Dose reduction is a feasible strategy in patients with plaque psoriasis who achieve sustained response with secukinumab: a retrospective, multicenter cohort study in daily practice setting.

BACKGROUND: Biological therapy dose modification is a common practice in the long-term treatment of plaque psoriasis. OBJECTIVE: The objective of the study was to determine prevalence, characteristics of patients, effectiveness, treatment survival of secukinumab dose reduction (SEC-DR) strategy and assess its safety and cost implications. METHODS: A retrospective, observational, multicenter cohort study was conducted in patients with plaque psoriasis treated with secukinumab and up to 2 years of follow-up. RESULTS: In 63/347 patients with an initial standard dose regimen, SEC-DR was tried at any moment in 18.2% of them after sustained response. In 51 patients, the interval between administrations was increased while in 12 patients, monthly dose was reduced to 150 mg. Successful SEC-DR was achieved in 77.8% of the patients, with sustained PASI response to the end of the study. Survival of secukinumab treatment and safety profile were not compromised by DR. The use of DR saved 33% of the cost, including failures in which standard treatment was resumed. LIMITATIONS: The proper of the study designed and the arbitrary definition of "DR success." CONCLUSION: Off-label SEC-DR strategy was used in patients with sustained response to standard dose regimen; this strategy showed long-term efficacy without compromising treatment survival or worsening the safety profile while also being cost saving.

The IFIH1/MDA5 rs1990760 Gene Variant (946Thr) Differentiates Early- vs. Late-Onset Skin Disease and Increases the Risk of Arthritis in a Spanish Cohort of Psoriasis.

The melanoma differentiation-associated protein 5 (MDA5; encoded by the IFIH1 gene) mediates the activation of the interferon pathway in response to a viral infection. This protein is also upregulated in autoimmune diseases and psoriasis skin lesions. IFIH1 gene variants that increase MDA5 activity have been associated with an increased risk for immune-mediated diseases, including psoriasis. Our aim is to determine the association between three IFIH1 variants (rs35337543 G/C, intron8 + 1; rs35744605 C/A, Glu627Stop; and rs1990760 C/T, Ala946Thr) and the main clinical findings in a cohort of Spanish patients with psoriasis (N = 572; 77% early-onset). Early-onset psoriasis patients (EOPs) had a significantly higher frequency of severe disease and the Cw6*0602 allele. Carriers of rs1990760 T (946Thr) were more common in the EOPs (p < 0.001), and the effect was more pronounced among Cw6*0602-negatives. This variant was also associated with an increased risk of psoriatic arthritis (PsA) independent from other factors (OR = 1.62, 95%CI = 1.11-2.37). The rs3533754 and rs35744605 polymorphisms did not show significant differences between the two onset age or PsA groups. Compared to the controls, the 946Thr variant was more common in the EOPs (nonsignificant difference) and significantly less common in patients aged >40 years (p = 0.005). In conclusion, the common IFIH1 rs1990760 T allele was significantly more frequent in early-onset compared to late-onset patients. This variant was also an independent risk factor for PsA in our cohort. Our study reinforces the widely reported role of the IFIH1 gene variants on psoriatic disease.

A quantitative systems pharmacology model for certolizumab pegol treatment in moderate-to-severe psoriasis.

Background: Psoriasis is a chronic immune-mediated inflammatory systemic disease with skin manifestations characterized by erythematous, scaly, itchy and/or painful plaques resulting from hyperproliferation of keratinocytes. Certolizumab pegol [CZP], a PEGylated antigen binding fragment of a humanized monoclonal antibody against TNF-alpha, is approved for the treatment of moderate-to-severe plaque psoriasis. Patients with psoriasis present clinical and molecular variability, affecting response to treatment. Herein, we utilized an in silico approach to model the effects of CZP in a virtual population (vPop) with moderate-to-severe psoriasis. Our proof-of-concept study aims to assess the performance of our model in generating a vPop and defining CZP response variability based on patient profiles. Methods: We built a quantitative systems pharmacology (QSP) model of a clinical trial-like vPop with moderate-to-severe psoriasis treated with two dosing schemes of CZP (200 mg and 400 mg, both every two weeks for 16 weeks, starting with a loading dose of CZP 400 mg at weeks 0, 2, and 4). We applied different modelling approaches: (i) an algorithm to generate vPop according to reference population values and comorbidity frequencies in real-world populations; (ii) physiologically based pharmacokinetic (PBPK) models of CZP dosing schemes in each virtual patient; and (iii) systems biology-based models of the mechanism of action (MoA) of the drug. Results: The combination of our different modelling approaches yielded a vPop distribution and a PBPK model that aligned with existing literature. Our systems biology and QSP models reproduced known biological and clinical activity, presenting outcomes correlating with clinical efficacy measures. We identified distinct clusters of virtual patients based on their psoriasis-related protein predicted activity when treated with CZP, which could help unravel differences in drug efficacy in diverse subpopulations. Moreover, our models revealed clusters of MoA solutions irrespective of the dosing regimen employed. Conclusion: Our study provided patient specific QSP models that reproduced clinical and molecular efficacy features, supporting the use of computational methods as modelling strategy to explore drug response variability. This might shed light on the differences in drug efficacy in diverse subpopulations, especially useful in complex diseases such as psoriasis, through the generation of mechanistically based hypotheses.

Determinación del grado de agresividad tumoral mediante técnicas de inteligencia artificial aplicadas a imágenes de resonancia magnética / Measuring tumor aggressiveness through artificial intelligence

Objetivo: Determinar el grado de agresividad tumoral mediante técnicas de inteligencia artificial utilizando imágenes de resonancia magnética de sarcomas con grado histológico comprobado. Materiales y Métodos: Dos cohortes retrospectivas independientes de pacientes con sarcomas de partes blandas. Para cada paciente de las dos cohortes se adquirieron tres tipos de secuencias de imágenes como indican los protocolos clínicos: potenciadas en T1, en T2 con supresión grasa (T2FS) y STIR. A fin de desarrollar el modelo de inteligencia artificial, se utilizaron 134 imágenes, tanto las de alto grado como las de bajo grado, en T1 y T2 tomando la imagen más representativa del tumor en cualquier corte. Esto se traduce en 36 millones de píxeles que serán analizados por el programa Landing AI. Resultados: La precisión promedio del modelo fue del 84,3% y la sensibilidad, del 73,3%, con un umbral de confianza de 0,66, lo que demuestra inicialmente que se obtuvo un modelo de buena calidad para predecir con imágenes de resonancia magnética el grado de agresividad de un sarcoma de partes blandas antes de la biopsia. Conclusiones: Se presenta un enfoque novedoso para abordar un tipo de enfermedad infrecuente usando técnicas de inteligencia artificial para determinar el grado tumoral en imágenes de resonancia magnética. Según los resultados de nuestro modelo, se lo puede considerar como una segunda opinión experta al realizar los estudios por imágenes antes de la biopsia. Nivel de Evidencia: III

Objective: To determine the degree of tumor aggressiveness by means of artificial intelligence techniques using magnetic resonance images of sarcomas with proven histological grade. Materials and Methods: Two independent cohorts of patients with soft tissue sarcomas (STS) were retrospectively collected. For each patient in the two cohorts, three types of imaging sequences were acquired as indicated by the clinical protocols: T1-weighted (T1), fat-suppressed T2-weighted (FST2) and STIR. For the development of the artificial intelligence model, 134 images were used, both high-grade and low-grade T1 and T2 images, taking the most representative image of the tumor at any slice. This translated into more than 36 million pixels that were analyzed by the Landing AI program. Results: To determine the degree of tumor aggressiveness by means of artificial intelligence techniques using magnetic resonance The model's average accuracy was 84.3%, and its sensitivity was 73.3%, with a confidence threshold of 0.66, indicating that a good quality model was generated for predicting the grade of aggressiveness of an STS prior to biopsy using MRI scans. Conclusions: A novel approach is presented to address a rare pathology using artificial intelligence techniques to determine the tumor grade based on nuclear magnetic resonance images. Based on the results of our model, it can be considered as a second expert opinion when performing imaging studies prior to biopsy. Level of Evidence: III

Secukinumab is effective and safe in the long-term treatment of plaque psoriasis in a daily practice setting: Multicenter study in 384 Spanish patients.

