Investigating attention-deficit hyperactivity disorder and autism spectrum disorder traits in the general population: What happens in adult life?

Artificial intelligence for children with attention deficit/hyperactivity disorder: a scoping review

Attention deficit/hyperactivity disorder is a common neuropsychiatric disorder that affects around 5%-7% of children worldwide. Artificial intelligence provides advanced models and algorithms for better diagnosis, prediction and classification of attention deficit/hyperactivity disorder. This study aims to explore artificial intelligence models used for the prediction, early diagnosis and classification of attention deficit/hyperactivity disorder as reported in the literature. A scoping review was conducted and reported in line with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. Out of the 1994 publications, 52 studies were included in the scoping review. The included articles reported the use of artificial intelligence for 3 different purposes. Of these included articles, artificial intelligence techniques were mostly used for the diagnosis of attention deficit/hyperactivity disorder (38/52, 79%). Magnetic resonance imaging (20/52, 38%) were the most frequently used data in the included articles. Most of the included articles used data sets with a size of <1,000 samples (28/52, 54%). Machine learning models were the most prominent branch of artificial intelligence used for attention deficit/hyperactivity disorder in the studies, and the support vector machine was the most used algorithm (34/52, 65%). The most commonly used validation in the studies was k-fold cross-validation (34/52, 65%). A higher level of accuracy (98.23%) was found in studies that used Convolutional Neural Networks algorithm. This review provides an overview of research on artificial intelligence models and algorithms for attention deficit/hyperactivity disorder, providing data for further research to support clinical decision-making in healthcare.

Network analysis of autism traits and problematic mobile phone use and their associations with depression among Chinese college students

The current study employed network analysis to examine the relationship between symptoms from factor level about autism traits and problematic mobile phone use (PMPU) and to explore their associations with depression. We measured the above three variables in 949 college students in China with Autism Spectrum Quotient (AQ), Smartphone Addiction Scale (SAS), Center for Epidemiological Studies Depression Scale (CES-D). Central and bridge symptoms were pinpointed through the examination of centrality index. In the AQ and PMPU network, results revealed that WD ("Withdrawal"), COR ("Cyberspace-oriented relationship") and OU ("Overuse") emerged as the core symptoms. AS ("Attention switching"), CO ("Communication") and COR ("Cyberspace-oriented relationship") were the most symptoms bridging the AQ and PMPU communities, suggesting that these symptoms could serve as focal points for interventions aimed at college students with concurrent autism traits and PMPU. SK ("Social skills"), COR ("Cyberspace-oriented relationship"), CO ("Communication"), and DLD ("Daily-life disturbance") were most strongly associated with depression. In addition, future research should consider various measurement tools and methods to investigate the location of AD ("Attention to detail"), because AD was an isolated symptom in the flow network of depression.

Where do neurodevelopmental conditions fit in transdiagnostic psychiatric frameworks? Incorporating a new neurodevelopmental spectrum

Features of autism spectrum disorder, attention-deficit/hyperactivity disorder, learning disorders, intellectual disabilities, and communication and motor disorders usually emerge early in life and are associated with atypical neurodevelopment. These "neurodevelopmental conditions" are grouped together in the DSM-5 and ICD-11 to reflect their shared characteristics. Yet, reliance on categorical diagnoses poses significant challenges in both research and clinical settings (e.g., high co-occurrence, arbitrary diagnostic boundaries, high within-disorder heterogeneity). Taking a transdiagnostic dimensional approach provides a useful alternative for addressing these limitations, accounting for shared underpinnings across neurodevelopmental conditions, and characterizing their common co-occurrence and developmental continuity with other psychiatric conditions. Neurodevelopmental features have not been adequately considered in transdiagnostic psychiatric frameworks, although this would have fundamental implications for research and clinical practices. Growing evidence from studies on the structure of neurodevelopmental and other psychiatric conditions indicates that features of neurodevelopmental conditions cluster together, delineating a "neurodevelopmental spectrum" ranging from normative to impairing profiles. Studies on shared genetic underpinnings, overlapping cognitive and neural profiles, and similar developmental course and efficacy of support/treatment strategies indicate the validity of this neurodevelopmental spectrum. Further, characterizing this spectrum alongside other psychiatric dimensions has clinical utility, as it provides a fuller view of an individual's needs and strengths, and greater prognostic utility than diagnostic categories. Based on this compelling body of evidence, we argue that incorporating a new neurodevelopmental spectrum into transdiagnostic frameworks has considerable potential for transforming our understanding, classification, assessment, and clinical practices around neurodevelopmental and other psychiatric conditions.

Young Adult ADHD Symptoms in the General Population and Neurocognitive Impairment

OBJECTIVE

Neurocognitive impairments are associated with child and adult ADHD in clinical settings. However, it is unknown whether adult ADHD symptoms in the general population are associated with the same pattern of cognitive impairment. We examined this using a prospective, population-based cohort spanning birth to age 25 years.

METHODS

We examined associations between self-reported adult ADHD symptoms and cognitive task performance (attention and response inhibition) in adulthood and childhood.

RESULTS

Self-rated ADHD symptoms at age 25 were associated with poorer performance in age 25 cognitive tasks capturing ADHD-related functioning (attention B = -0.03, 95% CI [0.05, -0.01], p = .005; response inhibition B = -0.03, 95% CI [-0.05, -0.01], p = .002).

CONCLUSIONS

Neurocognitive impairments linked to adult ADHD symptoms in the general population, are similar to those found in people with childhood ADHD symptoms and are consistent with findings in adult ADHD clinical samples.

ADHD-KG: a knowledge graph of attention deficit hyperactivity disorder

Purpose

Attention Deficit Hyperactivity Disorder (ADHD) is a widespread condition that affects human behaviour and can interfere with daily activities and relationships. Medication or medical information about ADHD can be found in several data sources on the Web. Such distribution of knowledge raises notable obstacles since researchers and clinicians must manually combine various sources to deeply explore aspects of ADHD. Knowledge graphs have been widely used in medical applications due to their data integration capabilities, offering rich data stores of information built from heterogeneous sources; however, general purpose knowledge graphs cannot represent knowledge in sufficient detail, thus there is an increasing interest in domain-specific knowledge graphs.

Methods

In this work we propose a Knowledge Graph of ADHD. In particular, we introduce an automated procedure enabling the construction of a knowledge graph that covers knowledge from a wide range of data sources primarily focusing on adult ADHD. These include relevant literature and clinical trials, prescribed medication and their known side-effects. Data integration between these data sources is accomplished by employing a suite of information linking procedures, which aim to connect resources by relating them to common concepts found in medical thesauri.

Results

The usability and appropriateness of the developed knowledge graph is evaluated through a series of use cases that illustrate its ability to enhance and accelerate information retrieval.

Conclusion

The Knowledge Graph of ADHD can provide valuable assistance to researchers and clinicians in the research, training, diagnostic and treatment processes for ADHD.

Genetic Overlap Between Midfrontal Theta Signals and Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder in a Longitudinal Twin Cohort

BACKGROUND

Cognitive control has been strongly linked to midfrontal theta (4-8 Hz) brain activity. Such control processes are known to be impaired in individuals with psychiatric conditions and neurodevelopmental diagnoses, including attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Temporal variability in theta, in particular, has been associated with ADHD, with shared genetic variance underlying the relationship. Here, we investigated the phenotypic and genetic relationships between theta phase variability, theta-related signals (the N2, error-related negativity, and error positivity), reaction time, and ADHD and ASD longitudinally in a large twin study of young adults to investigate the stability of the genetic relationships between these measures over time.

METHODS

Genetic multivariate liability threshold models were run on a longitudinal sample of 566 participants (283 twin pairs). Characteristics of ADHD and ASD were measured in childhood and young adulthood, while an electroencephalogram was recorded in young adulthood during an arrow flanker task.

RESULTS

Cross-trial theta phase variability in adulthood showed large positive phenotypic and genetic relationships with reaction time variability and both childhood and adult ADHD characteristics. Error positivity amplitude was negatively related phenotypically and genetically to ADHD and ASD at both time points.

CONCLUSIONS

We showed significant genetic associations between variability in theta signaling and ADHD. A novel finding from the current study is that these relationships were stable across time, indicating a core dysregulation of the temporal coordination of control processes in ADHD that persists in individuals with childhood symptoms. Error processing, indexed by the error positivity, was altered in both ADHD and ASD, with a strong genetic contribution.

