Individualized prediction models in ADHD: a systematic review and meta-regression.

There have been increasing efforts to develop prediction models supporting personalised detection, prediction, or treatment of ADHD. We overviewed the current status of prediction science in ADHD by: (1) systematically reviewing and appraising available prediction models; (2) quantitatively assessing factors impacting the performance of published models. We did a PRISMA/CHARMS/TRIPOD-compliant systematic review (PROSPERO: CRD42023387502), searching, until 20/12/2023, studies reporting internally and/or externally validated diagnostic/prognostic/treatment-response prediction models in ADHD. Using meta-regressions, we explored the impact of factors affecting the area under the curve (AUC) of the models. We assessed the study risk of bias with the Prediction Model Risk of Bias Assessment Tool (PROBAST). From 7764 identified records, 100 prediction models were included (88% diagnostic, 5% prognostic, and 7% treatment-response). Of these, 96% and 7% were internally and externally validated, respectively. None was implemented in clinical practice. Only 8% of the models were deemed at low risk of bias; 67% were considered at high risk of bias. Clinical, neuroimaging, and cognitive predictors were used in 35%, 31%, and 27% of the studies, respectively. The performance of ADHD prediction models was increased in those models including, compared to those models not including, clinical predictors (ß = 6.54, p = 0.007). Type of validation, age range, type of model, number of predictors, study quality, and other type of predictors did not alter the AUC. Several prediction models have been developed to support the diagnosis of ADHD. However, efforts to predict outcomes or treatment response have been limited, and none of the available models is ready for implementation into clinical practice. The use of clinical predictors, which may be combined with other type of predictors, seems to improve the performance of the models. A new generation of research should address these gaps by conducting high quality, replicable, and externally validated models, followed by implementation research.

The management of sleep disturbances in children with attention-deficit/hyperactivity disorder (ADHD): an update of the literature.

INTRODUCTION: Sleep disorders represent an important comorbidity in individuals with ADHD. While the links between ADHD and sleep disturbances have been extensively investigated, research on the management of sleep disorders in individuals with ADHD is relatively limited, albeit expanding. AREAS COVERED: The authors searched PubMed, Medline, PsycInfo, Embase+Embase Classic, Web of Sciences databases, and clinicaltrials.gov up to 4 January 2024, for randomized controlled trials (RCTs) of any intervention for sleep disorders associated with ADHD. They retained 16 RCTs (eight on pharmacological and eight on non-pharmacological interventions), supporting behavioral intervention and melatonin, and nine ongoing RCTs registered on clinicaltrials.gov. EXPERT OPINION: The pool of RCTs testing interventions for sleep disorders in individuals with ADHD is expanding. However, to inform clinical guidelines, there is a need for additional research in several areas, including 1) RCTs based on a precise phenotyping of sleep disorders; 2) pragmatic RCTs recruiting neurodevelopmental populations representative of those seen in clinical services; 3) trials testing alternative interventions (e.g. suvorexant or light therapy) or ways to deliver them (e.g. online); 4) sequential and longer-term RCTs; 5) studies testing the impact of sleep interventions on outcomes other than sleep; 6) and implementation of advanced evidence synthesis and precision medicine approaches.

Shared and Specific Neural Correlates of Attention Deficit Hyperactivity Disorder and Autism Spectrum Disorder: A Meta-Analysis of 243 Task-Based Functional MRI Studies.

