Open Access
Circular RNA expression profile in blood according to ischemic stroke etiology
(BioMed Central, 2020) Ostolaza, Aiora; Blanco Luquin, Idoia; Urdánoz Casado, Amaya; Rubio, Idoya; Labarga Gutiérrez, Alberto; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Gobierno de Navarra / Nafarroako Gobernua
Background: The discovery of novel biomarkers of stroke etiology would be most helpful in management of acute ischemic stroke patients. Recently, circular RNAs (circRNAs) have been proposed as candidate biomarkers of neurological conditions due to its high stability. circRNAs function as sponges, sequestering miRNAs and are involved in most relevant biological functions. Our aim was to identify differentially expressed circRNAs in acute ischemic stroke patients according to stroke etiology. Methods: A comprehensive expression profile of blood circRNAs was conducted by Arraystar Human circRNA arrays (13,617 probes) on a discovery cohort of 30 stroke patients with different stroke etiologies by TOAST classification. Real-time quantitative PCR (RT-qPCR) was used to validate array results in a cohort of 50 stroke patients. Functional in silico analysis was performed to identify potential interactions with microRNAs (miRNAs) and pathways underlying deregulated circRNAs. Results: A set of 60 circRNAs were found to be upregulated in atherotrombotic versus cardioembolic strokes (fold-change > = 1.5 and p-value ≤ 0.05). Differential expression of hsa_circRNA_102488, originated from UBA52 gene, was replicated in the validation cohort. RNA-binding proteins (RBPs) sites of hsa_circRNA_102488 clustered around AGO2 and FUS proteins. Further functional analysis revealed interactions between deregulated circRNAs and a set of miRNAs involved in stroke-related pathways, such as fatty acid biogenesis or lysine degradation. Conclusion: Different stroke subtypes show specific profiles of circRNAs expression. circRNAs may serve as a new source of biomarkers of stroke etiology in acute ischemic stroke patients.
Open Access
Extracción de información biológica mediante factorización matricial de datos de expresión génica
(2024) Labarga Gutiérrez, Alberto; Barajas Vélez, Miguel Ángel; Ciencias de la Salud; Osasun Zientziak
En las últimas décadas, la aparición de herramientas eficaces de secuenciación genómica y de la biotecnología experimental de alto rendimiento ha dado lugar a enormes avances en las ciencias de la vida y la medicina, aportando profundos conocimientos sobre distintas perspectivas de los mecanismos moleculares subyacentes a los procesos biológicos. Las funciones y procesos celulares dependen de la interacción y comunicación coordinadas entre una amplia variedad de biomoléculas, como genes, proteínas, metabolitos y reguladores epigenéticos. Existen múltiples capas en las que tiene lugar la regulación y, por tanto, diferentes perspectivas desde las que observar la actividad biológica. Las distintas tecnologías conocidas comúnmente como ‘ómicas’ nos permiten medir cuantitativa y cualitativamente la estructura y actividad de muchas de estas biomoléculas. El coste de estas tecnologías ha descendido en los últimos años, lo que las ha hecho más comunes y ha permitido disponer de muchos datos para la investigación. Esta situación ha creado la necesidad de nuevas formas de gestionar, procesar y dar sentido a todos estos datos de forma integrada. Teniendo en cuenta que los datos biológicos pueden representarse fácilmente como una red en la que los nodos representan los distintos componentes biológicos (genes, proteínas, etc.) y las aristas representan la relación entre ellos, permitir que el aprendizaje automático incorpore al modelo información sobre la estructura de los grafos de conocimiento multiómico abre nuevas vías para hacer predicciones o descubrir nuevos patrones utilizando este conocimiento relacional para su aplicación en nuevos usos.
Open Access
Mass spectrometry-based proteomic profiling of thrombotic material obtained by endovascular thrombectomy in patients with ischemic stroke
(MDPI, 2018) Muñoz, Roberto; Santamaría Martínez, Enrique; Rubio, Idoya; Ausín, Karina; Labarga Gutiérrez, Alberto; Ciencias de la Salud; Osasun Zientziak; Gobierno de Navarra / Nafarroako Gobernua, PC025
Thrombotic material retrieved from acute ischemic stroke (AIS) patients represents a valuable source of biological information. In this study, we have developed a clinical proteomics workflow to characterize the protein cargo of thrombi derived from AIS patients. To analyze the thrombus proteome in a large-scale format, we developed a workflow that combines the isolation of thrombus by endovascular thrombectomy and peptide chromatographic fractionation coupled to mass-spectrometry. Using this workflow, we have characterized a specific proteomic expression profile derived from four AIS patients included in this study. Around 1600 protein species were unambiguously identified in the analyzed material. Functional bioinformatics analyses were performed, emphasizing a clustering of proteins with immunological functions as well as cardiopathy-related proteins with blood-cell dependent functions and peripheral vascular processes. In addition, we established a reference proteomic fingerprint of 341 proteins commonly detected in all patients. Protein interactome network of this subproteome revealed protein clusters involved in the interaction of fibronectin with 14-3-3 proteins, TGFβ signaling, and TCP complex network. Taken together, our data contributes to the repertoire of the human thrombus proteome, serving as a reference library to increase our knowledge about the molecular basis of thrombus derived from AIS patients, paving the way toward the establishment of a quantitative approach necessary to detect and characterize potential novel biomarkers in the stroke field.
