Regional brain hypometabolism is unrelated to regional amyloid plaque burden

Similarities and differences in dynamic properties of brain networks between internet gaming disorder and tobacco use disorder

BACKGROUND

Internet gaming disorder (IGD) and tobacco use disorder (TUD) are two major addiction disorders that result in substantial financial loss. Identifying the similarities and differences between these two disorders is important to understand substance addiction and behavioral addiction. The current study was designed to compare these two disorders utilizing dynamic analysis.

METHOD

Resting-state data were collected from 35 individuals with IGD, 35 individuals with TUD and 35 healthy controls (HCs). Dynamic coactivation pattern analysis was employed to decipher their dynamic patterns.

RESULTS

IGD participants showed decreased coactivation patterns within the default mode network (DMN) and between the DMN and the salience network (SN). The SN showed reduced coactivation patterns with the executive control network (ECN) and DMN, and the ECN showed decreased coactivation patterns with the DMN. In the TUD group, the DMN exhibited decreased coactivation patterns with the SN, the SN exhibited reduced coactivation patterns with the DMN and ECN, and the ECN showed decreased coactivation patterns with the DMN and within the ECN. Furthermore, the triple network model was fitted to the dynamic properties of the two addiction disorders. Decoding analysis results indicated that addiction-related memory and memory retrieval displayed similar dysfunctions in both addictions.

CONCLUSION

The dynamic characteristics of IGD and TUD suggest that there are similarities in the dynamic features between the SN and DMN and differences in the dynamic features between the DMN and ECN. Our results revealed that the two addiction disorders have dissociable brain mechanisms, indicating that future studies should consider these two addiction disorders as having two separate mechanisms to achieve precise treatment for their individualized targets.

Disrupted mitochondrial response to nutrients is a presymptomatic event in the cortex of the APPSAA knock-in mouse model of Alzheimer's disease

INTRODUCTION

Reduced brain energy metabolism, mammalian target of rapamycin (mTOR) dysregulation, and extracellular amyloid beta (Aβ) oligomer (xcAβO) buildup are some well-known Alzheimer's disease (AD) features; how they promote neurodegeneration is poorly understood. We previously reported that xcAβOs inhibit nutrient-induced mitochondrial activity (NiMA) in cultured neurons. We now report NiMA disruption in vivo.

METHODS

Brain energy metabolism and oxygen consumption were recorded in heterozygous amyloid precursor protein knock-in (APPSAA) mice using two-photon fluorescence lifetime imaging and multiparametric photoacoustic microscopy.

RESULTS

NiMA is inhibited in APPSAA mice before other defects are detected in these Aβ-producing animals that do not overexpress APP or contain foreign DNA inserts into genomic DNA. Glycogen synthase kinase 3 (GSK3β) signals through mTORC1 to regulate NiMA independently of mitochondrial biogenesis. Inhibition of GSK3β with TWS119 stimulates NiMA in cultured human neurons, and mitochondrial activity and oxygen consumption in APPSAA mice.

DISCUSSION

NiMA disruption in vivo occurs before plaques, neuroinflammation, and cognitive decline in APPSAA mice, and may represent an early stage in human AD.

HIGHLIGHTS

Amyloid beta blocks communication between lysosomes and mitochondria in vivo. Nutrient-induced mitochondrial activity (NiMA) is disrupted long before the appearance of Alzheimer's disease (AD) histopathology in heterozygous amyloid precursor protein knock-in (APPSAA/+) mice. NiMA is disrupted long before learning and memory deficits in APPSAA/+ mice. Pharmacological interventions can rescue AD-related NiMA disruption in vivo.

Exploring the Mechanisms and Therapeutic Approaches of Mitochondrial Dysfunction in Alzheimer's Disease: An Educational Literature Review

Alzheimer's disease (AD) presents a significant challenge to global health. It is characterized by progressive cognitive deterioration and increased rates of morbidity and mortality among older adults. Among the various pathophysiologies of AD, mitochondrial dysfunction, encompassing conditions such as increased reactive oxygen production, dysregulated calcium homeostasis, and impaired mitochondrial dynamics, plays a pivotal role. This review comprehensively investigates the mechanisms of mitochondrial dysfunction in AD, focusing on aspects such as glucose metabolism impairment, mitochondrial bioenergetics, calcium signaling, protein tau and amyloid-beta-associated synapse dysfunction, mitophagy, aging, inflammation, mitochondrial DNA, mitochondria-localized microRNAs, genetics, hormones, and the electron transport chain and Krebs cycle. While lecanemab is the only FDA-approved medication to treat AD, we explore various therapeutic modalities for mitigating mitochondrial dysfunction in AD, including antioxidant drugs, antidiabetic agents, acetylcholinesterase inhibitors (FDA-approved to manage symptoms), nutritional supplements, natural products, phenylpropanoids, vaccines, exercise, and other potential treatments.

Aging Brain from a Lifespan Perspective

Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.

Disrupted mitochondrial response to nutrients is a presymptomatic event in the cortex of the APP SAA knock-in mouse model of Alzheimer's disease

Introduction

Reduced brain energy metabolism, mTOR dysregulation, and extracellular amyloid-β oligomer (xcAβO) buildup characterize AD; how they collectively promote neurodegeneration is poorly understood. We previously reported that xcAβOs inhibit N utrient-induced M itochondrial A ctivity (NiMA) in cultured neurons. We now report NiMA disruption in vivo .

Methods

Brain energy metabolism and oxygen consumption were recorded in APP SAA/+ mice using two-photon fluorescence lifetime imaging and multiparametric photoacoustic microscopy.

Results

NiMA is inhibited in APP SAA/+ mice before other defects are detected in these amyloid-β-producing animals that do not overexpress APP or contain foreign DNA inserts into genomic DNA. GSK3β signals through mTORC1 to regulate NiMA independently of mitochondrial biogenesis. Inhibition of GSK3β with lithium or TWS119 stimulates NiMA in cultured human neurons, and mitochondrial activity and oxygen consumption in APP SAA mice.

Conclusion

NiMA disruption in vivo occurs before histopathological changes and cognitive decline in APP SAA mice, and may represent an early stage in human AD.

Substantial Doubt Remains about the Efficacy of Anti-Amyloid Antibodies

With the FDA approval of aducanumab and lecanemab, and with the recent statistically significant phase 3 clinical trial for donanemab, there is growing enthusiasm for anti-amyloid antibodies in the treatment of Alzheimer's disease. Here, we discuss three substantial limitations regarding recent anti-amyloid clinical trials: 1) there is little evidence that amyloid reduction correlates with clinical outcome, 2) the reported efficacy of anti-amyloid therapies may be explained by functional unblinding, and 3) donanemab had no effect on tau burden in its phase 3 trial. Taken together, these observations call into question the efficacy of anti-amyloid therapies.

GLP-1 Analogs, SGLT-2, and DPP-4 Inhibitors: A Triad of Hope for Alzheimer's Disease Therapy

Alzheimer's is a prevalent, progressive neurodegenerative disease marked by cognitive decline and memory loss. The disease's development involves various pathomechanisms, including amyloid-beta accumulation, neurofibrillary tangles, oxidative stress, inflammation, and mitochondrial dysfunction. Recent research suggests that antidiabetic drugs may enhance neuronal survival and cognitive function in diabetes. Given the well-documented correlation between diabetes and Alzheimer's disease and the potential shared mechanisms, this review aimed to comprehensively assess the potential of new-generation anti-diabetic drugs, such as GLP-1 analogs, SGLT-2 inhibitors, and DPP-4 inhibitors, as promising therapeutic approaches for Alzheimer's disease. This review aims to comprehensively assess the potential therapeutic applications of novel-generation antidiabetic drugs, including GLP-1 analogs, SGLT-2 inhibitors, and DPP-4 inhibitors, in the context of Alzheimer's disease. In our considered opinion, antidiabetic drugs offer a promising avenue for groundbreaking developments and have the potential to revolutionize the landscape of Alzheimer's disease treatment.

