Percorrer por autor "Vicente, Astrid Moura"
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- Alle Frequency Distribution Of Clinicaly Relevant Pharmacogenetic Variants In Genes With CPIC Guidelines Across European Populations: A Scoping ReviewPublication . Simões, Raquel; Cardoso, Maria Luis; Martiniano, Hugo F. M. C.; Vicente, Astrid MouraIntroduction: Pharmacogenetics (PGx) is the study of how genetic variants affect drug response. PGx variants can affect either pharmacokinetics – the processes of drug absorption, distribution, metabolism, and elimination – or pharmacodynamics – the biochemical and physiological effects of drugs and their mechanisms of action. Pharmacokinetics gene variants often define haplotypes, which are described using the star (*) allele nomenclature for genes such as those in the Cytochrome P450 (CYP450) family. This results in phenotypes of normal, rapid, ultrarapid, or poor metabolisers, leading to various drug responses (1). In recognition of the importance of understanding the clinical impact of PGx variants, the Clinical Pharmacogenetics Implementation Consortium (CPIC) has developed guidelines that translate PGx test results into clinical recommendations for drug selection and dosing (2). Reports in the literature on ancestry‑related differences in drug response highlight the need for a broader investigation of PGx variants, namely in CYP450 genes, across diverse groups(3).
- Análise de uma rede de similaridade genética entre a perturbação do espetro do autismo e comorbilidades do foro neurológico e neuropsiquiátricoPublication . Vilela, Joana; Martiniano, Hugo; Marques, Ana Rita; Santos, João Xavier; Rasga, Célia; Oliveira, Guiomar; Vicente, Astrid MouraA Perturbação do Espetro do Autismo (PEA) é uma perturbação do neurodesenvolvimento com apresentação clínica heterogénea, nível de gravidade variável e ocorrência de múltiplas comorbilidades. A PEA tem uma arquitetura genética complexa que se reflete na sua heterogeneidade clínica, existindo evidência de uma sobreposição de genes alterados entre esta condição e diversas comorbilidades do foro neurológico e neuropsiquiátrico. Neste estudo, construímos uma rede de interação entre doenças baseada na similaridade genética, para explorar a componente genética compartilhada entre a PEA e comorbilidades neurológicas e neuropsiquiátricas. As doenças analisadas incluem o Défice Intelectual (DI), a Perturbação de Hiperatividade/ Défice de Atenção (PHDA) e a Epilepsia, bem como outras doenças neuropsiquiátricas como a Esquizofrenia (SCZ) e a Perturbação Bipolar (PB). Usando a base de dados de doenças da DisGeNET, a similaridade genética entre as doenças analisadas foi calculada a partir do coeficiente de Jaccard entre pares de doenças, e o algoritmo de Leiden foi usado para identificar comunidades de doenças na rede. Identificámos uma comunidade heterogénea de doenças geneticamente mais semelhantes à PEA, que inclui a Epilepsia, a PB, a PHDA com apresentação combinada, e algumas perturbações no espetro da SCZ. Esta abordagem permitiu obter uma maior clarificação acerca da componente genética compartilhada entre a PEA e comorbilidades neurológicas e neuropsiquiátricas, com implicações importantes para a nosologia, fisiopatologia e o tratamento o personalizado da doença.
- Base Legal para a Implementação da Iniciativa 1 Milhão de Genomas (1+MG) WorkshopPublication . Vicente, Astrid MouraThe 1+ Million Genomes initiative has the potential to improve disease prevention, allow for more personalised treatments and support groundbreaking research. The '1+ Million Genomes' (1+MG) initiative aims to enable secure access to genomics and the corresponding clinical data across Europe for better research, personalised healthcare and health policy making. Since the Digital Day 2018, 22 EU countries, the UK and Norway signed Member States’ declaration on stepping up efforts towards creating a European data infrastructure for genomic data and implementing common national rules enabling federated data access. The initiative forms part of the EU’s agenda for the Digital Transformation of Health and Care and is aligned with the goals of the European Health Data Space.
