Gingival lymphatic malformation. An atypical case report

Lymphatic malformations are a rare pathology that presents a highly variable clinical expression. Intraorally, it mainly affects the dorsum of the tongue. The objective of this work is to present a case of lymphatic malformation in an atypical location. A 20-year-old male who attended the clinic for multiple vesicular lesion in attached gingiva, asymptomatic and of unknown evolution. Removal of the lesion and subsequent histological analysis were performed, which showed a microcystic lymphatic vascular lesion. Immunohistochemistry for D2-40 was performed, which corroborated the lymphatic origin of the lesion. At 6 months, no recurrence of the lesion was recognized. Clinicians should include lymphatic malformations in the differential diagnosis of multiple vesicular lesions. Knowing the oral manifestations of this entity is essential for its proper diagnosis and clinical management

Clinicopathological and prognostic characterization of oral lichenoid disease and its main subtypes : a series of 384 cases

To clinicopathologically characterize the diagnosis of oral lichenoid disease (OLD) and its main subtypes: oral lichen planus (OLP) and oral lichenoid lesion (OLL), in order to correctly asses their prognosis. Ambispective cohort study of 384 patients with diagnosis of OLD, based on pre-established clinical and histopathological criteria. We have analysed 272 (70.8%) women and 112 (29.2%), whose mean age was 57.1+/-11.8 years (range 21-90); minimum follow-up time was 36 months. A specific protocol was designed for this study, where we gathered the data of each patient, including malignant transformation. OLP was diagnosed in 229 cases (77.9%) and OLL in 85 (22.1%). Tobacco consumption was found in 20.3% of the patients and alcohol intake in 41.1%. Liver pathology was present in 10.7% of the cases, thyroid pathology in 11.5%, arterial hypertension in 15.6%, diabetes mellitus in 7.6%, psycho-emotional disorders in 33.3%, skin involvement in 12% and genital involvement in 4.9%. Ten patients (2.6%) developed an oral squamous cell carcinoma, 5 (1.7%) with OLP and 5 (5.9%) with OLL. OLD is a potentially malignant disorder of the oral mucosa which has to be correctly diagnosed as either OLP or OLL, since the risk of malignancy of these subtypes is significantly different

Moderate-High Disease Activity in Patients with Recent-Onset Psoriatic Arthritis-Multivariable Prediction Model Based on Machine Learning

The aim was to identify patient- and disease-related characteristics predicting moderate-to-high disease activity in recent-onset psoriatic arthritis (PsA). We performed a multicenter observational prospective study (2-year follow-up, regular annual visits) in patients aged ≥18 years who fulfilled the CASPAR criteria and had less than 2 years since the onset of symptoms. The moderate-to-high activity of PsA was defined as DAPSA > 14. We trained a logistic regression model and random forest-type and XGBoost machine learning algorithms to analyze the association between the outcome measure and the variables selected in the bivariate analysis. The sample comprised 158 patients. At the first follow-up visit, 20.8% of the patients who attended the clinic had a moderate-to-severe disease. This percentage rose to 21.2% on the second visit. The variables predicting moderate-high activity were the PsAID score, tender joint count, level of physical activity, and sex. The mean values of the measures of validity of the machine learning algorithms were all high, especially sensitivity (98%; 95% CI: 86.89-100.00). PsAID was the most important variable in the prediction algorithms, reinforcing the convenience of its inclusion in daily clinical practice. Strategies that focus on the needs of women with PsA should be considered

A genome-wide association study suggests the HLA Class II region as the major susceptibility locus for IgA vasculitis.

