Multi-site genetic analysis of diffusion images and voxelwise heritability analysis : a pilot project of the ENIGMA–DTI working group

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA–DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18–85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/)

Mediation and Moderation of Intergenerational Epigenetic Effects of Trauma

Trauma and early-life stress have been linked to poor mental and physical health outcomes. In fact, research has identified trauma and stress can influence epigenetic marks on genes that can alter gene activity. It is suspected that epigenetically altered gene activity is involved in behavior and mental health. This may help explain why some individuals don’t experience great benefit from treatment for the effects of stress, and severe mental health symptoms can be chronic for decades or a lifetime. Moreover, some trauma-related mental health symptoms have shown generational patterns that appear linked to epigenetic marks. Therefore, this study sought to investigate the potential inter-generational influence of mother’s trauma history and mental health on her offspring’s DNA methylation and gene expression in umbilical cord blood. Standardized measures were used to assess mother’s trauma history and cumulative experienced fear (TLEQ), as well as mother’s mental health status during pregnancy (BSI). Genome-wide and candidate gene analyses were conducted after standard quality control data cleaning procedures. Batch and chip adjustments were made using the Combat package in R software, and the False Discovery Rate was employed to control for multiple comparisons. Results indicate mother’s exposure to trauma in childhood predicts DNA methylation and gene expression in offspring. Additionally, mother’s mental health status during pregnancy significantly predicts differential gene expression on 245 genes in males only. Finally, mother’s fear completely mediates the influence of trauma on her mental health functioning. In conclusion, a mother’s traumatic experience has potential to influence gene regulation in her offspring. Most importantly, mother’s mental health during pregnancy appears to exert a great influence on gene regulation in males compared to female offspring

Structural Neuroimaging of Anorexia Nervosa: Future Directions in the Quest for Mechanisms Underlying Dynamic Alterations.

Anorexia nervosa (AN) is a serious eating disorder characterized by self-starvation and extreme weight loss. Pseudoatrophic brain changes are often readily visible in individual brain scans, and AN may be a valuable model disorder to study structural neuroplasticity. Structural magnetic resonance imaging studies have found reduced gray matter volume and cortical thinning in acutely underweight patients to normalize following successful treatment. However, some well-controlled studies have found regionally greater gray matter and persistence of structural alterations following long-term recovery. Findings from diffusion tensor imaging studies of white matter integrity and connectivity are also inconsistent. Furthermore, despite the severity of AN, the number of existing structural neuroimaging studies is still relatively low, and our knowledge of the underlying cellular and molecular mechanisms for macrostructural brain changes is rudimentary. We critically review the current state of structural neuroimaging in AN and discuss the potential neurobiological basis of structural brain alterations in the disorder, highlighting impediments to progress, recent developments, and promising future directions. In particular, we argue for the utility of more standardized data collection, adopting a connectomics approach to understanding brain network architecture, employing advanced magnetic resonance imaging methods that quantify biomarkers of brain tissue microstructure, integrating data from multiple imaging modalities, strategic longitudinal observation during weight restoration, and large-scale data pooling. Our overarching objective is to motivate carefully controlled research of brain structure in eating disorders, which will ultimately help predict therapeutic response and improve treatment

Structural neuroimaging correlates of allelic variation of the BDNF val66met polymorphism.

BACKGROUND: The brain-derived neurotrophic factor (BDNF) val66met polymorphism is associated with altered activity dependent secretion of BDNF and a variable influence on brain morphology and cognition. Although a met-dose effect is generally assumed, to date the paucity of met-homozygotes have limited our understanding of the role of the met-allele on brain structure. METHODS: To investigate this phenomenon, we recruited sixty normal healthy subjects, twenty in each genotypic group (val/val, val/met and met/met). Global and local morphology were assessed using voxel based morphometry and surface reconstruction methods. White matter organisation was also investigated using tract-based spatial statistics and constrained spherical deconvolution tractography. RESULTS: Morphological analysis revealed an "inverted-U" shaped profile of cortical changes, with val/met heterozygotes most different relative to the two homozygous groups. These results were evident at a global and local level as well as in tractography analysis of white matter fibre bundles. CONCLUSION: In contrast to our expectations, we found no evidence of a linear met-dose effect on brain structure, rather our results support the view that the heterozygotic BDNF val66met genotype is associated with cortical morphology that is more distinct from the BDNF val66met homozygotes. These results may prove significant in furthering our understanding of the role of the BDNF met-allele in disorders such as Alzheimer's disease and depression

Neuroimaging genomics in psychiatry—a translational approach

Neuroimaging genomics is a relatively new field focused on integrating genomic and imaging data in order to investigate the mechanisms underlying brain phenotypes and neuropsychiatric disorders. While early work in neuroimaging genomics focused on mapping the associations of candidate gene variants with neuroimaging measures in small cohorts, the lack of reproducible results inspired better-powered and unbiased large-scale approaches. Notably, genome-wide association studies (GWAS) of brain imaging in thousands of individuals around the world have led to a range of promising findings. Extensions of such approaches are now addressing epigenetics, gene-gene epistasis, and gene-environment interactions, not only in brain structure, but also in brain function. Complementary developments in systems biology might facilitate the translation of findings from basic neuroscience and neuroimaging genomics to clinical practice. Here, we review recent approaches in neuroimaging genomics-we highlight the latest discoveries, discuss advantages and limitations of current approaches, and consider directions by which the field can move forward to shed light on brain disorders

