Paired Pulse Suppression and Prepulse Inhibition in Patients with Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder

Children with Autism Spectrum Disorder (ASD) or Attention Deficit Hyperactivity Disorder (ADHD) have shown an increased risk for violence and victimization. However, research on exposure to multiple forms of victimization in different contexts are scarce. Hence, the current aim is to review the evidence about polyvictimization among children with ASD or ADHD. PsycInfo, ERIC, ERC, Scopus, and PubMed databases were systematically searched until 12 March 2019 to identify empirical studies with reported prevalence rates of at least four forms of victimization among children with ASD or ADHD. A total of 6/1300 articles were included in the review, ranging in sample sizes from 92 to 4114. The reported prevalence rates for polyvictimization were 1.8% and 23.1% for children with ASD and 7.3% for children with ADHD. The results emphasize the high prevalence of violence and victimization, including polyvictimization, among children with ASD or ADHD. Polyvictimization among children with ASD or ADHD is a highly under researched area. Significant knowledge gaps and important methodological considerations that provide important implications for future research include lack of information on cyber bullying, frequency or intensity of victimization, and the failure to include children as informants and to report health outcomes associated with polyvictimization.

Attention problems are common in youngsters with attention deficit hyperactivity disorder (ADHD) as well as in adolescents with combined autism spectrum disorder (ASD) and ADHD. However, it is unknown whether there is psychophysiological overlap and/or a difference in electroencephalogram (EEG) power spectra between ADHD and comorbid ASD and ADHD (ASD + ADHD), on and off stimulant medication. To explore potential differences and overlap, measures of theta and beta power in adolescents diagnosed with ADHD (n = 33) versus adolescents with combined ASD + ADHD (n = 20), categorized by stimulant medication use (57 % of the total sample), were compared. EEG measures were acquired in three conditions: (1) resting state, eyes closed (2) resting state, eyes open and (3) during an oddball task. In addition, performance on the d2 attention test was analyzed. Adolescents with ADHD displayed more absolute theta activity than adolescents with ASD + ADHD during the eyes open and task conditions, independent of stimulant medication use. In addition, only the adolescents with ADHD showed an association between diminished attention test performance and increased theta in the eyes open condition. Results of the current study suggest that although there is behavioral overlap between ADHD characteristics in adolescents with ADHD and adolescents with combined ASD + ADHD, the underlying psychophysiological mechanisms may be different. Adolescents with ASD + ADHD exhibited fewer of the EEG physiological signs usually associated with ADHD, although there was an overlap in attentional problems between the groups. This may indicate that treatments developed for ADHD work differently in some adolescents with ASD + ADHD and adolescents with ADHD only.

Attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are two highly heritable neurodevelopmental disorders. Several lines of evidence point towards the presence of shared genetic factors underlying ASD and ADHD. We conducted genomic analyses of common risk variants (i.e. single nucleotide polymorphisms, SNPs) shared by ASD and ADHD, and those specific to each disorder. With the summary data from two GWAS, one on ASD (N=46,350) and another on ADHD (N=55,374) individuals, we used genomic structural equationmodelling and colocalization analysis to identify SNPs shared by ASD and ADHD and SNPs specific to each disorder. Functional genomic analyses were then conducted on shared and specific common genetic variants. Finally, we performed a bidirectional Mendelian randomization analysis to test whether the shared genetic risk between ASD and ADHD was interpretable in terms of reciprocal relationships between ASD and ADHD. We found that 37.5% of the SNPs associated with ASD (at p<1e-6) colocalized with ADHD SNPs and that 19.6% of the SNPs associated with ADHD colocalized with ASD SNPs. We identified genes mapped to SNPs that are specific to ASD or ADHD and that are shared by ASD and ADHD, including two novel genes INSM1 and PAX1. Our bidirectional Mendelian randomization analyses indicated that the risk of ASD was associated with an increased risk of ADHD and vice versa. Using multivariate genomic analyses, the present study uncovers shared and specific genetic variants associated with ASD and ADHD. Further functional investigation of genes mapped to those shared variants may help identify pathophysiological pathways and new targets for treatment.

Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorders (ASD) are two of the most represented neurodevelopmental conditions in childhood. The diagnostic shift introduced by the DSM-5, allowing a combined diagnosis of ADHD and ASD, poses different clinical challenges related to diagnostic overshadowing, accuracy of clinical judgment and potential delay in an ASD diagnosis in children presenting with ADHD. Here we tried to disentangle the clinical phenotype and specificity of the two co-occurring conditions in relation to autism traits and empathy, by comparing children with ASD with and without comorbid ADHD with children presenting ADHD only and children with typical development. The child versions of the Autism Quotient (C-AQ) and Empathy Quotient (C-EQ) were administered to a total sample of 198 male children between 6 and 14 years old with age appropriate language skills and normal intelligence. Univariate analysis demonstrated no significant differences in the C-AQ total and subscale scores as well as the C-EQ between children with ASD and children with ASD+ADHD, while children with ADHD alone presented an intermediate phenotype between ASD and TD. Furthermore, a receiver operating characteristic (ROC) analysis was applied to discriminate among the different phenotypes. We found that the C-AQ and C-EQ were accurate at distinguishing with satisfactory reliability between: a) ASD versus non- ASD (N-ASD) groups comprising both ADHD and TD children (Area Under the Curve AUC 88% for C-AQ and 81% for C-EQ); b) ASD and TD (AUC 92% for C-AQ and 95% for C-EQ); c) ASD and ADHD (AUC 80% for C-AQ and 68% for C-EQ). Our data confirm the reliability of the C-AQ and C-EQ as behavioural markers to differentiate ASD (regardless of comorbid ADHD) from an ADHD condition and TD. Interestingly, in our sample an ADHD condition does not increase the severity of the clinical phenotype in terms of autism traits distribution and empathy, suggesting that the psychological measures detected by the two quantitative instruments are independent of ADHD traits. This evidence will contribute to the translational efforts in developing better tailored treatments and preventive strategies.

Risky driving behavior among individuals with Autism, ADHD, and typically developing persons

Multiple subependymal pseudocysts in neonates play a role in later attention deficit hyperactivity and autistic spectrum disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by impairments in social interaction and communication and by the presence of restrictive, repetitive behavior. Attention deficit hyperactivity disorder (ADHD) is another common lifelong neurodevelopmental disorder characterized by three major presentations: predominantly hyperactive/impulsive, predominantly inattentive, and combined. Although ASD and ADHD are different clinical diagnoses, they share various common characteristics, including male dominance, early childhood onset, links to prenatal and perinatal factors, common comorbidity for each other, and, often, persistence into adulthood. They also have both unique and shared risk factors, which originate in early life and have lifelong implications on the affected individuals and families and society. While genetic factors contribute to ASD and ADHD risk, the environmental contribution to ASD and ADHD has been recognized as having potentially equal importance, which raises the hope for early prevention and intervention. Maternal folate levels, maternal metabolic syndrome, and metabolic biomarkers have been associated with the risk of childhood ASD; while maternal high-density lipoprotein, maternal psychosocial stress, and in utero exposure to opioids have been associated with the risk of childhood ADHD. As for shared factors, male sex, preterm birth, placental pathology, and early life exposure to acetaminophen have been associated with both ASD and ADHD. The high rate of comorbidity of ASD and ADHD and their many shared early life risk factors suggest that early identification and intervention of common early life risk factors may be cost-effective to lower the risk of both conditions. Efforts to improve maternal preconception, prenatal, and perinatal health will not only help reduce adverse reproductive and birth outcomes but will also help mitigate the risk of ASD and ADHD associated with those adverse early life events.