The aim of the study was to assess the long-term effectiveness and safety of secukinumab in Spanish patients with moderate-to-severe psoriasis in a daily practice setting. Nationwide multicenter, observational, retrospective, non-interventional, single-cohort study including patients who initiated treatment with secukinumab in daily clinical practice conditions. Subjects were followed for a minimum of 3 months and a maximum of 24 months. Psoriasis Area Severity Index (PASI), Body Surface Area and Physician's Global Assessments were collected at baseline and months 3, 6, 12, 18 and 24 during treatment. Adverse events and reasons for secukinumab withdrawal were collected and classified for analyses. A total of 384 patients were enrolled in the study. Median PASI declined rapidly from 14.3 at baseline to 2.7 at month 3, 2.1 at month 12, and remained low (2.8) at month 24. Within the group of patients with PASI ≥10 at baseline (n = 278), 58.3%, 60.4% and 56.5% achieved a PASI90 response at months 3, 12 and 24, respectively. As for absolute PASI, 86.5%, 69.5%, 42.7% and 37% achieved PASI <5, < 3, < 1 and 0, respectively, at month 3. Secukinumab was more effective in biologic-naïve patients and in those with lower Body Mass Index. Secukinumab presented a good long-term safety profile. Secukinumab was effective and safe in a routine clinical setting, in a large cohort of patients with moderate-to-severe plaque psoriasis, in the short-, medium- and long-term (up to 24 months).

Fast and sustained improvement of patient-reported outcomes in psoriatic patients treated with secukinumab in a daily practice setting.

Psoriasis is a chronic dermatological disease with great impact on patients' quality of life (QoL). The main objective of this study was to assess the impact of secukinumab treatment on different patient-reported outcomes (PROs) during a long-term follow-up in Spanish patients with moderate-to-severe psoriasis under real-world conditions. Retrospective, observational, open-label, nationwide multicenter cohort study that included patients who initiated treatment with secukinumab in daily clinical practice conditions. PROs assessing disease impact and QoL included Dermatology Life Quality Index (DLQI), Patient's Global Psoriasis Assessment, Itch Numerical Rating Scale and EuroQoL Thermometer Visual Analogue Scale. Outcomes, including PROs and Psoriasis Area and Severity Index (PASI), were assessed at months 3, 6, 12, 18, and 24 during treatment. A total of 238 patients were enrolled in the study. Patients had a mean DLQI score of 14.9 at baseline; 78.3%, 73.7%, and 71.7% of them achieved a DLQI 0/1 response at months 6, 12, and 24, respectively. DLQI score was lower in the long term for naïve patients. A sharp decrease in mean DLQI was observed during the first 3 months, reaching a plateau that was maintained until the end of follow-up. Similar findings were observed for the rest of QoL assessments. There was a close association between improvement in QoL and skin clearance (PASI), which progressively increased during follow-up. In this study, secukinumab sustainably improved patient's QoL during a 24-month follow-up, with strongest effects in patients naïve to biological therapies and with a direct correlation with PASI improvement.

Potential Differences in the Cardiometabolic Risk Profile of Patients with Psoriatic Disease according to Their HLA-C∗06 Status.

The human leukocyte antigen-C∗06 (HLA-C∗06, formerly HLA-Cw6) is the main genetic biomarker in psoriatic disease. It has been related to several phenotypic traits in psoriatic disease, but its role in relation to cardiometabolic comorbidities is unknown at present. Here, we analyze the potential connections between this biomarker and the cardiometabolic profile of these patients. We carried out a cross-sectional observational study including 400 patients recruited at a single university hospital. Clinical and classical cardiometabolic factors were compared between HLA-C∗06-positive and HLA-C∗06-negative individuals (OR with 95% CI). Multivariate regression analyses were carried out to check for disease traits associated with different cardiometabolic risk factors. The study population included 215 men (53.8%) and 185 women (46.2%), mean age of 46 ± 15 years, and an average disease evolution of 17 ± 12.6 years. Ninety-three (23.3%) patients met CASPAR criteria for psoriatic arthritis. HLA-C∗06 carriers (n: 160, 40%) showed an earlier age at disease onset, psoriasis family history, and more severe skin disease (type I disease). After correcting for age, sex, and disease duration, they also showed less hypertension (13.8% vs. 24.2%, OR 0.7 (95% CI: 0.42-0.78), p = 0.025), lower waist circumference (94.4 ± 13.7 vs. 98.3 ± 13.8 cm), and lower BMI (27 ± 4.4 vs. 28.1 ± 4.8, p < 0.05). We confirmed the well-known association between HLA-C∗06 and type I psoriatic disease. As a novel finding, patients carrying HLA-C∗06 showed a better cardiometabolic profile. In any case, these findings need further confirmation.

