Neurodegenerative Alzheimer Research Articles

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+ > 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<0.05 (t>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)<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>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 < 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 < 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+ > 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.

Gray to White Matter Signal Ratio as a novel biomarker of neurodegeneration in Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) is characterized neuropathologically by ß‐amyloid (Aß) plaques, hyperphosphorylated tau neurofibrillary tangles, and neurodegeneration which leads to a phenotypically heterogeneous cognitive‐behavioral dementia syndrome. Our understanding of how these neuropathological and neurodegeneration biomarkers relate to each other is still evolving. A relatively new approach to measuring structural brain change, gray matter to white matter signal intensity ratio (GWR), quantifies the signal contrast between these tissue compartments, and has emerged as a promising marker of AD‐related neurodegeneration. We sought to validate GWR as a novel MRI biomarker of neurodegeneration.MethodTwenty‐nine amyloid‐, tau‐, and neurodegeneration positive patients with atypical syndromes of AD (16 Posterior Cortical Atrophy, 10 logopenic variant of Primary Progressive Aphasia, and 3 Amnestic Dysexecutive phenotype) and 24 amyloid‐negative control participants underwent structural MRI, 11C‐Pittsburgh Compound B (PiB) PET, and 18F‐flortaucipir (FTP) PET scans. Whole‐cortex vertex‐wise general linear models (GLM) were created to identify areas of the cerebral cortex where AD patients showed abnormal signal in each modality, and Pearson’s correlation coefficients were computed to examine the strength of bivariate associations between each pair of modalities at the group level. We then constructed linear mixed‐effects models to test the relative contribution of each non‐FTP modality to explaining the variance in regional FTP uptake.ResultWe found that GWR was associated with cortical thickness, tau PET, and amyloid PET, with GWR showing a larger magnitude of abnormality than cortical thickness. We also found that combining GWR, cortical thickness, and amyloid PET better explained observed tau PET signal than using these modalities alone, suggesting that the three imaging biomarkers contribute independently and synergistically to explaining the variance in the distribution of tau pathology.ConclusionWe conclude that GWR is a uniquely sensitive in vivo marker of neurodegenerative change that reflects pathological mechanisms which may occur prior to cortical atrophy. By using all of these imaging biomarkers of AD together, we may be better able to capture, and possibly predict, AD neuropathologic changes in vivo, which we hope will ultimately contribute to better endpoints to evaluate the efficacy of therapeutic interventions as we move toward an era of disease‐modifying treatments for this devastating disease.

Prognostic value of plasma biomarkers in a clinical trial of mild‐to‐moderate Alzheimer’s Disease

AbstractBackgroundInformative, readily accessible plasma biomarkers of pathology, neuroinflammation, and neurodegeneration in Alzheimer’s disease (AD) could enhance targeted approaches to AD trial design and treatment. In post‐hoc analyses, we examined whether plasma biomarkers (Aβ1‐40, Aβ1‐42, total tau, p‐tau‐181, NfL, and GFAP) predicted 48‐week change in cognitive (ADAS‐Cog11), global function (CDR‐SB), and volumetric MRI (6 cortical regions and 2 whole brain measures) outcomes in T2 Protect AD, a phase‐2 placebo‐controlled RCT of troriluzole in mild‐to‐moderate AD (NCT03605667).MethodAt least one baseline biomarker measurement was available for 319 of 350 trial participants, forming the analytic sample. No significant treatment effects were found in T2 Protect AD (Feldman 2021, JPAD 8(4):s46); thus, treatment arms were pooled for this analysis. Baseline levels of, and 48‐week changes in, plasma biomarkers were assessed for association with 48‐week change in outcomes using linear regression adjusted for relevant covariates. Combinations of baseline plasma biomarkers that best predicted 48‐week decline on the ADAS‐Cog11 and CDR‐SB were identified using LASSO regression. Statistical significance level was 5%; p‐values were Bonferroni corrected for multiple comparisons.ResultParticipant characteristics are presented in Table 1. Higher baseline plasma NfL predicted greater 48‐week decline on ADAS‐Cog11 (p = 0.026) and CDR‐SB (p = 0.048; Fig. 1A). LASSO revealed that the combination of baseline plasma NfL, total tau, and Aβ42/40 ratio best predicted 48‐week decline on ADAS‐Cog11, whereas baseline NfL alone best predicted 48‐week decline on CDR‐SB. Regarding MRI outcomes, baseline NfL predicted increase in ventricular volume (p = 0.018; Fig 1A). Baseline NfL, GFAP, and p‐tau‐181 each predicted 48‐week decline in mid‐temporal cortical volume (all p<0.02; Fig.1B); LASSO results were similar. The only significant association between 48‐week biomarker change and clinical outcomes was between increased plasma NfL and worsening CDR‐SB.ConclusionElevated baseline plasma NfL predicted greater 48‐week decline on cognitive, global function, and MRI measures in a clinical trial of mild‐to‐moderate AD. Furthermore, greater increase in plasma NfL over time was associated with greater clinical decline. Plasma NfL is an easily accessible biomarker that may enhance AD clinical trial design and treatment strategies.Acknowledgement: Trial funding by Biohaven Pharmaceuticals; data and trial coordination by the Alzheimer’s Disease Cooperative Study (ADCS).

Using an ex vivo MRI atlas of the human medial temporal lobe to characterize the 3D distribution of neurofibrillary tangle burden across histologically defined subregions

AbstractBackgroundAccumulation of tau neurofibrillary tangles (NFT) in the medial temporal lobe (MTL) is an early pathological change associated with neurodegeneration in Alzheimer’s Disease (AD). Current understanding of the spread of NFTs within the MTL is based on 2‐D histological sections sampled at sparse locations. Here, using human MTL specimens from donors with diagnoses spanning the AD continuum, we examine 3‐D quantitative maps of NFT burden derived from serial histology leveraging a high‐resolution, ex vivo MRI atlas, thus enabling more granular analyses.MethodWe combined ex vivo MRI scans (0.2×0.2×0.2mm3, 9.4T) of 55 MTL specimens using a customized registration approach to construct a 3‐D atlas (Ravikumar et al., Acta Neuropathol Comm, 2021). MTL subregions in the atlas were labelled based on cytoarchitecture using serial Nissl histology (n = 17) (Fig.1). For 25 specimens with a primary diagnosis of AD or primary age‐related tauopathy (78.6±10.9 years; 16M/9F), quantitative NFT burden maps were derived from serial anti‐tau immunohistochemistry histology and registered to the atlas for group‐level analysis (Yushkevich et al., Brain, 2021). For quantitative comparisons, we computed the mean NFT burden and cortical thickness within each subregion.ResultFig.2A shows average and summary frequency maps of NFT burden, computed separately for specimens with a low Braak stage (Braak0‐II; n = 11) and high Braak stage (BraakIV‐VI), that reveal a clear anterior‐to‐posterior gradient in NFT burden. At low Braak stages, we observe high levels of NFT burden in cornu ammonis (CA)1, entorhinal cortex (EC), and Brodmann area 35 (BA35;≈transentorhinal region), particularly in the outer cortical layers. CA1 and EC also show higher NFT burden relative to BA35 (Fig.2C). At high Braak stages, overall NFT burden is visibly higher and more widespread, with significant increases found across almost all subregions (Fig.2B). Moreover, significant correlations between NFT burden and cortical thinning were found in the perforant pathway (PP; molecular layer of the subiculum), dentate gyrus, EC and Areas TE, TF and TH (Fig.3).ConclusionBuilding on earlier work, we provide a detailed characterization of the distribution of NFT burden in the MTL. Our findings of specific subregional involvement of early NFT pathology can help inform the development of improved in vivo neuroimaging biomarkers

Modulation of the p75 neurotrophin receptor in the PS19 tauopathy mouse model regulates transcription profiles and inter‐cellular communication across multiple populations of non‐neuronal cells

AbstractBackgroundTau pathologies contribute to neurodegeneration in Alzheimer’s Disease (AD) and other disorders via a variety of mechanisms. In tauopathy mouse models, administration of LM11A‐31 (C31), a small molecule modulator of the p75 neurotrophin receptor (p75NTR), reduced tau post‐translational modifications, accumulation of pathological tau species and microglial activation; restored synaptic plasticity, and reversed synaptic spine loss. We examined long‐term dosing with C31 at the single‐cell transcriptional level to further elucidate cell types and cellular mechanisms affected by treatment.MethodTauopathy model tauP301S mice (PS19) and age‐matched wildtype (Wt) mice were dosed by oral gavage with C31 or vehicle once daily for 3 months from 6 months of age, when tau pathology was well established. Whole cortex single‐nucleus RNA‐sequencing was analyzed using Seurat, with automated cell type annotation, followed by manual curation. Additional analyses compared AD‐associated biodomains and risk scored genes from TREAT‐AD with individual cell types. Finally, cell‐to‐cell communication was assessed via Liana ligand‐receptor (LR) interaction analysis.ResultSeveral neuronal, glial, and vascular cell types showed inverse correlations between C31 differential expression and both PS19 differential expression and TREAT‐AD biodomains (Figure 1), suggesting shifts in expression profiles in the opposite direction from those in human AD cohorts and mouse tauopathy models. In LR interaction analysis, vascular and leptomeningeal cells (VLMCs) were highly active as a signaling source to most other cells—particularly neurons—in the PS19 vehicle mice compared to all other groups (Figure 2). VLMC LR signals that were stronger in PS19 vehicle mice versus Wt vehicle were enriched for Focal Adhesion/PI3K‐Akt signaling, TGF‐beta signaling, AD‐presenilin pathways and regulation of synapse organization (Figure 3). VLMC LR signals that were stronger in PS19 C31 versus PS19 vehicle showed similar pathway enrichments and included several neuropilin‐semaphorin‐plexin complexes which may direct neuronal wiring and development.ConclusionThese findings demonstrate that broad patterns of expression and LR signaling in multiple cell types impacted by tauopathy show substantial reversion to wildtype‐like patterns when treated with C31. Further they indicate a possible role for VLMC signaling in the pathogenesis of tauopathies.