- Bridging Genetic Insights with Neuroimaging in Autism Spectrum Disorder - A Systematic ReviewPublication . Vilela, Joana; Rasga, Célia; Santos, João Xavier; Martiniano, Hugo; Marques, Ana Rita; Oliveira, Guiomar; Vicente, Astrid Moura; MDPIAutism Spectrum Disorder (ASD) is an early onset neurodevelopmental disorder characterized by impaired social interaction and communication, and repetitive patterns of behavior. Family studies show that ASD is highly heritable, and hundreds of genes have previously been implicated in the disorder; however, the etiology is still not fully clear. Brain imaging and electroencephalography (EEG) are key techniques that study alterations in brain structure and function. Combined with genetic analysis, these techniques have the potential to help in the clarification of the neurobiological mechanisms contributing to ASD and help in defining novel therapeutic targets. To further understand what is known today regarding the impact of genetic variants in the brain alterations observed in individuals with ASD, a systematic review was carried out using Pubmed and EBSCO databases and following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. This review shows that specific genetic variants and altered patterns of gene expression in individuals with ASD may have an effect on brain circuits associated with face processing and social cognition, and contribute to excitation–inhibition imbalances and to anomalies in brain volumes.
- Comprehensive Genetic Analysis Provides Novel Insights Into The MicroRNA Regulatory Landscape of Autism Spectrum DisorderPublication . Marques, Ana Rita; Martiniano, Hugo; Santos, João Xavier; Vilela, Joana; Asif, Muhammad; Sousa, Lisete; Oliveira, Guiomar; Vicente, Astrid MouraBackground: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a strong genetic component. Many risk genes are associated with ASD, however most of the genetic determinants are still unknown and a role for gene regulatory mechanisms is likely. MicroRNAs (miRNAs) regulate gene expression, playing key roles in neural development and function, and have been implicated in ASD onset and progression. Methods: To identify miRNA potentially associated with ASD, we conducted a comprehensive analysis of Single Nucleotide Variants (SNVs) and Copy Number Variants (CNVs) from ASD patients (N = 4300 and N = 3570, respectively) and control subjects (N = 67442 and N = 9649, respectively). We further performed functional enrichment analysis to understand the functional impact of these miRNAs variants. Results: Our results identified 28 miRNAs significantly enriched for putative disrupted SNVs and 31 miRNAs exclusively or more frequently targeted by CNVs in ASD cases, when compared to controls (α=0.05). These genes encode 70 mature miRNAs, including some novel and others previously implicated in ASD, that are predicted to target 2745 brain-expressed genes. Functional analysis indicates they are enriched in processes such as cellular signaling, gene regulation, protein metabolism, and chromatin structure, all of which are critical for ASD development. Interestingly, 44 of the identified miRNAs are predicted to regulate 71 genes strongly associated with increased ASD risk. Conclusion: This comprehensive gene-based analysis highlights miRNAs that regulate gene networks and cellular pathways essential for brain function and plasticity, which are often disrupted in ASD patients.
- Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disordersPublication . Vilela, Joana; Martiniano, Hugo; Marques, Ana Rita; Santos, João Xavier; Rasga, Célia; Oliveira, Guiomar; Vicente, Astrid MouraAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder with heterogeneous clinical presentation, variable severity, and multiple comorbidities. A complex underlying genetic architecture matches the clinical heterogeneity, and evidence indicates that several co-occurring brain disorders share a genetic component with ASD. In this study, we established a genetic similarity disease network approach to explore the shared genetics between ASD and frequent comorbid brain diseases (and subtypes), namely Intellectual Disability, Attention-Deficit/Hyperactivity Disorder, and Epilepsy, as well as other rarely co-occurring neuropsychiatric conditions in the Schizophrenia and Bipolar Disease spectrum. Using sets of disease-associated genes curated by the DisGeNET database, disease genetic similarity was estimated from the Jaccard coefficient between disease pairs, and the Leiden detection algorithm was used to identify network disease communities and define shared biological pathways. We identified a heterogeneous brain disease community that is genetically more similar to ASD, and that includes Epilepsy, Bipolar Disorder, Attention-Deficit/Hyperactivity Disorder combined type, and some disorders in the Schizophrenia Spectrum. To identify loss-of-function rare de novo variants within shared genes underlying the disease communities, we analyzed a large ASD whole-genome sequencing dataset, showing that ASD shares genes with multiple brain disorders from other, less genetically similar, communities. Some genes (e.g., SHANK3, ASH1L, SCN2A, CHD2, and MECP2) were previously implicated in ASD and these disorders. This approach enabled further clarification of genetic sharing between ASD and brain disorders, with a finer granularity in disease classification and multi-level evidence from DisGeNET. Understanding genetic sharing across disorders has important implications for disease nosology, pathophysiology, and personalized treatment.
- Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disordersPublication . Vilela, Joana; Martiniano, Hugo; Marques, Ana Rita; Santos, João; Rasga, Célia; Oliveira, Guiomar; Vicente, Astrid MouraBackground/Objectives: Autism Spectrum Disorder (ASD) is a clinically heterogeneous neurodevelopmental disorder , with variable severity and multiple comorbidities. Given the previous evidence of genetic overlap between ASD and several comorbid brain disorders, we sought to explore the genetic similarity with ASD across a range of brain disorders, using a genetic similarity disease network approach. Methods: We developed a genetic similarity disease network between ASD and Intellectual Disability, Attention-Deficit/Hyperactivity Disorder, Epilepsy, Schizophrenia and Bipolar Disease spectrum. Using gene-disease associations from the DisGeNET database, genetic similarities were estimated from the Jaccard coefficient between disease pairs. The Leiden algorithm identified network disease communities and shared biological pathways. Loss-of-function (LoF) rare de novo variants within shared genes underlying the disease communities were identified using the MSSNG whole-genome sequencing dataset. Results: We identified three disease communities. ASD is included in a heterogeneous community with Epilepsy, Bipolar Disorder, Attention-Deficit/Hyperactivity Disorder combined type, and some disorders in the Schizophrenia Spectrum. ASD and Intellectual Disability are in separate communities. The genes SHANK3, ASH1L, SCN2A, and CHD2, which are candidate genes for diseases in all communities, have a higher number of de novo rare LoF SNVs in ASD subjects. Conclusion: This approach enabled further clarification of genetic sharing between ASD and comorbid brain disorders, as we took advantage from a finer granularity in disease classification and multi-level evidence from DisGeNET, with important implications for disease nosology, pathophysiology, and personalized treatment.
- Estratégia Nacional para a Medicina Genómica (PT_MedGen)Publication . Vicente, Astrid MouraA Medicina Genómica utiliza a informação contida no DNA de cada individuo para informar os seus cuidados de saúde, contribuindo para diagnósticos mais precisos e atempados, para ajustar a terapêutica certa para cada individuo e para estimar a sua predisposiçao a determinadas doenças, potenciando a sua prevenção. É assim um componente-chave da Medicina Personalizada. (...)
- Estratégia Nacional para a Medicina Genómica - PT_MedGen: desafios e prioridadesPublication . Almeida, Fernando de; Vicente, Astrid Moura; Calado, Patrícia; Santos, Manuel; Carvalho, Ana Sofia; Águas, Cíntia; Pinto, Cátia Sousa; Silva, Mário Jorge Gaspar da; Melo, Ana Portugal; Oliveira, Mónica Duarte Correia de; Feijó, Joana; Vilarinho, Laura; Oliveira, CarlaO presente documento visa propor o conceito e as linhas de ação prioritárias da Estratégia Nacional para a Medicina Genómica (PT_MedGen). O documento baseia-se na auscultação de alguns dos principais stakeholders nacionais, representados na Comissão nomeada pelo Despacho n.o 5135/2021 coordenada pelo INSA, e ainda na consulta de outras entidades e peritos de relevância. A estratégia PT_MedGen tem a meta global de criar infraestruturas e processos que permitam a adoção de abordagens de medicina personalizada na prática clínica, a par com a contribuição para a iniciativa 1+MG. Esta estratégia promoverá ainda a investigação, a inovação, a competitividade e a internacionalização, permitindo a criação de conhecimento e valor significativos na área da saúde.
- A European Network for Genomics in HealthcarePublication . Vicente, Astrid MouraThe 1+ Million Genomes initiative has the potential to improve disease prevention, allow for more personalised treatments and support groundbreaking research. The '1+ Million Genomes' (1+MG) initiative aims to enable secure access to genomics and the corresponding clinical data across Europe for better research, personalised healthcare and health policy making. Since the Digital Day 2018, 22 EU countries, the UK and Norway signed Member States’ declaration on stepping up efforts towards creating a European data infrastructure for genomic data and implementing common national rules enabling federated data access. The initiative forms part of the EU’s agenda for the Digital Transformation of Health and Care and is aligned with the goals of the European Health Data Space.
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