Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease

Hypoperfusion in Alzheimer's Disease-Prone Regions and Dementia Conversion in Parkinson's Disease

PURPOSE OF THE REPORT

Although early detection of individuals at risk of dementia conversion is important in patients with Parkinson's disease (PD), there is still no consensus on neuroimaging biomarkers for predicting future cognitive decline. We aimed to investigate whether cerebral perfusion patterns on early-phase 18 F-N-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane ( 18 F-FP-CIT) PET have the potential to serve as a neuroimaging predictor for early dementia conversion in patients with PD.

MATERIALS AND METHODS

In this retrospective analysis, we enrolled 187 patients with newly diagnosed PD who underwent dual-phase 18 F-FP-CIT PET at initial assessment and serial cognitive assessments during the follow-up period (>5 years). Patients with PD were classified into 2 groups: the PD with dementia (PDD)-high-risk (PDD-H; n = 47) and the PDD-low-risk (PDD-L; n = 140) groups according to dementia conversion within 5 years of PD diagnosis. We explored between-group differences in the regional uptake in the early-phase 18 F-FP-CIT PET images. We additionally performed a linear discriminant analysis to develop a prediction model for early PDD conversion.

RESULTS

The PDD-H group exhibited hypoperfusion in Alzheimer's disease (AD)-prone regions (inferomedial temporal and posterior cingulate cortices, and insula) compared with the PDD-L group. A prediction model using regional uptake in the right entorhinal cortex, left amygdala, and left isthmus cingulate cortex could optimally distinguish the PDD-H group from the PDD-L group.

CONCLUSIONS

Regional hypoperfusion in the AD-prone regions on early-phase 18 F-FP-CIT PET can be a useful biomarker for predicting early dementia conversion in patients with PD.

Age-Related Brain Atrophy and the Positive Effects of Behavioral Enrichment in Middle-Aged Beagles

Aging dogs serve as a valuable preclinical model for Alzheimer's disease (AD) due to their natural age-related development of β-amyloid (Aβ) plaques, human-like metabolism, and large brains that are ideal for studying structural brain aging trajectories from serial neuroimaging. Here we examined the effects of chronic treatment with the calcineurin inhibitor (CNI) tacrolimus or the nuclear factor of activated T cells (NFAT)-inhibiting compound Q134R on age-related canine brain atrophy from a longitudinal study in middle-aged beagles (36 females, 7 males) undergoing behavioral enrichment. Annual MRI was analyzed using modern, automated techniques for region-of-interest-based and voxel-based volumetric assessments. We found that the frontal lobe showed accelerated atrophy with age, while the caudate nucleus remained relatively stable. Remarkably, the hippocampus increased in volume in all dogs. None of these changes were influenced by tacrolimus or Q134R treatment. Our results suggest that behavioral enrichment can prevent atrophy and increase the volume of the hippocampus but does not prevent aging-associated prefrontal cortex atrophy.

Evaluation of the Therapeutical Effect of Matricaria Chamomilla Extract vs. Galantamine on Animal Model Memory and Behavior Using 18F-FDG PET/MRI

The memory-enhancing activity of Matricaria chamomilla hydroalcoholic extract (MCE) is already being investigated by behavioral and biochemical assays in scopolamine-induced amnesia rat models, while the effects of scopolamine (Sco) on cerebral glucose metabolism are examined as well. Nevertheless, the study of the metabolic profile determined by an enriched MCE has not been performed before. The present experiments compared metabolic quantification in characteristic cerebral regions and behavioral characteristics for normal, only diseased, diseased, and MCE- vs. Galantamine (Gal)-treated Wistar rats. A memory deficit was induced by four weeks of daily intraperitoneal Sco injection. Starting on the eighth day, the treatment was intraperitoneally administered 30 min after Sco injection for a period of three weeks. The memory assessment comprised three maze tests. Glucose metabolism was quantified after the 18F-FDG PET examination. The right amygdala, piriform, and entorhinal cortex showed the highest differential radiopharmaceutical uptake of the 50 regions analyzed. Rats treated with MCE show metabolic similarity with normal rats, while the Gal-treated group shows features closer to the diseased group. Behavioral assessments evidenced a less anxious status and a better locomotor activity manifested by the MCE-treated group compared to the Gal-treated group. These findings prove evident metabolic ameliorative qualities of MCE over Gal classic treatment, suggesting that the extract could be a potent neuropharmacological agent against amnesia.

Constructing hierarchical attentive functional brain networks for early AD diagnosis

Analyzing functional brain networks (FBN) with deep learning has demonstrated great potential for brain disorder diagnosis. The conventional construction of FBN is typically conducted at a single scale with a predefined brain region atlas. However, numerous studies have identified that the structure and function of the brain are hierarchically organized in nature. This urges the need of representing FBN in a hierarchical manner for more effective analysis of the complementary diagnostic insights at different scales. To this end, this paper proposes to build hierarchical FBNs adaptively within the Transformer framework. Specifically, a sparse attention-based node-merging module is designed to work alongside the conventional network feature extraction modules in each layer. The proposed module generates coarser nodes for further FBN construction and analysis by combining fine-grained nodes. By stacking multiple such layers, a hierarchical representation of FBN can be adaptively learned in an end-to-end manner. The hierarchical structure can not only integrate the complementary information from multiscale FBN for joint analysis, but also reduce the model complexity due to decreasing node sizes. Moreover, this paper argues that the nodes defined by the existing atlases are not necessarily the optimal starting level to build FBN hierarchy and exploring finer nodes may further enrich the FBN representation. In this regard, each predefined node in an atlas is split into multiple sub-nodes, overcoming the scale limitation of the existing atlases. Extensive experiments conducted on various data sets consistently demonstrate the superior performance of the proposed method over the competing methods.

Altered structural and functional connectivity in Posterior Cortical Atrophy and Dementia with Lewy bodies

Posterior cortical atrophy (PCA) and dementia with Lewy bodies (DLB) show distinct atrophy and overlapping hypometabolism profiles, but it is unknown how disruptions in structural and functional connectivity compare between these disorders and whether breakdowns in connectivity relate to either atrophy or hypometabolism. Thirty amyloid-positive PCA patients, 24 amyloid-negative DLB patients and 30 amyloid-negative cognitively unimpaired (CU) healthy individuals were recruited at Mayo Clinic, Rochester, MN, and underwent a 3T head MRI, including structural MRI, resting state functional MRI (rsfMRI) and diffusion tensor imaging (DTI) sequences, as well as [18F] fluorodeoxyglucose (FDG) PET. We assessed functional connectivity within and between 12 brain networks using rsfMRI and the CONN functional connectivity toolbox and calculated regional DTI metrics using the Johns Hopkins atlas. Multivariate linear-regression models corrected for multiple comparisons and adjusted for age and sex compared DTI metrics and within-network and between-network functional connectivity across groups. Regional gray-matter volumes and FDG-PET standard uptake value ratios (SUVRs) were calculated and analyzed at the voxel-level using SPM12. We used univariate linear-regression models to investigate the relationship between connectivity measures, gray-matter volume, and FDG-PET SUVR. On DTI, PCA showed degeneration in occipito-parietal white matter, posterior thalamic radiations, splenium of the corpus collosum and sagittal stratum compared to DLB and CU, with greater degeneration in the temporal white matter and the fornix compared to CU. We observed no white-matter degeneration in DLB compared to CU. On rsfMRI, reduced within-network connectivity was present in dorsal and ventral default mode networks (DMN) and the dorsal-attention network in PCA compared to DLB and CU, with reduced within-network connectivity in the visual and sensorimotor networks compared to CU. DLB showed reduced connectivity in the cerebellar network compared to CU. Between-network analysis showed increased connectivity in both cerebellar-to-sensorimotor and cerebellar-to-dorsal attention network connectivity in PCA and DLB. PCA showed reduced anterior DMN-to-cerebellar and dorsal attention-to-sensorimotor connectivity, while DLB showed reduced posterior DMN-to-sensorimotor connectivity compared to CU. PCA showed reduced dorsal DMN-to-visual connectivity compared to DLB. The multimodal analysis revealed weak associations between functional connectivity and volume in PCA, and between functional connectivity and metabolism in DLB. These findings suggest that PCA and DLB have unique connectivity alterations, with PCA showing more widespread disruptions in both structural and functional connectivity; yet some overlap was observed with both disorders showing increased connectivity from the cerebellum.

Micro-RNA profiles of pathology and resilience in posterior cingulate cortex of cognitively intact elders

The posterior cingulate cortex (PCC) is a key hub of the default mode network underlying autobiographical memory retrieval, which falters early in the progression of Alzheimer's disease (AD). We recently performed RNA sequencing of post-mortem PCC tissue samples from 26 elderly Rush Religious Orders Study participants who came to autopsy with an ante-mortem diagnosis of no cognitive impairment but who collectively displayed a range of Braak I-IV neurofibrillary tangle stages. Notably, cognitively unimpaired subjects displaying high Braak stages may represent cognitive resilience to AD pathology. Transcriptomic data revealed elevated synaptic and ATP-related gene expression in Braak Stages III/IV compared with Stages I/II, suggesting these pathways may be related to PCC resilience. We also mined expression profiles for small non-coding micro-RNAs (miRNAs), which regulate mRNA stability and may represent an underexplored potential mechanism of resilience through the fine-tuning of gene expression within complex cellular networks. Twelve miRNAs were identified as differentially expressed between Braak Stages I/II and III/IV. However, the extent to which the levels of all identified miRNAs were associated with subject demographics, neuropsychological test performance and/or neuropathological diagnostic criteria within this cohort was not explored. Here, we report that a total of 667 miRNAs are significantly associated (rho > 0.38, P < 0.05) with subject variables. There were significant positive correlations between miRNA expression levels and age, perceptual orientation and perceptual speed. By contrast, higher miRNA levels correlated negatively with semantic and episodic memory. Higher expression of 15 miRNAs associated with lower Braak Stages I-II and 47 miRNAs were associated with higher Braak Stages III-IV, suggesting additional mechanistic influences of PCC miRNA expression with resilience. Pathway analysis showed enrichment for miRNAs operating in pathways related to lysine degradation and fatty acid synthesis and metabolism. Finally, we demonstrated that the 12 resilience-related miRNAs differentially expressed in Braak Stages I/II versus Braak Stages III/IV were predicted to regulate mRNAs related to amyloid processing, tau and inflammation. In summary, we demonstrate a dynamic state wherein differential PCC miRNA levels are associated with cognitive performance and post-mortem neuropathological AD diagnostic criteria in cognitively intact elders. We posit these relationships may inform miRNA transcriptional alterations within the PCC relevant to potential early protective (resilience) or pathogenic (pre-clinical or prodromal) responses to disease pathogenesis and thus may be therapeutic targets.

A 3D convolutional neural network to classify subjects as Alzheimer's disease, frontotemporal dementia or healthy controls using brain 18F-FDG PET

With the arrival of disease-modifying drugs, neurodegenerative diseases will require an accurate diagnosis for optimal treatment. Convolutional neural networks are powerful deep learning techniques that can provide great help to physicians in image analysis. The purpose of this study is to introduce and validate a 3D neural network for classification of Alzheimer's disease (AD), frontotemporal dementia (FTD) or cognitively normal (CN) subjects based on brain glucose metabolism. Retrospective [18F]-FDG-PET scans of 199 CE, 192 FTD and 200 CN subjects were collected from our local database, Alzheimer's disease and frontotemporal lobar degeneration neuroimaging initiatives. Training and test sets were created using randomization on a 90 %-10 % basis, and training of a 3D VGG16-like neural network was performed using data augmentation and cross-validation. Performance was compared to clinical interpretation by three specialists in the independent test set. Regions determining classification were identified in an occlusion experiment and Gradient-weighted Class Activation Mapping. Test set subjects were age- and sex-matched across categories. The model achieved an overall 89.8 % accuracy in predicting the class of test scans. Areas under the ROC curves were 93.3 % for AD, 95.3 % for FTD, and 99.9 % for CN. The physicians' consensus showed a 69.5 % accuracy, and there was substantial agreement between them (kappa = 0.61, 95 % CI: 0.49-0.73). To our knowledge, this is the first study to introduce a deep learning model able to discriminate AD and FTD based on [18F]-FDG PET scans, and to isolate CN subjects with excellent accuracy. These initial results are promising and hint at the potential for generalization to data from other centers.

Intermittent Theta Burst Stimulation Attenuates Cognitive Deficits and Alzheimer's Disease-Type Pathologies via ISCA1-Mediated Mitochondrial Modulation in APP/PS1 Mice

Intermittent theta burst stimulation (iTBS), a time-saving and cost-effective repetitive transcranial magnetic stimulation regime, has been shown to improve cognition in patients with Alzheimer's disease (AD). However, the specific mechanism underlying iTBS-induced cognitive enhancement remains unknown. Previous studies suggested that mitochondrial functions are modulated by magnetic stimulation. Here, we showed that iTBS upregulates the expression of iron-sulfur cluster assembly 1 (ISCA1, an essential regulatory factor for mitochondrial respiration) in the brain of APP/PS1 mice. In vivo and in vitro studies revealed that iTBS modulates mitochondrial iron-sulfur cluster assembly to facilitate mitochondrial respiration and function, which is required for ISCA1. Moreover, iTBS rescues cognitive decline and attenuates AD-type pathologies in APP/PS1 mice. The present study uncovers a novel mechanism by which iTBS modulates mitochondrial respiration and function via ISCA1-mediated iron-sulfur cluster assembly to alleviate cognitive impairments and pathologies in AD. We provide the mechanistic target of iTBS that warrants its therapeutic potential for AD patients.

Memory encoding and retrieval by retrosplenial parvalbumin interneurons are impaired in Alzheimer's disease model mice

Memory deficits in Alzheimer's disease (AD) show a strong link with GABAergic interneuron dysfunctions.1,2,3,4,5,6,7 The ensemble dynamics of GABAergic interneurons represent memory encoding and retrieval,8,9,10,11,12 but how GABAergic interneuron dysfunction affects inhibitory ensemble dynamics in AD is unknown. As the retrosplenial cortex (RSC) is critical for episodic memory13,14,15,16 and is affected by β-amyloid accumulation in early AD,17,18,19,20,21 we address this question by performing Ca2+ imaging in RSC parvalbumin (PV)-expressing interneurons during a contextual fear memory task in healthy control mice and the 5XFAD mouse model of AD. We found that populations of PV interneurons responsive to aversive electric foot shocks during contextual fear conditioning (shock-responsive) significantly decreased in the 5XFAD mice, indicating dysfunctions in the recruitment of memory-encoding PV interneurons. In the control mice, ensemble activities of shock-responsive PV interneurons were selectively upregulated during the freezing epoch of the contextual fear memory retrieval, manifested by synaptic potentiation of PV interneuron-mediated inhibition. However, such changes in ensemble dynamics during memory retrieval and synaptic plasticity were both absent in the 5XFAD mice. Optogenetic silencing of PV interneurons during contextual fear conditioning in the control mice mimicked the memory deficits in the 5XFAD mice, while optogenetic activation of PV interneurons in the 5XFAD mice restored memory retrieval. These results demonstrate the critical roles of contextual fear memory-encoding PV interneurons for memory retrieval. Furthermore, synaptic dysfunction of PV interneurons may disrupt the recruitment of PV interneurons and their ensemble dynamics underlying contextual fear memory retrieval, subsequently leading to memory deficits in AD.

Association of metabolic dysfunction with cognitive decline and Alzheimer's disease: A review of metabolomic evidence

The discovery of new biomarkers that can distinguish Alzheimer's disease (AD) from mild cognitive impairment (MCI) in the early stages will help to provide new diagnostic and therapeutic strategies and slow the transition from MCI to AD. Patients with AD may present with a concomitant metabolic disorder, such as diabetes, obesity, and dyslipidemia, as a risk factor for AD that may be involved in the onset of both AD pathology and cognitive impairment. Therefore, metabolite profiling, or metabolomics, can be very useful in diagnosing AD, developing new therapeutic targets, and evaluating both the course of treatment and the clinical course of the disease. In addition, studying the relationship between nutritional behavior and AD requires investigation of the role of conditions such as obesity, hypertension, dyslipidemia, and elevated glucose level. Based on this literature review, nutritional recommendations, including weight loss by reducing calorie and cholesterol intake and omega-3 fatty acid supplementation can prevent cognitive decline and dementia in the elderly. The underlying metabolic causes of the pathology and cognitive decline caused by AD and MCI are not well understood. In this review article, metabolomics biomarkers for diagnosis of AD and MCI and metabolic risk factors for cognitive decline in AD were evaluated.

Comparing Symmetric Dimethylarginine and Amyloid-β42 as Predictors of Alzheimer's Disease Development

Background

Physicians may soon be able to diagnose Alzheimer's disease (AD) in its early stages using fluid biomarkers like amyloid. However, it is acknowledged that additional biomarkers need to be characterized which would facilitate earlier monitoring of AD pathogenesis.

Objective

To determine if a potential novel inflammation biomarker for AD, symmetric dimethylarginine, has utility as a baseline serum biomarker for discriminating prodromal AD from cognitively unimpaired controls in comparison to cerebrospinal fluid amyloid-β42 (Aβ42).

Methods

Data including demographics, magnetic resonance imaging and fluorodeoxyglucose-positron emission tomography scans, Mini-Mental State Examination and Functional Activities Questionnaire scores, and biomarker concentrations were obtained from the Alzheimer's Disease Neuroimaging Initiative for a total of 146 prodromal AD participants and 108 cognitively unimpaired controls.

Results

Aβ42 (p = 0.65) and symmetric dimethylarginine (p = 0.45) were unable to predict age-matched cognitively unimpaired controls and prodromal AD participants. Aβ42 was negatively associated with regional brain atrophy and hypometabolism as well as cognitive and functional decline in cognitively unimpaired control participants (p < 0.05) that generally decreased in time. There were no significant associations between Aβ42 and symmetric dimethylarginine with imaging or neurocognitive biomarkers in prodromal AD patients.

Conclusions

Correlations were smaller between Aβ42 and neuropathological biomarkers over time and were absent in prodromal AD participants, suggesting a plateau effect dependent on age and disease stage. Evidence supporting symmetric dimethylarginine as a novel biomarker for AD as a single measurement was not found.

Is the cingulate island sign a marker for early dementia conversion in Parkinson's disease?

BACKGROUND

To investigate whether the cingulate island sign (CIS) ratio (i.e., the ratio of regional uptake in the posterior cingulate cortex relative to the precuneus and cuneus on cerebral perfusion scans) is associated with early dementia conversion in Parkinson's disease (PD).

