Bridging Genetic Insights with Neuroimaging in Autism Spectrum Disorder-A Systematic Review.

Autism 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.

Identification of Neurotransmission and Synaptic Biological Processes Disrupted in Autism Spectrum Disorder Using Interaction Networks and Community Detection Analysis.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by communication deficits and repetitive behavioral patterns. Hundreds of candidate genes have been implicated in ASD, including neurotransmission and synaptic (NS) genes; however, the genetic architecture of this disease is far from clear. In this study, we seek to clarify the biological processes affected by NS gene variants identified in individuals with ASD and the global networks that link those processes together.

Prevalence of Autism Spectrum Disorder in the Centro region of Portugal: a population based study of school age children within the ASDEU project.

Introduction: Accurate prevalence estimates for Autism Spectrum Disorder (ASD) are fundamental to adequately program medical and educational resources for children. However, estimates vary globally and across Europe, and it is therefore wise to conduct epidemiological studies in defined geo-cultural contexts.

Methods: We used a population screening approach to estimate the prevalence of ASD in the Centro region of Portugal, using a harmonized protocol as part of the Autism Spectrum Disorders in the European Union (ASDEU) project.

Evidence for an association of prenatal exposure to particulate matter with clinical severity of Autism Spectrum Disorder.

Early-life exposure to air pollutants, including ozone (O), particulate matter (PM or PM, depending on diameter of particles), nitrogen dioxide (NO) and sulfur dioxide (SO) has been suggested to contribute to the etiology of Autism Spectrum Disorder (ASD). In this study, we used air quality monitoring data to examine whether mothers of children with ASD were exposed to high levels of air pollutants during critical periods of pregnancy, and if higher exposure levels may lead to a higher clinical severity in their offspring. We used public data from the Portuguese Environment Agency to estimate exposure to these pollutants during the first, second and third trimesters of pregnancy, full pregnancy and first year of life of the child, for 217 subjects with ASD born between 2003 and 2016.

Mental Health of Healthcare Professionals: Two Years of the COVID-19 Pandemic in Portugal.

The COVID-19 pandemic increased psychosocial risk factors among healthcare professionals (HCPs). Objective: To characterize Portuguese HCPs mental health (MH), estimate anxiety, depression, post-traumatic stress disorder (PTSD) and burnout symptoms, and identify risk/protective factors. A cross-sectional online survey and a longitudinal assessment were conducted in 2020 (T0) and 2021 (T1).

Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders.

Autism 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.

A Role for Gene-Environment Interactions in Autism Spectrum Disorder Is Supported by Variants in Genes Regulating the Effects of Exposure to Xenobiotics.

Heritability estimates support the contribution of genetics and the environment to the etiology of Autism Spectrum Disorder (ASD), but a role for gene-environment interactions is insufficiently explored. Genes involved in detoxification pathways and physiological permeability barriers (e.g.

Gene Variants Involved in Nonsense-Mediated mRNA Decay Suggest a Role in Autism Spectrum Disorder.

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental condition with unclear etiology. Many genes have been associated with ASD risk, but the underlying mechanisms are still poorly understood. An important post-transcriptional regulatory mechanism that plays an essential role during neurodevelopment, the Nonsense-Mediated mRNA Decay (NMD) pathway, may contribute to ASD risk.

How personalised medicine will transform healthcare by 2030: the ICPerMed vision.

This commentary presents the vision of the International Consortium for Personalised Medicine (ICPerMed) on how personalised medicine (PM) will lead to the next generation of healthcare by 2030. This vision focuses on five perspectives: individual and public engagement, involvement of health professionals, implementation within healthcare systems, health-related data, and the development of sustainable economic models that allow improved therapy, diagnostic and preventive approaches as new healthcare concepts for the benefit of the public. We further identify four pillars representing transversal issues that are crucial for the successful implementation of PM in all perspectives.

Identification of biological mechanisms underlying a multidimensional ASD phenotype using machine learning.

The complex genetic architecture of Autism Spectrum Disorder (ASD) and its heterogeneous phenotype makes molecular diagnosis and patient prognosis challenging tasks. To establish more precise genotype-phenotype correlations in ASD, we developed a novel machine-learning integrative approach, which seeks to delineate associations between patients' clinical profiles and disrupted biological processes, inferred from their copy number variants (CNVs) that span brain genes. Clustering analysis of the relevant clinical measures from 2446 ASD cases in the Autism Genome Project identified two distinct phenotypic subgroups.

FunVar: A systematic pipeline to unravel the convergence patterns of genetic variants in ASD, a paradigmatic complex disease.