OBJECTIVE: To investigate shared and specific neural correlates of cognitive functions in attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), the authors performed a comprehensive meta-analysis and considered a balanced set of neuropsychological tasks across the two disorders. METHODS: A broad set of electronic databases was searched up to December 4, 2022, for task-based functional MRI studies investigating differences between individuals with ADHD or ASD and typically developing control subjects. Spatial coordinates of brain loci differing significantly between case and control subjects were extracted. To avoid potential diagnosis-driven selection bias of cognitive tasks, the tasks were grouped according to the Research Domain Criteria framework, and stratified sampling was used to match cognitive component profiles. Activation likelihood estimation was used for the meta-analysis. RESULTS: After screening 20,756 potentially relevant references, a meta-analysis of 243 studies was performed, which included 3,084 participants with ADHD (676 females), 2,654 participants with ASD (292 females), and 6,795 control subjects (1,909 females). ASD and ADHD showed shared greater activations in the lingual and rectal gyri and shared lower activations in regions including the middle frontal gyrus, the parahippocampal gyrus, and the insula. By contrast, there were ASD-specific greater and lower activations in regions including the left middle temporal gyrus and the left middle frontal gyrus, respectively, and ADHD-specific greater and lower activations in the amygdala and the global pallidus, respectively. CONCLUSIONS: Although ASD and ADHD showed both shared and disorder-specific standardized neural activations, disorder-specific activations were more prominent than shared ones. Functional brain differences between ADHD and ASD are more likely to reflect diagnosis-related pathophysiology than bias from the selection of specific neuropsychological tasks.

A state-of-the-art overview of candidate diagnostic biomarkers for Attention-deficit/hyperactivity disorder (ADHD).

INTRODUCTION: Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental conditions and is highly heterogeneous in terms of symptom profile, associated cognitive deficits, comorbidities, and outcomes. Heterogeneity may also affect the ability to recognize and diagnose this condition. The diagnosis of ADHD is primarily clinical but there are increasing research efforts aiming at identifying biomarkers that can aid the diagnosis. AREAS COVERED: We first discuss the definition of biomarkers and the necessary research steps from discovery to implementation. We then provide a broad overview of research studies on candidate diagnostic biomarkers in ADHD encompassing genetic/epigenetic, biochemical, neuroimaging, neurophysiological and neuropsychological techniques. Finally, we critically appraise current limitations in the field and suggest possible ways forward. EXPERT OPINION: Despite the large number of studies and variety of techniques used, no promising biomarkers have been identified so far. Clinical and biological heterogeneity as well as methodological limitations, including small sample size, lack of standardization, confounding factors, and poor replicability, have hampered progress in the field. Going forward, increased international collaborative efforts are warranted to support larger and more robustly designed studies, develop multimodal datasets to combine biomarkers and improve diagnostic accuracy, and ensure reproducibility and meaningful clinical translation.

Mental health during the COVID-19 pandemic in children and adolescents with ADHD: A systematic review of controlled longitudinal cohort studies.

Prior studies reported mixed effects of the COVID-19 pandemic on the mental health of children and adolescents with ADHD, but they were mainly cross-sectional and without controls. To clarify the impact, we searched Web of Science, EMBASE, Medline, and PsychINFO until 18/11/2023 and conducted a systematic review of controlled longitudinal cohort studies (Prospero: CRD42022308166). The Newcastle-Ottawa scale was used to assess quality. We identified 6 studies. Worsening of mental health symptoms was more evident in ADHD or control group according to symptom considered and context. However, those with ADHD had more persistent elevated symptoms and remained an at-risk population. Sleep problems deteriorated more significantly in those with ADHD. Lower pre-COVID emotion regulation skills and greater rumination were associated with worse mental health outcomes, and longer screen time with poorer sleep. Quality was rated as low in most studies, mainly due to self-report outcome measures and no information on attrition rates. Despite these limitations, results suggest a predominantly negative impact on youths with ADHD and may guide clinical practice and policy.

Poor response to methylphenidate is associated with a smaller dorsal attentive network in adult Attention-Deficit/Hyperactivity Disorder (ADHD).

Stimulants, such as methylphenidate (MPH), are effective in treating attention-deficit/hyperactivity disorder (ADHD), but there is individual variability in response, especially in adults. To improve outcomes, we need to understand the factors associated with adult treatment response. This longitudinal study investigated whether pre-treatment anatomy of the fronto-striatal and fronto-parietal attentional networks was associated with MPH treatment response. 60 adults with ADHD underwent diffusion brain imaging before starting MPH treatment, and response was measured at two months. We tested the association between brain anatomy and treatment response by using regression-based approaches; and compared the identified anatomical characteristics with those of 20 matched neurotypical controls in secondary analyses. Finally, we explored whether combining anatomical with clinical and neuropsychological data through machine learning provided a more comprehensive profile of factors associated with treatment response. At a group level, a smaller left dorsal superior longitudinal fasciculus (SLF I), a tract responsible for the voluntary control of attention, was associated with a significantly lower probability of being responders to two-month MPH-treatment. The association between the volume of the left SLF I and treatment response was driven by improvement on both inattentive and hyperactive/impulsive symptoms. Only non-responders significantly differed from controls in this tract metric. Finally, our machine learning approach identified clinico-neuropsychological factors associated with treatment response, such as higher cognitive performance and symptom severity at baseline. These novel findings add to our understanding of the pathophysiological mechanisms underlying response to MPH, pointing to the dorsal attentive network as playing a key role.

