Neurodegenerative Alzheimer Research Articles

Anti-Hypertensive Drugs Moderate the Relationship of Blood Pressure with Alzheimer's Pathologies and Neurodegenerative Markers in Non-Demented Hypertensive Older Adults.

We aimed to explore whether the relationships of blood pressures (BPs) with Alzheimer's disease (AD) endophenotypes varied by usage of antihypertensive drugs (AHDs). A total of 765 non-demented older adults (mean age: 74.4 years; female: 43.1%) with a self-reported history of hypertension were followed for 6 years. Multiple linear regression and linear-mixed effect models were used to investigate the interaction effects of five categories of AHDs (angiotensin-converting enzyme inhibitors [ACEI], angiotensin II receptor blockers [ARBs], β-blocker, calcium channel blockers [CCB], diuretic) with BPs (systolic blood pressure [SBP], diastolic blood pressure [DBP], and pulse pressure [PP]) on AD core pathology and neurodegenerative markers. After Bonferroni correction, significant interaction effects of BPs with AHDs were observed. Elevated SBP or PP in late-life was associated with higher levels of cerebral Aβ burden (diuretic alone/β-blocker × SBP), higher levels of CSF tau proteins (diuretic × SBP/PP, ARBs/CCB × SBP), and lower volume of entorhinal region (β-blocker × SBP, diuretic × PP) only among hypertensive patients who received no anti-hypertensive treatments, while these associations became compromised or null for users of specific AHDs except for ACEI. Compared to taking other classes of AHDs, elevated SBP in late-life was associated with lower cerebral Aβ burden in diuretic users (padjusted = 0.08) and was associated with higher CSF tau proteins in ACEI alone users (padjusted = 0.03). Longitudinal data validated the above-mentioned interaction effects on changes of cerebral Aβ burden (padjusted < 0.05), CSF tau proteins (padjusted < 0.10), and brain atrophy (padjusted < 0.05). The relationships of late-life BP with AD pathology and neurodegeneration could be modified by anti-hypertensive treatments and varied by AHD classification. These findings provide preliminary evidence for tailored BP management strategy for preventing AD among late-life hypertensive adults.

ALZHEIMER DISEASE: WHAT’S NEW, WHAT’S TRUE?

Alzheimer’s Disease (AD) is a devastating disorder estimated to affect 55 million individuals worldwide with 6.2 million cases in the US. AD is a significant clinical problem and numbers are only expected to increase. Alzheimer’s disease is characterized by structural changes in the brain including abnormal amyloid beta (Aβ) and neurofibrillary tau aggregation, neuroinflammation, and neuronal death. There is no effective treatment for AD and AD-related dementia (ADRD). For decades, the hypothesis that brain deposition of the amyloid-beta (Aβ) peptide initiates AD has dominated research and clinical trials. However, the FDA- approved antibody treatments targeting Aβ have yet to show convincing evidence for slowing the progression of disease symptomatology3, including no benefit to women and ApoE4 carriers over a period of 1.5 years4. Treatment failures can be attributed, at least in part, to an incomplete understanding of the pathogenic mechanisms of AD, which underscores the urgent need to examine alternative pathogenic mechanisms and therapeutic targets for AD. AD has been increasingly recognized as a multifactorial and heterogeneous disease with multiple contributors to its pathophysiology, where neuroinflammation is considered one of the cardinal features of AD. Traditionally, the pathways of Aβ production and neuroinflammation have been considered independently; however, recent studies suggest that these processes may converge to promote the pathology associated with AD. Surmounting evidence supports chronic dysregulation in inflammatory and immune pathways as drivers of AD neurodegeneration and provides insights into possible microbial mechanisms involved in the onset and progression of AD. Mounting evidence implicates gut microbiome dysbiosis in AD, even at the preclinical/asymptomatic and prodromal stages of the disease. Links have been made between the gut microbiome and established biomarkers of AD, including Aß, ApoE status, and tau. Further, links between the gut microbiota and brain connectivity, as measured by functional magnetic resonance imaging (fMRI), have recently emerged but are poorly understood in AD. Our research group previously demonstrated cerebrovascular dysfunction in prodromal AD, correlated with cognitive dysfunction. Specifically, reduced cerebral blood flow (CBF) and cerebrovascular reactivity (CVR) are associated with lower cognitive functioning in prodromal AD. Findings from our recent cross-sectional study indicate that pro-inflammatory gut bacteria more abundant in prodromal AD are associated with reduced CBF and CVR and elevated arterial transit time (ATT). Conversely, beneficial gut bacteria, more abundant in normal controls, are associated with better CBF and CVR and shorter ATT. Further, we identified the bile acid and lipid metabolism modifying organism and the oral pathogen (causes gingivitis and periodontal disease), to be differentially abundant in prodromal AD and CU cohorts, respectively. These results are undeniably promising for the future of AD in many ways including novel mechanistic discovery, non-invasive diagnostic testing, and novel treatment targets.

