Different effects of soluble and aggregated amyloid β42 on gene/protein expression and enzyme activity involved in insulin and APP pathways

Plasma metabolic profiles predict future dementia and dementia subtypes: a prospective analysis of 274,160 participants

BACKGROUND

Blood-based biomarkers for dementia are gaining attention due to their non-invasive nature and feasibility in regular healthcare settings. Here, we explored the associations between 249 metabolites with all-cause dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VaD) and assessed their predictive potential.

METHODS

This study included 274,160 participants from the UK Biobank. Cox proportional hazard models were employed to investigate longitudinal associations between metabolites and dementia. The importance of these metabolites was quantified using machine learning algorithms, and a metabolic risk score (MetRS) was subsequently developed for each dementia type. We further investigated how MetRS stratified the risk of dementia onset and assessed its predictive performance, both alone and in combination with demographic and cognitive predictors.

RESULTS

During a median follow-up of 14.01 years, 5274 participants developed dementia. Of the 249 metabolites examined, 143 were significantly associated with incident ACD, 130 with AD, and 140 with VaD. Among metabolites significantly associated with dementia, lipoprotein lipid concentrations, linoleic acid, sphingomyelin, glucose, and branched-chain amino acids ranked top in importance. Individuals within the top tertile of MetRS faced a significantly greater risk of developing dementia than those in the lowest tertile. When MetRS was combined with demographic and cognitive predictors, the model yielded the area under the receiver operating characteristic curve (AUC) values of 0.857 for ACD, 0.861 for AD, and 0.873 for VaD.

CONCLUSIONS

We conducted the largest metabolome investigation of dementia to date, for the first time revealed the metabolite importance ranking, and highlighted the contribution of plasma metabolites for dementia prediction.

Post-Translational Modifications of BACE1 in Alzheimer's Disease

Beta-Amyloid Cleaving Enzyme1 (BACE1) is a monospecific enzyme for the key rate-limiting step in the synthesis of beta-amyloid(Aβ) from cleavage of amyloid precursor protein (APP), to form senile plaques and causes cognitive dysfunction in Alzheimer's disease (AD). Post-translation modifications of BACE1, such as acetylation, glycosylation, palmitoylation, phosphorylation, play a crucial role in the trafficking and maturation process of BACE1. The study of BACE1 is of great importance not only for understanding the formation of toxic Aβ but also for the development of an effective therapeutic target for the treatment of AD. This paper review recent advances in the studies about BACE1, with focuses being paid to the relationship of Aβ, BACE1 with post- translational regulation of BACE1. In addition, we specially reviewed studies about the compounds that can be used to affect post-translational regulation of BACE1 or regulate BACE1 in the literature, which can be used for subsequent research on whether BACE1 is a post-translationally modified drug.

The Aβ(1-38) peptide is a negative regulator of the Aβ(1-42) peptide implicated in Alzheimer disease progression

The pool of β-Amyloid (Aβ) length variants detected in preclinical and clinical Alzheimer disease (AD) samples suggests a diversity of roles for Aβ peptides. We examined how a naturally occurring variant, e.g. Aβ(1-38), interacts with the AD-related variant, Aβ(1-42), and the predominant physiological variant, Aβ(1-40). Atomic force microscopy, Thioflavin T fluorescence, circular dichroism, dynamic light scattering, and surface plasmon resonance reveal that Aβ(1-38) interacts differently with Aβ(1-40) and Aβ(1-42) and, in general, Aβ(1-38) interferes with the conversion of Aβ(1-42) to a β-sheet-rich aggregate. Functionally, Aβ(1-38) reverses the negative impact of Aβ(1-42) on long-term potentiation in acute hippocampal slices and on membrane conductance in primary neurons, and mitigates an Aβ(1-42) phenotype in Caenorhabditis elegans. Aβ(1-38) also reverses any loss of MTT conversion induced by Aβ(1-40) and Aβ(1-42) in HT-22 hippocampal neurons and APOE ε4-positive human fibroblasts, although the combination of Aβ(1-38) and Aβ(1-42) inhibits MTT conversion in APOE ε4-negative fibroblasts. A greater ratio of soluble Aβ(1-42)/Aβ(1-38) [and Aβ(1-42)/Aβ(1-40)] in autopsied brain extracts correlates with an earlier age-at-death in males (but not females) with a diagnosis of AD. These results suggest that Aβ(1-38) is capable of physically counteracting, potentially in a sex-dependent manner, the neuropathological effects of the AD-relevant Aβ(1-42).

