Similar Subgroups Based on Cognitive Performance Parse Heterogeneity in Adults With ADHD and Healthy Controls

Finding Similarities in Differences Between Autistic Adults: Two Replicated Subgroups

Autism is heterogeneous, which complicates providing tailored support and future prospects. We aim to identify subgroups in autistic adults with average to high intelligence, to clarify if certain subgroups might need support. We included 14 questionnaire variables related to aging and/or autism (e.g., demographic, psychological, and lifestyle). Community detection analysis was used for subgroup identification in an original sample of 114 autistic adults with an adulthood diagnosis (autism) and 58 non-autistic adults as comparison group (COMP), and a replication sample (NAutism = 261; NCOMP = 287), both aged 30-89 years. Next, we identified subgroups and assessed external validity (for cognitive and psychological difficulties, and quality of life [QoL]) in the autism samples. To test specificity, we repeated the analysis after adding 123 adults with ADHD, aged 30-80 years. As expected, the autism and COMP groups formed distinct subgroups. Among autistic adults, we identified three subgroups of which two were replicated. One of these subgroups seemed most vulnerable on the cluster variables; this subgroup also reported the most cognitive and psychological difficulties, and lowest QoL. Adding the ADHD group did not alter results. Within autistic adults, one subgroup could especially benefit from support and specialized care, although this must be tested in future studies.

Identifying subgroups of attention-deficit/hyperactivity disorder from the psychopathological and neuropsychological profiles

The Research Domain Criteria (RDoC) advocates the dimensional approach in characterizing mental disorders. We followed RDoC to characterize children with ADHD using profiling based on the cognitive and psychopathological domains. We aimed to identify and validate ADHD subtypes with different clinical characteristics and functional impairments. We recruited 362 drug-naïve children with ADHD and 103 typically developing controls. The cluster analysis was used to identify subgroups based on the Child Behaviour Checklist (CBCL) and the Behaviour Rating Inventory of Executive Function (BRIEF). The subgroups' clinical characteristics and functional impairments were assessed using the WEISS Functional Impairment Rating Scale-Parent Report (WFIRS-P) and the Conners Parent Symptom Questionnaire (PSQ). The cluster analysis yielded four subgroups: (1) ADHD with severe impairment in psychopathology and executive functions (EF), (2) ADHD with mild executive dysfunctions and normal-level psychopathology, (3) ADHD with severe externalizing problems and (4) ADHD with severe executive dysfunctions. These subgroups showed different clinical characteristics and degrees of functional impairment. The EF impairment group displayed more serious learning problems and worse life skills than the externalizing group. The two groups with externalizing problems (i.e. the severe impairment group and the externalizing group) both exhibited higher rates of the combined subtype of ADHD and higher rates of comorbid ODD. Different subtypes of ADHD displayed different profiles of internalizing and externalizing problems and levels of executive dysfunctions. In particular, the subtype with severe impairment in EF exhibited more learning problems and worse life skills, suggesting EF is a critical target for intervention in children with ADHD.

Differential neurocognitive profiles in adult attention-deficit/hyperactivity disorder subtypes revealed by the Cambridge Neuropsychological Test Automated Battery

Adult attention-deficit/hyperactivity disorder (aADHD) represents a heterogeneous entity incorporating different subgroups in terms of symptomatology, course, and neurocognition. Although neurocognitive dysfunction is generally associated with aADHD, its severity, association with self-reported symptoms, and differences between subtypes remain unclear. We investigated 61 outpatients (65.6% male, mean age 31.5 ± 9.5) diagnosed using DSM-5 criteria together with age-, sex-, and education-matched healthy controls (HC) (n = 58, 63.8% male, mean age 32.3 ± 9.6). Neurocognitive alterations were assessed using the Cambridge Neuropsychological Test Automated Battery (CANTAB) and compared between groups using the generalized linear model (GLM) method. Multivariate effects were tested by principal component analysis combined with multivariate pattern analysis. Self-reported symptom severity was tested for correlations with neurocognitive performance. GLM analyses revealed nominally significant differences between the aADHD and HC groups in several domains, however, only the Rapid Visual Information Processing measures survived correction, indicating impaired sustained attention and response inhibition in the aADHD group. Comparison of the predominantly inattentive and the hyperactive-impulsive/combined subtypes yielded nominally significant differences with higher levels of dysfunction in the inattentive group. In the stepwise discriminant analysis aADHD and HC groups were best separated with 2 factors representing sustained attention and reaction time. We found only weak correlations between symptom severity and CANTAB factors. aADHD patients are neuropsychologically heterogeneous and subtypes show different neurocognitive profiles. Differences between the aADHD and HC groups were driven primarily by the inattentive subtype. Sustained attention and its factor derivative showed the most significant alterations in aADHD patients.

Clinical subtyping using community detection: Limited utility?

OBJECTIVES

To discover psychiatric subtypes, researchers are adopting a method called community detection. This method was not subjected to the same scrutiny in the psychiatric literature as traditional clustering methods. Furthermore, many community detection algorithms have been developed without psychiatric sample sizes and variable numbers in mind. We aim to provide clarity to researchers on the utility of this method.

METHODS

We provide an introduction to community detection algorithms, specifically describing the crucial differences between correlation-based and distance-based community detection. We compare community detection results to results of traditional methods in a simulation study representing typical psychiatry settings, using three conceptualizations of how subtypes might differ.

