazaki

Sato

, et al. Phospholipase D4 as a signature of toll-like receptor 7 or 9 signaling is expressed on blastic T-bet + B cells in systemic lupus erythematosus. Arthritis Res Ther 2023; 25: 200. https://doi.org/10.1186/s13075-023-03186-5

32.

Suthers

Sarantopoulos

. TLR7/TLR9-and B cell receptor-signaling crosstalk: promotion of potentially dangerous B cells. Front Immunol 2017; 8: 775. https://doi.org/10.3389/fimmu.2017.00775

33.

Christensen

Kashgarian

Alexopoulou

, et al. Toll-like receptor 9 controls anti-DNA autoantibody production in murine lupus. J Exp Med 2005; 202: 321–331. https://doi.org/10.1084/jem.20050338

34.

Benigni

Caroli

Longaretti

, et al. Involvement of renal tubular toll‐like receptor 9 in the development of tubulointerstitial injury in systemic lupus. Arthritis Rheum 2007; 56: 1569–1578. https://doi.org/10.1002/art.22524

35.

Elloumi

Fakhfakh

Abida

, et al. Relevant genetic polymorphisms and kidney expression of Toll-Like Receptor (TLR)-5 and TLR-9 in lupus nephritis. Clin Exp Immunol 2017; 190: 328–339. https://doi.org/10.1111/cei.13022

36.

Yuan

Zhao

, et al. Association of toll-like receptor 9 expression with prognosis of systemic lupus erythematosus, Exp Ther Med 2019; 17: 3247–3254. https://doi.org/10.3892/etm.2019.7290

37.

Gheita

Sayed

Azkalany

, et al. Toll-like receptor 9 in systemic sclerosis patients: relation to modified Rodnan skin score, disease severity, and functional status. Clin Rheumatol 2018; 37: 757–763. https://doi.org/10.1007/s10067-017-3880-6

38.

Bharti

Kumar

Mahla

, et al. The role of TLR9 polymorphism in susceptibility to pulmonary tuberculosis. Immunogenetics 2014; 66: 675–681. https://doi.org/10.1007/s00251-014-0806-1

39.

Carvalho

Osório

Saraiva

, et al. The C allele of rs5743836 polymorphism in the human TLR9 promoter links IL-6 and TLR9 up-regulation and confers increased B-cell proliferation. PLoS One 2011; 6: e28256. https://doi.org/10.1371/journal.pone.0028256

40.

Dos Santos

Valverde

Rohr

, et al. TLR7/8/9 polymorphisms and their associations in systemic lupus erythematosus patients from southern Brazil. Lupus 2012; 21: 302–309. https://doi.org/10.1177/0961203311425522

41.

Lee

Song

. Systemic lupus erythematosus and toll-like receptor 9 polymorphisms: a meta-analysis of genetic association studies. Lupus 2023; 32: 964–973. https://doi.org/10.1177/09612033231180695

42.

Cheng

Zhang

, et al. Associations between PTPN22 and TLR9 polymorphisms and systemic lupus erythematosus: a comprehensive meta-analysis. Arch Dermatol Res 2017; 309: 461–477. https://doi.org/10.1007/s00403-017-1745-0

43.

Al-Ghafri

AAM

. Investigation of TLR9 single nucleotide polymorphism (rs352139 and rs5743836) Association with systemic lupus erythematosus in Omani population. Sultan Qaboos University, 2021.

44.

De Jager

Richardson

Vyse

, et al. Genetic variation in toll‐like receptor 9 and susceptibility to systemic lupus erythematosus. Arthritis Rheum 2006; 54: 1279–1282. https://doi.org/10.1002/art.21755

45.

Demirci

FYK

Manzi

Ramsey-Goldman

, et al. Association study of Toll-Like Receptor 5 (TLR5) and Toll-Like Receptor 9 (TLR9) polymorphisms in systemic lupus erythematosus. J Rheumatol 2007; 34: 1708–1711.

46.

Frodlund

Walhelm

Dahle

, et al. Longitudinal analysis of anti-cardiolipin and anti-β2-glycoprotein-I antibodies in recent-onset systemic lupus erythematosus: a prospective study in Swedish patients. Front Med 2021; 8: 646846. https://doi.org/10.3389/fmed.2021.646846

47.

Buttgereit

Grünewald

Schüler-Maué

, et al. Value of anticardiolipin antibodies for monitoring disease activity in systemic lupus erythematosus and other rheumatic diseases. Clin Rheumatol 1997; 16: 562–569. https://doi.org/10.1007/BF02247796

48.

Huang

Chen

, et al. Association of toll-like receptor 9 gene polymorphism in Chinese patients with systemic lupus erythematosus in Taiwan. Rheumatol Int 2012; 32: 2105–2109. https://doi.org/10.1007/s00296-011-1925-8

49.

Lee

Choi

, et al. Association between toll-like receptor polymorphisms and systemic lupus erythematosus: a meta-analysis update. Lupus 2016; 25: 593–601. https://doi.org/10.1177/0961203315622823

50.

Nielsen

Nishizaki

Kato

, et al. TLR9: a double-dealing toll-like receptor. ImmunoTargets Ther 2025; 14: 1531–1554. https://doi.org/10.2147/ITT.S563765

51.

Nurjadi

Heeg

Weber

, et al. Toll-Like Receptor 9 (TLR-9) promotor polymorphisms and gene expression are associated with persistent Staphylococcus aureus nasal carriage. Clin Microbiol Infection 2018; 24: 1210. https://doi.org/10.1016/j.cmi.2018.02.014