Co-development of attention deficit hyperactivity disorder and autistic trait trajectories from childhood to early adulthood

BACKGROUND

Attention deficit hyperactivity disorder (ADHD) and autism, defined as traits or disorders, commonly co-occur. Developmental trajectories of ADHD and autistic traits both show heterogeneity in onset and course, but little is known about how symptom trajectories co-develop into adulthood.

METHODS

Using data from a population cohort, the Avon Longitudinal Study of Parents and Children, we examined correlations between ADHD and autistic traits across development, using the Social Communication Disorders Checklist and ADHD subscale of the Strengths and Difficulties Questionnaire. We modelled joint developmental trajectories of parent-reported ADHD and autistic traits between 4 and 25 years, then characterised trajectory classes based on sociodemographic, perinatal, psychopathology, cognition and social functioning variables and tested for associations with neurodevelopmental/psychiatric polygenic scores (PGS).

RESULTS

Three classes of trajectories were identified; a typically developing majority with low-stable ADHD-autistic traits (87%), a male-predominant subgroup with child/adolescent-declining traits (6%) and a subgroup with late-emerging traits (6%). ADHD-autistic trait correlations were greatest in young adulthood for the two nontypically developing classes. There were higher rates of emotional and conduct problems, low IQ, childhood seizures and poor social functioning in the declining and late-emerging classes compared to the low-stable class. Emotional, conduct and peer problems were more prevalent during childhood in the childhood/adolescent-declining class compared to other classes, but were more prevalent in young adulthood in the late-emerging class. Neurodevelopmental/psychiatric PGS also differed: both nontypically developing classes showed elevated ADHD PGS compared to the low-stable group, and the late-emerging group additionally showed elevated schizophrenia PGS and decreased executive function PGS, whereas the declining group showed elevated broad depression PGS.

CONCLUSIONS

Distinct patterns of ADHD-autism co-development are present across development in the general population, each with different characterising factors and genetic signatures as indexed by PGS.

Is quality of life related to high autistic traits, high ADHD traits and their Interaction? Evidence from a Young-Adult Community-Based twin sample

This study explored whether high autistic traits, high attention deficit hyperactivity disorder (ADHD) traits and their interaction were associated with quality of life (QoL) in a sample of 556 of young-adult twins (Mean age 22 years 5 months, 52% Female). Four participant groups were created: high autistic traits, high ADHD traits, high autistic/ADHD traits, and low ADHD/autistic traits. High autistic traits were associated with lower QoL across domains (physical, psychological, social, and environmental). High ADHD traits associated with lower physical, psychological, and environmental QoL. The interaction of autistic and ADHD traits was not significant in any domain. While mental health difficulties were associated with lower QoL, after accounting for mental health, most relationships between autistic traits, ADHD traits and QoL remained.

Diagnosing attention-deficit hyperactivity disorder (ADHD) using artificial intelligence: a clinical study in the UK

Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting a large percentage of the adult population. A series of ongoing efforts has led to the development of a hybrid AI algorithm (a combination of a machine learning model and a knowledge-based model) for assisting adult ADHD diagnosis, and its clinical trial currently operating in the largest National Health Service (NHS) for adults with ADHD in the UK. Most recently, more data was made available that has lead to a total collection of 501 anonymized records as of 2022 July. This prompted the ongoing research to carefully examine the model by retraining and optimizing the machine learning algorithm in order to update the model with better generalization capability. Based on the large data collection so far, this paper also pilots a study to examine the effectiveness of variables other than the Diagnostic Interview for ADHD in adults (DIVA) assessment, which adds considerable cost in the screenining process as it relies on specially trained senior clinicians. Results reported in this paper demonstrate that the newly trained machine learning model reaches an accuracy of 75.03% when all features are used; the hybrid model obtains an accuracy of 93.61%. Exceeding what clinical experts expected in the absence of DIVA, achieving an accuracy of 65.27% using a rule-based machine learning model alone encourages the development of a cost effective model in the future.

