Recently, carriers of a common variant in the autism risk gene, CNTNAP2, were found to have altered functional brain connectivity using functional MRI. Here, we scanned 328 young adults with high-field (4-Tesla) diffusion imaging, to test the hypothesis that carriers of this gene variant would have altered structural brain connectivity. All participants (209 women, 119 men, age: 23.4±2.17 SD years) were scanned with 105-gradient high-angular-resolution diffusion imaging (HARDI) at 4 Tesla. After performing a whole-brain fiber tractography using the full angular resolution of the diffusion scans, 70 cortical surface-based regions of interest were created from each individual's co-registered anatomical data to compute graph metrics for all pairs of cortical regions. In graph theory analyses, subjects homozygous for the risk allele (CC) had lower characteristic path length, greater small-worldness and global efficiency in whole-brain analyses, and lower eccentricity (maximum path length) in 60 of the 70 nodes in regional analyses. These results were not reducible to differences in more commonly studied traits such as fiber density or fractional anisotropy. This is the first study that links graph theory metrics of brain structural connectivity to a common genetic variant linked with autism and will help us understand the neurobiology of the circuits implicated in the risk for autism.
autism; CNTNAP2; graph theory; HARDI; structural connectivity; twins
Human brain connectivity is disrupted in a wide range of disorders – from Alzheimer’s disease to autism – but little is known about which specific genes affect it. Here we conducted a genome-wide association for connectivity matrices that capture information on the density of fiber connections between 70 brain regions. We scanned a large twin cohort (N=366) with 4-Tesla high angular resolution diffusion imaging (105-gradient HARDI). Using whole brain HARDI tractography, we extracted a relatively sparse 70×70 matrix representing fiber density between all pairs of cortical regions automatically labeled in co-registered anatomical scans. Additive genetic factors accounted for 1–58% of the variance in connectivity between 90 (of 122) tested nodes. We discovered genome-wide significant associations between variants and connectivity. GWAS permutations at various levels of heritability, and split-sample replication, validated our genetic findings. The resulting genes may offer new leads for mechanisms influencing aberrant connectivity and neurodegeneration.
genetics; high angular resolution diffusion imaging (HARDI); cortical surfaces; twin modeling; human connectome
Graph theory can be applied to matrices that represent the brain’s anatomical connections, to better understand global properties of anatomical networks, such as their clustering, efficiency and “small-world” topology. Network analysis is popular in adult studies of connectivity, but only one study – in just 30 subjects – has examined how network measures change as the brain develops over this period. Here we assessed the developmental trajectory of graph theory metrics of structural brain connectivity in a cross-sectional study of 467 subjects, aged 12 to 30. We computed network measures from 70×70 connectivity matrices of fiber density generated using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). We assessed global efficiency and modularity, and both age and age2 effects were identified. HARDI-based connectivity maps are sensitive to the remodeling and refinement of structural brain connections as the human brain develops.
graph theory; high angular resolution diffusion imaging (HARDI); tractography; network analyses; development; structural connectivity
Disruption of structural and functional neural connectivity has been widely reported in Autism Spectrum Disorder (ASD) but there is a striking lack of research attempting to integrate analysis of functional and structural connectivity in the same study population, an approach that may provide key insights into the specific neurobiological underpinnings of altered functional connectivity in autism. The aims of this study were (1) to determine whether functional connectivity abnormalities were associated with structural abnormalities of white matter (WM) in ASD and (2) to examine the relationships between aberrant neural connectivity and behavior in ASD. Twenty-two individuals with ASD and 22 age, IQ-matched controls completed a high-angular-resolution diffusion MRI scan. Structural connectivity was analysed using constrained spherical deconvolution (CSD) based tractography. Regions for tractography were generated from the results of a previous study, in which 10 pairs of brain regions showed abnormal functional connectivity during visuospatial processing in ASD. WM tracts directly connected 5 of the 10 region pairs that showed abnormal functional connectivity; linking a region in the left occipital lobe (left BA19) and five paired regions: left caudate head, left caudate body, left uncus, left thalamus, and left cuneus. Measures of WM microstructural organization were extracted from these tracts. Fractional anisotropy (FA) reductions in the ASD group relative to controls were significant for WM connecting left BA19 to left caudate head and left BA19 to left thalamus. Using a multimodal imaging approach, this study has revealed aberrant WM microstructure in tracts that directly connect brain regions that are abnormally functionally connected in ASD. These results provide novel evidence to suggest that structural brain pathology may contribute (1) to abnormal functional connectivity and (2) to atypical visuospatial processing in ASD.