INVESTIGATING THE GENETICS OF MICROSTRUCTURE OF THE CORPUS CALLOSUM IN THE AGEING BRAIN

Abstract: Age-related atrophy of the corpus callosum (CC) has been associated with cognitive impairment and neurodegenerative disease. To date, there is limited knowledge about the role genetics plays in age-related microstructural changes of CC. The current study sought to examine the role of genetic factors on the microstructure of CC in older individuals. Heritability, genetic correlation analyses and a genome-wide search for SNPs associated with the microstructural integrity of CC were undertaken. Brain imaging scans were collected from two studies of community-dwelling older adults the Older Australian Twins Study (OATS) and the Sydney Memory and Ageing Study (MAS). Diffusion tensor imaging (DTI) measures were estimated for the whole CC as well as for five subregions. Parcellation of the CC was performed using Analyze® software. Heritability analyses for CC DTI measures were undertaken in 284 healthy older twins (66% female; 79 MZ and 63 DZ pairs) from OATS (mean age = 69.82, SD=4.76 years). Heritability and genetic correlation analyses were undertaken using the SOLAR software package. Genome-wide association studies (GWAS) for CC DTI measures were undertaken in MAS and replication performed in OATS. Heritability (h2) analysis for the whole CC, indicated significant h2 for fractional anisotropy (FA) (h2=0.56), mean diffusivity (MD) (h2=0.52), radial diffusivity (RD) (h2=0.49) and axial diffusivity (AD) (h2=0.37). Bivariate genetic correlation analyses were also performed between whole CC DTI measures. Across the DTI measures for the whole CC, MD and RD shared 84% of the common genetic variance, followed by MD- AD (77%), FA - RD (52%), RD- AD (37%) and FA MD (11%). The GWAS did not identify any significant SNPs nor were any of the suggestive SNPs replicated in OATS. In addition, candidate CC DTI SNPs were not associated with CC DTI measures. These findings suggest that the CC white matter microstructure in older adults is generally under moderate genetic control. There was also evidence of shared genetic factors between all four CC DTI measures. This study did not identify any significant SNPs associated with CC DTI measures in the GWAS analysis. This work suggests larger genetic association studies may be required to find CC-DTI associated SNPs

Influence of the BDNF Genotype on Amygdalo-Prefrontal White Matter Microstructure is Linked to Nonconscious Attention Bias to Threat

Cognitive processing biases, such as increased attention to threat, are gaining recognition as causal factors in anxiety. Yet, little is known about the anatomical pathway by which threat biases cognition and how genetic factors might influence the integrity of this pathway, and thus, behavior. For 40 normative adults, we reconstructed the entire amygdalo-prefrontal white matter tract (uncinate fasciculus) using diffusion tensor weighted MRI and probabilistic tractography to test the hypothesis that greater fiber integrity correlates with greater nonconscious attention bias to threat as measured by a backward masked dot-probe task. We used path analysis to investigate the relationship between brain-derived nerve growth factor genotype, uncinate fasciculus integrity, and attention bias behavior. Greater structural integrity of the amygdalo-prefrontal tract correlates with facilitated attention bias to nonconscious threat. Genetic variability associated with brain-derived nerve growth factor appears to influence the microstructure of this pathway and, in turn, attention bias to nonconscious threat. These results suggest that the integrity of amygdalo-prefrontal projections underlie nonconscious attention bias to threat and mediate genetic influence on attention bias behavior. Prefrontal cognition and attentional processing in high bias individuals appear to be heavily influenced by nonconscious threat signals relayed via the uncinate fasciculus

BDNF Val66Met polymorphism moderates the association between sleep spindles and overnight visual recognition

A common single nucleotide polymorphism (SNP) of the brain-derived neurotrophic factor (BDNF) gene, Val66Met, has been reported to impair BDNF secretion and memory function. However, few studies have investigated the interaction of BDNF genotype and sleep characteristics, such as sleep spindles, that promote long-term potentiation during sleep. In this study we compared overnight visual memory between the carriers of BDNF Met and non-carriers (Val homozygotes), and examined how sleep spindle density associated with memory performance. The sample constituted of 151 adolescents (mean age 16.9 years; 69% Val homozygotes, 31% Met carriers). The learning task contained high and low arousal pictures from Interactive Affective Picture System. The learning task and all-night polysomnography were conducted at the homes of the adolescents. Slow (10–13 Hz) and fast (13–16 Hz) spindles were detected with automated algorithm. Neither post-sleep recognition accuracy nor spindle density differed between Val homozygotes and Met carriers. While frontal slow and fast spindle densities associated with better recognition accuracy in the entire sample, examining the allelic groups separately indicated paralleling associations in Val homozygotes only. Interaction analyses revealed a significant genotype-moderated difference in the associations between frontal fast sleep spindles and high arousal pictures. In sum, sleep spindles promote or indicate visual learning in Val homozygote adolescents but not in Met carriers. The result suggests that the role of sleep spindles in visual recognition memory is not equal across individuals but moderated by a common gene variant.Peer reviewe