METHODS

We enrolled 226 patients with newly diagnosed PD and 48 healthy controls who underwent dual-phase 18 F-FP-CIT PET scans. Patients with PD were classified into three groups according to the CIS ratio on early-phase 18 F-FP-CIT PET images: a PD group with CIS or high CIS ratios (PD-CIS; n = 96), a PD group with inverse CIS or low CIS ratios (PD-iCIS; n = 40), and a PD group consisting of the remaining patients with normal CIS ratios (PD-nCIS; n = 90). We compared the risk of dementia conversion within a 5-year time point between the groups.

RESULTS

There were no significant differences in age, sex, education, or baseline cognitive function between the PD groups. The PD-CIS group had higher Unified Parkinson's Disease Rating Scale (UPDRS) motor scores and more severely decreased dopamine transporter availability in the putamen. The PD-iCIS group had a smaller hippocampal volume compared with the other groups. The risk of dementia conversion in the PD-CIS group did not differ from that in the PD-iCIS and PD-nCIS groups. Meanwhile, the PD-iCIS group had a higher risk of dementia conversion than the PD-nCIS group.

CONCLUSION

The results of this study suggest that inverse CIS, rather than CIS, is relevant to early dementia conversion in patients with PD.

Alzheimer's disease and synapse Loss: What can we learn from induced pluripotent stem Cells?

BACKGROUND

Synaptic dysfunction is a major contributor to Alzheimeŕs disease (AD) pathogenesis in addition to the formation of neuritic β-amyloid plaques and neurofibrillary tangles of hyperphosphorylated Tau protein. However, how these features contribute to synaptic dysfunction and axonal loss remains unclear. While years of considerable effort have been devoted to gaining an improved understanding of this devastating disease, the unavailability of patient-derived tissues, considerable genetic heterogeneity, and lack of animal models that faithfully recapitulate human AD have hampered the development of effective treatment options. Ongoing progress in human induced pluripotent stem cell (hiPSC) technology has permitted the derivation of patient- and disease-specific stem cells with unlimited self-renewal capacity. These cells can differentiate into AD-affected cell types, which support studies of disease mechanisms, drug discovery, and the development of cell replacement therapies in traditional and advanced cell culture models.

AIM OF REVIEW

To summarize current hiPSC-based AD models, highlighting the associated achievements and challenges with a primary focus on neuron and synapse loss.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We aim to identify how hiPSC models can contribute to understanding AD-associated synaptic dysfunction and axonal loss. hiPSC-derived neural cells, astrocytes, and microglia, as well as more sophisticated cellular organoids, may represent reliable models to investigate AD and identify early markers of AD-associated neural degeneration.

A strategic tool to improve the study of molecular determinants of Alzheimer's disease: The role of glyceraldehyde

Alzheimer's disease (AD) is the most prevalent form of dementia and is characterized by progressive neurodegeneration leading to severe cognitive, memory, and behavioral impairments. The onset of AD involves a complex interplay among various factors, including age, genetics, chronic inflammation, and impaired energy metabolism. Despite significant efforts, there are currently no effective therapies capable of modifying the course of AD, likely owing to an excessive focus on the amyloid hypothesis and a limited consideration of other intracellular pathways. In the present review, we emphasize the emerging concept of AD as a metabolic disease, where alterations in energy metabolism play a critical role in its development and progression. Notably, glucose metabolism impairment is associated with mitochondrial dysfunction, oxidative stress, Ca2+ dyshomeostasis, and protein misfolding, forming interconnected processes that perpetuate a detrimental self-feeding loop sustaining AD progression. Advanced glycation end products (AGEs), neurotoxic compounds that accumulate in AD, are considered an important consequence of glucose metabolism disruption, and glyceraldehyde (GA), a glycolytic intermediate, is a key contributor to AGEs formation in both neurons and astrocytes. Exploring the impact of GA-induced glucose metabolism impairment opens up exciting possibilities for creating an easy-to-handle in vitro model that recapitulates the early stage of the disease. This model holds great potential for advancing the development of novel therapeutics targeting various intracellular pathways implicated in AD pathogenesis. In conclusion, looking beyond the conventional amyloid hypothesis could lead researchers to discover promising targets for intervention, offering the possibility of addressing the existing medical gaps in AD treatment.

Reduced gray matter volume in the default-mode network associated with insulin resistance

Insulin resistance may lead to structural and functional abnormalities of the human brain. However, the mechanism by which insulin resistance impairs the brain remains elusive. In this study, we used two large neuroimaging databases to investigate the brain regions where insulin resistance was associated with the gray matter volume and to examine the resting-state functional connectivity between these brain regions and each hypothalamic nucleus. Insulin resistance was associated with reduced gray matter volume in the regions of the default-mode and limbic networks in the cerebral cortex in older adults. Resting-state functional connectivity was prominent between these networks and the paraventricular nucleus of the hypothalamus, a hypothalamic interface connecting functionally with the cerebral cortex. Furthermore, we found a significant correlation in these networks between insulin resistance-related gray matter volume reduction and network paraventricular nucleus of the hypothalamus resting-state functional connectivity. These results suggest that insulin resistance-related gray matter volume reduction in the default-mode and limbic networks emerged through metabolic homeostasis mechanisms in the hypothalamus.

Oscillatory network markers of subcallosal cingulate deep brain stimulation for depression

Identifying functional biomarkers related to treatment success can aid in expediting therapy optimization, as well as contribute to a better understanding of the neural mechanisms of the treatment-resistant depression (TRD) and subcallosal cingulate deep brain stimulation (SCC-DBS). Magnetoencephalography data were obtained from 16 individuals with SCC-DBS for TRD and 25 healthy subjects. The first objective of the study was to identify region-specific oscillatory modulations that both (i) discriminate individuals with TRD (with SCC-DBS OFF) from healthy controls, and (ii) discriminate TRD treatment responders from non-responders (with SCC-DBS ON). The second objective of this work was to further explore the effects of stimulation intensity and frequency on oscillatory activity in the identified brain regions of interest. Oscillatory power analyses led to the identification of brain regions that differentiated responders from non-responders based on modulations of increased alpha (8-12 Hz) and decreased gamma (32-116 Hz) power within nodes of the default mode, central executive, and somatomotor networks, Broca's area, and lingual gyrus. Within these nodes, it was also found that low stimulation frequency had stronger effects on oscillatory modulation than increased stimulation intensity. The identified functional network biomarkers implicate modulation of TRD-related activity in brain regions involved in emotional control/processing, motor control, and the interaction between speech, vision, and memory, which have all been implicated in depression. These electrophysiological biomarkers have the potential to be used as functional proxies for therapy optimization. Additional stimulation parameter analyses revealed that oscillatory modulations can be strengthened by increasing stimulation intensity or reducing frequency, which may represent potential avenues of direction in non-responders.

Treatment of Alzheimer's Disease: Beyond Symptomatic Therapies

In an ever-increasing aged world, Alzheimer's disease (AD) represents the first cause of dementia and one of the first chronic diseases in elderly people. With 55 million people affected, the WHO considers AD to be a disease with public priority. Unfortunately, there are no final cures for this pathology. Treatment strategies are aimed to mitigate symptoms, i.e., acetylcholinesterase inhibitors (AChEI) and the N-Methyl-D-aspartate (NMDA) antagonist Memantine. At present, the best approaches for managing the disease seem to combine pharmacological and non-pharmacological therapies to stimulate cognitive reserve. Over the last twenty years, a number of drugs have been discovered acting on the well-established biological hallmarks of AD, deposition of β-amyloid aggregates and accumulation of hyperphosphorylated tau protein in cells. Although previous efforts disappointed expectations, a new era in treating AD has been working its way recently. The Food and Drug Administration (FDA) gave conditional approval of the first disease-modifying therapy (DMT) for the treatment of AD, aducanumab, a monoclonal antibody (mAb) designed against Aβ plaques and oligomers in 2021, and in January 2023, the FDA granted accelerated approval for a second monoclonal antibody, Lecanemab. This review describes ongoing clinical trials with DMTs and non-pharmacological therapies. We will also present a future scenario based on new biomarkers that can detect AD in preclinical or prodromal stages, identify people at risk of developing AD, and allow an early and curative treatment.

Aiming for [18F]FDG-PET acquisition time reduction in clinical practice for neurological patients

PURPOSE

Positron emission tomography (PET) imaging with [18F]FDG provides valuable information regarding the underlying pathological processes in neurodegenerative disorders. PET imaging for these populations should be as short as possible to limit head movements and improve comfort. This study aimed to validate an optimized [18F]FDG-PET image reconstruction protocol aiming to reduce acquisition time while maintaining adequate quantification accuracy and image quality.

METHODS

A time-reduced reconstruction protocol (5 min) was evaluated in [18F]FDG-PET retrospective data from healthy individuals and Alzheimer's disease (AD) patients. Standard (8 min) and time-reduced protocols were compared by means of image quality and quantification accuracy metrics, as well as standardized uptake value ratio (SUVR) and Z-scores (pons was used as reference). Images were randomly and blindly presented to experienced physicians and scored in terms of image quality.

RESULTS

No differences between protocols were identified during the visual assessment. Small differences (p < 0.01) in the pons SUVR were observed between the standard and time-reduced protocols for healthy individuals (-0.002 ± 0.011) and AD patients (-0.007 ± 0.013). Likewise, incorporating the PSF correction in the reconstruction algorithm resulted in small differences (p < 0.01) in SUVR between protocols (healthy individuals: -0.003 ± 0.011; AD patients: -0.007 ± 0.014).