Reduction of aluminum ion neurotoxicity through a small peptide application - NAP treatment of Alzheimer's disease

Alzheimer's disease (AD) is the most common cause of dementia in late life. It is difficult to precisely diagnose AD at early stages, making biomarker search essential for further developments. The objective of this study was to identify protein biomarkers associated with aluminum ions toxicity (AD-like toxicity) in a human neuroblastoma cell model, SH-SY5Y and assess potential prevention by NAP (NAPVSIPQ). Complete proteomic techniques were implemented. Four proteins were identified as up-regulated with aluminum ion treatment, CBP80/20-dependent translation initiation factor (CTIF), Early endosome antigen 1 (EEA1), Leucine-rich repeat neuronal protein 4 (LRRN4) and Phosphatidylinositol 3-kinase regulatory subunit beta (PI3KR2). Of these four proteins, EEA1 and PI3KR2 were down-regulated after NAP-induced neuroprotective activity in neuroblastoma cells. Thus, aluminum ions may increase the risk for neurotoxicity in AD, and the use of NAP is suggested as a treatment to provide additional protection against the effects of aluminum ions, via EEA1 and PI3KR2, associated with sorting and processing of the AD amyloid precursor protein (APP) through the endosomal system.

Diabetic Microvascular Disease: An Endocrine Society Scientific Statement

Both type 1 and type 2 diabetes adversely affect the microvasculature in multiple organs. Our understanding of the genesis of this injury and of potential interventions to prevent, limit, or reverse injury/dysfunction is continuously evolving. This statement reviews biochemical/cellular pathways involved in facilitating and abrogating microvascular injury. The statement summarizes the types of injury/dysfunction that occur in the three classical diabetes microvascular target tissues, the eye, the kidney, and the peripheral nervous system; the statement also reviews information on the effects of diabetes and insulin resistance on the microvasculature of skin, brain, adipose tissue, and cardiac and skeletal muscle. Despite extensive and intensive research, it is disappointing that microvascular complications of diabetes continue to compromise the quantity and quality of life for patients with diabetes. Hopefully, by understanding and building on current research findings, we will discover new approaches for prevention and treatment that will be effective for future generations.

The impact of methylphenidate and its enantiomers on dopamine synthesis and metabolism in vitro

Methylphenidate (MPH), a psychostimulant, is an effective first-line treatment for the symptoms associated with Attention-Deficit/Hyperactivity Disorder (ADHD). Although most MPH formulations are composed of the racemic 1:1 mixture of the two enantiomers (d- and l-threo), converging lines of evidence indicate that d-threo MPH seems to be superior to the l-isomer. We aimed to investigate whether MPH racemic mixture or pure enantiomers influence the enzyme activity of tyrosine hydroxylase (TH), monoamine oxidase B (MAO-B), catechol-O-methyltransferase (COMT), and aldehyde dehydrogenase (ALDH) in vitro in homogenates of rat PC12 cells incubated with racemic, d- and l-threo MPH (1nM up to 100μM), or a vehicle for control. We could observe dose dependent enhancement of TH activity with d-threo MPH, probably due to its higher affinity to the enzyme, which we could confirm for d-threo versus l-threo MPH via docking and molecular dynamic simulations analysis. MAO-B enzyme activity was found to be enhanced when incubated with both d- and l-isomers but not with the racemic mixture. This conflicting result was hypothesized to be due to possible aggregation of the two enantiomers or other molecular conformations. Such a possible interaction was observed indirectly, when TH was incubated with constant d-threo MPH while increasing l-isomer (increasing total MPH concentrations). Hence, TH activity was slightly decreased with increased l-isomer. In conclusion, the current in vitro investigation points to the stereoselectivity of the investigated enzymes and pharmacological effects of MPH enantiomers.

Knowledge-Based Compact Disease Models: A Rapid Path from High-Throughput Data to Understanding Causative Mechanisms for a Complex Disease

High-throughput profiling of human tissues typically yields the gene lists composed of a variety of more or less relevant molecular entities. These lists are riddle by false positive observations that often obstruct generation of mechanistic hypothesis that may explain complex phenotype. From general probabilistic considerations, the gene lists enriched by the mechanistically relevant targets can be far more useful for subsequent experimental design or data interpretation. Using Alzheimer's disease as example, the candidate gene lists were processed into different tiers of evidence consistency established by enrichment analysis across subdatasets collected within the same experiment and across different experiments and platforms. The cutoffs were established empirically through ontological and semantic enrichment; resultant shortened gene list was reexpanded by Ingenuity Pathway Assistant tool. The resulting subnetworks provided the basis for generating mechanistic hypotheses that were partially validated by mined experimental evidence. This approach differs from previous consistency-based studies in that the cutoff on the Receiver Operating Characteristic of the true-false separation process is optimized by flexible selection of the consistency building procedure. The resultant Compact Disease Models (CDM) composed of the gene list distilled by this analytic technique and its network-based representation allowed us to highlight possible role of the protein traffic vesicles in the pathogenesis of Alzheimer's. Considering the distances and complexity of protein trafficking in neurons, it is plausible to hypothesize that spontaneous protein misfolding along with a shortage of growth stimulation may provide a shortcut to neurodegeneration. Several potentially overlapping scenarios of early-stage Alzheimer pathogenesis are discussed, with an emphasis on the protective effects of Angiotensin receptor 1 (AT-1) mediated antihypertensive response on cytoskeleton remodeling, along with neuronal activation of oncogenes, luteinizing hormone signaling and insulin-related growth regulation, forming a pleiotropic model of its early stages. Compact Disease Model generation is a flexible approach for high-throughput data analysis that allows extraction of meaningful, mechanism-centered gene sets compatible with instant translation of the results into testable hypotheses.

The Essential Role of Soluble Aβ Oligomers in Alzheimer's Disease

Alzheimer's disease (AD) is a common neurodegenerative disease characterized by amyloid plaque and neurofibrillary tangles (NFT). With the finding that soluble nonfibrillar Aβ levels actually correlate strongly with the severity of the disease, the initial focus on amyloid plaques shifted to the contemporary concept that AD memory failure is caused by soluble Aβ oligomers. The soluble Aβ are known to be more neurotoxicthan fibrillar Aβ species. In this paper, we summarize the essential role of soluble Aβ oligomers in AD and discuss therapeutic strategies that target soluble Aβ oligomers.

Amyloid β oligomers in Alzheimer's disease pathogenesis, treatment, and diagnosis

Protein aggregation is common to dozens of diseases including prionoses, diabetes, Parkinson's and Alzheimer's. Over the past 15 years, there has been a paradigm shift in understanding the structural basis for these proteinopathies. Precedent for this shift has come from investigation of soluble Aβ oligomers (AβOs), toxins now widely regarded as instigating neuron damage leading to Alzheimer's dementia. Toxic AβOs accumulate in AD brain and constitute long-lived alternatives to the disease-defining Aβ fibrils deposited in amyloid plaques. Key experiments using fibril-free AβO solutions demonstrated that while Aβ is essential for memory loss, the fibrillar Aβ in amyloid deposits is not the agent. The AD-like cellular pathologies induced by AβOs suggest their impact provides a unifying mechanism for AD pathogenesis, explaining why early stage disease is specific for memory and accounting for major facets of AD neuropathology. Alternative ideas for triggering mechanisms are being actively investigated. Some research favors insertion of AβOs into membrane, while other evidence supports ligand-like accumulation at particular synapses. Over a dozen candidate toxin receptors have been proposed. AβO binding triggers a redistribution of critical synaptic proteins and induces hyperactivity in metabotropic and ionotropic glutamate receptors. This leads to Ca(2+) overload and instigates major facets of AD neuropathology, including tau hyperphosphorylation, insulin resistance, oxidative stress, and synapse loss. Because different species of AβOs have been identified, a remaining question is which oligomer is the major pathogenic culprit. The possibility has been raised that more than one species plays a role. Despite some key unknowns, the clinical relevance of AβOs has been established, and new studies are beginning to point to co-morbidities such as diabetes and hypercholesterolemia as etiological factors. Because pathogenic AβOs appear early in the disease, they offer appealing targets for therapeutics and diagnostics. Promising therapeutic strategies include use of CNS insulin signaling enhancers to protect against the presence of toxins and elimination of the toxins through use of highly specific AβO antibodies. An AD-dependent accumulation of AβOs in CSF suggests their potential use as biomarkers and new AβO probes are opening the door to brain imaging. Overall, current evidence indicates that Aβ oligomers provide a substantive molecular basis for the cause, treatment and diagnosis of Alzheimer's disease.

