ADHD in the DSM-5-TR: What has changed and what has not

Machine learning based predictive model of the risk of Tourette syndrome with SHAP value interpretation: a retrospective observational study

Tourette syndrome is a relatively prevalent neurological condition, particularly among children, characterized by sudden, involuntary, repetitive movements or vocalizations. Contemporary diagnostic approaches for Tourette syndrome (TS) primarily rely on behavioral assessments, which pose challenges due to symptom overlap with other psychiatric disorders and significant inter-individual variability. Establishing a machine learning-based predictive model for predicting the risk of TS could potentially enhance diagnostic precision and treatment effectiveness. The investigation was conducted at the Department of Pediatrics, Affiliated Hospital of Jiangnan University, spanning the period from January 2022 to October 2024. Clinical data, encompassing complete blood counts, liver and kidney function assessments, blood glucose levels, and serum electrolyte analyses, were collected. Feature selection was conducted using Boruta and multivariable logistic regression analyses, and model construction was undertaken employing 9 distinct machine learning algorithms. 10 distinct features were selected for machine learning algorithm development, and our results indicated that the Gradient Boosting Machine algorithm is the optimal model. Our study successfully established a predictive model for the risk of Tourette syndrome using Gradient Boosting Machine, and the SHAP method highlighted the key roles of β2-microglobulin and serum 25-hydroxyvitamin D3 levels in predicting TS risk.

Machine Learning Based Early Diagnosis of ADHD with SHAP Value Interpretation: A Retrospective Observational Study

Background

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder in children, characterized by inattention, hyperactivity, and impulsivity. Current diagnostic methods for ADHD rely primarily on behavioral assessments, which can be challenging due to symptom overlap with other psychiatric disorders and significant inter-individual variability. Developing potential early diagnostic methods for ADHD is imperative to mitigate the risk of misdiagnosis and enhance the evaluation of treatment efficacy.

Methods

The study was conducted at the Department of Pediatrics, Affiliated Hospital of Jiangnan University, from November 2022 to January 2024. Clinical data, including complete blood count, liver and kidney function tests, blood glucose levels, serum electrolyte tests, and serum 25-dihydroxyvitamin D3 levels, were collected. Feature selection and model construction were performed using various machine learning algorithms.

Results

Our results indicated that the Gradient Boosting Machine algorithm is the optimal model.

Conclusion

Our machine learning analyses suggest that the Gradient Boosting Machine (GBM) model may be the optimal choice, highlighting blood beta-2 microglobulin levels, red blood cell distribution width, 25-dihydroxyvitamin D3, and the percentage of eosinophils as key predictors of ADHD risk, thereby aiding early diagnosis. Further large-scale studies are warranted to validate these findings and explore the underlying mechanisms.

Gut-immune-brain interactions during neurodevelopment: from a brain-centric to a multisystem perspective

BACKGROUND

Neurodevelopmental disorders (NDDs) and epileptic syndromes are complex neurological conditions linked by shared abnormal neurobiological processes. Existing therapies mostly target symptoms, rather than addressing the underlying causes of the disease, leaving a burden of unmet clinical needs.

MAIN BODY

Emerging evidence suggests a significant role for the gut microbiota and associated immune responses in influencing brain development and function, changing the paradigm of a brain-centric origin of NDDs. This review discusses the pivotal interactions within the gut-immune-brain axis, highlighting how microbial dysbiosis and immune signaling contribute to neurological pathologies. We also explore the potential of microbial management and immunomodulation as novel therapeutic avenues, emphasizing the need for a shift towards addressing the root causes of these disorders rather than just their symptoms.

CONCLUSIONS

This integrated perspective offers new insights into the biological underpinnings of NDDs and epilepsy, proposing innovative biomarkers and therapeutic strategies.

Where Is My Mind? The Daydreaming Characteristics Questionnaire, a New Tool to Differentiate Absorptive Daydreaming From Mind-Wandering

OBJECTIVE

Maladaptive daydreaming (MD) is an impairing condition characterized by addiction to narrative, emotional fantasizing, involving dissociative absorption. By compulsively withdrawing toward vivid imaginative scenarios, MD hinders attentional functioning and replaces social interactions. Previous Interview-based research showed clinical importance in differentiating MD from ADHD and the associated construct of mind-wandering. We aimed to create a self-report tool asking directly about the content and structure of distracting thoughts.

METHOD

Two samples, namely, 346 undergraduate students and 381 adults from the general community, completed a novel measure, the Daydreaming Characteristics Questionnaire (DCQ), along with validated measures for ADHD, mind-wandering, MD, dissociation, and general distress.