Licochalcone A: A Potential Multitarget Drug for Alzheimer's Disease Treatment

Licochalcone A (Lico-A) is a flavonoid compound derived from the root of the Glycyrrhiza species, a plant commonly used in traditional Chinese medicine. While the Glycyrrhiza species has shown promise in treating various diseases such as cancer, obesity, and skin diseases due to its active compounds, the investigation of Licochalcone A's effects on the central nervous system and its potential application in Alzheimer's disease (AD) treatment have garnered significant interest. Studies have reported the neuroprotective effects of Lico-A, suggesting its potential as a multitarget compound. Lico-A acts as a PTP1B inhibitor, enhancing cognitive activity through the BDNF-TrkB pathway and exhibiting inhibitory effects on microglia activation, which enables mitigation of neuroinflammation. Moreover, Lico-A inhibits c-Jun N-terminal kinase 1, a key enzyme involved in tau phosphorylation, and modulates the brain insulin receptor, which plays a role in cognitive processes. Lico-A also acts as an acetylcholinesterase inhibitor, leading to increased levels of the neurotransmitter acetylcholine (Ach) in the brain. This mechanism enhances cognitive capacity in individuals with AD. Finally, Lico-A has shown the ability to reduce amyloid plaques, a hallmark of AD, and exhibits antioxidant properties by activating the nuclear factor erythroid 2-related factor 2 (Nrf2), a key regulator of antioxidant defense mechanisms. In the present review, we discuss the available findings analyzing the potential of Lico-A as a neuroprotective agent. Continued research on Lico-A holds promise for the development of novel treatments for cognitive disorders and neurodegenerative diseases, including AD. Further investigations into its multitarget action and elucidation of underlying mechanisms will contribute to our understanding of its therapeutic potential.

JCT, Soder RB, Fornari F. The brain-esophagus axis in subjects with and without obesity assessed by esophageal acid perfusion and functional brain imaging

Background

Gastroesophageal reflux disease (GERD) has a complex pathophysiology and a heterogeneous symptom profile. The brain-esophageal axis in GERD has been studied with functional brain imaging during the last decades, but data from obese patients was just recently reported. A comparison of such a group with non-obese subjects is lacking in the literature. This study aimed to evaluate heartburn perception and brain connectivity responses during esophageal acid stimulation in subjects with and without obesity, controlling for the presence of typical reflux symptoms.

Methods

In this cross-sectional study, 25 patients with obesity (body mass index ≥30 kg/m2) and 46 subjects without obesity underwent functional magnetic resonance imaging (fMRI) of the brain with esophageal water and acid perfusion. The fMRI paradigm and connectivity were assessed.

Results

About two-thirds of the participants had reflux symptoms. Heartburn perception during fMRI did not differ between subjects with and without obesity. The presence of reflux symptoms was associated with lower activation in frontal brain regions during acid perfusion compared to water perfusion. Compared to subjects without obesity, patients with obesity presented significantly lower connectivity within the anterior salience network. Corrected clusters included left caudate, left putamen and left anterior cingulate gyrus.

Conclusions

The brain-esophagus axis showed differences between subjects with and without obesity. Even without symptomatic differences following esophageal acid perfusion, patients with reflux symptoms showed less brain activation in frontal areas, while obese individuals presented lower connectivity within the anterior salience network.

Transcranial stimulation of alpha oscillations modulates brain state dynamics in sustained attention

The brain operates an advanced complex system to support mental activities. Cognition is thought to emerge from dynamic states of the complex brain system, which are organized spatially through large-scale neural networks and temporally via neural synchrony. However, specific mechanisms underlying these processes remain obscure. Applying high-definition alpha-frequency transcranial alternating-current stimulation (HD α-tACS) in a continuous performance task (CPT) during functional resonance imaging (fMRI), we causally elucidate these major organizational architectures in a key cognitive operation-sustained attention. We demonstrated that α-tACS enhanced both electroencephalogram (EEG) alpha power and sustained attention, in a correlated fashion. Akin to temporal fluctuations inherent in sustained attention, our hidden Markov modeling (HMM) of fMRI timeseries uncovered several recurrent, dynamic brain states, which were organized through a few major neural networks and regulated by the alpha oscillation. Specifically, during sustain attention, α-tACS regulated the temporal dynamics of the brain states by suppressing a Task-Negative state (characterized by activation of the default mode network/DMN) and Distraction state (with activation of the ventral attention and visual networks). These findings thus linked dynamic states of major neural networks and alpha oscillations, providing important insights into systems-level mechanisms of attention. They also highlight the efficacy of non-invasive oscillatory neuromodulation in probing the functioning of the complex brain system and encourage future clinical applications to improve neural systems health and cognitive performance.

Accelerated hypometabolism with disease progression associated with faster cognitive decline among amyloid positive patients

Objective

To evaluate the progression of brain glucose metabolism among participants with biological signature of Alzheimer's disease (AD) and its relevance to cognitive decline.

Method

We studied 602 amyloid positive individuals who underwent 18F-fluorodeoxyglucose PET (FDG-PET) scan, 18F-AV-45 amyloid PET (AV45-PET) scan, structural MRI scan and neuropsychological examination, including 116 cognitively normal (CN) participants, 314 participants diagnosed as mild cognitive impairment (MCI), and 172 participants diagnosed as AD dementia. The first FDG-PET scan satisfying the inclusion criteria was considered as the baseline scan. Cross-sectional analysis were conducted with the baseline FDG-PET data to compare the regional differences between diagnostic groups after adjusting confounding factors. Among these participants, 229 participants (55 CN, 139 MCI, and 35 AD dementia) had two-year follow-up FDG-PET data available. Regional glucose metabolism was computed and the progression rates of regional glucose metabolism were derived from longitudinal FDG-PET scans. Then the group differences of regional progression rates were examined to assess whether glucose metabolism deficit accelerates or becomes stable with disease progression. The association of cognitive decline rate with baseline regional glucose metabolism, and progression rate in longitudinal data, were evaluated.

Results

Participants with AD dementia showed substantial glucose metabolism deficit than CN and MCI at left hippocampus, in addition to the traditionally reported frontal and parietal-temporal lobe. More substantial metabolic change was observed with the contrast AD - MCI than the contrast MCI - CN, even after adjusting time duration since cognitive symptom onset. With the longitudinal data, glucose metabolism was observed to decline the most rapidly in the AD dementia group and at a slower rate in MCI. Lower regional glucose metabolism was correlated to faster cognitive decline rate with mild-moderate correlations, and the progression rate was correlated to cognitive decline rate with moderate-large correlations.

Discussion and conclusion

Hippocampus was identified to experience hypometabolism in AD pathology. Hypometabolism accelerates with disease progression toward AD dementia. FDG-PET, particularly longitudinal scans, could potentially help predict how fast cognition declines and assess the impact of treatment in interventional trials.

Virus-Like Cytosolic and Cell-Free Oxidatively Damaged Nucleic Acids Likely Drive Inflammation, Synapse Degeneration, and Neuron Death in Alzheimer's Disease

Oxidative stress, inflammation, and amyloid-β are Alzheimer's disease (AD) hallmarks that cause each other and other AD hallmarks. Most amyloid-β-lowering, antioxidant, anti-inflammatory, and antimicrobial AD clinical trials failed; none stopped or reversed AD. Although signs suggest an infectious etiology, no pathogen accumulated consistently in AD patients. Neuropathology, neuronal cell culture, rodent, genome-wide association, epidemiological, biomarker, and clinical studies, plus analysis using Hill causality criteria and revised Koch's postulates, indicate that the virus-like oxidative damage-associated molecular-pattern (DAMP) cytosolic and cell-free nucleic acids accumulated in AD patients' brains likely drive neuroinflammation, synaptotoxicity, and neurotoxicity. Cytosolic oxidatively-damaged mitochondrial DNA accumulated outside mitochondria dose-dependently in preclinical AD and AD patients' hippocampal neurons, and in AD patients' neocortical neurons but not cerebellar neurons or glia. In oxidatively-stressed neural cells and rodents' brains, cytosolic oxidatively-damaged mitochondrial DNA accumulated and increased antiviral and inflammatory proteins, including cleaved caspase-1, interleukin-1β, and interferon-β. Cytosolic double-stranded RNA and DNA are DAMPs that induce antiviral interferons and/or inflammatory proteins by oligomerizing with various innate-immune pattern-recognition receptors, e.g., cyclic GMP-AMP synthase and the nucleotide-binding-oligomerization-domain-like-receptor-pyrin-domain-containing-3 inflammasome. In oxidatively-stressed neural cells, cytosolic oxidatively-damaged mitochondrial DNA caused synaptotoxicity and neurotoxicity. Depleting mitochondrial DNA prevented these effects. Additionally, cell-free nucleic acids accumulated in AD patients' blood, extracellular vesicles, and senile plaques. Injecting cell-free nucleic acids bound to albumin oligomers into wild-type mice's hippocampi triggered antiviral interferon-β secretion; interferon-β injection caused synapse degeneration. Deoxyribonuclease-I treatment appeared to improve a severe-AD patient's Mini-Mental Status Exam by 15 points. Preclinical and clinical studies of deoxyribonuclease-I and a ribonuclease for AD should be prioritized.

