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/)

Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data

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 (h2 = 0.53–0.90, p < 10− 5), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests that the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application

The reliability and heritability of cortical folds and their genetic correlations across hemispheres

Cortical folds help drive the parcellation of the human cortex into functionally specific regions. Variations in the length, depth, width, and surface area of these sulcal landmarks have been associated with disease, and may be genetically mediated. Before estimating the heritability of sulcal variation, the extent to which these metrics can be reliably extracted from in-vivo MRI must be established. Using four independent test-retest datasets, we found high reliability across the brain (intraclass correlation interquartile range: 0.65–0.85). Heritability estimates were derived for three family-based cohorts using variance components analysis and pooled (total N \u3e 3000); the overall sulcal heritability pattern was correlated to that derived for a large population cohort (N \u3e 9000) calculated using genomic complex trait analysis. Overall, sulcal width was the most heritable metric, and earlier forming sulci showed higher heritability. The inter-hemispheric genetic correlations were high, yet select sulci showed incomplete pleiotropy, suggesting hemisphere-specific genetic influences

The reliability and heritability of cortical folds and their genetic correlations across hemispheres

Cortical folds help drive the parcellation of the human cortex into functionally specific regions. Variations in the length, depth, width, and surface area of these sulcal landmarks have been associated with disease, and may be genetically mediated. Before estimating the heritability of sulcal variation, the extent to which these metrics can be reliably extracted from in-vivo MRI must be established. Using four independent test-retest datasets, we found high reliability across the brain (intraclass correlation interquartile range: 0.65-0.85). Heritability estimates were derived for three family-based cohorts using variance components analysis and pooled (total N > 3000); the overall sulcal heritability pattern was correlated to that derived for a large population cohort (N > 9000) calculated using genomic complex trait analysis. Overall, sulcal width was the most heritable metric, and earlier forming sulci showed higher heritability. The inter-hemispheric genetic correlations were high, yet select sulci showed incomplete pleiotropy, suggesting hemisphere-specific genetic influences

Role of magnetic resonance spectroscopy in cerebral glutathione quantification for youth mental health:A systematic review

AIM: Oxidative stress is strongly implicated in many psychiatric disorders, which has resulted in the development of new interventions to attempt to perturb this pathology. A great deal of attention has been paid to glutathione, which is the brain's dominant antioxidant and plays a fundamental role in removing free radicals and other reactive oxygen species. Measurement of glutathione concentration in the brain in vivo can provide information on redox status and potential for oxidative stress to develop. Glutathione might also represent a marker to assess treatment response. METHODS: This paper systematically reviews studies that assess glutathione concentration (measured using magnetic resonance spectroscopy) in various mental health conditions. RESULTS: There is limited evidence showing altered brain glutathione concentration in mental disorders; the best evidence suggests glutathione is decreased in depression, but is not altered in bipolar disorder. The review then outlines the various methodological options for acquiring glutathione data using spectroscopy. CONCLUSIONS: Analysis of the minimum effect size measurable in existing studies indicates that increased number of participants is required to measure subtle but possibly important differences and move the field forward

Implementation of Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES) for quantification of ɣ-aminobutyric acid (GABA) and glutathione (GSH)

The present study aimed to accelerate and improve accuracy of ɣ-aminobutyric acid (GABA) and glutathione (GSH) quantification. These metabolites, present at low concentrations in the brain, are challenging to detect using MR spectroscopy due to the fact that their resonance frequencies overlap with those of other more abundant metabolites. The advanced spectral editing techniques involving J-difference editing that are required to resolve the overlapping signals of these low concentration metabolites are not routinely available on clinical MRI scanners. In this work we implemented on a 3T Siemens Skyra MRI a novel MRS technique called Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES) to simultaneously detect GABA and GSH, developed a novel postprocessing technique that simultaneously models the sum and various difference spectra, and evaluated the performance of the sequence and processing method both in phantoms and in vivo. HERMES was implemented by modifying the Siemens GABA-edited MEGA-PRESS WIP sequence to include two additional sub-experiments – one editing GSH with a single lobe pulse and one editing both GABA and GSH using a dual lobe pulse, and replacing the Siemens pulses with ‘universal' pulses similar to those used in a previous implementation of HERMES on a Philips platform. Performance was assessed in a phantom and 22 healthy adults, 15 of whom provided usable data (7 male, mean age 25.6 ± 2.7 yr). Three of the subjects were scanned 3 times to assess reproducibility. Data were processed and compared using a set of custom scripts in MATLAB. Following frequency and phase correction of individual averages with GANNET, we applied our custom simultaneous linear combination model that iteratively fit the concatenated sum and difference spectra using a least squares routine. SPM was used for tissue segmentation of structural images and FID-A to simulate high-resolution basis sets. The simultaneous modelling technique provided absolute quantification results for 15 metabolite moieties using internal unsuppressed water as a reference. The performance of the simultaneous fitting approach was compared to multiple independent fittings for HERCULES (Hadamard Editing Resolves Chemicals Using Linear-combination Estimation of Spectra) data that had been previously acquired on a 3T Philips Achieva MRI. Although the HERMES sequence implemented on the Siemens platform as part of this project was able to successfully edit both GABA and GSH, and generate line shapes consistent with the work by Saleh et al. (2016), quantification accuracy was disappointing. In the phantom data, GSH and GABA concentrations were both roughly 50% of known levels. Since the actual concentrations in vivo were not known, we were not able to establish accuracy, but quantification agreement between the MEGA-PRESS and HERMES sequences was poor for most metabolites. Specifically, GABA levels were two to three times higher than expected values using both HERMES and GABA-edited MEGA-PRESS. Despite poor absolute agreement, concentrations from HERMES and MEGA-PRESS data were moderately correlated, and HERMES data showed lower coefficients of variation across subjects, suggesting that it may be more reliable. HERMES was also more reproducible across scanning sessions and participants for more metabolites than GABA- or GSH-edited MEGA-PRESS. Our findings also showed that simultaneous fitting using the sum and difference spectra produces lower coefficients of variation for most metabolites than fittings to sum and difference spectra separately

Establishing reliable MR spectroscopy techniques for measuring GABA and Glutathione in the human brain

Background: Proton MR spectroscopy (MRS) is a well-established method for measuring the relative concentration of a wide range of metabolites in the human brain noninvasively. Lately, more advanced spectroscopic techniques, such as MEGAPRESS, have emerged enabling us to measure low concentrated metabolites with complex peak splitting patterns. Examples of such metabolites are the main inhibitory brain neurotransmitter, g-aminobutyric acid (GABA), and the main brain antioxidant, glutathione (GSH). Impairment of both GABA and GSH have been implicated in the pathophysiology of several psychiatric and neurodegenerative disorders, including schizophrenia, bipolar disorder, autism spectrum disorder (ASD), multiple sclerosis, Alzheimer’s disease, amyotrophic lateral sclerosis and Parkinson disease. An accurate and reliable quantification of these metabolites in vivo is therefore of utmost interest and clinical relevance. The PhD started with an ASD focus, setting out to examine brain MRS measurable differences between boys with ASD and controls. The focus, however, soon shifted to the methodological aspect of MRS, with a desire to contribute in establishing reliable MRS techniques for measuring GABA and GSH in the human brain. Aims: The aim of the ASD study was to explore the excitatory/inhibitory hypothesis in children with ASD by looking for imbalances in brain metabolites in boys with ASD compared with typically developing controls with standard and advanced MRS techniques. Validating GABA and GSH edited MEGA-PRESS, and comparing these sequences to the standard single voxel measurements; short TE STEAM and PRESS sequence. Methods: Four different studies were performed, all on a 3.0 T GE MRI scanner. The ASD study: 14 boys with ASD and 24 age-matched controls were examined with both the GABA edited MEGA-PRESS and PRESS sequence. Autism symptom severity were reported by the Autism Spectrum Screening Questionnaire (ASSQ). The GABA reprod study: Two 20 min long GABA edited MEGA-PRESS acquisition were performed in 21 healthy young male volunteers. The participants were scanned twice with identical protocols. By applying a timewindowing approach, within-and between-session reproducibility was calculated. The “Christmas phantom” study: 122 GSH edited MEGA-PRESS and PRESS spectra of a phantom containing GSH were acquired over a time period of 11 days. The resulting decaying GSH curve (GSH oxidizes to GSSG) were modelled. A 1-year-after follow-up acquisition for both sequences was also performed. The GSH reprod study: GSH edited MEGA-PRESS and short TE STEAM and PRESS acquisitions were performed in 36 healthy volunteers. The participants were scanned twice with identical protocols, one week apart. The timewindowing approach was applied for within- and between-session reproducibility for GSH edited MEGA-PRESS. Differences between quantified GSH levels between males and females were examined, and the three different methods of measuring GSH were evaluated. Main Results: There was a significant negative correlation in the ASD group between ASSQ and GABA levels, however there was no significant difference between the ASD group and the control group in MEGA-PRESS measured GABA levels. Increasing the number of repetitions in GABA edited MEGA-PRESS showed improvements for within- and between-session reproducibility up to about 218 paired repetitions (scan length ~ 13 min). Gannet combined with LCModel proved the best method processing the GABA data. Both GSH edited MEGA-PRESS and PRESS were able to measure the degradation of GSH in the phantom, however the modelled GSH edited MEGA-PRESS degradation curve was more accurate than PRESS. Between-session variability of GSH edited MEGA-PRESS stabilised at around 128 paired repetitions (~8 min). There were no significant correlations between GSH measured with MEGA-PRESS, STEAM and PRESS, and no differences in measured GSH levels between males and females. Conclusion: In line with other studies, the ASD participants have GABA values that seem to change with their clinical severity although there was no group difference with healthy controls. For both GABA and GSH, it is possible to acquire reproducible MEGA-PRESS measurements. GSH edited MEGA-PRESS measurements have somewhat higher coefficient of variation (meaning lower reproducibility), but stabilises at a shorter scan length than GABA edited MEGA-PRESS. MEGA-PRESS is more accurate that both PRESS and STEAM in measuring GSH for in vivo measurements. This is also reflected in its in vitro quantification, where the PRESS measurements fit of GSH seem to include oxidised GSH