Identifying the joint signature of brain atrophy and gene variant scores in Alzheimer’s Disease

The joint modeling of genetic data and brain imaging information allows for determining the pathophysiological pathways of neurodegenerative diseases such as Alzheimer’s disease (AD). This task has typically been approached using mass-univariate methods that rely on a complete set of Single Nucleotide Polymorphisms (SNPs) to assess their association with selected image-derived phenotypes (IDPs). However, such methods are prone to multiple comparisons bias and, most importantly, fail to account for potential cross-feature interactions, resulting in insufficient detection of significant associations. Ways to overcome these limitations while reducing the number of traits aim at conveying genetic information at the gene level and capturing the integrated genetic effects of a set of genetic variants, rather than looking at each SNP individually. Their associations with brain IDPs are still largely unexplored in the current literature, though they can uncover new potential genetic determinants for brain modulations in the AD continuum. In this work, we explored an explainable multivariate model to analyze the genetic basis of the grey matter modulations, relying on the AD Neuroimaging Initiative (ADNI) phase 3 dataset. Cortical thicknesses and subcortical volumes derived from T1-weighted Magnetic Resonance were considered to describe the imaging phenotypes. At the same time the genetic counterpart was represented by gene variant scores extracted by the Sequence Kernel Association Test (SKAT) filtering model. Moreover, transcriptomic analysis was carried on to assess the expression of the resulting genes in the main brain structures as a form of validation. Results highlighted meaningful genotype–phenotype interactionsas defined by three latent components showing a significant difference in the projection scores between patients and controls. Among the significant associations, the model highlighted EPHX1 and BCAS1 gene variant scores involved in neurodegenerative and myelination processes, hence relevant for AD. In particular, the first was associated with decreased subcortical volumes and the second with decreasedtemporal lobe thickness. Noteworthy, BCAS1 is particularly expressed in the dentate gyrus. Overall, the proposed approach allowed capturing genotype–phenotype interactions in a restricted study cohort that was confirmed by transcriptomic analysis, offering insights into the underlying mechanisms of neurodegeneration in AD in line with previous findings and suggesting new potential disease biomarkers.

Disease- and stage-specific alterations of the oral and fecal microbiota in Alzheimer's disease.

Microbial communities in the intestinal tract are suggested to impact the ethiopathogenesis of Alzheimer's disease (AD). The human microbiome might modulate neuroinflammatory processes and contribute to neurodegeneration in AD. However, the microbial compositions in patients with AD at different stages of the disease are still not fully characterized. We used 16S rRNA analyses to investigate the oral and fecal microbiota in patients with AD and mild cognitive impairment (MCI; n = 84), at-risk individuals (APOE4 carriers; n = 17), and healthy controls (n = 50) and investigated the relationship of microbial communities and disease-specific markers via multivariate- and network-based approaches. We found a slightly decreased diversity in the fecal microbiota of patients with AD (average Chao1 diversity for AD = 212 [SD = 66]; for controls = 215 [SD = 55]) and identified differences in bacterial abundances including Bacteroidetes, Ruminococcus, Sutterella, and Porphyromonadaceae. The diversity in the oral microbiota was increased in patients with AD and at-risk individuals (average Chao1 diversity for AD = 174 [SD = 60], for at-risk group = 195 [SD = 49]). Gram-negative proinflammatory bacteria including Haemophilus, Neisseria, Actinobacillus, and Porphyromonas were dominant oral bacteria in patients with AD and MCI and the abundance correlated with the cerebrospinal fluid biomarker. Taken together, we observed a strong shift in the fecal and the oral communities of patients with AD already prominent in prodromal and, in case of the oral microbiota, in at-risk stages. This indicates stage-dependent alterations in oral and fecal microbiota in AD which may contribute to the pathogenesis via a facilitated intestinal and systemic inflammation leading to neuroinflammation and neurodegeneration.

Affection of Motor Network Regions by Tau Pathology Across the Alzheimer's Disease Spectrum.

Stereotypical isocortical tau protein pathology along the Braak stages has been described as an instigator of neurodegeneration in Alzheimer's disease (AD). Less is known about tau pathology in motor regions, although higher-order motor deficits such as praxis dysfunction are part of the clinical description. Here, we examined how tau pathology in cytoarchitectonically mapped regions of the primary and higher-order motor network in comparison to primary visual and sensory regions varies across the clinical spectrum of AD. We analyzed tau PET scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort in patients with mild cognitive impairment (MCI; N = 84) and dementia of the Alzheimer's disease type (DAD; N = 25). Additionally, an amyloid-negative sample of healthy older individuals (HC; N = 26) were included. Standard uptake ratio values (SUVRs) were extracted in native space from the left and the right hemispheres. A repeated measurement analysis of variance was conducted to assess the effect of diagnostic disease category on tau pathology in the individual motor regions, controlling for age. We observed that tau pathology varies as a function of diagnostic category in predominantly higher motor regions (i.e., supplementary motor area, superior parietal lobe, angular gyrus, and dorsal premotor cortex) compared to primary visual, sensory and motor regions. Indeed, tau in higher-order motor regions was significantly associated with decline in cognitive function. Together, these results expand our knowledge on the in vivo pattern of tau pathology in AD and suggest that higher motor regions are not spared from tau aggregation in the course of disease, potentially contributing to the symptomatic appearance of the disease.

Systems Medicine as a Strategy to Deal with Alzheimer's Disease.