A cost-effective IoT learning environment for the training and assessment of surgical technical skills with visual learning analytics.

BACKGROUND: Surgeons need to train and certify their technical skills. This is usually done with the intervention of experts who monitor and assess trainees. Nevertheless, this is a time-consuming task that is subject to variations among evaluators. In recent decades, subjectivity has been significantly reduced through 1) the introduction of standard curricula, such as the Fundamentals of Laparoscopic Surgery (FLS) program, which measures students' performance in specific exercises, and 2) rubrics, which are widely accepted in the literature and serve to provide feedback about the overall technical skills of the trainees. Although these two elements reduce subjectivity, they do not, however, eliminate the figure of the expert evaluator, and so the process remains time consuming. OBJECTIVES: The objective of this work is to automate those parts of the work of the expert evaluator that the technology can measure objectively, using sensors to collect evidence, and visualizations to provide feedback. We designed and developed 1) a cost-effective IoT (Internet of Things) learning environment for the training and assessment of surgical technical skills and 2) visualizations supported by the literature on visual learning analytics (VLA) to provide feedback about the exercises (in real time) and overall performance (at the end of the training) of the trainee. METHODS: A hybrid approach was followed based on previous research for the design of the sensor based IoT learning environment. Previous studies were used as the basis for getting best practices on the tracking of surgical instruments and on the detection of the force applied to the tissue, with a focus on reducing the costs of data collection. The monitoring of the specific exercises required the design of sensors and collection mechanisms from scratch as there is little existing research on this subject. Moreover, it was necessary to design the overall architecture to collect, process, synchronize and communicate the data coming from the different sensors to provide high-level information relevant to the end user. The information to be presented was already validated by the literature and the focus was on how to visualize this information and the optimal time for its presentation to end users. The visualizations were validated with 18 VLA experts assessing the technical aspects of the visualizations and 4 medical experts assessing their functional aspects. RESULTS: This IoT learning environment amplifies the evaluation mechanisms already validated by the literature, allowing automatic data collection. First, it uses IoT sensors to automatically correct two of the exercises defined in the FLS (peg transfer and precision cutting), providing real-time visualizations. Second it monitors the movement of the surgical instruments and the force applied to the tissues during the exercise, computing 6 of the high-level indicators used by expert evaluators in their rubrics (efficiency, economy of movement, hand tremor, depth perception, bimanual dexterity, and respect for tissue), providing feedback about the technical skills of the trainee using a radar chart with these six indicators at the end of the training (summative visualizations). CONCLUSIONS: The proposed IoT learning environment is a promising and cost-effective alternative to help in the training and assessment of surgical technical skills. The system shows the trainees' progress and presents new indicators about the correctness of each specific exercise through real-time visualizations, as well as their general technical skills through summative visualizations, aligned with the 6 more frequent indicators in standardized scales. Early results suggest that although both types of visualizations are useful, it is necessary to reduce the cognitive load of the graphs presented in real time during training. Nevertheless, an additional evaluation is needed to confirm these results.

Multicenter Retrospective Study of Secukinumab Drug Survival in Psoriasis Patients in a Daily Practice Setting: A Long-Term Experience in Spain.

INTRODUCTION: There is limited and conflicting evidence over the real-world drug survival of secukinumab (SEC) in patients with psoriasis, especially in the long term. Our objective was to analyze the short- and long-term survival of SEC (S-SEC) and its predictive factors for the treatment of psoriasis. METHODS:  Patients clinically diagnosed with plaque psoriasis and under treatment with secukinumab (n = 384) in a daily practice setting were analyzed in a retrospective, multicenter study performed in a nationwide cohort and followed up for a period of 2 years. Kaplan-Meier curve was plotted to analyze drug survival time, and log-rank test was performed to compare several groups. Factors related to speed of treatment discontinuation were studied with a Cox regression model. RESULTS: The overall cumulative secukinumab drug survival rates observed at 6, 12, 18, and 24 months were 97.1%, 89.0%, 81.1%, and 74.3%, respectively. Obesity [hazard ratio (HR), 1.809, CI 95% 1.114-2.962; p = 0.004] and previous experience with biological therapies, particularly those who had been treated with ≥ 2 biologicals with different mechanisms of action (HR 3.476, CI 95% 1.875-6.444; p = 0.017) were associated with an early discontinuation, whereas psoriatic arthritis was associated with delayed discontinuation, (HR 0.493, CI 95% 0.265-0.917; p = 0.025). CONCLUSIONS: In our study, we found that cumulative secukinumab drug survival for psoriasis patients for the period 6-18 months was in the range of real-world evidence studies. Additionally, we observed a relatively high long-term survival rate at 24 months (74.3%).

Objective and automated assessment of surgical technical skills with IoT systems: A systematic literature review.

The assessment of surgical technical skills to be acquired by novice surgeons has been traditionally done by an expert surgeon and is therefore of a subjective nature. Nevertheless, the recent advances on IoT (Internet of Things), the possibility of incorporating sensors into objects and environments in order to collect large amounts of data, and the progress on machine learning are facilitating a more objective and automated assessment of surgical technical skills. This paper presents a systematic literature review of papers published after 2013 discussing the objective and automated assessment of surgical technical skills. 101 out of an initial list of 537 papers were analyzed to identify: 1) the sensors used; 2) the data collected by these sensors and the relationship between these data, surgical technical skills and surgeons' levels of expertise; 3) the statistical methods and algorithms used to process these data; and 4) the feedback provided based on the outputs of these statistical methods and algorithms. Particularly, 1) mechanical and electromagnetic sensors are widely used for tool tracking, while inertial measurement units are widely used for body tracking; 2) path length, number of sub-movements, smoothness, fixation, saccade and total time are the main indicators obtained from raw data and serve to assess surgical technical skills such as economy, efficiency, hand tremor, or mind control, and distinguish between two or three levels of expertise (novice/intermediate/advanced surgeons); 3) SVM (Support Vector Machines) and Neural Networks are the preferred statistical methods and algorithms for processing the data collected, while new opportunities are opened up to combine various algorithms and use deep learning; and 4) feedback is provided by matching performance indicators and a lexicon of words and visualizations, although there is considerable room for research in the context of feedback and visualizations, taking, for example, ideas from learning analytics.

Genome-wide association analysis of psoriasis patients treated with anti-TNF drugs.

While anti-TNF therapies are effective against psoriasis, 30%-50% of patients do not show an adequate response to these drugs. Different candidate-gene pharmacogenetics studies have identified single nucleotide polymorphisms that may predict anti-TNF drugs response in psoriasis. Nevertheless, only one paper has undertaken a pharmacogenomic approach failing to find significant biomarkers of biological drug response along the whole genome. Furthermore, most of the pharmacogenetic candidate biomarkers identified previously have not been confirmed in a different cohort of patients. The objective of this study was to find biomarkers that could predict anti-TNF drugs response along the whole genome and validate biomarkers identified previously. A genome-wide association study (GWAS) was performed using the Human Omni Express-8 v1.2 Beadchips in 243 psoriasis patients treated with anti-TNF drugs. This study was multicentric and did not interfere with clinical practice. Associations between single nucleotide polymorphisms (SNP) and PASI75 (a 75% reduction with respect to baseline PASI) at 3 months were evaluated. Imputation was performed using SNPs with R2  > 0.7. There were two SNPs located in NPFFR2 that were close to the significant threshold of 5 × 10-8 . These data suggest that NPFFR2 might be associated with anti-TNF drug response. However, further studies involving a larger cohort of patients are needed in order to confirm these results.

Gene Variant in the NF-κB Pathway Inhibitor NFKBIA Distinguishes Patients with Psoriatic Arthritis within the Spectrum of Psoriatic Disease.

BACKGROUND AND AIMS: The NF-κB pathway has been implicated in the genetic aetiology of psoriatic disease. However, since most patients with arthritis have psoriasis, discerning the genetic contributions to both aspects of psoriatic disease is not easy. Our aim was to study the association of common polymorphisms in genes of the NF-κB pathway in patients with psoriatic disease in order to dissect the contribution of this pathway in the appearance of each component (skin and joint) of the disease. PATIENTS AND METHODS: We investigated the association between three common variants in NFKB1 (rs230526), NFKBIA (rs7152376), and NFKBIZ (rs3217713 indel) and the risk of developing psoriatic disease. We genotyped a total of 690 psoriatic disease patients and 550 controls. Patients with cutaneous psoriasis of at least 10 years of evolution without associated arthritis were defined to have pure cutaneous psoriasis (PCP). RESULTS: The rare NFKBIA rs7152376 C was significantly more frequent in the PsA group vs. controls (OR = 2.03 (1.3-3.1), p < 0.01). The difference was even higher between PsA and PCP patients (OR = 3.2 (2.1-5.1), p < 0.001). Neither NFKB1 rs230526 nor NFKBIZ rs3217713 indel was associated with the risk of developing psoriatic disease as a whole compared to controls. CONCLUSIONS: Our study supports a significant effect of the NFKBIA gene on the risk of developing PsA, thus contributing to better discerning of the polymorphisms of this pathway that explain this risk within the spectrum of psoriatic disease. Additional studies with larger cohorts and from different populations are necessary to validate these results.

NFKBIZ and CW6 in Adalimumab Response Among Psoriasis Patients: Genetic Association and Alternative Transcript Analysis.

BACKGROUND: Nuclear factor (NF)-κB is an essential mediator of the tumor necrosis factor (TNF) pathway, and has been implicated in psoriasis. NFKBIZ is a nuclear inhibitor of NF-κB with a prominent role in the pathogenesis of psoriasis. The genetic variation at the NFKBIZ gene has been associated with the risk of developing psoriasis, and could also contribute to defining the response to anti-TNF biological drugs. OBJECTIVES: The objectives of this study were to determine the association of a common NFKBIZ insertion/deletion (indel) polymorphism (rs3217713) with the response to adalimumab and determine the differences in the relative expression of a NFKBIZ alternative transcript in patients with a positive versus negative response. METHODS: We genotyped a common NFKBIZ polymorphism in 169 psoriasis patients treated with adalimumab classified as responders (n = 120) and non-responders (n = 49), according to whether they had a 75% reduction in the Psoriasis Area and Severity Index score (PASI75) at week 24. The Cw6 polymorphism was also determined and allele and genotype frequencies were compared between the groups. We also determined the rate of the expression of a NFKBIZ transcript lacking exon 10 relative to the normal transcript in 60 patients (27 non-responders). In addition, because the intron indel could affect RNA splicing, we investigated whether the level of the alternative transcript was related to the intronic genotype. RESULTS: The NFKBIZ polymorphism was associated with adalimumab response, with carriers of the deletion allele significantly more frequent among responders (odds ratio = 2.76, 95% confidence interval 1.19-6.43; p = 0.015). The presence of the HLA-CW6 allele was also associated with a positive response in our cohort (p = 0.018). The alternative transcript was amplified in all the samples. We found higher but non-significant values of normal to alternative transcript in responders as well as in NFKBIZ insertion homozygotes. CONCLUSION: Our study supported a significant effect of a common NFKBIZ polymorphism on the response to adalimumab. This result could help to optimize the prescription of this anti-TNF, but requires confirmation in other cohorts.

Ustekinumab in psoriatic arthritis: need for studies from real-world evidence.

Ustekinumab (UST) is a recently approved drug for the treatment of psoriatic arthritis (PsA). The ACR response rates in randomized clinical trials (RCTs) with this drug have been slightly lower than that reported in RCTs of anti-TNF and anti-IL17 therapies. Therefore, the position that this drug may occupy in the treatment algorithms of PsA is not clear. More information is needed on the true efficacy of this agent under real clinical practice conditions. In this review of real-world evidence studies, it is shown that UST is effective and safe to treat PsA; nevertheless, it is necessary to homogenize the way in which the main outcomes and treatment objectives of these studies are presented.

Genetic Variation in the H19-IGF2 Cluster Might Confer Risk of Developing Impaired Renal Function.

