Identification of a de novo NLRP3 gene variation in an Italian Behçet syndrome patient.

A novel nonsynonymous variation of NLRP3 was identified in an Italian patient with Behçet syndrome using both bioinformatics and molecular methods. This variation was a thymine to guanine polymorphism responsible for the isoleucine to serine amino acid change at position 348. The novel variation was predicted to be a pathogenic allele.

The relationship between HLA-B*51 subtypes, clinical manifestations and severity of Behçet's syndrome: a large Italian cohort study.

Objectives: Behçet's syndrome (BS) is a chronic multisystemic inflammatory disorder of unclear aetiology. The predominant BS susceptibility locus was identified within HLA-B*51. HLA-B*51 subtypes were previously studied as disease susceptibility markers. Few data are now available about the relationship between B*51 subtypes and clinical phenotype. The aim of this study was to genotype HLA-B*51 subtypes in a series of Italian BS patients and to test the association with clinical manifestations and disease severity (Krause's index). Methods: HLA-B*51 subtype genotyping for 63 alleles (B*51:01-B*51:63) was performed by PCR after DNA extraction from whole blood of BS patients. The correlation of disease clinical manifestations and severity (Krause's index) with the HLA-B*51 allele and its subtypes was analysed. Results: We enrolled 241 (140 male and 101 female) BS patients, and HLA-B*51 frequency was 62.7% (151 of 241). One hundred and eight of the HLA-B*51-positive patients carried the B*51:01 subtype (108 of 151, 71.5%), 39 of 151 (25.8%) the B*51:08 subtype, 2 of 151 (1.3%) the B*51:02 subtype, 1 of 151 (0.7%) the B*51:05 subtype, and 1 of 151 (0.7%) the B*51:07 subtype. We found that ocular involvement was statistically associated with HLA-B*51 positivity and with B*51:01 and B*51:08 subtypes (P < 0.05). We also found that disease severity was higher in HLA-B*51-positive patients than in negative patients, but without statistical significance (median Krause's index 5.1 vs 4.1, P > 0.05). Conclusion: Here, we confirm a high frequency of the HLA-B*51 allele in our group of BS patients. B*51:01 and B*51:08 were found to be the most common subtypes, and an association of both subtypes with ocular involvement was also underlined.

TNFα rs1800629 Polymorphism and Response to Anti-TNFα Treatment in Behçet Syndrome: Data from an Italian Cohort Study.

Tumor Necrosis Factor-alpha (TNFα) rs1800629 (-308G>A) is a single nucleotide polymorphism (SNP) related to variable responses to anti-TNFα therapy. This therapy is efficient in severe and refractory manifestation of Behçet syndrome (BS), an auto-inflammatory systemic vasculitis. We investigated (1) the association between rs1800629 genotypes and responses to therapy and (2) the correlation between SNP and clinical patterns in a cohort of 74 BS Italian patients receiving anti-TNFα therapy with a follow-up of at least 12 months. The rs1800629 was genotyped through amplification, direct sequencing and bioinformatics analyses. The rs1800629 GG and GA genotypes were assessed as predictors of outcomes dividing the patients between therapy responders and non-responders. The rs1800629 GG and GA genotypes were found, respectively, in 59/74 (79.7%) and 15/74 BS patients (21.3%) (p < 0.05). We identified 16/74 (21.9%) non-responder patients, of which 9/16 (56.3%) showed the GG genotype and 7/16 (43.7%) the GA genotype. A total of 50/58 (86.2%) responder patients showed the GG genotype, and 8/58 (13.8%) the GA genotype (p < 0.05). The percentage of non-responder females (68.8%) was significantly higher than non-responder males (31.2%) (p < 0.05). No correlation between SNP and clinical patterns was observed. To successfully include rs1800629 as a predictive biomarker of TNFα inhibitor response, genome-wide association studies in larger, well-characterised cohorts are required.

Validity of Machine Learning in Predicting Giant Cell Arteritis Flare After Glucocorticoids Tapering.

Background: Inferential statistical methods failed in identifying reliable biomarkers and risk factors for relapsing giant cell arteritis (GCA) after glucocorticoids (GCs) tapering. A ML approach allows to handle complex non-linear relationships between patient attributes that are hard to model with traditional statistical methods, merging them to output a forecast or a probability for a given outcome. Objective: The objective of the study was to assess whether ML algorithms can predict GCA relapse after GCs tapering. Methods: GCA patients who underwent GCs therapy and regular follow-up visits for at least 12 months, were retrospectively analyzed and used for implementing 3 ML algorithms, namely, Logistic Regression (LR), Decision Tree (DT), and Random Forest (RF). The outcome of interest was disease relapse within 3 months during GCs tapering. After a ML variable selection method, based on a XGBoost wrapper, an attribute core set was used to train and test each algorithm using 5-fold cross-validation. The performance of each algorithm in both phases was assessed in terms of accuracy and area under receiver operating characteristic curve (AUROC). Results: The dataset consisted of 107 GCA patients (73 women, 68.2%) with mean age ( ± SD) 74.1 ( ± 8.5) years at presentation. GCA flare occurred in 40/107 patients (37.4%) within 3 months after GCs tapering. As a result of ML wrapper, the attribute core set with the least number of variables used for algorithm training included presence/absence of diabetes mellitus and concomitant polymyalgia rheumatica as well as erythrocyte sedimentation rate level at GCs baseline. RF showed the best performance, being significantly superior to other algorithms in accuracy (RF 71.4% vs LR 70.4% vs DT 62.9%). Consistently, RF precision (72.1%) was significantly greater than those of LR (62.6%) and DT (50.8%). Conversely, LR was superior to RF and DT in recall (RF 60% vs LR 62.5% vs DT 47.5%). Moreover, RF AUROC (0.76) was more significant compared to LR (0.73) and DT (0.65). Conclusions: RF algorithm can predict GCA relapse after GCs tapering with sufficient accuracy. To date, this is one of the most accurate predictive modelings for such outcome. This ML method represents a reproducible tool, capable of supporting clinicians in GCA patient management.

A First Step for the Molecular Characterization of Neurological Involvement of Behçet Syndrome: an Italian Pivotal Study.

Behçet syndrome (BS) is a vasculitis characterized by several clinical manifestations including the rare neurological involvement (neuro-BS, NBS). The aim of our pivotal study was to investigate the mutational status of several inflammation-related genes in a cohort of Italian patients with and without the neurological involvement (20 NBS vs 40 no-NBS patients). The preliminary in silico single nucleotide polymorphism (SNP) selection and primer design were performed by NCBI Primer-Blast tool. Genomic DNA was isolated and amplified using PCR. PCR amplicons were sequenced and bioinformatically analysed. Twelve tagSNPs were selected and genotyped: ERAP1 rs30187, rs17482078, and rs27044; IL10 rs1800872 and rs1518111, IL12A rs17810546, IL23R rs17375018, IL23R-IL12RB2 rs924080, STAT4 rs7572482, CCR1 rs7616215, KLRC4 rs2617170, and UBAC2 rs3825427. ERAP1 and IL23R SNPs showed statistically significant higher frequencies in NBS group than no-NBS. ERAP1 rs30187 AA was more common in no-NBS patients (20.0% NBS vs 47.5% no-NBS; p < 0.05), while rs17482078 GA frequency was higher in NBS patients (55.0% NBS vs 22.5% no-NBS; p < 0.05, OR: 4.21). IL23R rs17375018 GG was more frequent in NBS group (65.0% NBS vs 40.0% no-NBS; p < 0.05), according to a previous finding. No other statistically significant differences were found. In conclusion, ERAP1 and IL23R SNPs were found associated with neurological involvement of BS. Additional and larger analyses were required to verify our preliminary findings.

Correlation of Tumor Necrosis Factor-α -308G>A Polymorphism with Susceptibility, Clinical Manifestations, and Severity in Behçet Syndrome: Evidences from an Italian Genetic Case-Control Study.

To investigate the association between a functional drug-response tumor necrosis factor (TNF)α gene polymorphism (at the positions of -308; rs1800629; NG_007462.1:g.4682G>A) and both disease susceptibility and clinical manifestations in a cohort of 130 Italian patients with Behçet syndrome (BS). A group of 100 ethnically, age, and gender matched healthy controls (HC) was also recruited. Genotyping was performed using molecular (amplification and direct sequencing) and in silico methods. The genotype distribution of BS patients and HC underlined a lower percentage of wild-type GG genotype in BS patients versus HC (106/130 patients, 81.5% vs. 91/100 HC, 91%; p < 0.05), while the heterozygous genotype (GA) was identified in 24/130 patients (18.5%) versus 9/100 HC (9%) (p < 0.05). GA genotype was significantly associated with the disease (odds ratio = 2.29, 95% confidence interval 1.01-5.18). No significant association was recognized between the single nucleotide polymorphism (SNP) and the BS clinical manifestations, as well as with disease severity (Krause's index). We found statistically significant higher frequency of TNFα rs1800629 GA genotype in patients than in controls. No significant association was recognized between the polymorphism and the clinical parameters, as well as between the SNP and the disease severity. Our data need to be confirmed in larger cohort of patients and matched controls.

From structure to function for the characterization of ERAP1 active site in Behçet syndrome. A novel polymorphism associated with known gene variations.

