A tensor-based morphometry study of genetic influences on brain structure using a new fluid registration method

Early-Emerging Sulcal Patterns Are Atypical in Fetuses with Congenital Heart Disease

Fetuses with congenital heart disease (CHD) have third trimester alterations in cortical development on brain magnetic resonance imaging (MRI). However, the intersulcal relationships contributing to global sulcal pattern remain unknown. This study applied a novel method for examining the geometric and topological relationships between sulci to fetal brain MRIs from 21-30 gestational weeks in CHD fetuses (n = 19) and typically developing (TD) fetuses (n = 17). Sulcal pattern similarity index (SI) to template fetal brain MRIs was determined for the position, area, and depth for corresponding sulcal basins and intersulcal relationships for each subject. CHD fetuses demonstrated altered global sulcal patterns in the left hemisphere compared with TD fetuses (TD [SI, mean ± SD]: 0.822 ± 0.023, CHD: 0.795 ± 0.030, P = 0.002). These differences were present in the earliest emerging sulci and were driven by differences in the position of corresponding sulcal basins (TD: 0.897 ± 0.024, CHD: 0.878 ± 0.019, P = 0.006) and intersulcal relationships (TD: 0.876 ± 0.031, CHD: 0.857 ± 0.018, P = 0.033). No differences in cortical gyrification index, mean curvature, or surface area were present. These data suggest our methods may be more sensitive than traditional measures for evaluating cortical developmental alterations early in gestation.

The Congenital Heart Disease Brain: Prenatal Considerations for Perioperative Neurocritical Care

Altered brain development has been highlighted as an important contributor to adverse neurodevelopmental outcomes in children with congenital heart disease. Abnormalities begin prenatally and include micro- and macrostructural disturbances that lead to an altered trajectory of brain growth throughout gestation. Recent progress in fetal imaging has improved understanding of the neurobiological mechanisms and risk factors for impaired fetal brain development. The impact of the prenatal environment on postnatal neurological care has also gained increased focus. This review summarizes current data on the timing and pattern of altered prenatal brain development in congenital heart disease, the potential mechanisms of these abnormalities, and the association with perioperative neurological complications.

Brain Imaging Genomics: Integrated Analysis and Machine Learning

Brain imaging genomics is an emerging data science field, where integrated analysis of brain imaging and genomics data, often combined with other biomarker, clinical and environmental data, is performed to gain new insights into the phenotypic, genetic and molecular characteristics of the brain as well as their impact on normal and disordered brain function and behavior. It has enormous potential to contribute significantly to biomedical discoveries in brain science. Given the increasingly important role of statistical and machine learning in biomedicine and rapidly growing literature in brain imaging genomics, we provide an up-to-date and comprehensive review of statistical and machine learning methods for brain imaging genomics, as well as a practical discussion on method selection for various biomedical applications.

Applying tensor-based morphometry to parametric surfaces can improve MRI-based disease diagnosis

Many methods have been proposed for computer-assisted diagnostic classification. Full tensor information and machine learning with 3D maps derived from brain images may help detect subtle differences or classify subjects into different groups. Here we develop a new approach to apply tensor-based morphometry to parametric surface models for diagnostic classification. We use this approach to identify cortical surface features for use in diagnostic classifiers. First, with holomorphic 1-forms, we compute an efficient and accurate conformal mapping from a multiply connected mesh to the so-called slit domain. Next, the surface parameterization approach provides a natural way to register anatomical surfaces across subjects using a constrained harmonic map. To analyze anatomical differences, we then analyze the full Riemannian surface metric tensors, which retain multivariate information on local surface geometry. As the number of voxels in a 3D image is large, sparse learning is a promising method to select a subset of imaging features and to improve classification accuracy. Focusing on vertices with greatest effect sizes, we train a diagnostic classifier using the surface features selected by an L1-norm based sparse learning method. Stability selection is applied to validate the selected feature sets. We tested the algorithm on MRI-derived cortical surfaces from 42 subjects with genetically confirmed Williams syndrome and 40 age-matched controls, multivariate statistics on the local tensors gave greater effect sizes for detecting group differences relative to other TBM-based statistics including analysis of the Jacobian determinant and the largest eigenvalue of the surface metric. Our method also gave reasonable classification results relative to the Jacobian determinant, the pair of eigenvalues of the Jacobian matrix and volume features. This analysis pipeline may boost the power of morphometry studies, and may assist with image-based classification.

