Ertekin‐Taner, Nilüfer

AbstractObjectiveTo assess the relationships between MRI volumetry and [18F]flortaucipir PET of typical and atypical clinical phenotypes of Alzheimer’s disease, by genarian (age by decade).MethodsFive‐hundred and sixty‐four participants including those with typical (n = 86) or atypical (n = 80) Alzheimer’s dementia and normal controls (n = 398) underwent apolipoprotein E genotyping, MRI, flortaucipir, and 11C‐PiB; all 166 Alzheimer’s participants were beta‐amyloid positive and all controls were beta‐amyloid negative. Grey matter volume and flortaucipir standard uptake value ratios were calculated for hippocampus, entorhinal cortex, and neocortex. Ratios of hippocampal‐to‐neocortical and entorhinal‐to‐neocortical volume and flortaucipir uptake were also calculated. Linear regression models assessed relationships among regional volume, flortaucipir uptake, and ratios and phenotypes, within three genarians (50–59, 60–69, and 70+). Voxel‐level analyses were also performed.ResultsFor 50–59 greater medial temporal atrophy and flortaucipir uptake was observed in the typical compared with atypical phenotype. The typical phenotype also showed greater frontal neocortex uptake with the voxel‐level analysis. For 60–69 and 70+ there was greater hippocampal volume loss in the typical compared with atypical phenotype while only the 60–69, but not the 70+ group, showed a difference in hippocampal flortaucipir uptake. We also observed a pattern for higher neocortical flortaucipir uptake to correlate with younger age decade for both phenotypes.InterpretationMRI volumetry versus flortaucipir PET relationships differ across Alzheimer’s clinical phenotypes, and also within phenotype across age decades. This suggests that there is potential risk of masked effects by not accounting for genarian in participants with beta‐amyloid and tau‐positive biomarker defined Alzheimer’s disease.

Abstract OBJECTIVE Our goal is to identify new pathways perturbed in and which may lead to GRS. METHODS We collected brain transcriptome levels from healthy controls (n=5), patients with GRS (n=9), glioma without seizures (non-GRS, n=8), and idiopathic temporal lobe epilepsy (iTLE, n=7) using Illumina-based poly-A capture high-throughput RNA sequencing approach. Differential gene expression analysis was conducted to ascertain expression differences between the four groups. We identified molecular pathways enriched for differentially expressed genes (DEG) using Ingenuity Pathway Analysis. DEGs were defined as those with log2 fold change ≥ 2 and q-value < 0.01 when compared to GRS. RESULTS Principal component analysis revealed that diagnostic grouping was the main determinant of the transcriptome variance. We identified 212 DEGs in the GRS vs. non-GRS analysis. Among these, 108 genes were up-regulated and 104 genes were down-regulated. Among the genes that were down‐regulated, there was significant enrichment for those involved in acute phase response signaling and immune cell trafficking (e.g. H19, BMP5, CXCL8). Compared to iTLE samples, there were 1015 DEGs in the GRS samples. Among these 877 genes were up-regulated and 138 genes were down-regulated. There was significant enrichment for genes involved in cell-to-cell signaling among those that were either uniquely up‐regulated (e.g. NRK, RGS10, SLC4A4, and SELPLG) or down‐regulated in the GRS samples (e.g. SLC9A3 –Na+/H+ exchanger; SLC5A5-sodium-glucose co-transporter family). Further, two of the most down-regulated genes in samples with GRS, SCLC17A6- vesicular glutamate transporter 2 and FOSB, have previously been shown to be involved in glutamatergic transmission. CONCLUSIONS Our findings suggest that inflammation-related processes and alterations in cell-to cell signaling may underlie the pathogenesis of GRS. Our results also provide support for perturbations in glutamatergic transmission in GRS. Our findings require replication in larger human cohorts and functional experiments to explore the function of the genes perturbed in GRS.