Parent-reported and clinician-observed autism spectrum disorder (ASD) symptoms in children with attention deficit/hyperactivity disorder (ADHD): implications for practice under DSM-5

Grzadzinski, Rebecca; Dick, Catherine; Lord, Catherine; Bishop, Somer

doi:10.1186/s13229-016-0072-1

Cited by 140 publications

(146 citation statements)

References 55 publications

Supporting

Mentioning

134

Contrasting

Unclassified

Order By: Relevance

“…ADI-Current comprised the sum of scores from ADI-R items that have been mapped to DSM-5 criteria in previous studies. 7, 31 The ADI-R formal classification of autism (i.e., Autistic Disorder), as well as criteria recommended for classifying broader ASD, 32 are based on past behavior items from the diagnostic algorithm. Therefore, results of analyses are also reported for the total sum of diagnostic algorithm items (ADI-diagnostic, range 0–68).…”

Section: Methodsmentioning

confidence: 99%

Multidimensional Influences on Autism Symptom Measures: Implications for Use in Etiological Research

Havdahl

Bal

Huerta

et al. 2016

Journal of the American Academy of Child & Adolescent Psych

Self Cite

120

View full text Add to dashboard Cite

Objective Growing awareness that symptoms of autism spectrum disorder (ASD) transcend multiple diagnostic categories, and major advances in the identification of genetic syndromes associated with ASD, has led to widespread use of ASD symptom measures in etiological studies of neurodevelopmental disorders. Insufficient consideration of potentially confounding factors such as cognitive ability or behavior problems can have important negative consequences in interpretation of findings, including erroneous estimation of associations between ASD and etiological factors. Method Participants were 388 children aged 2–13 years with diagnoses of ASD or another neurodevelopmental disorder without ASD. Receiver operating characteristics methods were used to assess the influence of IQ and emotional/behavioral problems on the discriminative ability of three widely used ASD symptom measures; the Social Responsiveness Scale (SRS), the Autism Diagnostic Interview-Revised (ADI-R), and the Autism Diagnostic Observation Schedule (ADOS). Results IQ influenced the discriminative thresholds of the SRS and ADI-R, and emotional/behavioral problems affected the discriminative thresholds of the SRS, ADI-R, and ADOS. This resulted in low specificity of ASD cut-offs on the SRS and ADI-R for children with intellectual disability without ASD (27–42%), and low specificity across all three instruments for children without ASD with elevated emotional/behavioral problems (36–59%). Adjustment for these characteristics resulted in improved discriminative ability for all three ASD measures. Conclusion The findings indicate that scores on ASD symptom measures reflect far more than ASD symptoms. Valid interpretation of these measures requires steps to account for the influences of IQ and emotional/behavioral problems.

show abstract

Section: Methodsmentioning

confidence: 99%

Multidimensional Influences on Autism Symptom Measures: Implications for Use in Etiological Research

Havdahl

Bal

Huerta

et al. 2016

Journal of the American Academy of Child & Adolescent Psych

Self Cite

120

View full text Add to dashboard Cite

show abstract

“…Co-morbid ADHD often results in lower cognitive, adaptive, and social functioning [Rao & Landa, 2014;Yerys et al, 2009]. Also, about 20-60% of children with ADHD have social difficulties similar to autism higher than typically developing (TD) children [Grzadzinski, Dick, Lord, & Bishop, 2016]. There still remains confusion regarding ADHD or autism as the cause of these social difficulties.…”

Section: Introductionmentioning

confidence: 99%

Atomoxetine for attention deficit hyperactivity disorder in children and adolescents with autism: A systematic review and meta‐analysis

et al. 2019

View full text Add to dashboard Cite

Atomoxetine is prescribed to children with autism spectrum disorder having symptoms of attention deficit hyperactivity disorder. We sought to examine the efficacy and safety of atomoxetine in this population. After screening for inclusion criteria, we identified three randomized placebo controlled trials involving 241 children. We assessed internal validity using standard Cochrane Risk of bias tool for randomized controlled trials (RCTs). We used Revman 5.3 for meta‐analysis and GRADE approach to create summary of findings with grading of the quality of evidence. Atomoxetine had a benefit on improving parent‐rated hyperactivity (standardized mean difference [SMD] = −0.73, 95% Confidence Interval, CI = −1.15 to −0.34) and parent‐rated inattention (SMD = −0.53, 95% CI = −0.93 to −0.12) but the magnitude of effects is uncertain. However, atomoxetine was also associated with increased risk of non‐serious adverse effects like nausea and vomiting, decreased sleep, and decreased appetite. Atomoxetine may be effective in improving hyperactivity and inattention in children with autism spectrum disorder and attention deficit hyperactivity disorder. However, we are uncertain about the true effect of this intervention and need more RCTs trials designed to evaluate this. Autism Research 2019, 12: 542–552. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. Lay Summary Atomoxetine is prescribed for Attention Deficit Hyperactivity Disorder (ADHD). About a third of children and adolescents with autism also suffer from ADHD. We carried out an analysis of data reported from a specific kind of medication trials which had examined the effectiveness and side effects of atomoxetine in this patient population. We could find only three such trials and analyzed the reported data. Our analysis revealed that atomoxetine is effective in improving symptoms of ADHD like hyperactivity and inattention and also causes side effects like nausea, vomiting, decreased sleep, and decreased appetite. However, the existing data are insufficient to provide a conclusive statement with certainty and more trials are needed for this.