RESULTS

We discovered that the number of recovered subgroups was often incorrect with several community detection algorithms. Correlation-based community detection fared better than distance-based community detection, and performed relatively well with smaller sample sizes. Latent profile analysis was more consistent in recovering subtypes. Whether methods were successful depended on how differences were introduced.

CONCLUSIONS

Traditional methods like latent profile analysis remain reasonable choices. Furthermore, results depend on assumptions and theoretical choices underlying subtyping analyses, which researchers need to consider before drawing conclusions on subtypes. Employing multiple subtyping methods to establish method dependency is recommended.

Time Perception in Adult ADHD: Findings from a Decade-A Review

Time perception is impaired in adult ADHD. Since the term time perception subsumes different constructs, including time estimation, time reproduction, time production, and duration discrimination, it remains open whether certain domains are more affected than other domains in adult ADHD. The aim of this explorative review is to present the current state of research on time perception in adult ADHD by analysing studies from the past 10 years. A review of the literature addressing adult ADHD time perception, time estimation, and time reproduction was performed. The search strategy was conducted by using the databases "PubMed", "Medline", and "PSYNDEX". The results of the present review indicate that the number of studies on time perception in adult ADHD is very scarce. Moreover, the main investigated domains of time perception in the past decade were time estimation, time reproduction and time management. Whereas some of the found studies were able to demonstrate a distinct deficit in time estimation, time reproduction and time management other studies were unable to demonstrate a clear association between ADHD and time estimation and time reproduction deficits. However, the diagnostic protocols, study design, and methodology varied between studies. Further studies on time estimation and time reproduction need to be carried out.

ADHD Follow-Up in Adulthood among Subjects Treated for the Disorder in a Child and Adolescent Mental Health Service from 1995 to 2015

Background and Objectives: ADHD is a neurodevelopmental disorder characterized by inattention and hyperactivity/impulsivity and can persist in adulthood. The aim of this study is to deepen knowledge about adult ADHD follow-up. Materials and Methods: This observational study consists of one retrospective part aimed at collecting records of children and adolescents treated for ADHD in the Children and Adolescent Mental Health Service (CAMHS) from 1995 to 2015 and, successively, at identifying their adult follow-up in Adult Mental Health Service (AMHS); the second part consists of ADHD scale administration, Diagnostic Interview for ADHD in Adults (DIVA 2-0) and Adult Self Rating Scale (ASRSv1.1), for the subjects currently being treated at AMHS who agreed to participate in the study. Results: We observed that among the 55 patients treated at CAMHS between 1995 and 2015 for ADHD and subsequently at the AMHS, none presented a diagnosis of ADHD; instead, they were treated for Intellectual Dysfunction (33%), Borderline Personality Disorder (15%) and Anxiety Disorders (9%), and two individuals were also diagnosed with comorbid substance/alcohol abuse (4%). Of the 55 patients, only 25 (45%) were treated at AMHS during the study period. Though we asked for their informed consent to administer the questionnaires, we were able to test only seven patients. The ASRS-V1.1 score showed that 43% of patients reported symptoms of ADHD persistence in adulthood. For DIVA 2.0, 57% of individuals reported scores indicating the persistence of the ADHD inattention component, and 43% the persistence of both ADHD dimensions. Conclusions: ADHD cannot be considered a disorder confined to childhood/adolescence but instead is a chronic and complex condition that can persist into adulthood. The very small size of our final sample may account for both the high ADHD dropout rate over the long follow-up period and the difficult transition from child to adult health care in ADHD treatment. Our investigation suggests the need for specific training in the diagnosis and treatment of adult ADHD and the implementation of transition protocols between minor and adult services to improve long-term treatments.

Mechanism-based groups of children with ADHD are associated with distinct domains of impairment

Person-oriented analyses are commonly used to identify subgroups of children with mental health conditions in the hopes that they will meaningfully inform the taxonomy, assessment, and treatment of psychological disorder. However, whether these data-driven groups are demonstrably better at predicting important aspects of adaptive functioning than standard DSM taxonomy has not been established. Using Attention-Deficit-Hyperactivity-Disorder (ADHD) as a model condition, we utilized dimensions of personality and cognitive ability to identify person-centered profiles of school-aged children (N=246) and evaluated the association of these profiles with critical areas of adaptive functioning. A single profile ("Conscientious") represented non-ADHD controls and was characterized by faster drift rate and higher executive functioning scores. Three profiles ("Disagreeable," "Negative Emotionality," and "Extraverted") were identified for children with ADHD. Drift rate, but not executive functioning, distinguished among ADHD profiles, which were also distinctly associated with comorbid externalizing and internalizing psychopathology, social skills, and academic achievement. In contrast, the Diagnostic and Statistical Manual (DSM) presentations were not informative and showed similar patterns of impairment across domains. Person-centered profiles of children with ADHD are associated with distinct adaptive functioning deficits and may be useful in informing clinical practice.

