Left lateralized cerebral glucose metabolism declines in amyloid-β positive persons with mild cognitive impairment

Pathophysiological significance and modulation of the transient receptor potential canonical 3 ion channel

Transient receptor potential canonical 3 (TRPC3) protein belongs to the TRP family of nonselective cation channels. Its activation occurs by signaling through a G protein-coupled receptor (GPCR) and a phospholipase C-dependent (PLC) pathway. Perturbations in the expression of TRPC3 are associated with a plethora of pathophysiological conditions responsible for disorders of the cardiovascular, immune, and central nervous systems. The recently solved cryo-EM structure of TRPC3 provides detailed inputs about the underlying mechanistic aspects of the channel, which in turn enables more efficient ways of designing small-molecule modulators. Pharmacologically targeting TRPC3 in animal models has demonstrated great efficacy in treating diseases including cancers, neurological disorders, and cardiovascular diseases. Despite extensive scientific evidence supporting some strong correlations between the expression and activity of TRPC3 and various pathophysiological conditions, therapeutic strategies based on its pharmacological modulations have not led to clinical trials. The development of small-molecule TRPC3 modulators with high safety, sufficient brain penetration, and acceptable drug-like profiles remains in progress. Determining the pathological mechanisms for TRPC3 involvement in human diseases and understanding the requirements for a drug-like TRPC3 modulator will be valuable in advancing small-molecule therapeutics to future clinical trials. In this review, we provide an overview of the origin and activation mechanism of TRPC3 channels, diseases associated with irregularities in their expression, and new development in small-molecule modulators as potential therapeutic interventions for treating TRPC3 channelopathies.

Glycometabolic Reprogramming of Microglia in Neurodegenerative Diseases: Insights from Neuroinflammation

Neurodegenerative diseases (ND) are conditions defined by progressive deterioration of the structure and function of the nervous system. Some major examples include Alzheimer's disease (AD), Parkinson's disease (PD), and Amyotrophic lateral sclerosis (ALS). These diseases lead to various dysfunctions, like impaired cognition, memory, and movement. Chronic neuroinflammation may underlie numerous neurodegenerative disorders. Microglia, an important immunocell in the brain, plays a vital role in defending against neuroinflammation. When exposed to different stimuli, microglia are activated and assume different phenotypes, participating in immune regulation of the nervous system and maintaining tissue homeostasis. The immunological activity of activated microglia is affected by glucose metabolic alterations. However, in the context of chronic neuroinflammation, specific alterations of microglial glucose metabolism and their mechanisms of action remain unclear. Thus, in this paper, we review the glycometabolic reprogramming of microglia in ND. The key molecular targets and main metabolic pathways are the focus of this research. Additionally, this study explores the mechanisms underlying microglial glucose metabolism reprogramming in ND and offers an analysis of the most recent therapeutic advancements. The ultimate aim is to provide insights into the development of potential treatments for ND.

Redox imbalance and metabolic defects in the context of Alzheimer disease

Redox reactions play a critical role for intracellular processes, including pathways involved in metabolism and signaling. Reactive oxygen species (ROS) act either as second messengers or generators of protein modifications, fundamental mechanisms for signal transduction. Disturbance of redox homeostasis is associated with many disorders. Among these, Alzheimer's disease is a neurodegenerative pathology that presents hallmarks of oxidative damage such as increased ROS production, decreased activity of antioxidant enzymes, oxidative modifications of macromolecules, and changes in mitochondrial homeostasis. Interestingly, alteration of redox homeostasis is closely associated with defects of energy metabolism, involving both carbohydrates and lipids, the major energy fuels for the cell. As the brain relies exclusively on glucose metabolism, defects of glucose utilization represent a harmful event for the brain. During aging, a progressive perturbation of energy metabolism occurs resulting in brain hypometabolism. This condition contributes to increase neuronal cell vulnerability ultimately resulting in cognitive impairment. The current review discusses the crosstalk between alteration of redox homeostasis and brain energy defects that seems to act in concert in promoting Alzheimer's neurodegeneration.

Mitochondria in Alzheimer's Disease Pathogenesis

Alzheimer's disease (AD) is a progressive and incurable neurodegenerative disorder that primarily affects persons aged 65 years and above. It causes dementia with memory loss and deterioration in thinking and language skills. AD is characterized by specific pathology resulting from the accumulation in the brain of extracellular plaques of amyloid-β and intracellular tangles of phosphorylated tau. The importance of mitochondrial dysfunction in AD pathogenesis, while previously underrecognized, is now more and more appreciated. Mitochondria are an essential organelle involved in cellular bioenergetics and signaling pathways. Mitochondrial processes crucial for synaptic activity such as mitophagy, mitochondrial trafficking, mitochondrial fission, and mitochondrial fusion are dysregulated in the AD brain. Excess fission and fragmentation yield mitochondria with low energy production. Reduced glucose metabolism is also observed in the AD brain with a hypometabolic state, particularly in the temporo-parietal brain regions. This review addresses the multiple ways in which abnormal mitochondrial structure and function contribute to AD. Disruption of the electron transport chain and ATP production are particularly neurotoxic because brain cells have disproportionately high energy demands. In addition, oxidative stress, which is extremely damaging to nerve cells, rises dramatically with mitochondrial dyshomeostasis. Restoring mitochondrial health may be a viable approach to AD treatment.

Understanding the multifaceted role of miRNAs in Alzheimer's disease pathology

Small non-coding RNAs (miRNAs) regulate gene expression by binding to mRNA and mediating its degradation or inhibiting translation. Since miRNAs can regulate the expression of several genes, they have multiple roles to play in biological processes and human diseases. The majority of miRNAs are known to be expressed in the brain and are involved in synaptic functions, thus marking their presence and role in major neurodegenerative disorders, including Alzheimer's disease (AD). In AD, amyloid beta (Aβ) plaques and neurofibrillary tangles (NFTs) are known to be the major hallmarks. The clearance of Aβ and tau is known to be associated with miRNA dysregulation. In addition, the β-site APP cleaving enzyme (BACE 1), which cleaves APP to form Aβ, is also found to be regulated by miRNAs, thus directly affecting Aβ accumulation. Growing evidences suggest that neuroinflammation can be an initial event in AD pathology, and miRNAs have been linked with the regulation of neuroinflammation. Inflammatory disorders have also been associated with AD pathology, and exosomes associated with miRNAs are known to regulate brain inflammation, suggesting for the role of systemic miRNAs in AD pathology. Several miRNAs have been related in AD, years before the clinical symptoms appear, most of which are associated with regulating the cell cycle, immune system, stress responses, cellular senescence, nerve growth factor (NGF) signaling, and synaptic regulation. Phytochemicals, especially polyphenols, alter the expression of various miRNAs by binding to miRNAs or binding to the transcriptional activators of miRNAs, thus control/alter various metabolic pathways. Awing to the sundry biological processes being regulated by miRNAs in the brain and regulation of expression of miRNAs via phytochemicals, miRNAs and the regulatory bioactive phytochemicals can serve as therapeutic agents in the treatment and management of AD.

FDG-PET markers of heterogeneity and different risk of progression in amnestic MCI

INTRODUCTION

Amnestic mild cognitive impairment (aMCI) is emerging as a heterogeneous condition.

METHODS

We looked at a cohort of N = 207 aMCI subjects, with baseline fluorodeoxyglucose positron emission tomography (FDG-PET), T1 magnetic resonance imaging, cerebrospinal fluid (CSF), apolipoprotein E (APOE), and neuropsychological assessment. An algorithm based on FDG-PET hypometabolism classified each subject into subtypes, then compared biomarker measures and clinical progression.

RESULTS

Three subtypes emerged: hippocampal sparing-cortical hypometabolism, associated with younger age and the highest level of Alzheimer's disease (AD)-CSF pathology; hippocampal/cortical hypometabolism, associated with a high percentage of APOE ε3/ε4 or ε4/ε4 carriers; medial-temporal hypometabolism, characterized by older age, the lowest AD-CSF pathology, the most severe hippocampal atrophy, and a benign course. Within the whole cohort, the severity of temporo-parietal hypometabolism, correlated with AD-CSF pathology and marked the rate of progression of cognitive decline.

DISCUSSION

FDG-PET can distinguish clinically comparable aMCI at single-subject level with different risk of progression to AD dementia or stability. The obtained results can be useful for the optimization of pharmacological trials and automated-classification models.

HIGHLIGHTS

Algorithm based on FDG-PET hypometabolism demonstrates distinct subtypes across aMCI; Three different subtypes show heterogeneous biological profiles and risk of progression; The cortical hypometabolism is associated with AD pathology and cognitive decline; MTL hypometabolism is associated with the lowest conversion rate and CSF-AD pathology.

