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. Author manuscript; available in PMC: 2026 Aug 6.
Published in final edited form as: Dev Med Child Neurol. 2025 Aug 6;68(2):240–250. doi: 10.1111/dmcn.16395

Childhood white matter morphology and longitudinal change in symptoms of attention-deficit/hyperactivity disorder

KERI S ROSCH 1,2,3, CHRISTIAN HYDE 4, IAN FUELSCHER 4, DEANA CROCETTI 1, MERVYN SINGH 4, STEWART H MOSTOFSKY 1,3,5
PMCID: PMC12333549  NIHMSID: NIHMS2091735  PMID: 40768121

Abstract

Aim:

To identify features of childhood white matter morphology associated with longitudinal change in the symptoms of attention-deficit/hyperactivity disorder (ADHD) from childhood to adolescence and whether brain white matter microstructure in childhood predicts ADHD symptom progression into adolescence.

Method:

This was a single-site, prospective, longitudinal study of children with ADHD (n = 99, 31 females) and typically developing controls (n = 73, 24 females) assessed in childhood (aged 8–12 years) and adolescence (aged 12–17 years). Parent ratings of ADHD symptom severity were obtained in childhood and adolescence. Diffusion-weighted imaging data were collected in childhood; we derived measures of fiber bundle cross-section (morphology) using fixel-based analysis, a fiber-specific analytical framework. Linear regression was used to examine symptom change and nonparametric permutation testing was conducted for brain–behavior associations. Clinical trajectories and white matter microstructure were also compared between females and males to inform our understanding of the brain basis for sex differences in the clinical presentation of ADHD.

Results:

Females with ADHD showed greater improvement than males in inattention and similar reductions in hyperactivity and impulsivity from childhood to adolescence. Higher fiber cross-section in corticospinal and parieto-occipital pontine tracts in childhood was associated with greater improvement in the severity of ADHD hyperactivity and impulsivity symptoms into adolescence.

Interpretation:

ADHD symptom trajectories from childhood to adolescence differed between males and females and were related to individual variation in structural brain connectivity in childhood.

Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder of childhood, affecting 8% to 10% of school-age children.1 The clinical presentation of ADHD evolves across the lifespan, with variable patterns of symptom persistence and remission, although significant functional impairment is generally present into adolescence and adulthood.2 Importantly, there is mounting evidence that females diagnosed with ADHD in childhood are at increased risk for negative outcomes in adolescence and adulthood than males.3 Despite this, research on ADHD has predominantly focused on males because of initial prevalence data reporting sex ratios (M:F) ranging from 4:1 to 9:1,4,5 although more recent estimates among community samples suggest a lower sex disproportion of 2:1.6,7 Thus, there is limited understanding of the impact of sex on clinical trajectories given the focus on males, including symptom progression and functional outcomes; to our knowledge, no studies have reported the brain basis for sex differences in symptom expression across child to adolescent development.

There is increasing evidence of sex differences in children with ADHD at the brain,8–13 behavioral,14–19 and clinical levels.3,20–24 Published findings suggest a pattern of sex-based distinctions in neurobehavioral features in prepubertal children (aged 8–12 years) with ADHD regarding brain structure, functional connectivity, expressed behavioral patterns of inhibition, and response to reward. Specifically, males with ADHD show abnormalities in premotor basal ganglia circuits with impaired motor inhibition; on the other hand, females with ADHD show abnormalities in prefrontal and limbic circuits with heightened delay discounting (i.e. a stronger preference for smaller, immediate rewards over larger, delayed rewards).8,9,11–13,16 ADHD-related sex differences in brain and behavior in childhood may represent neurobehavioral risk phenotypes for poor outcomes in adolescence. However, we are unaware of any research that has examined childhood neurobehavioral predictors of clinical symptom trajectories in females and males with ADHD as they transition into adolescence.

Anomalous white matter organization, assessed with diffusion magnetic resonance imaging (dMRI), has been implicated in the pathophysiology of ADHD.25 A recent review of dMRI studies in young people with ADHD (aged 3–18 years) showed reduced fractional anisotropy, which is thought to reflect the strength of the white matter connections in the brain, in young people with ADHD. This was observed in several brain regions, with the most consistent findings in the frontostriatal tracts, corpus callosum, and superior longitudinal fasciculus.25 However, findings in the ADHD literature are inconsistent, probably because of potential confounders such as head motion,26 imbalanced sex distribution in the study samples,25 and the predominant use of diffusion tensor imaging to model white matter organization. Regarding the latter, diffusion tensor imaging is unable to reconcile complex (i.e. multiple) fiber orientations in a given voxel. This has led to criticism about the biological plausibility of diffusion tensor imaging-derived tractography, and the specificity of the quantitative metrics (e.g. fractional anisotropy) derived from the tensor model for inferring the microstructural and macrostructural properties of tracts.27

Extant longitudinal and developmental dMRI studies of ADHD have been examined using variable analytical approaches and study designs. Some studies reported reduced fractional anisotropy in several white matter tracts in adulthood, regardless of current ADHD status,28 whereas others reported fractional anisotropy differences in adults with persistent versus remitted ADHD.29 Studies also showed that improvement in symptoms of hyperactivity and impulsivity with age was associated with lower fractional anisotropy and greater fiber density at a later age (in adolescence) in an area where the left corticospinal tract (CST) crosses the left superior longitudinal fasciculus; however, neither fractional anisotropy at the earlier time point nor change in fractional anisotropy were associated with symptom change over time.30–32 Similarly, another study found that an increase in the symptoms of hyperactivity and impulsivity with age was associated with greater age-related decreases in axial diffusivity of several white matter tracts in children aged 4 to 16 years with and without ADHD.33 Finally, a very recent study by Fuelscher et al.34 reported that accelerated microscopic fiber development along corticospinal, frontopontine, striatal-premotor, and thalamo-premotor pathways was associated with greater reductions in ADHD symptom severity in a longitudinal sample of children with and without ADHD, with consistently lower fiber cross-section in the CST and middle cerebellar peduncle in the group with persistent ADHD. However, none of these studies examined dMRI metrics in childhood (e.g. younger than age 12 years) as predictors of clinical course (e.g. symptom change from childhood to adolescence), which may be particularly informative given that ADHD symptoms must be present before age 12 years35 and adolescence is a period of substantial brain and physical development during which many mental health conditions emerge.36

Collectively, these findings suggest that white matter integrity is implicated in the pathophysiology of ADHD and clinical trajectories. However, no studies to date have examined the associations between childhood white matter morphology (before age 13 years) and clinical symptom course. This information would have greater clinical utility as an early indicator of clinical prognosis than studies examining change in white matter integrity. Moreover, none of these studies considered the impact of sex, despite emerging evidence of ADHD-related sex differences in white matter microstructure in distinct frontal regions in childhood8 and in broader white matter pathways in adolescence.37 Consequently, whether childhood white matter microstructure is associated with longitudinal ADHD symptom progression is largely unknown and the impact of sex is thus far undetermined.

Addressing these gaps in knowledge, the goals of this study were to examine (1) longitudinal change in ADHD symptom severity from childhood to adolescence in females and males with ADHD relative to same-sex typically developing controls, (2) whether structural connectivity in childhood is associated with ADHD symptom progression into adolescence, and (3) whether brain regions shown to relate to ADHD symptom progression are differentially affected in females and males with ADHD. We hypothesized that (1) females with ADHD, relative to males with ADHD, would show a greater increase in ADHD symptom severity from childhood to adolescence, (2) higher structural white matter connectivity in childhood would be associated with greater longitudinal improvement in ADHD symptoms, and (3) brain regions associated with ADHD symptom progression would not be differentially affected in females and males with ADHD. Given the inconsistent results in the extant ADHD literature, we chose to delineate a comprehensive set of 72 white matter tracts, adopting a whole-brain-focused rather than a region-of-interest-focused approach. Moreover, we implemented a recently developed dMRI analysis method, fixel-based analysis, to address the limitations of diffusion tensor imaging modeling adopted in earlier cross-sectional and longitudinal studies for probing white matter organization in ADHD;34,38 this technique helps to address the ‘crossing fiber issue’, providing fiber-specific estimates of white matter organization even in the presence of multiple fiber populations.27

METHOD

Participants

This was a single-site, prospective, longitudinal study of 165 children either with a diagnosis of ADHD (n = 99; 31 females) or typically developing controls (n = 66; 21 females), who participated between 2009 and 2022. Participants first assessed between 8 and 12 years (time 1 [T1]) and who returned for an adolescent follow-up visit between 12 and 17 years (time 2 [T2]), with an average of 4 years 10 months (range = 1 years 7 months–9 years 6 months) between visits, were included in the analyses (Figure 1). Participants were recruited from local schools, pediatricians (flyers and electronically via MyChart), community centers (flyers and word of mouth), and local outpatient clinics. All parents completed telephone screening to determine the initial eligibility for the study based on medical and developmental history. Parents and child participants were then scheduled to complete the diagnostic and intellectual assessments. Study protocols were reviewed and approved by the local institutional review board; parents provided written informed consent with children providing assent.

Figure 1:

Figure 1:

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Attention-deficit/hyperactivity disorder (ADHD) sample distribution according to sex and age at each visit. Each line represents an individual participant, with diagnosis according to sex subgroup. The first point on the line reflects age at the initial visit in childhood; the second point on the line reflects age at the adolescent follow-up visit.

Exclusion criteria included a history of intellectual disability, seizures, traumatic brain injury, neurological illnesses, prenatal exposure to teratogens, genetic disorders, or other neurodevelopmental disorders (e.g. autism spectrum disorder); or an IQ below 80 based on the Weschler Intelligence Scales for Children, Fourth39 or Fifth Edition.40 The Weschler Intelligence Scales for Children General Ability Index was also computed as an estimate of intellectual reasoning ability (IQ), which excludes processing speed and working memory subtests, providing an index of general intellectual reasoning ability without the influence of cognitive functions that are often affected in ADHD. Eligible participants completed two laboratory sessions within 4 weeks with few exceptions, with the initial session involving intellectual assessment, a practice ‘mock’ MRI scan, and additional laboratory tasks; participants returned for a second session to complete the actual MRI scan, which included diffusion-weighted imaging. Participants taking stimulant medication were asked to withhold medication the day before the session and on the day of the session. The few children taking psychotropic medications other than stimulant medication (n = 4) did not discontinue their medication for the study visits.

Diagnostic and intellectual assessments

Before the initial laboratory session and at the adolescent follow-up visit, a diagnosis of ADHD was determined using a diagnostic parent interview administered either via phone or video conferencing. Participants were administered either the Diagnostic Interview for Children and Adolescents, Fourth Edition41 or the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS),42 as we transitioned to the K-SADS over the course of the study. Master’s level clinicians conducted all diagnostic interviews under the supervision of licensed doctoral-level clinical psychologists. Parents and teachers (when available) also completed the ADHD Rating Scale43 and the Conners Parent Rating Scale-Revised44 or the Conners Parent Rating Scale, Third Edition,45 depending on the most up-to-date version available at the time for an appropriate reference group, which were used to inform diagnostic decision-making and to provide dimensional measures of ADHD symptom severity. Parents were instructed on both the diagnostic interview and report forms to make ratings based on their children’s symptoms while off their regularly prescribed medication.

Participants were included in the ADHD group if they (1) met criteria for an ADHD diagnosis either on the Diagnostic Interview for Children and Adolescents, Fourth Edition or the K-SADS and (2) received a T score of 60 or higher on the Diagnostic and Statistical Manual of Mental Disorders Inattentive or Hyperactive-Impulsive Scales on the Conners Parent or Teacher (when available) Rating Scales, or a score of 2 or 3 (i.e. symptoms rated as occurring ‘often’ or ‘very often’) on at least six of nine items on the Inattentive or Hyperactivity/Impulsivity Scales of the ADHD Rating Scale Home and School versions (when available). Children with ADHD were allowed to meet the criteria for comorbid psychiatric diagnoses on the Diagnostic Interview for Children and Adolescents, Fourth Edition or K-SADS, including oppositional defiant disorder, anxiety, and depressive disorders.

Participants were included in the control group if they (1) did not meet the criteria for any psychiatric disorders on the Diagnostic Interview for Children and Adolescents, Fourth Edition or K-SADS, (2) scored below clinically significant cutoffs (T score < 60) on the Conners Parent and Teacher Rating Scales, and the ADHD Rating Scale Home and School versions, and (3) did not have an immediate family member with ADHD.

Image acquisition and processing

At T1, participants initially completed a mock MRI session to acclimate themselves to the MRI environment before undergoing magnetic resonance scanning on a Philips 3T MRI scanner (Philips Healthcare, Best, the Netherlands). High-resolution T1-weighted Magnetization Prepared RApid Gradient Echo images were acquired (slice thickness = 1mm; field of view = 26cm; acquisition matrix = 256 × 256 pixels). Diffusion-weighted images were acquired using a single-shot echo-planar sequence with sensitivity encoding, using either an 8-channel or a 32-channel head coil (repetition time = 6.356s; echo time = 75ms; sensitivity encoding acceleration factor = 2.5; 2.2-mm axial slices; acquisition matrix = 96 × 96 pixels [field of view = 212]; anterior-posterior phase-encoding direction). Two diffusion sequences were collected for each participant, with 32 noncollinear diffusion encoding directions (b value = 700s/mm2; one b0 for each run). A double-echo T2 image was collected to quantify magnetic field inhomogeneity using the second echo (repetition time = 4164ms; echo time = 12/80ms; flip angle = 90°; slice thickness = 2.2mm; slice number = 70; field of view = 212; reconstructed matrix = 256 × 256 pixels; duration = 4 minutes). Data were preprocessed with the FSL Diffusion Toolbox (FMRIB team, University of Oxford, Oxford, UK; see Appendix S1 for the detailed image processing methods).

After fixel-based analysis (described in Appendix S1), the fiber cross-section for each participant was calculated, providing a macroscopic measure of fiber bundle morphology (à la volume), expressed as the cross-section perpendicular to the fiber.46 Higher values reflect a greater number of axons, supporting more efficient transmission of neural signals. Fiber-cross section log was generated to ensure normality because fiber cross-section is commonly skewed, as recommended for group statistical analysis of fiber cross-section in the official MRtrix3 reference documentation. This step does not affect the interpretation of the data but is typically adopted so that fiber cross-section data can meet the statistical assumptions of parametric tests. Note that where we refer to fiber cross-section with regard to the results and interpretation of the analyses for this study, we are referring to fiber-cross section log in all cases. The TractSeg convolutional neural network-based approach was used to delineate all 72 tracts in the TractSeg library using the population fiber orientation distribution template to segment the voxels corresponding to each tract.47

Statistical analysis

Demographic and clinical characteristics were compared between females and males with and without ADHD compared to same-sex typically developing peers and to each other using χ2 tests for categorical variables (e.g. comorbid disorders, medication status) and independent samples Student’s t-tests for continuous variables (e.g. age, IQ, Hollingshead socioeconomic status).

Longitudinal change in ADHD symptoms in participants with ADHD (excluding typically developing young people) was examined using linear regression, with a change in the Conners Parent Report T score (T1-T2; positive values equaling an improvement in symptoms) for the Diagnostic and Statistical Manual of Mental Disorder Inattention and Hyperactivity/Impulsivity Scales as the dependent variable in separate regression models. Sex was included as a predictor variable; age at T1 and difference in age between T1 and T2 were included as control variables. Two-tailed tests were conducted to test for differential change in either direction. Only participants with complete data were included in the analyses.

The relationship between white matter organization in our tracts of interest at T1 and change in ADHD symptoms (T1-T2; positive values equaling an improvement in symptoms) was investigated using partial correlations and implemented using the connectivity-based fixel enhancement (CFE) method in MRtrix3. We examined whether the fiber cross-section log fold change for each tract of interest was associated with inattention, and hyperactive and impulsive, symptoms separately (after covarying for sex, age, and total cerebral volume48 in a subsample [n = 43] with good-quality diffusion-weighted image data). Connectivity-based fixel enhancement leverages nonparametric permutation testing (shuffled 5000 times) to provide a family-wise error-corrected p-value for each individual fixel.48,49 In doing so, it can be used to identify regions of significant fixels within a tract. Besides correcting multiple comparisons at the fixel level (family-wise error p < 0.05), we limited the number of analyses across tracts by combining the available tracts from the TractSeg library into 16 tract-based regions of interest (Appendix S1 and Figure S1).

Family-wise error-corrected p-value maps were inspected to ensure that significant fixels did not appear in isolation (these effects were considered spurious). The fiber cross-section was averaged across the significant fixels for each participant, allowing for visualization of the association between mean fiber cross-section and change in ADHD symptoms from childhood to adolescence. We also considered whether to include framewise displacement as an index of head motion, given that it affects ADHD versus control group differences,26 but we decided not to do this because framewise displacement did not differ between children with and without ADHD in our sample (p = 0.974, d = 0.01) and was uncorrelated with the fiber cross-section values reported in our main results.

Finally, we explored the effect of sex in the group with ADHD and typically developing controls, and the effect of diagnosis in females and males, using Welch’s t-tests and effect size estimates (Cohen’s d), on mean fiber cross-section of the fixels shown to predict longitudinal change in ADHD symptoms.

Hypotheses were deemed confirmatory because they had been derived a priori. Statistical thresholds were set at α = 0.05 and adjusted as described earlier. Assumption testing for parametric analyses involved checking the data for violations of normality (using Q–Q plots and histograms), homogeneity of variance, and for the presence of outliers (defined as data points with more than 3 SDs from the mean). Relevant assumptions were met unless otherwise stated. Welch’s t-tests were adopted to account for unequal variances between groups. Connectivity-based fixel enhancement analyses were based on nonparametric permutation testing using the Freedman–Lane method.50

RESULTS

Demographic and clinical characteristics

Descriptive statistics regarding the demographic and clinical characteristics for each diagnosis × sex subgroup (e.g. typically developing males, typically developing females, males with ADHD, females with ADHD) are provided in Table 1. Diagnostic groups did not differ regarding age (at T1 or T2), difference in age between T1 and T2, Hollingshead socioeconomic status, or distribution of sex, whereas IQ was significantly lower in males with ADHD compared to typically developing males. Females with ADHD were significantly younger than males with ADHD at T1 and had a larger difference in age between T1 and T2. For this reason, age was included as a covariate in all subsequent analyses. Regarding ADHD-related sex differences in symptom presentation, inattention T scores were greater in females compared to males with ADHD, whereas there were no significant differences in inattention raw scores (i.e. unadjusted for age and sex) and symptoms of hyperactivity and impulsivity (raw or T scores). The statistical significance of these results did not change when Welch’s t-tests were conducted due to adjustment of unequal variances. Diffusion imaging data were available for a subset of the larger sample (n = 76), including 43 children with ADHD (11 females). This subgroup did not differ from the full sample with ADHD on any of the demographic or clinical variables in Table 1.

Table 1:

Diagnosis × sex group comparisons of demographic and clinical characteristics

Demographic or clinical characteristic Typically developing (n = 66) ADHD (n = 99) Group comparison p
Males (n = 45) Females (n = 21) Males (n = 68) Females (n = 31) ADHD vs typically developing (all) ADHD vs typically developing (males) ADHD vs typically developing (females) ADHD males vs females
Sex,a % 68 32 68 32 0.945 – – –
Age (years:months) T1 (8–12 years) 10:1 (1:2) 9:11 (1:1) 10:1 (1:6) 9:4 (1:0) 0.298 0.868 0.050 0.008
Age (years:months) T2 (12–17 years) 14:8 (1:11) 14:11 (1:11) 14:6 (1:7) 14:11 (1:11) 0.615 0.506 0.946 0.255
T1-T2 age difference 4.6 (2.0) 5.0 (2.3) 4.5 (1.8) 5.7 (2.0) 0.826 0.617 0.303 0.044
SES T1 55.3 (7.8) 55.0 (8.7) 53.1 (9.5) 53.6 (9.3) 0.188 0.232 0.573 0.833
IQb T1 119 (13.8) 115 (11) 112 (13) 113 (14.7) 0.030 0.024 0.591 0.946
ODD T1, n (%) 0 0 22 (32) 14 (45) – – – 0.219
Anxiety disorder T1, n (%) 0 0 5 (7.4) 3 (9.7) – – – 0.694
Depressive disorder T1, n (%) 0 0 1 (1.5) 0 – – – 0.497
Stimulant medication T1, n (%) 0 0 46 (68) 14 (45) – – – 0.034
T1 ADHD inattention raw 2.6 (2.6) 3.2 (2.4) 18.8 (4.6) 20.4 (4.3) < 0.001 < 0.001 < 0.001 0.123
T1 ADHD hyperactivity/impulsivity raw 2.6 (2.5) 2.1 (2.4) 13.8 (6.1) 14.9 (6.6) < 0.001 < 0.001 < 0.001 0.441
T1 ADHD inattention T score 43.0 (4.8) 47.2 (6.4) 71.9 (10.5) 81.1 (9.3) < 0.001 < 0.001 < 0.001 < 0.001
T1 ADHD hyperactivity/impulsivity T score 46.0 (5.3) 46.4 (5.4) 71.7 (12.6) 72.5 (14.5) < 0.001 < 0.001 < 0.001 0.796
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Data are the mean (SD) unless otherwise stated. Significant p-values are indicated in bold.

a

Biological sex assigned at birth as reported by caregivers.

b

Wechsler Intelligence Scale for Children and Adolescents General Ability Index. Abbreviations: ADHD, attention-deficit/hyperactivity disorder; ODD, oppositional defiant disorder; SES, Hollingshead socioeconomic status.

Longitudinal change in ADHD symptoms

Regression results for the change in ADHD symptoms from childhood to adolescence in children with ADHD showed that females with ADHD had greater improvement in inattentive symptoms than males with ADHD (F[1,95] = 11.7, p < 0.001; Figure 2a). In contrast, the symptom severity of hyperactivity and impulsivity did not differentially decrease from childhood to adolescence in females and males (F[1,95] = 0.9, p = 0.333; Figure 2b).

Figure 2:

Figure 2:

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Longitudinal change in attention-deficit/hyperactivity disorder (ADHD) symptom severity. Average Conners Parent T score, adjusted for sex and age, for the Diagnostic and Statistical Manual of Mental Disorders ADHD Inattention (a) and Hyperactivity/Impulsivity (b) Scales in males (blue) and females (orange) with ADHD at the childhood (T1) and adolescent (T2) visits.

Childhood diffusion-weighted imaging predicts change in ADHD symptoms

A higher fiber cross-section in childhood was associated with a greater reduction in symptom severity of hyperactivity and impulsivity from childhood to adolescence. Averaged across the significant fixels from the connectivity-based fixel enhancement analysis (Figure 3b), significant associations were observed for the right CST (r = 0.48, p < 0.001; Figure 3a), the left CST (r = 0.42, p = 0.005), and the right parieto-occipital pontine tract (POPT) (r = 0.50, p < 0.001). Fiber cross-sections within the tracts associated with symptom change (T1-T2) were reduced in females relative to males with ADHD, with a large effect for the right CST (p = 0.005, d = −0.98; Figure 3c) and medium effects for the left CST (p = 0.099, d = −0.57) and right POPT (p = 0.109, d = −0.59). No significant difference was observed between females and males in the typically developing group, although there was a medium effect size for reduced fiber cross-section in typically developing females versus males in the right CST (p = 0.242, d = −0.41; Figure 3c). Regarding diagnosis effects, a medium effect size was observed for reduced fiber cross-section in the right CST in females with ADHD versus typically developing females (p = 0.137, d = −0.63), whereas there was no effect in males with ADHD versus typically developing males (p = 0.743, d = 0.010). There was no evidence of childhood fiber cross-section predicting change in inattention symptom severity for any of the tracts examined. Complete results for all the analyses are presented in Table S1.

Figure 3:

Figure 3:

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Relationship between childhood brain morphology, attention-deficit/hyperactivity disorder (ADHD) symptoms, and sex. (a) Partial correlation (covarying for sex, age, and total cerebral volume) between corticospinal tract (CST) fiber cross-section (log fold change) in childhood and change in symptoms of hyperactivity and impulsivity from childhood (T1) to adolescence (T2) in young people with ADHD (n = 43). (b) Regions of the CST where this effect was observed using the connectivity-based fixel enhancement method in MRtrix3. (c) Comparison of fiber cross-section in the CST between females (n = 11) and males (n = 32) with ADHD using Welch’s t-tests without adjusting for total cerebral volume because this would remove the variance of interest.

DISCUSSION

This study aimed to examine sex differences in developmental changes in ADHD symptom severity from childhood to adolescence in a case–control longitudinal sample, and whether brain white matter microstructure in childhood predicts ADHD symptom progression into adolescence. Our findings demonstrate that females with ADHD showed greater inattention symptom severity during childhood and greater reduction in symptoms of inattention into adolescence than males with ADHD. Moreover, white matter organization in childhood in the left and right CST and right POPT predicted the progression of ADHD symptoms of hyperactivity and impulsivity into adolescence. Finally, preliminary results (given the small sample size) suggested reduced fiber cross-section in the brain regions that predicted longitudinal symptom change (right CST), with a medium effect when comparing females with ADHD versus typically developing females and a large effect when comparing males with ADHD versus females. Collectively, these findings expand the limited extant literature on childhood neurobiological predictors of developmental changes in ADHD symptoms and provide preliminary results of sex differences in these relationships.

Crucially, our examination of ADHD symptom severity was adjusted for age and sex, providing a measure relative to a same-sex normative sample. Thus, our findings provide validated evidence that our cohort of females with ADHD, rather than males with ADHD, were showing more severe problems with inattention during childhood. In fact, there was no significant difference in raw scores for inattention; only when adjusted T scores were used, we could see this sex-related effect in the group with ADHD. The findings in our sample, which was primarily recruited from the community rather than clinics, are consistent with the broader understanding that females, relative to males, may need to display greater symptom severity in childhood to meet the diagnostic criteria for ADHD. They also inform the growing awareness that the ADHD diagnostic criteria are biased toward a ‘male presentation’ of the disorder, with females less likely to meet the full diagnostic criteria, although a subthreshold ADHD may be equally present in males and females.51

It is also important to note that while our findings show that females with ADHD had a greater reduction in symptom severity with age than males with ADHD, contrary to our hypothesis, their scores were higher at baseline, remained in the clinically elevated range in adolescence, and were equivalent to males. One of the first studies of ADHD-related sex differences in clinical trajectories reported that preschoolers diagnosed with ADHD showed persistently elevated ADHD symptoms into early adolescence, regardless of sex, whereas female preschoolers with ADHD (n = 20) showed a greater increase in anxiety and depression in adolescence than male preschoolers with ADHD.52 Thus, it is possible that there is a relative decrease in the symptom severity of inattention; however, there may also be increases in other symptoms of psychopathology that relate to poorer outcomes; for example, inattention in childhood is a precursor for other mental health symptoms and functional impairment in adolescent females with ADHD. An important next step will be to examine how changes in ADHD symptoms across development relate to the emergence of comorbidities or increased functional impairment and whether there are sex differences in these developmental pathways.

Given these potential sex biases in the diagnosis of ADHD, neuroimaging data may be important to understand sex-based differences and to parse the heterogeneity of ADHD, both in terms of clinical presentation and course, and treatment selection and development. Identifying the impact of sex on ADHD presentation and clinical course, and associated differences in brain structure and function, could help elucidate the pathophysiology of ADHD, with important implications for developing more objective diagnostic tools and personalized intervention approaches. Our findings suggest that a higher fiber cross-section in childhood within the CST and the right POPT predicted greater improvement in the symptom severity of ADHD hyperactivity and impulsivity into adolescence. This is consistent with previous findings of a relationship between developmental changes in white matter microstructure and symptoms of hyperactivity and impulsivity (but not inattention-related symptoms),33 particularly within the CST.30–32,34 The unique relationship between CST white matter morphology with hyperactivity and impulsivity rather than inattention may be related to developmental changes in motor control, given that CST fibers emanate largely from the primary motor cortex53 and white matter organization of the CST differentiates typical and atypical motor competence in children.54 The finding that increases in the cross-sectional area of the POPT in childhood were associated with ADHD symptom progression into adolescence is compatible with recent fixel-based analysis work demonstrating the relevance of the POPT to ADHD in childhood.55 While functional correlates of the POPT are poorly understood, our data raise the possibility that information transmission along this fiber bundle may subserve accelerated hyperactivity and impulsivity symptom reduction in ADHD. In contrast, we did not find evidence of childhood white matter predictors of change in symptoms of inattention, which differentially improved with age in females with ADHD, whereas symptoms of hyperactivity and impulsivity improved regardless of sex. This will be an important question for future longitudinal studies with larger samples of females.

Our results expand on prior findings relating developmental changes in white matter morphology to ADHD symptom progression by explicitly examining sex effects using fixel-based analysis and focusing on childhood (younger age range than in30–32) and childhood white matter morphology as a predictor of symptom change through late adolescence (rather than early adolescence as in Fuelscher et al.34), with our sample spanning a critical developmental period. Although this predictive relationship did not differ according to sex, exploratory analyses demonstrated that females with ADHD showed reduced fiber cross-section in childhood within the regions of the CST, showing a positive association with longitudinal improvement in ADHD symptoms. This finding suggests that childhood white matter morphology may be an important indicator of ADHD symptom progression into adolescence with particular relevance for females with ADHD, who show this anomaly to a greater extent in childhood. The CST has been consistently implicated in ADHD, although the direction of effects has varied. Two studies found widespread significantly lower diffusion metrics in the CST in children with ADHD.38,56 Another study reported higher fractional anisotropy in the CST in medication-naive children with ADHD.57 Finally, a study including adolescents with and without ADHD reported higher fractional anisotropy in females than males with ADHD in the CST and the inferior and superior longitudinal fasciculi.37 These inconsistencies support the need for additional research on this topic, with sufficient power to detect meaningful effects in structural brain differences in well-phenotyped samples and consideration of potentially confounding demographic and clinical characteristics.

This study has some limitations, which should be considered to guide future research on this topic. First, the small sample size is a significant limitation, particularly given the replication crisis in psychology. These findings are preliminary, but we hope they will draw attention to the need for longitudinal case–control designs in which females are oversampled to examine sex differences. Second, symptoms were assessed at a two time points for most participants, but the inclusion of multiple time points between the ages of 8 and 18 years would allow for nonlinear modeling to better characterize developmental trajectories of symptom progression. Regarding this point, the focus on difference scores rather than modeling latent change is a limitation because these may be less reliable, although this was done to allow the examination of brain–behavior relationships. Third, at the time of initial study participation, 68% of males with ADHD and 45% of females with ADHD were prescribed a stimulant medication. Parent ratings of ADHD symptoms may have been influenced by medication that effectively reduces ADHD symptom expression for most individuals. In future studies, it will be important to include larger samples and stimulant-naive samples to improve our understanding of the effects of stimulant medication on these relationships. Finally, the sample examined in the study had an above-average IQ, which may also limit the generalizability of the findings to individuals with ADHD. This could also suggest an inherent capacity to compensate for ADHD-related brain morphology (i.e. cognitive reserve), which may affect the relationship between brain structure and ADHD symptom severity.

These findings provide evidence for the impact of sex on the trajectory of ADHD symptoms from childhood to adolescence and suggest that atypical structural brain connectivity in childhood may be an important predictor of ADHD symptom change into adolescence. Further consideration of sex differences in relation to raw scores (i.e. unadjusted for age and sex) for ADHD symptoms and total cerebral volume (reduced in females) in future analyses, including larger samples of female participants, will be important for understanding these trajectories. Our results also suggest the need for additional studies of ADHD-related sex differences in brain structure and function, phenotypic expression, clinical course, and treatment response.

Supplementary Material

Supinfo1
Supinfo3
Supinfo2

Supporting information

The following additional material may be found online:

Table S1: Associations between whiter matter in childhood and ADHD symptom change

Figure S1: White matter pathways reconstructed using TractSeg

Appendix S1: Image processing

What this paper adds.

  • Longitudinal change in the symptoms of attention-deficit/hyperactivity disorder (ADHD) varied according to symptom domain.

  • Young males and females with ADHD showed different patterns of longitudinal change in ADHD symptoms.

  • Childhood white matter morphology was associated with changes in longitudinal symptoms.

ACKNOWLEDGEMENTS

This work was supported by the National Institutes of Health (NIH), with grants awarded to KSR (nos. K23-MH101322 and R03-MH119457) and SHM (nos. R01-MH078160 and R01-MH085328), and grant no. P50HD103538. The MRI equipment in this study was funded by NIH grant no. 1S10OD021648. Additional funding source: Waterloo Foundation, Grant/Award Number: 2013–4545. The sponsors had no role in study design, collection and analysis of the data, or interpretation of the data.

ABBREVIATIONS

CST

corticospinal tract

dMRI

diffusion magnetic resonance imaging

K-SADS

Kiddie Schedule for Affective Disorders and Schizophrenia

POPT

parieto-occipital pontine tract

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