Long-term central nervous system (CNS) consequences of COVID-19 in children.

INTRODUCTION: Neurological/neuropsychiatric symptoms are commonly reported by children/young people with long COVID, especially headache, fatigue, cognitive deficits, anosmia and ageusia, dizziness, mood symptoms, and sleep problems. However, reported prevalence estimates are highly variable due to study heterogeneity and often small sample size; most studies only considered short-term follow-ups; and, apart from mood and sleep problems, neuropsychiatric conditions have received less attention. Considering the potential debilitating effects of neurological/neuropsychiatric conditions, a comprehensive review of the topic is timely, and needed to support clinical recognition as well as to set the direction for future research. AREAS COVERED: The authors discuss neurological/neuropsychiatric manifestations of long COVID in pediatric populations, with a focus on prevalence, associated demographic characteristics, and potential pathogenetic mechanisms. EXPERT OPINION: Children/young people may develop persistent neurological/neuropsychiatric symptoms following acute SARS-CoV-2 infection, which may affect daily functioning and well-being. Studies in larger samples with longer follow-ups are needed to clarify prevalence and symptom duration; as well as less investigated risk factors, including genetic predisposition, ethnicity, and comorbidities. Controlled studies may help separate infection-related direct effects from pandemic-related psychosocial stressors. Clarifying pathogenetic mechanisms is paramount to develop more targeted and effective treatments; whilst screening programs and psychoeducation may enhance early recognition.

White matter alterations in Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review of 129 diffusion imaging studies with meta-analysis.

Aberrant anatomical brain connections in attention-deficit/hyperactivity disorder (ADHD) are reported inconsistently across diffusion weighted imaging (DWI) studies. Based on a pre-registered protocol (Prospero: CRD42021259192), we searched PubMed, Ovid, and Web of Knowledge until 26/03/2022 to conduct a systematic review of DWI studies. We performed a quality assessment based on imaging acquisition, preprocessing, and analysis. Using signed differential mapping, we meta-analyzed a subset of the retrieved studies amenable to quantitative evidence synthesis, i.e., tract-based spatial statistics (TBSS) studies, in individuals of any age and, separately, in children, adults, and high-quality datasets. Finally, we conducted meta-regressions to test the effect of age, sex, and medication-naïvety. We included 129 studies (6739 ADHD participants and 6476 controls), of which 25 TBSS studies provided peak coordinates for case-control differences in fractional anisotropy (FA)(32 datasets) and 18 in mean diffusivity (MD)(23 datasets). The systematic review highlighted white matter alterations (especially reduced FA) in projection, commissural and association pathways of individuals with ADHD, which were associated with symptom severity and cognitive deficits. The meta-analysis showed a consistent reduced FA in the splenium and body of the corpus callosum, extending to the cingulum. Lower FA was related to older age, and case-control differences did not survive in the pediatric meta-analysis. About 68% of studies were of low quality, mainly due to acquisitions with non-isotropic voxels or lack of motion correction; and the sensitivity analysis in high-quality datasets yielded no significant results. Findings suggest prominent alterations in posterior interhemispheric connections subserving cognitive and motor functions affected in ADHD, although these might be influenced by non-optimal acquisition parameters/preprocessing. Absence of findings in children may be related to the late development of callosal fibers, which may enhance case-control differences in adulthood. Clinicodemographic and methodological differences were major barriers to consistency and comparability among studies, and should be addressed in future investigations.

