Abstract
Objectives
Gout is caused by the response of the innate immune system to monosodium urate (MSU) crystals. A recent gout GWAS identified a signal of genetic association at a locus encompassing IL1RN-IL1F10. Colocalisation analysis using Genotype Tissue Expression Database (GTEx) eQTL data showed that the signal overlaps with genetic control of IL1RN/IL1F10 gene expression. We assess the functional implications of IL1RN rs9973741, the lead gout-associated variant.
Methods
We conducted functional validation of IL1RN rs9973741 in patients with gout and controls. The transcription level of IL1RN/IL1F10 was investigated in unstimulated or MSU-crystal co-stimulated PBMCs. Ex vivo functional assays were performed in PBMCs stimulated with C16 + MSU crystals or LPS for 24 h. Cytokine levels were assessed by ELISA.
Results
In unstimulated PBMCs, no association of IL1RN rs9973741 (gout risk allele G) to IL1RN expression was observed while IL-1F10 was hindered by low expression at both transcriptional and protein levels. However, G allele carriers showed lower IL1RN expression in PBMCs stimulated with C16/MSU crystal and lower concentrations of circulating IL-1Ra in both controls and gout patients. PBMCs depicted less spontaneous IL-1Ra release in GG homozygous controls and lower IL-1Ra production in response to C16 + MSU crystal costimulation in patients with gout. The G allele was associated with elevated IL-1β cytokine production in response to C16 + MSU crystal stimulation in controls.
Conclusions
The gout risk allele G associates with lower circulating IL-1Ra, lower IL-1Ra production in PBMC assays and elevated IL-1β production in PBMCs challenged with C16 + MSU crystals but not in unchallenged cells. Our data indicate that the genetic signal that associates with gout at IL1RN-IL1F10 region functions to alter expression of IL-1Ra when stimulated by MSU crystals.
Supplementary Information
The online version contains supplementary material available at 10.1186/s13075-024-03436-0.
Keywords: Gout, Urate, SNP, IL1RN, IL1F10, Locus
Introduction
Gout is a common inflammatory disorder affecting approximately 41 million adults worldwide [1–3]. The neccesary prerequisite for gout is the deposition of monosodium urate (MSU) crystals in the joints and other tissues as a result of elevated serum urate concentrations [4, 5].
Interleukin IL-1β is the crucial inflammatory cytokine in gout, which is antagonized by IL-1 Receptor antagonist (IL-1Ra), both of which are known to be modulated in gout and urate-driven inflammation [6]. IL-1Ra operates as an acute-phase protein, its expression being strongly induced by LPS, IL-1α and IL-1β, and interferon (IFN)-β [7, 8]. The balance between IL-1 and IL-1Ra is critical for the development of adaptive immune responses and for the regulation of innate immunity [9]. IL-1F10 (IL-38) is another anti-inflammatory member of the IL‐1 family that shares 41% sequence homology with IL‐1Ra [10] and is known to suppress inflammation [11].
Although the indispensable cause of gout (MSU crystal exposure) is well described in the literature [12–14], the genetic contribution to the progression from hyperuricemia to gout is still relatively poorly understood. Genome-wide association studies (GWAS) in gout using individuals with asymptomatic hyperuricemia as controls have mostly identified variants in urate transporters (ABCG2, SLC2A9, SLC22A11) as predictors of the transition to clinically evident gout [15–17]. These studies, however, need to be interpreted with caution, as higher urate levels measured once in hyperuricemic patients do not represent strong evidence for association of genetic variants in the transition from hyperuricemia to gout [18]. Recently, a large gout GWAS has identified variants near genes in inflammatory pathways, such as genetic variation at the IL1RN-IL1F10 region, with possible roles in the inflammatory aspects of transition from asymptomatic hyperuricemia to gout [19].
Our group previously described that soluble urate primes cells via epigenetic programming towards a higher inflammatory state along with downregulating the transcription of IL1RN [20]. High concentrations of urate facilitate IL-1β production in PBMCs along with downregulation of IL-1Ra, causing a shift in the IL-1β/IL-1Ra balance [21]. In addition, IL-1Ra has been shown to inhibit MSU crystal induced inflammation, being an important therapeutic target in gouty inflammation [6]. These findings implicate the IL1RN-IL1F10 loci in gout, representing well characterized molecules directly connected to IL-1β induced inflammation.
Therefore, in the present study, we tested for functional impact of genetic variation at the IL1RN-IL1F10 region in gout. Also, we assessed the association of the rs9973741 with IL1RN-IL1F10 expression in circulating mononuclear cells and cytokine production capacity in patients with gout and controls.
Materials and methods
Genetic analyses
Summary GWAS statistics for the UKBB blood cell traits were downloaded from https://ftp.sanger.ac.uk/pub/project/humgen/summary_statistics/UKBB_blood_cell_traits/ and for gout from Major et al. [22] study. Plots were generated using LocusZoom [23]. Correlated traits for the lead gout SNP were identified using LDtrait and linkage disequilibriu, (LD) was calculated using 1000 genomes in LDlink [24, 25]. The tissue-specific genetic effects of the rs9973741 SNP were studied accessing the Genotype-Tissue Expression (GTEx) Database, which can provide information on the expression levels of thousands of genes in diverse tissues granting access to test whether genetic variants might have a role in altering gene expressions, across various tissues [26]. Further, the eQTLGen Database was accessed, which is a large-scale resource, focused on understanding the genetic basis of gene expression regulation through expression quantitative trait loci (eQTLs) in whole blood [27]. This Database combines data from multiple cohorts to identify associations between genetic variants and gene expression across a wide range of individuals, representing one of the largest eQTL databases available online. Therefore, it represents a valuable tool for studying the genetic regulation of gene expression in whole blood.