RESULTS

Exploratory Factor Analyses on the DCQ, replicated across both samples, yielded two distinct factors (immersive daydreaming and daydream functionality) uniquely associated with MD.

CONCLUSION

The DCQ represents characteristics of immersive daydreaming much more than general attentional deficiency and is thus useful in differentiating MD from ADHD/mind-wandering distractions.

[Substance Use Disorder as a Comorbidity in Patients with Attention Deficit Hyperactivity Disorder]

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder manifested by inattention and/or hyperactivity and impulsivity. It is a disorder that begins in childhood but can persist into adulthood. It is associated with the emergence of various comorbidities, including, very often, the development of substance use disorders (SUD). When present simultaneously, they contribute to more severe presentations of both conditions and makes treatment more complex and challenging. Despite being different conditions, they have potentially common etiological pathways. The main aims of this article were to study the correlation between ADHD and SUD, particularly concerning the prevalence of this association, etiology and what are the best diagnostic and treatment strategies. We conclude that SUD is one of the most common comorbidities among ADHD patients, with genetic factors, neuroanatomical and neurophysiological impairments correlating both conditions. Patients with ADHD and SUD have an earlier onset of SUD, heavier abuse and worse outcomes. Special attention to this disorder is recommended in patients with ADHD. Furthermore, an active search for ADHD in patients with SUD is highly recommended, which can be carried out in the first place with self-reported scales. The appropriate treatment seems to involve a combination of pharmacological and non-pharmacological approaches, with strategies targeting both conditions.

Personality Traits in Adolescents with ADHD: Insights into Dimension Evaluation and Clinical Implications Using the Personality Inventory for the DSM-5 Questionnaire

Background/Objectives: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity, often persisting into adolescence and adulthood, with significant impacts on social, academic, and occupational functioning. Emerging research highlights the role of personality traits in ADHD, suggesting their influence on symptom presentation, functional impairments, and treatment adherence. This study aims to investigate maladaptive personality domains and traits in adolescents with ADHD using the Alternative Model of Personality Disorders (AMPD) framework and the Personality Inventory for DSM-5 Short Form (PID-5-SF), with a particular focus on the differences among same-sex peers and differences from typically developing peers. Methods: This study included 30 ADHD and 25 TD adolescents aged 11-17 (12.6 ± 2.1 vs. 14.9 ± 1.7; p < 0.001), recruited at IRCCS Centro Neurolesi "Bonino Pulejo". Participants underwent clinical assessments, cognitive evaluation, and standardized rating scales, with maladaptive personality traits measured using the PID-5-SF. Chi-squared and Mann-Whitney U tests were used to compare the two groups, as appropriate. Results: ADHD adolescents showed significantly higher scores than TD peers in restricted affectivity (p = 0.007), distractibility (p = 0.001), impulsivity (p = 0.049), irresponsibility (p = 0.036), hostility (p = 0.046), perseveration (p = 0.010), submissiveness (p = 0.023), and risk-taking (p = 0.032). Among personality domains, disinhibition was significantly higher in the ADHD group (p = 0.002), while detachment approached significance. Female ADHD participants scored higher than TD females in restricted affectivity, distractibility, and risk-taking. Conclusions: These findings suggest that maladaptive personality traits play a key role in ADHD during adolescence, highlighting the need for tailored interventions. Integrating personality assessment into clinical practice may enhance diagnostic accuracy and support more effective, individualized treatment strategies.

Artificial intelligence in ADHD: a global perspective on research hotspots, trends and clinical applications

Background

Artificial Intelligence (AI), has garnered attention in research on attention deficit hyperactivity disorder (ADHD). In the future, AI may have clinical applications in ADHD, particularly in facilitating the objective diagnosis and classification of ADHD. This study aimed to comprehensively analyze the current status and research frontiers of AI applications in ADHD, identifying hotspots and trends to guide future research directions and promote clinical advancements in this field.

Methods

Articles in the field of AI applications in ADHD were from the Web of Science Core Collection (WoSCC) database. Analysis was conducted using CiteSpace 6.3.R.1. Additionally, high-impact articles were analyzed.

Results

A total of 342 articles from 50 countries and regions were included. The United States led with 103 articles, having the highest H-index of 21, followed by China with 69 articles, and England with 34 articles. The State University of New York System produced the most articles (11), and Frontiers in Psychiatry had the most articles (12). Burst keywords in 2022-2024 included "diagnosis," "network," "attention deficit hyperactivity disorder" and "artificial intelligence."