neuroimaging; autism spectrum disorders; functional connectivity; diffusion tractography; constrained spherical deconvolution; visuospatial processing; structural connectivity; mental rotation
Genetic studies are rapidly identifying variants that shape risk for disorders of human cognition, but the question of how such variants predispose to neuropsychiatric disease remains. Noninvasive human brain imaging allows assessment of the brain in vivo, and the combination of genetics and imaging phenotypes remains one of the only ways to explore functional genotype-phenotype associations in human brain. Common variants in contactin-associated protein-like 2 (CNTNAP2), a neurexin superfamily member, have been associated with several allied neurodevelopmental disorders, including autism and specific language impairment, and CNTNAP2 is highly expressed in frontal lobe circuits in the developing human brain. Using functional neuroimaging, we have demonstrated a relationship between frontal lobar connectivity and common genetic variants in CNTNAP2. These data provide a mechanistic link between specific genetic risk for neurodevelopmental disorders and empirical data implicating dysfunction of long-range connections within the frontal lobe in autism. The convergence between genetic findings and cognitive-behavioral models of autism provides evidence that genetic variation at CNTNAP2 predisposes to diseases such asautism in part through modulation of frontal lobe connectivity.
A key question in diffusion imaging is how many diffusion-weighted images suffice to provide adequate signal-to-noise ratio (SNR) for studies of fiber integrity. Motion, physiological effects, and scan duration all affect the achievable SNR in real brain images, making theoretical studies and simulations only partially useful. We therefore scanned 50 healthy adults with 105-gradient high-angular resolution diffusion imaging (HARDI) at 4 Tesla. From gradient image subsets of varying size (6≤N≤94) that optimized a spherical angular distribution energy, we created SNR plots (versus gradient numbers) for seven common diffusion anisotropy indices: fractional and relative anisotropy (FA, RA), mean diffusivity (MD), volume ratio (VR), geodesic anisotropy (GA), its hyperbolic tangent (tGA), and generalized fractional anisotropy (GFA). SNR, defined in a region of interest in the corpus callosum, was near-maximal with 58, 66 and 62 gradients for MD, FA and RA in respectively, and with about 55 gradients for GA and tGA. For VR and GFA, SNR increased rapidly with more gradients. SNR was optimized when the ratio of diffusion-sensitized to non-sensitized images was 9.13 for GA and tGA, 10.57 for FA, 9.17 for RA, and 26 for MD and VR. In orientation density functions modeling the HARDI signal as a continuous mixture of tensors, the diffusion profile reconstruction accuracy rose rapidly with additional gradients. These plots may help in making trade-off decisions when designing diffusion imaging protocols.
High-Angular Resolution Diffusion imaging; anisotropic scalar; generalized fractional anisotropy; tensor; Signal-to-Noise ratio; Kullback-Leibler divergence
Several common genetic variants have recently been discovered that appear to influence white matter microstructure, as measured by diffusion tensor imaging (DTI). Each genetic variant explains only a small proportion of the variance in brain microstructure, so we set out to explore their combined effect on the white matter integrity of the corpus callosum. We measured six common candidate single-nucleotide polymorphisms (SNPs) in the COMT, NTRK1, BDNF, ErbB4, CLU, and HFE genes, and investigated their individual and aggregate effects on white matter structure in 395 healthy adult twins and siblings (age: 20–30 years). All subjects were scanned with 4-tesla 94-direction high angular resolution diffusion imaging. When combined using mixed-effects linear regression, a joint model based on five of the candidate SNPs (COMT, NTRK1, ErbB4, CLU, and HFE) explained ∼6% of the variance in the average fractional anisotropy (FA) of the corpus callosum. This predictive model had detectable effects on FA at 82% of the corpus callosum voxels, including the genu, body, and splenium. Predicting the brain's fiber microstructure from genotypes may ultimately help in early risk assessment, and eventually, in personalized treatment for neuropsychiatric disorders in which brain integrity and connectivity are affected.
neuroimaging; brain structure; DTI; genetics; genetic profiles; prediction; imaging; clinical or preclinical; neuroanatomy; neurogenetics; pharmacogenetics / pharmacogenomics; neuroimaging; brain structure; DTI; genetics; genetic profiles
The NTRK1 gene (also known as TRKA) encodes a high affinity receptor for NGF, a neurotrophin involved in nervous system development and myelination. NTRK1 has been implicated in neurological function via links between the T allele at rs6336 (NTRK1-T) and schizophrenia risk. A variant in the neurotrophin gene, BDNF, was previously associated with white matter integrity in young adults, highlighting the importance of neurotrophins to white matter development. We hypothesized that NTRK1-T would relate to lower FA in healthy adults.
We scanned 391 healthy adult human twins and their siblings (mean age: 23.6 ± 2.2 years; 31 NTRK1-T carriers, 360 non-carriers) using 105-gradient diffusion tensor imaging at 4 Tesla. We evaluated in brain white matter how NTRK1-T and NTRK1 rs4661063 allele A (rs4661063-A, which is in moderate linkage disequilibrium with rs6336) related to voxelwise fractional anisotropy – a common diffusion tensor imaging measure of white matter microstructure. We used mixed-model regression to control for family relatedness, age, and sex. The sample was split in half to test results reproducibility. The false discovery rate method corrected for voxelwise multiple comparisons.
NTRK1-T and rs4661063-A correlated with lower white matter fractional anisotropy, independent of age and sex (multiple comparisons corrected: false discovery rate critical p = 0.038 for NTRK1-T and 0.013 for rs4661063-A). In each half-sample, the NTRK1-T effect was replicated in the cingulum, corpus callosum, superior and inferior longitudinal fasciculi, inferior fronto-occipital fasciculus, superior corona radiata, and uncinate fasciculus. Our results suggest that NTRK1-T is important for developing white matter microstructure.
Recent genetic studies have implicated a number of candidate genes in the pathogenesis of Autism Spectrum Disorder (ASD). Polymorphisms of CNTNAP2 (contactin-associated like protein-2), a member of the neurexin family, have already been implicated as a susceptibility gene for autism by at least 3 separate studies. We investigated variation in white and grey matter morphology using structural MRI and diffusion tensor imaging. We compared volumetric differences in white and grey matter and fractional anisotropy values in control subjects characterised by genotype at rs7794745, a single nucleotide polymorphism in CNTNAP2. Homozygotes for the risk allele showed significant reductions in grey and white matter volume and fractional anisotropy in several regions that have already been implicated in ASD, including the cerebellum, fusiform gyrus, occipital and frontal cortices. Male homozygotes for the risk alleles showed greater reductions in grey matter in the right frontal pole and in FA in the right rostral fronto-occipital fasciculus compared to their female counterparts who showed greater reductions in FA of the anterior thalamic radiation. Thus a risk allele for autism results in significant cerebral morphological variation, despite the absence of overt symptoms or behavioural abnormalities. The results are consistent with accumulating evidence of CNTNAP2's function in neuronal development. The finding suggests the possibility that the heterogeneous manifestations of ASD can be aetiologically characterised into distinct subtypes through genetic-morphological analysis.