CONCLUSION

Quality metrics were similar between time-reduced and standard protocols. In the visual assessment of the images, the physicians did not consider the use of PSF adequate, as it degraded the quality image. Shortening the acquisition time is possible by optimizing the image reconstruction parameters while maintaining adequate quantification accuracy and image quality.

Spatial and single-nucleus transcriptomic analysis of genetic and sporadic forms of Alzheimer's Disease

The pathogenesis of Alzheimer's disease (AD) depends on environmental and heritable factors, with remarkable differences evident between individuals at the molecular level. Here we present a transcriptomic survey of AD using spatial transcriptomics (ST) and single-nucleus RNA-seq in cortical samples from early-stage AD, late-stage AD, and AD in Down Syndrome (AD in DS) donors. Studying AD in DS provides an opportunity to enhance our understanding of the AD transcriptome, potentially bridging the gap between genetic mouse models and sporadic AD. Our analysis revealed spatial and cell-type specific changes in disease, with broad similarities in these changes between sAD and AD in DS. We performed additional ST experiments in a disease timecourse of 5xFAD and wildtype mice to facilitate cross-species comparisons. Finally, amyloid plaque and fibril imaging in the same tissue samples used for ST enabled us to directly link changes in gene expression with accumulation and spread of pathology.

Axonal energy metabolism, and the effects in aging and neurodegenerative diseases

Human studies consistently identify bioenergetic maladaptations in brains upon aging and neurodegenerative disorders of aging (NDAs), such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and Amyotrophic lateral sclerosis. Glucose is the major brain fuel and glucose hypometabolism has been observed in brain regions vulnerable to aging and NDAs. Many neurodegenerative susceptible regions are in the topological central hub of the brain connectome, linked by densely interconnected long-range axons. Axons, key components of the connectome, have high metabolic needs to support neurotransmission and other essential activities. Long-range axons are particularly vulnerable to injury, neurotoxin exposure, protein stress, lysosomal dysfunction, etc. Axonopathy is often an early sign of neurodegeneration. Recent studies ascribe axonal maintenance failures to local bioenergetic dysregulation. With this review, we aim to stimulate research in exploring metabolically oriented neuroprotection strategies to enhance or normalize bioenergetics in NDA models. Here we start by summarizing evidence from human patients and animal models to reveal the correlation between glucose hypometabolism and connectomic disintegration upon aging/NDAs. To encourage mechanistic investigations on how axonal bioenergetic dysregulation occurs during aging/NDAs, we first review the current literature on axonal bioenergetics in distinct axonal subdomains: axon initial segments, myelinated axonal segments, and axonal arbors harboring pre-synaptic boutons. In each subdomain, we focus on the organization, activity-dependent regulation of the bioenergetic system, and external glial support. Second, we review the mechanisms regulating axonal nicotinamide adenine dinucleotide (NAD+) homeostasis, an essential molecule for energy metabolism processes, including NAD+ biosynthetic, recycling, and consuming pathways. Third, we highlight the innate metabolic vulnerability of the brain connectome and discuss its perturbation during aging and NDAs. As axonal bioenergetic deficits are developing into NDAs, especially in asymptomatic phase, they are likely exaggerated further by impaired NAD+ homeostasis, the high energetic cost of neural network hyperactivity, and glial pathology. Future research in interrogating the causal relationship between metabolic vulnerability, axonopathy, amyloid/tau pathology, and cognitive decline will provide fundamental knowledge for developing therapeutic interventions.

Turning the Spotlight to Cholinergic Pharmacotherapy of the Human Language System

Even though language is essential in human communication, research on pharmacological therapies for language deficits in highly prevalent neurodegenerative and vascular brain diseases has received little attention. Emerging scientific evidence suggests that disruption of the cholinergic system may play an essential role in language deficits associated with Alzheimer's disease and vascular cognitive impairment, including post-stroke aphasia. Therefore, current models of cognitive processing are beginning to appraise the implications of the brain modulator acetylcholine in human language functions. Future work should be directed further to analyze the interplay between the cholinergic system and language, focusing on identifying brain regions receiving cholinergic innervation susceptible to modulation with pharmacotherapy to improve affected language domains. The evaluation of language deficits in pharmacological cholinergic trials for Alzheimer's disease and vascular cognitive impairment has thus far been limited to coarse-grained methods. More precise, fine-grained language testing is needed to refine patient selection for pharmacotherapy to detect subtle deficits in the initial phases of cognitive decline. Additionally, noninvasive biomarkers can help identify cholinergic depletion. However, despite the investigation of cholinergic treatment for language deficits in Alzheimer's disease and vascular cognitive impairment, data on its effectiveness are insufficient and controversial. In the case of post-stroke aphasia, cholinergic agents are showing promise, particularly when combined with speech-language therapy to promote trained-dependent neural plasticity. Future research should explore the potential benefits of cholinergic pharmacotherapy in language deficits and investigate optimal strategies for combining these agents with other therapeutic approaches.

Higher order diffusion imaging as a putative index of human sleep-related microstructural changes and glymphatic clearance

The brain has a unique macroscopic waste clearance system, termed the glymphatic system which utilises perivascular tunnels surrounded by astroglia to promote cerebrospinal-interstitial fluid exchange. Rodent studies have demonstrated a marked increase in glymphatic clearance during sleep which has been linked to a sleep-induced expansion of the extracellular space and concomitant reduction in intracellular volume. However, despite being implicated in the pathophysiology of multiple human neurodegenerative disorders, non-invasive techniques for imaging glymphatic clearance in humans are currently limited. Here we acquired multi-shell diffusion weighted MRI (dwMRI) in twenty-one healthy young participants (6 female, 22.3 ± 3.2 years) each scanned twice, once during wakefulness and once during sleep induced by a combination of one night of sleep deprivation and 10 mg of the hypnotic zolpidem 30 min before scanning. To capture hypothesised sleep-associated changes in intra/extracellular space, dwMRI were analysed using higher order diffusion modelling with the prediction that sleep-associated increases in interstitial (extracellular) fluid volume would result in a decrease in diffusion kurtosis, particularly in areas associated with slow wave generation at the onset of sleep. In line with our hypothesis, we observed a global reduction in diffusion kurtosis (t15=2.82, p = 0.006) during sleep as well as regional reductions in brain areas associated with slow wave generation during early sleep and default mode network areas that are highly metabolically active during wakefulness. Analysis with a higher-order representation of diffusion (MAP-MRI) further indicated that changes within the intra/extracellular domain rather than membrane permeability likely underpin the observed sleep-associated decrease in kurtosis. These findings identify higher-order modelling of dwMRI as a potential new non-invasive method for imaging glymphatic clearance and extend rodent findings to suggest that sleep is also associated with an increase in interstitial fluid volume in humans.

Regional contributions of D-serine to Alzheimer's disease pathology in male AppNL-G-F/NL-G-F mice

Background

Neurodegenerative processes in Alzheimer's disease (AD) are associated with excitotoxicity mediated by the N-methyl-D-aspartate receptor (NMDAR). D-Serine is an endogenous co-agonist necessary for NMDAR-mediated excitotoxicity. In the mammalian brain, it is produced by serine racemase (SRR) from L-serine, suggesting that dysregulation of L-serine, D-serine, or SRR may contribute to AD pathogenesis.

Objective and methods

We examined the contributions of D-serine to AD pathology in the App^{NL-G-F/NL-G-F} gene knock-in (APPKI) mouse model of AD. We first examined brain SRR expression levels and neuropathology in APPKI mice and then assessed the effects of long-term D-serine supplementation in drinking water on neurodegeneration. To further confirm the involvement of endogenous D-serine in AD progression, we generated Srr gene-deleted APPKI (APPKI-SRRKO) mice. Finally, to examine the levels of brain amino acids, we conducted liquid chromatography-tandem mass spectrometry.

Results

Expression of SRR was markedly reduced in the retrosplenial cortex (RSC) of APPKI mice at 12 months of age compared with age-matched wild-type mice. Neuronal density was decreased in the hippocampal CA1 region but not altered significantly in the RSC. D-Serine supplementation exacerbated neuronal loss in the hippocampal CA1 of APPKI mice, while APPKI-SRRKO mice exhibited attenuated astrogliosis and reduced neuronal death in the hippocampal CA1 compared with APPKI mice. Furthermore, APPKI mice demonstrated marked abnormalities in the cortical amino acid levels that were partially reversed in APPKI-SRRKO mice.

Conclusion

These findings suggest that D-serine participates in the regional neurodegenerative process in the hippocampal CA1 during the amyloid pathology of AD and that reducing brain D-serine can partially attenuate neuronal loss and reactive astrogliosis. Therefore, regulating SRR could be an effective strategy to mitigate NMDAR-dependent neurodegeneration during AD progression.

Metabolism-related brain morphology accelerates aging and predicts neurodegenerative diseases and stroke: a UK Biobank study

Metabolic syndrome (MetS) is characterized by a constellation of metabolic risk factors, including obesity, hypertriglyceridemia, low high-density lipoprotein (HDL) levels, hypertension, and hyperglycemia, and is associated with stroke and neurodegenerative diseases. This study capitalized on brain structural images and clinical data from the UK Biobank and explored the associations of brain morphology with MetS and brain aging due to MetS. Cortical surface area, thickness, and subcortical volumes were assessed using FreeSurfer. Linear regression was used to examine associations of brain morphology with five MetS components and the MetS severity in a metabolic aging group (N = 23,676, age 62.8 ± 7.5 years). Partial least squares (PLS) were employed to predict brain age using MetS-associated brain morphology. The five MetS components and MetS severity were associated with increased cortical surface area and decreased thickness, particularly in the frontal, temporal, and sensorimotor cortex, and reduced volumes in the basal ganglia. Obesity best explained the variation of brain morphology. Moreover, participants with the most severe MetS had brain age 1-year older than those without MetS. Brain age in patients with stroke (N = 1042), dementia (N = 83), Parkinson's (N = 107), and multiple sclerosis (N = 235) was greater than that in the metabolic aging group. The obesity-related brain morphology had the leading discriminative power. Therefore, the MetS-related brain morphological model can be used for risk assessment of stroke and neurodegenerative diseases. Our findings suggested that prioritizing adjusting obesity among the five metabolic components may be more helpful for improving brain health in aging populations.

Individualized Summary Assessment of Detailed Neuropsychological Testing for the Etiological Diagnosis of Newly Detected Cognitive Impairment in Hospitalized Geriatric Patients

BACKGROUND

Neuropsychological testing (NPT) of geriatric inpatients can be affected by the acute illness and/or the hospitalization.

OBJECTIVE

To test individualized interpretation of detailed NPT for the differentiation between primary 'neurodegenerative' etiologies (predominantly Alzheimer's disease) and 'other' etiologies (including cerebrovascular disease) of newly detected cognitive impairment in geriatric inpatients without and with delirium in remission.

METHODS

96 geriatric inpatients (81.9±5.6 years, 64.6% females) with clinically uncertain cognitive impairment were included. 31.3% had delirium in remission that was not considered the primary cause of the cognitive impairment. Categorization of the most likely etiology as 'neurodegenerative' or 'other' was established retrospectively by a study neuropsychologist based on individualized summary assessment of detailed NPT compiled in a standardized vignette. The etiological diagnosis based on FDG-PET served as gold standard (54.2% 'neurodegenerative', 45.8% 'other').

RESULTS

Individualized summary assessment by the study neuropsychologist was correct in 80 patients (83.3%, 8 false positive, 8 false negative). The impact of delirium in remission was not significant (p = 0.237). Individualized summary assessment by an independent neuropsychologist resulted in more false positive cases (n = 22) at the same rate of false negative cases (n = 8). Automatic categorization with a decision tree model based on the most discriminative NPT scores was correct in 68 patients (70.8%, 14 false positive, 14 false negative).

CONCLUSION

Individualized summary assessment of detailed NPT in the context of relevant clinical information might be useful for the etiological diagnosis of newly detected cognitive impairment in hospitalized geriatric patients, also in patients with delirium in remission, but requires task-specific expertise.

Targeting Sigma Receptors for the Treatment of Neurodegenerative and Neurodevelopmental Disorders

The sigma-1 receptor is a 223 amino acid-long protein with a recently identified structure. The sigma-2 receptor is a genetically unrelated protein with a similarly shaped binding pocket and acts to influence cellular activities similar to the sigma-1 receptor. Both proteins are highly expressed in neuronal tissues. As such, they have become targets for treating neurological diseases, including Alzheimer's disease (AD), Huntington's disease (HD), Parkinson's disease (PD), multiple sclerosis (MS), Rett syndrome (RS), developmental and epileptic encephalopathies (DEE), and motor neuron disease/amyotrophic lateral sclerosis (MND/ALS). In recent years, there have been many pre-clinical and clinical studies of sigma receptor (1 and 2) ligands for treating neurological disease. Drugs such as blarcamesine, dextromethorphan and pridopidine, which have sigma-1 receptor activity as part of their pharmacological profile, are effective in treating multiple aspects of several neurological diseases. Furthermore, several sigma-2 receptor ligands are under investigation, including CT1812, rivastigmine and SAS0132. This review aims to provide a current and up-to-date analysis of the current clinical and pre-clinical data of drugs with sigma receptor activities for treating neurological disease.

Neuroimaging in Alzheimer's Disease for Early Diagnosis: A Comprehensive Review

Alzheimer's disease (AD) is the most common cause of dementia in the elderly, affecting roughly half of those over the age of 85. We briefly discussed the risk factors, epidemiology, and treatment options for AD. The development of therapeutic therapies operating very early in the disease cascade has been spurred by the realization that the disease process begins at least a decade or more before the manifestation of symptoms. Thus, the clinical significance of early diagnosis was emphasized. Using various keywords, a literature search was carried out using PubMed and other databases. For inclusion, pertinent articles were chosen and reviewed. This article has reviewed different neuroimaging techniques that are considered advanced tools to aid in establishing a diagnosis and highlighted the advantages as well as disadvantages of those techniques. Besides, the prevalence of several in vivo biomarkers aided in discriminating affected individuals from healthy controls in the early stages of the disease. Each imaging method has its advantages and disadvantages, hence no single imaging approach can be the optimum modality for diagnosis. This article also commented on a better approach to using these techniques to increase the likelihood of an early diagnosis.

Levetiracetam Increases Hippocampal Blood Flow in Alzheimer's Disease as Measured by Arterial Spin Labelling MRI

BACKGROUND

Patients with Alzheimer's disease (AD) have an increased risk of developing epileptiform discharges, which is associated with a more rapid rate of progression. This suggests that suppression of epileptiform activity could have clinical benefit in patients with AD.

OBJECTIVE

In the current study, we tested whether acute, intravenous administration of levetiracetam led to changes in brain perfusion as measured with arterial spin labeling MRI (ASL-MRI) in AD.

METHODS

We conducted a double-blind, within-subject crossover design study in which participants with mild AD (n = 9) received placebo, 2.5 mg/kg, and 7.5 mg/kg of LEV intravenously in a random order in three sessions. Afterwards, the participants underwent ASL-MRI.

RESULTS

Analysis of relative cerebral blood flow (rCBF) between 2.5 mg of levetiracetam and placebo showed significant decreases in a cluster that included the posterior cingulate cortex, the precuneus, the posterior part of the cingulate gyrus, while increased cerebral blood flow was found in both temporal lobes involving the hippocampus.

CONCLUSION

Administration of 2.5 mg/kg of LEV in patients without any history of epilepsy leads to changes in rCBF in areas known to be affected in the early stages of AD. These areas may be the focus of the epileptiform activity. Larger studies are needed to confirm the current findings.

Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer's disease?

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder that affects memory, thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD early is important for the development of a therapeutic plan and a care plan that may preserve cognitive function and prevent irreversible damage. Neuroimaging, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), has served as a critical tool in establishing diagnostic indicators of AD during the preclinical stage. However, as neuroimaging technology quickly advances, there is a challenge in analyzing and interpreting vast amounts of brain imaging data. Given these limitations, there is great interest in using artificial Intelligence (AI) to assist in this process. AI introduces limitless possibilities in the future diagnosis of AD, yet there is still resistance from the healthcare community to incorporate AI in the clinical setting. The goal of this review is to answer the question of whether AI should be used in conjunction with neuroimaging in the diagnosis of AD. To answer the question, the possible benefits and disadvantages of AI are discussed. The main advantages of AI are its potential to improve diagnostic accuracy, improve the efficiency in analyzing radiographic data, reduce physician burnout, and advance precision medicine. The disadvantages include generalization and data shortage, lack of in vivo gold standard, skepticism in the medical community, potential for physician bias, and concerns over patient information, privacy, and safety. Although the challenges present fundamental concerns and must be addressed when the time comes, it would be unethical not to use AI if it can improve patient health and outcome.

Vascular-water-exchange MRI (VEXI) enables the detection of subtle AXR alterations in Alzheimer's disease without MRI contrast agent, which may relate to BBB integrity

Blood-brain barrier (BBB) impairment is an important pathophysiological process in Alzheimer's disease (AD) and a potential biomarker for early diagnosis of AD. However, most current neuroimaging methods assessing BBB function need the injection of exogenous contrast agents (or tracers), which limits the application of these methods in a large population. In this study, we aim to explore the feasibility of vascular water exchange MRI (VEXI), a diffusion-MRI-based method proposed to assess the BBB permeability to water molecules without using a contrast agent, in the detection of the BBB breakdown in AD. We tested VEXI on a 3T MRI scanner on three groups: AD patients (AD group), mild cognitive impairment (MCI) patients due to AD (MCI group), and the age-matched normal cognition subjects (NC group). Interestingly, we find that the apparent water exchange across the BBB (AXR_BBB) measured by VEXI shows higher values in MCI compared with NC, and this higher AXR_BBB happens specifically in the hippocampus. This increase in AXR_BBB value gets larger and extends to more brain regions (medial orbital frontal cortex and thalamus) from MCI group to the AD group. Furthermore, we find that the AXR_BBB values of these three regions is correlated significantly with the impairment of respective cognitive domains independent of age, sex and education. These results suggest VEXI is a promising method to assess the BBB breakdown in AD.

Apolipoprotein E4 targets mitochondria and the mitochondria-associated membrane complex in neuropathology, including Alzheimer's disease

Apolipoprotein (apo) E4 sets the stage for neuropathology in Alzheimer's disease (AD) by causing mitochondrial dysfunction and altering mitochondria-associated membranes. Contact and apposition of mitochondrial-endoplasmic reticulum membranes are enhanced in brain cells in AD and associated with increases in tethering and spacing proteins that modulate many cellular processes. Contact site protein levels are higher in apoE4 cells. In apoE4 neurons, the NAD⁺/NADH ratio is lowered, reactive oxygen species are increased, and NAD/NADH pathway components and redox proteins are decreased. Oxidative phosphorylation is impaired and reserve ATP generation capacity is lacking. ApoE4 neurons have ∼50% fewer respiratory complex subunits (e.g., ATP synthase) and may increase translocase levels of the outer and inner mitochondrial membranes to facilitate delivery of nucleus-encoded complex subunits. Respiratory complex assembly relies on mitochondrial cristae organizing system subunits that are altered in apoE4 cells, and apoE4 increases mitochondrial proteases that control respiratory subunit composition for complex assembly.

