Pharmacogenetics of MicroRNAs and MicroRNAs Biogenesis Machinery in Pediatric Acute Lymphoblastic Leukemia

Despite the clinical success of acute lymphoblastic leukemia (ALL) therapy, toxicity is frequent. Therefore, it would be useful to identify predictors of adverse effects. In the last years, several studies have investigated the relationship between genetic variation and treatment-related toxicity. However, most of these studies are focused in coding regions. Nowadays, it is known that regions that do not codify proteins, such as microRNAs (miRNAs), may have an important regulatory function. MiRNAs can regulate the expression of genes affecting drug response. In fact, the expression of some of those miRNAs has been associated with drug response. Genetic variations affecting miRNAs can modify their function, which may lead to drug sensitivity. The aim of this study was to detect new toxicity markers in pediatric B-ALL, studying miRNA-related polymorphisms, which can affect miRNA levels and function. We analyzed 118 SNPs in pre-miRNAs and miRNA processing genes in association with toxicity in 152 pediatric B-ALL patients all treated with the same protocol (LAL/SHOP). Among the results found, we detected for the first time an association between rs639174 in DROSHA and vomits that remained statistically significant after FDR correction. DROSHA had been associated with alterations in miRNAs expression, which could affect genes involved in drug transport. This suggests that miRNA-related SNPs could be a useful tool for toxicity prediction in pediatric B-ALL.

Number of prior episodes and the presence of depressive symptoms are associated with longer length of stay for patients with acute manic episodes

Background: Few studies have analyzed predictors of length of stay (LOS) in patients admitted due to acute bipolar manic episodes. The purpose of the present study was to estimate LOS and to determine the potential sociodemographic and clinical risk factors associated with a longer hospitalization. Such information could be useful to identify those patients at high risk for long LOS and to allocate them to special treatments, with the aim of optimizing their hospital management. Methods: This was a cross-sectional study recruiting adult patients with a diagnosis of bipolar disorder (Diagnostic and Statistical Manual of Mental Disorders, 4th edition, text revision (DSM-IV-TR) criteria) who had been hospitalized due to an acute manic episode with a Young Mania Rating Scale total score greater than 20. Bivariate correlational and multiple linear regression analyses were performed to identify independent predictors of LOS. Results: A total of 235 patients from 44 centers were included in the study. The only factors that were significantly associated to LOS in the regression model were the number of previous episodes and the Montgomery-Åsberg Depression Rating Scale (MADRS) total score at admission (P < 0.05). Conclusions: Patients with a high number of previous episodes and those with depressive symptoms during mania are more likely to stay longer in hospital. Patients with severe depressive symptoms may have a more severe or treatment-resistant course of the acute bipolar manic episode.

Randomized, double-blind, placebo-controled clinical trial of sublingual immunotherapy in natural rubber latex allergic patients

Trial registration number: CTRN12611000543987

New genetic markers for treatment personalization in pediatric acute lymphoblastic leukemia

La Leucemia Linfoblástica Aguda (LLA) es el cáncer pediátrico más común. Es un desorden de las células linfoblásticas, que son las precursoras de las células linfáticas, y se caracteriza por la acumulación en médula ósea y sangre de pequeñas células blásticas con poco citoplasma y cromatina dispersa. En las últimas décadas, se ha conseguido aumentar la supervivencia del 10% al 80% pero todavía hay un 20% de pacientes que no responden al tratamiento. Esta mejoría se ha conseguido mediante la implantación de terapias combinadas y la adecuación de la terapia a grupos de riesgo. Los pacientes se separan en tres grupos de riesgo, Riesgo Estándar (RE), Alto Riesgo (AR) y Muy Alto Riesgo (MAR), en base a marcadores pronósticos, entre los que se incluyen alteraciones citogenéticas. Sin embargo, a lo largo del tratamiento, nos encontramos con dos problemas:1) Por un lado, algunos de los pacientes incluidos en el grupo de RE y AR no responden bien al tratamiento y pasan AR y MAR respectivamente. Esto quiere decir que los grupos de riesgo no están bien definidos. Por lo tanto, sería de interés poder caracterizar los pacientes que realmente son RE y AR y aquéllos que desde un principio deberían haber sido considerados como de mayor riesgo.2) Por otro lado, un alto porcentaje de pacientes experimenta toxicidad, que puede llegar a ser muy grave en algunos casos, siendo necesario parar el tratamiento. Por este motivo, sería altamente beneficioso poder reconocer a los pacientes que van a ser más sensibles al tratamiento para, de ese modo, poder ajustar la dosis.Por todo esto, creemos que una mejor asignación de los pacientes de LLA a grupos de riesgo y la personalización de la dosis, mediante nuevos marcadores genéticos, permitiría mejorar la respuesta al tratamiento.En este estudio nos planteamos, por lo tanto, dos objetivos: 1) Llevar a cabo la identificación de nuevas alteraciones genéticas presentes en el tumor para una mejor caracterización del riesgo y 2) Realizar una caracterización genética del individuo que permita predecir la respuesta al tratamiento.

Dynamics of Streptococcus pneumoniae Serotypes Causing Acute Otitis Media Isolated from Children with Spontaneous Middle-Ear Drainage over a 12-Year Period (1999–2010) in a Region of Northern Spain

10 p.

Countervailing incentives in adverse selection models. A synthesis

In this paper we propose a simple method of characterizing countervailing incentives in adverse selection problems. The key element in our characterization consists of analyzing properties of the full information problem. This allows solving the principal problem without using optimal control theory. Our methodology can also be applied to different economic settings: health economics, monopoly regulation, labour contracts, limited liabilities and environmental regulation.