Trait-Based Dimensions Discriminating Adults with Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD) and, Co-occurring ADHD/ASD

Machine learning-enabled detection of attention-deficit/hyperactivity disorder with multimodal physiological data: a case-control study

BACKGROUND

Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psychiatric condition that typically emerges during childhood but often persists into adulthood, significantly impacting individuals' functioning, relationships, productivity, and overall quality of life. However, the current diagnostic process exhibits limitations that can significantly affect its overall effectiveness. Notably, its face-to-face and time-consuming nature, coupled with the reliance on subjective recall of historical information and clinician subjectivity, stand out as key challenges. To address these limitations, objective measures such as neuropsychological evaluations, imaging techniques and physiological monitoring of the Autonomic Nervous System functioning, have been explored.

METHODS

The main aim of this study was to investigate whether physiological data (i.e., Electrodermal Activity, Heart Rate Variability, and Skin Temperature) can serve as meaningful indicators of ADHD, evaluating its utility in distinguishing adult ADHD patients. This observational, case-control study included a total of 76 adult participants (32 ADHD patients and 44 healthy controls) who underwent a series of Stroop tests, while their physiological data was passively collected using a multi-sensor wearable device. Univariate feature analysis was employed to identify the tests that triggered significant signal responses, while the Informative k-Nearest Neighbors (KNN) algorithm was used to filter out less informative data points. Finally, a machine-learning decision pipeline incorporating various classification algorithms, including Logistic Regression, KNN, Random Forests, and Support Vector Machines (SVM), was utilized for ADHD patient detection.

RESULTS

Results indicate that the SVM-based model yielded the optimal performance, achieving 81.6% accuracy, maintaining a balance between the experimental and control groups, with sensitivity and specificity of 81.4% and 81.9%, respectively. Additionally, integration of data from all physiological signals yielded the best results, suggesting that each modality captures unique aspects of ADHD.

CONCLUSIONS

This study underscores the potential of physiological signals as valuable diagnostic indicators of adult ADHD. For the first time, to the best of our knowledge, our findings demonstrate that multimodal physiological data collected via wearable devices can complement traditional diagnostic approaches. Further research is warranted to explore the clinical applications and long-term implications of utilizing physiological markers in ADHD diagnosis and management.

Reproducibility between preschool and school-age Social Responsiveness Scale forms in the Environmental influences on Child Health Outcomes program

Evidence suggests core autism trait consistency in older children, but development of these traits is variable in early childhood. The Social Responsiveness Scale (SRS) measures autism-related traits and broader autism phenotype, with two age-dependent forms in childhood (preschool, 2.5-4.5 years; school age, 4-18 years). Score consistency has been observed within forms, though reliability across forms has not been evaluated. Using data from the Environmental Influences on Child Health Outcomes (ECHO) program (n = 853), preschool, and school-age SRS scores were collected via maternal report when children were an average of 3.0 and 5.8 years, respectively. We compared reproducibility of SRS total scores (T-scores) and agreement above a clinically meaningful cutoff (T-scores ≥ 60) and examined predictors of discordance in cutoff scores across forms. Participant scores across forms were similar (mean difference: 3.3 points; standard deviation: 7), though preschool scores were on average lower than school-age scores. Most children (88%) were classified below the cutoff on both forms, and overall concordance was high (92%). However, discordance was higher in cohorts following younger siblings of autistic children (16%). Proportions of children with an autism diagnoses were also higher among those with discordant scores (27%) than among those with concordant scores (4%). Our findings indicate SRS scores are broadly reproducible across preschool and school-age forms, particularly for capturing broader, nonclinical traits, but also suggest that greater variability of autism-related traits in preschool-age children may reduce reliability with later school-age scores for those in the clinical range.

Gaze measurements during viewing human dialogue scenes in adults with ADHD: Preliminary findings

AIM

Eye gaze measurement to human dialogue scenes in adults with attention deficit hyperactivity disorder (ADHD) was investigated. We examined whether eye gaze measurement might be a biological marker of ADHD.

