Pattern Of Neurodegeneration Research Articles

Mapping Medial Temporal Lobe Longitudinal Change in Preclinical Alzheimer’s Disease

AbstractBackgroundThe medial temporal lobe (MTL) is a site of early tau pathology and neurodegeneration in AD. In recent work [1], we reported that rates of change in MTL subregion volumes on longitudinal structural T1‐MRI differ significantly between cognitively unimpaired individuals with and without amyloid pathology (A+CU vs A‐CU), suggesting that these measures are effective biomarkers for tracking disease progression in preclinical AD. Here, we develop a specialized pipeline that quantifies pointwise longitudinal change across the MTL, revealing more informative spatial patterns of early neurodegeneration than summary volumetric longitudinal measures.MethodOur pipeline, SkelDBM, combines skeletonization and deformation‐based morphometry to generate maps of annualized rate of atrophy on the skeleton of an MTL template (Figure 1). SkelDBM samples subjects’ atrophy maps along the skeleton of an MTL template, increasing robustness to subject‐to‐template registration errors. We evaluate SkelDBM using a subset of ADNI data studied in [1] (Table 1). Two preclinical AD groups (A+CU and tau‐positive A+CU) are compared to a control group (A‐CU) using general linear models (GLM) with age as nuisance covariate; permutation testing is used to derive statistically significant clusters.ResultThe full A+CU vs A‐CU comparison shows significant differences in rates of change in right anterior hippocampus, right entorhinal cortex, right transentorhinal cortex, and left posterior hippocampus (Figure 2). Limiting the A+CU group to tau‐positive individuals yields more widespread differences, including most of the right anterior MTL cortex and both hippocampi. These patterns align with volumetric longitudinal data reported in [1] but provide a richer characterization of spatial atrophy patterns.ConclusionSkelDBM is sensitive to longitudinal atrophy occurring over relatively short periods (∼2 years) in preclinical AD and characterizes patterns of atrophy more comprehensively than summary volumetric measures. Summary measures are also subject to biases, since larger structures are typically associated with less measurement error and hence may show exaggerated statistical effects compared to smaller structures even when the underlying neurodegeneration rates are the same. Regional maps of longitudinal change may be more robust to this bias and may help discovery of “signature regions” associated with specific pathological drivers of neurodegeneration. [1] Xie et al., Human Brain Mapping, 2020.

AD Biological Domains—an evolving computational resource for big data classification in AD from the TREAT‐AD Consortium

AbstractBackgroundAlzheimer’s disease (AD) is a highly heterogenous disease with a multitude of subtypes and interacting biological systems emerging in a complex pattern of pathology, neurodegeneration and cognitive decline. In order to help organize large scale data analysis in AD in an unbiased manner, we developed a computational model of endophenotypes associated with AD. We call these models the AD Biological Domains.MethodThe Common Alzheimer’s Disease Research Ontology (CADRO) was leveraged in association with literature mining to identify 19 parent endophenotypes that are largely sufficient to cover AD related pathology. These endophenotypes are instantiated as large sets of manually curated gene ontology (GO) terms and linked genes. This framework enables researchers to unambiguously move from an identified gene to a larger disease‐associated biological phenotype.ResultWe defined 19 biological domains in terms of constitutive sets of GO terms. A gene‐set enrichment analysis has confirmed that these 19 biological domains cover almost all AD‐enriched GO terms, barring those that fall outside the reach of the biological domains due to lack of specificity in biological implication. The size of the biological domains ranges from over a thousand GO terms for ‘Proteostasis’ and ‘Synapse’, and just over a dozen for the terms ‘APP Metabolism’ and ‘Tau homeostasis’. There is a low level of cross‐domain utilization of common GO terms, as the biological domains are effectively siloed in their definition, however, at the level of gene annotation we see high levels of promiscuity across domains, potentially providing a molecular trail to find interdependencies between domains. These biological domains are currently being used across several NIA‐funded consortia, including TREAT‐AD, AMP‐AD, MODEL‐AD, and have been adopted by partnered resources such as the AD‐Atlas and Agora. The full list of biological domains and associated GO terms and genes are openly accessible through the AD Knowledge Portal.ConclusionThe biological domains are an open resource designed to provide a community driven definition of discrete areas of AD biology, allowing AD investigators to utilize a standard set of computationally accessible resources to define emerging transcriptomic and proteomic datasets in a unified manner, making cross study comparisons more informative.