Assessing functional connectivity differences and work-related fatigue in surviving COVID-negative patients

The Coronavirus Disease 2019 (COVID-19) has affected all aspects of life around the world. Neuroimaging evidence suggests the novel coronavirus can attack the central nervous system (CNS), causing cerebro-vascular abnormalities in the brain. This can lead to focal changes in cerebral blood flow and metabolic oxygen consumption rate in the brain. However, the extent and spatial locations of brain alterations in COVID-19 survivors are largely unknown. In this study, we have assessed brain functional connectivity (FC) using resting-state functional MRI (RS-fMRI) in 38 (25 males) COVID patients two weeks after hospital discharge, when PCR negative and 31 (24 males) healthy subjects. FC was estimated using independent component analysis (ICA) and dual regression. When compared to the healthy group, the COVID group demonstrated significantly enhanced FC in the basal ganglia and precuneus networks (family wise error (fwe) corrected, pfwe < 0.05), while, on the other hand, reduced FC in the language network (pfwe < 0.05). The COVID group also experienced higher fatigue levels during work, compared to the healthy group (p < 0.001). Moreover, within the precuneus network, we noticed a significant negative correlation between FC and fatigue scores across groups (Spearman's ρ = -0.47, p = 0.001, r2 = 0.22). Interestingly, this relationship was found to be significantly stronger among COVID survivors within the left parietal lobe, which is known to be structurally and functionally associated with fatigue in other neurological disorders.

A Function of Amyloid-β in Mediating Activity-Dependent Axon/Synapse Competition May Unify Its Roles in Brain Physiology and Pathology

Amyloid-β protein precursor (AβPP) gives rise to amyloid-β (Aβ), a peptide at the center of Alzheimer's disease (AD). AβPP, however, is also an ancient molecule dating back in evolution to some of the earliest forms of metazoans. This suggests a possible ancestral function that may have been obscured by those that evolve later. Based on literature from the functions of Aβ/AβPP in nervous system development, plasticity, and disease, to those of anti-microbial peptides (AMPs) in bacterial competition as well as mechanisms of cell competition uncovered first by Drosophila genetics, I propose that Aβ/AβPP may be part of an ancient mechanism employed in cell competition, which is subsequently co-opted during evolution for the regulation of activity-dependent neural circuit development and plasticity. This hypothesis is supported by foremost the high similarities of Aβ to AMPs, both of which possess unique, opposite (i.e., trophic versus toxic) activities as monomers and oligomers. A large body of data further suggests that the different Aβ oligomeric isoforms may serve as the protective and punishment signals long predicted to mediate activity-dependent axonal/synaptic competition in the developing nervous system and that the imbalance in their opposite regulation of innate immune and glial cells in the brain may ultimately underpin AD pathogenesis. This hypothesis can not only explain the diverse roles observed of Aβ and AβPP family molecules, but also provide a conceptual framework that can unify current hypotheses on AD. Furthermore, it may explain major clinical observations not accounted for and identify approaches for overcoming shortfalls in AD animal modeling.

Integrating mind and body: Investigating differential activation of nodes of the default mode network

BACKGROUND

The default mode network (DMN) is a large-scale brain network tightly correlated with self and self-referential processing, activated by intrinsic tasks and deactivated by externally-directed tasks.

OBJECTIVE

In this study, we aim to investigate the novel approach of default mode activation during progressive muscle relaxation and examine whether differential activation patterns result from the movement of different body parts.

METHODS

We employed neuroimaging to investigate DMN activity during simple body movements, while performing progressive muscle relaxation. We focused on differentiating the neural response between facial movements and movements of other body parts.

RESULTS

Our results show that the movement of different body parts led to deactivation in several DMN nodes, namely the temporal poles, hippocampus, medial prefrontal cortex (mPFC), and posterior cingulate cortex. However, facial movement induced an inverted and selective positive BOLD pattern in some of these areas precisely. Moreover, areas in the temporal poles selective for face movement showed functional connectivity not only with the hippocampus and mPFC but also with the nucleus accumbens.

CONCLUSIONS

Our findings suggest that both conceptual and embodied self-related processes, including body movements during progressive muscle relaxation, may be mapped onto shared brain networks. This could enhance our understanding of how practices like PMR influence DMN activity and potentially offer insights to inform therapeutic strategies that rely on mindful body movements.

Disruption of the brain-esophagus axis in obese patients with heartburn

Obesity is a risk factor for gastroesophageal reflux disease. Studies addressing the brain-esophagus axis in obese are lacking. In obese with and without heartburn, we assessed: (i) the brain responses to esophageal acid perfusion during functional brain imaging; (ii) esophageal impedance baseline before and after acid perfusion; and (iii) abdominal fat distribution. In this exploratory study, 26 obese underwent functional magnetic resonance imaging (fMRI) of the brain combined with esophageal acid perfusion. Esophageal impedance baseline was determined before and after fMRI, followed by tomographic quantification of the abdominal fat. Among 26 obese (54% men, 39.7 years old, 33.5 kg/m2), there were 17 with heartburn and 9 without heartburn. Before fMRI, the esophageal impedance baseline was lower in obese with heartburn than without heartburn (median 1187 vs. 1890 Ω; P = 0.025). After acid perfusion, impedance baseline decreased in obese with heartburn (from 1187 to 899 Ω; P = 0.011) and was lower in this group than in obese without heartburn (899 vs. 1614 Ω; P = 0.001). fMRI task-residual analysis showed that obese with heartburn presented higher functional connectivity in several brain regions than obese without heartburn. Abdominal fat area did not differ between obese with and without heartburn either for total (72.8 ± 4.4% vs. 70.3 ± 6.0%; P = 0.280), subcutaneous (42.2 ± 9.0% vs. 37.4 ± 9.0%; P = 0.226), or visceral (30.6 ± 7.9% vs. 33.0 ± 7.8%; P = 0.484). In subjects with obesity, the brain-esophagus axis is disrupted centrally with higher functional brain connectivity and peripherally with decreased esophageal mucosa integrity in the presence of heartburn.

Ketones: potential to achieve brain energy rescue and sustain cognitive health during ageing

Alzheimer’s disease (AD) is the most common major neurocognitive disorder of ageing. Although largely ignored until about a decade ago, accumulating evidence suggests that deteriorating brain energy metabolism plays a key role in the development and/or progression of AD-associated cognitive decline. Brain glucose hypometabolism is a well-established biomarker in AD but was mostly assumed to be a consequence of neuronal dysfunction and death. However, its presence in cognitively asymptomatic populations at higher risk of AD strongly suggests that it is actually a pre-symptomatic component in the development of AD. The question then arises as to whether progressive AD-related cognitive decline could be prevented or slowed down by correcting or bypassing this progressive ‘brain energy gap’. In this review, we provide an overview of research on brain glucose and ketone metabolism in AD and its prodromal condition – mild cognitive impairment (MCI) – to provide a clearer basis for proposing keto-therapeutics as a strategy for brain energy rescue in AD. We also discuss studies using ketogenic interventions and their impact on plasma ketone levels, brain energetics and cognitive performance in MCI and AD. Given that exercise has several overlapping metabolic effects with ketones, we propose that in combination these two approaches might be synergistic for brain health during ageing. As cause-and-effect relationships between the different hallmarks of AD are emerging, further research efforts should focus on optimising the efficacy, acceptability and accessibility of keto-therapeutics in AD and populations at risk of AD.

