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ADHD severity is associated with white matter microstructure in the subgenual cingulum.

Cooper M, Thapar A, Jones DK - Neuroimage Clin (2015)

Bottom Line: Deterministic tractography based on spherical deconvolution methods was used to map the subgenual cingulum and corticospinal tract.No case-control differences were found.They provide further evidence that tract-specific approaches may a) reveal associations between microstructural metrics and indices of phenotypic variability which would not be detected using voxelwise approaches, and b) provide improved rather than differential sensitivity compared to voxelwise approaches.

View Article: PubMed Central - PubMed

Affiliation: Child & Adolescent Psychiatry Section, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK ; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK ; Cardiff University Brain Research Imaging Centre, Cardiff University School of Psychology, Cardiff, UK.

ABSTRACT

Aims: This analysis examined hypothesised associations between microstructural attributes in specific white matter (WM) tracts selected a priori and measures of clinical variability in adolescents with a diagnosis of attention deficit hyperactivity disorder (ADHD). Firstly, associations were explored between WM microstructure and ADHD severity in the subgenual cingulum. Secondly, to ensure that tract-specific approaches afforded enhanced rather than differential sensitivity, associations were measured between WM microstructure and autistic traits in the right corticospinal tract based on results of a previously-published voxelwise analysis.

Methods: 40 right-handed males aged 14-18 years (19 with DSM-IV combined type ADHD and 21 healthy controls) underwent a 60 direction diffusion MRI scan. Clinical ADHD and autism variation were assessed by validated questionnaires. Deterministic tractography based on spherical deconvolution methods was used to map the subgenual cingulum and corticospinal tract.

Results: Fractional anisotropy was positively correlated and radial diffusivity was negatively correlated with a) ADHD severity in the left subgenual cingulum and b) autistic traits in the inferior segment of the right corticospinal tract. No case-control differences were found.

Conclusions: Results shed light on possible anatomical correlates of ADHD severity and autistic symptoms in pathways which may be involved in the ADHD phenotype. They provide further evidence that tract-specific approaches may a) reveal associations between microstructural metrics and indices of phenotypic variability which would not be detected using voxelwise approaches, and b) provide improved rather than differential sensitivity compared to voxelwise approaches.

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Related in: MedlinePlus

Scatter plot of correlations between diffusion parameters and autistic symptom scores in the right inferior corticospinal tract. SCQ, social communication questionnaire. Units for radial diffusivity = 10−3 mm2 s−1. Linear trendlines are shown. For fractional anisotropy, R = 0.506 (p = 0.038). For radial diffusivity, R = −0.542 (p = 0.025).
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f0015: Scatter plot of correlations between diffusion parameters and autistic symptom scores in the right inferior corticospinal tract. SCQ, social communication questionnaire. Units for radial diffusivity = 10−3 mm2 s−1. Linear trendlines are shown. For fractional anisotropy, R = 0.506 (p = 0.038). For radial diffusivity, R = −0.542 (p = 0.025).

Mentions: A weak trend towards association was seen between autistic trait score and FA (Pearson's coefficient 0.358, p = 0.158) and autistic trait score and MD (Pearson's coefficient −0.401, p = 0.111) in the right corticospinal tract. When this tract was divided into inferior and superior segments, significant associations were found in the inferior corticospinal tract only, for FA (Pearson's coefficient 0.506, p = 0.038) and RD (Pearson's coefficient −0.542, p = 0.025) (Table 3, Fig. 3). No significant associations were found in the superior segment for either FA (p = 0.658) or MD (p = 0.183).


ADHD severity is associated with white matter microstructure in the subgenual cingulum.

Cooper M, Thapar A, Jones DK - Neuroimage Clin (2015)

Scatter plot of correlations between diffusion parameters and autistic symptom scores in the right inferior corticospinal tract. SCQ, social communication questionnaire. Units for radial diffusivity = 10−3 mm2 s−1. Linear trendlines are shown. For fractional anisotropy, R = 0.506 (p = 0.038). For radial diffusivity, R = −0.542 (p = 0.025).
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4375644&req=5

f0015: Scatter plot of correlations between diffusion parameters and autistic symptom scores in the right inferior corticospinal tract. SCQ, social communication questionnaire. Units for radial diffusivity = 10−3 mm2 s−1. Linear trendlines are shown. For fractional anisotropy, R = 0.506 (p = 0.038). For radial diffusivity, R = −0.542 (p = 0.025).
Mentions: A weak trend towards association was seen between autistic trait score and FA (Pearson's coefficient 0.358, p = 0.158) and autistic trait score and MD (Pearson's coefficient −0.401, p = 0.111) in the right corticospinal tract. When this tract was divided into inferior and superior segments, significant associations were found in the inferior corticospinal tract only, for FA (Pearson's coefficient 0.506, p = 0.038) and RD (Pearson's coefficient −0.542, p = 0.025) (Table 3, Fig. 3). No significant associations were found in the superior segment for either FA (p = 0.658) or MD (p = 0.183).

Bottom Line: Deterministic tractography based on spherical deconvolution methods was used to map the subgenual cingulum and corticospinal tract.No case-control differences were found.They provide further evidence that tract-specific approaches may a) reveal associations between microstructural metrics and indices of phenotypic variability which would not be detected using voxelwise approaches, and b) provide improved rather than differential sensitivity compared to voxelwise approaches.

View Article: PubMed Central - PubMed

Affiliation: Child & Adolescent Psychiatry Section, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK ; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK ; Cardiff University Brain Research Imaging Centre, Cardiff University School of Psychology, Cardiff, UK.

ABSTRACT

Aims: This analysis examined hypothesised associations between microstructural attributes in specific white matter (WM) tracts selected a priori and measures of clinical variability in adolescents with a diagnosis of attention deficit hyperactivity disorder (ADHD). Firstly, associations were explored between WM microstructure and ADHD severity in the subgenual cingulum. Secondly, to ensure that tract-specific approaches afforded enhanced rather than differential sensitivity, associations were measured between WM microstructure and autistic traits in the right corticospinal tract based on results of a previously-published voxelwise analysis.

Methods: 40 right-handed males aged 14-18 years (19 with DSM-IV combined type ADHD and 21 healthy controls) underwent a 60 direction diffusion MRI scan. Clinical ADHD and autism variation were assessed by validated questionnaires. Deterministic tractography based on spherical deconvolution methods was used to map the subgenual cingulum and corticospinal tract.

Results: Fractional anisotropy was positively correlated and radial diffusivity was negatively correlated with a) ADHD severity in the left subgenual cingulum and b) autistic traits in the inferior segment of the right corticospinal tract. No case-control differences were found.

Conclusions: Results shed light on possible anatomical correlates of ADHD severity and autistic symptoms in pathways which may be involved in the ADHD phenotype. They provide further evidence that tract-specific approaches may a) reveal associations between microstructural metrics and indices of phenotypic variability which would not be detected using voxelwise approaches, and b) provide improved rather than differential sensitivity compared to voxelwise approaches.

Show MeSH
Related in: MedlinePlus