White Matter Differences Among Adolescents Reporting Psychotic Experiences

O’Hanlon, Erik; Leemans, Alexander; Kelleher, Ian; Clarke, Mary; Roddy, Sarah; Coughlan, Helen; Harley, Michelle; Amico, Francesco; Hoscheit, Matthew; Tiedt, Lauren; Tabish, Javeria; McGettigan, Anna; Frodl, Thomas; Cannon, Mary

doi:10.1001/jamapsychiatry.2015.0137

Cited by 56 publications

(48 citation statements)

References 93 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, our finding of increased mean FA in schizophrenia offspring as compared with control adolescents may be in line with one study in adolescent offspring of schizophrenia patients (age range 9-18 years) reporting on increased volumetric measures of subcortical regions across age (Dougherty et al, 2012). Interestingly, a recent population-based case-control study showed that adolescents who reported subclinical psychotic symptoms also had increased FA in striatal regions (O'Hanlon et al, 2015). Although these individuals, in contrast to offspring, are not selected based on a genetic vulnerability, they are clearly at increased risk for developing schizophrenia as they display subclinical psychotic symptoms (Yung et al, 1998).…”

Section: Discussionsupporting

confidence: 91%

“…This result suggests that genetic vulnerability for schizophrenia (negatively) impacts frontostriatal network function during adolescence. However, to date, no DTI studies have been performed to investigate the impact of this genetic vulnerability on structural frontostriatal tracts in adolescence, although there is one study that reported increased FA values in the striatum in clinical at-risk adolescents who report psychotic experiences (O'Hanlon et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Changes in White Matter Organization in Adolescent Offspring of Schizophrenia Patients

Leeuw

Bohlken

Mandl

et al. 2016

Neuropsychopharmacol

View full text Add to dashboard Cite

Schizophrenia is associated with frontostriatal network impairments underlying clinical and cognitive symptoms. We previously found disruptions in anatomical pathways, including the tract connecting the left nucleus accumbens and left dorsolateral prefrontal cortex (DLPFC). Similar deficits are observed in unaffected siblings of schizophrenia patients, indicating that these deficits are linked to a genetic vulnerability for the disorder. Frontostriatal tract disruptions may arise during adolescence, preceding the clinical manifestation of the disorder. However, to date, no studies have been performed to investigate frontostriatal tract connections in adolescents who are at increased familial risk for schizophrenia. In this study, we investigate the impact of familial risk on frontostriatal tract connections using diffusion tensor imaging in 27 adolescent offspring of schizophrenia patients and 32 matched control adolescents, aged 10-18 years. Mean fractional anisotropy (FA) was calculated for the tracts connecting the striatum (caudate nucleus, putamen, nucleus accumbens) and frontal cortex regions (DLPFC, medial orbital frontal cortex, inferior frontal gyrus). As expected, based on siblings data, we found an impact of familial risk on frontostriatal development: schizophrenia offspring showed increased FA in the tracts connecting nucleus accumbens and DLPFC as compared with control adolescents. Moreover, while FA increased across age in control adolescents, it did not in schizophrenia offspring. We did not find differences in FA in other frontostriatal tracts. These results indicate altered development of white matter in subjects who are at familial risk for schizophrenia and may precede frontostriatal white matter alterations in adult schizophrenia patients and siblings.

show abstract

Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Changes in White Matter Organization in Adolescent Offspring of Schizophrenia Patients

Leeuw

Bohlken

Mandl

et al. 2016

Neuropsychopharmacol

View full text Add to dashboard Cite

show abstract

“…Subclinical manifestations of most mental health disorders exist in the general population, including in children and adolescents (White, 2015), and neuroimaging population studies and studies of children and adolescents with subclinical symptoms are not only important for understanding risk-factors or early manifestations of disorders, but also appear to support a dimensional perspective on several brain phenotypes associated with mental health. For example, individuals showing subclinical symptoms for psychosis spectrum disorders (clinical high-risk) and individuals with diagnosed relatives (genetic high-risk) have brain microstructural changes at least somewhat overlapping with those reported in clinical groups (Arat et al, 2015;O'Hanlon et al, 2015;Peters & Karlsgodt, 2015), and a recent longitudinal study showed how higher levels of anxiety and depression symptoms was associated with regionally reduced rates of FA development in typically developing youth (Albaugh et al, 2016).…”

Section: Individual Differences and Atypical Developmentmentioning

confidence: 98%

Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress

Tamnes

Roalf

Goddings

et al. 2017

Preprint

View full text Add to dashboard Cite

Diffusion magnetic resonance imaging (dMRI) continues to grow in popularity as a useful neuroimaging method to study brain development, and longitudinal studies that track the same individuals over time are emerging. Over the last decade, seminal work using dMRI has provided new insights into the development of brain white matter (WM) microstructure, connections and networks throughout childhood and adolescence. This review provides an introduction to dMRI, both diffusion tensor imaging (DTI) and other dMRI models, as well as common acquisition and analysis approaches. We highlight the difficulties associated with ascribing these imaging measurements and their changes over time to specific underlying cellular and molecular events. We also discuss selected methodological challenges that are of particular relevance for studies of development, including critical choices related to image acquisition, image analysis, quality control assessment, and the within-subject and longitudinal reliability of dMRI measurements. Next, we review the exciting progress in the characterization and understanding of brain development that has resulted from dMRI studies in childhood and adolescence, including brief overviews and discussions of studies focusing on sex and individual differences. Finally, we outline future directions that will be beneficial to the field.

show abstract

“…One key point shared between these methods is that they both require some form of correspondence between the studied structure of interest for each subjects, either by spatial registration to align the delineated ROIs (Froeling et al, 2016;Smith et al, 2006) or along the streamlines by resampling to a common number of points (Colby et al, 2012;Yeatman et al, 2012). Tractography based approaches can analyze the voxels traversed by a specific white matter bundle in a data driven way and reveal subtle local changes inside a bundle, while ROI based analysis discards the 3D spatial information but reveal widespread changes in the bundle (O'Hanlon et al, 2015). For tractography based analysis, metrics are either averaged by using all points forming a common bundle (Wakana et al, 2007) or collapsed as a representative pathway of the bundle (Colby et al, 2012;Cousineau et al, 2017;Yeatman et al, 2012) to study changes in scalar values along its length.…”

Section: Introductionmentioning

confidence: 99%

Reducing variability in along-tract analysis with diffusion profile realignment

et al. 2019

Self Cite

View full text Add to dashboard Cite

Diffusion weighted magnetic resonance imaging (dMRI) provides a non invasive virtual reconstruction of the brain's white matter structures through tractography. Analyzing dMRI measures along the trajectory of white matter bundles can provide a more specific investigation than considering a region of interest or tract-averaged measurements. However, performing group analyses with this along-tract strategy requires correspondence between points of tract pathways across subjects. This is usually achieved by creating a new common space where the representative streamlines from every subject are resampled to the same number of points. If the underlying anatomy of some subjects was altered due to, e.g., disease or developmental changes, such information might be lost by resampling to a fixed number of points. In this work, we propose to address the issue of possible misalignment, which might be present even after resampling, by realigning the representative streamline of each subject in this 1D space with a new method, coined diffusion profile realignment (DPR). Experiments on synthetic datasets show that DPR reduces the coefficient of variation for the mean diffusivity, fractional anisotropy and apparent fiber density when compared to the unaligned case. Using 100 in vivo datasets from the human connectome project, we simulated changes in mean diffusivity, fractional anisotropy and apparent fiber density. Independent Student's t-tests between these altered subjects and the original subjects indicate that regional changes are identified after realignment with the DPR algorithm, while preserving differences previously detected in the unaligned case. This new correction strategy contributes to revealing effects of interest which might be hidden by misalignment and has the potential to improve the specificity in longitudinal population studies beyond the traditional region of interest based analysis and along-tract analysis workflows.

show abstract

White Matter Differences Among Adolescents Reporting Psychotic Experiences

Cited by 56 publications

References 93 publications

Changes in White Matter Organization in Adolescent Offspring of Schizophrenia Patients

Changes in White Matter Organization in Adolescent Offspring of Schizophrenia Patients

Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress

Reducing variability in along-tract analysis with diffusion profile realignment

Contact Info

Product

Resources

About