Magnetic resonance imaging (MRI); Voxel-based morphometry (VBM); Diffusion tensor imaging (DTI); CNTNAP2; Autism; Endophenotype
The ascending reticular activating system (ARAS) mediates arousal, an essential component of human consciousness. Lesions of the ARAS cause coma, the most severe disorder of consciousness. Because of current methodological limitations, including of postmortem tissue analysis, the neuroanatomic connectivity of the human ARAS is poorly understood. We applied the advanced imaging technique of high angular resolution diffusion imaging (HARDI) to elucidate the structural connectivity of the ARAS in 3 adult human brains, 2 of which were imaged postmortem. HARDI tractography identified the ARAS connectivity previously described in animals and also revealed novel human pathways connecting the brainstem to the thalamus, hypothalamus, and basal forebrain. Each pathway contained different distributions of fiber tracts from known neurotransmitter-specific ARAS nuclei in the brainstem. The histologically guided tractography findings reported here provide initial evidence for human-specific pathways of the ARAS. The unique composition of neurotransmitter-specific fiber tracts within each ARAS pathway suggests structural specializations that subserve the different functional characteristics of human arousal. This ARAS connectivity analysis provides proof of principle that HARDI tractography may impact the study of human consciousness and its disorders, including in neuropathologic studies of patients dying in coma and the persistent vegetative state.
Arousal; Ascending reticular activating system (ARAS); Brainstem; Consciousness; High angular resolution diffusion imaging (HARDI); Neuroanatomy; Tractography
The claustrum and the insula are closely juxtaposed in the brain of the prosimian primate, the gray mouse lemur (Microcebus murinus). Whether the claustrum has closer affinities with the cortex or the striatum has been debated for many decades. Our observation of histological sections from primate brains and genomic data in the mouse suggest former. Given this, the present study compares the connections of the two structures in Microcebus using high angular resolution diffusion imaging (HARDI, with 72 directions), with a very small voxel size (90 micra), and probabilistic fiber tractography. High angular and spatial resolution diffusion imaging is non-destructive, requires no surgical interventions, and the connection of each and every voxel can be mapped, whereas in conventional tract tracer studies only a few specific injection sites can be assayed. Our data indicate that despite the high genetic and spatial affinities between the two structures, their connectivity patterns are very different. The claustrum connects with many cortical areas and the olfactory bulb; its strongest probabilistic connections are with the entorhinal cortex, suggesting that the claustrum may have a role in spatial memory and navigation. By contrast, the insula connects with many subcortical areas, including the brainstem and thalamic structures involved in taste and visceral feelings. Overall, the connections of the Microcebus claustrum and insula are similar to those of the rodents, cat, macaque, and human, validating our results. The insula in the Microcebus connects with the dorsolateral frontal cortex in contrast to the mouse insula, which has stronger connections with the ventromedial frontal lobe, yet this is consistent with the dorsolateral expansion of the frontal cortex in primates. In addition to revealing the connectivity patterns of the Microcebus brain, our study demonstrates that HARDI, at high resolutions, can be a valuable tool for mapping fiber pathways for multiple sites in fixed brains in rare and difficult-to-obtain species.
Microcebus murinus; gray mouse lemur; claustrum; insula; HARDI; probabilistic fiber tractography
Purpose of review
Imaging genomics is an emerging field that is rapidly identifying genes that influence the brain, cognition, and risk for disease. Worldwide, thousands of individuals are being scanned with high-throughput genotyping (genome-wide scans), and new imaging techniques [high angular resolution diffusion imaging and resting state functional magnetic resonance imaging (MRI)] that provide fine-grained measures of the brain’s structural and functional connectivity. Along with clinical diagnosis and cognitive testing, brain imaging offers highly reproducible measures that can be subjected to genetic analysis.
Recent studies of twin, pedigree, and population-based datasets have discovered several candidate genes that consistently show small to moderate effects on brain measures. Many studies measure single phenotypes from the images, such as hippocampal volume, but voxel-wise genomic methods can plot the profile of genetic association at each 3D point in the brain. This exploits the full arsenal of imaging statistics to discover and replicate gene effects.