Computerized cognitive training in attention-deficit/hyperactivity disorder (ADHD): a meta-analysis of randomized controlled trials with blinded and objective outcomes.

This meta-analysis investigated the effects of computerized cognitive training (CCT) on clinical, neuropsychological and academic outcomes in individuals with attention-deficit/hyperactivity disorder (ADHD). The authors searched PubMed, Ovid, and Web of Science until 19th January 2022 for parallel-arm randomized controlled trials (RCTs) using CCT in individuals with ADHD. Random-effects meta-analyses pooled standardized mean differences (SMD) between CCT and comparator arms. RCT quality was assessed with the Cochrane Risk of Bias 2.0 tool (PROSPERO: CRD42021229279). Thirty-six RCTs were meta-analysed, 17 of which evaluated working memory training (WMT). Analysis of outcomes measured immediately post-treatment and judged to be "probably blinded" (PBLIND; trial n = 14) showed no effect on ADHD total (SMD = 0.12, 95%CI[-0.01 to -0.25]) or hyperactivity/impulsivity symptoms (SMD = 0.12, 95%[-0.03 to-0.28]). These findings remained when analyses were restricted to trials (n: 5-13) with children/adolescents, low medication exposure, semi-active controls, or WMT or multiple process training. There was a small improvement in inattention symptoms (SMD = 0.17, 95%CI[0.02-0.31]), which remained when trials were restricted to semi-active controls (SMD = 0.20, 95%CI[0.04-0.37]), and doubled in size when assessed in the intervention delivery setting (n = 5, SMD = 0.40, 95%CI[0.09-0.71]), suggesting a setting-specific effect. CCT improved WM (verbal: n = 15, SMD = 0.38, 95%CI[0.24-0.53]; visual-spatial: n = 9, SMD = 0.49, 95%CI[0.31-0.67]), but not other neuropsychological (e.g., attention, inhibition) or academic outcomes (e.g., reading, arithmetic; analysed n: 5-15). Longer-term improvement (at ~6-months) in verbal WM, reading comprehension, and ratings of executive functions were observed but relevant trials were limited in number (n: 5-7). There was no evidence that multi-process training was superior to working memory training. In sum, CCT led to shorter-term improvements in WM, with some evidence that verbal WM effects persisted in the longer-term. Clinical effects were limited to small, setting specific, short-term effects on inattention symptoms.

The association between early childhood onset epilepsy and attention-deficit hyperactivity disorder (ADHD) in 3237 children and adolescents with Autism Spectrum Disorder (ASD): a historical longitudinal cohort data linkage study.

Children and young people with Autism Spectrum Disorder (ASD) have an increased risk of comorbidities, such as epilepsy and Attention-Deficit/Hyperactivity Disorder (ADHD). However, little is known about the relationship between early childhood epilepsy (below age 7) and later ADHD diagnosis (at age 7 or above) in ASD. In this historical cohort study, we examined this relationship using an innovative data source, which included linked data from routinely collected acute hospital paediatric records and childhood community and inpatient psychiatric records. In a large sample of children and young people with ASD (N = 3237), we conducted a longitudinal analysis to examine early childhood epilepsy as a risk factor for ADHD diagnosis while adjusting for potential confounders, including socio-demographic characteristics, intellectual disability, family history of epilepsy and associated physical conditions. We found that ASD children and young people diagnosed with early childhood epilepsy had nearly a twofold increase in risk of developing ADHD later in life, an association which persisted after adjusting for potential confounders (adjusted OR = 1.72, CI95% = 1.13-2.62). This study suggests that sensitive monitoring of ADHD symptoms in children with ASD who have a history of childhood epilepsy may be important to promote early detection and treatment. It also highlights how linked electronic health records can be used to examine potential risk factors over time for multimorbidity in neurodevelopmental conditions.

Efficacy of neurostimulation across mental disorders: systematic review and meta-analysis of 208 randomized controlled trials.