METHODS

Twenty-two individuals with ADHD (mean age, 34.5 years) attending the outpatient clinic of Showa University Karasuyama Hospital were included in the study, and 26 healthy individuals (mean age, 32.6 years) with no history of mental disorders were used as the control group. For the participants, intellectual functioning was estimated using the Japanese Adult Reading Test, and mental symptoms were assessed using the Autism Spectrum Quotient and Conner's Adult ADHD Rating Scale. We extracted human dialogue scenes from two classic movies as visual stimuli and recorded the participant's gaze while watching these scenes using Tobii's eye tracker.

RESULTS

For gazing time, repeated measures analysis of variance showed no significant main effect of "group" and no significant interaction effect between "group" and areas of interest "(AOI)." In the normal group, gazing time at the eyes was significantly longer than those at the mouth, body, and background; in the ADHD group, gazing time at the eyes was significantly longer than only that at the background.

CONCLUSION

Given the different results obtained in the past in ASD, these results suggest that it would be necessary to directly compare the two groups to determine whether the gaze measurement shows significant differences in ASD and ADHD.

Personalized functional network mapping for autism spectrum disorder and attention-deficit/hyperactivity disorder

Autism spectrum disorder (ASD) and Attention-deficit/hyperactivity disorder (ADHD) are two typical neurodevelopmental disorders that have a long-term impact on physical and mental health. ASD is usually comorbid with ADHD and thus shares highly overlapping clinical symptoms. Delineating the shared and distinct neurophysiological profiles is important to uncover the neurobiological mechanisms to guide better therapy. In this study, we aimed to establish the behaviors, functional connectome, and network properties differences between ASD, ADHD-Combined, and ADHD-Inattentive using resting-state functional magnetic resonance imaging. We used the non-negative matrix fraction method to define personalized large-scale functional networks for each participant. The individual large-scale functional network connectivity (FNC) and graph-theory-based complex network analyses were executed and identified shared and disorder-specific differences in FNCs and network attributes. In addition, edge-wise functional connectivity analysis revealed abnormal edge co-fluctuation amplitude and number of transitions among different groups. Taken together, our study revealed disorder-specific and -shared regional and edge-wise functional connectivity and network differences for ASD and ADHD using an individual-level functional network mapping approach, which provides new evidence for the brain functional abnormalities in ASD and ADHD and facilitates understanding the neurobiological basis for both disorders.

SNAP-25 Polymorphisms in Autism Spectrum Disorder: A Pilot Study towards a Possible Endophenotype

While there is substantial agreement on the diagnostic criteria for autism spectrum disorder, it is also acknowledged that it has a broad range of clinical presentations. This can complicate the diagnostic process and aggravate the choice of the most suitable rehabilitative strategy for each child. Attentional difficulties are among the most frequently reported comorbidities in autism spectrum disorder. We investigated the role of SNAP-25 polymorphisms. Synaptosome-associated protein 25 (SNAP25) is a presynaptic membrane-binding protein; it plays a crucial role in neurotransmission and has already been studied in numerous psychiatric disorders. It was also seen to be associated with hyperactivity in children with autism spectrum disorder. We collected clinical, behavioral and neuropsychological data on 41 children with a diagnosis of autism spectrum disorder, and then genotyped them for five single-nucleotide polymorphisms of SNAP-25. Participants were divided into two groups according to the Autism Diagnostic Observation Schedule (ADOS-2) Severity Score. In the group with the highest severity score, we found significant associations of clinical data with polymorphism rs363050 (A/G): children with the GG genotype had lower total IQ, more severe autistic functioning and more attentional difficulties. Our research could be the starting point for outlining a possible endophenotype among patients with autism spectrum disorder who are clinically characterized by severe autistic functioning and significant attentional difficulties.

Fifty years of executive control research in attention-deficit/hyperactivity disorder:What we have learned and still need to know

For 50 years, attention-deficit/hyperactivity disorder (ADHD) has been considered a disorder of executive control (EC), the higher-order, cognitive skills that support self-regulation, goal attainment and what we generally call "attention." This review surveys our current understanding of the nature of EC as it pertains to ADHD and considers the evidence in support of eight hypotheses that can be derived from the EC theory of ADHD. This paper provides a resource for practitioners to aid in clinical decision-making. To support theory building, I draw a parallel between the EC theory of ADHD and the common gene-common variant model of complex traits such as ADHD. The conclusion offers strategies for advancing collaborative research.