Imaging genomics efforts worldwide are now working together to discover and replicate many promising leads. By studying brain phenotypes closer to causative gene action, larger gene effects are detectable with realistic sample sizes obtainable from meta-analysis of smaller studies. Imaging genomics has broad applications to dementia, mental illness, and public health.
diffusion imaging; genome-wide association study; heritability; MRI; twins
Diffusion imaging of post-mortem brains could provide valuable data for validation of diffusion tractography of white matter pathways. Long scans (e.g., overnight) may also enable high-resolution diffusion images for visualization of fine structures. However, alterations to post-mortem tissue (T2 and diffusion coefficient) present significant challenges to diffusion imaging with conventional diffusion-weighted spin echo (DW-SE) acquisitions, particularly for imaging human brains on clinical scanners. Diffusion-weighted steady-state free precession (DW-SSFP) has been proposed as an alternative acquisition technique to ameliorate this tradeoff in large-bore clinical scanners. In this study, both DWSE and DW-SSFP are optimized for use in fixed white matter on a clinical 3-Tesla scanner. Signal calculations predict superior performance from DW-SSFP across a broad range of protocols and conditions. DW-SE and DW-SSFP data in a whole, post-mortem human brain are compared for 6- and 12-hour scan durations. Tractography is performed in major projection, commissural and association tracts (corticospinal tract, corpus callosum, superior longitudinal fasciculus and cingulum bundle). The results demonstrate superior tract-tracing from DW-SSFP data, with 6-hour DW-SSFP data performing as well as or better than 12-hour DW-SE scans. These results suggest that DW-SSFP may be a preferred method for diffusion imaging of post-mortem human brains. The ability to estimate multiple fibers in imaging voxels is also demonstrated, again with greater success in DW-SSFP data.
► Comparison of DW-SE and DW-SSFP for post-mortem imaging on clinical scanners. ► Optimization of protocols predicts 50-130% higher SNR efficiency in DW-SSFP. ► Comparison of tractography 6- and 12-hour DW-SE and DW-SSFP scans. ► Lower uncertainty on fibre direction in DW-SSFP produces superior tractography. ► Crossing fibres can be estimated from 12-hour DW-SSFP data.
Diffusion; Tractography; Post mortem; Steady-state free precession; DTI
Diffusion tensor imaging (DTI) is sensitive to the directionally- constrained flow of water, which diffuses preferentially along axons. Tractography programs may be used to infer matrices of connectivity (anatomical networks) between pairs of brain regions. Little is known about how these computed connectivity measures depend on the scans’ spatial and angular resolutions. To determine this, we scanned 8 young adults with DTI at 2.5 and 3 mm resolutions, and an additional subject at 4 resolutions between 2–4 mm. We computed 70×70 connectivity matrices, using whole-brain tractography to measure fiber density between all pairs of 70 cortical and subcortical regions. Spatial and angular resolution affected the computed connectivity for narrower tracts (internal capsule and cerebellum), but also for the corticospinal tract. Data resolution affected the apparent role of some key structures in cortical anatomic networks. Care is needed when comparing network data across studies, and interpreting apparent disagreements among findings.
Connectivity; diffusion imaging; tractography; networks; MRI; brain
Diffusion imaging is an MRI modality that measures the microscopic molecular motion of water in order to investigate white matter microstructure. The modality has been used extensively in recent years to investigate the neuroanatomical basis of congenital brain malformations. We review the basic principles of diffusion imaging and of specific techniques, including diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI). We show how DTI and HARDI, and their application to fiber tractography, has elucidated the aberrant connectivity underlying a number of congenital brain malformations. Finally, we discuss potential uses for diffusion imaging of developmental disorders in the clinical and research realms.