Early manifestations of genetic liability for ADHD, autism and schizophrenia at ages 18 and 24 months

Background

ADHD and autism are neurodevelopmental conditions, for which non-specific precursors or early signs include difficulties with language and motor skills, and differences in temperament in the first and second year of life. These early features have also been linked to later diagnosis of schizophrenia which is widely considered to have neurodevelopmental origins. Given that ADHD, autism and schizophrenia are all highly heritable, we tested the hypothesis that in the general population, measures of toddler language development, motor development and temperament are associated with genetic liability to ADHD, autism and/or schizophrenia.

Methods

Data were analysed from the Avon Longitudinal Study of Parents and Children (ALSPAC) which included motor development scores at age 18 months and language development and temperament scores at age 24 months (N=7498). Genetic liability was indexed by polygenic risk scores (PGS) for ADHD, autism and schizophrenia.

Results

ADHD PGS were associated with specific temperament scales (higher activity β=0.07, 95% CI=0.04, 0.09 and lower withdrawal β=-0.05, 95% CI=-0.07, -0.02) as well as better gross motor scores (β=0.04, 95% CI=0.01, 0.06). Schizophrenia PGS were associated with one specific temperament scale (negative mood β=0.04, 95% CI=0.02, 0.07). We did not find strong evidence of association of autism PGS with any of the toddler measures; there was also not strong evidence of association with motor or language delays for any of the PGS.

Conclusions

This study suggests that some specific aspects of early temperament and gross motor differences in the general population could represent part of the early manifestation of genetic liability to neurodevelopmental conditions.

Genetics of Attention-Deficit Hyperactivity Disorder

Attention-Deficit Hyperactivity Disorder (ADHD) has long been recognized as being a highly heritable condition and our understanding of the genetic contributions to ADHD has grown over the past few decades. This chapter will discuss the studies that have examined its heritability and the efforts to identify specific genetic risk-variants at the molecular genetic level. We outline the various techniques that have been used to characterize genetic contributions to ADHD, describing what we have learnt so far, what there is still to learn and the methodologies that can be used to further our knowledge. In doing so we will discuss research into rare and common genetic variants, polygenic risk scores, and gene-environment interplay, while also describing what genetic studies have revealed about the biological processes involved in ADHD and what they have taught us about the overlap between ADHD and other psychiatric and somatic disorders. Finally, we will discuss the strengths and limitations of the current methodologies and clinical implications of genetic research to date.

"Late-onset" ADHD symptoms in young adulthood: Is this ADHD?

Objective: We investigated whether "late-onset" ADHD that emerges in adolescence/adulthood is similar in risk factor profile to: (1) child-onset ADHD, but emerges later because of scaffolding/compensation from childhood resources; and (2) depression, because it typically onsets in adolescence/adulthood and shows symptom and genetic overlaps with ADHD. Methods: We examined associations between late-onset ADHD and ADHD risk factors, cognitive tasks, childhood resources and depression risk factors in a population-based cohort followed-up to age 25 years (N=4224-9764). Results: Parent-rated late-onset ADHD was like child-onset persistent ADHD in associations with ADHD polygenic risk scores and cognitive task performance, although self-rated late-onset ADHD was not. Late-onset ADHD was associated with higher levels of childhood resources than child-onset ADHD and did not show strong evidence of association with depression risk factors. Conclusions: Late-onset ADHD shares characteristics with child-onset ADHD when parent-rated, but differences for self-reports require investigation. Childhood resources may delay the onset of ADHD.

Autism Spectrum Disorder and IQ - A Complex Interplay

Autism spectrum disorder (ASD) is characterized as a very heterogeneous child-onset disorder, whose heterogeneity is partly determined by differences in intelligence quotient (IQ). Older epidemiological studies suggested that the IQ-related spectrum tends to be skewed to the left, i.e., a larger proportion of individuals with ASD have below average intelligence, while only few individuals with ASD may have an IQ above average. This picture changed over time with broadening the spectrum view. Within the present perspective article, we discuss discrepancies in IQ profiles between epidemiological and clinical studies and identify potential underlying aspects, for example, the influence of external factors such as sample biases or differences in availability of autism health services. Additionally, we discuss the validity and reciprocal influences of ASD diagnostics and IQ measurement. We put the impact of these factors for diagnostic as well as care and support situations of patients into perspective and want to encourage further research to contribute to the conceptualization of "autism" more comprehensively including the IQ as well as to examine broader (life) circumstances, interacting factors and diagnostic requirements of given diagnoses in childhood as compared to adulthood.