INTRODUCTION: ERAP1 has been recently proposed as risk marker of Behçet syndrome (BS). Gene single nucleotide polymorphisms (SNPs) could affect the enzymatic activity and the conserved active site is pivotal for the aminopeptidase function. This study aims to characterize the ERAP1 active site in a cohort of BS patients vs healthy controls (HC) integrating genomics, transcriptomics and bioinformatics approach. MATERIALS AND METHODS: We recruited 109 consecutive Italian BS patients (63M:46 F; mean age: 45.07 ± 12.28 years) and 106 matched HC (55M:51 F; mean age: 42.57 ± 12.29 years). DNA was isolated and amplified using PCR with home made-primer pairs. PCR products were directly sequenced and computational analyses were performed to search active site SNPs (NCBI-BlastN tool), to predict SNPs functional effect (PolyPhen-2 software) and to obtain protein 3D modelling (Protean3D software). In a second phase of analysis, RNA was extracted and reverse transcribed. Quantitative Real-Time PCR (qPCR) was performed to assess ERAP1 mRNA level in presence (target) and in absence (control) of gene polymorphisms. The Fold change was calculated for the relative quantification of gene expression. RESULTS: A novel coding variation (NG_027839.1:g.25637 T > G; NP_057526.3:p.Phe360Cys, HGSV nomenclature) was found in heterozygosity state in 5/109 BS patients (4.59 % of cases) and none of HC. It was recognized in association with rs2287987, rs30187, rs17482078, and rs27044 BS-related polymorphisms for 4 out of 5 patients. All patients carrying the novel SNP were HLA-B*51-positive. The novel SNP was released in GenBank database with MK140632.1 ID. The SNP was predicted to be damaging and resides within the Zn-binding HEXXH(X)18E region of the active site, changing the structurally conserved region for the amminopeptidase function. In fact, the change in energy (ΔE) score between wild-type and SNP-containing protein showed a less stable protein in presence of p.Cys360 (ΔE:3.584) (Protean3D prediction). Preliminary qPCR results underlined a significant difference in fold change value when target and control values were compared (p < 0.05), suggesting a reduced expression of ERAP1 mRNA in presence of the novel SNP. CONCLUSIONS: Our study strengthens the association between ERAP1 and BS. The most significant point was the localization of the novel p.Phe360Cys SNP within the Zn-binding region of protein active site that was predicted to affect its function, causing protein destabilization. Our findings need to be tested in larger genetic studies.

Genotyping of Italian patients with Behçet syndrome identified two novel ERAP1 polymorphisms using sequencing-based approach.

The endoplasmic reticulum aminopeptidase protein 1 gene (ERAP1) is related to several human diseases, including Behçet syndrome (BS), a multisystemic disorder with unknown etiology. ERAP1 is involved in immune response and its role can be influenced by gene single nucleotide variations (SNVs). We genotyped the ERAP1 whole structure in 50 consecutive BS patients and 50 ethnically-matched healthy controls using both bioinformatics and molecular methodologies. We identified two novel heterozygous missense SNVs of ERAP1 exon3 responsible for the p.Glu183Val and p.Phe199Ser changes. The first variation was recognized in 7/50 (14%) BS patients and involved the substrate binding site (p.Glu183) required for the anchorage of the peptide N-terminal group. The SNV was predicted to be a damaging variation, as well as the p.Phe199Ser substitution (PolyPhen-2 and SIFT on line software). 3D protein structure prediction showed a change in energy score when the wild-type and the variant states were compared, probably influencing the substrate binding and the protein folding. The first variation was associated to a more stable protein chain, while the second polymorphism was related to a less stable protein chain. Our data need to be tested in larger genetic studies.

Distribution of rs17482078 and rs27044 ERAP1 polymorphisms in a group of Italian Behçet's syndrome patients: a preliminary case-control study.

The Endoplasmic reticulum aminopeptidase protein 1 (ERAP1) trims N-terminal amino acids from epitope precursors for Major Histocompatibility Complex class I presentation. Genome-wide association studies demonstrated that ERAP1 gene single nucleotide polymorphisms (SNPs) are associated with Behçet's syndrome (BS). This study was conducted on the two most consistently BS-associated ERAP1 polymorphisms, rs17482078 (NG_027839.1:g.35983G>A) and rs27044 (NG_027839.1:g.35997C>G) to analyse their distribution in 55 Italian BS patients and 65 ethnically matched controls (healthy controls, HC) and to test their association with BS risk. SNPs were detected by isolation, amplification of genomic DNA and direct sequencing. SNPs functional effects were predicted by bioinformatics software. The odds ratio (OR) with 95% confidence intervals was calculated to assess the strength of BS association for genotypes and alleles, also validated by logistic regression (LR). LR was used to test the association between both SNPs and patients HLA genetic data. Bonferroni correction was also applied. Comparing patients and controls, we found a significant higher frequency of rs17482078 A allele (32.73% BS vs 17.69% HC, p = 0.007) and AA genotype (18.18% BS vs 0% HC; p = 0.0003) and rs27044 G allele (63.64% BS vs 46.92% HC; p = 0.0096) in BS group after Bonferroni correction. No association was found between HLA-B*51 and both ERAP1 SNPs. Although preliminary, our data show a stronger association of rs17482078 with BS compared to rs27044 by means of case-control genetic analysis and bioinformatics prediction of protein structure change. A larger series of patients and controls is required to confirm our preliminary findings.