Brain Functional Alterations and Association with Cognition in People with Preclinical Subjective Cognitive Decline and Objective Subtle Cognitive Difficulties

Subjective cognitive decline (SCD) and objective subtle cognitive difficulties (Obj-SCD) are considered the initial stages of aberrant cognition prior to mild cognitive impairment (MCI) due to Alzheimer's disease (AD). We aimed to determine the difference of brain function of SCD and Obj-SCD, furthermore, to figure out which one could be the marker of early AD. One hundred and eighty-five participants were enrolled in this study to determine the amyloid pathology and glucose metabolism changes in SCD and Obj-SCD. The association of amyloid deposition and glucose metabolism with cognitive domains were also investigated. Obj-SCD displayed significantly increased amyloid deposition in frontal and temporal lobes compared to SCD and normal cognitive control (NCC). No difference of amyloid deposition between SCD and NCC, and no difference of glucose metabolism among the three groups were observed. Amyloid deposition was associated with function of memory, language and executive domains, and glucose metabolism was only associated with executive function in Obj-SCD. Amyloid deposition was only associated with executive function in SCD. Obj-SCD could be the early stage of AD, which displayed significant increased amyloid deposition, and the increased amyloid deposition was associated with cognitive function in different domains.

A tripartite view of the posterior cingulate cortex

The posterior cingulate cortex (PCC) is one of the least understood regions of the cerebral cortex. By contrast, the anterior cingulate cortex has been the subject of intensive investigation in humans and model animal systems, leading to detailed behavioural and computational theoretical accounts of its function. The time is right for similar progress to be made in the PCC given its unique anatomical and physiological properties and demonstrably important contributions to higher cognitive functions and brain diseases. Here, we describe recent progress in understanding the PCC, with a focus on convergent findings across species and techniques that lay a foundation for establishing a formal theoretical account of its functions. Based on this converging evidence, we propose that the broader PCC region contains three major subregions - the dorsal PCC, ventral PCC and retrosplenial cortex - that respectively support the integration of executive, mnemonic and spatial processing systems. This tripartite subregional view reconciles inconsistencies in prior unitary theories of PCC function and offers promising new avenues for progress.

Cerebral white matter lesions and regional blood flow are associated with reduced cognitive function in early-stage cognitive impairment

Background

Differences in the extent of cerebral white matter lesions (WML) and regional cerebral blood flow (rCBF) in early-stage cognitive impairment (ESCI) contribute to the prognosis of cognitive decline; however, it is unclear precisely how WML and rCBF affect cognitive decline in ESCI.

Objective

We examined the association between WML, rCBF, and cognitive impairment in the ESCI, using path analysis to clarify how these variables affect each other.

Methods

Eighty-three patients who consulted our memory clinic regarding memory loss were included in this study based on the Clinical Dementia Rating. Participants underwent the Mini-Mental State Examination (MMSE), brain magnetic resonance imaging (MRI) for voxel-based morphometry analysis, and brain perfusion single-photon emission computed tomography (SPECT) for rCBF evaluation in cortical regions, using 3D stereotactic surface projection (3D-SSP) analysis.

Results

Path analysis was performed on the MRI voxel-based morphometry and SPECT 3D-SSP data, showing a significant correlation between both and MMSE scores. In the most suitable model (GFI = 0.957), correlations were observed between lateral ventricular (LV-V) and periventricular WML (PvWML-V) volumes [standardized coefficient (SC) = 0.326, p = 0.005], LV-V and rCBF of the anterior cingulate gyrus (ACG-rCBF; SC = 0.395, p < 0.0001), and ACG-rCBF and PvWML-V (SC = 0.231, p = 0.041). Furthermore, a direct relationship between PvWML-V and MMSE scores was identified (SC = -0.238, p = 0.026).

Conclusion

Significant interrelationships were observed among the LV-V, PvWML-V, and ACG-rCBF that directly affected the MMSE score in the ESCI. The mechanisms behind these interactions and the impact of PvWML-V on cognitive function require further investigation.

Functional Correlates of Striatal Dopamine Transporter Cerebrospinal Fluid Levels in Alzheimer's Disease: A Preliminary 18F-FDG PET/CT Study

The aim of our study was to investigate regional glucose metabolism with 18F-FDG positron emission tomography/computed tomography in a population of patients with Alzheimer's disease (AD) in relation to cerebrospinal (CSF) levels of striatal dopamine transporter (DAT). All patients underwent lumbar puncture and received a biomarker-based diagnosis of AD. Differences in regional brain glucose metabolism were assessed by Statistical Parametric Mapping version 12 with the use of age, gender, and MMSE as covariates in the analysis. A positive correlation between CSF DAT levels and glucose metabolism at the level of two brain areas involved in the pathophysiological process of Alzheimer's disease, the substantia nigra and the posterior cingulate gyrus, has been highlighted. Results indicate that patients with higher CSF DAT levels have a better metabolic pattern in two key zones, suggesting less advanced disease status in patients with more conserved dopaminergic systems.

Deep learning-based diagnosis of Alzheimer's disease using brain magnetic resonance images: an empirical study

The limited accessibility of medical specialists for Alzheimer's disease (AD) can make obtaining an accurate diagnosis in a timely manner challenging and may influence prognosis. We investigated whether VUNO Med-DeepBrain AD (DBAD) using a deep learning algorithm can be employed as a decision support service for the diagnosis of AD. This study included 98 elderly participants aged 60 years or older who visited the Seoul Asan Medical Center and the Korea Veterans Health Service. We administered a standard diagnostic assessment for diagnosing AD. DBAD and three panels of medical experts (ME) diagnosed participants with normal cognition (NC) or AD using T1-weighted magnetic resonance imaging. The accuracy (87.1% for DBAD and 84.3% for ME), sensitivity (93.3% for DBAD and 80.0% for ME), and specificity (85.5% for DBAD and 85.5% for ME) of both DBAD and ME for diagnosing AD were comparable; however, DBAD showed a higher trend in every analysis than ME diagnosis. DBAD may support the clinical decisions of physicians who are not specialized in AD; this may enhance the accessibility of AD diagnosis and treatment.

Estrogen deficiency exacerbates learning and memory deficits associated with glucose metabolism disorder in APP/PS1 double transgenic female mice

Alterations in glucose metabolism occur in the brain in the early stage of Alzheimer's disease (AD), and menopausal women have more severe metabolic dysfunction and are more prone to dementia than men. Although estrogen deficiency-induced changes in glucose metabolism have been previously studied in animal models, their molecular mechanisms in AD remain elusive. To investigate this issue, double transgenic (APP/PS1) female mice were subjected to bilateral ovariectomy at 3 months of age and were sacrificed 1 week, 1 month and 3 months after surgery to simulate early, middle and late postmenopause, respectively. Our analysis demonstrated that estrogen deficiency exacerbates learning and memory deficits in this mouse model of postmenopause. Estrogen deficiency impairs the function of mitochondria in glucose metabolism. It is possible that the occurrence of AD is associated with the aberrant mitochondrial ERβ-mediated IGF-1/IGF-1R/GSK-3β signaling pathway. In this study, we established a potential mechanism for the increased risk of AD in postmenopausal women and proposed a therapeutic target for AD due to postmenopause.

The Potential of Small Molecules to Modulate the Mitochondria–Endoplasmic Reticulum Interplay in Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common neurodegenerative disease affecting a growing number of elderly individuals. No disease-modifying drugs have yet been identified despite over 30 years of research on the topic, showing the need for further research on this multifactorial disease. In addition to the accumulation of amyloid β-peptide (Aβ) and hyperphosphorylated tau (p-tau), several other alterations have been associated with AD such as calcium (Ca2+) signaling, glucose-, fatty acid-, cholesterol-, and phospholipid metabolism, inflammation, and mitochondrial dysfunction. Interestingly, all these processes have been associated with the mitochondria–endoplasmic reticulum (ER) contact site (MERCS) signaling hub. We and others have hypothesized that the dysregulated MERCS function may be one of the main pathogenic pathways driving AD pathology. Due to the variety of biological processes overseen at the MERCS, we believe that they constitute unique therapeutic targets to boost the neuronal function and recover neuronal homeostasis. Thus, developing molecules with the capacity to correct and/or modulate the MERCS interplay can unleash unique therapeutic opportunities for AD. The potential pharmacological intervention using MERCS modulators in different models of AD is currently under investigation. Here, we survey small molecules with the potential to modulate MERCS structures and functions and restore neuronal homeostasis in AD. We will focus on recently reported examples and provide an overview of the current challenges and future perspectives to develop MERCS modulators in the context of translational research.