The genetic component of Immunoglobulin-A (IgA) vasculitis is still far to be elucidated. To increase the current knowledge on the genetic component of this vasculitis we performed the first genome-wide association study (GWAS) on this condition. 308 IgA vasculitis patients and 1,018 healthy controls from Spain were genotyped by Illumina HumanCore BeadChips. Imputation of GWAS data was performed using the 1000 Genomes Project Phase III dataset as reference panel. After quality control filters and GWAS imputation, 285 patients and 1,006 controls remained in the datasets and were included in further analysis. Additionally, the human leukocyte antigen (HLA) region was comprehensively studied by imputing classical alleles and polymorphic amino acid positions. A linkage disequilibrium block of polymorphisms located in the HLA class II region surpassed the genome-wide level of significance (OR = 0.56, 95% CI = 0.46-0.68). Although no polymorphic amino acid positions were associated at the genome-wide level of significance, P-values of potential relevance were observed for the positions 13 and 11 of HLA-DRB1 (P = 6.67E-05, P = 1.88E-05, respectively). Outside the HLA, potential associations were detected, but none of them were close to the statistical significance. In conclusion, our study suggests that IgA vasculitis is an archetypal HLA class II disease

Role of the IL33 and IL1RL1 pathway in the pathogenesis of Immunoglobulin A vasculitis

Cytokines signalling pathway genes are crucial factors of the genetic network underlying the pathogenesis of Immunoglobulin-A vasculitis (IgAV), an inflammatory vascular condition. An influence of the interleukin (IL)33- IL1 receptor like (IL1RL)1 signalling pathway on the increased risk of several immune-mediated diseases has been described. Accordingly, we assessed whether the IL33-IL1RL1 pathway represents a novel genetic risk factor for IgAV. Three tag polymorphisms within IL33 (rs3939286, rs7025417 and rs7044343) and three within IL1RL1 (rs2310173, rs13015714 and rs2058660), that also were previously associated with several inflammatory diseases, were genotyped in 380 Caucasian IgAV patients and 845 matched healthy controls. No genotypes or alleles differences were observed between IgAV patients and controls when IL33 and IL1RL1 variants were analysed independently. Likewise, no statistically significant differences were found in IL33 or IL1RL1 genotype and allele frequencies when IgAV patients were stratified according to the age at disease onset or to the presence/absence of gastrointestinal (GI) or renal manifestations. Similar results were disclosed when IL33 and IL1RL1 haplotypes were compared between IgAV patients and controls and between IgAV patients stratified according to the clinical characteristics mentioned above. Our results suggest that the IL33-IL1RL1 signalling pathway does not contribute to the genetic network underlying IgAV.Acknowledgements: We are indebted to the patients and healthy controls for their essential collaboration to this study. We also thank the National DNA Bank Repository (Salamanca) for supplying part of the control samples. This study was supported by European Union FEDER funds and `Fondo de Investigaciones Sanitarias´ (Grant PI18/00042) from ‘Instituto de Salud Carlos III’ (ISCIII, Health Ministry, Spain). DP-P is a recipient of a Río Hortega programme fellowship from the ISCIII, co-funded by the European Social Fund (ESF, `Investing in your future´) (Grant Number CM20/00006). SR-M is supported by funds of the RETICS Program (RD16/0012/0009) (ISCIII, cofunded by the European Regional Development Fund (ERDF)). VP-C is supported by a pre-doctoral grant from IDIVAL (PREVAL 18/01). BA-M is a recipient of a `López Albo´ Post-Residency Programme funded by Servicio Cántabro de Salud. LL-G is supported by funds from IDIVAL (INNVAL20/06). OG is staff personnel of Xunta de Galicia (Servizo Galego de Saude (SERGAS)) through a research-staff stabilization contract (ISCIII/SERGAS) and his work is funded by ISCIII and the European Union FEDER fund (Grant Numbers RD16/0012/0014 (RIER) and PI17/00409). He is beneficiary of project funds from the Research Executive Agency (REA) of the European Union in the framework of MSCA-RISE Action of the H2020 Programme, project 734899—Olive-Net. RL-M is a recipient of a Miguel Servet type I programme fellowship from the ISCIII, co-funded by ESF (`Investing in your future´) (Grant Number CP16/00033)