Participants
The participants in this study consisted of patients with gout (n = 246) and asymptomatic controls (n = 443) recruited at the Rheumatology Department of the “Iuliu Haţieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania for the HINT Project. (Hyperuricemia-induced Inflammation: Targeting the central role of uric acid in rheumatic and cardiovascular diseases, ID P 37 762; MySMIS 103587) implemented in Cluj-Napoca Romania at the Iuliu Haţieganu University of Medicine and Pharmacy. Subjects were enrolled after written informed consent. Peripheral blood was drawn from the cubital vein into EDTA tubes under sterile conditions. Experiments were conducted according to the principles expressed in the Declaration of Helsinki. The patient study was approved by the Ethical Committee of the „Iuliu Hațieganu” University of Medicine and Pharmacy, Cluj-Napoca (approval no. 425/2016). All study participants in the gout group were included based on ACR/EULAR 2015 classification criteria with a minimum score of 8 and controls had negative history of gout attacks. The described groups were similar in age and BMI. The gender distribution shows a higher number of men in the gout study group, consistent with the higher prevalence of gout in males.
PBMC isolation and stimulation
Isolation and stimulation of human peripheral blood mononuclear cells (PBMCs) was assessed as described previously [21]. PBMCs were separated using Ficoll-Paque and resuspended in RPMI culture medium with Dutch modification (Gibco), supplemented with human pooled serum. Cells were incubated for 24 h with culture medium as negative control or palmitate with MSU crystals (C16.0 + MSU) (gout relevant costimulation cocktail for TLR2 binding and NLRP3 inflammasome activation), or LPS (TLR4 ligand). Cells were incubated at 37 °C 5% CO2. Cytokine levels were measured in culture supernatants.
Cytokine measurements
Cytokine concentrations were determined in cell culture supernatants using specific sandwich ELISA kits for IL-1β, IL-1Ra, IL-6 (R&D Systems, Minneapolis). The lowest range of detection was 39 pg/ml for IL-1β; 390 pg/ml for IL-1Ra and 94 pg/ml for IL-6. Samples were diluted before assay 10-fold for IL-1β and IL-1Ra and 20-fold for IL-6.
Genotyping for IL1RN rs9973741
Two independent groups were genotyped (gout group N = 246 and control group N = 443). Genomic DNA was isolated from whole blood (Promega) and genotyping was performed on an Illumina Infinium HD assay platform using The Infinium Global Screening Array-24 v3.0 BeadChip. Quality control for genotyping data was performed Using Illumina’s GenomeStudio. The SNPs with < 95% call rate were excluded and all the remaining SNPs were verified and manually re-clustered or removed when necessary. The data were exported to PLINK format and further filters were applied: minor allele frequency > 0.01; Hardy-Weinberg equilibrium test p value > 10−6; samples with heterozygosity rate of +/−3 standard deviations and related individuals were excluded. For the final step, the strands were flipped and all the data was verified to align to the GRCh37 hg19 build.
Transcriptomics
Freshly isolated PBMCs were frozen in TRIzol Reagent (Invitrogen) and stored at − 80 °C until bulk RNA-Sequencing analysis (outsourced to Beijing Genomics Institute, BGI, Denmark). The integrity of extracted RNA was assessed using the Agilent 2100 Bioanalyzer. Oligo dT magnetic beads were used to capture mRNA from total RNA. Fragmented target RNA was reverse transcribed to cDNA using random N6 primers followed by end-repair and A tailing for adaptor ligation. Purified ligation products were enriched using PCR amplification followed by denaturation and cyclization of ssDNA by splint oligos and DNA ligase generating DNA nanoballs (DNBs). Sequencing of DNBs was performed on DNBseq platform. Raw data were generated by removing reads mapped to rRNAs. Clean reads were generated using the SOAPnuke software (v.1.5.2) by removing reads with adaptors, reads with unknown bases > 10% and low-quality reads. These were later defined as reads with a quality score less than 15 in over 50% bases. Clean reads were mapped to UniGenes and read counts were estimated using Bowtie2 and RSEM (v.1.2.12). Normalization, quality control and identification of differentially expressed genes (DEGs) was performed using the Bioconductor package DESeq2 (Version: DESeq2_1.24.0). Quality control at this stage consisted of removal of samples with highly abnormal values (PCA: ± 3 Standard Deviations on PC1 or PC2). The samples were sequenced in two different batches and the resulting effect was corrected using the limma package. The resulting variance stabilized (VS) counts were used for the target genes for statistical analysis.
Statistical methods
Statistical analysis was performed using GraphPad version 10.0.0 (GraphPad Software, La Jolla California USA) and R software. Comparisons were performed using One-Way ANOVA or Kruskal-Wallis when testing for at least 3 groups, and Student t-test or Mann-Whitney, when comparing 2 groups. Values of P < 0.05 were considered statistically significant.
Results
GWAS identified gout-associated IL1RN rs9973741 variant is an expression quantitative trait locus (eQTL) for IL1RN and IL1F10
As previously reported [22] the gout GWAS signal at the IL1RN locus colocalised with signals of genetic control of expression of both the IL1RN and IL1F10 genes (Fig. 1A-F). The index SNP with the lowest p-value at the IL1RN-IL1F10 region was rs9973741, for which the minor allele G significantly associated with IL-1β response to MSU crystal stimulation [β = 0.34, P = 3.6 × 10−4] [22]. The GWAS signal colocalises ((posterior probability of colocalisation > 0.8) with a signal of genetic control of expression (i.e. an expression quantitative trait locus (eQTL)) for each of IL1RN and IL1F10 [22]. The gout risk allele, G, was associated to discordant expression patterns in the GTEx data (lower IL1RN expression in adipose tissue versus higher IL1RN expression in testis), suggesting context-specific control of IL1RN expression, while IL1F10 (IL38) showed decreased expression in G allele carriers [22] in skin tissue samples, in both sun exposed and not exposed. Here we show that, in addition to the association of IL1RN rs9973741 with available GTEx data [28] (for IL1RN in subcutaneous adipose tissue and testis (Fig. 1C and D), and for IL1F10 in skin (Fig. 1E, F)) the rs9973741 variant is also an eQTL for IL1RN in whole blood according to eQTLGen data (Fig. 1B) (Table 1). However, in whole blood data, the variant represents a minor signal, possibly due to the existence of different cell-types in different states of activation [27] (Fig. 1B). The gout variant rs9973741_allele G in the eQTLGen dataset is negatively associated with the expression of the IL1RN gene (Z-score − 6,715, p = 1,88 × 10−11), consistent with a role for IL-1Ra in suppressing gout.