Open Access
Integrative multi-omics analysis for etiology classification and biomarker discovery in stroke: advancing towards precision medicine
(MDPI, 2024) Labarga Gutiérrez, Alberto; Martínez-González, Judith; Barajas Vélez, Miguel Ángel; Ciencias de la Salud; Osasun Zientziak
Recent advancements in high-throughput omics technologies have opened new avenues for investigating stroke at the molecular level and elucidating the intricate interactions among various molecular components. We present a novel approach for multi-omics data integration on knowledge graphs and have applied it to a stroke etiology classification task of 30 stroke patients through the integrative analysis of DNA methylation and mRNA, miRNA, and circRNA. This approach has demonstrated promising performance as compared to other existing single technology approaches.
Open Access
Telomere length correlates with subtelomeric DNA methylation in long-term mindfulness practitioners
(Nature Research, 2020) Mendióroz Iriarte, Maite; Puebla Guedea, Marta; Montero Marín, Jesús; Urdánoz Casado, Amaya; Labarga Gutiérrez, Alberto; Ciencias de la Salud; Osasun Zientziak
Mindfulness and meditation techniques have proven successful for the reduction of stress and improvement in general health. In addition, meditation is linked to longevity and longer telomere length, a proposed biomarker of human aging. Interestingly, DNA methylation changes have been described at specific subtelomeric regions in long-term meditators compared to controls. However, the molecular basis underlying these beneficial effects of meditation on human health still remains unclear. Here we show that DNA methylation levels, measured by the Infinium HumanMethylation450 BeadChip (Illumina) array, at specific subtelomeric regions containing GPR31 and SERPINB9 genes were associated with telomere length in long-term meditators with a strong statistical trend when correcting for multiple testing. Notably, age showed no association with telomere length in the group of long-term meditators. These results may suggest that long-term meditation could be related to epigenetic mechanisms, in particular gene-specific DNA methylation changes at distinct subtelomeric regions.
Open Access
Early epigenetic changes of Alzheimer's disease in the human hippocampus
(2020) Blanco Luquin, Idoia; Acha Santamaría, Blanca; Urdánoz Casado, Amaya; Sánchez Ruiz de Gordoa, Javier; Vicuña-Urriza, Janire; Roldán, Miren; Labarga Gutiérrez, Alberto; Zelaya Huerta, María Victoria; Cabello, Carolina; Méndez López, Iván; Mendióroz Iriarte, Maite; Ciencias de la Salud; Osasun Zientziak; Sociología y Trabajo Social; Soziologia eta Gizarte Lana; Gobierno de Navarra / Nafarroako Gobernua
The discovery of new biomarkers would be very valuable to improve the detection of early Alzheimer's disease (AD). DNA methylation marks may serve as epigenetic biomarkers of early AD. Here we identified epigenetic marks that are present in the human hippocampus from the earliest stages of AD. A previous methylome dataset of the human AD hippocampus was used to select a set of eight differentially methylated positions (DMPs) since early AD stages. Next, bisulphite pyrosequencing was performed in an expanded homogeneous cohort of 18 pure controls and 35 hippocampal samples with neuropathological changes of pure AD. Correlation between DNA methylation levels in DMPs and phospho-tau protein burden assessed by immunohistochemistry in the hippocampus was also determined. We found four DMPs showing higher levels of DNA methylation at early AD stages compared to controls, involving ELOVL2, GIT1/TP53I13 and the histone gene locus at chromosome 6. DNA methylation levels assessed by bisulphite pyrosequencing correlated with phospho-tau protein burden for ELOVL2 and HIST1H3E/HIST1H3 F genes. In this discovery study, a set of four epigenetic marks of early AD stages have been identified in the human hippocampus. It would be worth studying in-depth the specific pathways related to these epigenetic marks. These early alterations in DNA methylation in the AD hippocampus could be regarded as candidate biomarkers to be explored in future translational studies.