Altered large-scale brain network interactions associated with HIV infection and error processing

Altered activity within and between large-scale brain networks has been implicated across various neuropsychiatric conditions. However, patterns of network dysregulation associated with human immunodeficiency virus (HIV), and further impacted by cannabis (CB) use, remain to be delineated. We examined the impact of HIV and CB on resting-state functional connectivity (rsFC) between brain networks and associations with error awareness and error-related network responsivity. Participants (N = 106), stratified into four groups (HIV+/CB+, HIV+/CB-, HIV-/CB+, HIV-/CB-), underwent fMRI scanning while completing a resting-state scan and a modified Go/NoGo paradigm assessing brain responsivity to errors and explicit error awareness. We examined separate and interactive effects of HIV and CB on resource allocation indexes (RAIs), a measure quantifying rsFC strength between the default mode network (DMN), central executive network (CEN), and salience network (SN). We observed reduced RAIs among HIV+ (vs. HIV-) participants, which was driven by increased SN-DMN rsFC. No group differences were detected for SN-CEN rsFC. Increased SN-DMN rsFC correlated with diminished error awareness, but not with error-related network responsivity. These outcomes highlight altered network interactions among participants with HIV and suggest such rsFC dysregulation may persist during task performance, reflecting an inability to disengage irrelevant mental operations, ultimately hindering error processing.

Staging of Alzheimer's disease: past, present, and future perspectives

For many years Alzheimer's disease (AD) was associated with the dementia stage of the disease, the tail end of a pathophysiological process that lasts approximately two decades. Whereas early disease staging assessments focused on progressive deterioration of clinical functioning, brain imaging with positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarker studies highlighted the long preclinical phase of AD in which a cascade of detectable biological abnormalities precede cognitive decline. The recent proliferation of imaging and fluid biomarkers of AD pathophysiology provide an opportunity for the identification of several biological stages in the preclinical phase of AD. We discuss the use of clinical and biomarker information in past, present, and future staging of AD. We highlight potential applications of PET, CSF, and plasma biomarkers for staging AD severity in vivo.

Spatial Distribution and Hierarchical Clustering of β-Amyloid and Glucose Metabolism in Alzheimer’s Disease

Increased amyloid burden and decreased glucose metabolism are important characteristics of Alzheimer’s disease (AD), but their spatial distribution and hierarchical clustering organization are still poorly understood. In this study, we explored the distribution and clustering organization of amyloid and glucose metabolism based on ¹⁸F-florbetapir and ¹⁸F-fluorodeoxyglucose PET data from 68 AD patients and 20 cognitively normal individuals. We found that: (i) cortical regions with highest florbetapir binding were the regions with high glucose metabolism; (ii) the percentage changes of amyloid deposition were greatest in the frontal and temporal areas, and the hypometabolism was greatest in the parietal and temporal areas; (iii) brain areas can be divided into three hierarchical clusters by amyloid and into five clusters by metabolism using a hierarchical clustering approach, indicating that adjacent regions are more likely to be grouped into one sub-network; and (iv) there was a significant positive correlation in any pair of amyloid-amyloid and metabolism-metabolism sub-networks, and a significant negative correlation in amyloid-metabolism sub-networks. This may suggest that the influence forms and brain regions of AD on different pathological markers may not be synchronous, but they are closely related.

Identification of multimodal brain imaging association via a parameter decomposition based sparse multi-view canonical correlation analysis method

BACKGROUND

With the development of noninvasive imaging technology, collecting different imaging measurements of the same brain has become more and more easy. These multimodal imaging data carry complementary information of the same brain, with both specific and shared information being intertwined. Within these multimodal data, it is essential to discriminate the specific information from the shared information since it is of benefit to comprehensively characterize brain diseases. While most existing methods are unqualified, in this paper, we propose a parameter decomposition based sparse multi-view canonical correlation analysis (PDSMCCA) method. PDSMCCA could identify both modality-shared and -specific information of multimodal data, leading to an in-depth understanding of complex pathology of brain disease.

RESULTS

Compared with the SMCCA method, our method obtains higher correlation coefficients and better canonical weights on both synthetic data and real neuroimaging data. This indicates that, coupled with modality-shared and -specific feature selection, PDSMCCA improves the multi-view association identification and shows meaningful feature selection capability with desirable interpretation.

CONCLUSIONS

The novel PDSMCCA confirms that the parameter decomposition is a suitable strategy to identify both modality-shared and -specific imaging features. The multimodal association and the diverse information of multimodal imaging data enable us to better understand the brain disease such as Alzheimer's disease.

Synaptic dysfunction in early phases of Alzheimer's Disease

The synapse is the locus of plasticity where short-term alterations in synaptic strength are converted to long-lasting memories. In addition to the presynaptic terminal and the postsynaptic compartment, a more holistic view of the synapse includes the astrocytes and the extracellular matrix to form a tetrapartite synapse. All these four elements contribute to synapse health and are crucial for synaptic plasticity events and, thereby, for learning and memory processes. Synaptic dysfunction is a common pathogenic trait of several brain disorders. In Alzheimer's Disease, the degeneration of synapses can be detected at the early stages of pathology progression before neuronal degeneration, supporting the hypothesis that synaptic failure is a major determinant of the disease. The synapse is the place where amyloid-β peptides are generated and is the target of the toxic amyloid-β oligomers. All the elements constituting the tetrapartite synapse are altered in Alzheimer's Disease and can synergistically contribute to synaptic dysfunction. Moreover, the two main hallmarks of Alzheimer's Disease, i.e., amyloid-β and tau, act in concert to cause synaptic deficits. Deciphering the mechanisms underlying synaptic dysfunction is relevant for the development of the next-generation therapeutic strategies aimed at modifying the disease progression.

Transcranial stimulation of alpha oscillations up-regulates the default mode network

The default mode network (DMN) is the most-prominent intrinsic connectivity network, serving as a key architecture of the brain's functional organization. Conversely, dysregulated DMN is characteristic of major neuropsychiatric disorders. However, the field still lacks mechanistic insights into the regulation of the DMN and effective interventions for DMN dysregulation. The current study approached this problem by manipulating neural synchrony, particularly alpha (8 to 12 Hz) oscillations, a dominant intrinsic oscillatory activity that has been increasingly associated with the DMN in both function and physiology. Using high-definition alpha-frequency transcranial alternating current stimulation (α-tACS) to stimulate the cortical source of alpha oscillations, in combination with simultaneous electroencephalography and functional MRI (EEG-fMRI), we demonstrated that α-tACS (versus Sham control) not only augmented EEG alpha oscillations but also strengthened fMRI and (source-level) alpha connectivity within the core of the DMN. Importantly, increase in alpha oscillations mediated the DMN connectivity enhancement. These findings thus identify a mechanistic link between alpha oscillations and DMN functioning. That transcranial alpha modulation can up-regulate the DMN further highlights an effective noninvasive intervention to normalize DMN functioning in various disorders.

Recent Developments in Positron Emission Tomography Tracers for Proteinopathies Imaging in Dementia

An early detection and intervention for dementia represent tremendous unmet clinical needs and priorities in society. A shared feature of neurodegenerative diseases causing dementia is the abnormal accumulation and spreading of pathological protein aggregates, which affect the selective vulnerable circuit in a disease-specific pattern. The advancement in positron emission tomography (PET) biomarkers has accelerated the understanding of the disease mechanism and development of therapeutics for Alzheimer's disease and Parkinson's disease. The clinical utility of amyloid-β PET and the clinical validity of tau PET as diagnostic biomarker for Alzheimer's disease continuum have been demonstrated. The inclusion of biomarkers in the diagnostic criteria has introduced a paradigm shift that facilitated the early and differential disease diagnosis and impacted on the clinical management. Application of disease-modifying therapy likely requires screening of patients with molecular evidence of pathological accumulation and monitoring of treatment effect assisted with biomarkers. There is currently still a gap in specific 4-repeat tau imaging probes for 4-repeat tauopathies and α-synuclein imaging probes for Parkinson's disease and dementia with Lewy body. In this review, we focused on recent development in molecular imaging biomarkers for assisting the early diagnosis of proteinopathies (i.e., amyloid-β, tau, and α-synuclein) in dementia and discussed future perspectives.

Lack of association between cortical amyloid deposition and glucose metabolism in early stage Alzheimer´s disease patients

Background

Beta amyloid (Aβ) causes synaptic dysfunction leading to neuronal death. It is still controversial if the magnitude of Aβ deposition correlates with the degree of cognitive impairment. Diagnostic imaging may lead to a better understanding the role of Aβ in development of cognitive deficits. The aim of the present study was to investigate if Aβ deposition in the corresponding brain region of early stage Alzheimer´s disease (AD) patients, directly correlates to neuronal dysfunction and cognitive impairment indicated by reduced glucose metabolism.

