Implementación de una herramienta de aprendizaje automático como apoyo para el diagnóstico temprano de enfermedades neurodegenerativas

La tecnología de seguimiento ocular es utilizada en todo tipo de ámbitos para establecer una relación entre la función cognitiva y el movimiento ocular: desde el marketing en grandes empresas, hasta los estudios conductuales en psicología y una enorme variedad de aplicaciones biomédicas. La diversidad en modos de funcionamiento de los aparatos, y el tratamiento de las series temporales que ofrece cada uno como resultado, resultan en un complejo escoyo en el uso de esta técnica. Por lo tanto, el objetivo de este trabajo es la creación y validación de un protocolo sencillo de apoyo en el diagnóstico de enfermedades neurodegenerativas a partir de las series temporales completas resultantes del seguimiento ocular para evitar la pérdida de información. Los datos se obtuvieron de la colaboración con una residencia y un hospital. Para generar las series temporales a partir de la lectura de pequeños textos se utilizó una aplicación previamente desarrollada de funcionamiento intuitivo y sencillo. Para esta fase, debido a sus especificaciones técnicas, se escogió el Eye-tracker Tobii X2-30 para la recogida de datos. En este proyecto se usaron dos algoritmos de aprendizaje automático para hacer una comparativa entre ellos y usar el de mayor precisión para el apoyo en el diagnóstico médico. Se utilizaron los algoritmos Multivariate Time Series Classification with Learned Discretization (SMTS) y una red neuronal Long Short Term Memory (LSTM). Tras el preprocesamiento de los datos, y la comparativa de los modelos de machine learning, se obtuvo una precisión de un 92,30% al diferenciar pacientes con enfermedad neurodegenerativa de aquellos sanos y una precisión de un 89,6% para asignar el tipo de enfermedad específica a cada paciente. Por consiguiente, aunque los resultados finales estén influenciados por el uso de una cohorte pequeña, este estudio nos da una prometedora perspectiva respecto al uso de esta tecnología como apoyo en el diagnóstico de enfermedades neurodegenerativas, mediante un protocolo rápido y sencillo

Valor de la expresión del ARN mensajero de la isocitrato deshidrogenasa (IDH1) como predictor de agresividad en gliomas

Los gliomas son el tipo más común de tumor cerebral primario. En humanos, cinco genes codifican para la isocitrato deshidrogenasa: IDH1/2/3A/3B/3G. Mutaciones somáticas puntuales en el gen IDH1 son frecuentes en gliomas, la mayoría transiciones de una sola base: 395G-A y están asociadas a una mayor supervivencia de esos pacientes con glioma cuando los comparamos con aquellos que no tienen la mutación. Entre las consecuencias funcionales de la mutación de la IDH1, estudios demuestran un fuerte descenso en la producción de NADPH reducido dependiente de isocitrato en las células. Investigamos la expresión del ARNm del IDH1 y la presencia o ausencia de la mutación G395A en una serie de gliomas. En particular, estudiamos 38 casos de gliomas y 7 metástasis analizando el centro y la periferia de muestras en fresco y resección en bloque. No encontramos diferencias entre las regiones central y periférica con respecto a la expresión del ARNm y la mutación de IDH1. Sin embargo, podemos observar una mayor expresión del ARNm de IDH1 y una menor incidencia de la mutación en tumores de alto grado cuando los comparamos con aquellos de bajo grado. Este estudio muestra que los gliomas con IDH1 normal tienen una mayor expresión de ARNm independientemente de la zona del tumor. Esto podría conducir a un aumento en la actividad enzimática y mayor presencia de NADPH, lo cual se necesita para el crecimiento celular. Así, el mayor poder de reducción de estas células podría explicar la mayor agresividad de estos gliomas.Gliomas, are the most common type of primary brain tumors. In humans, five genes encode for isocitrate dehydrogenase: IDH1, IDH2, IDH3A, IDH3B, and IDH3G. Somatic point mutations in IDH1 are frequent in gliomas. Most mutations for IDH1 are single base transition substitutions: 395G_A and are associated with longer survival in patients with glioma when compared with those gliomas without IDH1 mutations. Among the functional consequences of IDH1 mutation, some studies have shown a strong decrease in the isocitrate dependent production of reduced NADPH production in the cells. We investigated mRNA expression of IDH1 and the presence or absence of the G395A mutation in a subset of gliomas. Specifically, we studied 38 cases of glioma and 7 methastasis analyzing central and peripheral regions from fresh and en block resection specimens. We found no differences between central and peripheral regions, in regard to IDH1 mRNA expression and G395A IDH1 mutation. However, we identified a significantly higher expression of IDH1 mRNA and a lesser incidence of mutation in high grade gliomas when compared with low grade ones. This study shows that those gliomas with IDH1 WT are associated with higher expression of IDH1 mRNA, independently of the tumor area. This could in turn lead to an increase in enzyme activity and more presence of NADPH which is needed for cellular growth. The greater reducing power in these cells could account for the greater aggressiveness of these gliomas