Fig. 1.
Locus Zoom plots of IL1RN locus in Euroean Gout GWAS, GTEx and eQTLGen dataset (whole blood). The IL1RN rs9973741 SNP is labeled in purple. Each dot represents an individual SNP with the colour representing the LD with the most associated (lead) SNP with gout in the panel. The vertical axis represents -log10 (p value) for assessment of the association of the SNP with IL1RN expression. The genes within the region are annotated, and the direction of the transcripts is shown by arrows. The plot was generated using LocusZoom [23]. Values for posterior probability of colocalisation (PPC) are included in the panels
Table 1.
Association of IL1RN rs9973741 with gene expression in GTEx and eQTLGen datasets, where the assessed allele is „G”
eQTL - IL1RN rs9973741 | |||||
---|---|---|---|---|---|
eQTL Gene | Tissue | P-value | Normalized EffectSize-GTEx | Z-score-eQTLGen | Source |
IL1F10 | Skin - Sun Exposed (Lower leg) | 1.10E-09 | −0.18 | - | GTEx Analysis Release V14 |
IL1F10 | Skin - Not Sun Exposed (Suprapubic) | 6.90E-07 | −0.16 | - | GTEx Analysis Release V15 |
IL1RN | Testis | 4.00E-11 | 0.29 | - | GTEx Analysis Release V16 |
IL1RN | Skin - Not Sun Exposed (Suprapubic) | 1.70E-08 | 0.13 | - | GTEx Analysis Release V17 |
IL1RN | Thyroid | 8.30E-07 | −0.18 | - | GTEx Analysis Release V18 |
IL1RN | Skin - Sun Exposed (Lower leg) | 0.0000069 | 0.091 | - | GTEx Analysis Release V19 |
IL1RN | Adipose - Subcutaneous | 0.00002 | −0.13 | - | GTEx Analysis Release V20 |
PSD4 | Lung | 0.0000074 | −0.15 | - | GTEx Analysis Release V21 |
PSD4 | Nerve - Tibial | 0.000022 | −0.16 | - | GTEx Analysis Release V22 |
PSD4 | Blood sample | 1.12E-17 | - | −8,5603 | eQTLGen-2019-12-25-release |
IL1RN | Blood sample | 1.88E-11 | - | −6,715 | eQTLGen-2019-12-26-release |
SLC20A1 | Blood sample | 2.71E-10 | - | −6,3146 | eQTLGen-2019-12-27-release |
Moreover, IL-1Ra was identified in a proteome-wide association study (PWAS) of serum urate and gout, showing that genetically-controlled higher IL-1Ra concentrations exhibit protection from gout [29]. The IL1RN-IL1F10 region has been found to be associated with different types of markers of systemic inflammation, including Interleukin-1 receptor antagonist protein (IL-1Ra), Interleukin-1 receptor type 1 (IL-1R1), Fibrinogen alpha chain (FGA), Complement factor H-related protein 5 (CFHR5), Interleukin-6 (IL-6) with the lead variant rs55709272 in these studies is in linkage disequilibrium (LD) with the gout variant rs9973741 (R2 = 0.83). In addition, the lead gout variant at IL1RN rs9973741 is also amongst the maximally associated variants for several blood cell traits identified in previous GWAS studies [30, 31] (Supplementary Fig. 1).
Basal expression and protein concentrations for IL-1Ra and IL-38 in rs9973741 carriers
We further examined the basal expression level of IL1RN in freshly isolated unstimulated PBMCs from patients with gout or controls (Fig. 2A). No association of rs9973741 with IL1RN read counts was observed. Variation in IL1F10 expression could not be assessed due to low expression levels of IL1F10 in PBMCs. We next assessed the basal protein concentration in the plasma of patients with gout and controls. We observed that the gout risk allele is associated with decreasing concentrations of circulating IL-1Ra, consistent with the gene expression data (Fig. 2B). For IL-38 protein concentrations, despite many samples being below the detection level (16 pg/ml), a significant association of rs9973741 could still be observed in the control group ( AA genotype carriers produced more IL-38 (mean 79.43 pg/ml +/- SEM 14.3 pg/ml) in comparison with AG genotype carriers (mean 76.41 pg/ml +/- SEM 16.3 pg/ml; p = 0,0073). However, this significant difference in the IL-38 circulating protein levels is not observed when comparing AA genotype carriers to GG genotype carriers (mean 59.38 pg/ml +/- SEM 24.42 pg/ml; p = 0,7824), possibly due to small number of samples with detectable levels.
Fig. 2.
Correlation of the GWAS SNP rs9973741 with IL1RN and IL38 expression levels (A) mRNA expression of the two genes in freshly isolated PBMCs originating from gout patients (n = 64) and asymptomatic controls (n = 128). The data is represented as variance stabilized (VS) counts. B Circulating IL-1Ra plasma concentrations in n = 443 controls and n = 246 gout patients. (C) Circulating IL38 concentrations measured in the serum of controls (n = 330) and gout patients (n = 238). Graphs depict means+/−SEM. Kruskal-Wallis and post-hoc analysis p < 0,05
Assessment of ex vivo cytokine production capacity in PBMCs of IL1RN rs9973741 carriers validates lower IL-1Ra release upon C16 and MSU crystal stimulation in patients with gout
Next, we performed ex vivo functional assays on PBMCs originating from patients with gout and controls, which were stimulated with C16 and MSU crystal for 24 h. Cells originating from the control group depicted less unstimulated IL-1Ra release in GG genotype carriers (Fig. 3A) but no differences were observed in patients with gout. However, a significantly lower IL-1Ra production was observed in patients with gout carrying the G allele in response to C16 + MSU crystal stimulation (p = 0,005) (Fig. 3A) and LPS 100 ng (p = 0.04) (Supplementary Fig. 2C), while no differences were present in the control group. IL-1β production in response to C16 + MSU crystal in cells of patients with gout were not significantly associated with genotype, however the IL-1β/IL-1Ra ratio showed significant differences (Fig. 3B). No other statistically significant differences were present in the studied samples (Supplementary Fig. 2A, B). Possibly due to lower numbers or due to a less optimal time point of 24 h, no significant difference in mRNA levels of the IL1RN and IL1B genes was detected in PBMCs of patients with gout exposed for 24 h with the C16 + MSU crystal condition (Fig. 3C).