show abstract

“…Behavioral phenotypes of ASD are known to be highly heterogeneous. Some individuals with ASD are hypoactive with elevated anxiety, and some are co-diagnosed with ADHD and show reduced anxiety [59][60][61][62]…”

Section: Cdh11 As An Asd Risk Genementioning

confidence: 99%

Association ofCDH11with ASD revealed by matched-gene co-expression analysis and mouse behavioral studies

Wang

Jia

et al. 2020

Preprint

View full text Add to dashboard Cite

Genetic variants of a large group of susceptibility genes have been associated with similar clinical manifestations of autism spectrum disorders (ASD), suggesting convergent function of these genes during brain development. Gene co-expression analysis has emerged as an important tool to identify convergent molecular pathways shared by ASD risk genes. In this study, four gene features, including gene size, mRNA length, mRNA abundance, and guanine-cytosine content, were found to profoundly affect gene co-expression. A new method termed "matched-gene coexpression analysis" (MGCA) was developed to screen for biologically meaningful gene coexpression relationships, taking into the consideration of the effect of these features on gene coexpression. With this method, significant convergence of the expression of high-confidence ASD risk genes (hcASDs) in the brain was demonstrated, and an improved efficacy in the prediction of convergent molecular pathways was achieved. This method also allowed the identification of " homophilic cell adhesion" as one of the convergent pathways of ASD-relevant genes. Analyses of CDH11 and CDH9, two specific genes coding for homophilic cell adhesion molecules, revealed that CDH11, but not CDH9, was significantly co-expressed with hcASDs. In addition, Cdh11-null mice, but not Cdh9-null mice, were found to exhibit multiple autistic-like behavioral alterations.These results suggest that CDH11 is an important ASD risk gene. Results of this study also highlight the importance of considering matched gene features in the analysis of gene coexpression.Conventionally, genome-wide gene co-expression networks are constructed after setting an empirically determined threshold of CC 6 . A major limitation in most of these studies is lack of consideration of effects of confounding factors such as the size, expression level (mRNA abundance), and guanine-cytosine (GC) content of genes on the result of gene co-expression analysis (GCA) 11 . Most hcASDs are large genes with a higher expression level in the brain than in other tissues 12 . It is unclear whether the size or expression level of genes affect the result of GCA. It is also unknown whether convergent expression is specific to ASD risk genes or a common property of genes with similar features, such as large gene size and high mRNA abundance 11 . Some hcASDs code for adhesion molecules, such as members of neurexin and neuroligin families, which mediate pre-and post-synaptic adhesion, respectively, in ASD-related brain circuits 13,14 . Genetic variants of several other adhesion molecules, including classical and nonclassical cadherin family members, are also frequently found to be associated with ASD by GWAS 15 and WES studies [16][17][18][19] . Cadherin family members play important roles in multiple developmental processes, including cell proliferation, polarization, neuronal migration, axon projection, dendrite arborization, and synapse assembly, by mediating homophilic and heterophilic cell-cell interactions [20][21][22][23][24] . It is unclear as...

show abstract

Parent-reported and clinician-observed autism spectrum disorder (ASD) symptoms in children with attention deficit/hyperactivity disorder (ADHD): implications for practice under DSM-5

Cited by 140 publications

References 55 publications

Multidimensional Influences on Autism Symptom Measures: Implications for Use in Etiological Research

Multidimensional Influences on Autism Symptom Measures: Implications for Use in Etiological Research

Atomoxetine for attention deficit hyperactivity disorder in children and adolescents with autism: A systematic review and meta‐analysis

Association ofCDH11with ASD revealed by matched-gene co-expression analysis and mouse behavioral studies

Contact Info

Product

Resources

About