The association between familial ASD diagnosis, autism symptomatology and developmental functioning in young children

Few studies have directly compared individuals with and without a relative diagnosed with ASD on various domains. The present study aimed to examine the relationship between familial ASD diagnosis and the exhibition of ASD symptoms in young children with and without ASD diagnoses. Participants included 8353 children aged 17-37 months old and their families. They were divided into four groups based on individual and family diagnosis, then compared on autism symptomatology and developmental domains. No differences were found between ASD groups on overall scores and each of the factor domains, indicating no association between family ASD diagnosis and ASD symptomatology or developmental functioning. Disparate results were found for atypically developing groups with and without relatives diagnosed with ASD. Implications of these results are discussed

Factors related to parental age of first concern in toddlers with autism spectrum disorder

PURPOSE: The age of first concern (AOC) of parents of children with autism spectrum disorders (ASD) has substantial implications for early diagnosis and intervention. The current study sought to determine the average AOC, what types of first concerns are most common, and what factors predict earlier AOC in toddlers with ASD. METHODS: This study analyzed the predictive influence of the type of concern, symptom severity, medical diagnoses, and other independent variables on AOC among toddlers with ASD using multiple regressions. RESULTS: The mean AOC was found to be 13.97 months (SD = 7.86). The most commonly reported first concern was speech/language. First concerns related to communication, speech/language predicted later AOC, while motor concerns predicted earlier AOC. CONCLUSIONS: Concerns that are more closely related to social communication deficits characteristic of ASD predicted later AOC. The implications of these findings on screening/assessment and intervention are discussed

Community-Academic Partnerships: A Systematic Review of the State of the Literature and Recommendations for Future Research.

Policy pointsCommunities, funding agencies, and institutions are increasingly involving community stakeholders as partners in research, to provide firsthand knowledge and insight. Based on our systematic review of major literature databases, we recommend using a single term, community-academic partnership (CAP), and a conceptual definition to unite multiple research disciplines and strengthen the field. Interpersonal and operational factors that facilitate or hinder the collaborative process have been consistently identified, including "trust among partners" and "respect among partners" (facilitating interpersonal factors) and "excessive time commitment" (hindering operational factor). Once CAP processes and characteristics are better understood, the effectiveness of collaborative partner involvement can be tested.ContextCommunities, funding agencies, and institutions are increasingly involving community stakeholders as partners in research. Community stakeholders can provide firsthand knowledge and insight, thereby increasing research relevance and feasibility. Despite the greater emphasis and use of community-academic partnerships (CAP) across multiple disciplines, definitions of partnerships and methodologies vary greatly, and no systematic reviews consolidating this literature have been published. The purpose of this article, then, is to facilitate the continued growth of this field by examining the characteristics of CAPs and the current state of the science, identifying the facilitating and hindering influences on the collaborative process, and developing a common term and conceptual definition for use across disciplines.MethodsOur systematic search of 6 major literature databases generated 1,332 unique articles, 50 of which met our criteria for inclusion and provided data on 54 unique CAPs. We then analyzed studies to describe CAP characteristics and to identify the terms and methods used, as well as the common influences on the CAP process and distal outcomes.FindingsCAP research spans disciplines, involves a variety of community stakeholders, and focuses on a large range of study topics. CAP research articles, however, rarely report characteristics such as membership numbers or duration. Most studies involved case studies using qualitative methods to collect data on the collaborative process. Although various terms were used to describe collaborative partnerships, few studies provided conceptual definitions. Twenty-three facilitating and hindering factors influencing the CAP collaboration process emerged from the literature. Outcomes from the CAPs most often included developing or refining tangible products.ConclusionsBased on our systematic review, we recommend using a single term, community-academic partnership, as well as a conceptual definition to unite multiple research disciplines. In addition, CAP characteristics and methods should be reported more systematically to advance the field (eg, to develop CAP evaluation tools). We have identified the most common influences that facilitate and hinder CAPs, which in turn should guide their development and sustainment

Community-Academic Partnerships: A Systematic Review of the State of the Literature and Recommendations for Future Research.