Diffusion tensor; DTI; White matter; Brain malformations; Children
Diffusion-weighted magnetic resonance imaging holds substantial promise as a technique for non-invasive imaging of white matter (WM) axonal projections. For diffusion imaging to be capable of providing new insight into the connectional neuroanatomy of the human brain, it will be necessary to histologically validate the technique against established tracer methods such as horseradish peroxidase and biocytin histochemistry. The macaque monkey provides an ideal model for histological validation of the diffusion imaging method due to the phylogenetic proximity between humans and macaques, the gyrencephalic structure of the macaque cortex, the large body of knowledge on the neuroanatomic connectivity of the macaque brain and the ability to use comparable magnetic resonance acquisition protocols in both species. Recently, it has been shown that high angular resolution diffusion imaging (HARDI) can resolve multiple axon orientations within an individual imaging voxel in human WM. This capability promises to boost the accuracy of tract reconstructions from diffusion imaging. If the macaque is to serve as a model for histological validation of the diffusion tractography method, it will be necessary to show that HARDI can also resolve intravoxel architecture in macaque WM. The present study therefore sought to test whether the technique can resolve intravoxel structure in macaque WM. Using a HARDI method called q-ball imaging (QBI) it was possible to resolve composite intravoxel architecture in a number of anatomic regions. QBI resolved intravoxel structure in, for example, the dorsolateral convexity, the pontine decussation, the pulvinar and temporal subcortical WM. The paper concludes by reviewing remaining challenges for the diffusion tractography project.
diffusion magnetic resonance imaging; high angular resolution diffusion imaging; macaque; white matter; connectivity; tractography
Structural and sequence variation have been described in several members of the contactin (CNTN) and contactin associated protein (CNTNAP) gene families in association with neurodevelopmental disorders, including autism. Using array comparative genome hybridization (CGH), we identified a maternally inherited ~535 kb deletion at 3p26.3 encompassing the 5′ end of the contactin 4 gene (CNTN4) in a patient with autism. Based on this finding and previous reports implicating genomic rearrangements of CNTN4 in autism spectrum disorders (ASDs) and 3p− microdeletion syndrome, we undertook sequencing of the coding regions of the gene in a local ASD cohort in comparison with a set of controls. Unique missense variants were identified in 4/75 unrelated individuals with an ASD, as well as in 1/107 controls. All of the amino acid substitutions were nonsynonomous, occurred at evolutionarily conserved positions, and were, thus, felt likely to be deleterious. However, these data did not reach statistical significance, nor did the variants segregate with disease within all of the ASD families. Finally, there was no detectable difference in binding of two of the variants to the interacting protein PTPRG in vitro. Thusadditional, larger studies will be necessary to determine whether CNTN4 functions as an autism susceptibility locus in combination with other genetic and/or environmental factors.
contactin 4; autism; autism spectrum disorder; 3p26 deletion; contactins; susceptibility locus
To investigate the topological alterations of the whole-brain white-matter (WM) structural networks in patients with neuromyelitis optica (NMO).
The present study involved 26 NMO patients and 26 age- and sex-matched healthy controls. WM structural connectivity in each participant was imaged with diffusion-weighted MRI and represented in terms of a connectivity matrix using deterministic tractography method. Graph theory-based analyses were then performed for the characterization of brain network properties. A multiple linear regression analysis was performed on each network metric between the NMO and control groups.
The NMO patients exhibited abnormal small-world network properties, as indicated by increased normalized characteristic path length, increased normalized clustering and increased small-worldness. Furthermore, largely similar hub distributions of the WM structural networks were observed between NMO patients and healthy controls. However, regional efficiency in several brain areas of NMO patients was significantly reduced, which were mainly distributed in the default-mode, sensorimotor and visual systems. Furthermore, we have observed increased regional efficiency in a few brain regions such as the orbital parts of the superior and middle frontal and fusiform gyri.
Although the NMO patients in this study had no discernible white matter T2 lesions in the brain, we hypothesize that the disrupted topological organization of WM networks provides additional evidence for subtle, widespread cerebral WM pathology in NMO.
A spectrum of brain-related disorders are nowadays known to manifest themselves in degradation of the integrity and connectivity of neural tracts in the white matter of the brain. Such damage tends to affect the pattern of water diffusion in the white matter – the information which can be quantified by means of diffusion MRI (dMRI). Unfortunately, practical implementation of dMRI still poses a number of challenges which hamper its wide-spread integration into regular clinical practice. Chief among these is the problem of long scanning times. In particular, in the case of High Angular Resolution Diffusion Imaging (HARDI), the scanning times are known to increase linearly with the number of diffusion-encoding gradients. In this research, we use the theory of compressive sampling (aka compressed sensing) to substantially reduce the number of the diffusion gradients without compromising the informational content of HARDI signals. The experimental part of our study compares the proposed method with a number of alternative approaches, and shows that the former results in more accurate estimation of HARDI data in terms of the mean squared error.