Disease and genetic contributions toward local tissue volume disturbances in schizophrenia: a tensor-based morphometry study

Structural brain deficits, especially frontotemporal volume reduction and ventricular enlargement, have been repeatedly reported in patients with schizophrenia. However, it remains unclear whether brain structural deformations may be attributable to disease-related or genetic factors. In this study, the structural magnetic resonance imaging data of 48 adult-onset schizophrenia patients, 65 first-degree nonpsychotic relatives of schizophrenia patients, 27 community comparison (CC) probands, and 73 CC relatives were examined using tensor-based morphometry (TBM) to isolate global and localized differences in tissue volume across the entire brain between groups. We found brain tissue contractions most prominently in frontal and temporal regions and expansions in the putamen/pallidum, and lateral and third ventricles in schizophrenia patients when compared with unrelated CC probands. Results were similar, though less prominent when patients were compared with their nonpsychotic relatives. Structural deformations observed in unaffected patient relatives compared to age-similar CC relatives were suggestive of schizophrenia-related genetic liability and were pronounced in the putamen/pallidum and medial temporal regions. Schizophrenia and genetic liability effects for the putamen/pallidum were confirmed by regions-of-interest analysis. In conclusion, TBM findings complement reports of frontal, temporal, and ventricular dysmorphology in schizophrenia and further indicate that putamen/pallidum enlargements, originally linked mainly with medication exposure in early studies, also reflect a genetic predisposition for schizophrenia. Thus, brain deformation profiles revealed in this study may help to clarify the role of specific genetic or environmental risk factors toward altered brain morphology in schizophrenia.

Logical circularity in voxel-based analysis: normalization strategy may induce statistical bias

Recent discussions within the neuroimaging community have highlighted the problematic presence of selection bias in experimental design. Although initially centering on the selection of voxels during the course of fMRI studies, we demonstrate how this bias can potentially corrupt voxel-based analyses. For such studies, template-based registration plays a critical role in which a representative template serves as the normalized space for group alignment. A standard approach maps each subject's image to a representative template before performing statistical comparisons between different groups. We analytically demonstrate that in these scenarios the popular sum of squared difference (SSD) intensity metric, implicitly surrogating as a quantification of anatomical alignment, instead explicitly maximizes effect size--an experimental design flaw referred to as "circularity bias." We illustrate how this selection bias varies in strength with the similarity metric used during registration under the hypothesis that while SSD-related metrics, such as Demons, will manifest similar effects, other metrics which are not formulated based on absolute intensity differences will produce less of an effect. Consequently, given the variability in voxel-based analysis outcomes with similarity metric choice, we caution researchers specifically in the use of SSD and SSD-related measures where normalization and statistical analysis involve the same image set. Instead, we advocate a more cautious approach where normalization of the individual subject images to the reference space occurs through corresponding image sets which are independent of statistical testing. Alternatively, one can use similarity terms that are less sensitive to this bias.

Genetic and environmental influences on neuroimaging phenotypes: a meta-analytical perspective on twin imaging studies

Because brain structure and function are affected in neurological and psychiatric disorders, it is important to disentangle the sources of variation in these phenotypes. Over the past 15 years, twin studies have found evidence for both genetic and environmental influences on neuroimaging phenotypes, but considerable variation across studies makes it difficult to draw clear conclusions about the relative magnitude of these influences. Here we performed the first meta-analysis of structural MRI data from 48 studies on >1,250 twin pairs, and diffusion tensor imaging data from 10 studies on 444 twin pairs. The proportion of total variance accounted for by genes (A), shared environment (C), and unshared environment (E), was calculated by averaging A, C, and E estimates across studies from independent twin cohorts and weighting by sample size. The results indicated that additive genetic estimates were significantly different from zero for all meta-analyzed phenotypes, with the exception of fractional anisotropy (FA) of the callosal splenium, and cortical thickness (CT) of the uncus, left parahippocampal gyrus, and insula. For many phenotypes there was also a significant influence of C. We now have good estimates of heritability for many regional and lobar CT measures, in addition to the global volumes. Confidence intervals are wide and number of individuals small for many of the other phenotypes. In conclusion, while our meta-analysis shows that imaging measures are strongly influenced by genes, and that novel phenotypes such as CT measures, FA measures, and brain activation measures look especially promising, replication across independent samples and demographic groups is necessary.