Usefulness of the autism spectrum quotient (AQ) in screening for autism spectrum disorder and social communication disorder

BACKGROUND

In the Diagnostic and Statistical Manual and Mental Disorders, Fifth Edition (DSM-5), autism spectrum disorder (ASD) and social (pragmatic) communication disorder (SCD) were described as a new category of psychiatry nosography. SCD involves impairments in social communication and social interaction but not restricted, repetitive patterns of behavior, interests, or activities. The autism spectrum quotient (AQ) was developed to screen for autism tendencies in adults with normal intelligence. However, AQ cutoff scores for screening ASD and SCD in the DSM-5 have not been established. This study examined whether the Japanese version of the AQ (AQ-J) total scores could discriminate between an ASD group, an SCD group, and a neurotypical (NT) group.

METHODS

Participants were 127 ASD patients, 52 SCD patients, and 49 NT individuals. Receiver operating characteristic (ROC) analyses were used to examine AQ-J total score cutoff values to distinguish between ASD and NT groups, SCD and NT groups, and ASD and SCD groups.

RESULTS

In the ROC analysis for the ASD and NT groups, the area under the curve (AUC) was 0.96, and the optimum cutoff value was 23 points (sensitivity 92.9%, specificity 85.7%). The AUC for the SCD and NT groups was 0.89, and the optimum cutoff value was 22 points (sensitivity 84.6%, specificity 85.7%). The AUC for the ASD and SCD groups was 0.75; the optimum cutoff value was 32 points (sensitivity 67.7%, specificity 71.2%).

CONCLUSION

Our findings suggest the usefulness of the AQ-J in screening for ASD and SCD.

Differences between subclinical attention-deficit/hyperactivity and autistic traits in default mode, salience, and frontoparietal network connectivities in young adult Japanese

Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are associated with attentional impairments, with both commonalities and differences in the nature of their attention deficits. This study aimed to investigate the neural correlates of ADHD and ASD traits in healthy individuals, focusing on the functional connectivity (FC) of attention-related large-scale brain networks (LSBNs). The participants were 61 healthy individuals (30 men; age, 21.9 ± 1.9 years). The Adult ADHD Self-Report Scale (ASRS) and Autism Spectrum Quotient (AQ) were administered as indicators of ADHD and ASD traits, respectively. Performance in the continuous performance test (CPT) was used as a behavioural measure of sustained attentional function. Functional magnetic resonance imaging scans were performed during the resting state (Rest) and auditory oddball task (Odd). Considering the critical role in attention processing, we focused our analyses on the default mode (DMN), frontoparietal (FPN), and salience (SN) networks. Region of interest (ROI)-to-ROI analyses (false discovery rate < 0.05) were performed to determine relationships between psychological measures with within-network FC (DMN, FPN, and SN) as well as with between-network FC (DMN-FPN, DMN-SN, and FPN-SN). ASRS scores, but not AQ scores, were correlated with less frequent commission errors and shorter reaction times in the CPT. During Odd, significant positive correlations with ASRS were demonstrated in multiple FCs within DMN, while significant positive correlations with AQ were demonstrated in multiple FCs within FPN. AQs were negatively correlated with FPN-SN FCs. During Rest, AQs were negatively and positively correlated with one FC within the SN and multiple FCs between the DMN and SN, respectively. These findings of the ROI-to-ROI analysis were only partially replicated in a split-half replication analysis, a replication analysis with open-access data sets, and a replication analysis with a structure-based atlas. The better CPT performance by individuals with subclinical ADHD traits suggests positive effects of these traits on sustained attention. Differential associations between LSBN FCs and ASD/ADHD traits corroborate the notion of differences in sustained and selective attention between clinical ADHD and ASD.

