Abstract Background Recent genome-wide association studies have identified genetic loci that jointly make a considerable contribution to risk of developing Alzheimer’s disease (AD). Because ...neuropathological features of AD can be present several decades before disease onset, we investigated whether effects of polygenic risk are detectable by neuroimaging in young adults. We hypothesised that higher polygenic risk scores (PRS) for AD would be associated with reduced volume of the hippocampus, and other limbic and paralimbic areas. We further hypothesised that AD PRS would affect the microstructure of fibre tracts connecting the hippocampus with other brain areas. Methods We analysed the association between AD PRS and brain imaging parameters using T1-weighted structural (n=272) and diffusion-weighted scans (n=197). Results We found a significant association between AD PRS and left hippocampal volume, with higher risk associated with lower left hippocampal volume (p=0.001). This effect remained when the APOE gene was excluded (p=0.031), suggesting that the relationship between hippocampal volume and AD is the result of multiple genetic factors, not exclusively variability in the APOE gene. The diffusion tensor imaging analysis revealed that fractional anisotropy of the right cingulum was inversely correlated with AD PRS (p=0.009). We thus show that polygenic effects of AD risk variants on brain structure can already be detected in young adults. Conclusions This finding paves the way for further investigation of the effects of AD risk variants and may become useful for efforts to combine genotypic and phenotypic data for risk prediction and to enrich future prevention trials of AD.
Structural MRI abnormalities are inconsistently reported in epilepsy. In the largest neuroimaging study to date, Whelan et al. report robust structural alterations across and within epilepsy ...syndromes, including shared volume loss in the thalamus, and widespread cortical thickness differences. The resulting neuroanatomical map will guide prospective studies of disease progression.
Abstract
Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen's d = −0.24 to −0.73; P < 1.49 × 10−4), and lower thickness in the precentral gyri bilaterally (d = −0.34 to −0.52; P < 4.31 × 10−6). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = −1.73 to −1.91, P < 1.4 × 10−19), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = −0.36 to −0.52; P < 1.49 × 10−4). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = −0.29 to −0.54; P < 1.49 × 10−4). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = −0.27 to −0.51; P < 1.49 × 10−4). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < −0.0018; P < 1.49 × 10−4). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed.
Alterations in functional connectivity between the nucleus accumbens (NAcc) and frontal cortices have been previously associated with the presence of psychiatric syndromes, including bipolar disorder ...(BD). Whether these alterations are a consequence or a risk factor for mental disorders remains unresolved.
This study included 35 patients with BD, 30 nonaffected siblings of patients with BD, and 23 healthy control subjects to probe functional connectivity at rest between NAcc and the rest of the brain in a cross-sectional design. Blood oxygen level–dependent time series at rest from NAcc were used as seed region in a voxelwise correlational analysis. The strength of the correlations found was compared across groups after Fisher’s Z transformation.
We found increased functional connectivity between the NAcc and the ventromedial prefrontal cortex—comprising mainly the subgenual anterior cingulate—in patients compared with healthy control subjects. Participants at increased genetic risk but yet resilient—nonaffected siblings—showed functional connectivity values midway between the former two groups.
Our results are indicative of the potential for the connectivity between NAcc and the ventromedial prefrontal cortex to represent an endophenotype for BD.
Brain region-specific changes have been demonstrated with a variety of cognitive training interventions. The effect of cognitive training on brain subnetworks in humans, however, remains largely ...unknown, with studies limited to functional networks. Here, we used a well-established working memory training program and state-of-the art neuroimaging methods in 40 healthy adults (21 females, mean age 26.5 years). Near and far-transfer training effects were assessed using computerized working memory and executive function tasks. Adaptive working memory training led to improvement on (non)trained working memory tasks and generalization to tasks of reasoning and inhibition. Graph theoretical analysis of the structural (white matter) network connectivity ("connectome") revealed increased global integration within a frontoparietal attention network following adaptive working memory training compared with the nonadaptive group. Furthermore, the impact on the outcome of graph theoretical analyses of different white matter metrics to infer "connection strength" was evaluated. Increased efficiency of the frontoparietal network was best captured when using connection strengths derived from MR metrics that are thought to be more sensitive to differences in myelination (putatively indexed by the quantitative longitudinal relaxation rate, R1) than previously used diffusion MRI metrics (fractional anisotropy or fiber-tracking recovered streamlines). Our findings emphasize the critical role of specific microstructural markers in providing important hints toward the mechanisms underpinning training-induced plasticity that may drive working memory improvement in clinical populations.