Mitochondrial Targeting against Alzheimer's Disease: Lessons from Hibernation

Alzheimer's disease (AD) is the most common cause of dementia worldwide and yet remains without effective therapy. Amongst the many proposed causes of AD, the mitochondrial cascade hypothesis is gaining attention. Accumulating evidence shows that mitochondrial dysfunction is a driving force behind synaptic dysfunction and cognitive decline in AD patients. However, therapies targeting the mitochondria in AD have proven unsuccessful so far, and out-of-the-box options, such as hibernation-derived mitochondrial mechanisms, may provide valuable new insights. Hibernators uniquely and rapidly alternate between suppression and re-activation of the mitochondria while maintaining a sufficient energy supply and without acquiring ROS damage. Here, we briefly give an overview of mitochondrial dysfunction in AD, how it affects synaptic function, and why mitochondrial targeting in AD has remained unsuccessful so far. We then discuss mitochondria in hibernation and daily torpor in mice, covering current advancements in hibernation-derived mitochondrial targeting strategies. We conclude with new ideas on how hibernation-derived dual mitochondrial targeting of both the ATP and ROS pathways may boost mitochondrial health and induce local synaptic protein translation to increase synaptic function and plasticity. Further exploration of these mechanisms may provide more effective treatment options for AD in the future.

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.

ApoE4-dependent lysosomal cholesterol accumulation impairs mitochondrial homeostasis and oxidative phosphorylation in human astrocytes

Recent developments in genome sequencing have expanded the knowledge of genetic factors associated with late-onset Alzheimer's disease (AD). Among them, genetic variant ε4 of the APOE gene (APOE4) confers the greatest disease risk. Dysregulated glucose metabolism is an early pathological feature of AD. Using isogenic ApoE3 and ApoE4 astrocytes derived from human induced pluripotent stem cells, we find that ApoE4 increases glycolytic activity but impairs mitochondrial respiration in astrocytes. Ultrastructural and autophagy flux analyses show that ApoE4-induced cholesterol accumulation impairs lysosome-dependent removal of damaged mitochondria. Acute treatment with cholesterol-depleting agents restores autophagic activity, mitochondrial dynamics, and associated proteomes, and extended treatment rescues mitochondrial respiration in ApoE4 astrocytes. Taken together, our study provides a direct link between ApoE4-induced lysosomal cholesterol accumulation and abnormal oxidative phosphorylation.

Association of the fibronectin type III domain-containing protein 5 rs1746661 single nucleotide polymorphism with reduced brain glucose metabolism in elderly humans

Fibronectin type III domain-containing protein 5 (FNDC5) and its derived hormone, irisin, have been associated with metabolic control in humans, with described FNDC5 single nucleotide polymorphisms being linked to obesity and metabolic syndrome. Decreased brain FNDC5/irisin has been reported in subjects with dementia due to Alzheimer's disease. Since impaired brain glucose metabolism develops in ageing and is prominent in Alzheimer's disease, here, we examined associations of a single nucleotide polymorphism in the FNDC5 gene (rs1746661) with brain glucose metabolism and amyloid-β deposition in a cohort of 240 cognitively unimpaired and 485 cognitively impaired elderly individuals from the Alzheimer's Disease Neuroimaging Initiative. In cognitively unimpaired elderly individuals harbouring the FNDC5 rs1746661(T) allele, we observed a regional reduction in low glucose metabolism in memory-linked brain regions and increased brain amyloid-β PET load. No differences in cognition or levels of cerebrospinal fluid amyloid-β42, phosphorylated tau and total tau were observed between FNDC5 rs1746661(T) allele carriers and non-carriers. Our results indicate that a genetic variant of FNDC5 is associated with low brain glucose metabolism in elderly individuals and suggest that FNDC5 may participate in the regulation of brain metabolism in brain regions vulnerable to Alzheimer's disease pathophysiology. Understanding the associations between genetic variants in metabolism-linked genes and metabolic brain signatures may contribute to elucidating genetic modulators of brain metabolism in humans.

An enquiry to the role of CB1 receptors in neurodegeneration

Neurodegenerative disorders are debilitating conditions that impair patient quality of life and that represent heavy social-economic burdens to society. Whereas the root of some of these brain illnesses lies in autosomal inheritance, the origin of most of these neuropathologies is scantly understood. Similarly, the cellular and molecular substrates explaining the progressive loss of brain functions remains to be fully described too. Indeed, the study of brain neurodegeneration has resulted in a complex picture, composed of a myriad of altered processes that include broken brain bioenergetics, widespread neuroinflammation and aberrant activity of signaling pathways. In this context, several lines of research have shown that the endocannabinoid system (ECS) and its main signaling hub, the type-1 cannabinoid (CB1) receptor are altered in diverse neurodegenerative disorders. However, some of these data are conflictive or poorly described. In this review, we summarize the findings about the alterations in ECS and CB1 receptors signaling in three representative brain illnesses, the Alzheimer's, Parkinson's and Huntington's diseases, and we discuss the relevance of these studies in understanding neurodegeneration development and progression, with a special focus on astrocyte function. Noteworthy, the analysis of ECS defects in neurodegeneration warrant much more studies, as our conceptual understanding of ECS function has evolved quickly in the last years, which now include glia cells and the subcellular-specific CB1 receptors signaling as critical players of brain functions.

The heterogeneity of asymmetric tau distribution is associated with an early age at onset and poor prognosis in Alzheimer's disease

PURPOSE

Left-right asymmetry, an important feature of brain development, has been implicated in neurodegenerative diseases, although it's less discussed in typical Alzheimer's disease (AD). We sought to investigate whether asymmetric tau deposition plays a potential role in AD heterogeneity.

METHODS

Two independent cohorts consisting of patients with mild cognitive impairment due to AD and AD dementia with tau PET imaging were enrolled [the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort with 18F-Flortaucipir, the Shanghai Memory Study (SMS) cohort with 18F-Florzolotau]. Based on the absolute global tau interhemispheric differences, each cohort was divided into two groups (asymmetric versus symmetric tau distribution). The two groups were cross-sectionally compared in terms of demographic, cognitive characteristics, and pathological burden. The cognitive decline trajectories were analyzed longitudinally.

RESULTS

Fourteen (23.3%) and 42 (48.3%) patients in the ADNI and SMS cohorts showed an asymmetric tau distribution, respectively. An asymmetric tau distribution was associated with an earlier age at disease onset (proportion of early-onset AD: ADNI/SMS/combined cohorts, p = 0.093/0.026/0.001) and more severe pathological burden (i.e., global tau burden: ADNI/SMS cohorts, p < 0.001/= 0.007). And patients with an asymmetric tau distribution were characterized by a steeper cognitive decline longitudinally (i.e., the annual decline of Mini-Mental Status Examination score: ADNI/SMS/combined cohorts, p = 0.053 / 0.035 / < 0.001).

CONCLUSIONS

Asymmetry in tau deposition, which may be associated with an earlier age at onset, more severe pathological burden, and a steeper cognitive decline, is potentially an important characteristic of AD heterogeneity.

Atrophy asymmetry in hippocampal subfields in patients with Alzheimer's disease and mild cognitive impairment

Volumetric analysis of hippocampal subfields and their asymmetry assessment recently has been useful biomarkers in neuroscience. In this study, hippocampal subfields atrophy and pattern of their asymmetry in the patient with Alzheimer's disease (AD) and mild cognitive impairment (MCI) were evaluated. MRI images of 20 AD patients, 20 MCI patients, and 20 healthy control (HC) were selected. The volumes of hippocampal subfields were extracted automatically using Freesurfer toolkit. The subfields asymmetry index (AI) and laterality ([Formula: see text]) were also evaluated. Analysis of covariance was used to compare the subfields volume between three patient groups (age and gender as covariates). We used ANOVA (P < 0.05) test for multiple comparisons with Bonferroni's post hoc correction method. Hippocampal subfields volume in AD patients were significantly lower than HC and MCI groups (P < 0.02); however, no significant difference was observed between MCI and HC groups. The asymmetry index (AI) in some subfields was significantly different between AD and MCI, as well as between AD and HC, while there was not any significant difference between MCI groups with HC. In all three patient groups, rightward laterality ([Formula: see text]) was seen in several subfields except subiculum, presubiculum, and parasubiculum, while in AD patient, rightward lateralization slightly decrease. Hippocampal subfields asymmetry can be used as a quantitative biomarker in neurocognitive disorders. In this study, it was observed that the asymmetry index of some subfields in AD is significantly different from MCI. In AD, patient rightward laterality was less MCI an HC group.

