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Roberson, E. D.

Publications and source records attributed to Roberson, E. D..

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Genome sequencing for early-onset dementia: high diagnostic yield and frequent observation of multiple contributory alleles

We assessed the utility of genome sequencing for early-onset dementia. Participants were selected from a memory disorders clinic. Genome sequencing was performed along with C9orf72 repeat expansion testing. All returned sequencing results were Sanger validated clinically. Prior clinical diagnoses included Alzheimers disease, frontotemporal dementia, and unspecified dementia. The mean age-of-onset was 54 (41-76). 50% of patients had a strong family history, 37.5% had some, and 12.5% had no known family history. Nine of 32 patients (28%) had a variant defined as pathogenic or likely pathogenic (P/LP) by American College of Medical Genetics standards, including variants in APP, C9orf72, CSF1R, and MAPT. Nine patients (including three with P/LP variants) harbored established risk alleles with moderate penetrance (odds ratios of about 2-5) in ABCA7, AKAP9, GBA, PLD3, SORL1, and TREM2. All six patients harboring these moderate penetrance variants but not P/LP variants also had one or two APOE {varepsilon}4 alleles. One patient had two APOE {varepsilon}4 alleles with no other established contributors. In total, 16 patients (50%) harbored one or more genetic variants likely to explain symptoms. We identified variants of uncertain significance (VUSs) in ABI3, ADAM10, ARSA, GRID2IP, MME, NOTCH3, PLCD1, PSEN1, TM2D3, TNK1, TTC3, and VPS13C, also often along with other variants. In summary, genome sequencing for early-onset dementia demonstrated high utility, with particular advantages where targeted testing may fail such as atypical variant-disease associations or presence of multiple moderate impact alleles. One or more established contributory alleles is often present in early-onset dementia, supporting an oligogenic model.

neuroscience

Biomarker Localization, Analysis, Visualization, Extraction, and Registration (BLAzER) Workflow for Research and Clinical Brain PET Applications

ObjectiveThere is a need for tools enabling efficient evaluation of amyloid- and tau-PET images suited for both clinical and research settings. The purpose of this study was to assess and validate a semi-automated imaging workflow, called Biomarker Localization, Analysis, Visualization, Extraction, and Registration (BLAzER). We tested BLAzER using two different segmentation platforms, FreeSurfer (FS) and Neuroreader (NR), for regional brain PET quantification in images from participants in the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset.\n\nMethods127 amyloid-PET and 55 tau-PET studies along with corresponding volumetric MRI were obtained from ADNI. The BLAzER workflow utilizes segmentation of MR images by FS or NR, then visualizes and quantifies regional brain PET data using FDA-cleared software (MIM), enabling quality control to ensure optimal registration and detect segmentation errors.\n\nResultsBLAzER analysis required only [~]5 min plus segmentation time. BLAzER using FS segmentation showed strong agreement with ADNI for global amyloid-PET standardized uptake value ratios (SUVRs) (r = 0.9922, p < 0.001) and regional tau-PET SUVRs across all Braak staging regions (r > 0.97, p < 0.001) with high inter-operator reproducibility for both (ICC > 0.97) and nearly identical dichotomization as amyloid-positive or -negative (2 discrepant cases out of 127). Comparing FS vs. NR segmentation with BLAzER, the global SUVRs were strongly correlated for global amyloid-PET (r = 0.9841, p < 0.001), but were systematically higher (4% on average) with NR, likely due to more inclusion of white matter, which has high florbetapir binding.\n\nConclusionsBLAzER provides an efficient workflow for regional brain PET quantification. FDA-cleared components and the ability to visualize registration reduce barriers between research and clinical applications.

neuroscience