The traits of Alzheimer's disease (AD) include amyloid plaques made of Aβ1-40 and Aβ1-42, and neurofibrillary tangles by the hyperphosphorylation of tau protein. AD is a complex disorder that is heterogenous in genetical, neuropathological, and clinical contexts. Current available therapeutics are unable to cure AD. Systems medicine is a strategy by viewing the body as a whole system, taking into account each individual's unique health profile, provide treatment and associated nursing care clinically for the patient, aiming for precision. Since the onset of AD can lead towards cognitive impairment, it is vital to intervene and diagnose early and prevent further progressive loss of neurons. Moreover, as the individual's brain functions are impaired due to neurodegeneration in AD, it is essential to reconstruct the neurons or brain cells to enable normal brain functions. Although there are different subtypes of AD due to varied pathological lesions, in the majority cases of AD, neurodegeneration and severe brain atrophy develop at the chronic stage. Novel approaches including RNA based gene therapy, stem cell based technology, bioprinting technology, synthetic biology for brain tissue reconstruction are researched in recent decades in the hope to decrease neuroinflammation and restore normal brain function in individuals of AD. Systems medicine include the prevention of disease, diagnosis and treatment by viewing the individual's body as a whole system, along with systems medicine based nursing as a strategy against AD that should be researched further.

Staging Neurodegeneration Across the AD Continuum

AbstractBackgroundWhile amyloid and tau staging are ubiquitous in Alzheimer’s disease (AD), there are no equivalent staging techniques for AD‐related neurodegeneration. Currently, neurodegeneration in AD is commonly assessed with structural MRI measures such as hippocampal volume and cortical thickness. However, recent work suggests that markers for microstructural neurodegeneration derived from diffusion MRI (DWI) may provide crucial additional information related to the onset and progression of AD. Neurite density index (NDI) and return to origin probability (RTOP) are two DWI metrics that have shown promise for characterizing these microstructural alterations.To investigate the utility of DWI for staging neurodegeneration in AD, we implemented logistic regression to compare the abilities of NDI, RTOP, and hippocampal volume to predict AD dementia in 481 late‐middle‐aged participants on the AD continuum.Methods481 participants (383 cognitively unimpaired [CU], 68 Mild Cognitive Impairment [MCI], 30 AD) from the Wisconsin Registry for Alzheimer’s Prevention and the Wisconsin Alzheimer’s Disease Research Center were imaged with T1‐weighted MRI and multi‐shell DWI. After delineating hippocampal volume, average NDI and RTOP values were extracted from the hippocampus and a whole brain white matter skeleton. All measures were fit to a logistic model with age, sex, and scanner as covariates.Corresponding ROC curves were used to derive cutoff values for NDI and RTOP by maximizing the Youden Index.ResultsBox plots and ROC curves are provided in Figures 1‐2 and cutoff values for each DWI metric are provided in Table 1. NDI and RTOP outperformed hippocampal volume in predicting AD across brain regions. The best performing marker was WM NDI (AUC = 0.905), followed closely by WM RTOP (AUC = .878). Meanwhile, hippocampal RTOP (AUC = 0.861) slightly outperformed hippocampal NDI (AUC = 0.844).ConclusionOur work adds to a growing body of literature which suggests that neuroimaging markers of brain microstructure may capture unique signatures of AD progression. Furthermore, the fact that both DWI measures performed best in whole brain WM reinforces WM degeneration as a core feature of AD pathophysiology. Future work will incorporate CSF and PET measures of amyloid and tau to better characterize AD‐specific neurodegeneration.

Microglia‐mediated T cell Infiltration Drives Neurodegeneration in Tauopathy

AbstractBackgroundExtracellular amyloid‐β (Aβ) deposition as neuritic plaques and intracellular accumulation of hyperphosphorylated, aggregated tau as neurofibrillary tangles (NFT) are two of the characteristic hallmarks in Alzheimer’s disease (AD). The regional progression of brain atrophy in AD highly correlates with tau accumulation but not amyloid deposition and the mechanisms of tau‐mediated neurodegeneration are not clear. Innate immune responses represent a common pathway for the initiation and progression of some neurodegenerative diseases. To date, little is known about the extent or role of the adaptive immune response in the presence of Aβ or tau pathology.MethodWe utilized transgenic mice that develop Aβ deposition or tau pathology and neurodegeneration. We isolated all immune cells in the brain followed by single cell RNA sequencing and systematically compared the immunological milieus in the brain of mice with amyloid deposition or tau aggregation and neurodegeneration. Histological, biochemical, and behavioral analyses were also performed to assess the immune response and brain damage in the different mice with or without different treatments.ResultWe found that mice with tauopathy but not amyloid, developed a unique innate and adaptive immune response and that depletion of microglia or T‐cells blocked tau‐mediated neurodegeneration. T cells, especially cytotoxic T cells, were markedly increased in areas with tau pathology in mice with tauopathy and in the AD brain. T cell numbers correlated with the extent of neuronal loss, and dynamically transformed their cellular characteristics from activated to exhausted states along with unique TCR clonal expansion. Inhibition of IFN‐γ and PD‐1 signaling both significantly ameliorated brain atrophy.ConclusionOur results thus reveal a tauopathy and neurodegeneration‐related immune hub involving activated microglia and T cell responses, which could serve as therapeutic targets for preventing neurodegeneration in AD and primary tauopathies.

Spatial transcriptomics identifies disrupted circadian gene expression in a mouse model of Alzheimer’s disease

AbstractBackgroundDisruptions in circadian rhythm are a common symptom of Alzheimer’s disease (AD), which occur early in disease progression and may contribute to the neurodegenerative process. However, the mechanisms that link alterations in rhythmic transcription and disease pathology are poorly understood. Here we used brain‐wide spatial transcriptomics to elucidate progressive disruptions in diurnal transcriptional rhythms in a mouse model of AD.MethodUsing Visium spatial transcriptomic technology, we investigated transcriptional changes with spatiotemporal resolution in APP23 transgenic mice, which overexpress human APP with the Swedish mutation. Sagittal brain slices from APP23 and littermate control mice were collected at 4 Zeitgeber times (ZT). We used community detection to cluster the spatial locations according to shared patterns of gene expression, which corresponded to major anatomical brain regions. Pseudobulk profiles were computed for each cluster in each sample, and these were used in subsequent differential expression analysis using DESeq2. Rhythmic gene expression was modeled as a sinusoidal function of ZT, while controlling for covariates (sex, genotype, and age) and their interaction with time. Results were further validated using non‐parametric tests for rhythmicity implemented in Metacycle.ResultOur analysis revealed a large increase in the number of diurnally rhythmic genes in APP23 mice in several brain structures, including regions affected by neurodegeneration in AD like the hippocampus and the cortex. Additionally, many genes showed increased rhythmicity or altered circadian phase in APP23 mice in specific brain regions, when compared to controls. For example, the expression of Slc5a3, a gene involved in osmotic stress response and deregulated in human AD brains, presented strong circadian rhythms in both APP23 and controls in cortical clusters, but the amplitude of expression was significantly larger in the dentate gyrus only in APP23 mice. Importantly, this effect was observed before and after the onset of amyloid pathology.ConclusionThese data map the changes in rhythmic gene expression over the course of AD progression in the spatiotemporal context of cortical and subcortical brain regions. Our findings elucidate molecular disruptions occurring early in the development of AD, which may drive disease progression.

BrainChart cortical thickness centile scores: a generalizable tool to detect age‐inappropriate cortical neurodegeneration in Alzheimer’s disease

AbstractBackgroundIdentifying age‐inappropriate cortical neurodegeneration on structural MRI is a key component of Alzheimer’s disease (AD) assessment. However, widely available reference standards that enable objective interpretation are lacking. BrainChart (www.BrainChart.io; https://github.com/BrainChart/Lifespan) calculates age and sex adjusted centile scores for structural MRI metrics using normative data from 101,457 participants across the lifecourse and can be applied across different datasets. We applied this approach to regional cortical thickness estimates and explored its utility in identifying patients with AD associated neurodegeneration.MethodsCross‐sectional BrainChart cortical thickness centile scores were calculated for 241 individuals with pathologically confirmed AD (median scan time prior to death 5.8 years), as well as 1432 cognitively normal participants (CN) from the NACC dataset. Area under the receiver operating characteristic curve (AUC) analyses were performed to identify the cortical regions that best identified patients with pathologically confirmed AD. This approach was then applied to 305 participants from the ADNI‐3 cohort, all of whom underwent clinical amyloid (florbetapir) PET and tau (flortaucipir) PET within 6 months of structural MRI (CN = 185; Mild Cognitive Impairment (MCI) = 95); AD = 26).ResultsThe top ten performing regions for differentiating pathologically confirmed AD from CN in the NACC dataset were entorhinal, middle temporal, inferior parietal, isthmus cingulate, fusiform, supramarginal, inferior temporal, superior temporal, precuneus and temporal pole. AUCs ranged from 0.72 – 0.77 (figure 1 and table 1). Combining these ten regions into a single model significantly improved diagnostic separability (AUC = 0.81, figure 1). Optimal cut‐points for individual regions ranged from the 25th centile to the 35th centile, with sensitivities ranging from 57.7% to 68.9%, and specificities ranging from 72.6% to 80.9%. Using progressively lower centile scores increased specificity but decreased sensitivity (table 1).In ADNI‐3 participants, a combined model of the same ten regions derived from the NACC dataset was able to discriminate amyloid and tau pet positive AD patients from amyloid and tau negative CN (AUC = 0.98), as well as amyloid and tau positive MCI patients from amyloid and tau negative CN (AUC = 0.85) (figure 2).ConclusionBrainChart age and sex adjusted cortical thickness centile scores, derived from an extensive normative dataset, represent a generalizable method for objectively identifying cortical neurodegeneration in AD.

BrainChart cortical thickness centile scores: a generalizable tool to detect age‐inappropriate cortical neurodegeneration in Alzheimer’s disease

AbstractBackgroundIdentifying age‐inappropriate cortical neurodegeneration on structural MRI is a key component of Alzheimer’s disease (AD) assessment. However, widely available reference standards that enable objective interpretation are lacking. BrainChart (www.BrainChart.io; https://github.com/BrainChart/Lifespan) calculates age and sex adjusted centile scores for structural MRI metrics using normative data from 101,457 participants across the lifecourse and can be applied across different datasets. We applied this approach to regional cortical thickness estimates and explored its utility in identifying patients with AD associated neurodegeneration.MethodCross‐sectional BrainChart cortical thickness centile scores were calculated for 241 individuals with pathologically confirmed AD (median scan time prior to death 5.8 years), as well as 1432 cognitively normal participants (CN) from the NACC dataset. Area under the receiver operating characteristic curve (AUC) analyses were performed to identify the cortical regions that best identified patients with pathologically confirmed AD. This approach was then applied to 305 participants from the ADNI‐3 cohort, all of whom underwent clinical amyloid (florbetapir) PET and tau (flortaucipir) PET within 6 months of structural MRI (CN = 185; Mild Cognitive Impairment (MCI) = 95); AD = 26).ResultThe top ten performing regions for differentiating pathologically confirmed AD from CN in the NACC dataset were entorhinal, middle temporal, inferior parietal, isthmus cingulate, fusiform, supramarginal, inferior temporal, superior temporal, precuneus and temporal pole. AUCs ranged from 0.72 – 0.77 (figure 1 and table 1). Combining these ten regions into a single model significantly improved diagnostic separability (AUC = 0.81, figure 1). Optimal cut‐points for individual regions ranged from the 25th centile to the 35th centile, with sensitivities ranging from 57.7% to 68.9%, and specificities ranging from 72.6% to 80.9%. Using progressively lower centile scores increased specificity but decreased sensitivity (table 1). In ADNI‐3 participants, a combined model of the same ten regions derived from the NACC dataset was able to discriminate amyloid and tau pet positive AD patients from amyloid and tau negative CN (AUC = 0.98), as well as amyloid and tau positive MCI patients from amyloid and tau negative CN (AUC = 0.85) (figure 2).ConclusionBrainChart age and sex adjusted cortical thickness centile scores, derived from an extensive normative dataset, represent a generalizable method for objectively identifying cortical neurodegeneration in AD.

ApoE and immune system in the pathogenesis of tau‐mediated neurodegeneration

AbstractBackgroundExtracellular amyloid‐β (Aβ) deposition as neuritic plaques and intracellular accumulation of hyperphosphorylated, aggregated tau as neurofibrillary tangles (NFT) are two of the characteristic hallmarks in Alzheimer’s disease (AD). The regional progression of brain atrophy in AD highly correlates with tau accumulation but not amyloid deposition and the mechanisms of tau‐mediated neurodegeneration remain elusive. Innate immune responses represent a common pathway for the initiation and progression of some neurodegenerative diseases. To date, little is known about the extent or role of the adaptive immune response and their interaction with innate immune response in the presence of Aβ or tau pathology.MethodWe systematically compared the immunological milieus in the brain with amyloid deposition or tau aggregation and neurodegeneration.ModelsThree AD mouse models, including Aβ models with amyloid deposition in both parenchyma and along the vessels and tau pathology models; as well as human brain samples with different Braak scores.ResultWe found that mice with tauopathy but not amyloid, developed a unique innate and adaptive immune response and that depletion of microglia or T‐cells blocked tau‐mediated neurodegeneration. T cells, especially cytotoxic T cells, were markedly increased in areas with tau pathology in mice with tauopathy and in the AD brain. T cell numbers correlated with the extent of neuronal loss, and dynamically transformed their cellular characteristics from activated to exhausted states along with unique TCR clonal expansion. Inhibition of IFN‐γ and PD‐1signaling both significantly ameliorated brain atrophy.ConclusionOur results thus reveal a tauopathy and neurodegeneration‐related immune hub involving activated microglia and T cell responses, which could serve as therapeutic targets for preventing neurodegeneration in AD and primary tauopathies.

Basic Science and Pathogenesis - Part 1.

Cerebrovascular alterations and innate immune activation are key features of Alzheimer's disease (AD). However, the mechanisms that link blood-brain barrier disruption to neurodegeneration are poorly understood and well-defined druggable targets at the neurovascular interface are limited. We identified the blood coagulation factor fibrinogen as necessary and sufficient for the induction of pathogenic neuroinflammation in neurologic diseases1. Fibrinogen induces spine elimination and promotes cognitive deficits in AD mouse models mediated by oxidative stress induction in microglia2, 3. Volume imaging in cleared mouse and human AD brains combined with repetitive in vivo two-photon imaging showed focal fibrinogen deposits associated with loss of dendritic spines independent of amyloid plaques. We developed a first-in-class fibrin-targeting immunotherapy to selectively inhibit fibrin-induced inflammation without interfering with its beneficial coagulation effects4. Fibrin-targeting immunotherapy entered the CNS, bound to fibrin, and inhibited amyloid-driven neurotoxicity and neurotoxic inflammatory gene programs in AD mice. Thus, fibrinogen links cerebrovascular damage with immune-mediated neurodegeneration and fibrin therapeutics may have important therapeutic implications inhibiting vascular-driven neurodegeneration in AD and related conditions. 1. Petersen et al., Nat Rev Neurosci. 2018, 19:283-301 2. Merlini et al. Neuron 2019, 101:1099-1108 3. Mendiola et al. Nat Immunol 2020, 21:513-524 4. Ryu et al. Nat Immunol 2018, 19:1212-1223.

Ex vivo identification of transcriptional regulation landscape and potential therapeutic targets against oxidative stress using Alzheimer’s disease patient‐derived dermal fibroblast: findings from BICWALZS cohort