Associations between aerobic fitness and subsequent memory performance in non‐demented Presenilin‐1 E280A mutation carriers: A preliminary report from the Colombia‐Boston longitudinal biomarker study

AbstractBackgroundGreater aerobic fitness, objectively measured by VO2‐max, is considered a critical component of overall health and a strong predictor of cognitive functioning. It has been associated with less neurodegeneration in Alzheimer’s disease (AD) and greater functional brain connectivity and plasticity in healthy older adults. Yet, less is known about how it relates to AD progression in people at increased risk for dementia. In this study, we examined whether VO2‐max predicted memory decline in non‐demented mutation carriers and non‐carriers from a Colombian kindred with autosomal dominant AD (ADAD), and hypothesized that those with greater VO2‐max levels would exhibit slower cognitive decline.Methods12 Presenilin‐1 E280A mutation carriers (ages: μ = 39.61 years, SD:4.18) and 14 non‐carriers (ages: μ = 37.11 years, SD:6.59) underwent a standard graded maximal exercise test performed on a treadmill to assess their VO2‐max, which is the maximal rate of oxygen consumption during exercise, measured in milliliters of oxygen per minute per kilogram body mass. Participants also completed the CERAD word list learning and delayed recall, a measure of episodic memory, at baseline and again 18‐24 months later. Group differences were tested using the Mann‐Whitney U test. Linear mixed models were used to examine associations among baseline VO2 max and changes in CERAD word list test scores.ResultsVO2‐max levels did not differ between groups (p = .16). Compared to mutation non‐carriers, mutation carriers performed worse in word list learning (p = .008) and recall (p<.001) at baseline. VO2‐max levels were not associated with baseline word list learning (non‐carriers: p = .93; carriers: p = .76) or recall scores (non‐carriers: p = .82; carriers: p = .63). Baseline VO2‐max levels did not predict change in word list learning (non‐carriers: p = .47; carriers: p = .85) or recall scores (non‐carriers: p = .70; carriers: p = .87).ConclusionPreliminary findings suggest that aerobic fitness, which can be increased with exercise and is associated with greater health, does not relate to memory decline in preclinical ADAD. This is an ongoing longitudinal study, and we will continue to collect more physical activity data in this kindred to characterize these associations better. More research with larger samples is needed to elucidate whether physical activity could help delay AD progression regardless of aerobic fitness levels.

Antagonistic Amyloid‐β and tau interactions with T1‐weighted/T2‐weighted magnetic resonance ratio in Alzheimer’s disesase continuum

AbstractBackgroundTau protein has been reported as a major cause of neurodegeneration in Alzheimer’s disease (AD) continuum. Decrease of T1‐weighted/T2‐weighted magnetic resonace (MR) ratio has been proposed as a measure of demyelination related to neurodegeneration, but some previous researches showed contradictory increase in several brain regions, which was considered as the effecs of other microstructures such as the amyloid‐related iron deposition. Therefore, amyloid β and tau proteins appear to affect the T1w/T2w ratio antagonistically, making their relationship need to be elucidated in order to unambiguously interpret the ratio.MethodWe obtained 221 individuals which include T1‐ and T2‐weighted MR images, and 18F‐florbetapir‐ and 18F‐flortaucipir‐PET images from ADNI. The subjects were then divided into four subgroups based on the status of global Aβ and tau accumulation amount: A‐T‐, A‐T+, A+T‐, and A+T+. We determined positive amyloid status(A+) as global Aβ PET SUVR > 1.11. When determining tau positivity, we used entorhinal cortex (EC) as the earliest tau accumulation region to selectively include tau‐negative individuals while amyloid is being presented. Group differences in regional T1w/T2w ratio values were evaluated.ResultWe found significant group differences in various cortical regions, but also observed distinct effects of Aβ and tau for the T1w/T2w difference. First of all, Aβ and tau affect the T1w/T2w ratio in an opposite direction. A+ individuals have greater T1w/T2w ratio values across wide cortical regions compared to A‐ individuals for both T‐ and T+ groups. However, A‐T+ groups have smaller T1w/T2w ratio values than A‐T‐ groups, while the significant group difference was observed across relatively few cortical regions. Second, Aβ has stronger effect on the T1w/T2w ratio than tau. Specifically, the group difference between A+T+ and A+T‐ shows that Aβ increase the ratio values more strongly than tau reduces the ratio values due to greater accumulation of Aβ in the A+T+ than A+T‐.ConclusionIn this work, we observed the antagonistic interaction of Aβ and tau with T1w/T2w ratio, while more interestingly, we also found that Aβ causes high T1w/T2w ratio, more than tau causes demyelination, followed by lowering T1w/T2w ratio.