Toward Precision Medicine in ADHD

Attention-Deficit Hyperactivity Disorder (ADHD) is a complex and heterogeneous neurodevelopmental condition for which curative treatments are lacking. Whilst pharmacological treatments are generally effective and safe, there is considerable inter-individual variability among patients regarding treatment response, required dose, and tolerability. Many of the non-pharmacological treatments, which are preferred to drug-treatment by some patients, either lack efficacy for core symptoms or are associated with small effect sizes. No evidence-based decision tools are currently available to allocate pharmacological or psychosocial treatments based on the patient's clinical, environmental, cognitive, genetic, or biological characteristics. We systematically reviewed potential biomarkers that may help in diagnosing ADHD and/or stratifying ADHD into more homogeneous subgroups and/or predict clinical course, treatment response, and long-term outcome across the lifespan. Most work involved exploratory studies with cognitive, actigraphic and EEG diagnostic markers to predict ADHD, along with relatively few studies exploring markers to subtype ADHD and predict response to treatment. There is a critical need for multisite prospective carefully designed experimentally controlled or observational studies to identify biomarkers that index inter-individual variability and/or predict treatment response.

Investigating data-driven biological subtypes of psychiatric disorders using specification-curve analysis

BACKGROUND

Cluster analyses have become popular tools for data-driven classification in biological psychiatric research. However, these analyses are known to be sensitive to the chosen methods and/or modelling options, which may hamper generalizability and replicability of findings. To gain more insight into this problem, we used Specification-Curve Analysis (SCA) to investigate the influence of methodological variation on biomarker-based cluster-analysis results.

METHODS

Proteomics data (31 biomarkers) were used from patients (n = 688) and healthy controls (n = 426) in the Netherlands Study of Depression and Anxiety. In SCAs, consistency of results was evaluated across 1200 k-means and hierarchical clustering analyses, each with a unique combination of the clustering algorithm, fit-index, and distance metric. Next, SCAs were run in simulated datasets with varying cluster numbers and noise/outlier levels to evaluate the effect of data properties on SCA outcomes.

RESULTS

The real data SCA showed no robust patterns of biological clustering in either the MDD or a combined MDD/healthy dataset. The simulation results showed that the correct number of clusters could be identified quite consistently across the 1200 model specifications, but that correct cluster identification became harder when the number of clusters and noise levels increased.

CONCLUSION

SCA can provide useful insights into the presence of clusters in biomarker data. However, SCA is likely to show inconsistent results in real-world biomarker datasets that are complex and contain considerable levels of noise. Here, the number and nature of the observed clusters may depend strongly on the chosen model-specification, precluding conclusions about the existence of biological clusters among psychiatric patients.

Characterizing neuroanatomic heterogeneity in people with and without ADHD based on subcortical brain volumes

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder. Neuroanatomic heterogeneity limits our understanding of ADHD's etiology. This study aimed to parse heterogeneity of ADHD and to determine whether patient subgroups could be discerned based on subcortical brain volumes.

METHODS

Using the large ENIGMA-ADHD Working Group dataset, four subsamples of 993 boys with and without ADHD and to subsamples of 653 adult men, 400 girls, and 447 women were included in analyses. We applied exploratory factor analysis (EFA) to seven subcortical volumes in order to constrain the complexity of the input variables and ensure more stable clustering results. Factor scores derived from the EFA were used to build networks. A community detection (CD) algorithm clustered participants into subgroups based on the networks.

RESULTS

Exploratory factor analysis revealed three factors (basal ganglia, limbic system, and thalamus) in boys and men with and without ADHD. Factor structures for girls and women differed from those in males. Given sample size considerations, we concentrated subsequent analyses on males. Male participants could be separated into four communities, of which one was absent in healthy men. Significant case-control differences of subcortical volumes were observed within communities in boys, often with stronger effect sizes compared to the entire sample. As in the entire sample, none were observed in men. Affected men in two of the communities presented comorbidities more frequently than those in other communities. There were no significant differences in ADHD symptom severity, IQ, and medication use between communities in either boys or men.

CONCLUSIONS

Our results indicate that neuroanatomic heterogeneity in subcortical volumes exists, irrespective of ADHD diagnosis. Effect sizes of case-control differences appear more pronounced at least in some of the subgroups.

Gray matter networks associated with attention and working memory deficit in ADHD across adolescence and adulthood

Attention-deficit/hyperactivity disorder (ADHD) is a childhood-onset neuropsychiatric disorder and may persist into adulthood. Working memory and attention deficits have been reported to persist from childhood to adulthood. How neuronal underpinnings of deficits differ across adolescence and adulthood is not clear. In this study, we investigated gray matter of two cohorts, 486 adults and 508 adolescents, each including participants from ADHD and healthy controls families. Two cohorts both presented significant attention and working memory deficits in individuals with ADHD. Independent component analysis was applied to the gray matter of each cohort, separately, to extract cohort-inherent networks. Then, we identified gray matter networks associated with inattention or working memory in each cohort, and projected them onto the other cohort for comparison. Two components in the inferior, middle/superior frontal regions identified in adults and one component in the insula and inferior frontal region identified in adolescents were significantly associated with working memory in both cohorts. One component in bilateral cerebellar tonsil and culmen identified in adults and one component in left cerebellar region identified in adolescents were significantly associated with inattention in both cohorts. All these components presented a significant or nominal level of gray matter reduction for ADHD participants in adolescents, but only one showed nominal reduction in adults. Our findings suggest although the gray matter reduction of these regions may not be indicative of persistency of ADHD, their persistent associations with inattention or working memory indicate an important role of these regions in the mechanism of persistence or remission of the disorder.

