NACC2, a molecular effector of miR-132 regulation at the interface between adult neurogenesis and Alzheimer's disease

The generation of new neurons at the hippocampal neurogenic niche, known as adult hippocampal neurogenesis (AHN), and its impairment, have been implicated in Alzheimer's disease (AD). MicroRNA-132 (miR-132), the most consistently downregulated microRNA (miRNA) in AD, was recently identified as a potent regulator of AHN, exerting multilayered proneurogenic effects in adult neural stem cells (NSCs) and their progeny. Supplementing miR-132 in AD mouse brain restores AHN and relevant memory deficits, yet the exact mechanisms involved are still unknown. Here, we identify NACC2 as a novel miR-132 target implicated in both AHN and AD. miR-132 deficiency in mouse hippocampus induces Nacc2 expression and inflammatory signaling in adult NSCs. We show that miR-132-dependent regulation of NACC2 is involved in the initial stages of human NSC differentiation towards astrocytes and neurons. Later, NACC2 function in astrocytic maturation becomes uncoupled from miR-132. We demonstrate that NACC2 is present in reactive astrocytes surrounding amyloid plaques in mouse and human AD hippocampus, and that there is an anticorrelation between miR-132 and NACC2 levels in AD and upon induction of inflammation. Unraveling the molecular mechanisms by which miR-132 regulates neurogenesis and cellular reactivity in AD, will provide valuable insights towards its possible application as a therapeutic target.

Aged-Related Changes in Microglia and Neurodegenerative Diseases: Exploring the Connection

Microglial cells exhibit properties akin to macrophages, thereby enabling them to support and protect the central nervous system environment. Aging induces alterations in microglial polarization, resulting in a shift toward a neurotoxic phenotype characterized by increased expression of pro-inflammatory markers. Dysregulation of microglial cells' regulatory pathways and interactions with neurons contribute to chronic activation and neurodegeneration. A better understanding of the involvement of microglia in neurodegenerative diseases such as Alzheimer's and Parkinson's is a critical topic for studying the role of inflammatory responses in disease progression. Furthermore, the metabolic changes in aged microglia, including the downregulation of oxidative phosphorylation, are discussed in this review. Understanding these mechanisms is crucial for developing better preventive and therapeutic strategies.

Contributions of genetic variation in astrocytes to cell and molecular mechanisms of risk and resilience to late onset Alzheimer's disease

Reactive astrocytes are associated with Alzheimer's disease (AD), and several AD genetic risk variants are associated with genes highly expressed in astrocytes. However, the contribution of genetic risk within astrocytes to cellular processes relevant to the pathogenesis of AD remains ill-defined. Here we present a resource for studying AD genetic risk in astrocytes using a large collection of induced pluripotent stem cell (iPSC) lines from deeply phenotyped individuals with a range of neuropathological and cognitive outcomes. IPSC lines from forty-four individuals were differentiated into astrocytes followed by unbiased molecular profiling using RNA sequencing and tandem mass tag-mass spectrometry. We demonstrate the utility of this resource in examining gene- and pathway-level associations with clinical and neuropathological traits, as well as in analyzing genetic risk and resilience factors through parallel analyses of iPSC-astrocytes and brain tissue from the same individuals. Our analyses reveal that genes and pathways altered in iPSC-derived astrocytes from AD individuals are concordantly dysregulated in AD brain tissue. This includes increased prefoldin proteins, extracellular matrix factors, COPI-mediated trafficking components and reduced proteins involved in cellular respiration and fatty acid oxidation. Additionally, iPSC-derived astrocytes from individuals resilient to high AD neuropathology show elevated basal levels of interferon response proteins and increased secretion of interferon gamma. Correspondingly, higher polygenic risk scores for AD are associated with lower levels of interferon response proteins. This study establishes an experimental system that integrates genetic information with a heterogeneous set of iPSCs to identify genetic contributions to molecular pathways affecting AD risk and resilience.

In vivo validation of late-onset Alzheimer's disease genetic risk factors

INTRODUCTION

Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action.

METHODS

Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE ε4/ε4 and Trem2*R47H. The potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts.

RESULTS

We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes.

DISCUSSION

These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

HIGHLIGHTS

A novel approach to validate genetic risk factors for late-onset AD (LOAD) is presented. LOAD risk variants were knocked in to conserved mouse loci. Variant effects were assayed by transcriptional analysis. Risk variants in Abca7, Mthfr, Plcg2, and Sorl1 loci modeled molecular signatures of clinical disease. This approach should generate more translationally relevant animal models.

Effectiveness and mechanisms of combined use of antioxidant nutrients in protecting against oxidative stress-induced neuronal loss and related neurological deficits

BACKGROUND

Oxidative stress is a well-known pathological factor driving neuronal loss and age-related neurodegenerative diseases. Melatonin, coenzyme Q10 and lecithin are three common nutrients with an antioxidative capacity. Here, we examined the effectiveness of them administrated individually and in combination in protecting against oxidative stress-induced neuronal death in vitro, and neurodegenerative conditions such as Alzheimer's disease and associated deficits in vivo.

METHODS

Mouse neuroblastoma Neuro-2a (N2a) cells were exposed with H2O2 for 6 h, and subsequently treated with melatonin, coenzyme Q10, and lecithin alone or in combination for further 24 h. Cell viability was assessed using the CCK-8 assay. Eight-week-old male mice were intraperitoneally injected with D-(+)-galactose for 10 weeks and administrated with melatonin, coenzyme Q10, lecithin, or in combination for 5 weeks starting from the sixth week, followed by behavioral tests to assess the effectiveness in mitigating neurological deficits, and biochemical assays to explore the underlying mechanisms.

RESULTS

Exposure to H2O2 significantly reduced the viability of N2a cells and increased oxidative stress and tau phosphorylation, all of which were alleviated by treatment with melatonin, coenzyme Q10, lecithin alone, and, most noticeably, by combined treatment. Administration of mice with D-(+)-galactose-induced oxidative stress and tau phosphorylation, brain aging, impairments in learning and memory, anxiety- and depression-like behaviors, and such detrimental effects were mitigated by melatonin, coenzyme Q10, lecithin alone, and, most consistently, by combined treatment.

CONCLUSIONS

These results suggest that targeting oxidative stress via supplementation of antioxidant nutrients, particularly in combination, is a better strategy to alleviate oxidative stress-mediated neuronal loss and brain dysfunction due to age-related neurodegenerative conditions.

Prediction of Cognitive Progression Due to Alzheimer's Disease in Normal Participants Based on Individual Default Mode Network Metabolic Connectivity Strength

BACKGROUND

Predicting cognitive decline among individuals in the aging population who are already amyloid-β (Aβ) positive or tau positive poses clinical challenges. In Alzheimer's disease research, intra-default mode network (DMN) connections play a pivotal role in diagnosis. In this article, we propose metabolic connectivity within the DMN as a supplementary biomarker to the Aβ, pathological tau, and neurodegeneration framework.

METHODS

Extracting data from 1292 participants in the Alzheimer's Disease Neuroimaging Initiative, we collected paired T1-weighted structural magnetic resonance imaging and 18F-labeled-fluorodeoxyglucose positron emission computed tomography scans. Individual metabolic DMN networks were constructed, and metabolic connectivity (MC) strength in the DMN was assessed. In the cognitively unimpaired group, the Cox model identified cognitively unimpaired (MC+), high-risk participants, with Kaplan-Meier survival analyses and hazard ratios revealing the strength of MC's predictive performance. Spearman correlation analyses explored relationships between MC strength, and Aβ, pathological tau, neurodegeneration biomarkers, and clinical scales. DMN standard uptake value ratio (SUVR) provided comparative insights in the analyses.

RESULTS

Both MC strength and SUVR exhibited gradual declines with cognitive deterioration, displaying significant intergroup differences. Survival analyses indicated enhanced Aβ and tau prediction with both metrics, with MC strength outperforming SUVR. Combined MC strength and Aβ yielded optimal predictive performance (hazard ratio = 9.29), followed by MC strength and tau (hazard ratio = 8.92). Generally, the strength of MC's correlations with Aβ, pathological tau, and neurodegeneration biomarkers exceeded SUVR.