IgA Vasculitis: Influence of CD40, BLK and BANK1 Gene Polymorphisms

CD40, BLK and BANK1 genes involved in the development and signaling of B-cells are identified as susceptibility loci for numerous inflammatory diseases. Accordingly, we assessed the potential influence of CD40, BLK and BANK1 on the pathogenesis of immunoglobulin-A vasculitis (IgAV), predominantly a B-lymphocyte inflammatory condition. Three genetic variants within CD40 (rs1883832, rs1535045, rs4813003) and BLK (rs2254546, rs2736340, rs2618476) as well as two BANK1 polymorphisms (rs10516487, rs3733197), previously associated with inflammatory diseases, were genotyped in 382 Caucasian patients with IgAV and 955 sex- and ethnically matched healthy controls. No statistically significant differences were observed in the genotype and allele frequencies of CD40, BLK and BANK1 when IgAV patients and healthy controls were compared. Similar results were found when CD40, BLK and BANK1 genotypes or alleles frequencies were compared between patients with IgAV stratified according to the age at disease onset or to the presence/absence of gastrointestinal or renal manifestations. Moreover, no CD40, BLK and BANK1 haplotype differences were disclosed between patients with IgAV and healthy controls and between patients with IgAV stratified according to the clinical characteristics mentioned above. Our findings indicate that CD40, BLK and BANK1 do not contribute to the genetic background of IgAV

Severe Disease in Patients With Recent-Onset Psoriatic Arthritis. Prediction Model Based on Machine Learning

To identify patient- and disease-related characteristics that make it possible to predict higher disease severity in recent-onset PsA. We performed a multicenter observational prospective study (2-year follow-up, regular annual visits). The study population comprised patients aged ≥ 18 years who fulfilled the CASPAR criteria and less than 2 years since the onset of symptoms. Severe disease was defined at each visit as fulfillment of at least 1 of the following criteria: need for systemic treatment, Health Assessment Questionnaire (HAQ) > 0.5, polyarthritis. The dataset contained data for the independent variables from the baseline visit and follow-up visit number 1. These were matched with the outcome measures from follow-up visits 1 and 2, respectively. We trained a logistic regression model and random forest-type and XGBoost machine learning algorithms to analyze the association between the outcome measure and the variables selected in the bivariate analysis. The sample comprised 158 patients. At the first follow-up visit, 78.2% of the patients who attended the clinic had severe disease. This percentage decreased to 76.4% at the second visit. The variables predicting severe disease were patient global pain, treatment with synthetic DMARDs, clinical form at diagnosis, high CRP, arterial hypertension, and psoriasis affecting the gluteal cleft and/or perianal area. The mean values of the measures of validity of the machine learning algorithms were all ≥ 80%. Our prediction model of severe disease advocates rigorous control of pain and inflammation, also addressing cardiometabolic comorbidities, in addition to actively searching for hidden psoriasis

Characteristics associated with the perception of high-impact disease (PsAID ≥4) in patients with recent-onset psoriatic arthritis. Machine learning-based model

To evaluate which patient and disease characteristics are associated with the perception of high-impact disease (PsAID ≥4) in recent-onset psoriatic arthritis. We performed a multicenter observational prospective study (2-year follow-up, regular annual visits). The study population comprised patients aged ≥18 years who fulfilled the CASPAR criteria and less than 2 years since the onset of symptoms. The dataset was generated using data for each patient at the 3 visits (baseline, first year, and second year of follow-up) matched with the PsAID values at each of the 3 visits. PsAID was categorized into two groups (<4 and ≥4). We trained a logistic regression model and random forest-type and XGBoost machine learning algorithms to analyze the association between the outcome measure and the variables selected in the bivariate analysis. A k-fold cross-validation with k = 5 was performed. The sample comprised 158 patients. Of the patients who attended the clinic, 45.8% scored PsAID ≥4 at baseline; 27.1%, at the first follow-up visit, and in 23.0%, at the second follow-up visit. The variables associated with PsAID ≥4 were, in decreasing order of importance: HAQ, pain, educational level, and physical activity. Higher HAQ (logistic regression coefficient 10.394; IC95% 7.777,13.011), higher pain (5.668; 4.016, 7.320), lower educational level (-2.064; -3.515, -0.613) and high level of physical activity (1.221; 0.158, 2.283) were associated with a higher frequency of PsAID ≥4. The mean values of the measures of validity of the algorithms were all ≥85%. Despite the higher weight given to pain when scoring PsAID, we observed a greater influence of physical function on disease impact