Heterozygous copy-number and missense variants in CNTNAP2 and NRXN1 have repeatedly been associated with a wide spectrum of neuropsychiatric disorders such as developmental language and autism spectrum disorders, epilepsy and schizophrenia. Recently, homozygous or compound heterozygous defects in either gene were reported as causative for severe intellectual disability.
99 patients with severe intellectual disability and resemblance to Pitt-Hopkins syndrome and/or suspected recessive inheritance were screened for mutations in CNTNAP2 and NRXN1. Molecular karyotyping was performed in 45 patients. In 8 further patients with variable intellectual disability and heterozygous deletions in either CNTNAP2 or NRXN1, the remaining allele was sequenced.
By molecular karyotyping and mutational screening of CNTNAP2 and NRXN1 in a group of severely intellectually disabled patients we identified a heterozygous deletion in NRXN1 in one patient and heterozygous splice-site, frameshift and stop mutations in CNTNAP2 in four patients, respectively. Neither in these patients nor in eight further patients with heterozygous deletions within NRXN1 or CNTNAP2 we could identify a defect on the second allele. One deletion in NRXN1 and one deletion in CNTNAP2 occurred de novo, in another family the deletion was also identified in the mother who had learning difficulties, and in all other tested families one parent was shown to be healthy carrier of the respective deletion or mutation.
We report on patients with heterozygous defects in CNTNAP2 or NRXN1 associated with severe intellectual disability, which has only been reported for recessive defects before. These results expand the spectrum of phenotypic severity in patients with heterozygous defects in either gene. The large variability between severely affected patients and mildly affected or asymptomatic carrier parents might suggest the presence of a second hit, not necessarily located in the same gene.
While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.
Imaging of water diffusion using magnetic resonance imaging has become an important noninvasive method for probing the white matter connectivity of the human brain for scientific and clinical studies. Current methods such as diffusion tensor imaging (DTI), high angular resolution diffusion imaging (HARDI) such as q-ball imaging, and diffusion spectrum imaging (DSI), are limited by low spatial resolution, long scan times, and low signal-to-noise ratio (SNR). These methods fundamentally perform reconstruction on a voxel-by-voxel level, effectively discarding the natural coherence of the data at different points in space. This paper attempts to overcome these tradeoffs by using spatial information to constrain the reconstruction from raw diffusion MRI data, and thereby improve angular resolution and noise tolerance. Spatial constraints are specified in terms of a prior probability distribution, which is then incorporated in a Bayesian reconstruction formulation. By taking the log of the resulting posterior distribution, optimal Bayesian reconstruction is reduced to a cost minimization problem. The minimization is solved using a new iterative algorithm based on successive least squares quadratic descent. Simulation studies and in vivo results are presented which indicate significant gains in terms of higher angular resolution of diffusion orientation distribution functions, better separation of crossing fibers, and improved reconstruction SNR over the same HARDI method, spherical harmonic q-ball imaging, without spatial regularization. Preliminary data also indicate that the proposed method might be better at maintaining accurate ODFs for smaller numbers of diffusion-weighted acquisition directions (hence faster scans) compared to conventional methods. Possible impacts of this work include improved evaluation of white matter microstructural integrity in regions of crossing fibers and higher spatial and angular resolution for more accurate tractography.