Cognitive characterization of adult attention deficit hyperactivity disorder by domains: a systematic review

Attention deficit hyperactivity disorder (ADHD) is reportedly the most frequent neurodevelopmental disorder diagnosed during childhood, and it is recognized as a common condition in adulthood. We review the evidence to help identify cognitive domains associated to deficits in adult ADHD. A systematic review with narrative synthesis was performed, assessing studies on adult ADHD, neuropsychology and research on involved cognitive domains in adults 18+ years old with an established diagnosis of ADHD, in seven electronic databases (PubMed, PsychInfo, WebOfScience, Embase, Scopus, OvidSPMedline, and Teseo), and Worldcat and OpenGrey grey literature databases. 93 studies were included for this review, encompassing findings from a total 5574 adults diagnosed only with ADHD, medication-naïve or non-medicated at the moment of the assessment and 4880 healthy controls. Adults diagnosed with ADHD may show, when compared to healthy controls, a cognitive profile characterized by deficits across all attention modalities, processing speed, executive function (mainly working memory and inhibition with emphasis on reward delay and interference control), verbal memory, reading skills, social cognition and arithmetic abilities. A cognitive characterization of adult ADHD by domains is established beyond the sole consideration of attention and executive function problems. Along with these, verbal memory, language (mainly reading), social cognition and arithmetic abilities may also contribute to a more comprehensive characterization of the cognitive profile in adult ADHD.

ADHD and the Choice of Small Immediate Over Larger Delayed Rewards: A Comparative Meta-Analysis of Performance on Simple Choice-Delay and Temporal Discounting Paradigms

Objective: Impulsive choices can lead to suboptimal decision making, a tendency which is especially marked in individuals with ADHD. We compared two different paradigms assessing impulsive choice: the simple choice paradigm (SCP) and the temporal discounting paradigm (TDP). Method: Random effects meta-analyses on 37 group comparisons (22 SCP; 15 TDP) consisting of 3.763 participants (53% ADHD). Results: Small-to-medium effect sizes emerged for both paradigms, confirming that participants with ADHD choose small immediate over large delayed rewards more frequently than controls. Moderation analyses show that offering real rewards in the SCP almost doubled the odds ratio for participants with ADHD. Conclusion: We suggest that a stronger than normal aversion toward delay interacts with a demotivating effect of hypothetical rewards, both factors promoting impulsive choice in participants with ADHD. Furthermore, we suggest the SCP as the paradigm of choice due to its larger ecological validity, contextual sensitivity, and reliability.

Neurophysiological markers of ADHD symptoms in typically-developing children

Children with attention-deficit/hyperactivity disorder (ADHD) are characterized by symptoms of inattention, impulsivity, and hyperactivity. Neurophysiological correlates of ADHD include changes in the P3 component of event-related brain potentials (ERPs). Motivated by recent advances towards a more dimensional understanding of ADHD, we investigate whether ADHD-related ERP markers relate to continuous variations in attention and executive functioning also in typically-developing children. ERPs were measured while 31 school children (9-11 years) completed an adapted version of the Continuous Performance Task that additionally to inhibitory processes also isolates effects of physical stimulus salience. Children with higher levels of parent-reported ADHD symptoms did not differ in task performance, but exhibited smaller P3 amplitudes related to stimulus salience. Furthermore, ADHD symptoms were associated with the variability of neural responses over time: Children with higher levels of ADHD symptoms demonstrated lower variability in inhibition- and salience-related P3 amplitudes. No effects were observed for ERP latencies and the salience-related N2. By demonstrating that ADHD-associated neurophysiological mechanisms of inhibition and salience processing covary with attention and executive functioning in a children community sample, our study provides neurophysiological support for dimensional models of ADHD. Also, temporal variability in event-related potentials is highlighted as additional indicator of ADHD requiring further investigation.

Working Memory Capacity and ADHD Symptoms in Boys: Examining the Heterogeneity of Working Memory Functioning Using Latent Profile Analysis

Recent studies demonstrate that working memory (WM) is integral to etiological models of ADHD; however, significant questions persist regarding the relation between WM performance across tasks with varying cognitive demands and ADHD symptoms. The current study incorporates an individual differences approach to WM heterogeneity (i.e., latent profile analysis) to (a) identify differential profiles of WM across the phonological and visuospatial WM subsystems; and (b) characterize differences in symptom presentation among WM profiles. Parent and teacher ratings of child behavior, obtained for boys with (n=51) and without (n=38) a diagnosis of ADHD, were compared across latent classes of visuospatial and phonological WM performance. Latent profile analysis identified three classes of WM functioning: Low WM, Moderate WM, and High WM. Membership in the Low and Moderate WM classes was associated with greater levels of parent- and teacher-rated inattentive and hyperactive symptoms. While 84% of the ADHD group were assigned to the Low and Moderate WM classes, more than a quarter of children without ADHD exhibited Moderate WM limitations. Collectively, these findings extend prior work suggesting that there is substantial heterogeneity in WM functioning in children with and without ADHD and that these differences contribute to the expression of symptoms of inattention and hyperactivity.