This is the first study to explore training-induced changes in the structural connectome using a well-controlled design to examine cognitive training with up-to-date neuroimaging methods. We found changes in global integration based on white matter connectivity within a frontoparietal attention network following adaptive working memory training compared with a nonadaptive comparison group. Furthermore, the impact of different diffusion MR metrics and more specific markers of white matter on the graph theoretical findings was evaluated. An increase in network global efficiency following working memory training was best captured when connection strengths were weighted by MR relaxation rates (influenced by myelination). These results are important for the optimization of cognitive training programs for healthy individuals and people with brain disease.
Adaptive working memory (WM) training may lead to cognitive benefits that are associated with white matter plasticity in parietofrontal networks, but the underlying mechanisms remain poorly ...understood. We investigated white matter microstructural changes after adaptive WM training relative to a nonadaptive comparison group. Microstructural changes were studied in the superior longitudinal fasciculus, the main parietofrontal connection, and the cingulum bundle as a comparison pathway. MRI-based metrics were the myelin water fraction and longitudinal relaxation rate R
from multicomponent relaxometry (captured with the mcDESPOT approach) as proxy metrics of myelin, the restricted volume fraction from the composite hindered and restricted model of diffusion as an estimate of axon morphology, and fractional anisotropy and radial diffusivity from diffusion tensor imaging. PCA was used for dimensionality reduction. Adaptive training was associated with benefits in a “WM capacity” component and increases in a microstructural component (increases in R
, restricted volume fraction, fractional anisotropy, and reduced radial diffusivity) that predominantly loaded on changes in the right dorsolateral superior longitudinal fasciculus and the left parahippocampal cingulum. In contrast, nonadaptive comparison activities were associated with the opposite pattern of reductions in WM capacity and microstructure. No group differences were observed for the myelin water fraction metric suggesting that R
was a more sensitive “myelin” index. These results demonstrate task complexity and location-specific white matter microstructural changes that are consistent with tissue alterations underlying myelination in response to training.
Fractional anisotropy in the uncinate fasciculus and the cingulum may be biomarkers for bipolar disorder and may even be distinctly affected in different subtypes of bipolar disorder, an area in need ...of further research.AimsThis study aims to establish if fractional anisotropy in the uncinate fasciculus and cingulum shows differences between healthy controls, patients with bipolar disorder type I (BD-I) and type II (BD-II), and their unaffected siblings.
Fractional anisotropy measures from the uncinate fasciculus, cingulum body and parahippocampal cingulum were compared with tractography methods in 40 healthy controls, 32 patients with BD-I, 34 patients with BD-II, 17 siblings of patients with BD-I and 14 siblings of patients with BD-II.
The main effects were found in both the right and left uncinate fasciculus, with patients with BD-I showing significantly lower fractional anisotropy than both patients with BD-II and healthy controls. Participants with BD-II did not differ from healthy controls. Siblings showed similar effects in the left uncinate fasciculus. In a subsequent complementary analysis, we investigated the association between fractional anisotropy in the uncinate fasciculus and polygenic risk for bipolar disorder and psychosis in a large cohort (n = 570) of healthy participants. However, we found no significant association.
Fractional anisotropy in the uncinate fasciculus differs significantly between patients with BD-I and patients with BD-II and healthy controls. This supports the hypothesis of differences in the physiological sub-tract between bipolar disorder subtypes. Similar results were found in unaffected siblings, suggesting the potential for this biomarker to represent an endophenotype for BD-I. However, fractional anisotropy in the uncinate fasciculus seems unrelated to polygenic risk for bipolar disorder or psychosis.Declaration of interestNone.