Few studies suggest possible links between attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and Alzheimer’s disease but they have been limited by small sample sizes, diagnostic and recall bias. We used two-sample Mendelian randomization (MR) to estimate the bidirectional causal association between genetic liability to ADHD and ASD on Alzheimer’s disease. In addition, we estimated the causal effects independently of educational attainment and IQ, through multivariable Mendelian randomization (MVMR). We employed genetic variants associated with ADHD (20,183 cases/35,191 controls), ASD (18,381 cases/27,969 controls), Alzheimer’s disease (71,880 cases/383,378 controls), educational attainment (n = 766,345) and IQ (n = 269,867) using the largest GWAS of European ancestry. There was limited evidence to suggest a causal effect of genetic liability to ADHD (odds ratio [OR] = 1.00, 95% CI: 0.98–1.02, P = 0.39) or ASD (OR = 0.99, 95% CI: 0.97–1.01, P = 0.70) on Alzheimer’s disease. Similar causal effect estimates were identified as direct effects, independent of educational attainment (ADHD: OR = 1.00, 95% CI: 0.99–1.01, P = 0.76; ASD: OR = 0.99, 95% CI: 0.98–1.00, P = 0.28) and IQ (ADHD: OR = 1.00, 95% CI: 0.99–1.02. P = 0.29; ASD: OR = 0.99, 95% CI: 0.98–1.01, P = 0.99). Genetic liability to Alzheimer’s disease was not found to have a causal effect on risk of ADHD or ASD (ADHD: OR = 1.12, 95% CI: 0.86–1.44, P = 0.37; ASD: OR = 1.19, 95% CI: 0.94–1.51, P = 0.14). We found limited evidence to suggest a causal effect of genetic liability to ADHD or ASD on Alzheimer’s disease; and vice versa.

Children with Down syndrome (DS) are more likely to be diagnosed with co-existing conditions, such as autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD). However, the correlation has not been fully delineated to date. Our study aimed to examine the associations of DS with ASD and ADHD in children and adolescents using a national population-based database. In this cross-sectional study, we included a total of 214,300 children aged 3-17 years from the National Health Interview Survey. Physician-diagnosed DS, ASD and ADHD were reported during an in-person household interview. Logistic regression with survey sampling weights was used to estimate the odds ratios (ORs) of ASD and ADHD, along with 95% confidence intervals (CIs). Among the 214,300 children, 329 were identified as having DS. Among those, 21 children were diagnosed with ASD, 48 with ADHD, and 6 exhibited co-existing ASD and ADHD. After adjusting for demographic factors, compared to those without DS, the ORs of ASD, ADHD and the co-occurrence of ASD and ADHD in children with DS were 5.40 (95% CI: 3.04-9.59), 1.72 (95% CI: 1.17-2.53), and 3.45(95% CI:1.29-9.20), respectively. Stratified analysis revealed that significant associations of DS with ASD and ADHD were detected for both male and female, but an interaction effect was only observed between sex and ASD (P < 0.001). Our study confirmed that children with DS are more likely to have comorbidities of ASD and ADHD than the general population, and these comorbidities may vary by sex.

BackgroundSuperior visual search is a replicated finding in the literature on Autism Spectrum Disorder (ASD). Conversely, results from the literature on Attention-Deficit/Hyperactivity Disorder (ADHD) are more mixed, with some studies showing typical performance and others pointing out less efficient serial search in ADHD. Finally, most studies on visual search in Schizophrenia highlighted deficits in focal attentional processing. However, similarities between attentional impairments in the three clinical groups have also been reported. The primary goal of our study is to determine the diagnostic specificity of search deficits. To our knowledge, the literature systematically comparing the visual search performance in patients with ADHD and Schizophrenia is limited to one study, while no study has so far included an ASD group in the comparison.MethodsFour groups of young adults, namely 29 typically developing (TD; 19.8±1.6, 41% males), 26 with ASD (19.7±1.9, 96% males), 28 with ADHD (19.9±1.4, 54% males) and 21 with Early-Onset Schizophrenia (SCZ; 19.7±1.7, 71% males) were presented a visual search task in which they had to quickly detect a target item among several similar-to-target distractor items. Eye movements were recorded binocularly with the Eye Link 1000+ system. Participants were matched on age and full-scale IQ. The ocular-motor behaviour was analysed using Data Viewer 3.2 and SPSS 2.3.ResultsInitiation of search – latency of the first saccade on the search grid – was typical in all participants except those with SCZ, who had significant higher intra-subject variability (ISV) than both TD and ADHD, but no delay in initiating search. Within search, ASD manifested significantly reduced mean and ISV of total search duration – between the first saccade on the grid and the last fixation on target – and of the first part of search – between the first saccade on the grid and the first fixation on target – in comparison with all other groups, including TD. Conversely, SCZ and ASD were significantly more variable than TD and ADHD regarding the duration of first fixation on target, while also being, to a lesser extent, slower than ADHD, but not than TD. Additionally, SCZ needed a higher frequency of fixations on target than ASD, but not compared to ADHD or TD, before making a decision. In the post-search phase – between the onset of the last fixation on target and the button press on the keyboard – SCZ were the slowest and most variable group, followed by ASD and ADHD who differed?non-significantly? from controls. The overall search performance – between trial onset and button press – resulted in typical manual mean RT in ASD and ADHD while being atypically longer in SCZ, compared to all other groups. Compared to TD, ISV was at par in ADHD, lower in ASD, and higher in SCZ.DiscussionResults suggest that the ability to extract individual targets is intact in ASD and ADHD. However, ASD only show a bias toward local information, as indicated by more variable first fixation duration, despite intact global processing. By contrast, lower search efficiency in SCZ might be explained by both (a) abnormal global processing due to impairment in the guidance mechanisms that affect the time until the first fixation on target, and (b) a deficit in central discrimination, with resulting difficulties in extracting critical features of the target.

Despite the high coexistence of autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) (ASD + ADHD), the underlying neurobiologicalbasis of this disorder remains unclear. Altered brain structural asymmetries have been verified in ASD and ADHD, respectively, making brain asymmetry a candidate for characterizing this coexisting disorder. Here, we measured the gray matter (GM) volume asymmetry in ASD + ADHD versus ASD without ADHD (ASD-only), ADHD without ASD (ADHD-only), and typically developing controls (TDc). High-resolutionT1-weighted data from 48 ASD + ADHD, 63 ASD-only, 32 ADHD-only, and 211 matched TDc were included in our study. We also assessed brain-behavior relationships and the effects of age on GM asymmetry. We found that there were both shared and disorder-specific GM volume asymmetry alterations in ASD + ADHD, ASD-only, and ADHD-only compared with TDc. This finding demonstrates that ASD + ADHD is neither an endophenocopy nor an additive pathology of ASD and ADHD, but an entirely different neuroanatomical pathology. In addition, ASD + ADHD displayed altered GM volume asymmetries in the prefrontal regions responsible for executive function and theory of mind compared with ASD-only. We also found significant effects of age on GM asymmetry. The present study may provide structural insights into the neural basis of ASD + ADHD.

Autism spectrum disorders (ASD) and attention deficit/hyperactivity disorder (ADHD) are very common developmental disorders which share some similar symptoms of social, emotional, and attentional deficits. This study is aimed to help understand the differences and similarities of these deficits using analysis of dense-array event-related potentials (ERP) during an illusory figure recognition task. Although ADHD and ASD seem very distinct, they have been shown to share some similarities in their symptoms. Our hypothesis was that children with ASD will show less pronounced differences in ERP responses to target and non-target stimuli as compared to typical children, and to a lesser extent, ADHD. Participants were children with ASD (N=16), ADHD (N=16), and controls (N=16). EEG was collected using a 128 channel EEG system. The task involved the recognition of a specific illusory shape, in this case a square or triangle, created by three or four inducer disks. There were no between group differences in reaction time (RT) to target stimuli, but both ASD and ADHD committed more errors, specifically the ASD group had statistically higher commission error rate than controls. Post-error RT in ASD group was exhibited in a post-error speeding rather than corrective RT slowing typical for the controls. The ASD group also demonstrated an attenuated error-related negativity (ERN) as compared to ADHD and controls. The fronto-central P200, N200, and P300 were enhanced and less differentiated in response to target and non-target figures in the ASD group. The same ERP components were marked by more prolonged latencies in the ADHD group as compared to both ASD and typical controls. The findings are interpreted according to the "minicolumnar" hypothesis proposing existence of neuropathological differences in ASD and ADHD, specifically minicolumnar number/width morphometry spectrum differences. In autism, a model of local hyperconnectivity and long-range hypoconnectivity explains many of the behavioral and cognitive deficits present in the condition, while the inverse arrangement of local hypoconnectivity and long-range hyperconnectivity in ADHD explains some deficits typical for this disorder. The current ERP study supports the proposed suggestion that some between group differences could be manifested in the frontal ERP indices of executive functions during performance on an illusory figure categorization task.

