Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence.
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ABSTRACT:
SUBMITTER: Genc E
PROVIDER: S-EPMC5954098 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A positive association between brain size and intelligence is firmly established, but whether region-specific anatomical differences contribute to general intelligence remains an open question. Results from voxel-based morphometry (VBM) - one of the most widely used morphometric methods - have remained inconclusive so far. Here, we applied cross-validated machine learning-based predictive modeling to test whether out-of-sample prediction of individual intelligence scores is possible on the basis of voxel-wise gray matter volume. Features were derived from structural magnetic resonance imaging data (N = 308) using (a) a purely data-driven method (principal component analysis) and (b) a domain knowledge-based approach (atlas parcellation). When using relative gray matter (corrected for total brain size), only the atlas-based approach provided significant prediction, while absolute gray matter (uncorrected) allowed for above-chance prediction with both approaches. Importantly, in all significant predictions, the absolute error was relatively high, i.e., greater than ten IQ points, and in the atlas-based models, the predicted IQ scores varied closely around the sample mean. This renders the practical value even of statistically significant prediction results questionable. Analyses based on the gray matter of functional brain networks yielded significant predictions for the fronto-parietal network and the cerebellum. However, the mean absolute errors were not reduced in contrast to the global models, suggesting that general intelligence may be related more to global than region-specific differences in gray matter volume. More generally, our study highlights the importance of predictive statistical analysis approaches for clarifying the neurobiological bases of intelligence and provides important suggestions for future research using predictive modeling.
| S-EPMC7473979 | biostudies-literature
Project description:OBJECTIVE:To quantify racial differences in brain structural characteristics in white and black octogenarians, and to examine whether these characteristics contribute to cognition. METHODS:Cross-sectional study of 283 adults 79-89 years old (59.4% white;42.0% women) with data on gray matter integrity via diffusion tensor imaging (mean diffusivity), gray matter atrophy (GMA), white matter hyperintensities (WMH), literacy, smoking, drinking, income, hypertension and diabetes. Participants were recruited from an ongoing epidemiological study of older adults living in the community with a range of chronic conditions, physical and cognitive function. Standardized betas (s?) of neuroimaging markers predicting Digit Symbol Substitution Test (DSST) and Modified Mini-Mental State Examination (3MS) scores were computed in multivariable regression models stratified by race. RESULTS:Compared to whites, blacks had lower DSST (p=0.001) and lower 3MS (p=0.006), but also lower mean diffusivity (i.e. higher gray matter microstructural integrity, p=0.032), independent of gender, income, literacy, body mass index, diabetes and drinking habits. Racial differences were not significant for WMH (p=0.062) or GMA (p=0.4). Among blacks, mean diffusivity and WMH were associated with DSST (s?=-.209, p=0.037 and -.211, p=.038, respectively) independent of each other and other covariates; among whites, mean diffusivity, but not WMH, was significantly associated with DSST and 3MS (s? =-.277, p=.002 and -.250, p=0.029, respectively). CONCLUSIONS:In this cohort of octogenarians living in the community, blacks appeared to have higher microstructural integrity of gray matter as compared to whites. This neuroimaging marker was related to higher cognition even in the presence of WMH and other cardiovascular conditions. If confirmed, these findings suggest microstructural gray matter integrity may be a target to improve cognition, especially among blacks who survive to very old age with a range of chronic cardiovascular conditions.
| S-EPMC5127649 | biostudies-literature
Project description:BackgroundDespite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both.MethodsDifferences in MRI-based GM density and volume were examined in 6-25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47-154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67-155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods.ResultsNo density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions.LimitationsThe method for determining "density" is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences.ConclusionsThese results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.