AD Biological Domains—an evolving computational resource for big data classification in AD from the TREAT‐AD Consortium

AbstractBackgroundAlzheimer’s disease (AD) is a highly heterogenous disease with a multitude of subtypes and interacting biological systems emerging in a complex pattern of pathology, neurodegeneration and cognitive decline. In order to help organize large scale data analysis in AD in an unbiased manner, we developed a computational model of endophenotypes associated with AD. We call these models the AD Biological Domains.MethodThe Common Alzheimer’s Disease Research Ontology (CADRO) was leveraged in association with literature mining to identify 19 parent endophenotypes that are largely sufficient to cover AD related pathology. These endophenotypes are instantiated as large sets of manually curated gene ontology (GO) terms and linked genes. This framework enables researchers to unambiguously move from an identified gene to a larger disease‐associated biological phenotype.ResultWe defined 19 biological domains in terms of constitutive sets of GO terms. A gene‐set enrichment analysis has confirmed that these 19 biological domains cover almost all AD‐enriched GO terms, barring those that fall outside the reach of the biological domains due to lack of specificity in biological implication. The size of the biological domains ranges from over a thousand GO terms for ‘Proteostasis’ and ‘Synapse’, and just over a dozen for the terms ‘APP Metabolism’ and ‘Tau homeostasis’. There is a low level of cross‐domain utilization of common GO terms, as the biological domains are effectively siloed in their definition, however, at the level of gene annotation we see high levels of promiscuity across domains, potentially providing a molecular trail to find interdependencies between domains. These biological domains are currently being used across several NIA‐funded consortia, including TREAT‐AD, AMP‐AD, MODEL‐AD, and have been adopted by partnered resources such as the AD‐Atlas and Agora. The full list of biological domains and associated GO terms and genes are openly accessible through the AD Knowledge Portal.ConclusionThe biological domains are an open resource designed to provide a community driven definition of discrete areas of AD biology, allowing AD investigators to utilize a standard set of computationally accessible resources to define emerging transcriptomic and proteomic datasets in a unified manner, making cross study comparisons more informative.

Mapping Medial Temporal Lobe Longitudinal Change in Preclinical Alzheimer’s Disease

AbstractBackgroundThe medial temporal lobe (MTL) is a site of early tau pathology and neurodegeneration in AD. In recent work [1], we reported that rates of change in MTL subregion volumes on longitudinal structural T1‐MRI differ significantly between cognitively unimpaired individuals with and without amyloid pathology (A+CU vs A‐CU), suggesting that these measures are effective biomarkers for tracking disease progression in preclinical AD. Here, we develop a specialized pipeline that quantifies pointwise longitudinal change across the MTL, revealing more informative spatial patterns of early neurodegeneration than summary volumetric longitudinal measures.MethodsOur pipeline, SkelDBM, combines skeletonization and deformation‐based morphometry to generate maps of annualized rate of atrophy on the skeleton of an MTL template (Figure 1). SkelDBM samples subjects’ atrophy maps along the skeleton of an MTL template, increasing robustness to subject‐to‐template registration errors. We evaluate SkelDBM using a subset of ADNI data studied in [1] (Table 1). Two preclinical AD groups (A+CU and tau‐positive A+CU) are compared to a control group (A‐CU) using general linear models (GLM) with age as nuisance covariate; permutation testing is used to derive statistically significant clusters.ResultsThe full A+CU vs A‐CU comparison shows significant differences in rates of change in right anterior hippocampus, right entorhinal cortex, right transentorhinal cortex, and left posterior hippocampus (Figure 2). Limiting the A+CU group to tau‐positive individuals yields more widespread differences, including most of the right anterior MTL cortex and both hippocampi. These patterns align with volumetric longitudinal data reported in [1] but provide a richer characterization of spatial atrophy patterns.ConclusionSkelDBM is sensitive to longitudinal atrophy occurring over relatively short periods (∼2 years) in preclinical AD and characterizes patterns of atrophy more comprehensively than summary volumetric measures. Summary measures are also subject to biases, since larger structures are typically associated with less measurement error and hence may show exaggerated statistical effects compared to smaller structures even when the underlying neurodegeneration rates are the same. Regional maps of longitudinal change may be more robust to this bias and may help discovery of “signature regions” associated with specific pathological drivers of neurodegeneration.[1] Xie et al., Human Brain Mapping, 2020.

Anatomical characterization of pT217‐tau in aged rhesus macaque association cortices: Relevance for trans‐synaptic propagation in sporadic Alzheimer’s Disease

AbstractBackgroundTau pathology in Alzheimer’s Disease (AD) targets higher cortical circuits, with evidence that phosphorylated tau propagates from the entorhinal cortex (ERC) to “seed” pathology throughout the neuronal network affecting the dorsolateral prefrontal cortex (dlPFC) with advanced neurodegeneration. Recent discoveries indicate that phosphorylated tau (pT217‐tau) can be captured in CSF and plasma as an early biomarker of ensuing disease. However, the role of pT217‐tau in brain tau pathology is unknown, especially as soluble tau species are dephosphorylated postmortem in humans. Rhesus macaques naturally develop the same qualitative pattern and sequence of tau and amyloid pathology, with neurofibrillary tangles comprised of paired helical filaments, identical to human AD. Perfusion fixed monkey tissue preserves phosphorylation state and allows imaging of molecular location and interactions with nanometer resolution not possible in humans due to postmortem degradation. The current study examined the ultrastructural localization of pT217‐tau in ERC and dlPFC of the aged rhesus macaques, focusing on potential evidence of propagation between neurons, and exposure to the extracellular space.MethodWe used immunohistochemistry paired with high spatial‐resolution immunoelectron microscopy (immunoEM) in aged rhesus macaques (18‐33 years) to localize pT217‐tau in ERC layer II, which show the earliest signatures of tau pathology in AD and dlPFC layer III critical for working memory.ResultpT217‐tau immunolabeling was predominantly observed in postsynaptic compartments and accumulated on the calcium‐storing smooth endoplasmic reticulum spine apparatus near axospinous asymmetric glutamatergic synapses in dendritic spines. We observed extensive, trans‐synaptic pT217‐tau trafficking between interconnected neurons within omega‐shaped bodies and endosomes, specifically near excitatory, but not inhibitory synapses. Within dendritic shafts, pT217‐tau aggregated on microtubules often in concordance with autophagic vacuoles indicative of neurite dystrophy.ConclusionpT217‐tau accumulates in ERC and dlPFC subcompartments known to be the earliest to show pathology in humans. The data provide the first evidence of pT217‐tau trafficking between neurons to “seed” tau pathology in higher brain circuits, potentially interfacing with the extracellular space to become readily accessible and captured in CSF and blood as a robust AD biomarker. Illuminating patterns of neurodegeneration with pT217‐tau could potentially guide earlier intervention of therapeutics that might mitigate tau hyperphosphorylation in AD.

Does texture analysis classify semantic dementia from Alzheimer’s disease better than volumetric analysis?

AbstractBackgroundTexture analysis may capture subtle changes in the gray matter more sensitively than volumetric analysis. We aimed to investigate the patterns of neurodegeneration in semantic dementia (SD) and Alzheimer’s disease (AD) by comparing the temporal gray matter texture and volume between cognitively normal controls and older adults with SD and AD.MethodWe enrolled all participants from three national university hospitals in Korea. We obtained T1‐weighted magnetic resonance images and compared the gray matter texture and volume of regions of interest (ROIs) between the groups using analysis of variance with Bonferroni posthoc comparisons. We also developed models for classifying SD, AD and control groups using logistic regression analyses, and validated the models using receiver operator characteristics analysis.ResultCompared to the AD group, the SD group showed lower volumes in five ROIs (bilateral temporal poles, and the left inferior, middle, and superior temporal cortices) and higher texture in these five ROIs and two additional ROIs (right inferior temporal and left entorhinal cortices). The performances of both texture‐ and volume‐based models were good and comparable in classifying SD from NC (mean area under the curve [AUC] = 0.914 for texture; mean AUC = 0.894 for volume). However, only the texture‐based model achieved a good level of performance in classifying SD and AD (mean AUC = 0.775 for texture; mean AUC = 0.658 for volume).ConclusionTexture may be a useful neuroimaging marker for early detection of SD in older adults and its differentiation from AD.

Developing Topics.

Apathy, defined as a lack of motivation towards goal-directed behavior, is a common neuropsychiatric symptom in Alzheimer's (AD) and Parkinson's (PD) disease. However, the mechanism underlying apathy is still unclear. Studies have postulated that the degeneration of frontal cortical and subcortical structures may play a major role in the mechanism of apathy. This study investigates whether associations between degeneration in structural and functional connectivity between frontal and subcortical regions contributes to the development of apathetic behavior and whether these associations differ by diseases. Forty-four patients, 8 with AD, 14 amnestic mild cognitive impairment (aMCI), and 22 PD, received MRI brain scans, a decision-making behavioral task, cognitive and psychosocial assessments including the dimensional apathy scale (DAS). We quantified functional connectivity and white matter tract integrity for a set of frontal and subcortical regions of interest, and examined the associations among fronto-subcortical connectivity, behavioral measures, and the DAS. These associations were tested for patient group interactions. Combining AD and aMCI into one patient group, the AD/aMCI group showed worse apathy than PD in terms of the total, the executive, and the behavioral/cognitive subscores (see Table 1), while the DAS emotional subscore was not different between the two groups. For the decision-making task, the proportion of trial acceptance was similar between the groups, but AD/aMCI had slower decision latency than PD. Group interaction with brain measures was observed in the association between DAS total score and the functional connectivity between the right pars triangularis in the inferior frontal gyrus and the caudate (See Figure 1; interaction effect: beta = -.367, p = .0422 FDR corrected). The white matter tract connecting the right pars triangularis to subcortical regions also showed a group interaction with DAS total score but at an uncorrected statistical level (Figure 2; beta = 3.61, p = .0454, uncorrected). Our preliminary analyses exposed phenotypic differences in apathy profiles and decision-making behavior between AD and PD. Furthermore, the observed functional and structural neurodegenerative changes associated with higher apathy severity may also differ between the two diseases. Future analyses in a larger cohort will examine distinct neurodegeneration patterns between the two diseases.

