Elliot Hong

Genetic Analysis of Cortical Thickness and Fractional Anisotropy of Water Diffusion in the Brain

Objectives: The thickness of the brain’s cortical gray matter (GM) and the fractional anisotropy (FA) of the cerebral white matter (WM) each follow an inverted U-shape trajectory with age. The two measures are positively correlated and may be modulated by common biological mechanisms. We employed four types of genetic analyses to localize individual genes acting pleiotropically upon these phenotypes. Methods: Whole-brain and regional GM thickness and FA values were measured from high-resolution anatomical and diffusion tensor MR images collected from 712, Mexican American participants (438 females, age = 47.9 ± 13.2 years) recruited from 73 (9.7 ± 9.3 individuals/family) large families. The significance of the correlation between two traits was estimated using a bivariate genetic correlation analysis. Localization of chromosomal regions that jointly influenced both traits was performed using whole-genome quantitative trait loci (QTL) analysis. Gene localization was performed using SNP genotyping on Illumina 1M chip and correlation with leukocyte-based gene-expression analyses. The gene-expressions were measured using the Illumina BeadChip. These data were available for 371 subjects. Results: Significant genetic correlation was observed among GM thickness and FA values. Significant logarithm of odds (LOD ≥ 3.0) QTLs were localized within chromosome 15q22–23. More detailed localization reported no significant association (p < 5·10−5) for 1565 SNPs located within the QTLs. Post hoc analysis indicated that 40% of the potentially significant (p ≤ 10−3) SNPs were localized to the related orphan receptor alpha (RORA) and NARG2 genes. A potentially significant association was observed for the rs2456930 polymorphism reported as a significant GWAS finding in Alzheimer’s disease neuroimaging initiative subjects. The expression levels for RORA and ADAM10 genes were significantly (p < 0.05) correlated with both FA and GM thickness. NARG2 expressions were significantly correlated with GM thickness (p < 0.05) but failed to show a significant correlation (p = 0.09) with FA. Discussion: This study identified a novel, significant QTL at 15q22–23. SNP correlation with gene-expression analyses indicated that RORA, NARG2, and ADAM10 jointly influence GM thickness and WM–FA values.

White matter hyperintensities on MRI in high-altitude U-2 pilots

Objective: To demonstrate that U-2 pilot occupational exposure to hypobaria leads to increased incidence of white matter hyperintensities (WMH) with a more uniform distribution throughout the brain irrespective of clinical neurologic decompression sickness history. Methods: We evaluated imaging findings in 102 U-2 pilots and 91 controls matched for age, health, and education levels. Three-dimensional, T2-weighted, high-resolution (1-mm isotropic) imaging data were collected using fluid-attenuated inversion recovery sequence on a 3-tesla MRI scanner. Whole-brain and regional WMH volume and number were compared between groups using a 2-tailed Wilcoxon rank sum test. Results: U-2 pilots demonstrated an increase in volume (394%; p = 0.004) and number (295%; p < 0.001) of WMH. Analysis of regional distribution demonstrated WMH more uniformly distributed throughout the brain in U-2 pilots compared with mainly frontal distribution in controls. Conclusion: Pilots with occupational exposure to hypobaria showed a significant increase in WMH lesion volume and number. Unlike the healthy controls with predominantly WMH in the frontal white matter, WMH in pilots were more uniformly distributed throughout the brain. This is consistent with our hypothesized pattern of damage produced by interaction between microemboli and cerebral tissue, leading to thrombosis, coagulation, inflammation, and/or activation of innate immune response, although further studies will be necessary to clarify the pathologic mechanisms responsible.

Elevated Levels of Plasma Phenylalanine in Schizophrenia: A Guanosine Triphosphate Cyclohydrolase-1 Metabolic Pathway Abnormality?

Background Phenylalanine and tyrosine are precursor amino acids required for the synthesis of dopamine, the main neurotransmitter implicated in the neurobiology of schizophrenia. Inflammation, increasingly implicated in schizophrenia, can impair the function of the enzyme Phenylalanine hydroxylase (PAH; which catalyzes the conversion of phenylalanine to tyrosine) and thus lead to elevated phenylalanine levels and reduced tyrosine levels. This study aimed to compare phenylalanine, tyrosine, and their ratio (a proxy for PAH function) in a relatively large sample of schizophrenia patients and healthy controls. Methods We measured non-fasting plasma phenylalanine and tyrosine in 950 schizophrenia patients and 1000 healthy controls. We carried out multivariate analyses to compare log transformed phenylalanine, tyrosine, and phenylalanine:tyrosine ratio between patients and controls. Results Compared to controls, schizophrenia patients had higher phenylalanine (p<0.0001) and phenylalanine: tyrosine ratio (p<0.0001) but tyrosine did not differ between the two groups (p = 0.596). Conclusions Elevated phenylalanine and phenylalanine:tyrosine ratio in the blood of schizophrenia patients have to be replicated in longitudinal studies. The results may relate to an abnormal PAH function in schizophrenia that could become a target for novel preventative and interventional approaches.

Lower neurocognitive function in U-2 pilots: Relationship to white matter hyperintensities

Objective: Determine whether United States Air Force (USAF) U-2 pilots (U2Ps) with occupational exposure to repeated hypobaria had lower neurocognitive performance compared to pilots without repeated hypobaric exposure and whether U2P neurocognitive performance correlated with white matter hyperintensity (WMH) burden. Methods: We collected Multidimensional Aptitude Battery–II (MAB-II) and MicroCog: Assessment of Cognitive Functioning (MicroCog) neurocognitive data on USAF U2Ps with a history of repeated occupational exposure to hypobaria and compared these with control data collected from USAF pilots (AFPs) without repeated hypobaric exposure (U2Ps/AFPs MAB-II 87/83; MicroCog 93/80). Additional comparisons were performed between U2Ps with high vs low WMH burden. Results: U2Ps with repeated hypobaric exposure had significantly lower scores than control pilots on reasoning/calculation (U2Ps/AFPs 99.4/106.5), memory (105.5/110.9), information processing accuracy (102.1/105.8), and general cognitive functioning (103.5/108.5). In addition, U2Ps with high whole-brain WMH count showed significantly lower scores on reasoning/calculation (high/low 96.8/104.1), memory (102.9/110.2), general cognitive functioning (101.5/107.2), and general cognitive proficiency (103.6/108.8) than U2Ps with low WMH burden (high/low WMH mean volume 0.213/0.003 cm3 and mean count 14.2/0.4). Conclusion: In these otherwise healthy, highly functioning individuals, pilots with occupational exposure to repeated hypobaria demonstrated lower neurocognitive performance, albeit demonstrable on only some tests, than pilots without repeated exposure. Furthermore, within the U2P population, higher WMH burden was associated with lower neurocognitive test performance. Hypobaric exposure may be a risk factor for subtle changes in neurocognition.

Integration of routine QA data into mega-analysis may improve quality and sensitivity of multisite diffusion tensor imaging studies

A novel mega‐analytical approach that reduced methodological variance was evaluated using a multisite diffusion tensor imaging (DTI) fractional anisotropy (FA) data by comparing white matter integrity in people with schizophrenia to controls. Methodological variance was reduced through regression of variance captured from quality assurance (QA) and by using Marchenko–Pastur Principal Component Analysis (MP‐PCA) denoising. N = 192 (119 patients/73 controls) data sets were collected at three sites equipped with 3T MRI systems: GE MR750, GE HDx, and Siemens Trio. DTI protocol included five b = 0 and 60 diffusion‐sensitized gradient directions (b = 1,000 s/mm2). In‐house DTI QA protocol data was acquired weekly using a uniform phantom; factor analysis was used to distil into two orthogonal QA factors related to: SNR and FA. They were used as site‐specific covariates to perform mega‐analytic data aggregation. The effect size of patient‐control differences was compared to these reported by the enhancing neuro imaging genetics meta‐analysis (ENIGMA) consortium before and after regressing QA variance. Impact of MP‐PCA filtering was evaluated likewise. QA‐factors explained ∼3–4% variance in the whole‐brain average FA values per site. Regression of QA factors improved the effect size of schizophrenia on whole brain average FA values—from Cohens d = .53 to .57—and improved the agreement between the regional pattern of FA differences observed in this study versus ENIGMA from r = .54 to .70. Application of MP‐PCA‐denoising further improved the agreement to r = .81. Regression of methodological variances captured by routine QA and advanced denoising that led to a better agreement with a large mega‐analytic study.

High-sensitivity and spatial resolution transient magnetic and electric field probes for transcranial magnetic stimulator characterizations

ABSTRACT Transcranial magnetic stimulation (TMS) is widely used for noninvasive brain stimulation. However, existing TMS tools cannot deliver targeted neural stimulation to deep brain regions, even though many important neurological disorders originate from there. To design TMS tools capable of delivering deep and focused stimulation, we have developed both electric and magnetic field probes to evaluate and improve new designs and calibrate products. Previous works related to magnetic field measurement had no detailed description of probe design or optimization. In this work, we demonstrated a magnetic field probe made of a cylindrical inductor and an electrical field probe modified from Rogowski coil structure. Both have much smaller size and higher directivity than commercial dipole probes. Using probe, we can calibrate and monitor any new types of TMS coil or array design and verify measured results with the other probe. We mathematically analyze their characteristics and performance and obtained a two-dimensional vector plot of the induced electric field, which matched the measured results from the second type of probe. A commercial circular coil and a figure-8 coil, with relatively complex vector field distribution, were used as examples to demonstrate the high-resolution and accurate measurement capability of our probes.

Sensor probes and phantoms for advanced transcranial magnetic stimulation system developments

Transcranial magnetic stimulation (TMS) has become one of the most widely used noninvasive method for brain tissue stimulation and has been used as a treatment tool for various neurological and psychiatric disorders including migraine, stroke, Parkinsons disease, dystonia, tinnitus and depression. In the process of developing advanced TMS deep brain stimulation tools, we need first to develop field measurement devices like sensory probes and brain phantoms, which can be used to calibrate the TMS systems. Currently there are commercially available DC magnetic or electric filed measurement sensors, but there is no instrument to measure transient fields. In our study, we used a commercial figure-8 shaped TMS coil to generate transient magnetic field and followed induced field and current. The coil was driven by power amplified signal from a pulse generator with tunable pulse rate, amplitude, and duration. In order to obtain a 3D plot of induced vector electric field, many types of probes were designed to detect single component of electric-field vectors along x, y and z axis in the space around TMS coil. We found that resistor probes has an optimized signal-to-noise ratio (SNR) near 3k ohm but it signal output is too weak compared with other techniques. We also found that inductor probes can have very high output for Curl E measurement, but it is not the E-field distribution we are interested in. Probes with electrical wire wrapped around iron coil can directly measure induced E-field with high sensitivity, which matched computer simulation results.

Deep Learning for Quality Control of Subcortical Brain 3D Shape Models

We present several deep learning models for assessing the morphometric fidelity of deep grey matter region models extracted from brain MRI. We test three different convolutional neural net architectures (VGGNet, ResNet and Inception) over 2D maps of geometric features. Further, we present a novel geometry feature augmentation technique based on parametric spherical mapping. Finally, we present an approach for model decision visualization, allowing human raters to see the areas of subcortical shapes most likely to be deemed of failing quality by the machine. Our training data is comprised of 5200 subjects from the ENIGMA Schizophrenia MRI cohorts, and our test dataset contains 1500 subjects from the ENIGMA Major Depressive Disorder cohorts. Our final models reduce human rater time by 46-70%. ResNet outperforms VGGNet and Inception for all of our predictive tasks.

12.4 BRAIN LACTATE IS RELATED TO COGNITION IN SCHIZOPHRENIA

Abstract Laura Rowland, University of Maryland School of Med: Bioenergetic function may be altered in schizophrenia as supported by post-mortem, preclinical, cerebrospinal fluid, and 31P-magnetic resonance spectroscopy (MRS) research. Impairments in bioenergetic function may lead to cognitive and functional dysfunction, characteristics of the illness. First, a 7T MRS study that tested the hypothesis that frontal lactate concentrations are elevated in schizophrenia and related to cognitive impairments will be presented. Second, recent advances in brain lactate measurements with 3T MRS will be presented. Methods Twenty-nine controls and 27 participants with schizophrenia completed the study. MRS scanning was conducted on a Philips ‘Achieva’ 7T scanner, and spectra were acquired from a frontal voxel using STEAM (TE/TM/TR=14/33/3000 ms, 128 NEX, 16 NEX water). Participants completed the MATRICS Consensus Cognitive Battery (MCCB) for cognitive function and UCSD Performance-Based Skills Assessment (UPSA) for functional capacity. The relationships between lactate, MCCB, and UPSA were examined. 3T MRS test-retest measures of lactate were conducted on a Siemens Prisma scanner using spectra editing (TE/TR=140/3, editing pulse at 4.1ppm with 30Hz bandwidth, 360 NEX, 16 NEX water). Results Patients had significantly higher lactate compared to controls (p = 0.045). Higher lactate was associated with poorer general cognitive function (r=-0.36, p=0.01) Visual learning, processing speed, and reasoning/problem solving cognitive domains showed the strongest relationships with lactate. Poorer functional capacity (r=-0.43, p=0.001) was also related to higher lactate. 3T spectral editing studies showed excellent reproducibility with a mean coefficient of variation of 4%. Discussion Higher frontal lactate levels in schizophrenia support the hypothesis that brain bioenergetics are altered and related to cognitive and functional impairments in schizophrenia. Higher lactate could be due to inefficient aerobic metabolism causing a shift towards anaerobic metabolism or poor utilization of lactate. Lactate measurements are doable at 3T field strength and may be a useful biomarker of cognition in schizophrenia. Interventions to promote efficient mitochondrial energy metabolism may prove useful for enhancing cognition and alleviating functional impairments in schizophrenia.

Electroencephalograph (EEG) study on self-contemplating image formation

Electroencephalography (EEG) is one of the most widely used electrophysiological monitoring methods and plays a significant role in studies of human brain electrical activities. Default mode network (DMN), is a functional connection of brain regions that are activated while subjects are not in task positive state or not focused on the outside world. In this study, EEG was used for human brain signals recording while all subjects were asked to sit down quietly on a chair with eyes closed and thinking about some parts of their own body, such as left and right hands, left and right ears, lips, nose, and the images of faces that they were familiar with as well as doing some simple mathematical calculation. The time is marker when the image is formed in the subject’s mind. By analyzing brain activity maps 300ms right before the time marked instant for each of the 4 wave bands, Delta, Theta, Alpha and Beta waves. We found that for most EEG datasets during this 300ms, Delta wave activity would mostly locate at the frontal lobe or the visual cortex, and the change and movement of activities are slow. Theta wave activity tended to rotate along the edge of cortex either clockwise or counterclockwise. Beta wave behaved like inquiry types of oscillations between any two regions spread over the cortex. Alpha wave activity looks like a mix of the Theta and Beta activities but more close to Theta activity. From the observation we feel that Beta and high Alpha are playing utility role for information inquiry. Theta and low Alpha are likely playing the role of binding and imagination formation in DMN operations.