Age-related differences in corpus callosum area of capuchin monkeys

Capuchin monkeys (Cebus apella) are New World primates with relatively large brains for their body size. The developmental trajectories of several brain regions-including cortical white matter, frontal lobe white matter, and basal ganglia nuclei-are similar to humans. Additionally, capuchins have independently evolved several behavioral and anatomical characteristics in common with humans and chimpanzees-including complex manipulative abilities, use of tools, and the use of precision grips-making them interesting species for studies of comparative brain morphology and organization. Here, we report the first investigation into the development of the corpus callosum (CC) and its regional subdivisions in capuchins. CC development was quantified using high-resolution structural magnetic resonance imaging (MRI) images from 39 socially reared subjects (male n=22; female n=18) ranging in age from 4 days (infancy) to 20 years (middle adulthood). The total area of the CC and the subdivisions of the genu, rostral midbody, medial midbody, caudal midbody, and splenium were traced from the midsagittal section. Total CC area displayed significant differences across this time span and was best explained by quadratic growth. Sustained linear growth was observed in the subdivisions of the genu, rostral midbody, and splenium; sustained quadratic growth was seen in the subdivision of the medial midbody. Differences in growth were not detected in the subdivision of the caudal midbody. Females had a larger raw area of the total CC and of the medial midbody and caudal midbody throughout the lifespan. Our results indicate that capuchins show continued white matter development beyond adolescence in regions related to cognitive and motor development.

Neurological imaging: statistics behind the pictures

Neurological imaging represents a powerful paradigm for investigation of brain structure, physiology and function across different scales. The diverse phenotypes and significant normal and pathological brain variability demand reliable and efficient statistical methodologies to model, analyze and interpret raw neurological images and derived geometric information from these images. The validity, reproducibility and power of any statistical brain map require appropriate inference on large cohorts, significant community validation, and multidisciplinary collaborations between physicians, engineers and statisticians.

COMPARISON OF VOLUMETRIC REGISTRATION ALGORITHMS FOR TENSOR-BASED MORPHOMETRY

Nonlinear registration of brain MRI scans is often used to quantify morphological differences associated with disease or genetic factors. Recently, surface-guided fully 3D volumetric registrations have been developed that combine intensity-guided volume registrations with cortical surface constraints. In this paper, we compare one such algorithm to two popular high-dimensional volumetric registration methods: large-deformation viscous fluid registration, formulated in a Riemannian framework, and the diffeomorphic "Demons" algorithm. We performed an objective morphometric comparison, by using a large MRI dataset from 340 young adult twin subjects to examine 3D patterns of correlations in anatomical volumes. Surface-constrained volume registration gave greater effect sizes for detecting morphometric associations near the cortex, while the other two approaches gave greater effects sizes subcortically. These findings suggest novel ways to combine the advantages of multiple methods in the future.

Blood pressure and cerebral white matter share common genetic factors in Mexican Americans

Elevated arterial pulse pressure and blood pressure (BP) can lead to atrophy of cerebral white matter (WM), potentially attributable to shared genetic factors. We calculated the magnitude of shared genetic variance between BP and fractional anisotropy of water diffusion, a sensitive measurement of WM integrity in a well-characterized population of Mexican Americans. The patterns of whole-brain and regional genetic overlap between BP and fractional anisotropy were interpreted in the context the pulse-wave encephalopathy theory. We also tested whether regional pattern in genetic pleiotropy is modulated by the phylogeny of WM development. BP and high-resolution (1.7 × 1.7 × 3 mm; 55 directions) diffusion tensor imaging data were analyzed for 332 (202 females; mean age 47.9 ± 13.3 years) members of the San Antonio Family Heart Study. Bivariate genetic correlation analysis was used to calculate the genetic overlap between several BP measurements (pulse pressure, systolic BP, and diastolic BP) and fractional anisotropy (whole-brain and regional values). Intersubject variance in pulse pressure and systolic BP exhibited a significant genetic overlap with variance in whole-brain fractional anisotropy values, sharing 36% and 22% of genetic variance, respectively. Regionally, shared genetic variance was significantly influenced by rates of WM development (r=-0.75; P=0.01). The pattern of genetic overlap between BP and WM integrity was generally in agreement with the pulse-wave encephalopathy theory. Our study provides evidence that a set of pleiotropically acting genetic factors jointly influence phenotypic variation in BP and WM integrity. The magnitude of this overlap appears to be influenced by phylogeny of WM development, suggesting a possible role for genotype-by-age interactions.

Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins

Information from the full diffusion tensor (DT) was used to compute voxel-wise genetic contributions to brain fiber microstructure. First, we designed a new multivariate intraclass correlation formula in the log-Euclidean framework. We then analyzed used the full multivariate structure of the tensor in a multivariate version of a voxel-wise maximum-likelihood structural equation model (SEM) that computes the variance contributions in the DTs from genetic (A), common environmental (C) and unique environmental (E) factors. Our algorithm was tested on DT images from 25 identical and 25 fraternal twin pairs. After linear and fluid registration to a mean template, we computed the intraclass correlation and Falconer's heritability statistic for several scalar DT-derived measures and for the full multivariate tensors. Covariance matrices were found from the DTs, and inputted into SEM. Analyzing the full DT enhanced the detection of A and C effects. This approach should empower imaging genetics studies that use DTI.

Mapping primary gyrogenesis during fetal development in primate brains: high-resolution in utero structural MRI of fetal brain development in pregnant baboons

The global and regional changes in the fetal cerebral cortex in primates were mapped during primary gyrification (PG; weeks 17-25 of 26 weeks total gestation). Studying pregnant baboons using high-resolution MRI in utero, measurements included cerebral volume, cortical surface area, gyrification index and length and depth of 10 primary cortical sulci. Seven normally developing fetuses were imaged in two animals longitudinally and sequentially. We compared these results to those on PG that from the ferret studies and analyzed them in the context of our recent studies of phylogenetics of cerebral gyrification. We observed that in both primates and non-primates, the cerebrum undergoes a very rapid transformation into the gyrencephalic state, subsequently accompanied by an accelerated growth in brain volume and cortical surface area. However, PG trends in baboons exhibited some critical differences from those observed in ferrets. For example, in baboons, the growth along the long (length) axis of cortical sulci was unrelated to the growth along the short (depth) axis and far outpaced it. Additionally, the correlation between the rate of growth along the short sulcal axis and heritability of sulcal depth was negative and approached significance (r = -0.60; p < 0.10), while the same trend for long axis was positive and not significant (p = 0.3; p = 0.40). These findings, in an animal that shares a highly orchestrated pattern of PG with humans, suggest that ontogenic processes that influence changes in sulcal length and depth are diverse and possibly driven by different factors in primates than in non-primates.

STATISTICALLY ASSISTED FLUID IMAGE REGISTRATION ALGORITHM - SAFIRA

In this paper, we develop and validate a new Statistically Assisted Fluid Registration Algorithm (SAFIRA) for brain images. A non-statistical version of this algorithm was first implemented in [2] and re-formulated using Lagrangian mechanics in [3]. Here we extend this algorithm to 3D: given 3D brain images from a population, vector fields and their corresponding deformation matrices are computed in a first round of registrations using the non-statistical implementation. Covariance matrices for both the deformation matrices and the vector fields are then obtained and incorporated (separately or jointly) in the regularizing (i.e., the non-conservative Lagrangian) terms, creating four versions of the algorithm. We evaluated the accuracy of each algorithm variant using the manually labeled LPBA40 dataset, which provides us with ground truth anatomical segmentations. We also compared the power of the different algorithms using tensor-based morphometry -a technique to analyze local volumetric differences in brain structure-applied to 46 3D brain scans from healthy monozygotic twins.

Genome-wide analysis reveals novel genes influencing temporal lobe structure with relevance to neurodegeneration in Alzheimer's disease