Fig. 3.
Association of the rs9973741 SNP with ex vivo cytokine production A. Freshly isolated PBMCs originating from gout patients (n = 113) and controls (n = 218) stimulated with RPMI, C16 50 μm + MSU 300ug/ml. After 24 h the supernatants were collected and IL-1Ra (R&D Systems, Minneapolis) was measured. B Concentration of IL-1β measured in the supernatants of PBMCs after stimulation for 24 h. Ratio of IL- 1β and IL-1Ra production in controls and gout patients upon C16/MSU stimulation. The lowest range of detection was 78 pg/ml for IL-1β; 390 pg/ml for IL-1Ra. C mRNA expression level of IL1RN and IL1B in PBMCs stimulated with C16 + MSU 300 ug/mL for 24 h. Graphs depict mean with SD. Kruskal-Wallis and post-hoc analysis p < 0,05
Functional validation of elevated IL-1β release associated to IL1RN rs9973741 in response to C16 + MSU crystal stimulation
As a confirmation of the results presented in our cohort, we investigated the data revealed in the Major et al. study [22] regarding the IL1RN rs9973741 SNP and cytokine production of PBMCs of healthy subjects. For this we used the Human Functional Genomcs Project (http://www.humanfunctionalgenomics.org/), where data from 316 healthy controls originating from the Netherlands (included in the 500FG cohort [32]) were used to test association of the rs9973741 SNP with cytokine production. The IL1RN rs9973741 G allele was associated with higher IL-1β in response to C16 + MSU crystal (Fig. 4A). This effect was specific for C16 + MSU crystal as this association was not observed for other stimuli, e.g. LPS or heat killed Candida albicans (Fig. 4B, C).
Fig. 4.
IL-1β and IL-6 production after 24 h stimulation of PBMCs in vitro. A Freshly isolated PBMCs originating from healthy controls (n = 316) stimulated with C16/MSU crystal 300ug/ml for 24 h. After 24 h the supernatants were collected and IL-1β and IL-6 (R&D Systems, Minneapolis) was measured. B Freshly isolated PBMCs originating from healthy controls (n = 316) stimulated with LPS 100ng for 24 h. After 24 h the supernatants were collected and IL-1β and IL-6 was measured. C Freshly isolated PBMCs originating from healthy controls (n = 316) stimulated with Candida albicans conidia for 24 h. After 24 h the supernatants were collected and IL-1β and IL-6 was measured. The lowest range of detection was 78 pg/ml for IL-1β; 312 pg/ml for IL-6. Graphs depict means with SD. Kruskal-Wallis and post-hoc analysis p < 0,05
Discerning regulatory mechanisms of IL1RN rs9973741
To further elucidate the functional role of our SNP of interest IL1RN rs9973741, we attempted to identify candidate causal variants using haploreg (version 4.2) and regulomeDB and determined that the genetic variants in linkage equilibrium (LD R2 > 0.90) with IL1RN rs9973741 [22] overlap candidate regions of regulatory function (Supplementary Table 1). These elements include DNA accessibility signatures in blood and transcription factor binding sites in blood cell lines (K652 and GM12878) including important immune cell transcription factors IRF1, CEBPB, MTIF, TFE3 and MAFG. Therefore it is possible that the causal variant could be altering the accesibility or transcriptional regulation of the IL1F10 and/or IL1RN, however these candidate variants remain to be functionally tested.
Discussion
Both genetic and environmental factors are known to account for the development of gout [33–36]. For instance, more than 200 urate-associated loci have been identified by genome-wide association studies [37–39]. Genes within the identified loci have been causally implicated in urate homeostasis and transport (e.g. SLC2A9, SLC22A12, ABCG2, SLC22A11, SLC17A1, SLC16A9, PDZK1, GCKR, INHBC, HNF4A, MAF), contributing to risk of gout via their implications for hyperuricemia [17, 40, 41]. Recently, 376 loci were associated to gout [22] and a subset of these genes that mapped under these loci were prioritised to be functionally linked to inflammation in gout. Notably, the signal at the IL1RN-IL1F10 region (encoding for the IL-1Ra and IL-38 proteins) was found to be associated to gout and to altered expression of IL1RN and IL1F10.
Both IL-1Ra and IL-38 are anti-inflammatory cytokines of the IL-1 family. IL-1Ra is a natural antagonist of IL-1 signaling, mainly produced by hepatic cells, though monocytes and macrophages also represent an important source. IL-1β is an important inducer of IL-1Ra production along with being one of the essential upstream inducer of many inflammatory cascades [42]. The balance between IL-1Ra and IL-1β plays an important role in preventing inflammation-related tissue damage [43]. Gout is often described as an IL-1 disease [1, 4], in which IL-1Ra is playing an important inhibitory function, by counterbalancing MSU crystal-induced inflammation [44]. IL-1F10 (IL-38) has a significant role in the immune responses, suppressing inflammatory conditions [45].