Policy pointsCommunities, funding agencies, and institutions are increasingly involving community stakeholders as partners in research, to provide firsthand knowledge and insight. Based on our systematic review of major literature databases, we recommend using a single term, community-academic partnership (CAP), and a conceptual definition to unite multiple research disciplines and strengthen the field. Interpersonal and operational factors that facilitate or hinder the collaborative process have been consistently identified, including "trust among partners" and "respect among partners" (facilitating interpersonal factors) and "excessive time commitment" (hindering operational factor). Once CAP processes and characteristics are better understood, the effectiveness of collaborative partner involvement can be tested.ContextCommunities, funding agencies, and institutions are increasingly involving community stakeholders as partners in research. Community stakeholders can provide firsthand knowledge and insight, thereby increasing research relevance and feasibility. Despite the greater emphasis and use of community-academic partnerships (CAP) across multiple disciplines, definitions of partnerships and methodologies vary greatly, and no systematic reviews consolidating this literature have been published. The purpose of this article, then, is to facilitate the continued growth of this field by examining the characteristics of CAPs and the current state of the science, identifying the facilitating and hindering influences on the collaborative process, and developing a common term and conceptual definition for use across disciplines.MethodsOur systematic search of 6 major literature databases generated 1,332 unique articles, 50 of which met our criteria for inclusion and provided data on 54 unique CAPs. We then analyzed studies to describe CAP characteristics and to identify the terms and methods used, as well as the common influences on the CAP process and distal outcomes.FindingsCAP research spans disciplines, involves a variety of community stakeholders, and focuses on a large range of study topics. CAP research articles, however, rarely report characteristics such as membership numbers or duration. Most studies involved case studies using qualitative methods to collect data on the collaborative process. Although various terms were used to describe collaborative partnerships, few studies provided conceptual definitions. Twenty-three facilitating and hindering factors influencing the CAP collaboration process emerged from the literature. Outcomes from the CAPs most often included developing or refining tangible products.ConclusionsBased on our systematic review, we recommend using a single term, community-academic partnership, as well as a conceptual definition to unite multiple research disciplines. In addition, CAP characteristics and methods should be reported more systematically to advance the field (eg, to develop CAP evaluation tools). We have identified the most common influences that facilitate and hinder CAPs, which in turn should guide their development and sustainment

Frequency and Complexity of De Novo Structural Mutation in Autism.

Genetic studies of autism spectrum disorder (ASD) have established that de novo duplications and deletions contribute to risk. However, ascertainment of structural variants (SVs) has been restricted by the coarse resolution of current approaches. By applying a custom pipeline for SV discovery, genotyping, and de novo assembly to genome sequencing of 235 subjects (71 affected individuals, 26 healthy siblings, and their parents), we compiled an atlas of 29,719 SV loci (5,213/genome), comprising 11 different classes. We found a high diversity of de novo mutations, the majority of which were undetectable by previous methods. In addition, we observed complex mutation clusters where combinations of de novo SVs, nucleotide substitutions, and indels occurred as a single event. We estimate a high rate of structural mutation in humans (20%) and propose that genetic risk for ASD is attributable to an elevated frequency of gene-disrupting de novo SVs, but not an elevated rate of genome rearrangement

Frequency and Complexity of De Novo Structural Mutation in Autism.

Genetic studies of autism spectrum disorder (ASD) have established that de novo duplications and deletions contribute to risk. However, ascertainment of structural variants (SVs) has been restricted by the coarse resolution of current approaches. By applying a custom pipeline for SV discovery, genotyping, and de novo assembly to genome sequencing of 235 subjects (71 affected individuals, 26 healthy siblings, and their parents), we compiled an atlas of 29,719 SV loci (5,213/genome), comprising 11 different classes. We found a high diversity of de novo mutations, the majority of which were undetectable by previous methods. In addition, we observed complex mutation clusters where combinations of de novo SVs, nucleotide substitutions, and indels occurred as a single event. We estimate a high rate of structural mutation in humans (20%) and propose that genetic risk for ASD is attributable to an elevated frequency of gene-disrupting de novo SVs, but not an elevated rate of genome rearrangement

Frequency and Complexity of De Novo Structural Mutation in Autism

Genetic studies of autism spectrum disorder (ASD) have established that de novo duplications and deletions contribute to risk. However, ascertainment of structural variants (SVs) has been restricted by the coarse resolution of current approaches. By applying a custom pipeline for SV discovery, genotyping, and de novo assembly to genome sequencing of 235 subjects (71 affected individuals, 26 healthy siblings, and their parents), we compiled an atlas of 29,719 SV loci (5,213/genome), comprising 11 different classes. We found a high diversity of de novo mutations, the majority of which were undetectable by previous methods. In addition, we observed complex mutation clusters where combinations of de novo SVs, nucleotide substitutions, and indels occurred as a single event. We estimate a high rate of structural mutation in humans (20%) and propose that genetic risk for ASD is attributable to an elevated frequency of gene-disrupting de novo SVs, but not an elevated rate of genome rearrangement