Conclusion

AI technologies have become a prominent topic in ADHD research, with the United States, China, and England leading in articles and influence. The State University of New York System was the most influential institution, while Frontiers in Psychiatry stood out as the key journal. Utilizing networks and other AI technologies for diagnosing ADHD represents current hotspots and future trends, potentially offering objective indicators for ADHD.

Validity of the Italian Version of DIVA-5: Semi-Structured Diagnostic Interview for Adult ADHD Based on the DSM-5 Criteria

Introduction: In 2019, an updated version of the Diagnostic Interview for ADHD in Adults (DIVA-5) was developed based on DSM-5 criteria, currently validated in Korean and Farsi. The aim of this study is to validate the DIVA-5 Italian version. Methods: 132 subjects in the Adult ADHD Screening Center of AUSL-Modena, who agreed to participate in this study, were selected. Socio-demographic and clinical variables were collected. DIVA-5, Barkley Adult ADHD Rating Scale (BAARS), and Adult ADHD Self Rating Scale (ASRS-v1.1) were administered. We assessed the internal consistency of the DIVA-5 Italian version and its concurrent validity with ASRS-v1.1 and BAARS-IV. An exploratory factor analysis (EFA) was conducted to evaluate the construct validity, and a multiple linear regression to evaluate the predictive validity. Results: Our analysis indicated good internal consistence of the DIVA-5 Italian version (Cronbach's alpha and Kuder coefficients ranged between 0.61 and 0.78). The EFA showed five factors representing specific variance. The correlation between the corresponding ADHD dimensions of DIVA-5 and BAARS was found to be statistically significant (Spearman's coefficient ranged between 0.61 and 0.47, p = 0.000), while the correlation between the DIVA-5 dimensions and ASRS-v1.1 was statistically significant for all the dimensions except child hyperactivity/impulsivity. The multiple linear regression showed a positive association of the DIVA-5 score with the "job" variable and a negative association with "drug therapy". DIVA-5 showed greater sensitivity for inattention in adulthood and greater specificity for hyperactivity/impulsivity in childhood. Conclusions: Our results confirm that the DIVA-5 Italian version represents a valid and reliable tool to diagnose adult ADHD.

Factors Associated with Mental Health Service Use Among Children with ADHD from Adolescence to Early Adulthood

Childhood attention-deficit/hyperactivity disorder (ADHD) is common and is associated with lifelong adverse outcomes. Little is known about factors associated with mental health service use (MHSU) among children with ADHD from adolescence to early adulthood. This retrospective cohort study aims to investigate factors associated with MHSU among children with ADHD from adolescence to early adulthood using secondary data from Waves I to III of the National Longitudinal Study of Adolescent Health (n = 554). Multivariable Poisson regression and Generalized Estimating Equation were used to estimate adjusted relative risks and 95% confidence intervals. Results indicate that factors significantly associated with MHSU from adolescence to early adulthood included race/ethnicity, a routine physical exam last year, and a history of suicidal ideation or attempt. Findings of the study extend the current understanding by identifying predictors and barriers for MHSU and inform the development of targeted intervention programs for increasing MHSU among children with ADHD.

Expression Patterns of miRNAs in Egyptian Children with ADHD: Clinical Study with Correlation Analysis

ADHD has huge knowledge gaps concerning its etiology. MicroRNAs (miRNAs) provide promising diagnostic biomarkers of human pathophysiology and may be a novel therapeutic option. The aim was to investigate the levels of miR-34c-3p, miR-155, miR-138-1, miR-296-5p, and plasma brain-derived neurotrophic factor (BDNF) in a group of children with ADHD compared to neurotypicals and to explore correlations between these measures and some clinical data. The participants were children with ADHD in Group I (N = 41; age: 8.2 ± 2) and neurotypical ones in Group II (N = 40; age: 8.6 ± 2.5). Group I was subjected to clinical examination, the Stanford Binet intelligence scale-5, the preschool language scale, and Conner's parent rating scale-R. Measuring the expression levels of the miRNAs was performed by qRT-PCR for all participants. The BDNF level was measured by ELISA. The lowest scores on the IQ subtest were knowledge and working memory. No discrepancies were noticed between the receptive and expressive language ages. The highest scores on the Conner's scale were those for cognitive problems. Participants with ADHD exhibited higher plasma BDNF levels compared to controls (p = 0.0003). Expression patterns of only miR-34c-3p and miR-138-1 were downregulated with significant statistical differences (p˂0.01). However, expression levels of miR-296-5p showed negative correlation with the total scores of IQ (p = 0.03). MiR-34c-3p, miR-138-1, while BDNF showed good diagnostic potential. The downregulated levels of miR-34c-3p and miR-138-1, together with high BDNF levels, are suggested to be involved in the etiology of ADHD in Egyptian children. Gender differences influenced the expression patterns of miRNAs only in children with ADHD.