AbstractBackgroundReactive oxygen species (ROS) is considered as a central pathophysiology for neurodegeneration in Alzheimer’s disease (AD). Many studies using in vitro cell line or in vivo mouse model have shown the possible association between ROS defense mechanisms and cellular damage. However, that connection was not elucidated well in AD patient‐derived cell or brain organoids. In this study, we aimed to identify transcriptional regulation landscape and potential therapeutic targets against oxidative stress using AD dementia patient‐derived dermal fibroblastMethodsFor the purposes of ex vivo research, we performed skin biopsy and stabilized dermal fibroblasts in vitro. Total of 20 AD dementia patients and 22 cognitively normal older adults were assessed. All of AD dementia patients were amyloid positive on PET imaging, APOE e4 carrier, and cognition was imparied. On the contrary, all of cognitively normal older adults were amyloid negative on PET imaging, and APOE e4 non‐carrier. We applied H2O2 (600 uM) to dermal fibroblast for 24 hours as an oxidant agent to promote oxidative stress. After that, to identify transcriptional regulation landscape against oxidative stress, RNA sequencing was performed.ResultsTotal of 406 transcripts (up = 61, down = 345) were commonly differentially expressed in both of AD dementia and cognitively normal older adults derived dermal fibroblast by ROS‐H2O2. These transcripts were enriched in GO categories related to cell division, cell cycle, and DNA repair. Interestingly, 133 transcripts (up = 41, down = 92) were only differentially expressed in AD dementia dermal fibroblast by ROS‐H2O2. These transcripts were enriched in GO categories related to DNA duplex unwinding, cell division, and DNA replication. Total of 147 transcripts (up = 67, down = 80) were only differentially expressed in cognitively normal older adults dermal fibroblast by ROS‐H2O2. These transcripts were enriched in GO categories related to negative regulation of cell proliferation, notch signaling pathway, and NMDA glutamate receptor signaling pathway.ConclusionWe identified transcriptional regulation landscape by ROS‐H2O2 in AD dementia and cognitively normal older adults dermal fibroblast. Further bioinformatic analysis with computational tools and validation experiments will be performed to find potential therapeutic targets against oxidative stress.

An exploratory pilot study on diffusion MRI measurement of cortical microstructural neurodegeneration for the assessment of dementia in a Japanese hospital setting

AbstractBackgroundThe use of diffusion MRI (dMRI) to assess cortical microstructure has demonstrated promise for measuring neurodegeneration in Alzheimer’s disease (PMID:33174658, PMID:36281682) and frontotemporal dementia (PMID:32641807, PMID:34686217) using retrospective research datasets. The ultimate translation of research findings to clinical practice requires prospective studies in hospital settings. A pilot study at the National Hospital Organization, Niigata, was designed and successfully delivered.MethodThe study was registered on Oct 5th 2021 (jRCT1032210367). Scanning took place between Oct 13th 2021 and June 30th 2022, on a 1.5T Philips Ingenia. MRI data was transferred using a secure cloud gateway (Cimar). A total of 10 healthy controls (HC), 10 Alzheimer’s disease (AD) patients, and 5 frontotemporal dementia (FTD) patients were recruited.Structural (3D T1‐weighted) and dMRI (2mm isotropic, 32 directions at b = 1000 s/mm2) scans were used to calculate cortical mean diffusivity and three neuropathologically‐inspired cortical diffusivity measures: the angle between the radial minicolumnar direction and the principal diffusion direction (AngleR); the principal diffusion component parallel with the minicolumns (ParlPD), and the diffusion components perpendicular to the minicolumns (PerpPD+). Metrics were also summarized over AD signature regions (Ridgway et al., CTAD 2022).ResultOf the n = 25 cases, 18 had clear clinical diagnoses after neurological and radiological assessment, while 7 were more complex (including focal bleeding, focal ischemia, meningioma, supra‐sellar tumour). Characteristics are given in Table 1.Figure 1 plots two whole‐brain measures: PerpPD+ and AngleR. A threshold of PerpPD+ &gt; 1.325 has 100% sensitivity to the 8 clear AD cases, with 86% specificity for 7 controls vs AD. Results were less clear for FTD using whole‐brain measures alone.The Cohen’s d effect size for clear AD versus clear HC was 2.82 using whole‐brain PerpPD+. Using signature regions (Figure 2b) improved separation to d = 3.08 for PerpPD+, compared to d = 1.87 for the cortical thickness signature (Figure 2a).ConclusionThe pilot study demonstrated practical feasibility and good performance for distinguishing AD from HC using cortical diffusivity measures acquired at the 1.5T field‐strength common in hospitals in Japan. Future work will investigate FTD signature regions. A larger multicentre study assessing diagnostic accuracy using additional AD biomarkers is warranted.

Association between brain [18F]FDG‐PET signal and genetic cell markers in the brain tissue

AbstractBackgroundBrain glucose hypometabolism, indexed by [18F]FDG‐PET, is considered a biomarker of neurodegeneration in Alzheimer’s disease (AD). However, other brain cells, such as astrocytes and microglia, also consume considerable amounts of glucose and may contribute to the [18F]FDG‐PET signal in the brain. Thus, the cellular source of the [18F]FDG‐PET signal remains controversial. Here, we aimed to evaluate whether canonical markers of different brain cell types (neuron, oligodendrocyte, astrocyte, and microglia) associate with brain [18F]FDG‐PET signal in humans and a rat model of human amyloidosis.Method[18F]FDG‐PET images were acquired in ten‐month‐old APP/PS1 (TgF344‐AD, n = 8) and wild‐type (WT, n = 6) rats. Next, we evaluated the gene expression of NeuN, Olig2, GFAP, S100B, and IBA1 in the frontal and temporoparietal cortices and cerebellum. Association maps integrating mRNA with brain [18F]FDG‐PET signal were conducted at the voxel level using RMINC. [18F]FDG‐PET and brain tissue mRNA (GFAP, ACSA2, S100B, GLAST, IBA1, CSF1R, TREM2, Olig2, Cldn11, NeuN) of cognitively unimpaired patients were obtained from ADNI and Allen Brain Atlas database, respectively. In humans, mean regional [18F]FDG‐PET SUVr (reference region: pons) and mRNA expression were used to evaluate their association using a gaussian model. Differences were considered statistically significant at p&lt;0.05 (t&gt;2).ResultGFAP and S100B mRNA levels in the temporoparietal and frontal cortices positively correlated with brain [18F]FDG‐PET signal (local maxima, GFAPt(13) = 9.4, S100Bt(13) = 6.6; Fig1B‐C). No associations were found with TREM2, Olig2 and NeuN (t(13)&lt;2; Fig1D‐F). We expanded our analysis by comparing gene astrocyte markers and astrocyte gene cell markers in humans. At the regional level, we found that FDG‐PET SUVr and astrocyte mRNA were positively associated: S100B (R‐squared = 0.34), GFAP (R‐squared = 0.33), GLAST (R‐squared = 0.31) and ACSA‐2 (R‐squared = 0.31; Fig1G).ConclusionOur findings suggest astrocyte mRNA markers are more closely associated with brain [18F]FDG‐PET signal than neuronal, oligodendrocyte, and microglial mRNA markers.