In recent years, the technological advances for capturing genetic variation in large populations led to the identification of large numbers of putative or disease-causing variants. However, their mechanistic understanding is lagging far behind and has posed new challenges regarding their relevance for disease phenotypes, particularly for common complex disorders. In this study, we propose a systematic pipeline to infer biological meaning from genetic variants, namely rare Copy Number Variants (CNVs).

Identifying disease genes using machine learning and gene functional similarities, assessed through Gene Ontology.

Identifying disease genes from a vast amount of genetic data is one of the most challenging tasks in the post-genomic era. Also, complex diseases present highly heterogeneous genotype, which difficult biological marker identification. Machine learning methods are widely used to identify these markers, but their performance is highly dependent upon the size and quality of available data.

Definition of a putative pathological region in PARK2 associated with autism spectrum disorder through in silico analysis of its functional structure.

Objective: The PARK2 gene encodes Parkin, a component of a multiprotein E3 ubiquitin ligase complex that targets substrate proteins for proteasomal degradation. PARK2 mutations are frequently associated with Parkinson's disease, but structural alterations have also been described in patients with neurodevelopmental disorders (NDD), suggesting a pathological effect ubiquitous to neurodevelopmental and neurodegenerative brain processes. The present study aimed to define the critical regions for NDD within PARK2.

Attitudes of the autism community to early autism research.

Investigation into the earliest signs of autism in infants has become a significant sub-field of autism research. This work invokes specific ethical concerns such as use of 'at-risk' language, communicating study findings to parents and the future perspective of enrolled infants when they reach adulthood. This study aimed to ground this research field in an understanding of the perspectives of members of the autism community.

Low-frequency and common genetic variation in ischemic stroke: The METASTROKE collaboration.

Objective: To investigate the influence of common and low-frequency genetic variants on the risk of ischemic stroke (all IS) and etiologic stroke subtypes.

Methods: We meta-analyzed 12 individual genome-wide association studies comprising 10,307 cases and 19,326 controls imputed to the 1000 Genomes (1 KG) phase I reference panel. We selected variants showing the highest degree of association (p < 1E-5) in the discovery phase for replication in Caucasian (13,435 cases and 29,269 controls) and South Asian (2,385 cases and 5,193 controls) samples followed by a transethnic meta-analysis.

Protein interaction networks reveal novel autism risk genes within GWAS statistical noise.

Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.

The Autism Simplex Collection: an international, expertly phenotyped autism sample for genetic and phenotypic analyses.

Background: There is an urgent need for expanding and enhancing autism spectrum disorder (ASD) samples, in order to better understand causes of ASD.

Methods: In a unique public-private partnership, 13 sites with extensive experience in both the assessment and diagnosis of ASD embarked on an ambitious, 2-year program to collect samples for genetic and phenotypic research and begin analyses on these samples. The program was called The Autism Simplex Collection (TASC).

Hope for GWAS: relevant risk genes uncovered from GWAS statistical noise.

Hundreds of genetic variants have been associated to common diseases through genome-wide association studies (GWAS), yet there are limits to current approaches in detecting true small effect risk variants against a background of false positive findings. Here we addressed the missing heritability problem, aiming to test whether there are indeed risk variants within GWAS statistical noise and to develop a systematic strategy to retrieve these hidden variants. Employing an integrative approach, which combines protein-protein interactions with association data from GWAS for 6 common diseases, we found that associated-genes at less stringent significance levels (p < 0.

Recurrent duplications of the annexin A1 gene (ANXA1) in autism spectrum disorders.

Background: Validating the potential pathogenicity of copy number variants (CNVs) identified in genome-wide studies of autism spectrum disorders (ASD) requires detailed assessment of case/control frequencies, inheritance patterns, clinical correlations, and functional impact. Here, we characterize a small recurrent duplication in the annexin A1 (ANXA1) gene, identified by the Autism Genome Project (AGP) study.

Methods: From the AGP CNV genomic screen in 2,147 ASD individuals, we selected for characterization an ANXA1 gene duplication that was absent in 4,964 population-based controls.

Dysfunction of the Heteromeric KV7.3/KV7.5 Potassium Channel is Associated with Autism Spectrum Disorders.

Heterozygous mutations in the KCNQ3 gene on chromosome 8q24 encoding the voltage-gated potassium channel KV7.3 subunit have previously been associated with rolandic epilepsy and idiopathic generalized epilepsy (IGE) including benign neonatal convulsions. We identified a de novo t(3;8) (q21;q24) translocation truncating KCNQ3 in a boy with childhood autism.

Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE collaboration): a meta-analysis of genome-wide association studies.

Background: Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes.

Methods: We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry.

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk.