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Item does not contain fulltext The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h(2)=0.53-0.90, p

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability. © 2014 Elsevier Inc.

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/). © 2013 The Authors.

Theory of Mind (ToM) or mentalizing is the ability of individuals to determine the intentions and behavior of others. This ability is known to be compromised in schizophrenia and has been shown to fluctuate with symptom severity. Neuropsychological investigations into relatives of individuals with schizophrenia have shown that some relatives also show a deficit in this area of social cognition. In order to address this state and trait issue, we investigated the performance of high-risk relatives of individuals with schizophrenia to those of a matched control group (n = 13) on a blocked design visual joke fMRI paradigm. The task involved looking at two sets of cartoon jokes, one set which required mentalizing abilities to understand the jokes and another set that did not require such abilities. Relatives were divided into two groups based on the presence (HR+, n = 12) or absence (HR−, n = 12) of positive symptoms. The task provided robust activations across the groups in areas previously associated with mentalizing abilities, such as the PFC, precuneus, and temporal lobes. Significant between-group activations were observed in the PFC (primarily BA6, 8, and 9) with the HR− activating significantly greater than the HR+ in these regions. Both a secondary state-specific analysis and a third post hoc analysis further investigating state effects showed significant PFC between-group differences. This study is the first time relatives of individuals with schizophrenia have been imaged using a ToM paradigm, and the results provide evidence of both a state and state-mediated trait effect.

Multicentre MRI studies offer great potential to increase study power and flexibility, but it is not yet clear how reproducible the results from multiple centres may be. Here we present results from the multicentre study ‘CaliBrain’, examining the reproducibility of fMRI data within and between three sites. Fourteen subjects were scanned twice on three 1.5 T GE scanners using an identical scanning protocol. We present data from a motor task with three conditions, sequential and random finger tapping and rest. Similar activation maps were obtained for each site and visit; brain areas consistently activated during the task included the premotor, primary motor and supplementary motor areas, the striatum and cerebellum. Reproducibility was evaluated within and between sites by comparing the extent and spatial agreement of activation maps at both the subject and group levels. The results were within the range previously reported for similar tasks on single scanners and both measures were found to be comparable within and between sites, with between site reproducibility similar to the within site measures. A variance components analysis was used to examine the effects of site, subject and visit. The contributions of site and visit were small and reproducibility was similar between and within sites, whereas the variance between subjects, and unexplained variance was large. These findings suggest that we can have confidence in combined results from multicentre fMRI studies, at least when a consistent protocol is followed on similar machines in all participating scanning sites and care is taken to select homogeneous subject groups.