Patients and methods

In 30 patients with a clinical phenotype of AD and amyloid positive brain imaging, 2-[18F] fluoro-2-deoxy-d-glucose (FDG) PET/CT was performed. We extracted the average [18F] flutemetamol (Vizamyl) uptake for each of the 16 regions of interest in both hemispheres and computed the standardized uptake value ratio (SUVR) by dividing the Vimazyl intensities by the mean signal of positive and negative control regions. Data were analysed using the R environment for statistical computing and graphics.

Results

Any negative correlation between Aβ deposition and glucose metabolism in 32 dementia related and corresponding brain regions in AD patients was not found. None of the correlation coefficient values were statistically significant different from zero based on two-sided p- value.

Conclusions

Regional Aβ deposition did not correlate negatively with local glucose metabolism in early stage AD patients. Our findings support the role of Aβ as a valid biomarker, but does not permit to conclude that Aβ is a direct cause for an aberrant brain glucose metabolism and neuronal dysfunction.

Human APOE ɛ3 and APOE ɛ4 Alleles Have Differential Effects on Mouse Olfactory Epithelium

BACKGROUND

Alzheimer's disease (AD) is a progressive age-dependent disorder whose risk is affected by genetic factors. Better models for investigating early effects of risk factors such as apolipoprotein E (APOE) genotype are needed.

OBJECTIVE

To determine whether APOE genotype produces neuropathologies in an AD-susceptible neural system, we compared effects of human APOE ɛ3 (E3) and APOE ɛ4 (E4) alleles on the mouse olfactory epithelium.

METHODS

RNA-Seq using the STAR aligner and DESeq2, immunohistochemistry for activated caspase-3 and phosphorylated histone H3, glucose uptake after oral gavage of 2-[1,2-3H (N)]-deoxy-D-glucose, and Seahorse Mito Stress tests on dissociated olfactory mucosal cells.

RESULTS

E3 and E4 olfactory mucosae show 121 differentially abundant mRNAs at age 6 months. These do not indicate differences in cell type proportions, but effects on 17 odorant receptor mRNAs suggest small differences in tissue development. Ten oxidoreductases mRNAs important for cellular metabolism and mitochondria are less abundant in E4 olfactory mucosae but this does not translate into differences in cellular respiration. E4 olfactory mucosae show lower glucose uptake, characteristic of AD susceptibility and consistent with greater expression of the glucose-sensitive gene, Asns. Olfactory sensory neuron apoptosis is unaffected at age 6 months but is greater in E4 mice at 10 months.

CONCLUSION

Effects of human APOE alleles on mouse olfactory epithelium phenotype are apparent in early adulthood, and neuronal loss begins to increase by middle age (10 months). The olfactory epithelium is an appropriate model for the ability of human APOE alleles to modulate age-dependent effects associated with the progression of AD.

Confirming Pathogenicity of the F386L PSEN1 Variant in a South Asian Family With Early-Onset Alzheimer Disease

Objectives

The F386L PSEN1 variant has been reported in 1 Japanese family with limited clinical information. We aimed to prove that F386L is pathogenic by demonstrating that it segregates with early-onset Alzheimer disease (AD).

Methods

Eight individuals in a South Asian family provided DNA for genetic testing and underwent a neurologic examination.

Results

The female proband was diagnosed with AD at age 45 years and died at age 49 years. She had a CSF biomarker profile consistent with AD, and her florbetaben PET scan was amyloid positive with high uptake in the striatum. Her MRI showed no prominent white matter disease. Her affected relatives had an age at onset range of 38–57 years and had imaging and biomarker profiles similar to hers.

Discussion

The results presented here, in conjunction with the prior report, confirm the pathogenicity of F386L. Furthermore, our study highlights the importance of studying families from underrepresented populations to identify or confirm the pathogenicity of rare variants that may be specific to certain genetic ancestries.

Vascular endothelial growth factor associated dissimilar cerebrovascular phenotypes in two different mouse models of Alzheimer's Disease

Vascular perturbations and cerebral hypometabolism are emerging as important components of Alzheimer's disease (AD). While various in vivo imaging modalities have been designed to detect changes of cerebral perfusion and metabolism in AD patients and animal models, study results were often heterogenous with respect to imaging techniques and animal models. We therefore evaluated cerebral perfusion and glucose metabolism of two popular transgenic AD mouse strains, TgCRND8 and 5xFAD, at 7 and 12 months-of-age under identical conditions and analyzed possible molecular mechanisms underlying heterogeneous cerebrovascular phenotypes. Results revealed disparate findings in these two strains, displaying important aspects of AD progression. TgCRND8 mice showed significantly decreased cerebral blood flow and glucose metabolism with unchanged cerebral blood volume (CBV) at 12 months-of-age whereas 5xFAD mice showed unaltered glucose metabolism with significant increase in CBV at 12 months-of-age and a biphasic pattern of early hypoperfusion followed by a rebound to normal cerebral blood flow in late disease. Finally, immunoblotting assays suggested that VEGF dependent vascular tone change may restore normoperfusion and increase CBV in 5xFAD.

Metabolism modulates network synchrony in the aging brain

Brain aging is associated with hypometabolism and global changes in functional connectivity. Using functional MRI (fMRI), we show that network synchrony, a collective property of brain activity, decreases with age. Applying quantitative methods from statistical physics, we provide a generative (Ising) model for these changes as a function of the average communication strength between brain regions. We find that older brains are closer to a critical point of this communication strength, in which even small changes in metabolism lead to abrupt changes in network synchrony. Finally, by experimentally modulating metabolic activity in younger adults, we show how metabolism alone-independent of other changes associated with aging-can provide a plausible candidate mechanism for marked reorganization of brain network topology.

The human connectome in Alzheimer disease - relationship to biomarkers and genetics

The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.

Effects of Mild Excitotoxic Stimulus on Mitochondria Ca2+ Handling in Hippocampal Cultures of a Mouse Model of Alzheimer's Disease

In Alzheimer’s disease (AD), the molecular mechanisms involved in the neurodegeneration are still incompletely defined, though this aspect is crucial for a better understanding of the malady and for devising effective therapies. Mitochondrial dysfunctions and altered Ca²⁺ signaling have long been implicated in AD, though it is debated whether these events occur early in the course of the pathology, or whether they develop at late stages of the disease and represent consequences of different alterations. Mitochondria are central to many aspects of cellular metabolism providing energy, lipids, reactive oxygen species, signaling molecules for cellular quality control, and actively shaping intracellular Ca²⁺ signaling, modulating the intensity and duration of the signal itself. Abnormalities in the ability of mitochondria to take up and subsequently release Ca²⁺ could lead to changes in the metabolism of the organelle, and of the cell as a whole, that eventually result in cell death. We sought to investigate the role of mitochondria and Ca²⁺ signaling in a model of Familial Alzheimer’s disease and found early alterations in mitochondria physiology under stressful condition, namely, reduced maximal respiration, decreased ability to sustain membrane potential, and a slower return to basal matrix Ca²⁺ levels after a mild excitotoxic stimulus. Treatment with an inhibitor of the permeability transition pore attenuated some of these mitochondrial disfunctions and may represent a promising tool to ameliorate mitochondria and cellular functioning in AD and prevent or slow down cell loss in the disease.

Cortical hypometabolism reflects local atrophy and tau pathology in symptomatic Alzheimer's disease

Posterior cortical hypometabolism measured with [18F]-Fluorodeoxyglucose (FDG)-PET is a well-known marker of Alzheimer's disease-related neurodegeneration, but its associations with underlying neuropathological processes are unclear. We assessed cross-sectionally the relative contributions of three potential mechanisms causing hypometabolism in the retrosplenial and inferior parietal cortices: local molecular (amyloid and tau) pathology and atrophy, distant factors including contributions from the degenerating medial temporal lobe or molecular pathology in functionally connected regions, and the presence of the apolipoprotein E (APOE) ε4 allele. Two hundred and thirty-two amyloid-positive cognitively impaired patients from two cohorts (University of California, San Francisco, UCSF, and Alzheimer's Disease Neuroimaging Initiative, ADNI) underwent MRI and PET with FDG, amyloid-PET using [11C]-Pittsburgh Compound B, [18F]-Florbetapir, or [18F]-Florbetaben, and [18F]-Flortaucipir tau-PET within one year. Standard uptake value ratios (SUVR) were calculated using tracer-specific reference regions. Regression analyses were run within cohorts to identify variables associated with retrosplenial or inferior parietal FDG SUVR. On average, ADNI patients were older and were less impaired than UCSF patients. Regional patterns of hypometabolism were similar between cohorts, though there were cohort differences in regional gray matter atrophy. Local cortical thickness and tau-PET (but not amyloid-PET) were independently associated with both retrosplenial and inferior parietal FDG SUVR (ΔR2 = .09 to .21) across cohorts in models that also included age and disease severity (local model). Including medial temporal lobe volume improved the retrosplenial FDG model in ADNI (ΔR2 = .04, p = .008) but not UCSF (ΔR2 < .01, p = .52), and did not improve the inferior parietal models (ΔR2s < .01, ps > .37). Interaction analyses revealed that medial temporal volume was more strongly associated with retrosplenial FDG SUVR at earlier disease stages (p = .06 in UCSF, p = .046 in ADNI). Exploratory analyses across the cortex confirmed overall associations between hypometabolism and local tau pathology and thickness and revealed associations between medial temporal degeneration and hypometabolism in retrosplenial, orbitofrontal, and anterior cingulate cortices. Finally, our data did not support hypotheses of a detrimental effect of pathology in connected regions or of an effect of the APOE ε4 allele in impaired participants. Overall, in two independent groups of patients at symptomatic stages of Alzheimer's disease, cortical hypometabolism mainly reflected structural neurodegeneration and tau, but not amyloid, pathology.

Resting-State Functional MRI for Determining Language Lateralization in Children with Drug-Resistant Epilepsy

BACKGROUND AND PURPOSE

Task-based fMRI is a noninvasive method of determining language dominance; however, not all children can complete language tasks due to age, cognitive/intellectual, or language barriers. Task-free approaches such as resting-state fMRI offer an alternative method. This study evaluated resting-state fMRI for predicting language laterality in children with drug-resistant epilepsy.

MATERIALS AND METHODS

A retrospective review of 43 children with drug-resistant epilepsy who had undergone resting-state fMRI and task-based fMRI during presurgical evaluation was conducted. Independent component analysis of resting-state fMRI was used to identify language networks by comparing the independent components with a language network template. Concordance rates in language laterality between resting-state fMRI and each of the 4 task-based fMRI language paradigms (auditory description decision, auditory category, verbal fluency, and silent word generation tasks) were calculated.

RESULTS

Concordance ranged from 0.64 (95% CI, 0.48-0.65) to 0.73 (95% CI, 0.58-0.87), depending on the language paradigm, with the highest concordance found for the auditory description decision task. Most (78%-83%) patients identified as left-lateralized on task-based fMRI were correctly classified as left-lateralized on resting-state fMRI. No patients classified as right-lateralized or bilateral on task-based fMRI were correctly classified by resting-state fMRI.

CONCLUSIONS

While resting-state fMRI correctly classified most patients who had typical (left) language dominance, its ability to correctly classify patients with atypical (right or bilateral) language dominance was poor. Further study is required before resting-state fMRI can be used clinically for language mapping in the context of epilepsy surgery evaluation in children with drug-resistant epilepsy.

Pathobiolgy and Management of Alzheimer's Disease

Amyloid and tau protein abnormalities have been identified as the main causes of Alzheimer's disease but exact mechanisms remain to be revealed. Especially, amyloid beta and tau protein coupling and neuroinflammatory and neurovascular contributions to Alzheimer disease are quite mysterious. Many animal models and basic biological research are trying to solve these puzzles. Known as aging processes, autophagy, mitochondrial degeneration with generation of reactive oxygen species, and age-related epigenetic modifications are also known to be associated with development of Alzheimer's disease. Environmental factors such as bacterial and viral infections, heavy metal ions, diet, sleep, stress, and gut microbiota are also risk factors of Alzheimer's disease. Future development of preventive and therapeutic modalities may be dependent on the pathobiology of Alzheimer's disease.

Polyphenol-Peptide Interactions in Mitigation of Alzheimer's Disease: Role of Biosurface-Induced Aggregation

Alzheimer's disease (AD) is the most common age-related neurodegenerative disorder, responsible for nearly two-thirds of all dementia cases. In this review, we report the potential AD treatment strategies focusing on natural polyphenol molecules (green chemistry) and more specifically on the inhibition of polyphenol-induced amyloid aggregation/disaggregation pathways: in bulk and on biosurfaces. We discuss how these pathways can potentially alter the structure at the early stages of AD, hence delaying the aggregation of amyloid-β (Aβ) and tau. We also discuss multidisciplinary approaches, combining experimental and modelling methods, that can better characterize the biochemical and biophysical interactions between proteins and phenolic ligands. In addition to the surface-induced aggregation, which can occur on surfaces where protein can interact with other proteins and polyphenols, we suggest a new concept referred as "confinement stability". Here, on the contrary, the adsorption of Aβ and tau on biosurfaces other than Aβ- and tau-fibrils, e.g., red blood cells, can lead to confinement stability that minimizes the aggregation of Aβ and tau. Overall, these mechanisms may participate directly or indirectly in mitigating neurodegenerative diseases, by preventing protein self-association, slowing down the aggregation processes, and delaying the progression of AD.

Neural and Genetic Bases for Human Ability Traits

The judgement of human ability is ubiquitous, from school admissions to job performance reviews. The exact make-up of ability traits, however, is often narrowly defined and lacks a comprehensive basis. We attempt to simplify the spectrum of human ability, similar to how five personality traits are widely believed to describe most personalities. Finding such a basis for human ability would be invaluable since neuropsychiatric disease diagnoses and symptom severity are commonly related to such differences in performance. Here, we identified four underlying ability traits within the National Institutes of Health Toolbox normative data (n = 1, 369): (1) Motor-endurance, (2) Emotional processing, (3) Executive and cognitive function, and (4) Social interaction. We used the Human Connectome Project young adult dataset (n = 778) to show that Motor-endurance and Executive and cognitive function were reliably associated with specific brain functional networks (r ² = 0.305 ± 0.021), and the biological nature of these ability traits was also shown by calculating their heritability (31 and 49%, respectively) from twin data.

β-amyloid: The known unknowns

Alzheimer's disease (AD) stands out as a major disease without any form of preventative or disease modifying therapy. This is not for lack of trying. 33 phase 3 clinical trials of drugs targeting amyloid beta (Aβ) have failed to slow cognitive decline in AD. The field is at a cross-roads about whether to continue anti-Aβ therapy or more actively pursue alternative targets. With the burden of this disease to patients, families, and healthcare budgets growing yearly, the need for disease modifying AD therapies has become one of the highest priorities in all of medicine. While pathology, genetic and biochemical data offer a popular narrative for the causative role of Aβ, there are alternative explanations, and dissenting findings that, now more than ever, warrant thorough reanalysis. This review questions the major assumptions about Aβ on which therapies for AD were premised, and invites renewed interrogation into AD pathogenesis.

Spatial Relationships between Molecular Pathology and Neurodegeneration in the Alzheimer's Disease Continuum

A deeper understanding of the spatial relationships of β-amyloid (Aβ), tau, and neurodegeneration in Alzheimer's disease (AD) could provide insight into pathogenesis and clinical trial design. We included 81 amyloid-positive patients (age 64.4 ± 9.5) diagnosed with AD dementia or mild cognitive impairment due to AD and available 11C-PiB (PIB), 18F-Flortaucipir (FTP),18F-FDG-PET, and 3T-MRI, and 31 amyloid-positive, cognitively normal participants (age 77.3 ± 6.5, no FDG-PET). W-score voxel-wise deviation maps were created and binarized for each imaging-modality (W > 1.64, P < 0.05) adjusting for age, sex, and total intracranial volume (sMRI-only) using amyloid-negative cognitively normal adults. For symptomatic patients, FDG-PET and atrophy W-maps were combined into neurodegeneration maps (ND). Aβ-pathology showed the greatest proportion of cortical gray matter suprathreshold voxels (spatial extent) for both symptomatic and asymptomatic participants (median 94-55%, respectively), followed by tau (79-11%) and neurodegeneration (41-3%). Amyloid > tau > neurodegeneration was the most frequent hierarchy for both groups (79-77%, respectively), followed by tau > amyloid > neurodegeneration (13-10%) and amyloid > neurodegeneration > tau (6-13%). For symptomatic participants, most abnormal voxels were PIB+/FTP+/ND- (median 35%), and the great majority of ND+ voxels (91%) colocalized with molecular pathology. Amyloid spatially exceeded tau and neurodegeneration, with individual heterogeneities. Molecular pathology and neurodegeneration showed a progressive overlap along AD course, indicating shared vulnerabilities or synergistic toxic mechanisms.