Non-invasive brain stimulation (NIBS), including transcranial magnetic stimulation (TMS), and transcranial direct current stimulation (tDCS), is a potentially effective treatment strategy for a number of mental conditions. However, no quantitative evidence synthesis of randomized controlled trials (RCTs) of TMS or tDCS using the same criteria including several mental conditions is available. Based on 208 RCTs identified in a systematic review, we conducted a series of random effects meta-analyses to assess the efficacy of NIBS, compared to sham, for core symptoms and cognitive functioning within a broad range of mental conditions. Outcomes included changes in core symptom severity and cognitive functioning from pre- to post-treatment. We found significant positive effects for several outcomes without significant heterogeneity including TMS for symptoms of generalized anxiety disorder (SMD = -1.8 (95% CI: -2.6 to -1), and tDCS for symptoms of substance use disorder (-0.73, -1.00 to -0.46). There was also significant effects for TMS in obsessive-compulsive disorder (-0.66, -0.91 to -0.41) and unipolar depression symptoms (-0.60, -0.78 to -0.42) but with significant heterogeneity. However, subgroup analyses based on stimulation site and number of treatment sessions revealed evidence of positive effects, without significant heterogeneity, for specific TMS stimulation protocols. For neurocognitive outcomes, there was only significant evidence, without significant heterogeneity, for tDCS for improving attention (-0.3, -0.55 to -0.05) and working memory (-0.38, -0.74 to -0.03) in individuals with schizophrenia. We concluded that TMS and tDCS can benefit individuals with a variety of mental conditions, significantly improving clinical dimensions, including cognitive deficits in schizophrenia which are poorly responsive to pharmacotherapy.

Double-dissociation between the mechanism leading to impulsivity and inattention in Attention Deficit Hyperactivity Disorder: A resting-state functional connectivity study.

Two core symptoms characterize Attention Deficit Hyperactivity Disorder (ADHD) subtypes: inattentiveness and hyperactivity-impulsivity. While previous brain imaging research investigated ADHD as if it was a homogenous condition, its two core symptoms may originate from different brain mechanisms. We, therefore, hypothesized that the functional connectivity of cortico-striatal and attentional networks would be different between ADHD subtypes. We studied 165 children (mean age 10.93 years; age range, 7-17 year old) diagnosed as having ADHD based on their revised Conner's rating scale score and 170 typical developing individuals (mean age 11.46 years; age range, 7-17 year old) using resting state functional fMRI. Groups were matched for age, IQ and head motion during the MRI acquisition. We fractionated the ADHD group into predominantly inattentive, hyperactive-impulsive and combined subtypes based on their revised Conner's rating scale score. We then analyzed differences in resting state functional connectivity of the cortico-striatal and attentional networks between these subtypes. We found a double dissociation of functional connectivity in the cortico-striatal and ventral attentional networks, reflecting the subtypes of the ADHD participants. Particularly, the hyperactive-impulsive subtype was associated with increased connectivity in cortico-striatal network, whereas the inattentive subtype was associated with increased connectivity in the right ventral attention network. Our study demonstrated for the first time a right lateralized, double dissociation between specific networks associated with hyperactivity-impulsivity and inattentiveness in ADHD children, providing a biological basis for exploring symptom dimensions and revealing potential targets for more personalized treatments.

Functional segregation and integration within fronto-parietal networks.

Experimental data on monkeys and functional studies in humans support the existence of a complex fronto-parietal system activating for cognitive and motor tasks, which may be anatomically supported by the superior longitudinal fasciculus (SLF). Advanced tractography methods have recently allowed the separation of the three branches of the SLF but are not suitable for their functional investigation. In order to gather comprehensive information about the functional organisation of these fronto-parietal connections, we used an innovative method, which combined tractography of the SLF in the largest dataset so far (129 participants) with 14 meta-analyses of functional magnetic resonance imaging (fMRI) studies. We found that frontal and parietal functions can be clustered into a dorsal spatial/motor network associated with the SLF I, and a ventral non-spatial/motor network associated with the SLF III. Further, all the investigated functions activated a middle network mostly associated with the SLF II. Our findings suggest that dorsal and ventral fronto-parietal networks are segregated but also share regions of activation, which may support flexible response properties or conscious processing. In sum, our novel combined approach provided novel findings on the functional organisation of fronto-parietal networks, and may be successfully applied to other brain connections.