| S-EPMC8633367 | biostudies-literature
Project description:Prior postmortem studies have shown gray matter (GM) microstructural abnormalities in schizophrenia. However, few studies to date have examined GM microstructural integrity in schizophrenia in vivo. Here, we employed diffusion kurtosis imaging (DKI) to test for differences in GM microstructure in eighteen schizophrenia (SZ) patients versus nineteen healthy controls (HC). GM microstructure was characterized in each participant using DKI-derived metrics of mean kurtosis (MK) and mean diffusivity (MD). Individual T1-weighted images were used to create subject-specific cortically-labelled regions of interest (ROIs) of the four cortical lobes and sixty-eight cortical GM regions delineated by the Desikan-Killiany atlas, and to derive the associated cortical thickness and area measures. The derived ROIs were also registered to the diffusion space of each subject and used to generate region-specific mean MK and MD values. We additionally administered the Wisconsin Card Sorting Test (WCST), Stroop test, and Trail Making Test part B (Trails-B) to test the relationship between GM metrics and executive function in SZ. We found significantly increased MK and MD in SZ compared to HC participants in the temporal lobe, sub-lobar temporal cortical regions (fusiform, inferior temporal, middle temporal and temporal pole), and posterior cingulate cortex after correcting for multiple comparisons. Correlational analyses revealed significant associations of MK and MD with executive function scores derived from the WCST, Stroop, and Trails-B tests, along with an inverse relationship between MK and MD and cortical thickness and area. A hierarchical multiple linear regression analysis showed that up to 85% of the inter-subject variability in cognitive function in schizophrenia measured by the WCST could be explained by MK in combination with either GM thickness or area. MK and MD appear to be sensitive to GM microstructural pathology in schizophrenia and may provide useful biomarkers of abnormal cortical microstructure in this disorder.
| S-EPMC7556324 | biostudies-literature
Project description:BackgroundAutism spectrum disorder (ASD) is a complex neurodevelopmental condition. Understanding the brain's microstructure and its relationship to clinical characteristics is important to advance our understanding of the neural supports underlying ASD. In the current work, we implemented Gray-Matter Based Spatial Statistics (GBSS) to examine and characterize cortical microstructure and assess differences between typically developing (TD) and autistic males.MethodsA multi-shell diffusion MRI (dMRI) protocol was acquired from 83 TD and 70 autistic males (5-to-21-years) and fit to the DTI and NODDI models. GBSS was performed for voxelwise analysis of cortical gray matter (GM). General linear models were used to investigate group differences, while age-by-group interactions assessed age-related differences between groups. Within the ASD group, relationships between cortical microstructure and measures of autistic symptoms were investigated.ResultsAll dMRI measures were significantly associated with age across the GM skeleton. Group differences and age-by-group interactions are reported. Group-wise increases in neurite density in autistic individuals were observed across frontal, temporal, and occipital regions of the right hemisphere. Significant age-by-group interactions of neurite density were observed within the middle frontal gyrus, precentral gyrus, and frontal pole. Negative relationships between neurite dispersion and the ADOS-2 Calibrated Severity Scores (CSS) were observed within the ASD group.DiscussionFindings demonstrate group and age-related differences between groups in neurite density in ASD across right-hemisphere brain regions supporting cognitive processes. Results provide evidence of altered neurodevelopmental processes affecting GM microstructure in autistic males with implications for the role of cortical microstructure in the level of autistic symptoms.ConclusionUsing dMRI and GBSS, our findings provide new insights into group and age-related differences of the GM microstructure in autistic males. Defining where and when these cortical GM differences arise will contribute to our understanding of brain-behavior relationships of ASD and may aid in the development and monitoring of targeted and individualized interventions.
| S-EPMC9817031 | biostudies-literature
Project description:Variations of the cholesteryl ester transfer protein polymorphism (CETP I405V/rs5882) have been associated with an increased risk for neurodegeneration, particularly when examined in conjunction with the epsilon 4 isoform of apolipoprotein E (ApoE4). Despite these identified relationships, the impact of I405V on gray matter microstructure remains unknown. The present study examined the impact of the CETP I405V polymorphism on gray matter integrity among 52 healthy adults between ages 51 and 85. Gray matter was measured bilaterally using diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). Participants were grouped according to a dominant statistical model (II genotype vs. IV/VV genotypes) and secondary analyses were completed to examine the interactive effects of CETP and ApoE4 on DTI metrics. Compared to individuals with the IV/VV genotypes, II homozygotes demonstrated significantly higher MD in bilateral temporal, parietal, and occipital gray matter. Secondary analyses revealed higher FA and AD in the left temporal lobe of IV/VV genotypes with an ApoE4 allele. Our results provide preliminary evidence that CETP II homozygosity is a predisposing risk factor for gray matter abnormalities in posterior brain regions in healthy older adults, independent of an ApoE4 allele.