The definition and measurement of heterogeneity

Heterogeneity is an important concept in psychiatric research and science more broadly. It negatively impacts effect size estimates under case-control paradigms, and it exposes important flaws in our existing categorical nosology. Yet, our field has no precise definition of heterogeneity proper. We tend to quantify heterogeneity by measuring associated correlates such as entropy or variance: practices which are akin to accepting the radius of a sphere as a measure of its volume. Under a definition of heterogeneity as the degree to which a system deviates from perfect conformity, this paper argues that its proper measure roughly corresponds to the size of a system's event/sample space, and has units known as numbers equivalent. We arrive at this conclusion through focused review of more than 100 years of (re)discoveries of indices by ecologists, economists, statistical physicists, and others. In parallel, we review psychiatric approaches for quantifying heterogeneity, including but not limited to studies of symptom heterogeneity, microbiome biodiversity, cluster-counting, and time-series analyses. We argue that using numbers equivalent heterogeneity measures could improve the interpretability and synthesis of psychiatric research on heterogeneity. However, significant limitations must be overcome for these measures-largely developed for economic and ecological research-to be useful in modern translational psychiatric science.

Toward a Revised Nosology for Attention-Deficit/Hyperactivity Disorder Heterogeneity

Attention-deficit/hyperactivity disorder (ADHD) is among the many syndromes in the psychiatric nosology for which etiological signal and clinical prediction are weak. Reducing phenotypic and mechanistic heterogeneity should be useful to arrive at stronger etiological and clinical prediction signals. We discuss key conceptual and methodological issues, highlighting the role of dimensional features aligned with Research Domain Criteria and cognitive, personality, and temperament theory as well as neurobiology. We describe several avenues of work in this area, utilizing different statistical, computational, and machine learning approaches to resolve heterogeneity in ADHD. We offer methodological and conceptual recommendations. Methodologically, we propose that an integrated approach utilizing theory and advanced computational logic to address targeted questions, with consideration of developmental context, can render the heterogeneity problem tractable for ADHD. Conceptually, we conclude that the field is on the cusp of justifying an emotionally dysregulated subprofile in ADHD that may be useful for clinical prediction and treatment testing. Cognitive profiles, while more nascent, may be useful for clinical prediction and treatment assignment in different ways depending on developmental stage. Targeting these psychological profiles for neurobiological and etiological study to capture different pathophysiological routes remains a near-term opportunity. Subtypes are likely to be multifactorial, cut across multiple dimensions, and depend on the research or clinical outcomes of interest for their ultimate selection. In this context parallel profiles based on cognition, emotion, and specific neural signatures appear to be on the horizon, each with somewhat different utilities. Efforts to integrate such cross-cutting profiles within a conceptual dysregulation framework are well underway.

Approaches to Defining Common and Dissociable Neurobiological Deficits Associated With Psychopathology in Youth

Psychiatric disorders show high rates of comorbidity and nonspecificity of presenting clinical symptoms, while demonstrating substantial heterogeneity within diagnostic categories. Notably, many of these psychiatric disorders first manifest in youth. We review progress and next steps in efforts to parse heterogeneity in psychiatric symptoms in youths by identifying abnormalities within neural circuits. To address this fundamental challenge in psychiatry, a number of methods have been proposed. We provide an overview of these methods, broadly organized into dimensional versus categorical approaches and single-view versus multiview approaches. Dimensional approaches including factor analysis and canonical correlation analysis aim to capture dimensional associations between psychopathology and brain measures across a continuous spectrum from health to disease. In contrast, categorical approaches, such as clustering and community detection, aim to identify subtypes of individuals within a class of symptoms or brain features. We highlight several studies that apply these methods to samples of youths and discuss issues to consider when using these approaches. Finally, we end by highlighting avenues for future research.

Heterogeneity and Subtyping in Attention-Deficit/Hyperactivity Disorder-Considerations for Emerging Research Using Person-Centered Computational Approaches

Few if any experts believe that existing psychiatric diagnostic categories included in DSM and ICD are actually discrete disease entities. Attention-deficit/hyperactivity disorder (ADHD) is emblematic of the problems in the existing psychiatric classification system. ADHD symptoms reliably cluster into two correlated dimensions in factor analysis. However, children with ADHD vary considerably in their symptom profiles, symptom trajectories, clinical outcomes, and biological and psychological correlates. Thus, the field has sought alternative approaches that harness the dimensions of emotional, cognitive, and behavioral functioning that underlie ADHD and other existing psychiatric categories to create informative phenotypes that improve clinical prediction and clarify etiology. Within ADHD, cognitive (neuropsychological) and temperament/personality features have received considerable attention. In some cases, subphenotypes based on these features appear to improve on existing classifications and could eventually be translated into clinical practice. This review summarizes findings from subphenotyping efforts in ADHD that use cognitive, emotion-related, and other features to highlight major considerations for research applying person-oriented approaches to inform an improved psychiatric nosology. Considerations related to feature selection, validation of newly proposed divisions, defining populations of interest, and incorporating a developmental perspective are discussed.

Individual differences v. the average patient: mapping the heterogeneity in ADHD using normative models

BACKGROUND

The present paper presents a fundamentally novel approach to model individual differences of persons with the same biologically heterogeneous mental disorder. Unlike prevalent case-control analyses, that assume a clear distinction between patient and control groups and thereby introducing the concept of an 'average patient', we describe each patient's biology individually, gaining insights into the different facets that characterize persistent attention-deficit/hyperactivity disorder (ADHD).

METHODS

Using a normative modeling approach, we mapped inter-individual differences in reference to normative structural brain changes across the lifespan to examine the degree to which case-control analyses disguise differences between individuals.