Estimating sparse functional connectivity networks via hyperparameter-free learning model

Functional connectivity networks (FCNs) provide a potential way for understanding the brain organizational patterns and diagnosing neurological diseases. Currently, researchers have proposed many methods for FCN construction, among which the most classic example is Pearson's correlation (PC). Despite its simplicity and popularity, PC always results in dense FCNs, and thus a thresholding strategy is usually needed in practice to sparsify the estimated FCNs prior to the network analysis, which undoubtedly causes the problem of threshold parameter selection. As an alternative to PC, sparse representation (SR) can directly generate sparse FCNs due to the l₁ regularizer in the estimation model. However, similar to the thresholding scheme used in PC, it is also challenging to determine suitable values for the regularization parameter in SR. To circumvent the difficulty of parameter selection involved in these traditional methods, we propose a hyperparameter-free method for FCN construction based on the global representation among fMRI time courses. Interestingly, the proposed method can automatically generate sparse FCNs, without any thresholding or regularization parameters. To verify the effectiveness of the proposed method, we conduct experiments to identify subjects with mild cognitive impairment (MCI) and Autism spectrum disorder (ASD) from normal controls (NCs) based on the estimated FCNs. Experimental results on two benchmark databases demonstrate that the achieved classification performance of our proposed scheme is comparable to four conventional methods.

Spatially Distributed Amyloid-β Reduces Glucose Metabolism in Mild Cognitive Impairment

Background:

Several positron emission tomography (PET) studies have explored the relationship between amyloid-β (Aβ), glucose metabolism, and the APOEɛ4 genotype. It has been reported that APOEɛ4, and not aggregated Aβ, contributes to glucose hypometabolism in pre-clinical stages of Alzheimer’s disease (AD) pathology.

Objective:

We hypothesize that typical measurements of Aβ taken either from composite regions-of-interest with relatively high burden actually cover significant patterns of the relationship with glucose metabolism. In contrast, spatially weighted measures of Aβ are more related to glucose metabolism in cognitively normal (CN) aging and mild cognitive impairment (MCI).

Methods:

We have generated a score of amyloid burden based on a joint singular value decomposition (SVD) of the cross-correlation structure between glucose metabolism, as measured by [¹⁸F]2-fluoro-2-deoxyglucose (FDG) PET, and Aβ, as measured by [¹⁸F]florbetapir PET, from the Alzheimer’s Disease Neuroimaging Initiative study. This SVD-based score reveals cortical regions where a reduced glucose metabolism is maximally correlated with distributed patterns of Aβ.

Results:

From an older population of CN and MCI subjects, we found that the SVD-based Aβ score was significantly correlated with glucose metabolism in several cortical regions. Additionally, the corresponding Aβ network has hubs that contribute to distributed glucose hypometabolism, which, in turn, are not necessarily foci of Aβ deposition.

Conclusions:

Our approach uncovered hidden patterns of the glucose metabolism-Aβ relationship. We showed that the SVD-based Aβ score produces a stronger relationship with decreasing glucose metabolism than either APOEɛ4 genotype or global measures of Aβ burden.

Associating Multi-Modal Brain Imaging Phenotypes and Genetic Risk Factors via a Dirty Multi-Task Learning Method

Brain imaging genetics becomes more and more important in brain science, which integrates genetic variations and brain structures or functions to study the genetic basis of brain disorders. The multi-modal imaging data collected by different technologies, measuring the same brain distinctly, might carry complementary information. Unfortunately, we do not know the extent to which the phenotypic variance is shared among multiple imaging modalities, which further might trace back to the complex genetic mechanism. In this paper, we propose a novel dirty multi-task sparse canonical correlation analysis (SCCA) to study imaging genetic problems with multi-modal brain imaging quantitative traits (QTs) involved. The proposed method takes advantages of the multi-task learning and parameter decomposition. It can not only identify the shared imaging QTs and genetic loci across multiple modalities, but also identify the modality-specific imaging QTs and genetic loci, exhibiting a flexible capability of identifying complex multi-SNP-multi-QT associations. Using the state-of-the-art multi-view SCCA and multi-task SCCA, the proposed method shows better or comparable canonical correlation coefficients and canonical weights on both synthetic and real neuroimaging genetic data. In addition, the identified modality-consistent biomarkers, as well as the modality-specific biomarkers, provide meaningful and interesting information, demonstrating the dirty multi-task SCCA could be a powerful alternative method in multi-modal brain imaging genetics.

Selective neuronal vulnerability in Alzheimer's disease

Alzheimer's disease (AD) is defined by a deficiency in specific behavioural and/or cognitive domains, pointing to selective vulnerabilities of specific neurons from different brain regions. These vulnerabilities can be compared across neuron subgroups to identify the most vulnerable neuronal types, regions, and time points for further investigation. Thus, the relevant organizational frameworks for brain subgroups will hold great values for a clear understanding of the progression in AD. Presently, the neuronal vulnerability has yet urgently required to be elucidated as not yet been clearly defined. It is suggested that cell-autonomous and non-cell-autonomous mechanisms can affect the neuronal vulnerability to stressors, and in turn modulates AD progression. This review examines cell-autonomous and non-cell-autonomous mechanisms that contribute to the neuronal vulnerability. Collectively, the cell-autonomous mechanisms seem to be the primary drivers responsible for initiating specific stressor-related neuronal vulnerability with pathological changes in certain brain areas, which then utilize non-cell-autonomous mechanisms and result in subsequent progression of AD. In summary, this article has provided a new perspective on the preventative and therapeutic options for AD.

Dysregulation of cofilin-1 activity-the missing link between herpes simplex virus type-1 infection and Alzheimer's disease

Alzheimer's disease (AD) is a multifactorial disease triggered by environmental factors in combination with genetic predisposition. Infectious agents, in particular herpes simplex virus type 1 (HSV-1), are gradually being recognised as important factors affecting the development of AD. However, the mechanism linking HSV-1 and AD remains unknown. Of note, HSV-1 manipulates the activity of cofilin-1 to ensure their efficient infection in neuron cells. Cofilin-1, the main regulator of actin cytoskeleton reorganization, is implicating for the plastic of dendritic spines and axon regeneration of neuronal cells. Moreover, dysfunction of cofilin-1 is observed in most AD patients, as well as in mice with AD and ageing. Further, inhibition of cofilin-1 activity ameliorates the host cognitive impairment in an animal model of AD. Together, dysregulation of cofilin-1 led by HSV-1 infection is a potential link between HSV-1 and AD. Herein, we critically summarize the role of cofilin-1-mediated actin dynamics in both HSV-1 infection and AD, respectively. We also propose several hypotheses regarding the connecting roles of cofilin-1 dysregulation in HSV-1 infection and AD. Our review provides a foundation for future studies targeting individuals carrying HSV-1 in combination with cofilin-1 to promote a more individualised approach for treatment and prevention of AD.

Fine-grain atlases of functional modes for fMRI analysis

Population imaging markedly increased the size of functional-imaging datasets, shedding new light on the neural basis of inter-individual differences. Analyzing these large data entails new scalability challenges, computational and statistical. For this reason, brain images are typically summarized in a few signals, for instance reducing voxel-level measures with brain atlases or functional modes. A good choice of the corresponding brain networks is important, as most data analyses start from these reduced signals. We contribute finely-resolved atlases of functional modes, comprising from 64 to 1024 networks. These dictionaries of functional modes (DiFuMo) are trained on millions of fMRI functional brain volumes of total size 2.4 ​TB, spanned over 27 studies and many research groups. We demonstrate the benefits of extracting reduced signals on our fine-grain atlases for many classic functional data analysis pipelines: stimuli decoding from 12,334 brain responses, standard GLM analysis of fMRI across sessions and individuals, extraction of resting-state functional-connectomes biomarkers for 2500 individuals, data compression and meta-analysis over more than 15,000 statistical maps. In each of these analysis scenarii, we compare the performance of our functional atlases with that of other popular references, and to a simple voxel-level analysis. Results highlight the importance of using high-dimensional "soft" functional atlases, to represent and analyze brain activity while capturing its functional gradients. Analyses on high-dimensional modes achieve similar statistical performance as at the voxel level, but with much reduced computational cost and higher interpretability. In addition to making them available, we provide meaningful names for these modes, based on their anatomical location. It will facilitate reporting of results.

