Dataset Information

Regional brain volume predicts response to methylphenidate treatment in individuals with ADHD.

ABSTRACT:

Background

Despite the effectiveness of methylphenidate for treating ADHD, up to 30% of individuals with ADHD show poor responses to methylphenidate. Neuroimaging biomarkers to predict medication responses remain elusive. This study characterized neuroanatomical features that differentiated between clinically good and poor methylphenidate responders with ADHD.

Methods

Using a naturalistic observation design selected from a larger cohort, we included 79 drug-naive individuals (aged 6-42?years) with ADHD without major psychiatric comorbidity, who had acceptable baseline structural MRI data quality. Based on a retrospective chart review, we defined responders by individuals' responses to at least one-month treatment with methylphenidate. A nonparametric mass-univariate voxel-based morphometric analysis was used to compare regional gray matter volume differences between good and poor responders. A multivariate pattern recognition based on the support vector machine was further implemented to identify neuroanatomical indicators to predict an individual's response.

Results

63 and 16 individuals were classified in the good and poor responder group, respectively. Using the small-volume correction procedure based on the hypothesis-driven striatal and default-mode network masks, poor responders had smaller regional volumes of the left putamen as well as larger precuneus volumes compared to good responders at baseline. The machine learning approach identified that volumetric information among these two regions alongside the left frontoparietal regions, occipital lobes, and posterior/inferior cerebellum could predict clinical responses to methylphenidate in individuals with ADHD.

Conclusion

Our results suggest regional striatal and precuneus gray matter volumes play a critical role in mediating treatment responses in individuals with ADHD.

SUBMITTER: Chang JC

PROVIDER: S-EPMC7798216 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Regional brain volume predicts response to methylphenidate treatment in individuals with ADHD.

Chang Jung-Chi JC Lin Hsiang-Yuan HY Lv Jinglei J Tseng Wen-Yih Issac WI Gau Susan Shur-Fen SS

BMC psychiatry 20210111 1

<h4>Background</h4>Despite the effectiveness of methylphenidate for treating ADHD, up to 30% of individuals with ADHD show poor responses to methylphenidate. Neuroimaging biomarkers to predict medication responses remain elusive. This study characterized neuroanatomical features that differentiated between clinically good and poor methylphenidate responders with ADHD.<h4>Methods</h4>Using a naturalistic observation design selected from a larger cohort, we included 79 drug-naive individuals (aged ...[more]

PMID: 33430830

Similar Datasets

Project description:OBJECTIVE:To determine whether treatment of attention-deficit/hyperactivity disorder (ADHD) with osmotic-release oral system (OROS) methylphenidate promotes abstinence from smoking among smokers with ADHD who have greater severity of ADHD symptoms at baseline or greater improvement in ADHD during treatment. METHOD:This is a secondary analysis of data from a randomized, double-blind, 11-week trial conducted between December 2005 and January 2008 at 6 clinical sites; the original trial was sponsored by the National Drug Abuse Clinical Trials Network. Adult cigarette smokers (aged 18-55 years) who met DSM-IV criteria for ADHD were randomly assigned to OROS methylphenidate (72 mg/d) (n = 127) or matching placebo (n = 128). All participants received nicotine patches (21 mg/d) and weekly individual smoking cessation counseling. Logistic regression was used to model prolonged abstinence from smoking (ascertained by self-report and breath carbon monoxide testing) as a function of treatment, baseline ADHD Rating Scale-IV (ADHD-RS) score, change in ADHD-RS score during treatment, and their interactions. RESULTS:Treatment interacted with both ADHD-RS score at baseline (P = .01) and change in ADHD-RS score during treatment (P = .008). Among patients with higher ADHD-RS scores (> 36) at baseline and the most improvement in ADHD during treatment (ADHD-RS change score ? 24), 70.0% of those who took OROS methylphenidate achieved abstinence from smoking compared to 36.8% of those who took placebo (P = .02). In contrast, among patients with the lowest ADHD-RS baseline scores (? 30), 30.3% of those who took OROS methylphenidate achieved abstinence from smoking compared to 60.7% of those who took placebo (P = .02). CONCLUSIONS:OROS methylphenidate, in combination with nicotine patch, may be an effective treatment for nicotine dependence among smokers with more severe ADHD and more robust response of ADHD symptoms to medication. OROS methylphenidate may be counterproductive among smokers with lower severity of ADHD. TRIAL REGISTRATION:ClinicalTrials.gov identifier: NCT00253747.

