Structural Connectivity in Down Syndrome and Alzheimer’s Disease

Down syndrome (DS) arises from the triplication of chromosome 21, which leads to an atypical neurodevelopment and the overproduction of the amyloid precursor protein, predisposing to early Alzheimer’s disease (AD). Not surprisingly, trisomy 21 is widely considered a model to study predementia stages of AD. After decades, in which neural loss was the main focus, research in AD is now moving toward understanding the neurodegenerative aspects affecting white matter. Motivated by the development of magnetic resonance imaging (MRI)-based diffusion techniques, this shift in focus has led to several exploratory studies on both young and older individuals with DS. In this review, we synthesise the initial efforts made by researchers in characterising in-vivo structural connectivity in DS, together with the AD footprint on top of such pre-existing connectivity related to atypical brain development. The white matter structures found to be affected in DS are the corpus callosum and all the main long-association fibres, namely the inferior fronto-occipital fasciculus, the inferior and superior longitudinal fasciculus, the uncinate fasciculus and the cingulum bundle. Furthermore, the cingulum bundle and the corpus callosum appear to be particularly sensitive to early AD changes in this population. Findings are discussed in terms of their functional significance, alongside methodological considerations and implications for future research

Autism is associated with interindividual variations of gray and white matter morphology

Background: Although many studies have explored atypicalities in gray matter (GM) and white matter (WM) morphology of autism, most of them relied on unimodal analyses that did not benefit from the likelihood that different imaging modalities may reflect common neurobiology. We aimed to establish brain patterns of modalities that differentiate between individuals with and without autism and explore associations between these brain patterns and clinical measures in the autism group. Methods: We studied 183 individuals with autism and 157 nonautistic individuals (age range, 6-30 years) in a large, deeply phenotyped autism dataset (EU-AIMS LEAP [European Autism Interventions-A Multicentre Study for Developing New Medications Longitudinal European Autism Project]). Linked independent component analysis was used to link all participants' GM volume and WM diffusion tensor images, and group comparisons of modality shared variances were examined. Subsequently, we performed univariate and multivariate brain-behavior correlation analyses to separately explore the relationships between brain patterns and clinical profiles. Results: One multimodal pattern was significantly related to autism. This pattern was primarily associated with GM volume in bilateral insula and frontal, precentral and postcentral, cingulate, and caudate areas and co-occurred with altered WM features in the superior longitudinal fasciculus. The brain-behavior correlation analyses showed a significant multivariate association primarily between brain patterns that involved variation of WM and symptoms of restricted and repetitive behavior in the autism group. Conclusions: Our findings demonstrate the assets of integrated analyses of GM and WM alterations to study the brain mechanisms that underpin autism and show that the complex clinical autism phenotype can be interpreted by brain covariation patterns that are spread across the brain involving both cortical and subcortical areas

Diffusion tensor imaging of Parkinson's disease, multiple system atrophy and progressive supranuclear palsy: a tract-based spatial statistics study

Although often clinically indistinguishable in the early stages, Parkinson's disease (PD), Multiple System Atrophy (MSA) and Progressive Supranuclear Palsy (PSP) have distinct neuropathological changes. The aim of the current study was to identify white matter tract neurodegeneration characteristic of each of the three syndromes. Tract-based spatial statistics (TBSS) was used to perform a whole-brain automated analysis of diffusion tensor imaging (DTI) data to compare differences in fractional anisotropy (FA) and mean diffusivity (MD) between the three clinical groups and healthy control subjects. Further analyses were conducted to assess the relationship between these putative indices of white matter microstructure and clinical measures of disease severity and symptoms. In PSP, relative to controls, changes in DTI indices consistent with white matter tract degeneration were identified in the corpus callosum, corona radiata, corticospinal tract, superior longitudinal fasciculus, anterior thalamic radiation, superior cerebellar peduncle, medial lemniscus, retrolenticular and anterior limb of the internal capsule, cerebral peduncle and external capsule bilaterally, as well as the left posterior limb of the internal capsule and the right posterior thalamic radiation. MSA patients also displayed differences in the body of the corpus callosum corticospinal tract, cerebellar peduncle, medial lemniscus, anterior and superior corona radiata, posterior limb of the internal capsule external capsule and cerebral peduncle bilaterally, as well as the left anterior limb of the internal capsule and the left anterior thalamic radiation. No significant white matter abnormalities were observed in the PD group. Across groups, MD correlated positively with disease severity in all major white matter tracts. These results show widespread changes in white matter tracts in both PSP and MSA patients, even at a mid-point in the disease process, which are not found in patients with PD

Linking functional and structural brain organisation with behaviour in autism: a multimodal EU-AIMS Longitudinal European Autism Project (LEAP) study

Neuroimaging analyses of brain structure and function in autism have typically been conducted in isolation, missing the sensitivity gains of linking data across modalities. Here we focus on the integration of structural and functional organisational properties of brain regions. We aim to identify novel brain-organisation phenotypes of autism. We utilised multimodal MRI (T1-, diffusion-weighted and resting state functional), behavioural and clinical data from the EU AIMS Longitudinal European Autism Project (LEAP) from autistic (n = 206) and non-autistic (n = 196) participants. Of these, 97 had data from 2 timepoints resulting in a total scan number of 466. Grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps were extracted from respective MRI modalities and were then integrated with Linked Independent Component Analysis. Linear mixed-effects models were used to evaluate the relationship between components and group while accounting for covariates and non-independence of participants with longitudinal data. Additional models were run to investigate associations with dimensional measures of behaviour. We identified one component that differed significantly between groups (coefficient = 0.33, p$_{adj}$ = 0.02). This was driven (99%) by variance of the right fusiform gyrus connectopic map 2. While there were multiple nominal (uncorrected p < 0.05) associations with behavioural measures, none were significant following multiple comparison correction. Our analysis considered the relative contributions of both structural and functional brain phenotypes simultaneously, finding that functional phenotypes drive associations with autism. These findings expanded on previous unimodal studies by revealing the topographic organisation of functional connectivity patterns specific to autism and warrant further investigation

Imbalanced social-communicative and restricted repetitive behavior subtypes of autism spectrum disorder exhibit different neural circuitry

Abstract: Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97–99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry

Frontoparietal Tracts Linked to Lateralized Hand Preference and Manual Specialization

Humans show a preference for using the right hand over the left for tasks and activities of everyday life. While experimental work in non-human primates has identified the neural systems responsible for reaching and grasping, the neural basis of lateralized motor behavior in humans remains elusive. The advent of diffusion imaging tractography for studying connectional anatomy in the living human brain provides the possibility of understanding the relationship between hemispheric asymmetry, hand preference, and manual specialization. In this study, diffusion tractography was used to demonstrate an interaction between hand preference and the asymmetry of frontoparietal tracts, specifically the dorsal branch of the superior longitudinal fasciculus, responsible for visuospatial integration and motor planning. This is in contrast to the corticospinal tract and the superior cerebellar peduncle, for which asymmetry was not related to hand preference. Asymmetry of the dorsal frontoparietal tract was also highly correlated with the degree of lateralization in tasks requiring visuospatial integration and fine motor control. These results suggest a common anatomical substrate for hand preference and lateralized manual specialization in frontoparietal tracts important for visuomotor processing