Search

La presencia de la discapacidad en un miembro de la familia ocasiona transformaciones en los roles familiares, así como en su dinámica. El objetivo de esta tesis es crear y validar un instrumento de evaluación del impacto que un miembro con síndrome de Down (SD) provoca, tanto en las principales dimensiones de la rutina familiar, como en los miembros que la conforman y la elaboración de un manual de apoyo y orientación a las familias. Para ello, se ha optado por un diseño metodológico mixto, con una primera fase cualitativa en la que se busca desarrollar los ítems de la escala y concretar las principales áreas de impacto familiar, y una segunda etapa cuantitativa en la que se procede a la validación de la escala. Durante la fase cualitativa se han efectuado entrevistas semiestructuradas a cuatro profesionales del ámbito de la educación especial y a tres padres y tres madres con un hijo con SD, a partir de las cuáles se ha elaborado una escala piloto. En la etapa cuantitativa, la escala piloto se ha remitido a una muestra de 31 personas como paso previo a la elaboración de una versión definitiva validada por una muestra de 117 individuos. Como resultado se ha desarrollado una versión definitiva del instrumento que cuenta con 30 ítems que presenta un alfa de Cronbach de 0,783, y se ha certificado asimismo su validez de constructo. El análisis factorial de la escala ha determinado la existencia de cinco dimensiones de impacto diferenciadas. Los resultados de la escala y de la fase cualitativa coinciden en señalar un impacto heterogéneo que implica tanto puntos positivos como negativos, a partir de los que se ha elaborado un manual de apoyo y orientación a las familias. Madrid ESP

International audience; The traditional approach to biomarker discovery for any pathology has been through hypothesis-based research one candidate at a time. The objective of this study was to develop an agnostic approach for the simultaneous screening of plasma for consistent molecular differences between a group of individuals exhibiting a pathology and a group of healthy individuals. To achieve this, we focused on developing a predictive tool based on plasma for the amount of brain amyloid-β deposition as observed in PET scans. The accumulation of brain amyloid-β (Aβ) plaques is a key risk factor for the development of Alzheimer's disease. A contrast was established between cognitively normal individuals above the age of 70 that differed for the amount of brain amyloid-β observed in PET scans (INSIGHT study group). Positive selection was performed against a pool of plasma from individuals with high brain amyloid and negative selection against a pool of plasma from individuals with low brain amyloid This enriched, selected library was then applied to plasma samples from 11 individuals with high levels of brain amyloid and 11 individuals with low levels of brain Aβ accumulation. Each of these individually selected libraries was then characterized by next generation sequencing, and the relative frequency of 10,000 aptamer sequences that were observed in each selection was screened for ability to explain variation in brain amyloid using sparse partial least squares discriminant analysis. From this analysis a subset of 44 aptamers was defined, and the individual aptamers were synthesized. This subset was applied to plasma samples from 70 cognitively normal individuals all above the age of 70 that differed for brain amyloid deposition. 54 individuals were used as a training set, and 15 as a test set. Three of the 15 individuals in the test set were mis-classified resulting in an overall accuracy of 80% with 86% sensitivity and 75% specificity. The aptamers included in the subset serve directly as biomarkers, thus we have named them Aptamarkers. There are two potential applications of these results: extending the predictive capacity of these aptamers across a broader range of individuals, and/or using the individual aptamers to identify targets through covariance analysis and reverse omics approaches. We are currently expanding applications of the Aptamarker platform to other diseases and target matrices.