Major et al. showed discordant patterns of association for IL1RN expression in different tissues (gout risk allele G associated with increasing expression of IL1RN in testis and decreasing expression in adipose tissue) [22]. Further, the identified signal was not associated with urate levels, emphasising a role in inflammatory regulation in gout and not the control of urate levels. The possible mechanism of how the risk variant at this locus could contribute to progression from asymptomatic hyperuricemia to gout pathogenesis needs further assessment. It is conceivable that epigenetic regulatory mechanisms could be at play to explain the control of gene expression observed in association to this genetic signal, given its position within regulatory elements.
Querying the eQTLGen expression data associated the rs9973741 SNP with altered IL1RN expression also in whole blood. This suggests that circulating blood cells are a relevant system to study this SNP and inflammatory consequences. Furthermore, the IL1RN-IL1F10 region has also been found to associate with circulating markers of inflammation, including IL-1Ra and IL-6 protein levels, in previous GWAS [29–31]. The lead SNP in these GWAS is in LD with the lead gout SNP presented in this paper (IL1RN rs9974741) suggesting that these signals of association “gout, IL-1Ra and IL6” are shared.
In our study, when assessing IL1RN gene expression in unstimulated freshly isolated PBMCs from patients with gout or controls we did not observe an association with the IL1RN rs9973741 SNP. Importantly however, the gout risk allele G was associated to significantly lower concentrations of circulating IL-1Ra in both controls and patients with gout. This is consistent with the other associations for blood cell traits from the UKBB centered on the gout SNP rs9974741 at the IL1RN-IL1F10 region which include monocyte count and monocyte percentage suggesting that IL1RN expression in these alternative tissues alters the composition of monocytes in blood which could contribute to levels of circulating IL-1Ra.
Ex vivo cytokine secretion by freshly isolated PBMCs revealed significantly lower IL-1Ra production in response to C16 + MSU crystal costimulation in patients with gout. In line with the lower IL-1Ra in G allele carriers, the SNP was associated with significantly elevated IL-1β/IL-1Ra ratio in gout patients and in controls. The rise in IL-1β cytokine production in response to C16 + MSU crystals was observed in G-allele carriers among the healthy controls of the 500FG cohort. Our data indicate that the IL1RN rs9973741 variant is associated with differential cytokine production in blood mononuclear cells with possible implications for inflammatory risk in gout progression: the decrease in IL-1Ra circulating protein production in addition to an altered cytokine profile could contribute to elevated IL-1β production by myeloid cells when activated with MSU crystals and synergizing stimuli. This can subsequently mediate the autoinflammatory events characteristic to symptomatic gout.
On the one hand, the downregulation of IL-1Ra in the context of gout was already reported in the literature [46, 47]. On the other hand, in other rheumatic disorders, such as systemic lupus erythematosus (SLE) high IL-1Ra production by monocytes was observed when comparing to controls [48]. Moreover, elevated systemic IL-1Ra concentrations are described in individuals with cardiometabolic risk factors, such as obesity, insulin resistance and type 2 diabetes mellitus [49–51]. These findings show that IL-1Ra is a marker of inflammation (being induced in inflammatory conditions), as well as a potent inhibitor of IL-1R1 signaling. Nevertheless, the severe deficit of IL-1Ra results in life-theatening autoinflammatory disease [52], therefore the association of the rs9973741 SNP with reduced IL-1Ra production is extremely relevant and might contribute to the inflammatory state in gout.
The model of IL-1β/IL-1Ra dysregulation in the pathogenesis of gout has also been evoked in other studies. In PBMCs from healthy donors, urate influences inflammatory responses by causing a shift in the IL-1β/IL-1Ra balance, decreasing IL-1Ra concentrations at both the transcriptional and protein levels, contributing to more robust inflammatory responses upon subsequent stimulation in vitro [20, 21]. Importantly, in a recent proteome-wide association study of serum urate and gout an association between genetically higher levels of IL1Ra and lower odds of gout was observed [29], supporting the results presented in this study.
Some limitations of our research need mentioning. First, the participants involved in the study were all of European descent, which restricts the generalisation of these findings to other ancestries. Another limitation is the cross-sectional design, making causal interpretations of association between IL1RN rs9973741 and inflammation difficult – this variant, while the strongest associated at the locus, could be in linkage disequilibrium with the causal variant. Furthermore, the high inter-individual variability in cytokine data coming from primary cells precludes robust conclusions in some comparisons with moderate sample sizes, and it is obvious that larger cohorts are needed. Nevertheless, this study has the strength of assessing the association of the SNP of interest with IL1-Ra cytokine production at several layers: transcription data together with circulating proteins and ex vivo cytokine measurements in stimulated primary PBMCs of a relatively large number of patients with gout and controls. With respect to variation in IL-38 levels, we report here a small but significant reduction in circulating IL-38. However, due to the lack of expression of IL-38 in PBMCs in our dataset, further variation of IL-38 production in PBMCs functional assays was not possible in this study. Further studies assessing this cytokine in relationship to the rs9973741 SNP may benefit from assessing other tissues where IL-38 is constitutively expressed [53].
In conclusion, using two independent study cohorts and the lead gout SNP, we show that the G allele of the IL1RN rs9973741 variant associates with lower circulating concentrations of IL-1Ra, lower IL-1Ra production in PBMC assays and elevated IL-1β production in PBMCs challenged with C16 + MSU crystals. Our data indicate that the genetic signal that associates with gout at IL1RN-IL1F10 region (or locus) revealed to alter the expression of both IL1RN and IL1F10 resulting in modified cytokine profiles, leading to elevated bioactive IL-1β. Therefore, with this genetic variant, PBMCs are more likely to react aggressively to inflammatory triggers through higher IL-1β release. This enhanced inflammatory state may contribute to the shift from the silent phase of hyperuricemia to the symptomatic phase of gout more promptly upon MSU crystal formation in joints or tissues. As the G allele carriers have a lower threshold for inflammation, it can be speculated that the transition from asymptomatic to symptomatic disease might occur earlier or could be associated with more severe manifestations, and this warrants further assessment in future studies. Hence, the IL1RN rs9973741 G allele could serve as a genetic marker to identify individuals at higher risk of developing gout and might influence future strategies for early intervention in gout management.