We investigated the structural brain networks of 562 young adults in relation to polygenic risk for Alzheimer's disease, using magnetic resonance imaging (MRI) and genotype data from the Avon ...Longitudinal Study of Parents and Children.
Diffusion MRI data were used to perform whole-brain tractography and generate structural brain networks for the whole-brain connectome, and for the default mode, limbic and visual subnetworks. The mean clustering coefficient, mean betweenness centrality, characteristic path length, global efficiency and mean nodal strength were calculated for these networks, for each participant. The connectivity of the rich-club, feeder and local connections was also calculated. Polygenic risk scores (PRS), estimating each participant's genetic risk, were calculated at genome-wide level and for nine specific disease pathways. Correlations were calculated between the PRS and (a) the graph theoretical metrics of the structural networks and (b) the rich-club, feeder and local connectivity of the whole-brain networks.
In the visual subnetwork, the mean nodal strength was negatively correlated with the genome-wide PRS (
= -0.19,
= 1.4 × 10
), the mean betweenness centrality was positively correlated with the plasma lipoprotein particle assembly PRS (
= 0.16,
= 5.5 × 10
), and the mean clustering coefficient was negatively correlated with the tau-protein binding PRS (
= -0.16,
= 0.016). In the default mode network, the mean nodal strength was negatively correlated with the genome-wide PRS (
= -0.14,
= 0.044). The rich-club and feeder connectivities were negatively correlated with the genome-wide PRS (
= -0.16,
= 0.035;
= -0.15,
= 0.036).
We identified small reductions in brain connectivity in young adults at risk of developing Alzheimer's disease in later life.
The link between brain structural connectivity and schizotypy was explored in two healthy participant cohorts, collected at two different neuroimaging centres, comprising 140 and 115 participants, ...respectively. The participants completed the Schizotypal Personality Questionnaire (SPQ), through which their schizotypy scores were calculated. Diffusion-MRI data were used to perform tractography and to generate the structural brain networks of the participants. The edges of the networks were weighted with the inverse radial diffusivity. Graph theoretical metrics of the default mode, sensorimotor, visual, and auditory subnetworks were derived and their correlation coefficients with the schizotypy scores were calculated. To the best of our knowledge, this is the first time that graph theoretical measures of structural brain networks are investigated in relation to schizotypy. A positive correlation was found between the schizotypy score and the mean node degree and mean clustering coefficient of the sensorimotor and the default mode subnetworks. The nodes driving these correlations were the right postcentral gyrus, the left paracentral lobule, the right superior frontal gyrus, the left parahippocampal gyrus, and the bilateral precuneus, that is, nodes that exhibit compromised functional connectivity in schizophrenia. Implications for schizophrenia and schizotypy are discussed.
We investigated the topological organisation of the structural brain networks, derived via tractography, of healthy participants with varying schizotypy scores, in two independent cohorts comprising 140 and 115 participants, respectively. In order to capture the possible impact of myelination or axonal density on the structural networks, we used the inverse radial diffusivity as the edge weight. We observed that participants with the higher schizotypy scores exhibited higher node degree and clustering coefficient in the sensorimotor and default mode networks. This provides evidence of stronger structural connectivity in participants with higher schizotypy, which could indicate a possible protective mechanism against schizophrenia, or imply that structural alterations observed in schizophrenia are a correlate or consequence of the disease rather than its cause.
Understanding how human brain microstructure influences functional connectivity
is an important endeavor. In this work, magnetic resonance imaging data from 90
healthy participants were used to ...calculate structural connectivity matrices
using the streamline count, fractional anisotropy, radial diffusivity, and a
myelin measure (derived from multicomponent relaxometry) to assign connection
strength. Unweighted binarized structural connectivity matrices were also
constructed. Magnetoencephalography resting-state data from those participants
were used to calculate functional connectivity matrices, via correlations of the
Hilbert envelopes of beamformer time series in the delta, theta, alpha, and beta
frequency bands. Nonnegative matrix factorization was performed to identify the
components of the functional connectivity. Shortest path length and
search-information analyses of the structural connectomes were used to predict
functional connectivity patterns for each participant. The
microstructure-informed algorithms predicted the components of the functional
connectivity more accurately than they predicted the total functional
connectivity. This provides a methodology to understand functional mechanisms
better. The shortest path length algorithm exhibited the highest prediction
accuracy. Of the weights of the structural connectivity matrices, the streamline
count and the myelin measure gave the most accurate predictions, while the
fractional anisotropy performed poorly. Overall, different structural metrics
paint very different pictures of the structural connectome and its relationship
to functional connectivity.
We use microstructural MRI and resting-state MEG data to investigate the
relationship between the brain’s structure and function. We construct
functional brain networks by calculating correlations between the Hilbert
envelope of the beamformer time series in different brain areas. We also
construct structural brain networks using tractography, for five different edge
weightings (number of streamlines, fractional anisotropy, myelination, radial
diffusivity, and a binary weighting). Those structural networks are then used in
function-predicting algorithms, and the predicted functional networks are
compared to the measured ones. We observe that the shortest-path-length
algorithm is better at predicting the observed patterns of functional
connectivity, and that the number of streamlines and myelination are the edge
weightings that lead to the highest correlations between the predicted and the
observed functional connectivity.
Abstract
Genome-wide association studies have identified multiple Alzheimer’s disease risk loci with small effect sizes. Polygenic risk scores, which aggregate these variants, are associated with ...grey matter structural changes. However, genome-wide scores do not allow mechanistic interpretations. The present study explored associations between disease pathway-specific scores and grey matter structure in younger and older adults. Data from two separate population cohorts were used as follows: the Avon Longitudinal Study of Parents and Children, mean age 19.8, and UK Biobank, mean age 64.4 (combined n = 18 689). Alzheimer’s polygenic risk scores were computed using the largest genome-wide association study of clinically assessed Alzheimer’s to date. Relationships between subcortical volumes and cortical thickness, pathway-specific scores and genome-wide scores were examined. Increased pathway-specific scores were associated with reduced cortical thickness in both the younger and older cohorts. For example, the reverse cholesterol transport pathway score showed evidence of association with lower left middle temporal cortex thickness in the younger Avon participants (P = 0.034; beta = −0.013, CI −0.025, −0.001) and in the older UK Biobank participants (P = 0.019; beta = −0.003, CI −0.005, −4.56 × 10−4). Pathway scores were associated with smaller subcortical volumes, such as smaller hippocampal volume, in UK Biobank older adults. There was also evidence of positive association between subcortical volumes in Avon younger adults. For example, the tau protein-binding pathway score was negatively associated with left hippocampal volume in UK Biobank (P = 8.35 × 10−05; beta = −11.392, CI −17.066, −5.718) and positively associated with hippocampal volume in the Avon study (P = 0.040; beta = 51.952, CI 2.445, 101.460). The immune response score had a distinct pattern of association, being only associated with reduced thickness in the right posterior cingulate in older and younger adults (P = 0.011; beta = −0.003, CI −0.005, −0.001 in UK Biobank; P = 0.034; beta = −0.016, CI −0.031, −0.001 in the Avon study). The immune response score was associated with smaller subcortical volumes in the older adults, but not younger adults. The disease pathway scores showed greater evidence of association with imaging phenotypes than the genome-wide score. This suggests that pathway-specific polygenic methods may allow progress towards a mechanistic understanding of structural changes linked to polygenic risk in pre-clinical Alzheimer’s disease. Pathway-specific profiling could further define pathophysiology in individuals, moving towards precision medicine in Alzheimer’s disease.
This study investigated the relationship between Alzheimer’s disease pathway–specific polygenic risk scores and grey matter structure in younger and older adults. Results indicated that pathway-specific scores were associated with reduced cortical thickness and smaller subcortical volumes, particularly in the older cohort, suggesting that pathway-specific polygenic risk scores may provide more mechanistic insights.
Graphical Abstract
Graphical Abstract
PDF
