Dataset Information

Multiscale heterogeneity of white matter morphometry in psychiatric disorders.

ABSTRACT:

Background

Inter-individual variability in neurobiological and clinical characteristics in mental illness is often overlooked by classical group-mean case-control studies. Studies using normative modelling to infer person-specific deviations of grey matter volume have indicated that group means are not representative of most individuals. The extent to which this variability is present in white matter morphometry, which is integral to brain function, remains unclear.

Methods

We applied Warped Bayesian Linear Regression normative models to T1-weighted magnetic resonance imaging data and mapped inter-individual variability in person-specific white matter volume deviations in 1,294 cases (58% male) diagnosed with one of six disorders (attention-deficit/hyperactivity, autism, bipolar, major depressive, obsessive-compulsive and schizophrenia) and 1,465 matched controls (54% male) recruited across 25 scan sites. We developed a framework to characterize deviation heterogeneity at multiple spatial scales, from individual voxels, through inter-regional connections, specific brain regions, and spatially extended brain networks.

Results

The specific locations of white matter volume deviations were highly heterogeneous across participants, affecting the same voxel in fewer than 8% of individuals with the same diagnosis. For autism and schizophrenia, negative deviations (i.e., areas where volume is lower than normative expectations) aggregated into common tracts, regions and large-scale networks in up to 35% of individuals.

Conclusions

The prevalence of white matter volume deviations was lower than previously observed in grey matter, and the specific location of these deviations was highly heterogeneous when considering voxel-wise spatial resolution. Evidence of aggregation within common pathways and networks was apparent in schizophrenia and autism but not other disorders.

SUBMITTER: Segal A

PROVIDER: S-EPMC11326206 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

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Publications

Multiscale heterogeneity of white matter morphometry in psychiatric disorders.

Segal Ashlea A Smith Robert E RE Chopra Sidhant S Oldham Stuart S Parkes Linden L Aquino Kevin K Kia Seyed Mostafa SM Wolfers Thomas T Franke Barbara B Hoogman Martine M Beckmann Christian F CF Westlye Lars T LT Andreassen Ole A OA Zalesky Andrew A Harrison Ben J BJ Davey Christopher G CG Soriano-Mas Carles C Cardoner Narcís N Tiego Jeggan J Yücel Murat M Braganza Leah L Suo Chao C Berk Michael M Cotton Sue S Bellgrove Mark A MA Marquand Andre F AF Fornito Alex A

bioRxiv : the preprint server for biology 20240806

<h4>Background</h4>Inter-individual variability in neurobiological and clinical characteristics in mental illness is often overlooked by classical group-mean case-control studies. Studies using normative modelling to infer person-specific deviations of grey matter volume have indicated that group means are not representative of most individuals. The extent to which this variability is present in white matter morphometry, which is integral to brain function, remains unclear.<h4>Methods</h4>We app ...[more]

PMID: 39149253

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Project description:ObjectiveIn both children and adults, psychiatric illness is associated with structural brain alterations, particularly in the prefrontal cortex (PFC). However, most studies compare gray matter volume (GMV) in healthy volunteers (HVs) to one psychiatric group. We compared GMV among youth with anxiety disorders, bipolar disorder (BD), disruptive mood dysregulation disorder (DMDD), attention-deficit/hyperactivity disorder (ADHD), and HVs.Method3-Tesla T1-weighted magnetic resonance imaging scans were acquired in 184 youths (39 anxious, 20 BD, 52 DMDD, 20 ADHD, and 53 HV). Voxel-based morphometry analyses were conducted. One-way analysis of variance tested GMV differences with whole-brain familywise error (p < .05) correction; secondary, exploratory whole-brain analyses used a threshold of p < .001, ≥200 voxels. Given recent frameworks advocating dimensional approaches in psychopathology research, we also tested GMV associations with continuous anxiety, irritability, and inattention symptoms.ResultsSpecificity emerged in the left dorsolateral PFC (dlPFC), which differed among youth with BD, anxiety, and HVs; GMV was increased in youth with anxiety, but decreased in BD, relative to HVs. Secondary analyses revealed BD-specific GMV decreases in the right lateral PFC, right dlPFC, and dorsomedial PFC, and also anxiety-specific GMV increases in the left dlPFC, right ventrolateral PFC, frontal pole, and right parahippocampal gyrus/lingual gyrus. Both BD and DMDD showed decreased GMV relative to HVs in the right dlPFC/superior frontal gyrus. GMV was not associated with dimensional measures of anxiety, irritability, or ADHD symptoms.ConclusionBoth disorder-specific and shared GMV differences manifest in pediatric psychopathology. Some differences were specific to anxiety disorders, others specific to BD, and others shared between BD and DMDD. Further developmental research might map commonalities and differences of structure and function in diverse pediatric psychopathologies.

Project description:Verbal memory is the most commonly impaired cognitive domain in patients with temporal lobe epilepsy (TLE). Although damage to the hippocampus and adjacent temporal lobe structures is known to contribute to memory impairment, little is known of the relative contributions of white versus gray matter structures, or whether microstructural versus morphometric measures of temporal lobe pathology are stronger predictors of impairment. We evaluate whether measures of temporal lobe pathology derived from diffusion tensor imaging (DTI; microstructural) versus structural MRI (sMRI; morphometric) contribute the most to memory performances in TLE, after controlling for hippocampal volume (HCV). DTI and sMRI were performed on 26 patients with TLE and 35 controls. Verbal memory was measured with the Logical Memory (LM) subtest of the Wechsler Memory Scale-III. Hierarchical regression analyses were performed to examine unique contributions of DTI and sMRI measures to verbal memory with HCV entered in block 1. In patients, impaired recall was associated with increased mean diffusivity (MD) of multiple fiber tracts that project through the temporal lobes. In addition, increased MD of the left cortical and bilateral pericortical white matter was associated with impaired recall. After controlling for left HCV, only microstructural measures of white matter pathology contributed to verbal recall. The best predictive model included left HCV and MD of the left inferior longitudinal fasciculus (ILF) and pericortical white matter beneath the left entorhinal cortex. This model explained 60% of the variance in delayed recall and revealed that MD of the left ILF was the strongest predictor. These data reveal that white matter microstructure within the temporal lobe can be used in conjunction with left HCV to enhance the prediction of verbal memory impairment, and speak to the complementary nature of DTI and sMRI for understanding cognitive dysfunction in epilepsy and possibly other memory disorders.

Project description:BackgroundWhile gross measures of brain structure have shown alterations with increasing body mass index (BMI), the extent and nature of such changes has varied substantially across studies. Here, we sought to determine whether small-scale morphometric measures might prove more sensitive and reliable than larger scale measures and whether they might offer a valuable opportunity to link cortical changes to underlying white matter changes. To examine this, we explored the association of BMI with millimetre-scale Gaussian curvature, in addition to standard measures of morphometry such as cortical thickness, surface area and mean curvature. We also assessed the volume and integrity of the white matter, using white matter signal intensity and fractional anisotropy (FA). We hypothesised that BMI would be linked to small-scale changes in Gaussian curvature and that this phenomenon would be mediated by changes in the integrity of the underlying white matter.MethodsThe association of global measures of T1-weighted cortical morphometry with BMI was examined using linear regression and mediation analyses in two independent groups of healthy young to middle aged human subjects (n1 = 52, n2 = 202). In a third dataset of (n3 = 897), which included diffusion tensor images, we sought to replicate the significant associations established in the first two datasets, and examine the potential mechanistic link between BMI-associated cortical changes and global FA.ResultsGaussian curvature of the white matter surface showed a significant, positive association with BMI across all three independent datasets. This effect was mediated by a negative association between the integrity of the white matter and BMI.ConclusionsIncreasing BMI is associated with changes in white matter microstructure in young to middle-aged healthy adults. Our results are consistent with a model whereby BMI-linked cortical changes are mediated by the effects of BMI on white matter microstructure.

Dataset Information

Multiscale heterogeneity of white matter morphometry in psychiatric disorders.

Background

Methods

Results

Conclusions

Publications

Multiscale heterogeneity of white matter morphometry in psychiatric disorders.

Similar Datasets

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