Linehan's biosocial model applied to emotion dysregulation in autism: a narrative review of the literature and an illustrative case conceptualization

Emotion dysregulation (ED) is a transdiagnostic difficulty prevalent in autism spectrum condition (ASC). Importantly, recent research has suggested that ED is involved in self-harm and suicidality. Pre-existing models on the etiology of ED in ASC focus mainly on biological factors to ASC features, such as sensory sensitivities, poor flexibility, and sensitivity to change. However, although psychosocial factors seem to play a role in the emergence of ED in ASC as well (e.g., childhood maltreatment and camouflaging), there is a lack of a comprehensive model conceptualizing biosocial factors involved in ED in autistic people. Linehan's biosocial model (1993) is one of the leading etiological models of ED in borderline personality disorder (BPD). It conceptualizes ED as emerging from transactions between a pre-existing emotional vulnerability in the child and an invalidating developmental environment. Beyond its clinical relevance, Linehan's model has gathered empirical evidence supporting its pertinence in BPD and in other psychiatric disorders. Although ASC and BPD are two distinct diagnoses, because they may share ED, Linehan's biosocial model might be useful for understanding the development of ED in ASC. Hence, this article aims to provide an application and extension of Linehan's model to conceptualize ED in ASC. To do so, we conducted a narrative review of the literature on ED and its underlying factors in ASC from a developmental perspective. To investigate the pertinence of the biosocial model applied to ED in autistic people, we were interested on data on (i) ED and its behavioral correlates in ASC, in relation to the biosocial model, (ii) the potential biological and psychosocial correlates of ED in ASC and (iii) the overlapping difficulties in ASC and BPD. Finally, to assess the pertinence of the model, we applied it to the case of an autistic woman presenting with ED and suicidal behaviors. Our review and application to the case of an autistic woman suggest that ED in ASC encompasses factors related to both biological and psychosocial risk factors as conceptualized in the BPD framework, although in both domains ASC-specific factors might be involved.

Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder: Shared or Unique Neurocognitive Profiles?

Attention-deficit/hyperactivity (ADHD) and autism spectrum (ASD) disorders are commonly co-occurring conditions characterized by neurocognitive impairments. Few studies have directly compared neurocognitive profiles in ADHD and ASD and fewer still have controlled for comorbidity of ADHD and ASD. All direct comparisons have been in clinic samples, leaving the question of generalizability of results unaddressed. We compared neurocognitive performance in clinically ascertained ASD (n = 261) and ADHD (n = 423) cases and controls (n = 162), 6.0-17.9 years of age. We also compared ASD (n = 190) and ADHD (n = 926) cases ascertained in the community with controls (n = 14,842) of similar age. Using the stop-signal task (SST), we measured response inhibition (stop-signal reaction time-SSRT), sustained attention (defined as reaction time variability-RTV), and reaction time (RT). We controlled for comorbidity using ADHD and ASD trait scores and categorically-defined ADHD. Compared with controls, both clinic ADHD and ASD had significantly longer SSRT and RTV than controls and did not differ from each other. ADHD traits accounted for neurocognitive impairment in ASD, but not vice versa. There were no group differences for RT. Similar patterns of neurocognitive impairment were observed in the community sample. In the largest direct comparison of ADHD and ASD to date, we found impaired response inhibition and sustained attention in both disorders. However, neurocognitive impairment in ASD was almost completely accounted for by comorbid ADHD. Results generalized in the community sample indicating that referral bias alone did not drive results. Response inhibition and sustained attention likely play a role in ADHD and ASD.

The utility of the autism-spectrum quotient to screen for autism spectrum disorder in adults with attention deficit/hyperactivity disorder

The co-occurrence of attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) has been reported to be highly prevalent in adults. However, very few studies have assessed the usefulness of screening instruments to detect this co-occurrence, particularly when screening for ASD in the context of ADHD. Our study aimed at assessing the utility of the autism-spectrum quotient (AQ) as a screening tool of ASD in a sample of 153 adults referred for ADHD assessment. Our results showed that the AQ is of limited use in this context as its positive predictive value was low (47%). Particularly, the more severe the attentional deficits the more likely individuals with ADHD were to be misclassified as having a co-occurring ASD based on the AQ. However, the "imagination" subscale of the AQ was able to discriminate those who met ASD criteria from those who did not, suggesting that targeting imagination impairments might be useful when assessing for the ADHD+ASD co-occurrence in clinical settings.

Autistic Traits and Empathy in Children With Attention Deficit Hyperactivity Disorder, Autism Spectrum Disorder and Co-occurring Attention Deficit Hyperactivity Disorder/Autism Spectrum Disorder

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 vs. 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 behavioral 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.