| S-EPMC4618053 | biostudies-literature
Project description:With increasing age, functional connectomes become dissimilar across normal individuals, reflecting heterogenous aging effects on functional connectivity (FC). We investigated the distribution of these effects across the connectome and their relationship with age-related differences in dopamine (DA) D1 receptor availability and gray matter density (GMD). With this aim, we determined aging effects on mean and interindividual variance of FC using fMRI in 30 younger and 30 older healthy subjects and mapped the contribution of each connection to the patterns of age-related similarity loss. Aging effects on mean FC accounted mainly for the dissimilarity between connectomes of younger and older adults, and were related, across brain regions, to aging effects on DA D1 receptor availability. Aging effects on the variance of FC indicated a global increase in variance with advancing age, explained connectome dissimilarity among older subjects and were related to aging effects on variance of GMD. The relationship between aging and the similarity of connectomes can thus be partly explained by age differences in DA modulation and gray matter structure.
| S-EPMC7981334 | biostudies-literature
Project description:BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental condition commonly studied in the context of early childhood. As ASD is a life-long condition, understanding the characteristics of brain microstructure from adolescence into adulthood and associations to clinical features is critical for improving outcomes across the lifespan. In the current work, we utilized Tract Based Spatial Statistics (TBSS) and Gray Matter Based Spatial Statistics (GBSS) to examine the white matter (WM) and gray matter (GM) microstructure in neurotypical (NT) and autistic males.MethodsMulti-shell diffusion MRI was acquired from 78 autistic and 81 NT males (12-to-46-years) and fit to the DTI and NODDI diffusion models. TBSS and GBSS were performed to analyze WM and GM microstructure, respectively. General linear models were used to investigate group and age-related group differences. Within the ASD group, relationships between WM and GM microstructure and measures of autistic symptoms were investigated.ResultsAll dMRI measures were significantly associated with age across WM and GM. Significant group differences were observed across WM and GM. No significant age-by-group interactions were detected. Within the ASD group, positive relationships with WM microstructure were observed with ADOS-2 Calibrated Severity Scores.ConclusionUsing TBSS and GBSS our findings provide new insights into group differences of WM and GM microstructure in autistic males from adolescence into adulthood. Detection of microstructural differences across the lifespan as well as their relationship to the level of autistic symptoms will deepen to our understanding of brain-behavior relationships of ASD and may aid in the improvement of intervention options for autistic adults.
| S-EPMC10565827 | biostudies-literature
Project description:Integrins are heterodimeric extracellular matrix receptors that are essential for the proper development of the vertebrate nervous system. We report here that selective loss of integrin β1 in excitatory neurons leads to reductions in the size and complexity of hippocampal dendritic arbors, hippocampal synapse loss, impaired hippocampus-dependent learning, and exaggerated psychomotor sensitivity to cocaine in mice. Our biochemical and genetic experiments demonstrate that the intracellular tail of integrin β1 binds directly to Arg kinase and that this interaction stimulates activity of the Arg substrate p190RhoGAP, an inactivator of the RhoA GTPase. Moreover, genetic manipulations that reduce integrin β1 signaling through Arg recapitulate the integrin β1 knock-out phenotype in a gene dose-sensitive manner. Together, these results describe a novel integrin β1-Arg-p190RhoGAP pathway that regulates dendritic arbor size, promotes synapse maintenance, supports proper hippocampal function, and mitigates the behavioral consequences of cocaine exposure.
| S-EPMC3313657 | biostudies-literature
Project description:Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are widely used models to infer microstructural features in the brain from diffusion-weighted MRI. Several studies have recently applied both models to increase sensitivity to biological changes, however, it remains uncertain how these measures are associated. Here we show that cortical distributions of DTI and NODDI are associated depending on the choice of b-value, a factor reflecting strength of diffusion weighting gradient. We analyzed a combination of high, intermediate and low b-value data of multi-shell diffusion-weighted MRI (dMRI) in healthy 456 subjects of the Human Connectome Project using NODDI, DTI and a mathematical conversion from DTI to NODDI. Cortical distributions of DTI and DTI-derived NODDI metrics were remarkably associated with those in NODDI, particularly when applied highly diffusion-weighted data (b-value?=?3000?sec/mm2). This was supported by simulation analysis, which revealed that DTI-derived parameters with lower b-value datasets suffered from errors due to heterogeneity of cerebrospinal fluid fraction and partial volume. These findings suggest that high b-value DTI redundantly parallels with NODDI-based cortical neurite measures, but the conventional low b-value DTI is hard to reasonably characterize cortical microarchitecture.
| S-EPMC6706419 | biostudies-literature