Antiretroviral therapies have become widely available, and as a result, individuals infected with the human immunodeficiency virus (HIV) are living longer, and becoming integrated into the geriatric population. Around half of the HIV+ population shows some degree of cognitive impairment, but it is unknown how their neural networks and brain connectivity compare to those of noninfected people. Here we combined magnetic resonance imaging-based cortical parcellations with high angular resolution diffusion tensor imaging tractography in 55 HIV-seropositive patients and 30 age-matched controls, to map white matter connections between cortical regions. We set out to determine selective virus-associated disruptions in the brain's structural network. All individuals in this study were aged 60–80, with full access to antiretroviral therapy. Frontal and motor connections were compromised in HIV+ individuals. HIV+ people who carried the apolipoprotein E4 allele (ApoE4) genotype—which puts them at even greater risk for neurodegeneration—showed additional network structure deficits in temporal and parietal connections. The ApoE4 genotype interacted with duration of illness. Carriers showed greater brain network inefficiencies the longer they were infected. Neural network deficiencies in HIV+ populations exceed those typical of normal aging, and are worse in those genetically predisposed to brain degeneration. This work isolates neuropathological alterations in HIV+ elders, even when treated with antiretroviral therapy. Network impairments may contribute to the neuropsychological abnormalities in elderly HIV patients, who will soon account for around half of all HIV+ adults.
ApoE4; diffusion tensor imaging (DTI); fractional anisotropy (FA); geriatrics; high angular resolution diffusion imaging; imaging genetics; structural brain networks
In contrast to the more common Diffusion Tensor Imaging (DTI), High Angular Resolution Diffusion Imaging (HARDI) allows superior delineation of angular microstructures of brain white matter, and makes possible multiple-fiber modeling of each voxel for better characterization of brain connectivity. However, the complex orientation information afforded by HARDI makes registration of HARDI images more complicated than scalar images. In particular, the question of how much orientation information is needed for satisfactory alignment has not been sufficiently addressed. Low order orientation representation is generally more robust than high order representation, although the latter provides more information for correct alignment of fiber pathways. However, high order representation, when naïvely utilized, might not necessarily be conducive to improving registration accuracy since similar structures with significant orientation differences prior to proper alignment might be mistakenly taken as non-matching structures. We present in this paper a HARDI registration algorithm, called SPherical Harmonic Elastic REgistration (SPHERE), which in a principled means hierarchically extracts orientation information from HARDI data for structural alignment. The image volumes are first registered using robust, relatively direction invariant features derived from the Orientation Distribution Function (ODF), and the alignment is then further refined using spherical harmonic (SH) representation with gradually increasing orders. This progression from non-directional, single-directional to multi-directional representation provides a systematic means of extracting directional information given by diffusion-weighted imaging. Coupled with a template-subject-consistent soft-correspondence-matching scheme, this approach allows robust and accurate alignment of HARDI data. Experimental results show marked increase in accuracy over a state-of-the-art DTI registration algorithm.
High Angular Resolution Diffusion Imaging (HARDI); Diffusion-Weighted Imaging (DWI); Deformable Registration; Spherical Harmonics; Brain White Matter; Brain Circuitry
Despite an increasing amount of specific correlation studies between structural and functional connectivity, there is still a need for combined studies, especially in pathological conditions. Impairments of brain white matter (WM) and diffuse axonal injuries are commonly suspected to be responsible for the disconnection hypothesis in traumatic brain injury (TBI) patients. Moreover, our previous research on TBI patients shows a strong relationship between abnormalities in topological organization of brain networks and behavioral deficits. In this study, we combined task-related functional connectivity (using event-related fMRI) with structural connectivity (derived from fiber tractography using diffusion MRI data) estimates in the same participants (17 adults with TBI and 16 controls), allowing for direct comparison between graph metrics of the different imaging modalities. Connectivity matrices were computed covering the switching motor network, which includes the basal ganglia, anterior cingulate cortex/supplementary motor area, and anterior insula/inferior frontal gyrus. The edges constituting this network consisted of the partial correlations between the fMRI time series from each node of the switching motor network. The interregional anatomical connections between the switching-related areas were determined using the fiber tractography results. We found that graph metrics and hubs obtained showed no agreement in both groups. The topological properties of brain functional networks could not be solely accounted for by the properties of the underlying structural networks. However, combining complementary information from both imaging modalities could improve accuracy in prediction of switching performance. Direct comparison between functional task-related and anatomical structural connectivity, presented here for the first time in TBI patients, links two powerful approaches to map the patterns of brain connectivity that may underlie behavioral deficits in brain-injured patients.
functional connectivity; structural connectivity; brain networks; graph theoretical analysis; brain injury