CONCLUSIONS

Individuals with normal cognition and disrupted DMN metabolic connectivity face an elevated risk of cognitive decline linked to Aβ that precedes metabolic issues.

The causal effect of Alzheimer's disease and family history of Alzheimer's disease on non-ischemic cardiomyopathy and left ventricular structure and function: a Mendelian randomization study

Background

Previous studies have shown that Alzheimer's disease (AD) can cause myocardial damage. However, whether there is a causal association between AD and non-ischemic cardiomyopathy (NICM) remains unclear. Using a comprehensive two-sample Mendelian randomization (MR) method, we aimed to determine whether AD and family history of AD (FHAD) affect left ventricular (LV) structure and function and lead to NICM, including hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM).

Methods

The summary statistics for exposures [AD, paternal history of AD (PH-AD), and maternal history of AD (MH-AD)] and outcomes (NICM, HCM, DCM, and LV traits) were obtained from the large European genome-wide association studies. The causal effects were estimated using inverse variance weighted, MR-Egger, and weighted median methods. Sensitivity analyses were conducted, including Cochran's Q test, MR-Egger intercept test, MR pleiotropy residual sum and outlier, MR Steiger test, leave-one-out analysis, and the funnel plot.

Results

Genetically predicted AD was associated with a lower risk of NICM [odds ratio (OR) 0.9306, 95% confidence interval (CI) 0.8825-0.9813, p = 0.0078], DCM (OR 0.8666, 95% CI 0.7752-0.9689, p = 0.0119), and LV remodeling index (OR 0.9969, 95% CI 0.9940-0.9998, p = 0.0337). Moreover, genetically predicted PH-AD was associated with a decreased risk of NICM (OR 0.8924, 95% CI 0.8332-0.9557, p = 0.0011). MH-AD was also strongly associated with a decreased risk of NICM (OR 0.8958, 95% CI 0.8449-0.9498, p = 0.0002). Different methods of sensitivity analysis demonstrated the robustness of the results.

Conclusion

Our study revealed that AD and FHAD were associated with a decreased risk of NICM, providing a new genetic perspective on the pathogenesis of NICM.

Xenografted human microglia display diverse transcriptomic states in response to Alzheimer's disease-related amyloid-β pathology

Microglia are central players in Alzheimer's disease pathology but analyzing microglial states in human brain samples is challenging due to genetic diversity, postmortem delay and admixture of pathologies. To circumvent these issues, here we generated 138,577 single-cell expression profiles of human stem cell-derived microglia xenotransplanted in the brain of the AppNL-G-F model of amyloid pathology and wild-type controls. Xenografted human microglia adopt a disease-associated profile similar to that seen in mouse microglia, but display a more pronounced human leukocyte antigen or HLA state, likely related to antigen presentation in response to amyloid plaques. The human microglial response also involves a pro-inflammatory cytokine/chemokine cytokine response microglia or CRM response to oligomeric Aβ oligomers. Genetic deletion of TREM2 or APOE as well as APOE polymorphisms and TREM2R47H expression in the transplanted microglia modulate these responses differentially. The expression of other Alzheimer's disease risk genes is differentially regulated across the distinct cell states elicited in response to amyloid pathology. Thus, we have identified multiple transcriptomic cell states adopted by human microglia in a multipronged response to Alzheimer's disease-related pathology, which should be taken into account in translational studies.

Artificial intelligence for drug discovery and development in Alzheimer's disease

The complex molecular mechanism and pathophysiology of Alzheimer's disease (AD) limits the development of effective therapeutics or prevention strategies. Artificial Intelligence (AI)-guided drug discovery combined with genetics/multi-omics (genomics, epigenomics, transcriptomics, proteomics, and metabolomics) analysis contributes to the understanding of the pathophysiology and precision medicine of the disease, including AD and AD-related dementia. In this review, we summarize the AI-driven methodologies for AD-agnostic drug discovery and development, including de novo drug design, virtual screening, and prediction of drug-target interactions, all of which have shown potentials. In particular, AI-based drug repurposing emerges as a compelling strategy to identify new indications for existing drugs for AD. We provide several emerging AD targets from human genetics and multi-omics findings and highlight recent AI-based technologies and their applications in drug discovery using AD as a prototypical example. In closing, we discuss future challenges and directions in AI-based drug discovery for AD and other neurodegenerative diseases.

Artificial intelligence and open science in discovery of disease-modifying medicines for Alzheimer's disease

The high failure rate of clinical trials in Alzheimer's disease (AD) and AD-related dementia (ADRD) is due to a lack of understanding of the pathophysiology of disease, and this deficit may be addressed by applying artificial intelligence (AI) to "big data" to rapidly and effectively expand therapeutic development efforts. Recent accelerations in computing power and availability of big data, including electronic health records and multi-omics profiles, have converged to provide opportunities for scientific discovery and treatment development. Here, we review the potential utility of applying AI approaches to big data for discovery of disease-modifying medicines for AD/ADRD. We illustrate how AI tools can be applied to the AD/ADRD drug development pipeline through collaborative efforts among neurologists, gerontologists, geneticists, pharmacologists, medicinal chemists, and computational scientists. AI and open data science expedite drug discovery and development of disease-modifying therapeutics for AD/ADRD and other neurodegenerative diseases.

Novel Development and Prospects in Pathogenesis, Diagnosis, and Therapy of Alzheimer's Disease

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease with cognitive decline and behavioral dysfunction. AD will become a global public health concern due to its increasing prevalence brought on by the severity of global aging. It is critical to understand the pathogenic mechanisms of AD and investigate or pursue a viable therapy strategy in clinic. Amyloid-β (Aβ) accumulation and abnormally hyperphosphorylated tau protein are the main regulating variables in the pathological phase of AD. And neuroinflammation brought on by activated microglia was found to be one risk factor contributing to changes in Aβ and tau pathology. It is important to investigate the unique biomarkers of early diagnosis and advanced stage, which may help to elucidate the specific pathological process of AD and provide potential novel therapeutic targets or preventative measures.

Sex- and region-specific cortical and hippocampal whole genome transcriptome profiles from control and APP/PS1 Alzheimer's disease mice

A variety of Alzheimer's disease (AD) mouse models has been established and characterized within the last decades. To get an integrative view of the sophisticated etiopathogenesis of AD, whole genome transcriptome studies turned out to be indispensable. Here we carried out microarray data collection based on RNA extracted from the retrosplenial cortex and hippocampus of age-matched, eight months old male and female APP/PS1 AD mice and control animals to perform sex- and brain region specific analysis of transcriptome profiles. The results of our studies reveal novel, detailed insight into differentially expressed signature genes and related fold changes in the individual APP/PS1 subgroups. Gene ontology and Venn analysis unmasked that intersectional, upregulated genes were predominantly involved in, e.g., activation of microglial, astrocytic and neutrophilic cells, innate immune response/immune effector response, neuroinflammation, phagosome/proteasome activation, and synaptic transmission. The number of (intersectional) downregulated genes was substantially less in the different subgroups and related GO categories included, e.g., the synaptic vesicle docking/fusion machinery, synaptic transmission, rRNA processing, ubiquitination, proteasome degradation, histone modification and cellular senescence. Importantly, this is the first study to systematically unravel sex- and brain region-specific transcriptome fingerprints/signature genes in APP/PS1 mice. The latter will be of central relevance in future preclinical and clinical AD related studies, biomarker characterization and personalized medicinal approaches.

Explore the Role of Frailty as a Contributor to the Association Between AT(N) Profiles and Cognition in Alzheimer's Disease

Background

The relationship between Alzheimer's disease (AD)-related pathology and cognition was not exactly consistent.

Objective

To explore whether the association between AD pathology and cognition can be moderated by frailty.

Methods

We included 1711 participants from the Alzheimer's Disease Neuroimaging Initiative database. Levels of cerebrospinal fluid amyloid-β, p-tau, and t-tau were identified for AD-related pathology based on the amyloid-β/tau/neurodegeneration (AT[N]) framework. Frailty was measured using a modified Frailty Index-11 (mFI-11). Regression and interaction models were utilized to assess the relationship among frailty, AT(N) profiles, and cognition. Moderation models analyzed the correlation between AT(N) profiles and cognition across three frailty levels. All analyses were corrected for age, sex, education, and APOEɛ4 status.

Results

In this study, frailty (odds ratio [OR] = 1.71, p < 0.001) and AT(N) profiles (OR = 2.00, p < 0.001) were independently associated with cognitive status. The model fit was improved when frailty was added to the model examining the relationship between AT(N) profiles and cognition (p < 0.001). There was a significant interaction between frailty and AT(N) profiles in relation to cognitive status (OR = 1.12, pinteraction = 0.028). Comparable results were obtained when Mini-Mental State Examination scores were utilized as the measure of cognitive performance. The association between AT(N) profiles and cognition was stronger with the levels of frailty.

Conclusions

Frailty may diminish patients' resilience to AD pathology and accelerate cognitive decline resulting from abnormal AD-related pathology. In summary, frailty contributes to elucidating the relationship between AD-related pathology and cognitive impairment.

The inverse association between the apolipoprotein E ε4 allele and C-reactive protein levels is stronger in persons with obesity and diabetes

BACKGROUND

C-reactive protein (CRP) is lower in patients who carry the apolipoprotein E epsilon 4 allele variant (APOEε4) of the APOE gene. This could however be explained by other factors observed in APOEε4 carriers, such as lower body mass index (BMI), possibly less diabetes and more use of statins, all associated with CRP concentrations.

OBJECTIVES

To assess the association between CRP and APOEε4 stratified by BMI, statin use and diabetes.

METHODS

We included 2700 community-dwelling older adults from the Hordaland health study with genotyping of the APOE gene by a one-step polymerase chain reaction and CRP measured using immuno-MALDI-TOF MS. Differences in CRP concentrations by APOE (ε4 vs no ε4) were assessed using the Mann-Whitney U tests, also stratified by statin use, diabetes and BMI categories. Finally, we performed linear regression with log (CRP) as the outcome and APOEε4 together with statin use, diabetes, BMI and their respective interactions.

RESULTS

CRP was higher in APOEε4 carriers irrespective of BMI, diabetes and statin use. In APOEε4 non-carriers, CRP was elevated with diabetes and obesity as expected. However, this was attenuated or even reversed in APOEε4 carriers. Such differences were not observed for statin use.

CONCLUSIONS

Statin use, obesity or diabetes did not confound the known association between the APOEε4 allele and lower CRP. Our data suggest that CRP is less responsive to inflammatory cues involved in diabetes and obesity in APOEε4 carriers. Epidemiological studies should take note of these relationships, as CRP, APOEε4, diabetes and obesity are both linked to neurodegenerative and cardiovascular disease.

In vivo validation of late-onset Alzheimer's disease genetic risk factors

Introduction

Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action.

Methods

Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE4 and Trem2*R47H. Potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts.

Results

We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes.

Discussion

These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

Critical thinking of Alzheimer's transgenic mouse model: current research and future perspective

Transgenic models are useful tools for studying the pathogenesis of and drug development for Alzheimer's Disease (AD). AD models are constructed usually using overexpression or knock-in of multiple pathogenic gene mutations from familial AD. Each transgenic model has its unique behavioral and pathological features. This review summarizes the research progress of transgenic mouse models, and their progress in the unique mechanism of amyloid-β oligomers, including the first transgenic mouse model built in China based on a single gene mutation (PSEN1 V97L) found in Chinese familial AD. We further summarized the preclinical findings of drugs using the models, and their future application in exploring the upstream mechanisms and multitarget drug development in AD.

