Characterization of cortical and subcortical abnormalities in drug-naive boys with attention-deficit/hyperactivity disorder

Larger putamen in individuals at risk and with manifest bipolar disorder

BACKGROUND

Individuals at risk for bipolar disorder (BD) have a wide range of genetic and non-genetic risk factors, like a positive family history of BD or (sub)threshold affective symptoms. Yet, it is unclear whether these individuals at risk and those diagnosed with BD share similar gray matter brain alterations.

METHODS

In 410 male and female participants aged 17-35 years, we compared gray matter volume (3T MRI) between individuals at risk for BD (as assessed using the EPIbipolar scale; n = 208), patients with a DSM-IV-TR diagnosis of BD (n = 87), and healthy controls (n = 115) using voxel-based morphometry in SPM12/CAT12. We applied conjunction analyses to identify similarities in gray matter volume alterations in individuals at risk and BD patients, relative to healthy controls. We also performed exploratory whole-brain analyses to identify differences in gray matter volume among groups. ComBat was used to harmonize imaging data from seven sites.

RESULTS

Both individuals at risk and BD patients showed larger volumes in the right putamen than healthy controls. Furthermore, individuals at risk had smaller volumes in the right inferior occipital gyrus, and BD patients had larger volumes in the left precuneus, compared to healthy controls. These findings were independent of course of illness (number of lifetime manic and depressive episodes, number of hospitalizations), comorbid diagnoses (major depressive disorder, attention-deficit hyperactivity disorder, anxiety disorder, eating disorder), familial risk, current disease severity (global functioning, remission status), and current medication intake.

CONCLUSIONS

Our findings indicate that alterations in the right putamen might constitute a vulnerability marker for BD.

Common and distinct cortical thickness alterations in youth with autism spectrum disorder and attention-deficit/hyperactivity disorder

BACKGROUND

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental disorders with overlapping behavioral features and genetic etiology. While brain cortical thickness (CTh) alterations have been reported in ASD and ADHD separately, the degree to which ASD and ADHD are associated with common and distinct patterns of CTh changes is unclear.

METHODS

We searched PubMed, Web of Science, Embase, and Science Direct from inception to 8 December 2023 and included studies of cortical thickness comparing youth (age less than 18) with ASD or ADHD with typically developing controls (TDC). We conducted a comparative meta-analysis of vertex-based studies to identify common and distinct CTh alterations in ASD and ADHD.

RESULTS

Twelve ASD datasets involving 458 individuals with ASD and 10 ADHD datasets involving 383 individuals with ADHD were included in the analysis. Compared to TDC, ASD showed increased CTh in bilateral superior frontal gyrus, left middle temporal gyrus, and right superior parietal lobule (SPL) and decreased CTh in right temporoparietal junction (TPJ). ADHD showed decreased CTh in bilateral precentral gyri, right postcentral gyrus, and right TPJ relative to TDC. Conjunction analysis showed both disorders shared reduced TPJ CTh located in default mode network (DMN). Comparative analyses indicated ASD had greater CTh in right SPL and TPJ located in dorsal attention network and thinner CTh in right TPJ located in ventral attention network than ADHD.

CONCLUSIONS

These results suggest shared thinner TPJ located in DMN is an overlapping neurobiological feature of ASD and ADHD. This alteration together with SPL alterations might be related to altered biological motion processing in ASD, while abnormalities in sensorimotor systems may contribute to behavioral control problems in ADHD. The disorder-specific thinner TPJ located in disparate attention networks provides novel insight into distinct symptoms of attentional deficits associated with the two neurodevelopmental disorders.

TRIAL REGISTRATION

PROSPERO CRD42022370620. Registered on November 9, 2022.

Evaluation of individual-based morphological brain network alterations in children with attention-deficit/hyperactivity disorder: a multi-method investigation

To investigate the topological organization of individual-based morphological brain networks (MBNs) in attention-deficit/hyperactivity disorder (ADHD) children with different methods. A total of 60 ADHD children and 60 typically developing (TD) controls matched for age and gender were enrolled. Each participant underwent a structural 3D T1-weighted scan. Based on the inter-regional morphological similarity of GM regions, Kullback-Leibler-based similarity (KLS), Multivariate Euclidean Distance (MED), and Tijms's method were used to construct individual-based MBNs, respectively. The between-group difference of global and nodal network topological profiles was estimated, and partial correlation analysis was used for further analysis. According to KLS and MED-based network, ADHD showed a decreased global efficiency (Eglob) and increased characteristic path length (Lp) compared to the TD group, while Tijms's method-based network showed no between-group difference in global and nodal profiles. Nodal profiles were significantly decreased in the bilateral caudate, and nodal efficiency of the bilateral caudate was negatively correlated with clinical symptom severity of ADHD (P < 0.05, FDR-corrected) by the KLS-based network. Nodal betweenness was significantly decreased in the left inferior occipital gyrus and correlated with clinical symptom severity of ADHD (P < 0.05, FDR-corrected) by the MED-based network. ADHD was found to have a significantly less integrated organization and a shift to a "weaker small-worldness" pattern, while abnormal nodal profiles were mainly in the corpus striatum and default-mode networks. Our study highlights the crucial role of abnormal morphological connectivity patterns in understanding the brain maturational effects in ADHD and enriching the insights into MBNs at an individual level.

Neuroprotection in late life attention-deficit/hyperactivity disorder: A review of pharmacotherapy and phenotype across the lifespan

For decades, psychostimulants have been the gold standard pharmaceutical treatment for attention-deficit/hyperactivity disorder (ADHD). In the United States, an astounding 9% of all boys and 4% of girls will be prescribed stimulant drugs at some point during their childhood. Recent meta-analyses have revealed that individuals with ADHD have reduced brain volume loss later in life (>60 y.o.) compared to the normal aging brain, which suggests that either ADHD or its treatment may be neuroprotective. Crucially, these neuroprotective effects were significant in brain regions (e.g., hippocampus, amygdala) where severe volume loss is linked to cognitive impairment and Alzheimer's disease. Historically, the ADHD diagnosis and its pharmacotherapy came about nearly simultaneously, making it difficult to evaluate their effects in isolation. Certain evidence suggests that psychostimulants may normalize structural brain changes typically observed in the ADHD brain. If ADHD itself is neuroprotective, perhaps exercising the brain, then psychostimulants may not be recommended across the lifespan. Alternatively, if stimulant drugs are neuroprotective, then this class of medications may warrant further investigation for their therapeutic effects. Here, we take a bottom-up holistic approach to review the psychopharmacology of ADHD in the context of recent models of attention. We suggest that future studies are greatly needed to better appreciate the interactions amongst an ADHD diagnosis, stimulant treatment across the lifespan, and structure-function alterations in the aging brain.

Surface values, volumetric measurements and radiomics of structural MRI for the diagnosis and subtyping of attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is diagnosed subjectively based on an individual's behaviour and performance. The clinical community has no objective biomarker to inform the diagnosis and subtyping of ADHD. This study aimed to explore the potential diagnostic biomarkers of ADHD among surface values, volumetric metrics and radiomic features that were extracted from structural MRI images. Public data of New York University and Peking University were downloaded from the ADHD-200 Consortium. MRI T1-weighted images were pre-processed using CAT12. We calculated surface values based on the Desikan-Killiany atlas. The volumetric metrics (mean grey matter volume and mean white matter volume) and radiomic features within each automated anatomical labelling (AAL) brain area were calculated using DPABI and IBEX, respectively. The differences among three groups of participants were tested using ANOVA or Kruskal-Wallis test depending on the normality of the data. We selected discriminative features and classified typically developing controls (TDCs) and ADHD patients as well as two ADHD subtypes using least absolute shrinkage and selection operator and support vector machine algorithms. Our results showed that the radiomics-based model outperformed the others in discriminating ADHD from TDC and classifying ADHD subtypes (area under the curve [AUC]: 0.78 and 0.94 in training test; 0.79 and 0.85 in testing set). Combining grey matter volumes, surface values and clinical factors with radiomic features can improve the performance for classifying ADHD patients and TDCs with training and testing AUCs of 0.82 and 0.83, respectively. This study demonstrates that MRI T1-weighted features, especially radiomic features, are potential diagnostic biomarkers of ADHD.

A Unified Framework for Inattention Estimation From Resting State Phase Synchrony Using Machine Learning

Inattention is one of the most significant clinical symptoms for evaluating attention deficit hyperactivity disorder (ADHD). Previous inattention estimations were performed using clinical scales. Recently, predictive models for inattention have been established for brain-behavior estimation using neuroimaging features. However, the performance of inattention estimation could be improved for conventional brain-behavior models with additional feature selection, machine learning algorithms, and validation procedures. This paper aimed to propose a unified framework for inattention estimation from resting state fMRI to improve the classical brain-behavior models. Phase synchrony was derived as raw features, which were selected with minimum-redundancy maximum-relevancy (mRMR) method. Six machine learning algorithms were applied as regression methods. 100 runs of 10-fold cross-validations were performed on the ADHD-200 datasets. The relevance vector machines (RVMs) based on the mRMR features for the brain-behavior models significantly improve the performance of inattention estimation. The mRMR-RVM models could achieve a total accuracy of 0.53. Furthermore, predictive patterns for inattention were discovered by the mRMR technique. We found that the bilateral subcortical-cerebellum networks exhibited the most predictive phase synchrony patterns for inattention. Together, an optimized strategy named mRMR-RVM for brain-behavior models was found for inattention estimation. The predictive patterns might help better understand the phase synchrony mechanisms for inattention.

Neuroimaging in Attention-Deficit/Hyperactivity Disorder: Recent Advances

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental condition, leading to impaired attention and impulsive behaviors diagnosed in, but not limited to, children. ADHD can cause symptoms throughout life. This article summarizes structural (conventional, volumetric, and diffusion tensor imaging MRI) and functional [task-based functional MRI (fMRI), resting state fMRI, PET, and MR spectroscopy] brain findings in patients with ADHD. Consensus is lacking regarding altered anatomic or functional imaging findings of the brain in children with ADHD, likely because of the disorder's heterogeneity. Most anatomic studies report abnormalities in the frontal lobes, basal ganglia, and corpus callosum; decreased surface area in the left ventral frontal and right prefrontal cortex; thinner medial temporal lobes; and smaller caudate nuclei. Using fMRI, researchers have focused on the prefrontal and temporal regions, reflecting perception-action mapping alterations. Artificial intelligence models evaluating brain anatomy have highlighted changes in cortical thickness and shape of the inferior frontal cortex, bilateral sensorimotor cortex, left temporal lobe, and insula. Early intervention and/or normal brain maturation can alter imaging patterns and convert functional imaging studies to a normal pattern. While the imaging findings provide insight into the disease's neuropathophysiology, no definitive structural or functional pattern defines the disorder from a neuroradiologic perspective.

Brain morphometric abnormalities in boys with attention-deficit/hyperactivity disorder revealed by sulcal pits-based analyses

AIM

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder associated with widespread brain morphological abnormalities. Here, we utilized a sulcal pits-based method to provide new insight into the atypical cortical folding morphology in ADHD.

METHODS

Sulcal pits, the locally deepest points in each fold, were first extracted from magnetic resonance imaging data of 183 boys with ADHD (10.62 ± 1.96 years) and 167 age- and gender-matched typically developing controls (10.70 ± 1.73 years). Then, the geometrical properties of sulcal pits were statistically compared between ADHD and controls.

RESULTS

Our results demonstrated that the number of sulcal pits was reduced and confined to the superficial secondary sulci in the ADHD group relative to controls (P < .05). We also found that ADHD boys were associated with significantly increased pit depth in the left superior frontal junction, circular insular sulcus, right inferior frontal junction, and bilateral cingulate sulcus, as well as significantly decreased pit depth in the bilateral orbital sulcus (P < .05, corrected).

CONCLUSION

The experimental findings reveal atypical sulcal anatomy in boys with ADHD and support the feasibility of sulcal pits as anatomic landmarks for disease diagnosis.

Reduced striatal GABA in unmedicated children with ADHD at 7T

Attention-deficit hyperactive disorder (ADHD) is characterized by inattention and increased impulsive and hypermotoric behaviors.Despite the high prevalence and impact of ADHD, little is known about the underlying neurophysiology of ADHD. The main inhibitory and excitatory neurotransmitters γ-aminobutyric acid (GABA) and glutamate are receiving increased attention in ADHD and can be measured using Magnetic Resonance Spectroscopy (MRS). However, MRS studies in ADHD are limited. We measured GABA and glutamate in young unmedicated participants, utilizing high magnetic field strength. Fifty unmedicated children (26 with ADHD, 24 controls) aged 5-9 years completed MRS at 7T and behavioral testing. GABA and glutamate were measured in dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), premotor cortex (PMC), and striatum, and estimated using LCModel. Children with ADHD showed poorer inhibitory control and significantly reduced GABA/Cr in the striatum, but not in ACC, DLPFC, or PMC regions. There were no significant group differences for Glu/Cr levels, or correlations with behavioral manifestations of ADHD. The primary finding of this study is a reduction of striatal GABA levels in unmedicated children with ADHD at 7T. These findings provide guidance for future studies or interventions. Reduced striatal GABA may be a marker for specific GABA-related treatment for ADHD.

Spontaneous and stimulus-driven rhythmic behaviors in ADHD adults and controls

Many aspects of human behavior are inherently rhythmic, requiring production of rhythmic motor actions as well as synchronizing to rhythms in the environment. It is well-established that individuals with ADHD exhibit deficits in temporal estimation and timing functions, which may impact their ability to accurately produce and interact with rhythmic stimuli. In the current study we seek to understand the specific aspects of rhythmic behavior that are implicated in ADHD. We specifically ask whether they are attributed to imprecision in the internal generation of rhythms or to reduced acuity in rhythm perception. We also test key predictions of the Preferred Period Hypothesis, which suggests that both perceptual and motor rhythmic behaviors are biased towards a specific personal 'default' tempo. To this end, we tested several aspects of rhythmic behavior and the correspondence between them, including spontaneous motor tempo (SMT), preferred auditory perceptual tempo (PPT) and synchronization-continuations tapping in a broad range of rhythms, from sub-second to supra-second intervals. Moreover, we evaluate the intra-subject consistency of rhythmic preferences, as a means for testing the reality and reliability of personal 'default-rhythms'. We used a modified operational definition for assessing SMT and PPT, instructing participants to tap or calibrate the rhythms most comfortable for them to count along with, to avoid subjective interpretations of the task. Our results shed new light on the specific aspect of rhythmic deficits implicated in ADHD adults. We find that individuals with ADHD are primarily challenged in producing and maintaining isochronous self-generated motor rhythms, during both spontaneous and memory-paced tapping. However, they nonetheless exhibit good flexibility for synchronizing to a broad range of external rhythms, suggesting that auditory-motor entrainment for simple rhythms is preserved in ADHD, and that the presence of an external pacer allows overcoming their inherent difficulty in self-generating isochronous motor rhythms. In addition, both groups showed optimal memory-paced tapping for rhythms near their 'counting-based' SMT and PPT, which were slightly faster in the ADHD group. This is in line with the predictions of the Preferred Period Hypothesis, indicating that at least for this well-defined rhythmic behavior (i.e., counting), individuals tend to prefer similar time-scales in both motor production and perceptual evaluation.