Project description:ObjectiveSleep problems is the most common side effect of methylphenidate (MPH) treatment in ADHD youth and carry potential to negatively impact long-term self-regulatory functioning. This study aimed to examine whether applying machine learning approaches to pre-treatment demographic, clinical questionnaire, environmental, neuropsychological, genetic, and neuroimaging features can predict sleep side effects following MPH administration.MethodThe present study included 83 ADHD subjects as a training dataset. The participants were enrolled in an 8-week, open-label trial of MPH. The Barkley Stimulant Side Effects Rating Scale was used to determine the presence/absence of sleep problems at the 2nd week of treatment. Prediction of sleep side effects were performed with step-wise addition of variables measured at baseline: demographics (age, gender, IQ, height/weight) and clinical variables (ADHD Rating Scale-IV (ADHD-RS) and Disruptive Behavior Disorder rating scale) at stage 1, neuropsychological test (continuous performance test (CPT), Stroop color word test) and genetic/environmental variables (dopamine and norepinephrine receptor gene (DAT1, DRD4, ADRA2A, and SLC6A2) polymorphisms, blood lead, and urine cotinine level) at stage 2, and structural connectivities of frontostriatal circuits at stage 3. Three different machine learning algorithms ((Logistic Ridge Regression (LR), support vector machine (SVM), J48) were used for data analysis. Robustness of classifier model was validated in the independent dataset of 36 ADHD subjects.ResultsClassification accuracy of LR was 95.5% (area under receiver operating characteristic curve (AUC) 0.99), followed by SVM (91.0%, AUC 0.85) and J48 (90.0%, AUC 0.87) at stage 3 for predicting sleep problems. The inattention symptoms of ADHD-RS, CPT response time variability, the DAT1, ADRA2A DraI, and SLC6A2 A-3081T polymorphisms, and the structural connectivities between frontal and striatal brain regions were identified as the most differentiating subset of features. Validation analysis achieved accuracy of 86.1% (AUC 0.92) at stage 3 with J48.ConclusionsOur results provide preliminary support to the combination of multimodal classifier, in particular, neuroimaging features, as an informative method that can assist in predicting MPH side effects in ADHD.

Project description:BACKGROUND:Widespread brain atrophy in alcohol-dependent individuals (ALC) has been consistently documented in pathological and magnetic resonance imaging (MRI) studies. Longitudinal MRI studies have shown that the regional brain volume losses in ALC are partially reversible during abstinence from alcohol. The goal of this study was to determine volume reductions in cortical and subcortical regions functionally important to substance use behavior and their changes during short-term (1 week to 1 month) and long-term abstinence (1 to 7 months) from alcohol. The regions of interest (ROIs) were as follows: anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex (OFC), insula, amygdala, and hippocampus. METHODS:A total of 85 unique ALC were assessed at 1 week (n = 65), 1 month (n = 82), and 7 months (n = 36) of abstinence. In addition, 17 light/nondrinking healthy controls (CON) were assessed at baseline and follow-up over a 10-month interval. Regional brain volumes were derived from FreeSurfer. Cross-sectional statistical analyses using 1-way analysis of variance or Fisher's exact test were applied to identify group differences. Longitudinal statistical analyses using linear mixed models were applied to identify regional volume increases and nonlinear volume recovery trajectories. RESULTS:We demonstrated significant regional volume reductions in ACC, DLPFC, and hippocampus. Older age was associated with smaller DLPFC and OFC, and higher average monthly drinking over 1 year prior to study was associated with smaller OFC. We also demonstrated significant volume increases of all ROIs except amygdala in ALC and significant nonlinear volume recovery trajectories of DLPFC, OFC, and insula. CONCLUSIONS:Results showed significant volume reductions in key regions of the executive control, salience, and emotion networks in ALC at entry into treatment and significant volume increases during short-term and long-term abstinence that were nonlinear over the entire abstinence period for the DLPFC, OFC, and insula. This gray matter plasticity during alcohol abstinence may have important neurobiological and neurocognitive implications in ALC, and it may contribute to an individual's ability to maintain abstinence from alcohol at different phases.

Project description:To investigate longitudinal changes in global and regional brain volume in patients 1 year after mild traumatic brain injury (MTBI) and to correlate such changes with clinical and neurocognitive metrics.This institutional review board-approved study was HIPAA compliant. Twenty-eight patients with MTBI (with 19 followed up at 1 year) with posttraumatic symptoms after injury and 22 matched control subjects (with 12 followed up at 1 year) were enrolled. Automated segmentation of brain regions to compute regional gray matter (GM) and white matter (WM) volumes was performed by using three-dimensional T1-weighted 3.0-T magnetic resonance imaging, and results were correlated with clinical metrics. Pearson and Spearman rank correlation coefficients were computed between longitudinal brain volume and neurocognitive scores, as well as clinical metrics, over the course of the follow-up period.One year after MTBI, there was measurable global brain atrophy, larger than that in control subjects. The anterior cingulate WM bilaterally and the left cingulate gyrus isthmus WM, as well as the right precuneal GM, showed significant decreases in regional volume in patients with MTBI over the 1st year after injury (corrected P < .05); this was confirmed by means of cross-sectional comparison with data in control subjects (corrected P < .05). Left and right rostral anterior cingulum WM volume loss correlated with changes in neurocognitive measures of memory (r = 0.65, P = .005) and attention (r = 0.60, P = .01). At 1-year follow-up, WM volume in the left cingulate gyrus isthmus correlated with clinical scores of anxiety (Spearman rank correlation r = -0.68, P = .007) and postconcussive symptoms (Spearman rank correlation r = -0.65, P = .01).These observations demonstrate structural changes to the brain 1 year after injury after a single concussive episode. Regional brain atrophy is not exclusive to moderate and severe traumatic brain injury but may be seen after mild injury. In particular, the anterior part of the cingulum and the cingulate gyrus isthmus, as well as the precuneal GM, may be distinctively vulnerable 1 year after MTBI.

Dataset Information

Regional brain volume predicts response to methylphenidate treatment in individuals with ADHD.

Background

Methods

Results

Conclusion

Publications

Regional brain volume predicts response to methylphenidate treatment in individuals with ADHD.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets