Dorsal-to-ventral imbalance in the superior longitudinal fasciculus mediates methylphenidate's effect on beta oscillations in ADHD

Prediction of methylphenidate treatment response for ADHD using conventional and radiomics T1 and DTI features: Secondary analysis of a randomized clinical trial

BACKGROUND

Attention-Deficit/Hyperactivity Disorder (ADHD) is commonly treated with methylphenidate (MPH). Although highly effective, MPH treatment still has a relatively high non-response rate of around 30%, highlighting the need for a better understanding of treatment response. Radiomics of T1-weighted images and Diffusion Tensor Imaging (DTI) combined with machine learning approaches could offer a novel method for assessing MPH treatment response.

PURPOSE

To evaluate the accuracy of both conventional and radiomics approaches in predicting treatment response based on baseline T1 and DTI data in stimulant-naive ADHD participants.

METHODS

We performed a secondary analysis of a randomized clinical trial (ePOD-MPH), involving 47 stimulant-naive ADHD participants (23 boys aged 11.4 ± 0.4 years, 24 men aged 28.1 ± 4.3 years) who underwent 16 weeks of treatment with MPH. Baseline T1-weighted and DTI MRI scans were acquired. Treatment response was assessed at 8 weeks (during treatment) and one week after cessation of 16-week treatment (post-treatment) using the Clinical Global Impressions - Improvement scale as our primary outcome. We compared prediction accuracy using a conventional model and a radiomics model. The conventional approach included the volume of bilateral caudate, putamen, pallidum, accumbens, and hippocampus, and for DTI the mean fractional anisotropy (FA) of the entire brain white matter, bilateral Anterior Thalamic Radiation (ATR), and the splenium of the corpus callosum, totaling 14 regional features. For the radiomics approach, 380 features (shape-based and first-order statistics) were extracted from these 14 regions. XGBoost models with nested cross-validation were used and constructed for the total cohort (n = 47), as well as children (n = 23) and adults (n = 24) separately. Exact binomial tests were employed to compare model performance.

RESULTS

For the conventional model, balanced accuracy (bAcc) in predicting treatment response during treatment was 63 % for the total cohort, 32 % for children, and 36 % for adults (Area Under the Receiver Operating Characteristic Curve (AUC-ROC): 0.69, 0.33, 0.41 respectively). Radiomics models demonstrated bAcc's of 68 %, 64 %, and 64 % during treatment (AUC-ROCs of 0.73, 0.62, 0.69 respectively). These predictions were better than chance for both conventional and radiomics models in the total cohort (p = 0.04, p = 0.003 respectively). The radiomics models outperformed the conventional models during treatment in children only (p = 0.02). At post-treatment, performance was markedly reduced.

CONCLUSION

While conventional and radiomics models performed equally well in predicting clinical improvement across children and adults during treatment, radiomics features offered enhanced structural information beyond conventional region-based volume and FA averages in children. Prediction of symptom improvement one week after treatment cessation was poor, potentially due to the transient effects of stimulant treatment on symptom improvement.

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.

Alpha/beta-gamma decoupling in methylphenidate medicated ADHD patients

There is much interest to understand how different neural rhythms function, interact and are regulated. Here, we focus on WM delay gamma to investigate its coupling with alpha/beta rhythms and its neuromodulation by methylphenidate. We address this through the use of human EEG conducted in healthy and ADHD subjects which revealed ADHD-specific electrophysiological deficits and MPH-induced normalization of gamma amplitude and its coupling with alpha/beta rhythms. Decreased alpha/beta-gamma coupling is known to facilitate memory representations via disinhibition of gamma ensembles coding the maintained stimuli. Here, we present EEG evidence which suggests that these dynamics are sensitive to catecholaminergic neuromodulation. MPH decreased alpha/beta-gamma coupling and this was related to the increase in delay-relevant gamma activity evoked by the same drug. These results add further to the neuromodulatory findings that reflect an electrophysiological dimension to the well-known link between WM delay and catecholaminergic transmission.

Methylphenidate for children and adolescents with attention deficit hyperactivity disorder (ADHD)

BACKGROUND

Attention deficit hyperactivity disorder (ADHD) is one of the most commonly diagnosed and treated psychiatric disorders in childhood. Typically, children and adolescents with ADHD find it difficult to pay attention and they are hyperactive and impulsive. Methylphenidate is the psychostimulant most often prescribed, but the evidence on benefits and harms is uncertain. This is an update of our comprehensive systematic review on benefits and harms published in 2015.

OBJECTIVES

To assess the beneficial and harmful effects of methylphenidate for children and adolescents with ADHD.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, three other databases and two trials registers up to March 2022. In addition, we checked reference lists and requested published and unpublished data from manufacturers of methylphenidate.

SELECTION CRITERIA

We included all randomised clinical trials (RCTs) comparing methylphenidate versus placebo or no intervention in children and adolescents aged 18 years and younger with a diagnosis of ADHD. The search was not limited by publication year or language, but trial inclusion required that 75% or more of participants had a normal intellectual quotient (IQ > 70). We assessed two primary outcomes, ADHD symptoms and serious adverse events, and three secondary outcomes, adverse events considered non-serious, general behaviour, and quality of life.

DATA COLLECTION AND ANALYSIS

Two review authors independently conducted data extraction and risk of bias assessment for each trial. Six review authors including two review authors from the original publication participated in the update in 2022. We used standard Cochrane methodological procedures. Data from parallel-group trials and first-period data from cross-over trials formed the basis of our primary analyses. We undertook separate analyses using end-of-last period data from cross-over trials. We used Trial Sequential Analyses (TSA) to control for type I (5%) and type II (20%) errors, and we assessed and downgraded evidence according to the GRADE approach.