In a genome-wide association study of structural brain degeneration, we mapped the 3D profile of temporal lobe volume differences in 742 brain MRI scans of Alzheimer's disease patients, mildly impaired, and healthy elderly subjects. After searching 546,314 genomic markers, 2 single nucleotide polymorphisms (SNPs) were associated with bilateral temporal lobe volume (P<5 x 10(-7)). One SNP, rs10845840, is located in the GRIN2B gene which encodes the N-methyl-d-aspartate (NMDA) glutamate receptor NR2B subunit. This protein - involved in learning and memory, and excitotoxic cell death - has age-dependent prevalence in the synapse and is already a therapeutic target in Alzheimer's disease. Risk alleles for lower temporal lobe volume at this SNP were significantly over-represented in AD and MCI subjects vs. controls (odds ratio=1.273; P=0.039) and were associated with mini-mental state exam scores (MMSE; t=-2.114; P=0.035) demonstrating a negative effect on global cognitive function. Voxelwise maps of genetic association of this SNP with regional brain volumes, revealed intense temporal lobe effects (FDR correction at q=0.05; critical P=0.0257). This study uses large-scale brain mapping for gene discovery with implications for Alzheimer's disease.

Genetics of microstructure of cerebral white matter using diffusion tensor imaging

We analyzed the degree of genetic control over intersubject variability in the microstructure of cerebral white matter (WM) using diffusion tensor imaging (DTI). We performed heritability, genetic correlation and quantitative trait loci (QTL) analyses for the whole-brain and 10 major cerebral WM tracts. Average measurements for fractional anisotropy (FA), radial (L( perpendicular)) and axial (L( vertical line)) diffusivities served as quantitative traits. These analyses were done in 467 healthy individuals (182 males/285 females; average age 47.9+/-13.5 years; age range: 19-85 years), recruited from randomly-ascertained pedigrees of extended families. Significant heritability was observed for FA (h(2)=0.52+/-0.11; p=10(-7)) and L( perpendicular) (h(2)=0.37+/-0.14; p=0.001), while L( vertical line) measurements were not significantly heritable (h(2)=0.09+/-0.12; p=0.20). Genetic correlation analysis indicated that the FA and L( perpendicular) shared 46% of the genetic variance. Tract-wise analysis revealed a regionally diverse pattern of genetic control, which was unrelated to ontogenic factors, such as tract-wise age-of-peak FA values and rates of age-related change in FA. QTL analysis indicated linkages for whole-brain average FA (LOD=2.36) at the marker D15S816 on chromosome 15q25, and for L( perpendicular) (LOD=2.24) near the marker D3S1754 on the chromosome 3q27. These sites have been reported to have significant co-inheritance with two psychiatric disorders (major depression and obsessive-compulsive disorder) in which patients show characteristic alterations in cerebral WM. Our findings suggest that the microstructure of cerebral white matter is under a strong genetic control and further studies in healthy as well as patients with brain-related illnesses are imperative to identify the genes that may influence cerebral white matter.

Genetics of primary cerebral gyrification: Heritability of length, depth and area of primary sulci in an extended pedigree of Papio baboons

Genetic control over morphological variability of primary sulci and gyri is of great interest in the evolutionary, developmental and clinical neurosciences. Primary structures emerge early in development and their morphology is thought to be related to neuronal differentiation, development of functional connections and cortical lateralization. We measured the proportional contributions of genetics and environment to regional variability, testing two theories regarding regional modulation of genetic influences by ontogenic and phenotypic factors. Our measures were surface area, and average length and depth of eleven primary cortical sulci from high-resolution MR images in 180 pedigreed baboons. Average heritability values for sulcal area, depth and length (h(2)(Area)=.38+/-.22; h(2)(Depth)=.42+/-.23; h(2)(Length)=.34+/-.22) indicated that regional cortical anatomy is under genetic control. The regional pattern of genetic contributions was complex and, contrary to previously proposed theories, did not depend upon sulcal depth, or upon the sequence in which structures appear during development. Our results imply that heritability of sulcal phenotypes may be regionally modulated by arcuate U-fiber systems. However, further research is necessary to unravel the complexity of genetic contributions to cortical morphology.

Sex differences in brain structure in auditory and cingulate regions

We applied a new method to visualize the three-dimensional profile of sex differences in brain structure based on MRI scans of 100 young adults. We compared 50 men with 50 women, matched for age and other relevant demographics. As predicted, left hemisphere auditory and language-related regions were proportionally expanded in women versus men, suggesting a possible structural basis for the widely replicated sex differences in language processing. In men, primary visual, and visuo-spatial association areas of the parietal lobes were proportionally expanded, in line with prior reports of relative strengths in visuo-spatial processing in men. We relate these three-dimensional patterns to prior functional and structural studies, and to theoretical predictions based on nonlinear scaling of brain morphometry.