Retrospective study to identify risk factors for chronic kidney disease in children with congenital solitary functioning kidney detected by neonatal renal ultrasound screening

To evaluate the prognostic significance of factors frequently associated with a reduction in renal mass, such as prematurity, low birth weight, and congenital anomalies of kidney and urinary tract (CAKUT), in patients with solitary functioning kidney (SFK) and investigate signs of early renal injury due to glomerular hyperfiltration damage or dysplasia in the remaining kidney. Retrospective observational study of congenital SFK diagnosed and followed at a tertiary care hospital over a period of 10 years in which 32,900 newborns underwent routine neonatal abdominal ultrasound screening. We analyzed age at diagnosis, sex, gestational age, anthropometric measurements at birth and prenatal and neonatal ultrasound findings, in addition to follow-up data corresponding to imaging findings (ultrasound, micturating cystourethrography, dimercaptosuccinic acid renal, and scintigraphy), ipsilateral CAKUT, compensatory hypertrophy, and renal injury in the form of albuminuria, blood pressure, and estimated glomerular filtration rate (eGFR). In total, 128 congenital SFK cases were detected (1 per 257 live births). Of these, 117 (91.4%) were diagnosed by neonatal ultrasound screening and 44.5% of these had been previously identified by prenatal ultrasound. Neonatal ultrasound had a specificity of 100% and a sensitivity of 92.1%. Forty-five patients (35.2%) had ipsilateral CAKUT and the most common type was urinary collecting system anomalies (75.5%). Over a median follow-up of 6.3 years (1?10 years), compensatory renal hypertrophy was observed in 81 patients (63.7%), most of whom had ipsilateral CAKUT (76.1% vs 56.6% of patients without ipsilateral CAKUT). Albuminuria and hypertension were observed in 3.12% and 5% of patients, respectively, and both were associated with ipsilateral CAKUT (P<.05). In addition, 75% of albuminuria cases (P=.031), 83.3% of hypertension cases (P=.004), and 100% of decreased eGFRcases (P=.031) were significantly associated with CAKUT (renal parenchymal anomaly category), being the strongest predictor of GFR the presence or absence of CAKUT. Neonatal ultrasound screening is useful for the early diagnosis of SFK. The presence of ipsilateral CAKUT should be evaluated in all patients with SFK as congenital anomalies of the renal parenchyma are associated with a poorer prognosis. Because morbidity from CAKUTs may not develop until adulthood, patients should be closely followed throughout life

Caso clinicopatológico: varón joven con disminución del nivel de conciencia y consumo reciente de cocaína

Varón de 43 años, consumidor habitual de cocaína, que habiendo sido encontrado en su domicilio con bajo nivel de conciencia es remitido a nuestro hospital. Se le practica TAC craneal que muestra hematomas lobar izquierdo y subdural interhemisférico, así como infarto isquémico frontoparietal izquierdo, siendo intervenido a continuación para evacuación del hematoma. La evolución inicial es tórpida en UCI, con diversas infecciones pulmonares bacterianas. Pasa a planta convencional de forma estable al 21 día del ingreso. El día 30 del ingreso presenta muerte súbita.This is the case of a 43 years old male, cocaine user, found at home with low level of consciousness and admitted to our hospital. A brain CT was performed, founding parenchymal and subdural hematoma and ischemic left stroke, undergoing brain surgery. He had a torpid evolution at the ICU, with several bacterial lung infections, and went to the neurosurgical unit after 21 days. He died suddenly, with no previous sympthoms, at the 30th day of admission

Multiscale, multimodal analysis of tumor heterogeneity in IDH1 mutant vs wild-type diffuse gliomas.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations

Discovery of biomarker panels for neural dysfunction in inborn errors of amino acid metabolism.

Patients with inborn errors of amino acid metabolism frequently show neuropsychiatric symptoms despite accurate metabolic control. This study aimed to gain insight into the underlying mechanisms of neural dysfunction. Here we analyzed the expression of brain-derived neurotrophic factor (BDNF) and 10 genes required for correct brain functioning in plasma and blood of patients with Urea Cycle Disorders (UCD), Maple Syrup Urine Disease (MSUD) and controls. Receiver-operating characteristic (ROC) analysis was used to evaluate sensitivity and specificity of potential biomarkers. CACNA2D2 (α2δ2 subunit of voltage-gated calcium channels) and MECP2 (methyl-CpG binding protein 2) mRNA and protein showed an excellent neural function biomarker signature (AUC ≥ 0,925) for recognition of MSUD. THBS3 (thrombospondin 3) mRNA and AABA gave a very good biomarker signature (AUC 0,911) for executive-attention deficits. THBS3, LIN28A mRNA, and alanine showed a perfect biomarker signature (AUC 1) for behavioral and mood disorders. Finally, a panel of BDNF protein and at least two large neural AAs showed a perfect biomarker signature (AUC 1) for recognition of psychomotor delay, pointing to excessive protein restriction as central causative of psychomotor delay. To conclude, our study has identified promising biomarker panels for neural function evaluation, providing a base for future studies with larger samples

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment