White matter microstructure in children and adolescents with ADHD

Glymphatic system dysfunction in adult ADHD: Relationship to cognitive performance

OBJECTIVES

While attention-deficit/hyperactivity disorder (ADHD) persists into adulthood, the relationship between glymphatic system function and cognitive performance in adult ADHD remains unclear. This study investigated the association between glymphatic system markers and cognitive outcomes in adults with ADHD.

METHODS

This case-control study includes 41 adults with ADHD and 108 age-matched healthy controls (HCs). Glymphatic function was evaluated using choroid plexus volume (CPV), diffusion tensor imaging along the perivascular space (DTI-ALPS) index and coupling between blood‑oxygen-level-dependent signals and cerebrospinal fluid signals (BOLD-CSF coupling). Cognitive performance was measured using standardized neuropsychological tests.

RESULTS

Compared with HCs, adults with ADHD exhibited significantly lower bilateral and whole-brain ALPS indices (P < 0.05). Although CPV was increased in the ADHD group, this difference did not reach statistical significance, and no significant differences were observed in BOLD-CSF coupling between the two groups. Furthermore, whole-brain ALPS indices were positively associated with visual memory performance (r = 0.422, P = 0.005), an effect that was more pronounced in the right hemisphere (r = 0.458, P = 0.002).

LIMITATIONS

The cross-sectional design limits causal inferences, and the effects of medication were not fully accounted for.

CONCLUSIONS

These findings identify an association between glymphatic dysfunction and cognitive impairment in adults with ADHD. The observed correlation suggests that alterations in glymphatic function may underlie ADHD-related cognitive deficits. Targeting these pathways could provide novel therapeutic opportunities in the management of adult ADHD.

Causal relationships between white matter connectome and mental disorders: a large-scale genetic correlation study

BACKGROUND

Abnormalities in white matter integrity in mental disorders have attracted widespread attention, yet the genetic correlations and causal effects between white matter structural connectome and various psychiatric conditions remain largely unexplored.

METHODS

In this study, we employed linkage disequilibrium score (LDSC) and high-definition likelihood (HDL) methods to analyze genetic correlations between white matter connectome and mental disorders, followed by bidirectional two-sample Mendelian randomization (MR) analysis to investigate causal relationships. We utilized 206 white matter connectome magnetic resonance imaging (MRI) phenotypes derived from the processed UK Biobank dataset (n = 26,333 individuals) and 12 mental disorders from the latest FinnGen database (n = 402,965 to 449,029 individuals).

RESULTS

Using both methods, we observed 26 pairs of brain white matter connectivity phenotypes and mental disorders showing significant correlations. Forward MR analysis identified two white matter structural connectome phenotypes causally associated with psychiatric disorder risk. Increased connectivity in left-hemisphere visual network(VIS) to right-hemisphere limbic network(LIM)white-matter structural connectivity was associated with increased risk of anxiety disorders. Additionally, decreased connectivity in left-hemisphere visual network to hippocampus white-matter structural connectivity was associated with reduced risk of post-traumatic stress disorder (PTSD). However, reverse MR analysis results did not survive multiple testing correction.

CONCLUSION

These findings provide crucial insights into the complex interplay between white matter structural connectivity and mental disorders, potentially offering new avenues for understanding the neurobiological underpinnings of psychiatric conditions and informing future diagnostic and therapeutic strategies.

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

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

White Matter Microstructural Abnormalities in Children with Familial vs. Non-Familial Attention-Deficit/Hyperactivity Disorder (ADHD)

Background: Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent, heterogeneous neurodevelopmental disorder. Methods: This study presents, for the first time, a comprehensive investigation of white matter microstructural differences between familial ADHD (ADHD-F) and non-familial ADHD (ADHD-NF) using advanced diffusion tensor imaging analyses in a large community-based sample. Results: Children with ADHD-F exhibited significantly greater volume in the right anterior thalamic radiations and the left inferior fronto-occipital fasciculus compared to controls, and greater volume in the left inferior longitudinal fasciculus relative to ADHD-NF. The ADHD-NF group showed reduced fractional anisotropy in the left inferior longitudinal fasciculus compared to the controls. In both the ADHD-F and ADHD-NF groups, a greater volume of anterior thalamic radiation significantly contributed to reduced ADHD symptoms. Conclusions: Our findings suggest that white matter microstructural alterations along the frontal-thalamic pathways may play a critical role in hereditary factors among children with ADHD-F and significantly contribute to elevated inattentive and hyperactive/impulsive behaviors in the affected children.

White matter microstructural subgroups of children with ADHD: Similar clinical presentations and distinct neuropsychological profiles

OBJECTIVES

The current study aimed to explore whether it is possible to subgroup ADHD using white matter microstructural characteristics.

METHODS

In a cohort comprising subjects with ADHD (n = 227) (all aged 6-15 years) and their healthy counterparts (n = 89), the Diffusion Tensor Imaging (DTI) was used to assess fractional anisotropy (FA) in several regions: the body, genu, and splenium of corpus callosum (CC), the bilateral anterior corona radiata, the bilateral internal capsule, and the bilateral superior longitudinal fasciculus. Clinical and neuropsychological profiles were assessed using the ADHD rating scale (ADHD-RS), the Child Behavior Checklist (CBCL), the Behavior Rating Inventory of Executive Function (BRIEF), and CANTAB. Responses to methylphenidate of some of the subjects with ADHD (n = 52) were documented in the Hospital Information System. Cluster analysis was applied to subgroup the ADHD participants. Subsequent between-group comparisons were analyzed using ANCOVA and logistic regression, controlling for age and sex.

RESULTS

Cluster analysis stratified the ADHD subjects into two subgroups. Subsequent analysis revealed that there are no significant differences in those behavioral measures from ADHD-RS, CBCL, or BRIEF between the two ADHD subgroups (all P > .05). Compared with the control group, Cluster-2 exhibited lower FA and performed worse on processing speed, while Cluster-1 had higher FA but showed poorer response inhibition and sustained attention. Additionally, Cluster-2 exhibited a superior response to methylphenidate treatment compared to Cluster-1.

CONCLUSIONS

Although with similar clinical features, ADHD participants could be stratified by their microstructural characteristics, which were further linked to distinct cognitive dysfunction and responses to methylphenidate.

Increasing Health Literacy on ADHD: A Cross-Disciplinary Integrative Review Examining the Impact of ADHD on Brain Maturation, Composition and Function and Cognitive Processes Across the Life Course

There is a significant need to improve ADHD health literacy. This cross-disciplinary integrative review was conducted to synthesise the evidence on the impact ADHD has on brain maturation, composition and function as well as cognitive processes, across the life course. Although results are highly heterogenous, ADHD appears to be associated with (1) a significant delay in cortical maturation and differences in neuroanatomy that do not appear to fully resolve in adulthood, (2) atypical brain function, and (3) atypical cognitive processes. The cognitive processes implicated include working memory, inhibitory control, cognitive flexibility, alerting attention, reward processing, long-term memory, reaction time, time perception and estimation, planning, and complex decision making/problem-solving. We aim to use this data to develop a 'framework/checklist" that parents, adults and clinicians can use to identify the possible mechanisms that may be contributing to an individual with ADHD's challenges. This information can also be used to inform the content of ADHD education programs to ensure participants receive empirically-determine information from high quality review studies and meta-analysis that accurately reflects the rigor and limitations of study findings.

Cerebral blood flow in attention deficit hyperactivity disorder: A systematic review

BACKGROUND AND OBJECTIVES

Attention deficit hyperactivity disorder (ADHD) is one of the most frequent and disabling neurodevelopmental disorders. Recent research on cerebral blood flow (CBF) has enhanced understanding of the underlying pathophysiology in neuropsychiatric disorders. This systematic review aims to synthesize the existing literature on CBF anomalies among individuals with ADHD in comparison to controls.

METHODS

Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach, a systematic literature search was conducted using PubMed, PsycInfo, and Web of Science to identify relevant studies on CBF in ADHD.

RESULTS

Twenty studies, encompassing a total of 1652 participants with ADHD and 580 controls, were included, employing measurements from SPECT (n = 9), ASL (n = 6), PET (n = 4), and BOLD-derived quantitative maps (n = 1). In individuals with ADHD during resting state, hypoperfusion was frequently observed in the right orbitofrontal gyrus, temporal cortex, basal ganglia and putamen. Conversely, hyperperfusion was noted in frontal lobes, left postcentral gyrus, and occipital lobes. During cognitive tasks, hyperperfusion was observed in frontal areas, temporal regions, cingulate cortex and the precuneus. Furthermore, the administration of methylphenidate was associated with increased CBF in striatal and posterior periventricular regions, the right thalamus, and the precentral gyrus.

CONCLUSION

This review highlights diverse CBF anomalies in ADHD. The most consistently reported findings suggest hypoperfusion during resting state in prefrontal and temporal areas, along with the basal ganglia, while there is a hyperperfusion in frontal, parietal and occipital regions. Further research, including longitudinal studies, is essential to develop a comprehensive understanding of CBF implications in ADHD.

Do specific myelin autoantibodies and increased cerebral dopamine neurotrophic factor in the context of inflammation predict the diagnosis of attention deficit hyperactivity disorder in medication-free children?

BACKGROUND

The aim of this study was to investigate the serum levels of anti-myelin basic protein (anti-MBP), anti-myelin oligodentrocyte glycoprotein (anti-MOG), myelin-associated glycoprotein (MAG), high-sensitivity C-reactive protein (hs-CRP), cerebral dopamine neurotrophic factor (CDNF), cerebellin-1, and reelin and their relationships with clinical severity and irritability behaviours in children with attention deficit (AD) hyperactivity disorder (ADHD) and typically developing (TD) healthy controls.

METHODS

In this study, 141 children with ADHD between the ages of 8 and 14 years who were medication-free and 135 TD healthy controls were included. The serum levels of anti-MBP, anti-MOG, MAG, CDNF, hs-CRP, cerebellin, and reelin were measured using enzyme-linked immunosorbent assay kits. The Turgay Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV)-based Screening and Evaluation Scale for Attention Deficit and Disruptive Behavior Disorders-Parent Form (TDSM-IV-O) and the affective reactivity index (ARI) scale were used to assess clinical severity and irritability behaviours in the children.

RESULTS

The MAG, CDNF, hs-CRP, reelin, and cerebellin levels were significantly higher in the ADHD group than in the control group, but no significant differences in anti-MBP and anti-MOG levels were found between the groups. Compared with the controls, the patients with ADHD showed significantly higher scores on the ARI self- and parent-report scales. The reelin, hs-CRP, and MAG levels were significantly associated with the TDSM-IV-O AD scores, AD and oppositional defiant (OD) disorder scores and hyperactivity, and OD and conduct disorder scores, respectively. Hs-CRP was significantly associated with anti-MBP and cerebellin levels. In an analysis of covariance, the results were unchanged even after controlling for potential confounders such as age, body mass index, and sex.

CONCLUSION

This study demonstrates that MAG, CDNF, hs-CRP, reelin, and cerebellin levels may play a potential role in the pathogenesis of ADHD.

Neurobiology of attention-deficit hyperactivity disorder: historical challenges and emerging frontiers

Extensive investigations spanning multiple levels of inquiry, from genetic to behavioural studies, have sought to unravel the mechanistic foundations of attention-deficit hyperactivity disorder (ADHD), with the aspiration of developing efficacious treatments for this condition. Despite these efforts, the pathogenesis of ADHD remains elusive. In this Review, we reflect on what has been learned about ADHD while also providing a framework that may serve as a roadmap for future investigations. We emphasize that ADHD is a highly heterogeneous disorder with multiple aetiologies that necessitates a multifactorial dimensional phenotype, rather than a fixed dichotomous conceptualization. We highlight new findings that suggest a more brain-wide, 'global' view of the disorder, rather than the traditional localizationist framework, which asserts that a limited set of brain regions or networks underlie ADHD. Last, we underscore how underpowered studies that have aimed to associate neurobiology with ADHD phenotypes have long precluded the field from making progress. However, a new age of ADHD research with refined phenotypes, advanced methods, creative study designs and adequately powered investigations is beginning to put the field on a good footing. Indeed, the field is at a promising juncture to advance the neurobiological understanding of ADHD and fulfil the promise of clinical utility.

Elucidating Microstructural Alterations in Neurodevelopmental Disorders: Application of Advanced Diffusion-Weighted Imaging in Children With Rasopathies

Neurodevelopmental disorders (NDDs) can severely impact functioning yet effective treatments are limited. Greater insight into the neurobiology underlying NDDs is critical to the development of successful treatments. Using a genetics-first approach, we investigated the potential of advanced diffusion-weighted imaging (DWI) techniques to characterize the neural microstructure unique to neurofibromatosis type 1 (NF1) and Noonan syndrome (NS). In this prospective study, children with NF1, NS, and typical developing (TD) were scanned using a multi-shell DWI sequence optimized for neurite orientation density and dispersion imaging (NODDI) and diffusion kurtosis imaging (DKI). Region-of-interest and tract-based analysis were conducted on subcortical regions and white matter tracts. Analysis of covariance, principal components, and linear discriminant analysis compared between three groups. 88 participants (Mage = 9.36, SDage = 2.61; 44 male) were included: 31 NS, 25 NF1, and 32 TD. Subcortical regions differed between NF1 and NS, particularly in the thalamus where the neurite density index (NDI; estimated difference 0.044 [95% CI: -0.034, 0.053], d = 2.36), orientation dispersion index (ODI; estimate 0.018 [95% CI: 0.010, 0.026], d = 1.39), and mean kurtosis (MK; estimate 0.049 [95% CI: 0.025, 0.072], d = 1.39) were lower in NF1 compared with NS (all p < 0.0001). Reduced NDI was found in NF1 and NS compared with TD in all 39 white matter tracts investigated (p < 0.0001). Reduced MK was found in a majority of the tracts in NF1 and NS relative to TD, while fewer differences in ODI were observed. The middle cerebellar peduncle showed lower NDI (estimate 0.038 [95% CI: 0.021, 0.056], p < 0.0001) and MK (estimate 0.057 [95% CI: 0.026, 0.089], p < 0.0001) in NF1 compared to NS. Multivariate analyses distinguished between groups using NDI, ODI, and MK measures. Principal components analysis confirmed that the clinical groups differ most from TD in white matter tract-based NDI and MK, whereas ODI values appear similar across the groups. The subcortical regions showed several differences between NF1 and NS, to the extent that a linear discriminant analysis could classify participants with NF1 with an accuracy rate of 97%. Differences in neural microstructure were detected between NF1 and NS, particularly in subcortical regions and the middle cerebellar peduncle, in line with pre-clinical evidence. Advanced DWI techniques detected subtle alterations not found in prior work using conventional diffusion tensor imaging.

Modeling Shared and Specific Variances of Irritability, Inattention, and Hyperactivity Yields Novel Insights Into White Matter Perturbations

OBJECTIVE

Irritability, inattention, and hyperactivity, which are common presentations of childhood psychopathology, have been associated with perturbed white matter microstructure. However, similar tracts have been implicated across these phenotypes; such non-specificity could be rooted in their high co-occurrence. To address this problem, we use a bifactor approach parsing unique and shared components of irritability, inattention, and hyperactivity, which we then relate to white matter microstructure.

METHOD

We developed a bifactor model based on the Conners Comprehensive Behavioral Rating Scale in a sample of youth with no psychiatric diagnosis or a primary diagnosis of attention-deficit/hyperactivity disorder or disruptive mood dysregulation disorder (n = 521). We applied the model to an independent yet sociodemographically and clinically comparable sample (n = 152), in which we tested associations between latent variables and fractional anisotropy (FA).

RESULTS

The bifactor model fit well (comparative fit index = 0.99; root mean square error of approximation = 0.07). The shared factor was positively associated with an independent measure of impulsivity (ρS = 0.88, pFDR < .001) and negatively related to whole-brain FA (r = -0.20), as well as FA of the corticospinal tract (all pFWE < .05). FA increased with age and deviation from this curve, indicating that altered white matter maturation was associated with the hyperactivity-specific factor (r = -0.16, pFWE < .05). Inattention-specific and irritability-specific factors were not linked to FA.

CONCLUSION

Perturbed white matter microstructure may represent a shared neurobiological mechanism of irritability, inattention, and hyperactivity related to heightened impulsivity. Furthermore, hyperactivity might be uniquely associated with a delay in white matter maturation.

PLAIN LANGUAGE SUMMARY

In this study, researchers developed a model identifying shared aspects of key symptoms of disruptive mood dysregulation disorder (DMDD) and attention-deficit hyperactivity disorder (ADHD), more specifically irritability, inattention, and hyperactivity. In 521 participants, impulsivity emerged as a shared factor. Applied to 152 youth with brain imaging data, shared impulsivity, not specific symptoms, related to atypical brain structure. Additionally, hyperactivity was linked to delayed white matter maturation. Study findings suggest this approach might identify mechanisms of these childhood disorders that remain hidden when relying on traditional diagnostic categories.

Machine-learning-based feature selection to identify attention-deficit hyperactivity disorder using whole-brain white matter microstructure: A longitudinal study

BACKGROUND

We aimed to identify important features of white matter microstructures collectively distinguishing individuals with attention-deficit/hyperactivity disorder (ADHD) from those without ADHD using a machine-learning approach.

METHODS

Fifty-one ADHD patients and 60 typically developing controls (TDC) underwent diffusion spectrum imaging at two time points. We evaluated three models to classify ADHD and TDC using various machine-learning algorithms. Model 1 employed baseline white matter features of 45 white matter tracts at Time 1; Model 2 incorporated features from both time points; and Model 3 (main analysis) further included the relative rate of change per year of white matter tracts.

RESULTS

The random forest algorithm demonstrated the best performance for classification. Model 1 achieved an area-under-the-curve (AUC) of 0.67. Model 3, incorporating Time 2 variables and relative rate of change per year, improved the performance (AUC = 0.73). In addition to identifying several white matter features at two time points, we found that the relative rate of change per year in the superior longitudinal fasciculus, frontal aslant tract, stria terminalis, inferior fronto-occipital fasciculus, thalamic and striatal tracts, and other tracts involving sensorimotor regions are important features of ADHD. A higher relative change rate in certain tracts was associated with greater improvement in visual attention, spatial short-term memory, and spatial working memory.

CONCLUSIONS

Our findings support the significant diagnostic value of white matter microstructure and the developmental change rates of specific tracts, reflecting deviations from typical development trajectories, in identifying ADHD.

Quantification of myelination in children with attention-deficit/hyperactivity disorder: a comparative assessment with synthetic MRI and DTI

Evaluation of myelin content is crucial for attention-deficit/hyperactivity disorder (ADHD). To estimate myelin content in ADHD based on synthetic MRI-based method and compare it with established diffusion tensor imaging (DTI) method. Fifth-nine ADHD and fifty typically developing (TD) children were recruited. Global and regional myelin content (myelin volume fraction [MVF] and myelin volume [MYV]) were assessed using SyMRI and compared with DTI metrics (fractional anisotropy and mean/radial/axial diffusivity). The relationship between significant MRI parameters and clinical variables were assessed in ADHD. No between-group differences of whole-brain myelin content were found. Compared to TDs, ADHD showed higher mean MVF in bilateral internal capsule, external capsule, corona radiata, and corpus callosum, as well as in left tapetum, left superior fronto-occipital fascicular, and right cingulum (all PFDR-corrected < 0.05). Increased MYV were found in similar regions. Abnormalities of DTI metrics were mainly in bilateral corticospinal tract. Besides, MVF in right retro lenticular part of internal capsule was negatively correlated with cancellation test scores (r = - 0.41, P = 0.002), and MYV in right posterior limb of internal capsule (r = 0.377, P = 0.040) and left superior corona radiata (r = 0.375, P = 0.041) were positively correlated with cancellation test scores in ADHD. Increased myelin content underscored the important pathway of frontostriatal tract, posterior thalamic radiation, and corpus callosum underlying ADHD, which reinforced the insights into myelin quantification and its potential role in pathophysiological mechanism and disease diagnosis. Prospectively registered trials number: ChiCTR2100048109; date: 2021-07.

Human transcriptome array analysis and diffusion tensor imaging in attention-deficit/hyperactivity disorder

The mRNA markers identified using microarray assay and diffusion tensor magnetic resonance imaging (DTI) were applied to elucidate the pathophysiology of attention-deficit hyperactivity disorder (ADHD). First, we obtained total RNA from leukocytes from three children with ADHD and three healthy controls for analysis with microarray assays. Subsequently, we applied real-time quantitative polymerase chain reaction (qRT‒PCR) assays to validate the differential expression of 7 genes (COX7B, CYCS, TFAM, UTP14A, ZNF280C, IFT57 and NDUFB5) between 130 ADHD patients and 70 controls, and we built an ADHD prediction model based on the ΔCt values of aforementioned seven genes (AUROC = 0.98). Finally, in a validation group (28 patients with ADHD and 27 healthy controls), mRNA expression of the above seven genes also significantly differentiated ADHD patients from controls (AUROC value = 0.91). The DTI analysis showed increased fractional anisotropy (FA) of the forceps minor, superior corona radiata, posterior corona radiata and anterior corona radiata in ADHD patients. Moreover, the FA of the right superior corona radiata tract was positively correlated with ΔCt levels of the COX7B gene and the IFT57 gene. The results shed a new light on a genetic profile of ADHD that may help in deciphering the white matter microstructural features in disease pathogenesis.

Microstructural White Matter Abnormalities in Children and Adolescents With Narcolepsy Type 1

BACKGROUND

In 2010, the H1N1 Pandemrix vaccination campaign was followed by a sudden increase in narcolepsy type 1 (NT1). We investigated the brain white matter microstructure in children with onset of NT1 within two years after the Pandemrix vaccination.

METHODS

We performed diffusion-weighted magnetic resonance imaging (MRI) on 19 children and adolescents with NT1 and 19 healthy controls. Imaging was performed at a median of 4 years after the diagnosis at a median age of 16 years. For the MRI, we used whole-brain tractography and tract-based spatial statistics (TBSS). We compared these results with medical records and questionnaire data.

RESULTS

Narcoleptic children showed a global decrease in mean, axial, and radial diffusivity and an increase in planarity coefficient in the white matter TBSS skeleton and tractography. These differences were widespread, and there was an increased asymmetry of the mean diffusivity in children with NT1. The global microstructural metrics were reflected in behavior, and especially the axial diffusion levels correlated with anxiety and depression symptoms and social and behavioral problems.

CONCLUSIONS

In pediatric patients with Pandemrix-associated NT1, several global changes in the brain white matter network skeleton were observed within five years after the onset of NT1. The degree of changes correlates with behavioral problems.

Association of Chronic Obstructive Pulmonary Disease with Risk of Psychiatric Disorders: A Two-Sample Mendelian Randomization Study

Background

Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disorder often accompanied by comorbidities. Although the past few years have witnessed significant scientific progress, the potential relationship between COPD and mental illness remains a subject of debate.

Materials and Methods

We retrieved COPD data from the genome-wide association studies (GWAS) directory and data on mental illnesses, including Alzheimer's disease, schizophrenia, panic disorder, attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder, multiple disabilities, obsessive-compulsive disorder, post-traumatic stress disorder, and schizophrenia, from the Psychiatric Genomics Consortium. A two-sample Mendelian randomization (MR) approach was applied to explore the association between COPD and mental illnesses, with subgroup analyses based on smoking history.

Results

Our two-sample MR analysis revealed no causal link between overall COPD and the development of common psychiatric disorders. Subgroup analyses based on smoking history showed no causal association between never-smokers with COPD and the occurrence of psychiatric disorders. However, ever-smokers with COPD were associated with a significantly increased risk of ADHD (OR: 2.303, 95% CI: 1.558-3.403, P = 0.001) and a modestly reduced risk of Alzheimer's disease (OR: 0.994, 95% CI: 0.988-0.999, P = 0.034).

Conclusion

COPD patients with a history of smoking face a higher risk of developing ADHD but may experience a slight reduction in the risk of Alzheimer's disease. Conversely, there was no observed causal association between COPD and psychiatric disorders among patients who never smoked.

Abnormal wiring of the structural connectome in adults with ADHD

Current knowledge of white matter changes in large-scale brain networks in adult attention-deficit/hyperactivity disorder (ADHD) is scarce. We collected diffusion-weighted magnetic resonance imaging data in 40 adults with ADHD and 36 neurotypical controls and used constrained spherical deconvolution-based tractography to reconstruct whole-brain structural connectivity networks. We used network-based statistic (NBS) and graph theoretical analysis to investigate differences in these networks between the ADHD and control groups, as well as associations between structural connectivity and ADHD symptoms assessed with the Adult ADHD Self-Report Scale or performance in the Conners Continuous Performance Test 2 (CPT-2). NBS revealed decreased connectivity in the ADHD group compared to the neurotypical controls in widespread unilateral networks, which included subcortical and corticocortical structures and encompassed dorsal and ventral attention networks and visual and somatomotor systems. Furthermore, hypoconnectivity in a predominantly left-frontal network was associated with higher amount of commission errors in CPT-2. Graph theoretical analysis did not reveal topological differences between the groups or associations between topological properties and ADHD symptoms or task performance. Our results suggest that abnormal structural wiring of the brain in adult ADHD is manifested as widespread intrahemispheric hypoconnectivity in networks previously associated with ADHD in functional neuroimaging studies.

General anaesthesia, the developing brain, and cerebral white matter alterations: a narrative review

The potential neurotoxic impact of anaesthetic agents has been the subject of sustained debate and continuing research. White matter, which comprises more than half of the brain volume and largely consists of myelinated axonal bundles, is critical for communication between diverse brain regions and for supporting neurobehavioural function. Evidence points to a correlation between exposure to anaesthesia and white matter alterations, which might underpin the ensuing cognitive and behavioural abnormalities. This review summarises the neuropathological and neuroimaging findings related to anaesthesia-induced white matter alterations in the developing brain. Future research is required to understand the effects of anaesthesia exposure on white matter development.

Maternal Thyroid Function During Pregnancy and Offspring White Matter Microstructure in Early Adulthood: A Prospective Birth Cohort Study

Background: The fetus is fully dependent on maternal thyroid hormones until mid-gestation and suboptimal maternal thyroid function has been associated with alterations in the neurodevelopment of the offspring. We used maternal free thyroxine (fT4) and thyrotropin (TSH) levels in early gestation to study the association of maternal thyroid function during early pregnancy and offspring brain white matter (WM) integrity in early adulthood. Methods: Our study population consisted of a total of 292 mother-child pairs. Maternal fT4 and TSH were used as predictors and offspring multimodal imaging measures of fractional anisotropy, mean diffusivity, and magnetization transfer ratio (FA, MD, and MTR) as dependent variables. First, as Global analysis, all analyzed 14 WM tracts were studied simultaneously using linear-mixed effect models. Second, if a global effect was detected, a post hoc Tract-wise analysis was carried out using linear models individually in each WM tract. Study population was stratified by sex. Results: We found a positive association between maternal fT4 and offspring Global FA in males when adjusted for all maternal and offspring covariates (n = 114; β = 0.154; confidence interval = 0.045-0.263; p = 0.006). The finding was observed to be driven by multiple WM tracts, of which three projection fiber tracts and the forceps minor survived correcting for multiple comparisons in Tract-wise analysis. Conclusions: Maternal thyroid function in early pregnancy was observed to be associated with WM microstructure in male offspring in early adulthood. Our results suggest that maternal fT4 levels in early pregnancy may modulate axonal characteristics, with a long-term effect on offspring WM development.

Distributed genetic effects of the corpus callosum subregions suggest links to neuropsychiatric disorders and related traits

BACKGROUND

The corpus callosum (CC) is a brain structure with a high heritability and potential role in psychiatric disorders. However, the genetic architecture of the CC and the genetic link with psychiatric disorders remain largely unclear. We investigated the genetic architectures of the volume of the CC and its subregions and the genetic overlap with psychiatric disorders.

METHODS

We applied multivariate genome-wide association study (GWAS) to genetic and T1-weighted magnetic resonance imaging (MRI) data of 40,894 individuals from the UK Biobank, aiming to boost genetic discovery and to assess the pleiotropic effects across volumes of the five subregions of the CC (posterior, mid-posterior, central, mid-anterior and anterior) obtained by FreeSurfer 7.1. Multivariate GWAS was run combining all subregions, co-varying for relevant variables. Gene-set enrichment analyses were performed using MAGMA. Linkage disequilibrium score regression (LDSC) was used to determine Single nucleotide polymorphism (SNP)-based heritability of total CC volume and volumes of its subregions as well as their genetic correlations with relevant psychiatric traits.

RESULTS

We identified 70 independent loci with distributed effects across the five subregions of the CC (p < 5 × 10-8). Additionally, we identified 33 significant loci in the anterior subregion, 23 in the mid-anterior, 29 in the central, 7 in the mid-posterior and 56 in the posterior subregion. Gene-set analysis revealed 156 significant genes contributing to volume of the CC subregions (p < 2.6 × 10-6). LDSC estimated the heritability of CC to (h2SNP = 0.38, SE = 0.03) and subregions ranging from 0.22 (SE = 0.02) to 0.37 (SE = 0.03). We found significant genetic correlations of total CC volume with bipolar disorder (BD, rg = -0.09, SE = 0.03; p = 5.9 × 10-3) and drinks consumed per week (rg = -0.09, SE = 0.02; p = 4.8 × 10-4), and volume of the mid-anterior subregion with BD (rg = -0.12, SE = 0.02; p = 2.5 × 10-4), major depressive disorder (MDD) (rg = -0.12, SE = 0.04; p = 3.6 × 10-3), drinks consumed per week (rg = -0.13, SE = 0.04; p = 1.8 × 10-3) and cannabis use (rg = -0.09, SE = 0.03; p = 8.4 × 10-3).

CONCLUSIONS

Our results demonstrate that the CC has a polygenic architecture implicating multiple genes and show that CC subregion volumes are heritable. We found that distinct genetic factors are involved in the development of anterior and posterior subregions, consistent with their divergent functional specialisation. Significant genetic correlation between volumes of the CC and BD, drinks per week, MDD and cannabis consumption subregion volumes with psychiatric traits is noteworthy and deserving of further investigation.

Microstructure abnormalities of the diffusion quantities in children with attention-deficit/hyperactivity disorder: an AFQ and TBSS study

Objective

To explore the specific alterations of white matter microstructure in children with attention-deficit/hyperactivity disorder (ADHD) by automated fiber quantification (AFQ) and tract-based spatial statistics (TBSS), and to analyze the correlation between white matter abnormality and impairment of executive function.

Methods

In this prospective study, a total of twenty-seven patients diagnosed with ADHD (20 males, 7 females; mean age of 8.89 ± 1.67 years) and twenty-two healthy control (HC) individuals (11 males, 11 females, mean age of 9.82 ± 2.13 years) were included. All participants were scanned with diffusion kurtosis imaging (DKI) and assessed for executive functions. AFQ and TBSS analysis methods were used to investigate the white matter fiber impairment of ADHD patients, respectively. Axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD) and fractional anisotropy (FA) of 17 fiber properties were calculated using the AFQ. The mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), mean diffusivity (MDDKI), axial diffusivity (ADDKI), radial diffusivity (RDDKI) and fractional anisotropy (FADKI) of DKI and AD, RD, MD, and FA of diffusion tensor imaging (DTI) assessed the integrity of the white matter based on TBSS. Partial correlation analyses were conducted to evaluate the correlation between white matter abnormalities and clinical test scores in ADHD while taking age, gender, and education years into account. The analyses were all family-wise error rate (FWE) corrected.

Results

ADHD patients performed worse on the Behavior Rating Inventory of Executive Function (BRIEF) test (p < 0.05). Minor variances existed in gender and age between ADHD and HC, but these variances did not yield statistically significant distinctions. There were no significant differences in TBSS for DKI and DTI parameters (p > 0.05, TFCE-corrected). Compared to HC volunteers, the mean AD value of right cingulum bundle (CB_R) fiber tract showed a significantly higher level in ADHD patients following the correction of FWE. As a result of the point-wise comparison between groups, significant alterations (FWE correction, p < 0.05) were mainly located in AD (nodes 36-38, nodes 83-97) and MD (nodes 92-95) of CB_R. There was no significant correlation between white matter diffusion parameters and clinical test scores in ADHD while taking age, gender, and education years into account.

Conclusion

The AFQ method can detect ADHD white matter abnormalities in a specific location with greater sensitivity, and the CB_R played a critical role. Our findings may be helpful in further studying the relationship between focal white matter abnormalities and ADHD.

Cognitive Sparing in Proton versus Photon Radiotherapy for Pediatric Brain Tumor Is Associated with White Matter Integrity: An Exploratory Study

Radiotherapy for pediatric brain tumors is associated with reduced white matter structural integrity and neurocognitive decline. Superior cognitive outcomes have been reported following proton radiotherapy (PRT) compared to photon radiotherapy (XRT), presumably due to improved sparing of normal brain tissue. This exploratory study examined the relationship between white matter change and late cognitive effects in pediatric brain tumor survivors treated with XRT versus PRT. Pediatric brain tumor survivors treated with XRT (n = 10) or PRT (n = 12) underwent neuropsychological testing and diffusion weighted imaging >7 years post-radiotherapy. A healthy comparison group (n = 23) was also recruited. Participants completed age-appropriate measures of intellectual functioning, visual-motor integration, and motor coordination. Tractography was conducted using automated fiber quantification (AFQ). Fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) were extracted from 12 tracts of interest. Overall, both white matter integrity (FA) and neuropsychological performance were lower in XRT patients while PRT patients were similar to healthy control participants with respect to both FA and cognitive functioning. These findings support improved long-term outcomes in PRT versus XRT. This exploratory study is the first to directly support for white matter integrity as a mechanism of cognitive sparing in PRT.

A fatal alliance: Glial connexins, myelin pathology and mental disorders

Mature oligodendrocytes are myelin forming glial cells which are responsible for myelination of neuronal axons in the white matter of the central nervous system. Myelin pathology is a major feature of severe neurological disorders. Oligodendrocyte-specific gene mutations and/or white matter alterations have also been addressed in a variety of mental disorders. Breakdown of myelin integrity and demyelination is associated with severe symptoms, including impairments in motor coordination, breathing, dysarthria, perception (vision and hearing), and cognition. Furthermore, there is evidence indicating that myelin sheath defects and white matter pathology contributes to the affective and cognitive symptoms of patients with mental disorders. Oligodendrocytes express the connexins GJC2; mCx47 [human (GJC2) and mouse (mCx47) connexin gene nomenclature according to Söhl and Willecke (2003)], GJB1; mCx32, and GJD1; mCx29 in both white and gray matter. Preclinical findings indicate that alterations in connexin expression in oligodendrocytes and astrocytes can induce myelin defects. GJC2; mCx47 is expressed at early embryonic stages in oligodendrocyte precursors cells which precedes central nervous system myelination. In adult humans and animals GJC2, respectively mCx47 expression is essential for oligodendrocyte function and ensures adequate myelination as well as myelin maintenance in the central nervous system. In the past decade, evidence has accumulated suggesting that mental disorders can be accompanied by changes in connexin expression, myelin sheath defects and corresponding white matter alterations. This dual pathology could compromise inter-neuronal information transfer, processing and communication and eventually contribute to behavioral, sensory-motor, affective and cognitive symptoms in patients with mental disorders. The induction of myelin repair and remyelination in the central nervous system of patients with mental disorders could help to restore normal neuronal information propagation and ameliorate behavioral and cognitive symptoms in individuals with mental disorders.

Atypical development in white matter microstructures in ADHD: A longitudinal diffusion imaging study

BACKGROUND

In cross-sectional studies, alterations in white matter microstructure are evident in children with attention-deficit/hyperactivity disorder (ADHD) but not so prominent in adults with ADHD compared to typically-developing controls (TDC). Moreover, the developmental trajectories of white matter microstructures in ADHD are unclear, given the limited longitudinal imaging studies that characterize developmental changes in ADHD vs. TDC.

METHODS

This longitudinal study acquired diffusion spectrum imaging (DSI) at two time points. The sample included 55 participants with ADHD and 61 TDC. The enrollment/first DSI age ranged from 7 to 18 years, with a five-year mean follow-up time. We examined time-by-diagnosis interaction on the generalized fractional anisotropy (GFA) of 45 white matter tracts, adjusting for confounding factors and correcting for multiple comparisons. We also tested whether the longitudinal changes of microstructures were associated with ADHD symptoms and attention performance in a computerized continuous performance test.

RESULTS

Participants with ADHD showed more rapid development of GFA in the arcuate fasciculus, superior longitudinal fasciculus, frontal aslant tract, cingulum, inferior fronto-occipital fasciculus (IFOF), frontostriatal tract connecting the prefrontal cortex (FS-PFC), thalamic radiation, corticospinal tract, and corpus callosum. Within participants with ADHD, more rapid GFA increases in cingulum and FS-PFC were associated with slower decreases in inattention symptoms. In addition, in all participants, more rapid GFA increases in cingulum and IFOF were associated with greater improvement in attention performance.

CONCLUSION

Our findings suggest atypical developmental trajectories of white matter tracts in ADHD, characterized by normalization and possible compensatory neuroplastic processes with age from childhood to early adulthood.

Better characterization of attention and hyperactivity/impulsivity in children with ADHD: The key to understanding the underlying white matter microstructure

The apparent increase in the prevalence of the attention deficit hyperactivity disorder (ADHD) diagnosis raises many questions regarding the variability of the subjective diagnostic method. This comprehensive review reports findings in studies assessing white matter (WM) bundles in diffusion MRI and symptom severity in children with ADHD. These studies suggested the involvement of the connections between the frontal, parietal, and basal ganglia regions. This review discusses the limitations surrounding diffusion tensor imaging (DTI) and suggests novel imaging techniques allowing for a more reliable representation of the underlying biology. We propose a more inclusive approach to studying ADHD that includes known endophenotypes within the ADHD diagnosis. Aligned with the Research Domain Criteria Initiative, we also propose to investigate attentional capabilities and impulsive behaviours outside of the borders of the diagnosis. We support the existing hypothesis that ADHD originates from a developmental error and propose that it could lead to an accumulation in time of abnormalities in WM microstructure and pathways. Finally, state-of-the-art diffusion processing and novel artificial intelligence approaches would be beneficial to fully understand the pathophysiology of ADHD.

Decomposition-Based Correlation Learning for Multi-Modal MRI-Based Classification of Neuropsychiatric Disorders

Multi-modal magnetic resonance imaging (MRI) is widely used for diagnosing brain disease in clinical practice. However, the high-dimensionality of MRI images is challenging when training a convolution neural network. In addition, utilizing multiple MRI modalities jointly is even more challenging. We developed a method using decomposition-based correlation learning (DCL). To overcome the above challenges, we used a strategy to capture the complex relationship between structural MRI and functional MRI data. Under the guidance of matrix decomposition, DCL takes into account the spike magnitude of leading eigenvalues, the number of samples, and the dimensionality of the matrix. A canonical correlation analysis (CCA) was used to analyze the correlation and construct matrices. We evaluated DCL in the classification of multiple neuropsychiatric disorders listed in the Consortium for Neuropsychiatric Phenomics (CNP) dataset. In experiments, our method had a higher accuracy than several existing methods. Moreover, we found interesting feature connections from brain matrices based on DCL that can differentiate disease and normal cases and different subtypes of the disease. Furthermore, we extended experiments on a large sample size dataset and a small sample size dataset, compared with several other well-established methods that were designed for the multi neuropsychiatric disorder classification; our proposed method achieved state-of-the-art performance on all three datasets.

Clinical and Socio-Demographic Variables Associated with the Diagnosis of Long COVID Syndrome in Youth: A Population-Based Study

This study examines the demographic, clinical and socioeconomic factors associated with diagnosis of long COVID syndrome (LCS). Data of 20,601 COVID-19-positive children aged 5 to 18 years were collected between 2020 and 2021 in an Israeli database. Logistic regression analysis was used to evaluate the adjusted odds ratio for the characteristics of the COVID-19 infection and pre-COVID-19 morbidities. Children with LCS were significantly more likely to have been severely symptomatic, required hospitalization, and experienced recurrent acute infection within 180 days. In addition, children with LCS were significantly more likely to have had ADHD, chronic urticaria, and allergic rhinitis. Diagnosis of LCS is significantly associated with pre-COVID-19 ADHD diagnosis, suggesting clinicians treating ADHD children who become infected with COVID-19 remain vigilant for the possibility of LCS. Although the risk of severe COVID-19 infection and LCS in children is low, further research on possible morbidity related to LCS in children is needed.