Comparison of self-esteem and quality of life in 8-12-year-old children with ADHD with and without learning disorders

BACKGROUND

Attention Deficit/Hyperactivity Disorder (ADHD) is one of the most common disorders in school-aged children. Learning disorder (LD) is also one of the most important psychiatric disorders in children, which can often be associated with ADHD. In this study, we sought to compare self-esteem and quality of life in 8 to 12-year-old children with attention deficit/hyperactivity disorder with and without co-occurring learning disorders in order to emphasize the importance of attention and diagnosis in children with ADHD.

METHOD

Among the 8- to 12-year-old outpatients referred to the child and adolescent psychiatry clinic of Omid Babol Clinic, 120 children aged 8 to 12 years with attention deficit/hyperactivity disorder whose disease was diagnosed by a child and adolescent psychiatry subspecialist. Among the tools used to collect information was the Colorado Learning Difficulties Questionnaire by Wilcott et al. (CLDQ), five-scale self-esteem test of Pepe et al. (1989) for children and quality-of-life questionnaire for 8-12-year-old children (PedsQL).

RESULTS

This study investigated self-esteem and quality of life in children with ADHD (n = 120, 51.7% boys). Children with ADHD and learning disabilities reported significantly lower self-esteem and quality of life compared to those with ADHD alone.

CONCLUSION

Considering the relatively high probability of co-occurrence of ADHD and learning disorders, if one of them is diagnosed in a child, it is possible to look for other disorders in the child in order to avoid the more severe negative effects that this co-occurrence can have on the child by diagnosing it as soon as possible.

Adult ADHD: it is old and new at the same time - what is it?

Even though the number of studies aiming to improve comprehension of ADHD pathology has increased in recent years, there still is an urgent need for more effective studies, particularly in understanding adult ADHD, both at preclinical and clinical levels, due to the increasing evidence that adult ADHD is highly distinct and a different entity from childhood ADHD. This review paper outlines the symptoms, diagnostics, and neurobiological mechanisms of ADHD, with emphasis on how adult ADHD could be different from childhood-onset. Data show a difference in the environmental, genetic, epigenetic, and brain structural changes, when combined, could greatly impact the behavioral presentations and the severity of ADHD in adults. Furthermore, a crucial aspect in the quest to fully understand this disorder could be through longitudinal analysis. In this way, we will determine if and how the pathology and pharmacology of ADHD change with age. This goal could revolutionize our understanding of the disorder and address the weaknesses in the current clinical classification systems, improving the characterization and validity of ADHD diagnosis, specifically those in adults.

Attention Deficit Hyperactivity Disorder Among Youth at Clinical High Risk of Psychosis

Background

Attention Deficit Hyperactivity Disorder (ADHD) affects a significant proportion of the population and is associated with numerous adverse outcomes including lower educational attainment, occupational challenges, increased substance use, and various mental health issues including psychosis. This study examined the demographic, clinical, cognitive, social cognitive, and functional differences between youth at clinical high-risk (CHR) for psychosis with and without comorbid ADHD.

Method

Data were drawn from the North American Prodrome Longitudinal Studies (NAPLS2 and NAPLS3), which included 764 and 710 CHR individuals, respectively. After applying exclusion criteria, the sample consisted of 271 CHR participants with ADHD and 1118 without ADHD. All data were examined cross-sectionally.

Results

Compared with the non-ADHD group, the ADHD group was younger, had more difficulties with role functioning, premorbid functioning, and social cognition, were more likely to have a comorbid learning disorder, and reported less depression symptoms. There were no significant differences between the groups on positive or negative psychotic symptoms, transition rates, adverse events, or other comorbid disorders including substance use and depression.

Discussion

Comorbid ADHD is likely not a significant predictor of transition to psychosis among CHR youth; however, those CHR with ADHD may experience symptoms at a younger age than those without and present with a distinct clinical profile.

Behavior Rating Inventory of Executive Function in Preschool (BRIEF-P) and Attention-Deficit and Hyperactivity Disorders (ADHD): A Systematic Review and Meta-Analysis of Floor and Ceiling Effects

BACKGROUND

ADHD is a neurodevelopmental disorder that is accompanied by executive challenges.