APOE and metabolic dysfunction in Alzheimer's disease

The strongest genetic risk factor for sporadic Alzheimer's disease (AD) is carriage of the E4 allele of APOE. Metabolic dysfunction also increases risk of dementia and AD. Facing a need for effective therapies and an aging global population, studies aimed at uncovering new therapeutic targets for AD have become critical. Insight into the biology underlying the effects of E4 and metabolic impairment on the brain may lead to novel therapies to reduce AD risk. An understudied hallmark of both AD patients and E4 individuals is a common metabolic impairment-cerebral glucose hypometabolism. This is a robust and replicated finding in humans, and begins decades prior to cognitive decline. Possession of E4 also appears to alter several other aspects of cerebral glucose metabolism, fatty acid metabolism, and management of oxidative stress through the pentose phosphate pathway. A critical knowledge gap in AD is the mechanism by which APOE alters cerebral metabolism and clarification as to its relevance to AD risk. Facing a need for effective therapies, studies aimed at uncovering new therapeutic targets have become critical. One such approach is to gain a better understanding of the metabolic mechanisms that may underlie E4-associated cognitive dysfunction and AD risk.

Topographical distribution of Aβ predicts progression to dementia in Aβ positive mild cognitive impairment

INTRODUCTION

Abnormal brain amyloid beta (Aβ) is typically assessed in vivo using global concentrations from cerebrospinal fluid and positron emission tomography (PET). However, it is unknown whether the assessment of the topographical distribution of Aβ pathology can provide additional information to identify, among global Aβ positive individuals, those destined for dementia.

METHODS

We studied 260 amnestic mild cognitive impairment (MCI) subjects who were Aβ-PET positive with [18F]florbetapir. Using [18F]florbetapir, we assessed the percentage of voxels sowing Aβ abnormality as well as the standardized uptake value ratio (SUVR) values across brain regions. Regressions tested the predictive effect of Aβ on progression to dementia over 2 years.

RESULTS

Neither global nor regional [18F]florbetapir SUVR concentrations predicted progression to dementia. In contrast, the spatial extent of Aβ pathology in regions comprising the default mode network was highly associated with the development of dementia over 2 years.

DISCUSSION

These results highlight that the regional distribution of Aβ abnormality may provide important complementary information at an individual level regarding the likelihood of Aβ positive MCI to progress to dementia.

Mitochondria dysfunction in the pathogenesis of Alzheimer's disease: recent advances

Alzheimer's disease (AD) is one of the most prevalent neurodegenerative diseases, characterized by impaired cognitive function due to progressive loss of neurons in the brain. Under the microscope, neuronal accumulation of abnormal tau proteins and amyloid plaques are two pathological hallmarks in affected brain regions. Although the detailed mechanism of the pathogenesis of AD is still elusive, a large body of evidence suggests that damaged mitochondria likely play fundamental roles in the pathogenesis of AD. It is believed that a healthy pool of mitochondria not only supports neuronal activity by providing enough energy supply and other related mitochondrial functions to neurons, but also guards neurons by minimizing mitochondrial related oxidative damage. In this regard, exploration of the multitude of mitochondrial mechanisms altered in the pathogenesis of AD constitutes novel promising therapeutic targets for the disease. In this review, we will summarize recent progress that underscores the essential role of mitochondria dysfunction in the pathogenesis of AD and discuss mechanisms underlying mitochondrial dysfunction with a focus on the loss of mitochondrial structural and functional integrity in AD including mitochondrial biogenesis and dynamics, axonal transport, ER-mitochondria interaction, mitophagy and mitochondrial proteostasis.

Gaussian Graphical Models Reveal Inter-Modal and Inter-Regional Conditional Dependencies of Brain Alterations in Alzheimer's Disease

Alzheimer's disease (AD) is characterized by a sequence of pathological changes, which are commonly assessed in vivo using various brain imaging modalities such as magnetic resonance imaging (MRI) and positron emission tomography (PET). Currently, the most approaches to analyze statistical associations between regions and imaging modalities rely on Pearson correlation or linear regression models. However, these models are prone to spurious correlations arising from uninformative shared variance and multicollinearity. Notably, there are no appropriate multivariate statistical models available that can easily integrate dozens of multicollinear variables derived from such data, being able to utilize the additional information provided from the combination of data sources. Gaussian graphical models (GGMs) can estimate the conditional dependency from given data, which is conceptually expected to closely reflect the underlying causal relationships between various variables. Hence, we applied GGMs to assess multimodal regional brain alterations in AD. We obtained data from N = 972 subjects from the Alzheimer's Disease Neuroimaging Initiative. The mean amyloid load (AV45-PET), glucose metabolism (FDG-PET), and gray matter volume (MRI) were calculated for each of the 108 cortical and subcortical brain regions. GGMs were estimated using a Bayesian framework for the combined multimodal data and the resulted conditional dependency networks were compared to classical covariance networks based on Pearson correlation. Additionally, graph-theoretical network statistics were calculated to determine network alterations associated with disease status. The resulting conditional dependency matrices were much sparser (≈10% density) than Pearson correlation matrices (≈50% density). Within imaging modalities, conditional dependency networks yielded clusters connecting anatomically adjacent regions. For the associations between different modalities, only few region-specific connections were detected. Network measures such as small-world coefficient were significantly altered across diagnostic groups, with a biphasic u-shape trajectory, i.e., increased small-world coefficient in early mild cognitive impairment (MCI), similar values in late MCI, and decreased values in AD dementia patients compared to cognitively normal controls. In conclusion, GGMs removed commonly shared variance among multimodal measures of regional brain alterations in MCI and AD, and yielded sparser matrices compared to correlation networks based on the Pearson coefficient. Therefore, GGMs may be used as alternative to thresholding-approaches typically applied to correlation networks to obtain the most informative relations between variables.

ApoE and cerebral insulin: Trafficking, receptors, and resistance

Central nervous system (CNS) insulin resistance is associated with Alzheimer's disease (AD). In addition, the apolipoprotein E4 (apoE4) isoform is a risk factor for AD. The connection between these two factors in relation to AD is being actively explored. We summarize this literature with a focus on the transport of insulin and apoE across the blood-brain barrier (BBB) and into the CNS, the impact of apoE and insulin on the BBB, and the interactions between apoE, insulin, and the insulin receptor once present in the CNS. We highlight how CNS insulin resistance is apparent in AD and potential ways to overcome this resistance by repurposing currently approved drugs, with apoE genotype taken into consideration as the treatment response following most interventions is apoE isoform-dependent. This review is part of a special issue focusing on apoE in AD and neurodegeneration.

Functional dedifferentiation of associative resting state networks in older adults - A longitudinal study

Healthy aging is associated with weaker functional connectivity within resting state brain networks and stronger functional interaction between these networks. This phenomenon has been characterized as reduced functional segregation and has been investigated mainly in cross-sectional studies. Here, we used a longitudinal dataset which consisted of four occasions of resting state fMRI and psychometric cognitive ability data, collected from a sample of healthy older adults (baseline N = 232, age range: 64-87 y, age M = 70.8 y), to investigate the functional segregation of several well-defined resting state networks encompassing the whole brain. We characterized the ratio of within-network and between-network correlations via the well-established segregation index. Our findings showed a decrease over a 4-year interval in the functional segregation of the default mode, frontoparietal control and salience ventral attention networks. In contrast, we showed an increase in the segregation of the limbic network over the same interval. More importantly, the rate of change in functional segregation of the frontoparietal control network was associated with the rate of change in processing speed. These findings support the hypothesis of functional dedifferentiation in healthy aging as well as its role in cognitive function in elderly.