Volume of contrast‐based Substantia Nigra segmentation is decreased in dementia patients compared to healthy controls

AbstractBackgroundThe substantia nigra (SN) is susceptible to neurodegeneration in Alzheimer’s disease. Automatic segmentation of the SN using MRI permits in vivo morphological assessment of the SN in cohort studies. Here we evaluate the multi‐brain segmentation (MB, Brudfors, 2020) to learn a probabilistic tissue prior of the SN using neuromelanin‐sensitive MRI while systematically studying effects of (A) SN tissue contrast; and (B) volumetric differences between healthy subjects and memory patients.MethodWe studied 50 3T single‐site T1w FLASH MRI from cognitively healthy older adults from the DZNEDELCODE cohort and a second ageing cohort in Magdeburg and 25 multi‐site diagnosed memory patients (MCI or AD). We quantified local SN signal contrast and image noise as a quality metric (obtained from CAT/SPM toolbox). We learnt tissue priors for each 10, 20, 30 and 50 older adults with the highest SN tissue contrast. For each tissue prior, we obtained model‐based SN tissue segments and calculated (integrated) SN volume. We compared SN volume between tissue prior segmentations and correlated it to age and quality. We coregistered all patients to the N = 50 tissue prior and compared volumetric differences between healthy adults and patients using voxel‐based morphometry (VBM).ResultThe template‐space N = 50 SN prior (in red) was visually larger than all other priors (Fig 1A). Patients visually had a lower SN volume than healthy from N = 50 (Fig 1B). The N = 50 native space SN tissue prior volume was significantly higher than all other tissue prior volumes (p&gt;0.01, Fig 2A). SN volume correlated with quality for N = 50 (p = 0.02, Fig 2B). The N = 50 sample SN contrast (Fig 2C) did not differ between patients and healthy adults. Patients had a decreased volume in a cluster overlapping with the SN (N = 268, pFDR corrected = 0.02 (Fig 2D).ConclusionHere we demonstrate that model‐based learning of a probabilistic SN tissue prior using intensity‐based generative approach to segmentation is feasable in a heterogenous cohort. Additionally, using this prior, we showed that while there is no difference of the SN contrast, there is a significant decrease in SN volume consistent with previous analyses (Krohn et al 2022).

The relationship between [18F]FDG‐PET signal and key‐players of brain glucose metabolism

AbstractBackgroundNeuronal activity is supported by activity‐dependent lactate production from astrocytes, as postulated by the astrocyte–neuron lactate shuttle (ANLS) hypothesis. Indeed, astrocytic glutamate uptake is a main trigger for brain glucose consumption. [18F]fluorodeoxyglucose (FDG)‐PET showing a hypometabolic signature has been used as an index of neurodegeneration in Alzheimer’s disease (AD). In the early stages of the disease, soluble amyloid‐beta (Aβ) has been associated with neuronal hyperactivity due to decreased astrocytic glutamate uptake. It is hypothesized that this phenomenon occurs especially in regions with high ongoing baseline activity. Over time, neurodegeneration and hypometabolism in such regions may contribute to the progress of the AD continuum. Thus, we investigated whether the [18F]FDG‐PET signal in typical hypometabolic regions in AD is associated with the expression of ANLS transporters and enzymes in the healthy brain.MethodGene expression of GLUT1, GLUT3, MCT1, MCT2, MCT4, LDHA, and LDHB (ANLS genes) from postmortem brain tissue of healthy individuals were obtained from the Allen Human Brain Atlas. [18F]FDG‐PET data from cognitively unimpaired individuals were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Pearson correlations were performed between the mean gene expression and the mean [18F]FDG‐PET SUVr across typically hypometabolic brain regions in AD (precuneus, angular and temporal gyri, and parietal and cingulate regions) and non‐vulnerable regions (uncorrected p‐value &lt; 0.05).ResultsThe expression of ANLS genes had a stronger positive correlation with [18F]FDG‐PET SUVr across the AD hypometabolic regions than the non‐vulnerable regions (p &lt; 0.05). Of note, the astrocytic glucose transporter GLUT1 presented a stronger correlation with [18F]FDG‐PET than the neuronal transporter GLUT3 in AD‐vulnerable regions. Figure 1 presents all correlations.ConclusionOur results show that the physiological expression of transporters and enzymes responsible for the brain glucose metabolism correlate more with the [18F]FDG‐PET signal in typical brain regions of the AD hypometabolic signature. This suggests these regions present a higher baseline activity and may be more susceptible to Aβ‐induced hyperactivation in early AD, which could lead to a bioenergetic collapse in later disease stages, as shown in the [18F]FDG‐PET of AD individuals.

