A PheWAS Model Of Autism Spectrum Disorder

Children with Autism Spectrum Disorder (ASD) exhibit a wide diversity in type, number, and severity of social deficits as well as communicative and cognitive difficulties. It is a challenge to categorize the phenotypes of a particular ASD patient with their unique genetic variants. There is a need for a better understanding of the connections between genotype information and the phenotypes to sort out the heterogeneity of ASD. In this study, single nucleotide polymorphism (SNP) and phenotype data obtained from a simplex ASD sample are combined using a PheWAS-inspired approach to construct a phenotype-phenotype network. The network is clustered, yielding groups of etiologically related phenotypes. These clusters are analyzed to identify relevant genes associated with each set of phenotypes. The results identified multiple discriminant SNPs associated with varied phenotype clusters such as ASD aberrant behavior (self-injury, compulsiveness and hyperactivity), as well as IQ and language skills. Overall, these SNPs were linked to 22 significant genes. An extensive literature search revealed that eight of these are known to have strong evidence of association with ASD. The others have been linked to related disorders such as mental conditions, cognition, and social functioning, Clinical relevance - This study further informs on connections between certain groups of ASD phenotypes and their unique genetic variants. Such insight regarding the heterogeneity of ASD would support clinicians to advance more tailored interventions and improve outcomes for ASD patients

Connecting Phenotype To Genotype: PheWAS-inspired Analysis Of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is extremely heterogeneous clinically and genetically. There is a pressing need for a better understanding of the heterogeneity of ASD based on scientifically rigorous approaches centered on systematic evaluation of the clinical and research utility of both phenotype and genotype markers. This paper presents a holistic PheWAS-inspired method to identify meaningful associations between ASD phenotypes and genotypes. We generate two types of phenotype-phenotype (p-p) graphs: a direct graph that utilizes only phenotype data, and an indirect graph that incorporates genotype as well as phenotype data. We introduce a novel methodology for fusing the direct and indirect p-p networks in which the genotype data is incorporated into the phenotype data in varying degrees. The hypothesis is that the heterogeneity of ASD can be distinguished by clustering the p-p graph. The obtained graphs are clustered using network-oriented clustering techniques, and results are evaluated. The most promising clusterings are subsequently analyzed for biological and domain-based relevance. Clusters obtained delineated different aspects of ASD, including differentiating ASD-specific symptoms, cognitive, adaptive, language and communication functions, and behavioral problems. Some of the important genes associated with the clusters have previous known associations to ASD. We found that clusters based on integrated genetic and phenotype data were more effective at identifying relevant genes than clusters constructed from phenotype information alone. These genes included five with suggestive evidence of ASD association and one known to be a strong candidate

Autism spectrum disorder: molecular profiling analysis and identification of candidate genes through complex Systems Biology approaches

Los trastornos del espectro autista (TEA) engloban una amplia gama de afecciones neurológicas y del desarrollo caracterizadas por alteraciones en las habilidades sociales, conductas repetitivas, habla y comunicación no verbal. Existen muchos subtipos de autismo, influenciados por una combinación de factores genéticos, neurológicos, inmunológicos y ambientales y frecuentemente acompañados de una carga sustancial de comorbilidad. La gran variabilidad clínica y etiológica entre los individuos con TEA hace que la biología de sistemas sea el enfoque más prometedor en la búsqueda de tratamientos eficaces. En esta tesis doctoral se exploran diferentes estrategias de biología de sistemas para descifrar la heterogeneidad clínica y neurobiológica del autismo mediante la búsqueda de genes candidatos. Nuestro objetivo es desentrañar la complejidad de los mecanismos neurológicos subyacentes a los TEA, sus comorbilidades y las posibles limitaciones evolutivas diferenciadoras, para identificar nuevos genes y rutas biológicas clave en los resultados funcionales, contribuyendo al avance de la medicina personalizada.Autism spectrum disorders (ASD) encompass a wide range of neurological and developmental conditions characterized by alterations in social skills, repetitive behaviors, speech and nonverbal communication. There are many subtypes of autism, influenced by a combination of genetic, neurological, immunological and environmental factors and often accompanied by a substantial burden of comorbidity. The enormous clinical and etiological variability among individuals with ASD makes systems biology the most promising approach in the search for effective treatments. In this doctoral thesis different strategies of the emerging field of systems biology are explored to better understand the clinical and neurobiological heterogeneity of autism by using genome-wide search for autism candidate genes. Our goal is to disentangle the complexity of ASD underlying neurological mechanisms, overlapping genes, comorbidities and differential evolutionary constraints, in order to identify novel genes and biological pathways that may specifically impact functional outcomes, contributing to advance in the field of personalized medicine.Tesis Univ. Jaén. Departamento de Biología Experimental. Leída el 24 de junio de 2021

Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2020

The Identification of the Genetic Components of Autism Spectrum Disorders 2020 will be a useful resource for laboratory and clinical scientists, translational-based researchers, primary healthcare providers and physicians, psychologists/psychiatrists, neurologists, developmental pediatricians, clinical geneticists, teachers, special educators, and caregivers involved with individuals who have autism spectrum disorders (ASD), with the goal to translate information directly to the clinical, education and home settings. Other professionals, students at all levels, and families who are interested in this important neurodevelopmental disorder will find this textbook of value by obtaining a better awareness of the causes, testing, and understanding of genetic components leading to autism, and research that may open avenues for treatment with new approaches. This textbook includes nine chapters divided into three sections (clinical, genetics, other) written by experts in the field dedicated to genetics research and clinical care, description, and treatment by generating reviews for ASD and related disorders. These chapters include information on discoveries, risk factors, causation, diagnosis, treatment, and phenotyping with characterization of genomic or genetic factors and the environment, as genetics play an important role in up to 90% of individuals with autism via over 800 currently recognized genes

Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2019

The Identification of the Genetic Components of Autism Spectrum Disorders 2019 will serve as a resource for laboratory and clinical scientists as well as translational-based researchers, primary healthcare providers or physicians, psychologists/psychiatrists, neurologists, developmental pediatricians, clinical geneticists, and other healthcare providers, teachers, caregivers and students involved in autism spectrum disorders (ASD) with the goal to translate information directly to the clinic, education and home setting. Other professionals, students and families might find this textbook of value based on better awareness, causes and understanding of genetic components leading to autism and open avenues for treatment. Genetics play a role with up to 90% of autism, with over 800 currently recognized genes contributing to causes, clinical presentation, treatment, and counseling of family members. This textbook includes 13 chapters divided into three sections (clinical, genetics, other) written by experts in the field dedicated to research and clinical care, description, treatment and generating relevant reviews for ASD and related disorders impacting gene expression, profiling, and pathways. Identification of potential risk factors will be discussed, including obesity, microbiota, malignancy, and the immune system, as well as their direct or indirect contribution to ASD treatment and causation