OBJECTIVES

To obtain evidence of the usefulness of the BRIEF-P and to analyze the possible ceiling and floor effect of its scores in the assessment of executive function in preschoolers with signs compatible with a possible diagnosis of ADHD.

METHOD

A search was performed in Science Direct, NCBI (PubMed), and ProQuest Education Journals during the period 2012-2022. We included studies that evaluated samples of individuals with symptomatology compatible with ADHD, with an age range between 2 and 6 years, published in English or Spanish. Of a total of 2538 articles, only seven met the inclusion criteria. The risk of bias was assessed using the QUADAS-2 questionnaire. The main variables were age and executive functioning.

CONCLUSIONS

Executive deficits in early-age individuals with symptoms compatible with ADHD are more extensive than just deficits in working memory. A floor effect has been found in tests associated with hot executive functions and a ceiling effect in cold executive functions. This makes it necessary to use different tests to assess executive performance in preschoolers with ADHD-compatible symptomatology and to design intervention proposals accordingly. The BRIEF-P is an instrument that facilitates obtaining a sensitive and discriminative executive profile, although it should be used in combination with other neuropsychological performance tests.

Dopamine in the Regulation of Glucose Homeostasis, Pathogenesis of Type 2 Diabetes, and Chronic Conditions of Impaired Dopamine Activity/Metabolism: Implication for Pathophysiological and Therapeutic Purposes

Dopamine regulates several functions, such as voluntary movements, spatial memory, motivation, sleep, arousal, feeding, immune function, maternal behaviors, and lactation. Less clear is the role of dopamine in the pathophysiology of type 2 diabetes mellitus (T2D) and chronic complications and conditions frequently associated with it. This review summarizes recent evidence on the role of dopamine in regulating insular metabolism and activity, the pathophysiology of traditional chronic complications associated with T2D, the pathophysiological interconnection between T2D and chronic neurological and psychiatric disorders characterized by impaired dopamine activity/metabolism, and therapeutic implications. Reinforcing dopamine signaling is therapeutic in T2D, especially in patients with dopamine-related disorders, such as Parkinson's and Huntington's diseases, addictions, and attention-deficit/hyperactivity disorder. On the other hand, although specific trials are probably needed, certain medications approved for T2D (e.g., metformin, pioglitazone, incretin-based therapy, and gliflozins) may have a therapeutic role in such dopamine-related disorders due to anti-inflammatory and anti-oxidative effects, improvement in insulin signaling, neuroinflammation, mitochondrial dysfunction, autophagy, and apoptosis, restoration of striatal dopamine synthesis, and modulation of dopamine signaling associated with reward and hedonic eating. Last, targeting dopamine metabolism could have the potential for diagnostic and therapeutic purposes in chronic diabetes-related complications, such as diabetic retinopathy.

Subcortical structural covariance predicts symptoms in children with different subtypes of ADHD

Attention-deficit/hyperactivity disorder has increasingly been conceptualized as a disorder of abnormal brain connectivity. However, far less is known about the structural covariance in different subtypes of this disorder and how those differences may contribute to the symptomology of these subtypes. In this study, we used a combined volumetric-based methodology and structural covariance approach to investigate structural covariance of subcortical brain volume in attention-deficit/hyperactivity disorder-combined and attention-deficit/hyperactivity disorder-inattentive patients. In addition, a linear support vector machine was used to predict patient's attention-deficit/hyperactivity disorder symptoms. Results showed that compared with TD children, those with attention-deficit/hyperactivity disorder-combined exhibited decreased volume of both the left and right pallidum. Moreover, we found increased right hippocampal volume in attention-deficit/hyperactivity disorder-inattentive children. Furthermore and when compared with the TD group, both attention-deficit/hyperactivity disorder-combined and attention-deficit/hyperactivity disorder-inattentive groups showed greater nonhomologous inter-regional correlations. The abnormal structural covariance network in the attention-deficit/hyperactivity disorder-combined group was located in the left amygdala-left putamen/left pallidum/right pallidum and right pallidum-left pallidum; in the attention-deficit/hyperactivity disorder-inattentive group, this difference was noted in the left hippocampus-left amygdala/left putamen/right putamen and right hippocampus-left amygdala. Additionally, different combinations of abnormalities in subcortical structural covariance were predictive of symptom severity in different attention-deficit/hyperactivity disorder subtypes. Collectively, our findings demonstrated that structural covariance provided valuable diagnostic markers for attention-deficit/hyperactivity disorder subtypes.