RESULTS

At the level of the individual, deviations from the normative model were frequent in persistent ADHD. However, the overlap of more than 2% between participants with ADHD was only observed in few brain loci. On average, participants with ADHD showed significantly reduced gray matter in the cerebellum and hippocampus compared to healthy individuals. While the case-control differences were in line with the literature on ADHD, individuals with ADHD only marginally reflected these group differences.

CONCLUSIONS

Case-control comparisons, disguise inter-individual differences in brain biology in individuals with persistent ADHD. The present results show that the 'average ADHD patient' has limited informative value, providing the first evidence for the necessity to explore different biological facets of ADHD at the level of the individual and practical means to achieve this end.

Neurocognitive Profiles in Children With ADHD and Their Predictive Value for Functional Outcomes

OBJECTIVE

We examined whether neurocognitive profiles could be distinguished in children with ADHD and typically developing (TD) children, and whether neurocognitive profiles predicted externalizing, social, and academic problems in children with ADHD.

METHOD

Neurocognitive data of 81 children with ADHD and 71 TD children were subjected to confirmatory factor analysis. The resulting factors were used for community detection in the ADHD and TD group.

RESULTS

Four subgroups were detected in the ADHD group, characterized by (a) poor emotion recognition, (b) poor interference control, (c) slow processing speed, or (d) increased attentional lapses and fast processing speed. In the TD group, three subgroups were detected, closely resembling Subgroups (a) to (c). Neurocognitive subgroups in the ADHD sample did not differ in externalizing, social, and academic problems.

CONCLUSION

We found a neurocognitive profile unique to ADHD. The clinical validity of neurocognitive profiling is questioned, given the lack of associations with functional outcomes.

Progress in psychoradiology, the clinical application of psychiatric neuroimaging

Psychoradiology is an emerging field that applies radiological imaging technologies to psychiatric conditions. In the past three decades, brain imaging techniques have rapidly advanced understanding of illness and treatment effects in psychiatry. Based on these advances, radiologists have become increasingly interested in applying these advances for differential diagnosis and individualized patient care selection for common psychiatric illnesses. This shift from research to clinical practice represents the beginning evolution of psychoradiology. In this review, we provide a summary of recent progress relevant to this field based on their clinical functions, namely the (1) classification and subtyping; (2) prediction and monitoring of treatment outcomes; and (3) treatment selection. In addition, we provide guidelines for the practice of psychoradiology in clinical settings and suggestions for future research to validate broader clinical applications. Given the high prevalence of psychiatric disorders and the importance of increased participation of radiologists in this field, a guide regarding advances in this field and a description of relevant clinical work flow patterns help radiologists contribute to this fast-evolving field.

ADHD symptoms are associated with the modular structure of intrinsic brain networks in a representative sample of healthy adults

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders with significant and often lifelong effects on social, emotional, and cognitive functioning. Influential neurocognitive models of ADHD link behavioral symptoms to altered connections between and within functional brain networks. Here, we investigate whether network-based theories of ADHD can be generalized to understanding variations in ADHD-related behaviors within the normal (i.e., clinically unaffected) adult population. In a large and representative sample, self-rated presence of ADHD symptoms varied widely; only 8 out of 291 participants scored in the clinical range. Subject-specific brain network graphs were modeled from functional MRI resting-state data and revealed significant associations between (nonclinical) ADHD symptoms and region-specific profiles of between-module and within-module connectivity. Effects were located in brain regions associated with multiple neuronal systems including the default-mode network, the salience network, and the central executive system. Our results are consistent with network perspectives of ADHD and provide further evidence for the relevance of an appropriate information transfer between task-negative (default-mode) and task-positive brain regions. More generally, our findings support a dimensional conceptualization of ADHD and contribute to a growing understanding of cognition as an emerging property of functional brain networks.

Brain-behavior patterns define a dimensional biotype in medication-naïve adults with attention-deficit hyperactivity disorder

BACKGROUND

Childhood-onset attention-deficit hyperactivity disorder (ADHD) in adults is clinically heterogeneous and commonly presents with different patterns of cognitive deficits. It is unclear if this clinical heterogeneity expresses a dimensional or categorical difference in ADHD.

METHODS

We first studied differences in functional connectivity in multi-echo resting-state functional magnetic resonance imaging (rs-fMRI) acquired from 80 medication-naïve adults with ADHD and 123 matched healthy controls. We then used canonical correlation analysis (CCA) to identify latent relationships between symptoms and patterns of altered functional connectivity (dimensional biotype) in patients. Clustering methods were implemented to test if the individual associations between resting-state brain connectivity and symptoms reflected a non-overlapping categorical biotype.

RESULTS

Adults with ADHD showed stronger functional connectivity compared to healthy controls, predominantly between the default-mode, cingulo-opercular and subcortical networks. CCA identified a single mode of brain-symptom co-variation, corresponding to an ADHD dimensional biotype. This dimensional biotype is characterized by a unique combination of altered connectivity correlating with symptoms of hyperactivity-impulsivity, inattention, and intelligence. Clustering analyses did not support the existence of distinct categorical biotypes of adult ADHD.

CONCLUSIONS

Overall, our data advance a novel finding that the reduced functional segregation between default-mode and cognitive control networks supports a clinically important dimensional biotype of childhood-onset adult ADHD. Despite the heterogeneity of its presentation, our work suggests that childhood-onset adult ADHD is a single disorder characterized by dimensional brain-symptom mediators.