Ex vivo identification of transcriptional regulation landscape and potential therapeutic targets against ER stress using Alzheimer’s disease patient‐derived dermal fibroblast: findings from BICWALZS cohort

AbstractBackgroundEndoplasmic reticulum (ER) stress is considered as a central pathophysiology for neurodegeneration in Alzheimer’s disease (AD). Many studies using in vitro cell line or in vivo mouse model have shown the possible association between ER stress and neurodegeneration. However, that connection was not elucidated well in AD patient‐derived cell or brain organoids. In this study, we aimed to identify transcriptional regulation landscape and potential therapeutic targets against ER stress using AD dementia patient‐derived dermal fibroblast.MethodFor the purposes of ex vivo research, we performed skin biopsy and stabilized dermal fibroblasts in vitro. Total of 20 AD dementia patients and 22 cognitively normal older adults were assessed. All of AD dementia patients were amyloid positive on PET imaging, APOE e4 carrier, and cognition was imparied. On the contrary, all of cognitively normal older adults were amyloid negative on PET imaging, and APOE e4 non‐carrier. We applied thabsigargin (10 nM) to dermal fibroblast for 24 hours to promote ER stress. After that, to identify transcriptional regulation landscape against ER stress, RNA sequencing was performed.ResultTotal of 252 transcripts (up = 162, down = 90) were commonly differentially expressed in both of AD dementia and cognitively normal older adults derived dermal fibroblast by ER stress‐thabsigargin. These transcripts were enriched in GO categories related to protein folding in ER, response to ER stress, and ERAD pathway. Interestingly, 80 transcripts (up = 33, down = 47) were only differentially expressed in AD dementia dermal fibroblast by ER stress‐thabsigargin. These transcripts were enriched in GO categories related to cell division, miotic cell cycle, and microtubule‐based movement. Total of 60 transcripts (up = 41, down = 19) were only differentially expressed in cognitively normal older adults dermal fibroblast by ER stress‐thabsigargin. These transcripts were enriched in GO categories related to cholesterol biosynthesis process, DNA replication checkpoint, and cAMP‐mediated signaling.ConclusionWe identified transcriptional regulation landscape by ER stress‐thabsigargin in AD dementia and cognitively normal older adults dermal fibroblast. Further bioinformatic analysis with computational tools and validation experiments will be performed to find potential therapeutic targets against ER stress.

An exploratory pilot study on diffusion MRI measurement of cortical microstructural neurodegeneration for the assessment of dementia in a Japanese hospital setting

AbstractBackgroundThe use of diffusion MRI (dMRI) to assess cortical microstructure has demonstrated promise for measuring neurodegeneration in Alzheimer’s disease (PMID:33174658, PMID:36281682) and frontotemporal dementia (PMID:32641807, PMID:34686217) using retrospective research datasets. The ultimate translation of research findings to clinical practice requires prospective studies in hospital settings. A pilot study at the National Hospital Organization, Niigata, was designed and successfully delivered.MethodThe study was registered on Oct 5th 2021 (jRCT1032210367). Scanning took place between Oct 13th 2021 and June 30th 2022, on a 1.5T Philips Ingenia. MRI data was transferred using a secure cloud gateway (Cimar). A total of 10 healthy controls (HC), 10 Alzheimer’s disease (AD) patients, and 5 frontotemporal dementia (FTD) patients were recruited. Structural (3D T1‐weighted) and dMRI (2mm isotropic, 32 directions at b = 1000 s/mm2) scans were used to calculate cortical mean diffusivity and three neuropathologically‐inspired cortical diffusivity measures: the angle between the radial minicolumnar direction and the principal diffusion direction (AngleR); the principal diffusion component parallel with the minicolumns (ParlPD), and the diffusion components perpendicular to the minicolumns (PerpPD+). Metrics were also summarized over AD signature regions (Ridgway et al., CTAD 2022).ResultOf the n = 25 cases, 18 had clear clinical diagnoses after neurological and radiological assessment, while 7 were more complex (including focal bleeding, focal ischemia, meningioma, supra‐sellar tumour). Characteristics are given in Table 1. Figure 1 plots two whole‐brain measures: PerpPD+ and AngleR. A threshold of PerpPD+ &gt; 1.325 has 100% sensitivity to the 8 clear AD cases, with 86% specificity for 7 controls vs AD. Results were less clear for FTD using whole‐brain measures alone. The Cohen’s d effect size for clear AD versus clear HC was 2.82 using whole‐brain PerpPD+. Using signature regions (Figure 2b) improved separation to d = 3.08 for PerpPD+, compared to d = 1.87 for the cortical thickness signature (Figure 2a).ConclusionThe pilot study demonstrated practical feasibility and good performance for distinguishing AD from HC using cortical diffusivity measures acquired at the 1.5T field‐strength common in hospitals in Japan. Future work will investigate FTD signature regions. A larger multicentre study assessing diagnostic accuracy using additional AD biomarkers is warranted.