Identifying Loci for the Overlap Between Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Using a Genome-wide QTL Linkage Approach

BackgroundSchizophrenia (SCZ) is a clinically and genetically heterogeneous disorder that shares genetic factors with autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). A genome-wide association study (GWAS) differentiating ADHD from ASD was performed recently. Although genetic correlations of regional cortical structures with the risk of SCZ, ASD, and ADHD have been identified, no study has yet investigated the genetic correlations between the genetic factor differentiating ADHD from ASD and brain cortical structures or whether this genetic factor influences cognitive functions and brain cortical structures in patients with SCZ.Aims & ObjectivesGiven the clinical and genetic heterogeneity of SCZ and its significant overlap with ASD and ADHD, our study focuses specifically on SCZ to better understand the distinct genetic contributions to cognitive impairments and cortical abnormalities within this population. By isolating SCZ as the primary condition, we aim to elucidate the unique and shared genetic underpinnings that differentiate it from other neurodevelopmental disorders.The significance of this study lies in its potential to unravel the specific genetic influences on cognitive impairments and cortical abnormalities in SCZ. By exploring the polygenic risk scores (PRSs) differentiating ADHD from ASD, we aim to contribute to the understanding of the genetic architecture that impacts cognitive functions and brain structures in SCZ. This could lead to more precise diagnostic tools and personalized treatment strategies, ultimately improving outcomes for individuals with SCZ.MethodBased on the GWAS data (9,315 ASD and 11,964 ADHD patients), PRSs differentiating ADHD from ASD (indicating a greater risk of ADHD and a lower risk of ASD) were calculated for SCZ patients (n=168). Cognitive performance, including verbal comprehension (VC), perceptual organization (PO), working memory (WM), and processing speed (PS), was assessed using the WAIS-III (n=145). The surface areas and cortical thicknesses of 34 bilateral brain regions were extracted using FreeSurfer (n=126). We examined the associations of these PRSs with cognitive performance and cortical structures in SCZ patients.ResultsAmong the four cognitive domains, a higher PRS, indicating a greater risk of ADHD, was associated with impaired WM in SCZ patients (beta=-0.21, p=0.012). A lower PRS, indicating a greater risk of ASD, was associated with decreased surface areas of the left medial orbitofrontal (beta=0.21, p=8.29×10-4), left entorhinal (beta=0.21, p=0.025), left postcentral (beta=0.18, p=7.52×10-3), right fusiform (beta = 0.17, p = 6.64×10-3), and left fusiform cortices (beta=0.17, p=7.77×10-3) in SCZ patients. A higher PRS, indicating a greater risk of ADHD, was associated with decreased cortical thickness in the bilateral transverse temporal regions (left, beta=-0.17, p=0.039; right, beta=-0.17, p=0.045).Discussion & ConclusionsOur study revealed a relationship between genetic factors that differentiate ADHD patients from ASD patients and both cortical structure and cognitive performance in SCZ patients. These findings suggest that the heterogeneity of SCZ might be partly derived from genetic factors related to neurodevelopmental and psychiatric disorders other than SCZ.

Advances in Our Understanding of Genetic Risk Factors for Autism Spectrum Disorders