Minimal disease activity (MDA) in patients with recent-onset psoriatic arthritis : predictive model based on machine learning

Very few data are available on predictors of minimal disease activity (MDA) in patients with recent-onset psoriatic arthritis (PsA). Such data are crucial, since the therapeutic measures used to change the adverse course of PsA are more likely to succeed if we intervene early. In the present study, we used predictive models based on machine learning to detect variables associated with achieving MDA in patients with recent-onset PsA. We performed a multicenter observational prospective study (2-year follow-up, regular annual visits). The study population comprised patients aged ≥18 years who fulfilled the CASPAR criteria and less than 2 years since the onset of symptoms. The dataset contained data for the independent variables from the baseline visit and from follow-up visit number 1. These were matched with the outcome measures from follow-up visits 1 and 2, respectively. We trained a random forest-type machine learning algorithm to analyze the association between the outcome measure and the variables selected in the bivariate analysis. In order to understand how the model uses the variables to make its predictions, we applied the SHAP technique. We used a confusion matrix to visualize the performance of the model. The sample comprised 158 patients. 55.5% and 58.3% of the patients had MDA at the first and second follow-up visit, respectively. In our model, the variables with the greatest predictive ability were global pain, impact of the disease (PsAID), patient global assessment of disease, and physical function (HAQ-Disability Index). The percentage of hits in the confusion matrix was 85.94%. A key objective in the management of PsA should be control of pain, which is not always associated with inflammatory burden, and the establishment of measures to better control the various domains of PsA

Efficacy of Anakinra in Refractory Adult-Onset Still's Disease: Multicenter Study of 41 Patients and Literature Review

Adult-onset Still's disease (AOSD) is often refractory to standard therapy. Anakinra (ANK), an interleukin-1 receptor antagonist, has demonstrated efficacy in single cases and small series of AOSD. We assessed the efficacy of ANK in a series of AOSD patients. Multicenter retrospective open-label study. ANK was used due to lack of efficacy to standard synthetic immunosuppressive drugs and in some cases also to at least 1 biologic agent. Forty-one patients (26 women/15 men) were recruited. They had a mean age of 34.4 ± 14 years and a median [interquartile range (IQR)] AOSD duration of 3.5 [2-6] years before ANK onset. At that time the most common clinical features were joint manifestations 87.8%, fever 78%, and cutaneous rash 58.5%. ANK yielded rapid and maintained clinical and laboratory improvement. After 1 year of therapy, the frequency of joint and cutaneous manifestations had decreased to 41.5% and to 7.3% respectively, fever from 78% to 14.6%, anemia from 56.1% to 9.8%, and lymphadenopathy from 26.8% to 4.9%. A dramatic improvement of laboratory parameters was also achieved. The median [IQR] prednisone dose was also reduced from 20 [11.3-47.5] mg/day at ANK onset to 5 [0-10] at 12 months. After a median [IQR] follow-up of 16 [5-50] months, the most important side effects were cutaneous manifestations (n = 8), mild leukopenia (n = 3), myopathy (n = 1), and infections (n = 5). ANK is associated with rapid and maintained clinical and laboratory improvement, even in nonresponders to other biologic agents. However, joint manifestations are more refractory than the systemic manifestations