Sex and gender differences in dementia

The dementia landscape has undergone a striking paradigm shift. The advances in understanding of neurodegeneration and proteinopathies has changed our approach to patients with cognitive impairment. Firstly, it has recently been shown that the various proteinopathies that are the cause of the dementia begin to build up long before the appearance of any obvious symptoms. This has cemented the idea that there is an urgency in diagnosis as it occurs very late in the pathophysiology of these diseases. Secondly, that accurate diagnosis is required to deliver targeted therapies, that is precision medicine. With this latter point, the realization that various factors of a person need to be considered as they may impact the presentation and progression of disease has risen to the forefront. Two of these factors aside from race and age are biological sex and gender (social construct), as both can have tremendous impact on manifestation of disease. This chapter will cover what is known and remains to be known on the interaction of sex and gender with some of the major causes of dementia.

DAFT: A universal module to interweave tabular data and 3D images in CNNs

Prior work on Alzheimer's Disease (AD) has demonstrated that convolutional neural networks (CNNs) can leverage the high-dimensional image information for diagnosing patients. Beside such data-driven approaches, many established biomarkers exist and are typically represented as tabular data, such as demographics, genetic alterations, or laboratory measurements from cerebrospinal fluid. However, little research has focused on the effective integration of tabular data into existing CNN architectures to improve patient diagnosis. We introduce the Dynamic Affine Feature Map Transform (DAFT), a general-purpose module for CNNs that incites or represses high-level concepts learned from a 3D image by conditioning feature maps of a convolutional layer on both a patient's image and tabular clinical information. This is achieved by using an auxiliary neural network that outputs a scaling factor and offset to dynamically apply an affine transformation to the feature maps of a convolutional layer. In our experiments on AD diagnosis and time-to-dementia prediction, we show that the DAFT is highly effective in combining 3D image and tabular information by achieving a mean balanced accuracy of 0.622 for diagnosis, and mean c-index of 0.748 for time-to-dementia prediction, thus outperforming all baseline methods. Finally, our extensive ablation study and empirical experiments reveal that the performance improvement due to the DAFT is robust with respect to many design choices.

Early alterations in brain glucose metabolism and vascular function in a transgenic rat model of Alzheimer's disease

Alteration in brain metabolism predates clinical onset of Alzheimer's Disease (AD). Realizing its potential as an early diagnostic marker, however, requires understanding how early AD metabolic dysregulation manifests on non-invasive brain imaging. We presently utilized magnetic resonance imaging and spectroscopy to map glucose and ketone metabolic profiles and image cerebrovascular function in a rat model of early stage AD - 9-month-old TgF344-AD (TgAD) rats - and their age-matched non-transgenic (nTg) littermates. Compared to the nTg rats, TgAD rats displayed attenuation in global cerebral and hippocampal vasoreactivity to hypercapnia, by 49±17% and 58±19%, respectively, while their functional hyperemia to somatosensory stimulation diminished by 69±5%. To assess brain glucose uptake, rats were fasted overnight and then challenged with an intravenous infusion of 2-deoxy-D-glucose (2DG). Compared to their non-transgenic littermates, TgAD rats exhibited 99±10% and 52±5% smaller glucose uptake in the entorhinal cortex and the hippocampus, respectively. Moreover, hippocampal glucose uptake reduction in male TgAD rats compared to the nTg was 54±36% greater than the reduction seen in female TgAD rats. TgAD rats also showed a 59±42% increase in total choline level in the hippocampus, suggesting increased membrane turnover. In combination with our earlier findings of impaired electrophysiological metrics at this early stage of AD pathology progression, our findings suggest that subtle neuronal function alterations that would be difficult to assess in a clinical population may be accompanied by MRI-detectable changes in brain glucose metabolism and cerebrovascular function.

The TAS Test project: a prospective longitudinal validation of new online motor-cognitive tests to detect preclinical Alzheimer's disease and estimate 5-year risks of cognitive decline and dementia

BACKGROUND

The worldwide prevalence of dementia is rapidly rising. Alzheimer's disease (AD), accounts for 70% of cases and has a 10-20-year preclinical period, when brain pathology covertly progresses before cognitive symptoms appear. The 2020 Lancet Commission estimates that 40% of dementia cases could be prevented by modifying lifestyle/medical risk factors. To optimise dementia prevention effectiveness, there is urgent need to identify individuals with preclinical AD for targeted risk reduction. Current preclinical AD tests are too invasive, specialist or costly for population-level assessments. We have developed a new online test, TAS Test, that assesses a range of motor-cognitive functions and has capacity to be delivered at significant scale. TAS Test combines two innovations: using hand movement analysis to detect preclinical AD, and computer-human interface technologies to enable robust 'self-testing' data collection. The aims are to validate TAS Test to [1] identify preclinical AD, and [2] predict risk of cognitive decline and AD dementia.

METHODS

Aim 1 will be addressed through a cross-sectional study of 500 cognitively healthy older adults, who will complete TAS Test items comprising measures of motor control, processing speed, attention, visuospatial ability, memory and language. TAS Test measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 (p-tau181). Aim 2 will be addressed through a 5-year prospective cohort study of 10,000 older adults. Participants will complete TAS Test annually and subtests of the Cambridge Neuropsychological Test Battery (CANTAB) biennially. 300 participants will undergo in-person clinical assessments. We will use machine learning of motor-cognitive performance on TAS Test to develop an algorithm that classifies preclinical AD risk (p-tau181-defined) and determine the precision to prospectively estimate 5-year risks of cognitive decline and AD.

DISCUSSION

This study will establish the precision of TAS Test to identify preclinical AD and estimate risk of cognitive decline and AD. If accurate, TAS Test will provide a low-cost, accessible enrichment strategy to pre-screen individuals for their likelihood of AD pathology prior to more expensive tests such as blood or imaging biomarkers. This would have wide applications in public health initiatives and clinical trials.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05194787 , 18 January 2022. Retrospectively registered.

GLP-1 Receptor Agonists in Neurodegeneration: Neurovascular Unit in the Spotlight

Defects in brain energy metabolism and proteopathic stress are implicated in age-related degenerative neuronopathies, exemplified by Alzheimer’s disease (AD) and Parkinson’s disease (PD). As the currently available drug regimens largely aim to mitigate cognitive decline and/or motor symptoms, there is a dire need for mechanism-based therapies that can be used to improve neuronal function and potentially slow down the underlying disease processes. In this context, a new class of pharmacological agents that achieve improved glycaemic control via the glucagon-like peptide 1 (GLP-1) receptor has attracted significant attention as putative neuroprotective agents. The experimental evidence supporting their potential therapeutic value, mainly derived from cellular and animal models of AD and PD, has been discussed in several research reports and review opinions recently. In this review article, we discuss the pathological relevance of derangements in the neurovascular unit and the significance of neuron–glia metabolic coupling in AD and PD. With this context, we also discuss some unresolved questions with regard to the potential benefits of GLP-1 agonists on the neurovascular unit (NVU), and provide examples of novel experimental paradigms that could be useful in improving our understanding regarding the neuroprotective mode of action associated with these agents.

Posterior cingulate cortex reveals an expression profile of resilience in cognitively intact elders

The posterior cingulate cortex, a key hub of the default mode network, underlies autobiographical memory retrieval and displays hypometabolic changes early in Alzheimer disease. To obtain an unbiased understanding of the molecular pathobiology of the aged posterior cingulate cortex, we performed RNA sequencing (RNA-seq) on tissue obtained from 26 participants of the Rush Religious Orders Study (11 males/15 females; aged 76-96 years) with a pre-mortem clinical diagnosis of no cognitive impairment and post-mortem neurofibrillary tangle Braak Stages I/II, III, and IV. Transcriptomic data were gathered using next-generation sequencing of RNA extracted from posterior cingulate cortex generating an average of 60 million paired reads per subject. Normalized expression of RNA-seq data was calculated using a global gene annotation and a microRNA profile. Differential expression (DESeq2, edgeR) using Braak staging as the comparison structure isolated genes for dimensional scaling, associative network building and functional clustering. Curated genes were correlated with the Mini-Mental State Examination and semantic, working and episodic memory, visuospatial ability, and a composite Global Cognitive Score. Regulatory mechanisms were determined by co-expression networks with microRNAs and an overlap of transcription factor binding sites. Analysis revealed 750 genes and 12 microRNAs significantly differentially expressed between Braak Stages I/II and III/IV and an associated six groups of transcription factor binding sites. Inputting significantly different gene/network data into a functional annotation clustering model revealed elevated presynaptic, postsynaptic and ATP-related expression in Braak Stages III and IV compared with Stages I/II, suggesting these pathways are integral for cognitive resilience seen in unimpaired elderly subjects. Principal component analysis and Kruskal-Wallis testing did not associate Braak stage with cognitive function. However, Spearman correlations between genes and cognitive test scores followed by network analysis revealed upregulation of classes of synaptic genes positively associated with performance on the visuospatial perceptual orientation domain. Upregulation of key synaptic genes suggests a role for these transcripts and associated synaptic pathways in cognitive resilience seen in elders despite Alzheimer disease pathology and dementia.