Knowledge-based compact disease models identify new molecular players contributing to early-stage Alzheimer's disease

BACKGROUND

High-throughput profiling of human tissues typically yield as results the gene lists comprised of a mix of relevant molecular entities with multiple false positives that obstruct the translation of such results into mechanistic hypotheses. From general probabilistic considerations, gene lists distilled for the mechanistically relevant components can be far more useful for subsequent experimental design or data interpretation.

RESULTS

The input candidate gene lists were processed into different tiers of evidence consistency established by enrichment analysis across subsets of the same experiments and across different experiments and platforms. The cut-offs were established empirically through ontological and semantic enrichment; resultant shortened gene list was re-expanded by Ingenuity Pathway Assistant tool. The resulting sub-networks provided the basis for generating mechanistic hypotheses that were partially validated by literature search. This approach differs from previous consistency-based studies in that the cut-off on the Receiver Operating Characteristic of the true-false separation process is optimized by flexible selection of the consistency building procedure. The gene list distilled by this analytic technique and its network representation were termed Compact Disease Model (CDM). Here we present the CDM signature for the study of early-stage Alzheimer's disease. The integrated analysis of this gene signature allowed us to identify the protein traffic vesicles as prominent players in the pathogenesis of Alzheimer's. Considering the distances and complexity of protein trafficking in neurons, it is plausible that spontaneous protein misfolding along with a shortage of growth stimulation result in neurodegeneration. Several potentially overlapping scenarios of early-stage Alzheimer pathogenesis have been discussed, with an emphasis on the protective effects of AT-1 mediated antihypertensive response on cytoskeleton remodeling, along with neuronal activation of oncogenes, luteinizing hormone signaling and insulin-related growth regulation, forming a pleiotropic model of its early stages. Alignment with emerging literature confirmed many predictions derived from early-stage Alzheimer's disease' CDM.

CONCLUSIONS

A flexible approach for high-throughput data analysis, the Compact Disease Model generation, allows extraction of meaningful, mechanism-centered gene sets compatible with instant translation of the results into testable hypotheses.

Glucose levels and risk of dementia

BACKGROUND

Diabetes is a risk factor for dementia. It is unknown whether higher glucose levels increase the risk of dementia in people without diabetes.

METHODS

We used 35,264 clinical measurements of glucose levels and 10,208 measurements of glycated hemoglobin levels from 2067 participants without dementia to examine the relationship between glucose levels and the risk of dementia. Participants were from the Adult Changes in Thought study and included 839 men and 1228 women whose mean age at baseline was 76 years; 232 participants had diabetes, and 1835 did not. We fit Cox regression models, stratified according to diabetes status and adjusted for age, sex, study cohort, educational level, level of exercise, blood pressure, and status with respect to coronary and cerebrovascular diseases, atrial fibrillation, smoking, and treatment for hypertension.

RESULTS

During a median follow-up of 6.8 years, dementia developed in 524 participants (74 with diabetes and 450 without). Among participants without diabetes, higher average glucose levels within the preceding 5 years were related to an increased risk of dementia (P=0.01); with a glucose level of 115 mg per deciliter (6.4 mmol per liter) as compared with 100 mg per deciliter (5.5 mmol per liter), the adjusted hazard ratio for dementia was 1.18 (95% confidence interval [CI], 1.04 to 1.33). Among participants with diabetes, higher average glucose levels were also related to an increased risk of dementia (P=0.002); with a glucose level of 190 mg per deciliter (10.5 mmol per liter) as compared with 160 mg per deciliter (8.9 mmol per liter), the adjusted hazard ratio was 1.40 (95% CI, 1.12 to 1.76).

CONCLUSIONS

Our results suggest that higher glucose levels may be a risk factor for dementia, even among persons without diabetes. (Funded by the National Institutes of Health.)