Neural correlates of cognitive function and symptoms in attention-deficit/hyperactivity disorder in adults

While gray matter (GM) anomalies have been reported for attention-deficit/hyperactivity disorder (ADHD), investigating their associations with cognitive deficits and individual symptom domains can help pinpoint the neural underpinnings critical for the pathology of ADHD, particularly the persist form of ADHD. In this work, we performed both independent component analysis and voxel-based morphometry analysis on whole brain GM of 486 adults including 214 patients, 96 unaffected siblings, and 176 healthy controls, in relation to cognition and symptoms. Independent component analysis revealed that higher GM volume in inferior semilunar lobule, inferior frontal gyri, and superior and middle frontal gyri was associated with better working memory performance, and lower GM volume in cerebellar tonsil and culmen was associated with more severe inattention symptoms. Consistently, voxel-based morphometry analysis showed that higher GM volume in multiple regions of frontal lobe, cerebellum and temporal lobe was related to better working memory performance. Focusing on the networks derived from ICA, our results integrated prefrontal regions and cerebellar regions through associations with working memory and inattention symptoms, lending support for the theory of ‘cool’-cognition dysfunction being mediated by inferior fronto-striato-cerebellar networks in ADHD. Siblings showed intermediate cognitive impairments between patients and controls but presented GM anomalies in unique focal regions, suggesting they are a separate group potentially affected by the shared genetic and environmental risks with ADHD patients.

•

Frontal and cerebellar regions associated with adult ADHD working memory deficits.

•

Gray matter reduction in cerebellum related to inattention symptoms in adult ADHD.

•

Siblings presented intermediate cognitive impairments.

•

Adult ADHD showed gray matter reduction in middle frontal gyrus.

Transdiagnostic Symptom Clusters and Associations With Brain, Behavior, and Daily Function in Mood, Anxiety, and Trauma Disorders

IMPORTANCE

The symptoms that define mood, anxiety, and trauma disorders are highly overlapping across disorders and heterogeneous within disorders. It is unknown whether coherent subtypes exist that span multiple diagnoses and are expressed functionally (in underlying cognition and brain function) and clinically (in daily function). The identification of cohesive subtypes would help disentangle the symptom overlap in our current diagnoses and serve as a tool for tailoring treatment choices.

OBJECTIVE

To propose and demonstrate 1 approach for identifying subtypes within a transdiagnostic sample.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study analyzed data from the Brain Research and Integrative Neuroscience Network Foundation Database that had been collected at the University of Sydney and University of Adelaide between 2006 and 2010 and replicated at Stanford University between 2013 and 2017. The study included 420 individuals with a primary diagnosis of major depressive disorder (n = 100), panic disorder (n = 53), posttraumatic stress disorder (n = 47), or no disorder (healthy control participants) (n = 220). Data were analyzed between October 2016 and October 2017.

MAIN OUTCOMES AND MEASURES

We followed a data-driven approach to achieve the primary study outcome of identifying transdiagnostic subtypes. First, machine learning with a hierarchical clustering algorithm was implemented to classify participants based on self-reported negative mood, anxiety, and stress symptoms. Second, the robustness and generalizability of the subtypes were tested in an independent sample. Third, we assessed whether symptom subtypes were expressed at behavioral and physiological levels of functioning. Fourth, we evaluated the clinically meaningful differences in functional capacity of the subtypes. Findings were interpreted relative to a complementary diagnostic frame of reference.

RESULTS

Four hundred twenty participants with a mean (SD) age of 39.8 (14.1) years were included in the final analysis; 256 (61.0%) were female. We identified 6 distinct subtypes characterized by tension (n=81; 19%), anxious arousal (n=55; 13%), general anxiety (n=38; 9%), anhedonia (n=29; 7%), melancholia (n=37; 9%), and normative mood (n=180; 43%), and these subtypes were replicated in an independent sample. Subtypes were expressed through differences in cognitive control (F5,383 = 5.13, P < .001, ηp2 = 0.063), working memory (F5,401 = 3.29, P = .006, ηp2 = 0.039), electroencephalography-recorded β power in a resting paradigm (F5,357 = 3.84, P = .002, ηp2 = 0.051), electroencephalography-recorded β power in an emotional paradigm (F5,365 = 3.56, P = .004, ηp2 = 0.047), social functional capacity (F5,414 = 21.33, P < .001, ηp2 = 0.205), and emotional resilience (F5,376 = 15.10, P < .001, ηp2 = 0.171).

CONCLUSIONS AND RELEVANCE

These findings offer a data-driven framework for identifying robust subtypes that signify specific, coherent, meaningful associations between symptoms, behavior, brain function, and observable real-world function, and that cut across DSM-IV-defined diagnoses of major depressive disorder, panic disorder, and posttraumatic stress disorder.

Neuropsychological functioning in college students with and without ADHD

OBJECTIVE

Increasing numbers of students with attention-deficit/hyperactivity disorder (ADHD) are attending college; however, little empirical information is available concerning the functional impairment experienced by these students. Although preliminary studies suggest that college students with ADHD are more likely to experience a variety of psychosocial and academic difficulties compared to their peers without the disorder, findings regarding neuropsychological functioning have been inconsistent with some studies reporting that college students with ADHD perform more poorly on various cognitive and neuropsychological tasks while others report no differences compared to their peers without ADHD.