MAIN RESULTS

We included 212 trials (16,302 participants randomised); 55 parallel-group trials (8104 participants randomised), and 156 cross-over trials (8033 participants randomised) as well as one trial with a parallel phase (114 participants randomised) and a cross-over phase (165 participants randomised). The mean age of participants was 9.8 years ranging from 3 to 18 years (two trials from 3 to 21 years). The male-female ratio was 3:1. Most trials were carried out in high-income countries, and 86/212 included trials (41%) were funded or partly funded by the pharmaceutical industry. Methylphenidate treatment duration ranged from 1 to 425 days, with a mean duration of 28.8 days. Trials compared methylphenidate with placebo (200 trials) and with no intervention (12 trials). Only 165/212 trials included usable data on one or more outcomes from 14,271 participants. Of the 212 trials, we assessed 191 at high risk of bias and 21 at low risk of bias. If, however, deblinding of methylphenidate due to typical adverse events is considered, then all 212 trials were at high risk of bias.

PRIMARY OUTCOMES

methylphenidate versus placebo or no intervention may improve teacher-rated ADHD symptoms (standardised mean difference (SMD) -0.74, 95% confidence interval (CI) -0.88 to -0.61; I² = 38%; 21 trials; 1728 participants; very low-certainty evidence). This corresponds to a mean difference (MD) of -10.58 (95% CI -12.58 to -8.72) on the ADHD Rating Scale (ADHD-RS; range 0 to 72 points). The minimal clinically relevant difference is considered to be a change of 6.6 points on the ADHD-RS. Methylphenidate may not affect serious adverse events (risk ratio (RR) 0.80, 95% CI 0.39 to 1.67; I² = 0%; 26 trials, 3673 participants; very low-certainty evidence). The TSA-adjusted intervention effect was RR 0.91 (CI 0.31 to 2.68).

SECONDARY OUTCOMES

methylphenidate may cause more adverse events considered non-serious versus placebo or no intervention (RR 1.23, 95% CI 1.11 to 1.37; I² = 72%; 35 trials 5342 participants; very low-certainty evidence). The TSA-adjusted intervention effect was RR 1.22 (CI 1.08 to 1.43). Methylphenidate may improve teacher-rated general behaviour versus placebo (SMD -0.62, 95% CI -0.91 to -0.33; I² = 68%; 7 trials 792 participants; very low-certainty evidence), but may not affect quality of life (SMD 0.40, 95% CI -0.03 to 0.83; I² = 81%; 4 trials, 608 participants; very low-certainty evidence).

AUTHORS' CONCLUSIONS

The majority of our conclusions from the 2015 version of this review still apply. Our updated meta-analyses suggest that methylphenidate versus placebo or no-intervention may improve teacher-rated ADHD symptoms and general behaviour in children and adolescents with ADHD. There may be no effects on serious adverse events and quality of life. Methylphenidate may be associated with an increased risk of adverse events considered non-serious, such as sleep problems and decreased appetite. However, the certainty of the evidence for all outcomes is very low and therefore the true magnitude of effects remain unclear. Due to the frequency of non-serious adverse events associated with methylphenidate, the blinding of participants and outcome assessors is particularly challenging. To accommodate this challenge, an active placebo should be sought and utilised. It may be difficult to find such a drug, but identifying a substance that could mimic the easily recognised adverse effects of methylphenidate would avert the unblinding that detrimentally affects current randomised trials. Future systematic reviews should investigate the subgroups of patients with ADHD that may benefit most and least from methylphenidate. This could be done with individual participant data to investigate predictors and modifiers like age, comorbidity, and ADHD subtypes.

Attention-deficit/hyperactivity disorder and white matter microstructure: the importance of dimensional analyses and sex differences

Background

Attention-deficit/hyperactive disorder (ADHD) has substantial heterogeneity in clinical presentation. A potentially important clue may be variation in brain microstructure. Using fractional anisotropy (FA), previous studies have produced equivocal results in relation to ADHD. This may be due to insufficient consideration of possible sex differences and ADHD's multi-componential nature.

Methods

Using whole-brain analyses, we investigated the association between FA and both ADHD diagnosis and ADHD symptom domains in a well-characterized, ADHD (n = 234; 32% female youth) and non-ADHD (n = 177; 52% female youth), case-control cohort (ages 7-12). Sex-specific effects were tested.

Results

No ADHD group differences were found using categorical assessment of ADHD without consideration of moderators. However, dimensional analyses found total symptoms were associated with higher FA in the superior corona radiata. Further, inattention symptoms were associated with higher FA in the corpus callosum and ansa lenticularis, and lower FA in the superior longitudinal fasciculus, after control for overlap with hyperactivity-impulsivity. Hyperactivity-impulsivity symptoms were associated with higher FA in the superior longitudinal fasciculus, and lower FA in the superior cerebellar peduncles, after control for overlap with inattention. Meanwhile, both categorical and dimensional analyses revealed ADHD-by-sex interactions (voxel-wise p < 0.01). Girls with ADHD had higher FA, but boys with ADHD had lower FA (or no effect), compared to their same-sex peers, in the bilateral anterior corona radiata. Further, higher ADHD symptom severity was associated with higher FA in girls, but lower FA in boys, in the anterior and posterior corona radiata and cerebral peduncles.

Conclusions

ADHD symptom domains appear to be differentially related to white matter microstructure, highlighting the multi-componential nature of the disorder. Further, sex differences will be crucial to consider in future studies characterizing ADHD-related differences in white matter microstructure.