Brain metabolic correlates of Locus Coeruleus degeneration in Alzheimer's disease: a multimodal neuroimaging study

Locus Coeruleus (LC) degeneration occurs early in Alzheimer's disease (AD) and this could affect several brain regions innervated by LC noradrenergic axon terminals, as these bear neuroprotective effects and modulate neurovascular coupling/neuronal activity. We used LC-sensitive Magnetic Resonance imaging (MRI) sequences enabling LC integrity quantification, and [18F]Fluorodeoxyglucose (FDG) PET, to investigate the association of LC-MRI changes with brain glucose metabolism in cognitively impaired patients (30 amnesticMCI and 13 demented ones). Fifteen cognitively intact age-matched controls (HCs) were submitted only to LC-MRI for comparison with patients. Voxel-wise regression analyses of [18F]FDG images were conducted using the LC-MRI parameters signal intensity (LC_CR) and LC-belonging voxels (LC_VOX). Both LC_CR and LC_VOX were significantly lower in patients compared to HCs, and were directly associated with [18F]FDG uptake in fronto-parietal cortical areas, mainly involving the left hemisphere (p < 0.001, kE > 100). These results suggest a possible association between LC degeneration and cortical hypometabolism in degenerative cognitive impairment with a prevalent left-hemispheric vulnerability, and that LC degeneration might be linked to large-scale functional network alteration in AD pathology.

Magnetic resonance imaging Locus Coeruleus abnormality in amnestic Mild Cognitive Impairment is associated with future progression to dementia

BACKGROUND AND PURPOSE

Human neuropathological studies indicate that the pontine nucleus Locus Coeruleus (LC) undergoes significant and early degeneration in Alzheimer's disease. This line of evidence alongside experimental data suggests that the LC functional/structural decay may represent a critical factor for Alzheimer's disease pathophysiological and clinical progression. In the present prospective study, we used Magnetic Resonance Imaging (MRI) with LC-sensitive sequence (LC-MRI) to investigate in vivo the LC involvement in Alzheimer's disease progression, and whether specific LC-MRI features at baseline are associated with prognosis and cognitive performance in amnestic Mild Cognitive Impairment.

METHODS

LC-MRI parameters were measured at baseline by a template-based method on 3.0-T magnetic resonance images in 34 patients with Alzheimer's disease dementia, 73 patients with amnestic Mild Cognitive Impairment, and 53 cognitively intact individuals. A thorough neurological and neuropsychological assessment was performed at baseline and 2.5-year follow-up.

RESULTS

In subjects with Mild Cognitive Impairment who converted to dementia (n = 32), the LC intensity and number of LC-related voxels were significantly lower than in cognitively intact individuals, resembling those observed in demented patients. Such a reduction was not detected in Mild Cognitive Impairment individuals, who remained stable at follow-up. In Mild Cognitive Impairment subjects converting to dementia, LC-MRI parameter reduction was maximal in the rostral part of the left nucleus. Structural equation modeling analysis showed that LC-MRI parameters positively correlate with cognitive performance.

CONCLUSIONS

Our findings highlight a potential role of LC-MRI for predicting clinical progression in Mild Cognitive Impairment and support the key role of LC degeneration in the Alzheimer clinical continuum.

Altered functional connectivity pattern of hippocampal subfields in individuals with objectively-defined subtle cognitive decline and its association with cognition and cerebrospinal fluid biomarkers

Recent studies have shown that in the preclinical phase of Alzheimer's disease (AD), subtle cognitive changes can be detected using sensitive neuropsychological measures, and have proposed the concept of objectively-defined subtle cognitive decline (Obj-SCD). We aimed to assess the functional alteration of hippocampal subfields in individuals with Obj-SCD and its association with cognition and pathological biomarkers. Forty-two participants with cognitively normal (CN), 29 with Obj-SCD, and 55 with mild cognitive impairment (MCI) were retrospectively collected from the ADNI database. Neuropsychological performance, functional MRI, and cerebrospinal fluid (CSF) data were obtained. We calculated the seed-based functional connectivity (FC) of hippocampal subfields (cornu ammonis1 [CA1], CA2/3/dentate gyrus [DG], and subiculum) with whole-brain voxels. Additionally, we analyzed the correlation between FC values of significantly altered regions and neuropsychological performance and CSF biomarkers. The Obj-SCD group showed lower FC between left CA1-CA2/3/DG and right thalamus and higher FC between right subiculum and right superior parietal gyrus (SPG) compared with the CN and MCI groups. In the Obj-SCD group, FC values between left CA2/3/DG and right thalamus were positively associated with Auditory Verbal Learning Test (AVLT) recognition (r = 0.395, p = 0.046) and CSF Aβ1-42 levels (r = 0.466, p = 0.019), and FC values between left CA1 and right thalamus were positively correlated with CSF Aβ1-42 levels (r = 0.530, p = 0.006). Taken together, dysfunction in CA1-CA2/3/DG subregions suggests subtle cognitive impairment and AD-specific pathological changes in individuals with Obj-SCD. Additionally, increased subiculum connectivity may indicate early functional compensation for subtle cognitive changes.

Endogenous drivers of altered immune cell metabolism

Dysregulated metabolism has long been recognized as a feature of many metabolic disorders. However, recent studies demonstrating that metabolic reprogramming occurs in immune cells have led to a growing interest in the relationship between metabolic rewiring and immune-mediated disease pathogeneses. It is clear now that immune cell subsets engage in different metabolic pathways depending on their activation and/or maturation state. As a result, it may be possible to modulate metabolic reprogramming for clinical benefit. In this review, we provide an overview of immune cell metabolism with focus on endogenous drivers of metabolic reprogramming given their link to a number of immune-mediated disorders.

3T sodium MR imaging in Alzheimer's disease shows stage-dependent sodium increase influenced by age and local brain volume

INTRODUCTION

Application of MRI in clinical routine mainly addresses structural alterations. However, pathological changes at a cellular level are expected to precede the occurrence of brain atrophy clusters and of clinical symptoms. In this context, ²³Na-MRI examines sodium changes in the brain as a potential metabolic parameter. Recently, we have shown that ²³Na-MRI at ultra-high-field (7 T) was able to detect increased tissue sodium concentration (TSC) in Alzheimer's disease (AD). In this work, we aimed at assessing AD-pathology with ²³Na-MRI in a larger cohort and on a clinical 3T MR scanner.

METHODS

We used a multimodal MRI protocol on 52 prodromal to mild AD patients and 34 cognitively healthy control subjects on a clinical 3T MR scanner. We examined the TSC, brain volume, and cortical thickness in association with clinical parameters. We further compared TSC with intra-individual normalized TSC for the reduction of inter-individual TSC variability resulting from physiological as well as experimental conditions. Normalized TSC maps were created by normalizing each voxel to the mean TSC inside the brain stem.

RESULTS

We found increased normalized TSC in the AD cohort compared to elderly control subjects both on global as well as on a region-of-interest-based level. We further confirmed a significant association of local brain volume as well as age with TSC. TSC increase in the left temporal lobe was further associated with the cognitive state, evaluated via the Montreal cognitive assessment (MoCA) screening test. An increase of normalized TSC depending on disease stage reflected by the Clinical Dementia Rating (CDR) was found in our AD patients in temporal lobe regions. In comparison to classical brain volume and cortical thickness assessments, normalized TSC had a higher discriminative power between controls and prodromal AD patients in several regions of the temporal lobe.

DISCUSSION

We confirm the feasibility of ²³Na-MRI at 3T and report an increase of TSC in AD in several regions of the brain, particularly in brain regions of the temporal lobe. Furthermore, to reduce inter-subject variability caused by physiological factors such as circadian rhythms and experimental conditions, we introduced normalized TSC maps. This showed a higher discriminative potential between different clinical groups in comparison to the classical TSC analysis. In conclusion, ²³Na-MRI represents a potential translational imaging marker applicable e.g.for diagnostics and the assessment of intervention outcomes in AD even under clinically available field strengths such as 3T. Implication of ²³Na-MRI in association with other metabolic imaging marker needs to be further elucidated.

The significance of glycolysis index and its correlations with immune infiltrates in Alzheimer’s disease

Alzheimer’s disease (AD) is a common neurodegenerative disorder without an effective treatment, and results in an increasingly serious health problem. However, its pathogenesis is complex and poorly understood. Nonetheless, the exact role of dysfunctional glucose metabolism in AD pathogenesis remains unclear. We screened 28 core glycolysis-related genes and introduced a novel metric, the glycolysis index, to estimate the activation of glycolysis. The glycolysis index was significantly lower in the AD group in four different brain regions (frontal cortex, FC; temporal cortex, TC; hippocampus, HP; and entorhinal cortex, EC) than that in the control group. Combined with differential expression and over-representation analyses, we determined the clinical and pathological relevance of glycolysis in AD. Subsequently, we investigated the role of glycolysis in the AD brain microenvironment. We developed a glycolysis-brain cell marker connection network, which revealed a close relationship between glycolysis and seven brain cell types, most of which presented abundant variants in AD. Using immunohistochemistry, we detected greater infiltrated microglia and higher expression of glycolysis-related microglia markers in the APP/PS1 AD model than that in the control group, consistent with our bioinformatic analysis results. Furthermore, the excellent predictive value of the glycolysis index has been verified in different populations. Overall, our present findings revealed the clinical and biological significance of glycolysis and the brain microenvironment in AD.

Aberrant Energy Metabolism in Alzheimer's Disease

To maintain energy supply to the brain, a direct energy source called adenosine triphosphate (ATP) is produced by oxidative phosphorylation and aerobic glycolysis of glucose in the mitochondria and cytoplasm. Brain glucose metabolism is reduced in many neurodegenerative diseases, including Alzheimer's disease (AD), where it appears presymptomatically in a progressive and region-specific manner. Following dysregulation of energy metabolism in AD, many cellular repair/regenerative processes are activated to conserve the energy required for cell viability. Glucose metabolism plays an important role in the pathology of AD and is closely associated with the tricarboxylic acid cycle, type 2 diabetes mellitus, and insulin resistance. The glucose intake in neurons is from endothelial cells, astrocytes, and microglia. Damage to neurocentric glucose also damages the energy transport systems in AD. Gut microbiota is necessary to modulate bidirectional communication between the gastrointestinal tract and brain. Gut microbiota may influence the process of AD by regulating the immune system and maintaining the integrity of the intestinal barrier. Furthermore, some therapeutic strategies have shown promising therapeutic effects in the treatment of AD at different stages, including the use of antidiabetic drugs, rescuing mitochondrial dysfunction, and epigenetic and dietary intervention. This review discusses the underlying mechanisms of alterations in energy metabolism in AD and provides potential therapeutic strategies in the treatment of AD.

Connectivity alterations underlying the breakdown of pseudoneglect: New insights from healthy and pathological aging

A right-hemisphere dominance for visuospatial attention has been invoked as the most prominent neural feature of pseudoneglect (i.e., the leftward visuospatial bias exhibited in neurologically healthy individuals) but the neurophysiological underpinnings of such advantage are still controversial. Previous studies investigating visuospatial bias in multiple-objects visual enumeration reported that pseudoneglect is maintained in healthy elderly and amnesic mild cognitive impairment (aMCI), but not in Alzheimer’s disease (AD). In this study, we aimed at investigating the neurophysiological correlates sustaining the rearrangements of the visuospatial bias along the progression from normal to pathological aging. To this aim, we recorded EEG activity during an enumeration task and analyzed intra-hemispheric fronto-parietal and inter-hemispheric effective connectivity adopting indexes from graph theory in patients with mild AD, patients with aMCI, and healthy elderly controls (HC). Results revealed that HC showed the leftward bias and stronger fronto-parietal effective connectivity in the right as compared to the left hemisphere. A breakdown of pseudoneglect in patients with AD was associated with both the loss of the fronto-parietal asymmetry and the reduction of inter-hemispheric parietal interactions. In aMCI, initial alterations of the attentional bias were associated with a reduction of parietal inter-hemispheric communication, but not with modulations of the right fronto-parietal connectivity advantage, which remained intact. These data provide support to the involvement of fronto-parietal and inter-parietal pathways in the leftward spatial bias, extending these notions to the complex neurophysiological alterations characterizing pathological aging.

Introducing a gatekeeping system for amyloid status assessment in mild cognitive impairment

Background

In patients with mild cognitive impairment (MCI), enhanced cerebral amyloid-β plaque burden is a high-risk factor to develop dementia with Alzheimer’s disease (AD). Not all patients have immediate access to the assessment of amyloid status (A-status) via gold standard methods. It may therefore be of interest to find suitable biomarkers to preselect patients benefitting most from additional workup of the A-status. In this study, we propose a machine learning–based gatekeeping system for the prediction of A-status on the grounds of pre-existing information on APOE-genotype ¹⁸F-FDG PET, age, and sex.

Methods

Three hundred and forty-two MCI patients were used to train different machine learning classifiers to predict A-status majority classes among APOE-ε4 non-carriers (APOE4-nc; majority class: amyloid negative (Aβ-)) and carriers (APOE4-c; majority class: amyloid positive (Aβ +)) from ¹⁸F-FDG-PET, age, and sex. Classifiers were tested on two different datasets. Finally, frequencies of progression to dementia were compared between gold standard and predicted A-status.

Results

Aβ- in APOE4-nc and Aβ + in APOE4-c were predicted with a precision of 87% and a recall of 79% and 51%, respectively. Predicted A-status and gold standard A-status were at least equally indicative of risk of progression to dementia.

Conclusion

We developed an algorithm allowing approximation of A-status in MCI with good reliability using APOE-genotype, ¹⁸F-FDG PET, age, and sex information. The algorithm could enable better estimation of individual risk for developing AD based on existing biomarker information, and support efficient selection of patients who would benefit most from further etiological clarification. Further potential utility in clinical routine and clinical trials is discussed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-022-05879-6.

Functional Connectivity Dynamics Altered of the Resting Brain in Subjective Cognitive Decline

Background

Subjective cognitive decline (SCD) appears in the preclinical stage of the Alzheimer's disease continuum. In this stage, dynamic features are more sensitive than static features to reflect early subtle changes in functional brain connectivity. Therefore, we studied local and extended dynamic connectivity of the resting brain of people with SCD to determine their intrinsic brain changes.

Methods

We enrolled cognitively normal older adults from the communities and divided them into SCD and normal control (NC) groups. We used mean dynamic amplitude of low-frequency fluctuation (mdALFF) to evaluate region of interest (ROI)-wise local dynamic connectivity of resting-state functional MRI. The dynamic functional connectivity (dFC) between ROIs was tested by whole-brain-based statistics.

Results

When comparing SCD (N = 40) with NC (N = 45), mdALFF_mean decreased at right inferior parietal lobule (IPL) of the frontoparietal network (FPN). Still, it increased at the right middle temporal gyrus (MTG) of the ventral attention network (VAN) and right calcarine of the visual network (VIS). Also, the mdALFF_var (variance) increased at the left superior temporal gyrus of AUD, right MTG of VAN, right globus pallidum of the cingulo-opercular network (CON), and right lingual gyrus of VIS. Furthermore, mdALFF_mean at right IPL of FPN are correlated negatively with subjective complaints and positively with objective cognitive performance. In the dFC seeded from the ROIs with local mdALFF group differences, SCD showed a generally lower dFC_mean and higher dFC_var (variance) to other regions of the brain. These weakened and unstable functional connectivity appeared among FPN, CON, the default mode network, and the salience network, the large-scale networks of the triple network model for organizing neural resource allocations.

Conclusion

The local dynamic connectivity of SCD decreased in brain regions of cognitive executive control. Meanwhile, compensatory visual efforts and bottom-up attention rose. Mixed decrease and compensatory increase of dynamics of intrinsic brain activity suggest the transitional nature of SCD. The FPN local dynamics balance subjective and objective cognition and maintain cognitive preservation in preclinical dementia. Aberrant triple network model features the dFC alternations of SCD. Finally, the right lateralization phenomenon emerged early in the dementia continuum and affected local dynamic connectivity.

A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer's disease

Background

Alzheimer's disease, the most common cause of dementia, causes a progressive and irreversible deterioration of cognition that can sometimes be difficult to diagnose, leading to suboptimal patient care.

Methods

We developed a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted MRI scans, with or without cognitive scores. For each patient, a biomarker called "Alzheimer's Predictive Vector" (ApV) was derived using a two-stage least absolute shrinkage and selection operator (LASSO).

Results

The ApV reliably discriminates between people with (ADrp) and without (nADrp) Alzheimer's related pathologies (98% and 81% accuracy between ADrp - including the early form, mild cognitive impairment - and nADrp in internal and external hold-out test sets, respectively), without any a priori assumptions or need for neuroradiology reads. The new test is superior to standard hippocampal atrophy (26% accuracy) and cerebrospinal fluid beta amyloid measure (62% accuracy). A multiparametric analysis compared DTI-MRI derived fractional anisotropy, whose readout of neuronal loss agrees with ADrp phenotype, and SNPrs2075650 is significantly altered in patients with ADrp-like phenotype.

Conclusions

This new data analytic method demonstrates potential for increasing accuracy of Alzheimer diagnosis.

Glucose Metabolism, Neural Cell Senescence and Alzheimer’s Disease

Alzheimer’s disease (AD), an elderly neurodegenerative disorder with a high incidence and progressive memory decline, is one of the most expensive, lethal, and burdening diseases. To date, the pathogenesis of AD has not been fully illustrated. Emerging studies have revealed that cellular senescence and abnormal glucose metabolism in the brain are the early hallmarks of AD. Moreover, cellular senescence and glucose metabolism disturbance in the brain of AD patients may precede amyloid-β deposition or Tau protein phosphorylation. Thus, metabolic reprogramming targeting senescent microglia and astrocytes may be a novel strategy for AD intervention and treatment. Here, we recapitulate the relationships between neural cell senescence and abnormal glucose metabolism (e.g., insulin signaling, glucose and lactate metabolism) in AD. We then discuss the potential perspective of metabolic reprogramming towards an AD intervention, providing a theoretical basis for the further exploration of the pathogenesis of and therapeutic approach toward AD.