Exploring ADHD Symptoms and Associated Impairment across Development

OBJECTIVE

ADHD symptoms typically decline with age, but less is known about whether the presentation of specific ADHD symptoms differs across development. This study aimed to examine the frequency and associated impairment of specific ADHD symptoms in childhood, adolescence, and young adulthood.

METHOD

A prospective, longitudinal cohort, the Avon Longitudinal Study of Parents and Children, was utilized (N = 2,327). ADHD symptoms and impairment were assessed using the Development and Well Being Assessment at ages 7, 15, and 25.

RESULTS

Specific ADHD symptom frequencies and their associated impairment varied across development for the majority of symptoms, although easily distracted was one of the most commonly reported symptoms at each age, and difficulty sustaining attention was consistently associated with high levels of impairment.

CONCLUSION

These findings suggest differences in the presentations of ADHD symptoms across development: current understanding of how ADHD presents in childhood/adolescence may not be generalizable to young adulthood.

Association of bisphenol A, bisphenol F, and bisphenol S with ADHD symptoms in children

BACKGROUND

Bisphenol A (BPA) has been linked to attention-deficit/hyperactivity disorder (ADHD) symptoms, but the neurotoxic effects of bisphenol substitutes such as bisphenol F (BPF) and S (BPS) have not been well investigated. We investigated the associations between BPA, BPF, and BPS with ADHD symptoms at multiple time points in children.

METHODS

The levels of BPA (at ages 4, 6, and 8), BPF (at ages 6 and 8), and BPS (at ages 6 and 8) were measured in 619 children. Because of the low detection frequency of BPF and BPS levels, participants were divided into categories (<or ≥ limit of detection (LOD) for BPF; < LOD, ≥ LOD and < median, or ≥ median for BPS). ADHD symptoms were assessed using the ADHD Rating Scale IV (ARS). The relationship between bisphenols and ARS scores was analyzed using Poisson regression models, and generalized additive models and piecewise regression models were further explored for BPA.

RESULTS

BPA was detected in most participants (>97%), whereas BPF and BPS were less frequently detected (age 6: 17.5% for BPF and 42.0% for BPS; age 8: 51.6% for BPF and 73.3% for BPS). Doubling in BPA levels was associated with increased ARS scores by 4.7% (95% confidence intervals [CI]: 0.5, 9.2) at age 6. The association was greater with BPA levels higher than 3.0 μg/g creatinine (24.2% [95% CI: 15.5, 33.6] increase). The BPF ≥ LOD group had 10.8% (95% CI: 1.2, 21.4) higher ARS scores than the BPF < LOD group. The BPS ≥ median group had 11.4% (95% CI: 2.0, 21.7) higher ARS scores than the BPS < LOD group.

CONCLUSION

All bisphenols, in particular those at or above the LOD or median levels, were associated with ADHD symptoms at age 6. Further prospective studies are warranted to determine causal inference.

The association of prenatal and childhood pyrethroid pesticide exposure with school-age ADHD traits

BACKGROUND

Pyrethroid insecticides are commonly used in residential settings, and their use has increased rapidly. Although research has been scarce, they have been reported to be associated with impaired neurodevelopment. Moreover, susceptible exposure windows and the long-term effects of pyrethroids have not been investigated. We examined the association between pyrethroid exposure and attention-deficit/hyperactivity disorder (ADHD) symptoms over time, with exposure windows spanning from the prenatal period to school-age.

METHODS

Using 524 mother-child pairs, we measured urinary concentrations of 3-phenoxybenzoic acid (3-PBA), a major pyrethroid metabolite, and asked parents to fill-out the ADHD Rating Scale IV (ARS). We used Poisson regression to identify the susceptible periods of pyrethroid exposure, by correlating various 3-PBA exposure windows (prenatal, ages 2, 4, 6 and 8) with ADHD symptoms at ages 6 and 8.