Supplementary Information
Additional file 1: Supplementary Fig. 1. Locus Zoom plots for blood cell traits centered on the gout rs9973741 SNP using the UKBB dataset. The IL1RN rs9973741 SNP is labeled in purple. The plot was generated using LocusZoom [23]. Supplementary Fig. 2. IL-6 and IL-1Ra production after 24 h stimulation of PBMCs in vitro A.Freshly isolated PBMCs originating from gout patients (n = 113) and controls (n = 218) stimulated with C16/MSU 300ug/ml for 24 h. After 24 h the supernatants were collected and IL-1β and IL-6 (R&D Systems, Minneapolis) was measured. B. Freshly isolated PBMCs originating from from gout patients (n = 113) and controls (n = 193) stimulated with LPS 100ng for 24 h. After 24 h the supernatants were collected and IL-6 was measured. C. Freshly isolated PBMCs originating from gout patients (n = 113) and controls (n = 218) stimulated with LPS 100ng for 24 h. After 24 h the supernatants were collected and IL-1Ra was measured. The lowest range of detection was 78 pg/ml for IL-1β; 312 pg/ml for IL-6. Graphs depict means+/−SEM. Kruskal-Wallis and post-hoc analysis p < 0,01.
Additional file 2: Supplementary Table 1. Annotations of potential regulatory SNPs in regulomeDB and Haploreg.
Acknowledgements
This work was supported by a Competitiveness Operational Programme grant of the Romanian Ministry of European Funds (P_37_762, MySMIS 103587) and by a Romania’s National Recovery and Resilience Plan grant of the Romanian Ministry of Investments and European Projects (PNRR-III-C9-2022-I8, CF 85 / 15.11.2022). O.I. Gaal was supported by a grant for doctoral research projects (2462/22) of the University of Medicine and Pharmacy „Iuliu Hațieganu”, Cluj-Napoca, Romania.
Authors’ contributions
OIG, ML, VN, GC, MB, DMG performed the experiments and acquired the data. OIG, ML, VN, ZZ, YL analyzed the data. IH, CP, SR provided patient material and data. TRM, TOC, and LABJ designed the work. OIG, TOC, and LABJ drafted the manuscript. All authors contributed to data interpretation, revised the manuscript, and approved the final version.
Funding
This work was supported by a Competitiveness Operational Programme grant of the Romanian Ministry of European Funds (P_37_762, MySMIS 103587) and by a Romania’s National Recovery and Resilience Plan grant of the Romanian Ministry of Investments and European Projects (PNRR-III-C9-2022-I8, CF 85 / 15.11.2022). O.I. Gaal was supported by a grant for doctoral research projects (2462/22) of the University of Medicine and Pharmacy „Iuliu Hațieganu”, Cluj-Napoca, Romania.
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The patient study was approved by the Ethical Committee of the „Iuliu Hațieganu” University of Medicine and Pharmacy, Cluj-Napoca (approval no. 425/2016). Subjects were enrolled after written informed consent.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Dalbeth N, Gosling AL, Gaffo A, Abhishek A, Gout. Lancet. 2021;397(10287):1843–55. [DOI] [PubMed] [Google Scholar]
- 2.Mattiuzzi C, Lippi G. Recent updates on worldwide gout epidemiology. Clin Rheumatol. 2020;39(4):1061–3. [DOI] [PubMed]
- 3.Kuo CF, Grainge MJ, Zhang W, Doherty M. Global epidemiology of gout: prevalence, incidence and risk factors. Nat Rev Rheumatol. 2015;11(11):649–62. [DOI] [PubMed]
- 4.Dalbeth N, Choi HK, Joosten LAB, Khanna PP, Matsuo H, Perez-Ruiz F, et al. Gout. Nat Rev Dis Primers. 2019;5(1):69. [DOI] [PubMed] [Google Scholar]
- 5.Narang RK, Dalbeth N. Pathophysiology of gout. Semin Nephrol. 2020;40(6):550–63. [DOI] [PubMed] [Google Scholar]
- 6.Klück V, Liu R, Joosten LAB. The role of interleukin-1 family members in hyperuricemia and gout. Joint Bone Spine. 2021;88(2):105092. [DOI] [PubMed] [Google Scholar]
- 7.Arena WP, Malyak M, Guthridge CJ, Gabay C. Interleukin-1 receptor antagonist: role in biology. Annu Rev Immunol. 1998;16:27–55. [DOI] [PubMed] [Google Scholar]
- 8.Frühbeck G, Catalán V, Ramírez B, Valentí V, Becerril S, Rodríguez A, et al. Serum levels of IL-1 RA increase with obesity and type 2 diabetes in relation to adipose tissue dysfunction and are reduced after bariatric surgery in parallel to Adiposity. J Inflamm Res. 2022;15(February):1331–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Mantovani A, Dinarello CA, Molgora M, Garlanda C. IL-1 and related cytokines in innate and adaptive immunity in health and disease. Immunity. 2019;50(4):778. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Bensen JT, Dawson PA, Mychaleckyj JC, Bowden DW. Identification of a novel human cytokine gene in the interleukin gene cluster on chromosome 2q12-14. J Interferon Cytokine Res. 2001;21(11):899–904. [DOI] [PubMed] [Google Scholar]
- 11.Xu WD, Huang AF. Role of interleukin-38 in chronic inflammatory diseases: a comprehensive review. Front Immunol. 2018;9:9(JUN). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Renaudin F, Orliaguet L, Castelli F, Fenaille F, Prignon A, Alzaid F, et al. Gout and pseudo-gout-related crystals promote GLUT1-mediated glycolysis that governs NLRP3 and interleukin-1β activation on macrophages. Ann Rheum Dis. 2020;79(11):1506–14. [DOI] [PubMed] [Google Scholar]
- 13.Vazirpanah N, Ottria A, Van Der Linden M, Wichers CGK, Schuiveling M, Van Lochem E, et al. MTOR inhibition by metformin impacts monosodium urate crystal-induced inflammation and cell death in gout: a prelude to a new add-on therapy? Ann Rheum Dis. 2019;78(5):663–71. [DOI] [PubMed] [Google Scholar]
- 14.Martinon F, Pétrilli V, Mayor A, Tardivel A, Tschopp J. Gout-associated uric acid crystals activate the NALP3 inflammasome. Nature. 2006;440(7081):237–41. [DOI] [PubMed]
- 15.Sandoval-Plata G, Morgan K, Abhishek A. Variants in urate transporters, ADH1B, GCKR and MEPE genes associate with transition from asymptomatic hyperuricaemia to gout: results of the first gout versus asymptomatic hyperuricaemia GWAS in caucasians using data from the UK Biobank. Ann Rheum Dis. 2021;80(9):1220–6. [DOI] [PubMed] [Google Scholar]
- 16.Lin CY, Chang YS, Liu TY, Huang CM, Chung CC, Chen YC, et al. Genetic contributions to female gout and hyperuricaemia using genome-wide association study and polygenic risk score analyses. Rheumatology. 2023;62(2):638–46. [DOI] [PubMed] [Google Scholar]
- 17.Kawamura Y, Nakaoka H, Nakayama A, Okada Y, Yamamoto K, Higashino T, et al. Genome-wide association study revealed novel loci which aggravate asymptomatic hyperuricaemia into gout. Ann Rheum Dis. 2019;78(10):1430. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Sumpter NA, Takei R, Leask MP, Reynolds RJ, Merriman TR. Genetic association studies of the progression from hyperuricaemia to gout. Rheumatology (Oxford). 2022;61(6):e139–40. [DOI] [PubMed] [Google Scholar]
- 19.Major TJ, Takei R, Matsuo H, Leask MP, Topless RK, Shirai Y, et al. A genome-wide association analysis of 2,622,830 individuals reveals new pathogenic pathways in gout. medRxiv. 2022;2022.11.26.22281768.
- 20.Badii M, Gaal OI, Cleophas MC, Klück V, Davar R, Habibi E, et al. Urate-induced epigenetic modifications in myeloid cells. Arthritis Res Ther. 2021;23(1):1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Crișan TO, Cleophas MC, Oosting M, Lemmers H, Toenhake-Dijkstra H, Netea MG, Jansen TL, Joosten LA. Soluble uric acid primes TLR-induced proinflammatory cytokine production by human primary cells via inhibition of IL-1Ra. Ann Rheum Dis. 2016;75(4):755–62. [DOI] [PubMed]
- 22.Major TJ, Takei R, Matsuo H, Leask MP, Sumpter NA, Topless RK, et al. A genome-wide association analysis reveals new pathogenic pathways in gout. Nat Genet. 2024;56(11):2392–406. [DOI] [PubMed]
- 23.Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics. 2011;27(13):2336–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Lin SH, Brown DW, Machiela MJ. LDtrait: an online tool for identifying published phenotype associations in linkage disequilibrium. Cancer Res. 2020;80(16):3443–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Machiela MJ, Chanock SJ. LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. Bioinformatics. 2015;31(21):3555–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Consortium G. The GTEx Consortium atlas of genetic regulatory effects across human tissues. The GTEx Consortium* Downloaded from. 2021. Available from: http://science.sciencemag.org/.
- 27.Võsa U, Claringbould A, Westra HJ, Bonder MJ, Deelen P, Zeng B, et al. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nat Genet. 2021;53(9):1300–10. 10.1038/s41588-021-00913-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013;45(6):580–5. [DOI] [PMC free article] [PubMed]
- 29.Zhang J, Dutta D, Köttgen A, Tin A, Schlosser P, Grams ME, et al. Plasma proteome analyses in individuals of European and African ancestry identify cis-pQTLs and models for proteome-wide association studies. Nat Genet. 2022;54(5):593–602. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Astle WJ, Elding H, Jiang T, Allen D, Ruklisa D, Mann AL, et al. The allelic landscape of human blood cell trait variation and links to common complex disease. Cell. 2016;167(5):1415-1429.e19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Tekola Ayele F, Doumatey A, Huang H, Zhou J, Charles B, Erdos M, et al. Genome-wide associated loci influencing interleukin (IL)-10, IL-1Ra, and IL-6 levels in African Americans. Immunogenetics. 2012;64(5):351–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Ter Horst R, Jaeger M, Smeekens SP, Oosting M, Swertz MA, Li Y, et al. Host and environmental factors influencing individual human cytokine responses. Cell. 2016;167(4):1111-1124.e13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Matsuo H, Takada T, Ichida K, Nakamura T, Nakayama A, Ikebuchi Y, et al. Common defects of ABCG2, a high-capacity urate exporter, cause gout: a function-based genetic analysis in a Japanese population. Sci Transl Med. 2009;1(5):5ra11. [DOI] [PubMed] [Google Scholar]
- 34.Li Z, Zhou Z, Hou X, Lu D, Yuan X, Lu J, et al. Replication of gout/urate concentrations GWAS susceptibility loci associated with gout in a Han Chinese population. Sci Rep. 2017;7(1):4094. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Boocock J, Leask M, Okada Y, Matsuo H, Kawamura Y, Shi Y, et al. Genomic dissection of 43 serum urate-associated loci provides multiple insights into molecular mechanisms of urate control. Hum Mol Genet. 2020. [DOI] [PubMed]
- 36.Takei R, Sumpter NA, Phipps-Green A, Cadzow M, Topless RK, Reynolds RJ, Merriman TR. Correspondence on 'Variants in urate transporters, ADH1B, GCKR and MEPE genes associated with transition from asymptomatic hyperuricaemia to gout: results of the first gout versus asymptomatic hyperuricaemia GWAS in Caucasians using data from the UK Biobank'. Ann Rheum Dis. 2023;82(7):e174. [DOI] [PubMed]
- 37.Köttgen A, Albrecht E, Teumer A, Vitart V, Krumsiek J, Hundertmark C, et al. Genome-wide association analyses identify 18 new loci associated with serum urate concentrations. Nat Genet. 2013;45(2):145–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Tin A, Marten J, Halperin Kuhns VL, Li Y, Wuttke M, Kirsten H, et al. Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels. Nat Genet. 2019. [DOI] [PMC free article] [PubMed]
- 39.Major TJ, Dalbeth N, Stahl EA, Merriman TR. An update on the genetics of hyperuricaemia and gout. Nat Rev Rheumatol. 2018;14(6):341–53. [DOI] [PubMed] [Google Scholar]
- 40.Matsuo H, Yamamoto K, Nakaoka H, Nakayama A, Sakiyama M, Chiba T, et al. Genome-wide association study of clinically defined gout identifies multiple risk loci and its association with clinical subtypes. Ann Rheum Dis. 2016;75(4):652. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Nakayama A, Nakaoka H, Yamamoto K, Sakiyama M, Shaukat A, Toyoda Y, et al. GWAS of clinically defined gout and subtypes identifies multiple susceptibility loci that include urate transporter genes. Ann Rheum Dis. 2017;76(5):869. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Dinarello CA. Immunological and inflammatory functions of the Interleukin-1 family. Annu Rev Immunol. 2009;27(1):519–50. [DOI] [PubMed] [Google Scholar]
- 43.Arend WP, Gabay C. Physiologic role of interleukin-1 receptor antagonist. Arthritis Res. 2000;2(4):245–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.ElSayed S, Jay GD, Cabezas R, Qadri M, Schmidt TA, Elsaid KA. Recombinant human proteoglycan 4 regulates phagocytic activation of monocytes and reduces IL-1β secretion by Urate Crystal stimulated gout PBMCs. Front Immunol. 2021;12(December):1–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Graaf DM De, Jaeger M, Den ICL Van, Mercurio L, Madonna S, Rutten JHW, et al. Reduced concentrations of the B cell cytokine interleukin 38 are associated with cardiovascular disease risk in overweight subjects. 2021:662–71. [DOI] [PMC free article] [PubMed]
- 46.Roberge CJ, de Médicis R, Dayer JM, Rola-Pleszczynski M, Naccache PH, Poubelle PE. Crystal-induced neutrophil activation. V. Differential production of biologically active IL-1 and IL-1 receptor antagonist. J Immunol. 1994;152(11):5485–94. [PubMed] [Google Scholar]
- 47.Crişan TO, Cleophas MCP, Novakovic B, Erler K, Van De Veerdonk FL, Stunnenberg HG, et al. Uric acid priming in human monocytes is driven by the AKT-PRAS40 autophagy pathway. Proc Natl Acad Sci U S A. 2017;114(21):5485–90. [DOI] [PMC free article] [PubMed]
- 48.Italiani P, Manca ML, Angelotti F, Melillo D, Pratesi F, Puxeddu I, et al. IL-1 family cytokines and soluble receptors in systemic lupus erythematosus. Arthritis Res Ther. 2018;20(1):1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Meier CA, Bobbioni E, Gabay C, Assimacopoulos-Jeannet F, Golay A, Dayer JM. IL-1 receptor antagonist serum levels are increased in human obesity: a possible link to the resistance to leptin? J Clin Endocrinol Metab. 2002;87(3):1184–8. [DOI] [PubMed] [Google Scholar]
- 50.Abdullah AR, Hasan HA, Raigangar VL. Analysis of the relationship of leptin, high-sensitivity C-reactive protein, adiponectin, insulin, and uric acid to metabolic syndrome in lean, overweight, and obese young females. Metab Syndr Relat Disord. 2009;7(1):17–22. [DOI] [PubMed] [Google Scholar]
- 51.Volarevic V, Al-Qahtani A, Arsenijevic N, Pajovic S, Lukic ML. Interleukin-1 receptor antagonist (IL-1Ra) and IL-1Ra producing mesenchymal stem cells as modulators of diabetogenesis. Autoimmunity. 2010;43(4):255–63. [DOI] [PubMed] [Google Scholar]
- 52.Aksentijevich I, Masters SL, Ferguson PJ, Dancey P, Frenkel J, van Royen-Kerkhoff A, et al. An autoinflammatory disease with deficiency of the interleukin-1-receptor antagonist. N Engl J Med. 2009;360(23):2426–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.de Graaf DM, Teufel LU, Joosten LAB, Dinarello CA. Interleukin-38 in health and disease. Cytokine. 2022;152: 155824. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Additional file 1: Supplementary Fig. 1. Locus Zoom plots for blood cell traits centered on the gout rs9973741 SNP using the UKBB dataset. The IL1RN rs9973741 SNP is labeled in purple. The plot was generated using LocusZoom [23]. Supplementary Fig. 2. IL-6 and IL-1Ra production after 24 h stimulation of PBMCs in vitro A.Freshly isolated PBMCs originating from gout patients (n = 113) and controls (n = 218) stimulated with C16/MSU 300ug/ml for 24 h. After 24 h the supernatants were collected and IL-1β and IL-6 (R&D Systems, Minneapolis) was measured. B. Freshly isolated PBMCs originating from from gout patients (n = 113) and controls (n = 193) stimulated with LPS 100ng for 24 h. After 24 h the supernatants were collected and IL-6 was measured. C. Freshly isolated PBMCs originating from gout patients (n = 113) and controls (n = 218) stimulated with LPS 100ng for 24 h. After 24 h the supernatants were collected and IL-1Ra was measured. The lowest range of detection was 78 pg/ml for IL-1β; 312 pg/ml for IL-6. Graphs depict means+/−SEM. Kruskal-Wallis and post-hoc analysis p < 0,01.
Additional file 2: Supplementary Table 1. Annotations of potential regulatory SNPs in regulomeDB and Haploreg.
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.