Dihuang-Yinzi Alleviates Cognition Deficits via Targeting Energy-Related Metabolism in an Alzheimer Mouse Model as Demonstrated by Integration of Metabolomics and Network Pharmacology

Energy metabolism disturbance and the consequent reactive oxygen species (ROS) overproduction play a key and pathogenic role in the onset and progression of Alzheimer’s disease (AD). Dihuang-Yinzi (DHYZ) is a traditional Chinese herbal prescription clinically applied to treat AD and other neurodegenerative diseases for a long time. However, the systematical metabolic mechanism of DHYZ against AD remains largely unclear. Here we aimed to explore the mechanism of DHYZ in the treatment of AD comprehensively in an in vivo metabolic context by performing metabolomics analysis coupled with network pharmacology study and experimental validation. The network pharmacology was applied to dig out the potential target of DHYZ against AD. The metabolomics analysis based on UPLC-HRMS was carried out to profile the urine of 2× Tg-AD mice treated with DHYZ. By integrating network pharmacology and metabolomics, we found DHYZ could ameliorate 4 key energy-related metabolic pathways, including glycerophospholipid metabolism, nicotinate/nicotinamide metabolism, glycolysis, and tricarboxylic acid cycle. Besides, we identified 5 potential anti-AD targets of DHYZ, including DAO, HIF1A, PARP1, ALDH3B2, and ACHE, and 14 key differential metabolites involved in the 4 key energy-related metabolic pathways. Furthermore, DHYZ depressed the mitochondrial dysfunction and the resultant ROS overproduction through ameliorating glycerophospholipid metabolism disturbance. Thereby DHYZ increased nicotinamide adenine dinucleotide (NAD⁺) content and promoted glycolysis and tricarboxylic acid (TCA) cycle, and consequently improved oxidative phosphorylation and energy metabolism. In the present study, we provided a novel, comprehensive and systematic insight into investigating the therapeutic efficacy of DHYZ against AD via ameliorating energy-related metabolism.

Brain Metabolic Alterations in Alzheimer's Disease

The brain is one of the most energy-consuming organs in the body. Satisfying such energy demand requires compartmentalized, cell-specific metabolic processes, known to be complementary and intimately coupled. Thus, the brain relies on thoroughly orchestrated energy-obtaining agents, processes and molecular features, such as the neurovascular unit, the astrocyte-neuron metabolic coupling, and the cellular distribution of energy substrate transporters. Importantly, early features of the aging process are determined by the progressive perturbation of certain processes responsible for adequate brain energy supply, resulting in brain hypometabolism. These age-related brain energy alterations are further worsened during the prodromal stages of neurodegenerative diseases, namely Alzheimer's disease (AD), preceding the onset of clinical symptoms, and are anatomically and functionally associated with the loss of cognitive abilities. Here, we focus on concrete neuroenergetic features such as the brain's fueling by glucose and lactate, the transporters and vascular system guaranteeing its supply, and the metabolic interactions between astrocytes and neurons, and on its neurodegenerative-related disruption. We sought to review the principles underlying the metabolic dimension of healthy and AD brains, and suggest that the integration of these concepts in the preventive, diagnostic and treatment strategies for AD is key to improving the precision of these interventions.

Effects of Involuntary and Voluntary Exercise in Combination with Acousto-Optic Stimulation on Adult Neurogenesis in an Alzheimer's Mouse Model

Single-factor intervention, such as physical exercise and auditory and visual stimulation, plays a positive role on the prevention and treatment of Alzheimer's disease (AD); however, the therapeutic effects of single-factor intervention are limited. The beneficial effects of these multifactor combinations on AD and its molecular mechanism have yet to be elucidated. Here, we investigated the effect of multifactor intervention, voluntary wheel exercise, and involuntary treadmill running in combination with acousto-optic stimulation, on adult neurogenesis and behavioral phenotypes in a mouse model of AD. We found that 4 weeks of multifactor intervention can significantly increase the production of newborn cells (BrdU⁺ cells) and immature neurons (DCX⁺ cells) in the hippocampus and lateral ventricle of Aβ oligomer-induced mice. Importantly, the multifactor intervention could promote BrdU⁺ cells to differentiate into neurons (BrdU⁺ DCX⁺ cells or BrdU⁺ NeuN⁺ cells) and astrocytes (BrdU⁺GFAP⁺ cells) in the hippocampus and ameliorate Aβ oligomer-induced cognitive impairment and anxiety- and depression-like behaviors in mice evaluated by novel object recognition, Morris water maze tests, elevated zero maze, forced swimming test, and tail suspension test, respectively. Moreover, multifactor intervention could lead to an increase in the protein levels of PSD-95, SYP, DCX, NeuN, GFAP, Bcl-2, BDNF, TrkB, and pSer473-Akt and a decrease in the protein levels of BAX and caspase-9 in the hippocampal lysates of Aβ oligomer-induced mice. Furthermore, sequencing analysis of serum metabolites revealed that aberrantly expressed metabolites modulated by multifactor intervention were highly enriched in the biological process associated with keeping neurons functioning and neurobehavioral function. Additionally, the intervention-mediated serum metabolites mainly participated in glutamate metabolism, glucose metabolism, and the tricarboxylic acid cycle in mice. Our findings suggest the potential of multifactor intervention as a non-invasive therapeutic strategy for AD to anti-Aβ oligomer neurotoxicity.

Astrocytes as Key Regulators of Brain Energy Metabolism: New Therapeutic Perspectives

Astrocytes play key roles in the regulation of brain energy metabolism, which has a major impact on brain functions, including memory, neuroprotection, resistance to oxidative stress and homeostatic tone. Energy demands of the brain are very large, as they continuously account for 20–25% of the whole body’s energy consumption. Energy supply of the brain is tightly linked to neuronal activity, providing the origin of the signals detected by the widely used functional brain imaging techniques such as functional magnetic resonance imaging and positron emission tomography. In particular, neuroenergetic coupling is regulated by astrocytes through glutamate uptake that triggers astrocytic aerobic glycolysis and leads to glucose uptake and lactate release, a mechanism known as the Astrocyte Neuron Lactate Shuttle. Other neurotransmitters such as noradrenaline and Vasoactive Intestinal Peptide mobilize glycogen, the reserve for glucose exclusively localized in astrocytes, also resulting in lactate release. Lactate is then transferred to neurons where it is used, after conversion to pyruvate, as a rapid energy substrate, and also as a signal that modulates neuronal excitability, homeostasis, and the expression of survival and plasticity genes. Importantly, glycolysis in astrocytes and more generally cerebral glucose metabolism progressively deteriorate in aging and age-associated neurodegenerative diseases such as Alzheimer’s disease. This decreased glycolysis actually represents a common feature of several neurological pathologies. Here, we review the critical role of astrocytes in the regulation of brain energy metabolism, and how dysregulation of astrocyte-mediated metabolic pathways is involved in brain hypometabolism. Further, we summarize recent efforts at preclinical and clinical stages to target brain hypometabolism for the development of new therapeutic interventions in age-related neurodegenerative diseases.

The Impact of Medium Chain and Polyunsaturated ω-3-Fatty Acids on Amyloid-β Deposition, Oxidative Stress and Metabolic Dysfunction Associated with Alzheimer's Disease

Alzheimer’s disease (AD), the most common cause of dementia in the elderly population, is closely linked to a dysregulated cerebral lipid homeostasis and particular changes in brain fatty acid (FA) composition. The abnormal extracellular accumulation and deposition of the peptide amyloid-β (Aβ) is considered as an early toxic event in AD pathogenesis, which initiates a series of events leading to neuronal dysfunction and death. These include the induction of neuroinflammation and oxidative stress, the disruption of calcium homeostasis and membrane integrity, an impairment of cerebral energy metabolism, as well as synaptic and mitochondrial dysfunction. Dietary medium chain fatty acids (MCFAs) and polyunsaturated ω-3-fatty acids (ω-3-PUFAs) seem to be valuable for disease modification. Both classes of FAs have neuronal health-promoting and cognition-enhancing properties and might be of benefit for patients suffering from mild cognitive impairment (MCI) and AD. This review summarizes the current knowledge about the molecular mechanisms by which MCFAs and ω-3-PUFAs reduce the cerebral Aβ deposition, improve brain energy metabolism, and lessen oxidative stress levels.

Hippocampus- and Thalamus-Related Fiber-Specific White Matter Reductions in Mild Cognitive Impairment

Early diagnosis of mild cognitive impairment (MCI) fascinates screening high-risk Alzheimer's disease (AD). White matter is found to degenerate earlier than gray matter and functional connectivity during MCI. Although studies reveal white matter degenerates in the limbic system for MCI, how other white matter degenerates during MCI remains unclear. In our method, regions of interest with a high level of resting-state functional connectivity with hippocampus were selected as seeds to track fibers based on diffusion tensor imaging (DTI). In this way, hippocampus-temporal and thalamus-related fibers were selected, and each fiber's DTI parameters were extracted. Then, statistical analysis, machine learning classification, and Pearson's correlations with behavior scores were performed between MCI and normal control (NC) groups. Results show that: 1) the mean diffusivity of hippocampus-temporal and thalamus-related fibers are significantly higher in MCI and could be used to classify 2 groups effectively. 2) Compared with normal fibers, the degenerated fibers detected by the DTI indexes, especially for hippocampus-temporal fibers, have shown significantly higher correlations with cognitive scores. 3) Compared with the hippocampus-temporal fibers, thalamus-related fibers have shown significantly higher correlations with depression scores within MCI. Our results provide novel biomarkers for the early diagnoses of AD.

Mitochondrial defects: An emerging theranostic avenue towards Alzheimer's associated dysregulations

Mitochondria play a crucial role in expediting the energy homeostasis under varying environmental conditions. As mitochondria are controllers of both energy production and apoptotic pathways, they are also distinctively involved in controlling the neuronal cell survival and/or death. Numerous factors are responsible for mitochondria to get degraded with aging and huge functional failures in mitochondria are also found to be associated with the commencement of numerous neurodegenerative conditions, including Alzheimer's disease (AD). A large number of existing literatures promote the pivotal role of mitochondrial damage and oxidative impairment in the pathogenesis of AD. Numerous mitochondria associated processes such as mitochondrial biogenesis, fission, fusion, mitophagy, transportation and bioenergetics are crucial for proper functioning of mitochondria but are reported to be defective in AD patients. Though, the knowledge on the precise and in-depth mechanisms of these actions is still in infancy. Based upon the outcome of various significant studies, mitochondria are also being considered as therapeutic targets for AD. Here, we review the current status of mitochondrial defects in AD and also summarize the possible role of these defects in the pathogenesis of AD. The various approaches for developing the mitochondria-targeted therapies are also discussed here in detail. Consequently, it is suggested that improving mitochondrial activity via pharmacological and/or non-pharmacological interventions could postpone the onset and slow the development of AD. Further research and consequences of ongoing clinical trials should extend our understanding and help to validate conclusions regarding the causation of AD.

The role of microRNA-34 family in Alzheimer's disease: A potential molecular link between neurodegeneration and metabolic disorders

Growing evidence indicates that overexpression of the microRNA-34 (miR-34) family in the brain may play a crucial role in Alzheimer's disease (AD) pathogenesis by targeting and downregulating genes associated with neuronal survival, synapse formation and plasticity, Aβ clearance, mitochondrial function, antioxidant defense system, and energy metabolism. Additionally, elevated levels of the miR-34 family in the liver and pancreas promote the development of metabolic syndromes (MetS), such as diabetes and obesity. Importantly, MetS represent a well-documented risk factor for sporadic AD. This review focuses on the recent findings regarding the role of the miR-34 family in the pathogenesis of AD and MetS, and proposes miR-34 as a potential molecular link between both disorders. A comprehensive understanding of the functional roles of miR-34 family in the molecular and cellular pathogenesis of AD brains may lead to the discovery of a breakthrough treatment strategy for this disease.

Amyloid-Beta Influences Memory via Functional Connectivity During Memory Retrieval in Alzheimer's Disease

Objective: Amnesia in Alzheimer's disease (AD) appears early and could be caused by encoding deficiency, consolidation dysfunction, and/or impairment in the retrieval of stored memory information. The relationship between AD pathology biomarker β-amyloid and memory dysfunction is unclear. Method: The memory task functional MRI and amyloid PET were simultaneously performed to investigate the relationship between memory performance, memory phase-related functional connectivity, and cortical β-amyloid deposition. We clustered functional networks during memory maintenance and compared network connectivity between groups in each memory phase. Mediation analysis was performed to investigate the mediator between β-amyloid and related cognitive performance. Results: Alzheimer's disease was primarily characterized by decreased functional connectivity in a data-driven network composed of an a priori default mode network, limbic network, and frontoparietal network during the memory maintenance (0.205 vs. 0.236, p = 0.04) and retrieval phase (0.159 vs. 0.183, p = 0.017). Within the network, AD had more regions with reduced connectivity during the retrieval than the maintenance and encoding phases (chi-square p = 0.01 and < 0.001). Furthermore, the global cortical β-amyloid negatively correlated with network connectivity during the memory retrieval phase (R = - 0.247, p = 0.032), with this relationship mediating the effect of cortical β-amyloid on memory performance (average causal mediation effect = - 0.05, p = 0.035). Conclusion: We demonstrated that AD had decreased connectivity in specific networks during the memory retrieval phase. Impaired functional connectivity during memory retrieval mediated the adverse effect of β-amyloid on memory. These findings help to elucidate the involvement of cortical β-amyloid (Aβ) in the memory performance in the early stages of AD.

Asymmetric Amyloid Deposition as an Early Sign of Progression in Mild Cognitive Impairment Due to Alzheimer Disease

PURPOSE

In typical Alzheimer disease with dementia (ADD), amyloid pathologies affect both cerebral hemispheres symmetrically. However, the spatial distribution of amyloid-β (Aβ) in the early stage of ADD or over the course of disease has not been investigated. Therefore, we explored asymmetric pattern of Aβ deposition in both hemispheres according to the ADD continuum using 18F-florbetaben PET.

METHODS

Sixty-eight subjects, including 15 Aβ-negative normal controls, 28 Aβ-positive mild cognitive impairment (Aβ+ MCI), and 25 Aβ-positive ADD (Aβ+ ADD) subjects, were enrolled. Differences in the asymmetry index and SUV ratio in each of the 6 target regions (4 cortical lobes, cingulate, precuneus) plus composite region between groups were explored.

RESULTS

The composite and target regional asymmetry indices were significantly different between groups and was highest in Aβ+ MCI (composite, occipital, and temporal, P < 0.001; frontal, P = 0.004). The composite and target regional SUV ratios were significantly different according to 3 groups with gradual increase and were highest in Aβ+ ADD (composite and all target regions, P < 0.001).

CONCLUSIONS

The asymmetric pattern of amyloid deposition was distinct between Aβ-negative normal controls and Aβ+ MCI. This pattern disappeared as the disease progressed. These data indicate that asymmetric amyloid deposition may be an early sign of MCI over the course of ADD.

SMILE: systems metabolomics using interpretable learning and evolution

Background

Direct link between metabolism and cell and organism phenotype in health and disease makes metabolomics, a high throughput study of small molecular metabolites, an essential methodology for understanding and diagnosing disease development and progression. Machine learning methods have seen increasing adoptions in metabolomics thanks to their powerful prediction abilities. However, the “black-box” nature of many machine learning models remains a major challenge for wide acceptance and utility as it makes the interpretation of decision process difficult. This challenge is particularly predominant in biomedical research where understanding of the underlying decision making mechanism is essential for insuring safety and gaining new knowledge.

Results

In this article, we proposed a novel computational framework, Systems Metabolomics using Interpretable Learning and Evolution (SMILE), for supervised metabolomics data analysis. Our methodology uses an evolutionary algorithm to learn interpretable predictive models and to identify the most influential metabolites and their interactions in association with disease. Moreover, we have developed a web application with a graphical user interface that can be used for easy analysis, interpretation and visualization of the results. Performance of the method and utilization of the web interface is shown using metabolomics data for Alzheimer’s disease.

Conclusions

SMILE was able to identify several influential metabolites on AD and to provide interpretable predictive models that can be further used for a better understanding of the metabolic background of AD. SMILE addresses the emerging issue of interpretability and explainability in machine learning, and contributes to more transparent and powerful applications of machine learning in bioinformatics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04209-1.

A Graph Gaussian Embedding Method for Predicting Alzheimer's Disease Progression With MEG Brain Networks

Characterizing the subtle changes of functional brain networks associated with the pathological cascade of Alzheimer's disease (AD) is important for early diagnosis and prediction of disease progression prior to clinical symptoms. We developed a new deep learning method, termed multiple graph Gaussian embedding model (MG2G), which can learn highly informative network features by mapping high-dimensional resting-state brain networks into a low-dimensional latent space. These latent distribution-based embeddings enable a quantitative characterization of subtle and heterogeneous brain connectivity patterns at different regions, and can be used as input to traditional classifiers for various downstream graph analytic tasks, such as AD early stage prediction, and statistical evaluation of between-group significant alterations across brain regions. We used MG2G to detect the intrinsic latent dimensionality of MEG brain networks, predict the progression of patients with mild cognitive impairment (MCI) to AD, and identify brain regions with network alterations related to MCI.

Detection Gap of Right-Asymmetric Neuronal Degeneration by CERAD Test Battery in Alzheimer's Disease

Objectives: Asymmetric disease characteristics on neuroimaging are common in structural and functional imaging of neurodegenerative diseases, particularly in Alzheimer‘s disease (AD). However, a standardized clinical evaluation of asymmetric neuronal degeneration and its impact on clinical findings has only sporadically been investigated for F-18-fluorodeoxyglucose positron emission tomography (F-18-FDG-PET). This study aimed to evaluate the impact of lateralized neuronal degeneration on the detection of AD by detailed clinical testing. Furthermore, we compared associations between clinical evaluation and lateralized neuronal degeneration between FDG-PET hypometabolism and hippocampal atrophy. Finally, we investigated if specific subtests show associations with lateralized neuronal degeneration.

Methods: One-hundred and forty-six patients with a clinical diagnosis of AD (age 71 ± 8) were investigated by FDG-PET and the “Consortium to Establish a Registry for Alzheimer’s disease” (CERAD) test battery. For assessment of neuronal degeneration, FDG-PET hypometabolism in brain regions typically affected in AD were graded by visual (3D-surface projections) and semiquantitative analysis. Asymmetry of the hippocampus (left-right) in magnetic resonance tomography (MRI) was rated visually by the Scheltens scale. Measures of asymmetry were calculated to quantify lateralized neuronal degeneration and asymmetry scores were subsequently correlated with CERAD.

Results: Asymmetry with left-dominant neuronal degeneration to FDG-PET was an independent predictor of cognitive impairment (visual: β = −0.288, p < 0.001; semiquantitative: β = −0.451, p < 0.001) when controlled for age, gender, years of education and total burden of neuronal degeneration, whereas hippocampal asymmetry to MRI was not (β = −0.034; p = 0.731). Direct comparison of CERAD-PET associations in cases with right- and left-lateralized neuronal degeneration estimated a detection gap of 2.7 years for right-lateralized cases. Left-hemispheric neuronal degeneration was significantly associated with the total CERAD score and multiple subscores, whereas only MMSE (semiquantitative: β = 0.429, p < 0.001) and constructional praxis (semiquantitative: β = 0.292, p = 0.008) showed significant associations with right-hemispheric neuronal degeneration.

Conclusions: Asymmetry of deteriorated cerebral glucose metabolism has a significant impact on the coupling between neuronal degeneration and cognitive function. Right dominant neuronal degeneration shows a delayed detection by global CERAD testing and requires evaluation of specific subdomains of cognitive testing.

Impact of Genetic Risk Factors for Alzheimer's Disease on Brain Glucose Metabolism

Alzheimer's disease (AD) is a devastating neurodegenerative disease that affects more than 30 million people worldwide. Despite growing knowledge of AD pathophysiology, a complete understanding of the pathogenic mechanisms underpinning AD is lacking, and there is currently no cure for AD. Extant literature suggests that AD is a polygenic and multifactorial disease underscored by complex and dynamic pathogenic mechanisms. Despite extensive research and clinical trials, there has been a dearth of novel drugs for AD treatment on the market since memantine in 2003. This lack of therapeutic success has directed the entire research community to approach the disease from a different angle. In this review, we discuss growing evidence for the close link between altered glucose metabolism and AD pathogenesis by exploring how genetic risk factors for AD are associated with dysfunctional glucose metabolism. We also discuss modification of genes responsible for metabolic pathways implicated in AD pathology.

Pathological Correlations of Neuropsychiatric Symptoms in Institutionalized People with Dementia

BACKGROUND

Comprehensive clinicopathological studies of neuropsychiatric symptoms (NPS) in dementia are lacking.

OBJECTIVE

To describe the pathological correlations of NPS in a sample of institutionalized people with dementia.

METHODS

We studied 59 people who were consecutively admitted to a nursing home and donated their brain. Correlations between pathological variables and NPS upon admission (n = 59) and at one-year follow-up assessment (n = 46) were explored and confirmed using bivariate and multivariate statistical methods.

RESULTS

Mean (SD) age at admission was 83.2 (6.4) years and mean (SD) age at demise was 85.4 (6.6); 73% of the subjects were female and 98% presented advanced dementia. The most frequent etiological diagnosis was Alzheimer's disease (AD; 74.6% clinical diagnosis, 67.8% pathological diagnosis). The pathological diagnosis of AD was associated with aggression (β est 0.31), depression (β est 0.31), anxiety (β est 0.38), and irritability (β est 0.28). Tau stage correlated with aggressive symptoms (β est 0.32) and anxiety (βest 0.33). Coexistence of AD and Lewy body pathology was associated with depression (β est 0.32), while argyrophilic grains were associated with eating symptoms (β est 0.29). Predictive models were achieved for apathy, including cognitive performance, basal ganglia ischemic lesions, and sex as predictors (R2 0.38) and for sleep disorders, including pathological diagnosis of AD and age at demise (R2 0.18) (all p-values <0.05, unadjusted).

CONCLUSION

AD was the main pathological substrate of NPS in our sample of very elderly people with advanced dementia. However, correlations were mild, supporting a model of focal/asymmetric rather than diffuse brain damage, along with relevance of environmental and other personal factors, in the genesis of those symptoms.

Parallels between retinal and brain pathology and response to immunotherapy in old, late-stage Alzheimer's disease mouse models

Despite growing evidence for the characteristic signs of Alzheimer's disease (AD) in the neurosensory retina, our understanding of retina-brain relationships, especially at advanced disease stages and in response to therapy, is lacking. In transgenic models of AD (APPSWE/PS1∆E9; ADtg mice), glatiramer acetate (GA) immunomodulation alleviates disease progression in pre- and early-symptomatic disease stages. Here, we explored the link between retinal and cerebral AD-related biomarkers, including response to GA immunization, in cohorts of old, late-stage ADtg mice. This aged model is considered more clinically relevant to the age-dependent disease. Levels of synaptotoxic amyloid β-protein (Aβ)1-42, angiopathic Aβ1-40, non-amyloidogenic Aβ1-38, and Aβ42/Aβ40 ratios tightly correlated between paired retinas derived from oculus sinister (OS) and oculus dexter (OD) eyes, and between left and right posterior brain hemispheres. We identified lateralization of Aβ burden, with one-side dominance within paired retinal and brain tissues. Importantly, OS and OD retinal Aβ levels correlated with their cerebral counterparts, with stronger contralateral correlations and following GA immunization. Moreover, immunomodulation in old ADtg mice brought about reductions in cerebral vascular and parenchymal Aβ deposits, especially of large, dense-core plaques, and alleviation of microgliosis and astrocytosis. Immunization further enhanced cerebral recruitment of peripheral myeloid cells and synaptic preservation. Mass spectrometry analysis identified new parallels in retino-cerebral AD-related pathology and response to GA immunization, including restoration of homeostatic glutamine synthetase expression. Overall, our results illustrate the viability of immunomodulation-guided CNS repair in old AD model mice, while shedding light onto similar retino-cerebral responses to intervention, providing incentives to explore retinal AD biomarkers.

Aberrant White Matter Microstructure as a Potential Diagnostic Marker in Alzheimer's Disease by Automated Fiber Quantification

Neuroimaging evidence has suggested white matter microstructure are heavily affected in Alzheimer's disease (AD). However, whether white matter dysfunction is localized at the specific regions of fiber tracts and whether they would be a potential biomarker for AD remain unclear. By automated fiber quantification (AFQ), we applied diffusion tensor images from 25 healthy controls (HC), 24 amnestic mild cognitive impairment (aMCI) patients and 18 AD patients to create tract profiles along 16 major white matter fibers. We compared diffusion metrics [Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR)] between groups. To assess the diagnostic value, we applied a random forest (RF) classifier, a type of machine learning method. In the global tract level, we found that aMCI and AD patients showed higher MD, DA, and DR values in some fiber tracts mostly in the left hemisphere compared to HC. In the point-wise level, widespread disruption were distributed on specific locations of different tracts. The point-wise MD measurements presented the best classification performance with respect to differentiating AD from HC. The two most important variables were localized in the prefrontal potion of left uncinate fasciculus and anterior thalamic radiation. In addition, the point-wise DA in the posterior component of the left cingulum cingulate displayed the most robust discriminative ability to identify AD from aMCI. Our findings provide evidence that white matter abnormalities based on the AFQ method could be as a diagnostic biomarker in AD.

Effects of a Nutritional Formulation Containing Caprylic and Capric Acid, Phosphatidylserine, and Docosahexaenoic Acid in Streptozotocin-Lesioned Rats

Background

It has been studied that nutrition can influence Alzheimer's disease (AD) onset and progression. Some studies on rodents using intraventricular streptozotocin (STZ) injection showed that this toxin changes cerebral glucose metabolism and insulin signaling pathways.

Objective

The aim of the present study was to evaluate whether a nutritional formulation could reduce cognitive impairment in STZ-induced animals.

Methods

The rats were randomly divided into two groups: sham and STZ. The STZ group received a single bilateral STZ-ICV injection (1 mg/kg). The sham group received a bilateral ICV injection of 0.9% saline solution. The animals were treated with AZ1 formulation (Instanth^® NEO, Prodiet Medical Nutrition) (1 g/kg, PO) or its vehicle (saline solution) for 30 days, once a day starting one day after the stereotaxic surgery (n = 6-10). The rats were evaluated using the open field test to evaluate locomotor activity at day 27 after surgery. Cognitive performance was evaluated at day 28 using the object recognition test and the spatial version of the Y-maze test. At day 30, the rats were anesthetized with chloral hydrate (400 mg/kg, i.p) and euthanized in order to evaluate IBA1 in the hippocampus. The differences were analyzed using one-way ANOVA with Bonferroni's or Kruskal Wallis with Dunn's post-hoc test.