RESULTS

Doubling of prenatal and age 2 3-PBA concentrations was associated with increased ADHD symptoms at age 6 (2.7% change, 95% confidence interval [CI]: 0.3, 5.2; 5.2% change [95% CI: 0.5, 10.2], respectively). The 3-PBA concentrations at age 4 and age 6 were linked with ADHD symptoms at age 8 (2.7% change [95% CI: 0.3, 5.3]; 3.3% change [95% CI: 0.2, 6.4], respectively). There were no clear sex-specific patterns in association.

DISCUSSION

Both prenatal and early-childhood exposure to 3-PBA were found to be associated with ADHD symptoms. Exposure during pregnancy, and at ages 2 to 6 were found to be susceptible periods for pyrethroid neurotoxicity at ages 6 and 8.

Variable Emergence of Autism Spectrum Disorder Symptoms From Childhood to Early Adulthood

OBJECTIVE

Autism spectrum disorder (ASD) is currently considered an early-onset neurodevelopmental condition. Follow-up studies of clinic-ascertained autism suggest that autistic symptoms typically decline with age, although symptom improvement is limited for some. To date there have been no population-based prospective studies investigating the natural history of autistic symptoms from childhood to adulthood. The aim of this study was to characterize the development and heterogeneity of autistic symptoms in a population-based cohort from childhood to age 25.

METHODS

Data were analyzed in a prospective U.K. population-based cohort (ALSPAC). Trajectories were derived using five assessments of the parent-rated Social and Communication Disorders Checklist (SCDC) spanning ages 7-25. Additional measures were used to validate symptom trajectories.

RESULTS

Three distinct SCDC symptom trajectory classes were identified: low (88.5%), declining (5.0%), and late-emerging (6.5%). Both the declining and late-emerging trajectory classes were associated with child and adult ASD measures, low IQ, communication problems, peer problems, and worse adult functioning compared with the low trajectory class. Male sex was associated with a higher likelihood of being in the declining trajectory class (odds ratio=2.84, 95% CI=2.19, 3.69). This sex difference was not observed in the late-emerging class (odds ratio=1.00, 95% CI=0.80, 1.24) compared with the low trajectory class.

CONCLUSIONS

ASD symptom levels that emerged early tended to decline across development, although impairment was still present in adulthood for some. For others, autistic symptoms emerged across adolescence and adulthood. This challenges our current understanding that ASD symptoms inevitably first manifest early in development.

Mapping relationships between ADHD genetic liability, stressful life events, and ADHD symptoms in healthy adults

Attention-deficit/hyperactivity disorder (ADHD) symptoms are continuously distributed in the general population, where both genetic and environmental factors play roles. Stressful life events (SLEs) have been associated with ADHD diagnosis, but the relationship between ADHD genetic liability, SLEs, and ADHD symptoms in healthy individuals is less clear. Using a sample of 1,531 healthy adults (average age 26.9 years; 55.8% female), we investigated relationships between ADHD polygenic risk scores (ADHD-PRSs), SLEs, and ADHD symptoms in a general population sample. Confirming earlier findings in an overlapping sample, all SLE-measures assessed (lifetime SLEs, recent SLEs, and childhood trauma (CT)) were significantly correlated with total ADHD, inattention (IA), and hyperactivity-impulsivity (HI) scores (r² range = .08-.15; all p < .005). ADHD-PRSs was associated with HI (R²_best-fit  = .37%), lifetime SLEs (R²_best-fit  = .56%), and CT (R²_best-fit  = .40%). Mediation analyses showed that lifetime SLEs partially mediated the association between ADHD-PRSs and HI (indirect effect: β = 68.6, bias corrected accelerated 95% confident interval (BCa95%CI) [11.9, 131.0], p = .016, proportion mediated (P_M ) =19.5%), with strongest effects contributed by CT (β = 34.4, BCa95%CI [0.4, 76.5], p = .040, P_M  = 9.8%). On the other hand, HI partially mediated the association between the ADHD-PRSs and lifetime SLEs (β = 42.9, BCa95%CI [7.3, 83.9], p = .014, P_M  = 18.8%). Our study observed a complex relationship of genetic and environmental risk factors contributing to ADHD symptoms in the healthy adult population.