18F-FDG PET Imaging in Neurodegenerative Dementing Disorders: Insights into Subtype Classification, Emerging Disease Categories, and Mixed Dementia with Copathologies

Since the invention of ¹⁸F-FDG as a neurochemical tracer in the 1970s, ¹⁸F-FDG PET has been used extensively for dementia research and clinical applications. FDG, a glucose analog, is transported into the brain via glucose transporters and metabolized in a concerted process involving astrocytes and neurons. Although the exact cellular mechanisms of glucose consumption are still under investigation, ¹⁸F-FDG PET can sensitively detect altered neuronal activity due to neurodegeneration. Various neurodegenerative disorders affect different areas of the brain, which can be depicted as altered ¹⁸F-FDG uptake by PET. The spatial patterns and severity of such changes can be reproducibly visualized by statistical mapping technology, which has become widely available in the clinic. The differentiation of 3 major neurodegenerative disorders by ¹⁸F-FDG PET, Alzheimer disease (AD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB), has become standard practice. As the nosology of FTD evolves, frontotemporal lobar degeneration, the umbrella term for pathology affecting the frontal and temporal lobes, has been subclassified clinically into behavioral variant FTD; primary progressive aphasia with 3 subtypes, semantic, nonfluent, and logopenic variants; and movement disorders including progressive supranuclear palsy and corticobasal degeneration. Each of these subtypes is associated with differential ¹⁸F-FDG PET findings. The discovery of new pathologic markers and clinicopathologic correlations via larger autopsy series have led to newly recognized or redefined disease categories, such as limbic-predominant age-related TDP-43 encephalopathy, hippocampus sclerosis, primary age-related tauopathy, and argyrophilic grain disease, which have become a focus of investigations by molecular imaging. These findings need to be integrated into the modern interpretation of ¹⁸F-FDG PET. Recent pathologic investigations also have revealed a high prevalence, particularly in the elderly, of mixed dementia with overlapping and coexisting pathologies. The interpretation of ¹⁸F-FDG PET is evolving from a traditional dichotomous diagnosis of AD versus FTD (or DLB) to a determination of the most predominant underlying pathology that would best explain the patient's symptoms, for the purpose of care guidance. ¹⁸F-FDG PET is a relatively low cost and widely available imaging modality that can help assess various neurodegenerative disorders in a single test and remains the workhorse in clinical dementia evaluation.

Lower Posterior Cingulate N-Acetylaspartate to Creatine Level in Early Detection of Biologically Defined Alzheimer's Disease

Alzheimer’s disease (AD) was recently defined as a biological construct to reflect neuropathologic status, and both abnormal amyloid and tau are required for a diagnosis of AD. We aimed to determine the proton MR spectroscopic (1H-MRS) patterns of the posterior cingulate in biologically defined AD. A total of 68 participants were included in this study, comprising 37 controls, 16 early AD, and 15 late AD, who were classified according to their amyloid and tau status and presence of hippocampal atrophy. Compared with controls, early AD showed lower N-acetylaspartate (NAA)/creatine (Cr) (p = 0.003), whereas late AD showed lower NAA/Cr and higher myoInositol (mI)/Cr (all with p < 0.05). Lower NAA/Cr correlated with a greater global amyloid load (r = −0.47, p < 0.001) and tau load (r = −0.51, p < 0.001) and allowed a discrimination of early AD from controls (p < 0.001). Subgroup analysis showed that NAA/Cr also allowed a differentiation of early AD from controls in the cognitively unimpaired subjects, with an area under the receiver operating characteristics curve, sensitivity, and specificity of 0.96, 100%, and 83.8%, respectively. Lower posterior cingulate NAA levels may help to inform underlying neuropathologic changes in the early stage of AD.

Effects of Moxa Cone Moxibustion Therapy on Cognitive Function and Brain Metabolic Changes in MCI Patients: A Pilot 1H-MRS Study

Objective

To explore the effect of moxa cone moxibustion on N-acetyl aspartate/total creatinine (NAA/tCr) and choline/total creatinine (Cho/tCr) in the bilateral hippocampus (HIP) and bilateral posterior cingulate gyrus (PCG) in patients with mild cognitive impairment (MCI) using hydrogen proton magnetic resonance spectroscopy (¹H-MRS) and to provide imaging basis for moxa cone moxibustion treatment for MCI.

Methods

One hundred eight patients with MCI were served as the MCI group, and 67 age-matched subjects were enrolled as the normal control group. The MCI group was randomized and allocated into acupoint group, drug group, and sham acupoint group, with 36 cases in each group. Some patients in each group withdrew. Finally, 25 cases were included in the acupoint group, 24 cases in the drug group, and 20 cases in the sham acupoint group. The drug group was treated with oral donepezil hydrochloride. The acupoint group and sham acupoint group received moxa cone moxibustion treatment. Mini-mental state exam (MMSE) and Montreal cognitive assessment (MoCA) scores were recorded before intervention, at the end of the first and the second months of intervention, and in the 5th month of follow-up. The NAA/tCr and Cho/tCr ratios in the HIP and PCG were bilaterally measured by ¹H-MRS before and after intervention.

Results

Before intervention, compared with the normal control group, the MMSE and MoCA scores, the Cho/tCr ratio in the right HIP, the NAA/tCr ratio in the bilateral HIP, and the NAA/tCr ratio in the left PCG in the three treatment groups decreased significantly (both p < 0.01), and the NAA/tCr ratio in the right PCG significantly reduced in the acupoint and drug groups (p < 0.05). After two months of treatment, compared with the normal control group, there were no differences in the MoCA scores, the NAA/tCr, and Cho/tCr ratios in the bilateral PCG and bilateral HIP in the three treatment groups (p > 0.05). However, the MMSE scores in the drug group decreased when compared with the acupoint group and normal control group (p < 0.05, p < 0.01). The scores of MMSE and MoCA in the acupoint group and sham acupoint group at all time points were better than those in the drug group, which were similar to those in the normal control group.

Conclusion

Our findings suggest that moxibustion could improve the cognitive function of patients with MCI. The mechanism may be related to the improvement of abnormal brain metabolism in HIP and PCG.

Disrupted coupling between salience network segregation and glucose metabolism is associated with cognitive decline in Alzheimer's disease - A simultaneous resting-state FDG-PET/fMRI study

•

Hybrid PET/MRI was used to explore network segregation and glucose metabolism in AD.

•

DMN, CEN, and SN showed reduced segregation in AD.

•

In salience network, segregation coupled with glucose metabolism in CN group.

•

The coupled segregation and glucose metabolism in CN disappeared in MCI and AD.

•

Reduced segregation and hypometabolism were associated with cognitive impairments.

The aberrant organization and functioning of three core neurocognitive networks (NCNs), i.e., default-mode network (DMN), central executive network (CEN), and salience network (SN), are among the prominent features in Alzheimer’s disease (AD). The dysregulation of both intra- and inter-network functional connectivities (FCs) of the three NCNs contributed to AD-related cognitive and behavioral abnormalities. Brain functional network segregation, integrating intra- and inter-network FCs, is essential for maintaining the energetic efficiency of brain metabolism. The association of brain functional network segregation, together with glucose metabolism, with age-related cognitive decline was recently shown. Yet how these joint functional-metabolic biomarkers relate to cognitive decline along with mild cognitive impairment (MCI) and AD remains to be elucidated. In this study, under the framework of the triple-network model, we performed a hybrid FDG-PET/fMRI study to evaluate the concurrent changes of resting-state brain intrinsic FCs and glucose metabolism of the three NCNs across cognitively normal (CN) (N = 24), MCI (N = 21), and AD (N = 21) groups. Lower network segregation and glucose metabolism were observed in all three NCNs in patients with AD. More interestingly, in the SN, the coupled relationship between network segregation and glucose metabolism existed in the CN group (r = 0.523, p = 0.013) and diminished in patients with MCI (r = 0.431, p = 0.065) and AD (r = 0.079, p = 0.748). Finally, the glucose metabolism of the DMN (r = 0.380, p = 0.017) and the network segregation of the SN (r = 0.363, p = 0.023) were significantly correlated with the general cognitive status of the patients. Our findings suggest that the impaired SN segregation and its uncoupled relationship with glucose metabolism contribute to the cognitive decline in AD.

Design, Synthesis, and Preliminary Evaluation of [68Ga]Ga-NOTA-Insulin as a PET Probe in an Alzheimer's Disease Mouse Model

Aberrant insulin signaling has been considered one of the risk factors for the development of Alzheimer's disease (AD) and has drawn considerable attention from the research community to further study its role in AD pathophysiology. Herein, we describe the development of an insulin-based novel positron emission tomography (PET) probe, [⁶⁸Ga]Ga-NOTA-insulin, to noninvasively study the role of insulin in AD. The developed PET probe [⁶⁸Ga]Ga-NOTA-insulin showed a significantly higher uptake (0.396 ± 0.055 SUV) in the AD mouse brain compared to the normal (0.140 ± 0.027 SUV) mouse brain at 5 min post injection and also showed a similar trend at 10, 15, and 20 min post injection. In addition, [⁶⁸Ga]Ga-NOTA-insulin was found to have a differential uptake in various brain regions at 30 min post injection. Among the brain regions, the cortex, thalamus, brain stem, and cerebellum showed a significantly higher standard uptake value (SUV) of [⁶⁸Ga]Ga-NOTA-insulin in AD mice as compared to normal mice. The inhibition of the insulin receptor (IR) with an insulin receptor antagonist peptide (S961) in normal mice showed a similar brain uptake profile of [⁶⁸Ga]Ga-NOTA-insulin as it was observed in the AD case, suggesting nonfunctional IR in AD and the presence of an alternative insulin uptake route in the absence of a functional IR. The Gjedde-Patlak graphical analysis was also performed to predict the input rate of [⁶⁸Ga]Ga-NOTA-insulin into the brain using MicroPET imaging data and supported the in vivo results. The [⁶⁸Ga]Ga-NOTA-insulin PET probe was successfully synthesized and evaluated in a mouse model of AD in comparison with [¹⁸F]AV1451 and [¹¹C]PIB to noninvasively study the role of insulin in AD pathophysiology.