METHOD

The purposes of the present study, the Trajectories Related to ADHD in College project, a longitudinal study following the 4-year outcomes of college students with and without ADHD, were to (a) examine the performance of 436 first-year college students with and without ADHD (51.6% female) on measures of executive function (EF) and intelligence and (b) investigate the association of self-reported use of stimulant medication and neuropsychological performance in students with ADHD. Participant data from their first year of involvement in the study were analyzed.

RESULTS

Participants with ADHD performed more poorly on task-based and self-report EF measures relative to the comparison group. In contrast, no significant group differences were found with respect to intellectual performance. Within the ADHD group, use of prescription stimulant medication was associated with improved performance on some, but not all, neuropsychological tasks. Additional analyses also revealed significant group differences in EF based on clinical diagnostic status.

CONCLUSION

College students with ADHD demonstrated poorer EF than their peers without ADHD and psychostimulant medication was associated with improved EF performance. No group differences were found with respect to intellectual functioning, Lastly, having one or more comorbid psychiatric diagnoses in addition to ADHD was associated with poorer EF outcomes. (PsycINFO Database Record

Aberrant Spatial and Temporal Prefrontal Activation Patterns in Medication-Naïve Adults with ADHD

Previous near-infrared spectroscopy (NIRS) studies using a verbal fluency task (VFT) have consistently reported that adults with attention-deficit hyperactivity disorder (ADHD) showed significantly smaller oxygenated-hemoglobin [oxy-Hb] activations in the prefrontal cortex (PFC) compared to those in healthy controls (HC). Despite this consistent evidence of brain dysfunction in ADHD, ADHD is currently diagnosed based only on subjective clinical and scoring measures, which are often unreliable. Hence, it is necessary to establish objective neuroimaging biomarkers for ADHD. While most NIRS studies have utilized averaged [oxy-Hb] values during the whole task period for group comparisons, we used a cluster-based non-parametric randomization test to compare the [oxy-Hb] time-course changes with a 0.1-s time resolution between drug-naïve adults with ADHD and HC, which may provide us with more details regarding abnormal prefrontal activation patterns in ADHD. A total of 101 participants, consisting of 63 drug-naïve adult individuals with ADHD and 38 HC, were included in this study. We identified that adults with ADHD showed significantly smaller [oxy-Hb] activations than those in HC at spatially and temporally connected clusters located in the bilateral PFC (more prominent on the left) and temporal brain region (more prominent on the left). We further found that aberrant [oxy-Hb] activation differs according to the time period during the task or according to brain location. Our findings indicate more detailed aberrant prefrontal and temporal activation patterns of ADHD compared with those in previous studies, possibly representing a biological marker for ADHD.

Beyond Lumping and Splitting: A Review of Computational Approaches for Stratifying Psychiatric Disorders

Heterogeneity is a key feature of all psychiatric disorders that manifests on many levels, including symptoms, disease course, and biological underpinnings. These form a substantial barrier to understanding disease mechanisms and developing effective, personalized treatments. In response, many studies have aimed to stratify psychiatric disorders, aiming to find more consistent subgroups on the basis of many types of data. Such approaches have received renewed interest after recent research initiatives, such as the National Institute of Mental Health Research Domain Criteria and the European Roadmap for Mental Health Research, both of which emphasize finding stratifications that are based on biological systems and that cut across current classifications. We first introduce the basic concepts for stratifying psychiatric disorders and then provide a methodologically oriented and critical review of the existing literature. This shows that the predominant clustering approach that aims to subdivide clinical populations into more coherent subgroups has made a useful contribution but is heavily dependent on the type of data used; it has produced many different ways to subgroup the disorders we review, but for most disorders it has not converged on a consistent set of subgroups. We highlight problems with current approaches that are not widely recognized and discuss the importance of validation to ensure that the derived subgroups index clinically relevant variation. Finally, we review emerging techniques-such as those that estimate normative models for mappings between biology and behavior-that provide new ways to parse the heterogeneity underlying psychiatric disorders and evaluate all methods to meeting the objectives of such as the National Institute of Mental Health Research Domain Criteria and Roadmap for Mental Health Research.

Quantifying patterns of brain activity: Distinguishing unaffected siblings from participants with ADHD and healthy individuals

Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent and heritable psychiatric disorders. While previous studies have focussed on mapping focal or connectivity differences at the group level, the present study employed pattern recognition to quantify group separation between unaffected siblings, participants with ADHD, and healthy controls on the basis of spatially distributed brain activations. This was achieved using an fMRI-adapted version of the Stop-Signal Task in a sample of 103 unaffected siblings, 184 participants with ADHD, and 128 healthy controls. We used activation maps derived from three task regressors as features in our analyses employing a Gaussian process classifier. We showed that unaffected siblings could be distinguished from participants with ADHD (area under the receiver operating characteristic curve (AUC) = 0.65, p = 0.002, 95% Modified Wald CI: 0.59-0.71 AUC) and healthy controls (AUC = 0.59, p = 0.030, 95% Modified Wald CI: 0.52-0.66 AUC), although the latter did not survive correction for multiple comparisons. Further, participants with ADHD could be distinguished from healthy controls (AUC = 0.64, p = 0.001, 95% Modified Wald CI: 0.58-0.70 AUC). Altogether the present results characterise a pattern of frontolateral, superior temporal and inferior parietal expansion that is associated with risk for ADHD. Unaffected siblings show differences primarily in frontolateral regions. This provides evidence for a neural profile shared between participants with ADHD and their healthy siblings.