Data‐driven comparison of neurodegeneration patterns between autosomal dominant and sporadic late‐onset Alzheimer’s disease

AbstractBackgroundAutosomal dominant Alzheimer’s disease (ADAD) and sporadic late‐onset AD (LOAD) have similar biomarker profiles, supporting a shared pathophysiology. While both ADAD and LOAD are known to be heterogeneous, there are few studies that have compared the heterogeneity of neurodegeneration as indexed by volumetric MRI in LOAD to that of ADAD. Here we apply a data‐driven model of brain atrophy subtypes from LOAD to characterize atrophy within ADAD.MethodWe used cross‐sectional MRI from ADNI (LOAD) and the Estudio de la Enfermaded de Alzheimer en Jalisciences (EEAJ; ADAD). We used 13 cortical and subcortical Freesurfer‐based regions from 1,912 ADNI participants to train a Subtype and Stage Inference (SuStaIn) model of brain atrophy progression within LOAD. We built a three‐subtype model and applied it to subtype and stage 61 EEAJ participants: 47 carriers of the A431E mutation in PSEN1 and 14 carriers of the V717I mutation in APP. To harmonize the two datasets, we removed the effects of age, sex, education years, ICV and study (ADNI vs. EEAJ flag) from each regional volumetric biomarker prior to analysis. We retained 47 of the 61 EEAJ participants with an estimate SuStaIn stage greater than zero (in any subtype) for subsequent analyses.ResultThe progression patterns for each of the three data‐driven brain atrophy subtypes (typical, cortical, subcortical) are presented in Figures 1 A‐C. These are consistent with previous findings in LOAD. We found no difference in the percentage of participants in each subtype between LOAD, ADAD‐PSEN1 and ADAD‐APP groups (χ2 = 1.5, p = 0.84; Figure 1D). Within ADAD, those assigned the typical subtype had a slightly lower average stage of progression than those in the other two subtypes (t = ‐2.0, p = 0.049; Figure 2A). The triangle plot shows the probability of subtype membership is mostly clustered around the typical and cortical subtypes (Figure 2B), while the estimated stages increase dramatically after disease onset, as expected (Figure 2C).ConclusionWe found a comparable distribution of LOAD‐based atrophy subtypes within both the PSEN1 and APP carriers groups in ADAD, showing that heterogeneous neurodegeneration is another commonality between ADAD and LOAD.

52 Open Access, Normative Morphometric Software Indicate Neurodegeneration Associated with Episodic Memory Dysfunction in Amnestic MCI

Objective:Neurodegeneration in Alzheimer’s disease (AD) is typically assessed through brain MRI, and proprietary software can provide normative quantification of regional atrophy. However, proprietary software can be cost-prohibitive for research settings. Thus, we used the freely available software NOrmative Morphometry Image Statistics (NOMIS) which generates normative z-scores of segmented T1-weighted images from FreeSurfer to determine if these scores replicate established patterns of neurodegeneration in the context of amnestic mild cognitive impairment (aMCI), and whether these measures correlate with episodic memory test performance.Participants and Methods:Patients with aMCI (n = 25) and cognitively normal controls (CN; n = 74) completed brain MRI and two neuropsychological tests of episodic memory (the Rey Auditory Verbal Learning Test and the Wechsler Logical Memory Tests I & II), from which a single composite of normed scores was computed. A subset returned for follow-up (aMCI n = 11, CN n = 52) after ∼15 months and completed the same procedures. T1-weighted images were segmented using FreeSurfer v6.0 and the outputs were submitted to NOMIS to generate normative morphometric estimates for AD-relevant regions (i.e., hippocampus, parahippocampus, entorhinal cortex, amygdala) and control regions (i.e., cuneus, lingual gyrus, pericalcarine gyrus), controlling for age, sex, head size, scanner manufacturer, and field strength. Baseline data were used to test for differences in ROI volumes and memory between groups and to assess the within-group associations between ROI volumes and memory performance. We also evaluated changes in ROI volumes and memory over the follow-up interval by testing the main effects of time, group, and the group X time interactions. Lastly, we tested whether change in volume was associated with declines in memory.Results:At baseline, the aMCI group performed 2 SD below the CN group on episodic memory and exhibited smaller volumes in all AD-relevant regions (volumes 0.4 - 1.2 SD below CN group, ps < .041). There were no group differences in control region volumes. Memory performance was associated with volumes of the AD-relevant regions in the aMCI group (average rho = .51) but not with control regions. ROI volumes were not associated with memory in the CN group. At follow-up, the aMCI group continued to perform 2 SD below the CN group on episodic memory tests; however, change of performance over time did not differ between groups. The aMCI group continued to exhibit smaller volumes in all AD-relevant regions than the CN group, with greater declines in hippocampal volume (17% annual decline vs. 8% annual decline) and entorhinal volume (54% annual decline vs. 5% annual decline). There was a trending Group X Time interaction such that decrease in hippocampal volume was marginally associated with decline in memory for the aMCI group but not the CN group.Conclusions:Normative morphometric values generated from freely available software demonstrated expected patterns of group differences in AD-related volumes and associations with memory. Significant effects were localized to AD-relevant brain regions and only occurred in the aMCI group. These findings support the validity of these free tools as reliable and cost-effective alternatives to proprietary software.

Astrocyte Reactivity and Neurodegeneration in the Female Rat Brain Following Alcohol Dependence.

Recent evidence suggests that alcohol use disorder (AUD) may manifest itself differently in women compared to men. Women experience AUDs on an accelerated timeline and may have certain regional vulnerabilities. In male rats, neuronal cell death and astrocyte reactivity are noted following induction of alcohol dependence in an animal model of an AUD. However, the regional and temporal patterns of neurodegeneration and astrocyte reactivity have yet to be fully examined in females using this model. Therefore, adult female rats were exposed to a 4-day binge model of alcohol dependence followed by different periods of abstinence. Histological markers for FluoroJade B, a label of degenerating neurons, and vimentin, a marker for reactive astrocytes, were utilized. The expression of these markers in cortical and limbic regions was quantified immediately after their last dose (e.g., T0), or 2, 7, and 14days later. Significant neuronal cell death was noted in the entorhinal cortex and the hippocampus, similar to previous reports in males, but also in several cortical regions not previously observed. Vimentin immunoreactivity was noted in the same regions as previously reported, in addition to three novel regions. Vimentin immunoreactivity also occurred at earlier and later time points in some cortical and hippocampal regions. These data suggest that both neuronal cell death and astrocyte reactivity could be more widespread in females compared to males. Therefore, this study provides a framework for specific regions and time points which should be examined in future studies of alcohol-induced damage that include female rats.

Edaravone Improves Streptozotocin-Induced Memory Impairment via Alleviation of Behavioral Dysfunction, Oxidative Stress, Inflammation, and Histopathological Parameters.

Alzheimer's disease (AD), as the main cause of dementia, has a progressive and neurodegenerative pattern with number of cases increasing over the next decades. Therefore, discovering an effective treatment with the ability to invert memory impairment and pathophysiological events of AD seems to be required. The present study performed to investigate the probable effects of Edaravone (EDV) in AD-like disorder induced by intracerebroventricular streptozotocin (ICV-STZ) administration in mice. This study also compares the two different methods of ICV-STZ in the memory impairment induction. NMRI male mice were administrated with 3 mg/kg of STZ for two times during 48 hours span, and after 24 hours, animals were treated with EDV (5 and 10 mg/kg), Donepezil, and Memantine for 14 days. After behavioral tests regarding memory and cognitive function, animals were sacrificed, and the hippocampi were utilized for further analyses. Our results demonstrated that administration of STZ induced memory impairment in the Morris water maze (MWM) test and decreased the discriminative factor in novel object recognition (NOR). The biochemical output shows a significant decrease in ferric reducing antioxidant power (FRAP) and glutathione (GSH) levels followed by increase in malondialdehyde (MDA) and protein carbonylation (PCO) levels. The output showed no difference between the patterns of AD-like disorder induction. Following our treatment groups, administration of EDV (5 and 10 mg/kg), Donepezil, and Memantine significantly improved memory performance and discriminatory behavior. Aforementioned treatments managed to improve FRAP and GSH content of hippocampus, while significantly attenuating MDA, PCO, and nitric oxide overproduction. In addition, no significant difference has been observed between the effect of 5 and 10 mg/kg EDV application. It was supposed that EDV managed to ameliorate memory dysfunction, discriminatory behavior, oxidative stress, and cellular antioxidant power in a dose-independent pattern in mice.

Grey matter volume and CSF biomarkers predict neuropsychological subtypes of MCI

There is increasing evidence of different subtypes of individuals with mild cognitive impairment (MCI). An important line of research is whether neuropsychologically-defined subtypes have distinct patterns of neurodegeneration and cerebrospinal fluid (CSF) biomarker composition. In our study, we demonstrated that MCI participants of the ADNI database (N = 640) can be discriminated into 3 coherent neuropsychological subgroups. Our clustering approach revealed amnestic MCI, mixed MCI, and cluster-derived normal subgroups. Furthermore, classification modeling revealed that specific predictive features can be used to differentiate amnestic and mixed MCI from cognitively normal (CN) controls: CSF Aβ142 concentration for the former and CSF Aβ1–42 concentration, tau concentration as well as grey matter atrophy (especially in the temporal and occipital lobes) for the latter. In contrast, participants from the cluster-derived normal subgroup exhibited an identical profile to CN controls in terms of cognitive performance, brain structure, and CSF biomarker levels. Our comprehensive data analytics strategy provides further evidence that multimodal neuropsychological subtyping is both clinically and neurobiologically meaningful.

Prolonged exposure to high fluoride levels during adolescence to adulthood elicits molecular, morphological, and functional impairments in the hippocampus

Fluoride is added to water due to its anticariogenic activity. However, due to its natural presence in soils and reservoirs at high levels, it could be a potential environmental toxicant. This study investigated whether prolonged exposure to fluoride from adolescence to adulthood—at concentrations commonly found in artificially fluoridated water and in fluorosis endemic areas—is associated with memory and learning impairments in mice, and assessed the molecular and morphological aspects involved. For this endeavor, 21-days-old mice received 10 or 50 mg/L of fluoride in drinking water for 60 days and the results indicated that the increased plasma fluoride bioavailability was associated with the triggering of short- and long-term memory impairments after high F concentration levels. These changes were associated with modulation of the hippocampal proteomic profile, especially of proteins related to synaptic communication, and a neurodegenerative pattern in the CA3 and DG. From a translational perspective, our data provide evidence of potential molecular targets of fluoride neurotoxicity in the hippocampus at levels much higher than that in artificially fluoridated water and reinforce the safety of exposure to low concentrations of fluoride. In conclusion, prolonged exposure to the optimum fluoride level of artificially fluoridated water was not associated with cognitive impairments, while a higher concentration associated with fluorosis triggered memory and learning deficits, associated with a neuronal density reduction in the hippocampus.

Spatiotemporal profile of atrophy in the first year following moderate-severe traumatic brain injury.

Traumatic brain injury (TBI) triggers progressive neurodegeneration resulting in brain atrophy that continues months-to-years following injury. However, a comprehensive characterization of the spatial and temporal evolution of TBI-related brain atrophy remains incomplete. Utilizing a sensitive and unbiased morphometry analysis pipeline optimized for detecting longitudinal changes, we analyzed a sample consisting of 37 individuals with moderate-severe TBI who had primarily high-velocity and high-impact injury mechanisms. They were scanned up to three times during the first year after injury (3 months, 6 months, and 12 months post-injury) and compared with 33 demographically matched controls who were scanned once. Individuals with TBI already showed cortical thinning in frontal and temporal regions and reduced volume in the bilateral thalami at 3 months post-injury. Longitudinally, only a subset of cortical regions in the parietal and occipital lobes showed continued atrophy from 3 to 12 months post-injury. Additionally, cortical white matter volume and nearly all deep gray matter structures exhibited progressive atrophy over this period. Finally, we found that disproportionate atrophy of cortex along sulci relative to gyri, an emerging morphometric marker of chronic TBI, was present as early as 3 month post-injury. In parallel, neurocognitive functioning largely recovered during this period despite this pervasive atrophy. Our findings demonstrate msTBI results in characteristic progressive neurodegeneration patterns that are divergent across regions and scale with the severity of injury. Future clinical research using atrophy during the first year of TBI as a biomarker of neurodegeneration should consider the spatiotemporal profile of atrophy described in this study.

Molecular patterns of neurodegeneration in coronavirus infection caused by SARS-CoV-2

BACKGROUND: The reports on the neurological and psychiatric consequences of coronavirus infection are of particular relevance owing to their limited availability. The molecular patterns of nerve tissue damage are an important task for understanding the underlying mechanisms of neurodegeneration.
 AIM: To study the dynamics of changes in the content of markers of neurodegeneration and neuroplasticity in patients with coronavirus infection in the acute and long-term periods.
 MATERIALS AND METHODS: A total of 200 patients aged 5183 years were assessed and categorized into two age groups: 5165 years and 6683 years. The levels of neurodegeneration markers were determined in the blood serum: neurofilament heavy chains (NEFH), S100 A6 protein, S100 B protein, -amyloid 1-42 (A1-42), microfilament associated tau protein (MAPt), serum amyloid P (SAP), and neuroplasticity: neurotrophin 3 (NT3), neurotrophin 4 (NT4). The study was performed thrice in the acute period of the disease at the time of admission to the hospital and at 6 and 12 months after discharge.
 RESULTS: In the first group of patients, in the acute period of coronavirus infection, women showed higher concentrations of S100 A6 (3.20.2), S100 B (0.40.06), NT3 (1.10.1), and MAPt (0.130.02), while the values for the men were NEFH (0.150.03), A1-42 (2.10.1), and SAP (4.50.06). In the long-term, a general tendency of long persistence of high levels of the markers of neurodegeneration and neuroprotection was noted in young men compared to women, indicating a long period of rehabilitation. After 12 months, the level of calcium-binding proteins S100 A6 and S100 B in men was 1.50.2 pg/mL and 0.30.04 ng/mL, which was 1.10.1 pg/mL and 0.20.04 ng/mL, respectively, in women. The level of SAP in men during the long-term period after 12 months was 4.30.1 versus 3.90.2 ng/mL in women, indicating a significant difference.
 Analyses of the results for the patients in the second group indicated a higher level of S100 A6 and A1-42 in the acute period for women, while men showed higher levels of S100 B, NT3, and SAP.
 CONCLUSION: The changes in patients with coronavirus infection both in the acute and late periods indicated active neurodegeneration processes in different age groups, which manifested as a result of an increase in the concentration of specific proteins in the blood serum.

Applying Joint Graph Embedding to Study Alzheimer's Neurodegeneration Patterns in Volumetric Data.

Neurodegeneration measured through volumetry in MRI is recognized as a potential Alzheimer's Disease (AD) biomarker, but its utility is limited by lack of specificity. Quantifying spatial patterns of neurodegeneration on a whole brain scale rather than locally may help address this. In this work, we turn to network based analyses and extend a graph embedding algorithm to study morphometric connectivity from volume-change correlations measured with structural MRI on the timescale of years. We model our data with the multiple random eigengraphs framework, as well as modify and implement a multigraph embedding algorithm proposed earlier to estimate a low dimensional embedding of the networks. Our version of the algorithm guarantees meaningful finite-sample results and estimates maximum likelihood edge probabilities from population-specific network modes and subject-specific loadings. Furthermore, we propose and implement a novel statistical testing procedure to analyze group differences after accounting for confounders and locate significant structures during AD neurodegeneration. Family-wise error rate is controlled at 5% using permutation testing on the maximum statistic. We show that results from our analysis reveal networks dominated by known structures associated to AD neurodegeneration, indicating the framework has promise for studying AD. Furthermore, we find network-structure tuples that are not found with traditional methods in the field.

Predicting cortical thickness with [18F]flortaucipir PET: A longitudinal MRI study

AbstractBackgroundThe association between tau pathology and neurodegeneration (atrophy) in Alzheimer’s disease (AD) is not fully understood. This study aimed to investigate whether tau pathology is associated with concurrent and longitudinal cortical thickness in individuals along the AD continuum.MethodWe included 92 amyloid‐positive cognitively impaired individuals (age 65±7, 48% female, MMSE 23±4) with AD dementia (n = 73) or mild cognitive impairment due to AD (MCI, n = 19) and 61 cognitively normal individuals (CN; age 66±8, 48% female, MMSE 29±1) with subjective cognitive decline (SCD, n = 55, 19 amyloid‐positive) or healthy controls (HC, n = 6, amyloid‐status unknown). All participants underwent dynamic [18F]flortaucipir PET and structural 3T‐MRI at baseline. A subset underwent two‐year follow‐up structural 3T‐MRI (CN: n = 35, time‐interval 24±8 months; AD: n = 26; time‐interval 28±4 months). Parametric [18F]flortaucipir binding potential (BPND) images were generated using receptor parametric mapping (cerebellar gray matter reference region) to quantify tau pathology. Cortical thickness (over time) was measured using Freesurfer (version 6.0.1). Regional associations between [18F]flortaucipir BPND and cortical thickness were assessed using linear mixed models in three commonly used a priori defined regions‐of‐interest, including entorhinal, middle‐and inferior temporal, and neocortical areas. Models were adjusted for age, sex and amyloid status (in case of CN individuals).ResultFor cognitively impaired individuals, higher [18F]flortaucipir BPND (in all three regions) was associated with lower concurrent cortical thickness in the entorhinal cortex [Table‐1&Fig‐1]. Higher middle‐ and inferior temporal and neocortical BPND was associated with cortical thinning over time within the same region (intra‐regionally). Higher middle‐ and inferior temporal BPND additionally showed associations with cortical thinning over time in the neocortex (inter‐regionally). For cognitively normal individuals, we found no associations between [18F]flortaucipir BPND and cortical thickness (over time) [Table‐1&Figure‐1].ConclusionTau pathology is associated with both concurrent and longitudinal atrophy in a region‐specific manner in cognitively impaired individuals (MCI/AD), but not in cognitively normal individuals (HC/SCD). The regional‐specificity of these associations might suggest that there are similarities between tau‐related progression patterns and patterns of neurodegeneration. Taking into account a temporal delay between the development of region‐specific tau pathology and neurodegeneration, this potentially suggests that tau pathology is a (partial) driver of neurodegeneration in AD.

Reactive astrocytes as imaged with 11C‐DED in patients with different dementia disorders

AbstractBackgroundNeuroinflammation, which receives ever increasing interest in neurodegenerative diseases, comprises a heterogeneous cascade of events that are thought to be related to the downstream neurodegeneration. The aim of this study was to evaluate the binding of 11C‐Deuterium‐L‐Deprenyl PET (DED) as a measure of reactive astrocytes in patients with different dementia disorders, and to assess its association with other disease biomarkers.MethodEleven patients with a clinical diagnosis of semantic variant of primary progressive aphasia (svPPA, n = 5) and behavioral variant of frontotemporal dementia (bvFTD, n = 6) were recruited. All patients had a cerebrospinal fluid biomarker profile that was inconsistent with Alzheimer’s disease (AD) or a negative amyloid‐β PET scan. The imaging protocol included 11C‐DED‐PET, 18F‐FDG‐PET, and a 3D T1 MRI. A group of amyloid‐beta positive patients with AD (n = 20) that underwent similar investigations were used for comparison. Z‐scores were created for 11C‐DED binding (Patlak slopes) and tracer relative delivery (R1 parameter) relative to that of healthy controls (HC; n = 20), for assessing the load of reactive astrocytes and cerebral perfusion, respectively.ResultThe patients with svPPA and bvFTD showed significantly higher 11C‐DED binding in frontotemporal areas, compared to HC. Patients with AD showed significantly higher 11C‐DED binding in temporo‐occipital areas, compared to HC. The regional distribution of 11C‐DED binding in the patients with svPPA and bvFTD was consistent with the expected underlying pattern of neurodegeneration in those disorders, although the load of binding was heterogeneous across patients with the same clinical diagnosis.ConclusionReactive astrocytes appear to be a common feature of different dementia disorders, although the regional pattern of reactivity differs. Ongoing work evaluates the relationship between patterns of reactive astrocyte activation, cerebral perfusion, glucose metabolism, atrophy, and cognitive performance.

Clinical Profiles and Patterns of Neurodegeneration in Amyotrophic Lateral Sclerosis: A Cluster-Based Approach Based on MR Imaging Metrics.

The previous studies described phenotype-associated imaging findings in amyotrophic lateral sclerosis (ALS) with a prior categorization of patients based on clinical characteristics. We investigated the natural segregation of patients through a radiologic cluster-based approach without a priori patient categorization using 3 well-known prognostic MR imaging biomarkers in ALS, namely bilateral precentral and paracentral gyrus cortical thickness and medulla oblongata volume. We aimed to identify clinical/prognostic features that are cluster-associated. Bilateral precentral and paracentral gyri and medulla oblongata volume were calculated using FreeSurfer in 90 patients with amyotrophic lateral sclerosis and 25 healthy controls. A 2-step cluster analysis was performed using precentral and paracentral gyri (averaged pair-wise) and medulla oblongata volume. We identified 3 radiologic clusters: 28 (31%) patients belonged to "cluster-1"; 51 (57%), to "cluster 2"; and 11 (12%), to "cluster 3." Patients in cluster 1 showed statistically significant cortical thinning of the analyzed cortical areas and lower medulla oblongata volume compared with subjects in cluster 2 and cluster 3, respectively. Patients in cluster 3 exhibited significant cortical thinning of both paracentral and precentral gyri versus those in cluster 2, and this latter cluster showed lower medulla oblongata volume than cluster 3. Patients in cluster 1 were characterized by older age, higher female prevalence, greater disease severity, higher progression rate, and lower survival compared with patients in clusters 2 and 3. Patients with amyotrophic lateral sclerosis spontaneously segregate according to age and sex-specific patterns of neurodegeneration. Some patients with amyotrophic lateral sclerosis showed an early higher impairment of cortical motor neurons with relative sparing of bulbar motor neurons (cluster 3), while others expressed an opposite pattern (cluster 2). Moreover, 31% of patients showed an early simultaneous impairment of cortical and bulbar motor neurons (cluster 1), and they were characterized by higher disease severity and lower survival.

Distinct patterns of neurodegeneration after TBI and in Alzheimer's disease.

Traumatic brain injury (TBI) is a dementia risk factor, with Alzheimer's disease (AD) more common following injury. Patterns of neurodegeneration produced by TBI can be compared to AD and aging using volumetric MRI. A total of 55 patients after moderate to severe TBI (median age 40), 45 with AD (median age 69), and 61 healthy volunteers underwent magnetic resonance imaging over 2 years. Atrophy patterns were compared. AD patients had markedly lower baseline volumes. TBI was associated with increased white matter (WM) atrophy, particularly involving corticospinal tracts and callosum, whereas AD rates were increased across white and gray matter (GM). Subcortical WM loss was shared in AD/TBI, but deep WM atrophy was TBI-specific and cortical atrophy AD-specific. Post-TBI atrophy patterns were distinct from aging, which resembled AD. Post-traumatic neurodegeneration 1.9-4.0 years (median) following moderate-severe TBI is distinct from aging/AD, predominantly involving central WM. This likely reflects distributions of axonal injury, a neurodegeneration trigger. We compared patterns of brain atrophy longitudinally after moderate to severe TBI in late-onset AD and healthy aging. Patients after TBI had abnormal brain atrophy involving the corpus callosum and other WM tracts, including corticospinal tracts, in a pattern that was specific and distinct from AD and aging. This pattern is reminiscent of axonal injury following TBI, and atrophy rates were predicted by the extent of axonal injury on diffusion tensor imaging, supporting a relationship between early axonal damage and chronic neurodegeneration.