Results/Conclusion

STZ-lesioned rats present memory impairment besides the increased microglial activation. The treatment with AZ1 formulation reversed the memory impairment observed in the object recognition test and Y-maze and also reduced IBA1 in CA1 and DG.

Lateralized memory circuit dropout in Alzheimer’s disease patients

Altered connectivity within neuronal networks is often observed in Alzheimer’s disease. However, delineating pro-cognitive compensatory changes from pathological network decline relies on characterizing network and task effects together. In this study, we interrogated the dynamics of occipito-temporo-frontal brain networks responsible for implicit and explicit memory processes using high-density EEG and dynamic causal modelling. We examined source-localized network activity from patients with Alzheimer’s disease (n = 21) and healthy controls (n = 21), while they performed both visual recognition (explicit memory) and implicit priming tasks. Parametric empirical Bayes analyses identified significant reductions in temporo-frontal connectivity and in subcortical visual input in patients, specifically in the left hemisphere during the recognition task. There was also slowing in frontal left hemisphere signal transmission during the implicit priming task, with significantly more distinct dropout in connectivity during the recognition task, suggesting that these network drop-out effects are affected by task difficulty. Furthermore, during the implicit memory task, increased right frontal activity was correlated with improved task performance in patients only, suggesting that right-hemisphere compensatory mechanisms may be employed to mitigate left-lateralized network dropout in Alzheimer’s disease. Taken together, these findings suggest that Alzheimer’s disease is associated with lateralized memory circuit dropout and potential compensation from the right hemisphere, at least for simpler memory tasks.

Asymmetric Differences in the Gray Matter Volume and Functional Connections of the Amygdala Are Associated With Clinical Manifestations of Alzheimer's Disease

Objective

Asymmetry is a subtle but pervasive aspect of the human brain, which may be altered in several neuropsychiatric conditions. Magnetic resonance imaging (MRI) studies have reported that cerebral structural asymmetries are altered in Alzheimer’s disease (AD), but most of these studies were conducted at the region-of-interest level. At the functional level, there are few reports of resting-state functional asymmetries based on functional MRI. In this study, we investigated lateral differences in structural volumes and strengths of functional connectivity between individuals with AD and healthy controls (HCs) at the voxel level.

Methods

Forty-eight patients with AD and 32 matched HCs were assessed. An analysis of voxel-based morphometry (VBM) of gray matter volume was performed at the whole-brain level to explore anatomical cerebral asymmetries in AD. We then performed a seed-to-whole-brain functional connectivity (FC) analysis to reveal FC asymmetries in AD. An asymmetry index (AI) was used to measure these changes, and the relationship between the structural and functional AIs and the clinical symptoms of AD was explored.

Results

A VBM analysis revealed a rightward and a leftward lateralization in the amygdala and the thalamus, respectively, in patients with AD. FC between the amygdala and the precuneus showed a rightward lateralization in AD, which was the opposite of the lateralization in the HCs. The asymmetric changes in structure and function were associated with disease severity and functional impairment in AD.

Conclusion

Our study highlights the value of considering asymmetries in the amygdala and the thalamus in clinical evaluations and their relevance to clinical measures.

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.

Glucose, glycolysis, and neurodegenerative diseases

Prolonged survival of a typical postmitotic neuron hinges on a balance between multiple processes, among these are a sustenance of ATP production and protection against reactive oxygen species. In neuropathological conditions, mitochondrial defects often lead to both a drop in ATP levels, as well as increase reactive oxygen species production from inefficient electron transport processes and NADPH-oxidases activities. The former often resulted in the phenomenon of compensatory aerobic glycolysis. The latter stretches the capacity of the cell's redox buffering capacity, and may lead to damages of key enzymes involved in energy metabolism. Several recent reports have indicated that enhancing glucose availability and uptake, as well as increasing glycolytic flux via pharmacological or genetic manipulation of glycolytic enzymes, could be protective in animal models of several major neurodegenerative diseases, including Parkinson's disease, Huntington's disease, and Amyotrophic lateral sclerosis. Activation of canonical Wnt signaling, which improves disease symptoms in mouse models of Alzheimer's disease also appears to work via an elevation of glycolytic enzymes and enhance glucose metabolism. Here, I discuss these findings and the possible underlying mechanisms of how an increase in glucose uptake and glycolysis could be neuroprotective. Increased glycolytic production of ATP would help alleviate energy deficiency, and ATP's hydrotropic effect may enhance solubility and clearance of toxic aggregates prevalent in many neurodegenerative diseases. Furthermore, channeling of glucose into the Pentose Phosphate Pathway would increase the redox buffering capacity of the cell.

Medial temporal lobe connectivity and its associations with cognition in early Alzheimer's disease

Human episodic memory critically depends on subregions of the medial temporal lobe, which are part of functional brain systems such as the anterior-temporal and the posterior-medial system. Here we analysed how Alzheimer's pathology affects functional connectivity within these systems. Data from 256 amyloid-β-negative cognitively unimpaired, 103 amyloid-β-positive cognitively unimpaired, and 83 amyloid-β-positive individuals with mild cognitive impairment were analysed. Amyloid-β and tau pathology were measured using the CSF amyloid-β42/40 ratio and phosphorylated tau, respectively. We found that amyloid-β-positive cognitively unimpaired individuals were mainly characterized by decreased functional connectivity between the medial temporal lobe and regions in the anterior-temporal system, most prominently between left perirhinal/entorhinal cortices and medial prefrontal cortex. Furthermore, correlation analysis in this group revealed decreasing functional connectivity between bilateral perirhinal/entorhinal cortices, anterior hippocampus and posterior-medial regions with increasing levels of phosphorylated tau. The amyloid-β-positive individuals with mild cognitive impairment mostly exhibited reduced connectivity between the medial temporal lobe and posterior-medial regions, predominantly between the anterior hippocampus and posterior cingulate cortex. In addition, they showed hyperconnectivity within the medial temporal lobe and its immediate proximity. Lower medial temporal-cortical functional connectivity networks resulting from the group comparisons of cognitively unimpaired individuals were associated with reduced memory performance and more rapid longitudinal memory decline as shown by linear mixed-effects regression analysis. Finally, we found that reduced medial temporal-cortical connectivity in mildly cognitively impaired individuals was related to reduced entorhinal thickness and white matter integrity of the parahippocampal cingulum and the fornix. No such relationships were found in cognitively unimpaired individuals. In conclusion, our findings show that the earliest changes in preclinical Alzheimer's disease might involve decreased connectivity within the anterior-temporal system, and early changes in connectivity might be related to memory impairment, but not to structural changes. With disease progression and increased tau pathology, medial temporal functional connectivity with posterior-medial regions seems to be increasingly impaired. In individuals with mild cognitive impairment, reduced functional connectivity is associated with structural brain changes as well as the emergence of locally increased connectivity patterns. Thus, functional connectivity between the medial temporal lobe and the anterior-temporal and posterior-medial system could serve as stage-specific functional markers in early Alzheimer's disease.

Differential Regional Brain Spontaneous Activity in Subgroups of Mild Cognitive Impairment

Background: Amnestic mild cognitive impairment (aMCI) has a high conversion risk to Alzheimer's disease (AD). The aMCI patients may have only a memory deficit (single-domain-aMCI, sd-aMCI) or deficits in multiple cognitive domains (multiple-domain-aMCI, md-aMCI). However, differences in intrinsic brain activity between these two sub-types remain unclear. Method: Neuropsychological and resting-state functional magnetic resonance imaging (fMRI) data were acquired from 24 patients with sd-aMCI, 23 patients with md-aMCI, and 32 healthy controls (HCs). We used the fractional amplitude of low-frequency fluctuation (fALFF) to characterize the intensity of spontaneous brain activity. The analysis of covariance (ANCOVA) and post hoc tests was performed to determine the between-group differences in fALFF. Results: We found higher fALFF in left-sided superior-to-middle frontal gyri and middle-to-inferior temporal gyri in sd-aMCI compared to both the md-aMCI and HCs. Conversely, a lower fALFF was found in the left inferior parietal lobe in both the md-aMCI and sd-aMCI patients. The fALFF values in the left middle and inferior temporal gyri were correlated with cognitive performances. Conclusion: The gradual reduction in the left inferior parietal lobe from single to multiple domain aMCI suggest a functional inefficiency underlying cognitive impairment, while increased activity in the frontal and temporal gyri in sd-aMCI rather than md-aMCI might indicate functional compensation. This study indicates differential functional profiles in the sd-aMCI and md-aMCI, which may be helpful for the prediction of the future conversion of aMCI to AD.