The H19-IGF2 imprinted gene region could be implicated in the risk of developing impaired renal function (IRF). Our aim was to determine the association of several common H19-IGF2 variants and IRF in a cohort of elderly healthy individuals. The study involved 675 individuals >65 years of age, 184 with type 2 diabetes mellitus (T2DM), and 105 with IRF (estimated glomerular filtration rate [eGFR] <60). They were genotyped for two common H19 single nucleotide polymorphisms (SNPs) (rs2839698 and rs10732516), one H19-IGF2 intergenic indel (rs201858505), and one indel in the 3'UTR of the IGF2. For the H19 SNPs, we also determined the allele present in the methylated chromosome through genotyping the DNA digested with a methylation-sensitive endonuclease. None of the four H19-IGF2 variants was associated with IRF in our cohort. We found a significantly higher frequency of the 3'UTR IGF2 deletion (D) in the eGFR <60 group (p = 0.01; odds ratio = 1.16, 95% confidence interval = 1.10-2.51). This association was independent of age and T2DM, two strong predictors of IRF. In conclusion, a common indel variant in the 3'UTR of the IGF2 gene was associated with the risk of IRF. This association could be explained by the role of IGF2 in podocyte survival, through regulation of IGF2 expression by differential binding of miRNAs to the indel sequences. Functional studies should be necessary to clarify this issue.

High rates of tuberculin skin test positivity due to methotrexate therapy: False positive results?

RATIONALE: The tuberculin skin test (TST) and interferon ? release assays (IGRAs) are commonly used for latent tuberculosis infection (LTBI) screening. Unexpectedly high TST positivity rates have been reported in patients with rheumatic diseases, and methotrexate is frequently used in this population. We hypothesized that methotrexate use could be associated with false-positive TST results. OBJECTIVES: To investigate whether treatment with methotrexate and other factors are associated with false-positive TST results in patients with rheumatic diseases. METHODS: Prospective single-center study conducted between April 2013 and March 2016. Adult patients with rheumatic diseases were evaluated with a TST and two IGRAs for LTBI screening. We compared TST and IGRA results in patients treated and not treated with methotrexate and analyzed for factors associated with positive TST results. CONCLUSIONS: Our data suggest false-positive TST results associated with methotrexate therapy. Thus, we recommend against using the TST for LTBI screening in patients receiving methotrexate and the preferential use of IGRAs in such patients. MEASUREMENTS AND MAIN RESULTS: We studied 393 patients with rheumatic diseases, including ankylosing spondylitis (ASP, n = 90), rheumatoid arthritis (RA; n = 120), psoriatic arthritis (PA, n = 126), and other disorders (n = 57). The rate of TST positivity varied across the groups: ASP 22.2%, RA 25%, PA 35.7%, and other disorders (22.8%). Positivity rates were lower with IGRAs. Methotrexate use was associated with a statistically significant two-fold increase in the risk of a positive TST and a dose\x96 response relationship was observed. We found no statistically significant associations between methotrexate use and IGRA test positivity.

Gene variants in the NF-KB pathway (NFKB1, NFKBIA, NFKBIZ) and their association with type 2 diabetes and impaired renal function.

The NF-kappaB pathway might play a role in the pathogenesis of renal disease and type 2 diabetes (T2DM). Our aim was to determine whether common polymorphisms in NF-kappaB genes were associated with impaired renal function and T2DM in a cohort of healthy elderly individuals. We studied 487 individuals, all Caucasian and aged 65-85 years. A total of 104 (21%) had impaired renal function (estimated glomerular filtration rate, eGFR < 60) and 146 (30%) were classified as diabetics. The genotypes of 4 common variants were determined through PCR-RFLP or fluorescent capillary electrophoresis. The NFKB1 variants were significantly associated with T2DM: rs7667496 p = 0.01, OR = 1.68; and rs28362491 p = 0.02, OR = 1.67. They remained significantly associated in a multiple logistic regression with age, gender, hypertension, body mass index, and cholesterol. There was a trend toward the association of these variants with eGFR < 60. The two NFKB1 variants were in linkage disequilibrium (D' = -0.86), and homozygous for the two non-risk alleles (rs7667496 CC + rs28362491 II), were significantly more common in the non-diabetics (p = 0.02). In our cohort the NFKB1 variation was an independent risk factor for developing T2DM. Additional studies to confirm this association are of special interest, as well as studies to give a functional explanation to the genetic association.