An interpretable Alzheimer's disease oligogenic risk score informed by neuroimaging biomarkers improves risk prediction and stratification

Introduction

Stratification of Alzheimer's disease (AD) patients into risk subgroups using Polygenic Risk Scores (PRS) presents novel opportunities for the development of clinical trials and disease-modifying therapies. However, the heterogeneous nature of AD continues to pose significant challenges for the clinical broadscale use of PRS. PRS remains unfit in demonstrating sufficient accuracy in risk prediction, particularly for individuals with mild cognitive impairment (MCI), and in allowing feasible interpretation of specific genes or SNPs contributing to disease risk. We propose adORS, a novel oligogenic risk score for AD, to better predict risk of disease by using an optimized list of relevant genetic risk factors.

Methods

Using whole genome sequencing data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (n  =  1,545), we selected 20 genes that exhibited the strongest correlations with FDG-PET and AV45-PET, recognized neuroimaging biomarkers that detect functional brain changes in AD. This subset of genes was incorporated into adORS to assess, in comparison to PRS, the prediction accuracy of CN vs. AD classification and MCI conversion prediction, risk stratification of the ADNI cohort, and interpretability of the genetic information included in the scores.

Results

adORS improved AUC scores over PRS in both CN vs. AD classification and MCI conversion prediction. The oligogenic model also refined risk-based stratification, even without the assistance of APOE, thus reflecting the true prevalence rate of the ADNI cohort compared to PRS. Interpretation analysis shows that genes included in adORS, such as ATF6, EFCAB11, ING5, SIK3, and CD46, have been observed in similar neurodegenerative disorders and/or are supported by AD-related literature.

Discussion

Compared to conventional PRS, adORS may prove to be a more appropriate choice of differentiating patients into high or low genetic risk of AD in clinical studies or settings. Additionally, the ability to interpret specific genetic information allows the focus to be shifted from general relative risk based on a given population to the information that adORS can provide for a single individual, thus permitting the possibility of personalized treatments for AD.

Neuronal γ-secretase regulates lipid metabolism, linking cholesterol to synaptic dysfunction in Alzheimer's disease

Presenilin mutations that alter γ-secretase activity cause familial Alzheimer's disease (AD), whereas ApoE4, an apolipoprotein for cholesterol transport, predisposes to sporadic AD. Both sporadic and familial AD feature synaptic dysfunction. Whether γ-secretase is involved in cholesterol metabolism and whether such involvement impacts synaptic function remains unknown. Here, we show that in human neurons, chronic pharmacological or genetic suppression of γ-secretase increases synapse numbers but decreases synaptic transmission by lowering the presynaptic release probability without altering dendritic or axonal arborizations. In search of a mechanism underlying these synaptic impairments, we discovered that chronic γ-secretase suppression robustly decreases cholesterol levels in neurons but not in glia, which in turn stimulates neuron-specific cholesterol-synthesis gene expression. Suppression of cholesterol levels by HMG-CoA reductase inhibitors (statins) impaired synaptic function similar to γ-secretase inhibition. Thus, γ-secretase enables synaptic function by maintaining cholesterol levels, whereas the chronic suppression of γ-secretase impairs synapses by lowering cholesterol levels.

GABAergic signaling abnormalities in a novel CLU mutation Alzheimer's disease mouse model

The CLU rs11136000C mutation (CLUC) is the third most common risk factor for Alzheimer's disease (AD). However, the mechanism by which CLUC leads to abnormal GABAergic signaling in AD is unclear. To address this question, this study establishes the first chimeric mouse model of CLUC AD. Examination of grafted CLUC medial ganglionic eminence progenitors (CLUC hiMGEs) revealed increased GAD65/67 and a high frequency of spontaneous releasing events. CLUC hiMGEs also impaired cognition in chimeric mice and caused AD-related pathologies. The expression of GABA A receptor, subunit alpha 2 (Gabrα2) was higher in chimeric mice. Interestingly, cognitive impairment in chimeric mice was reversed by treatment with pentylenetetrazole, which is a GABA A receptor inhibitor. Taken together, these findings shed light on the pathogenesis of CLUC AD using a novel humanized animal model and suggest sphingolipid signaling over-activation as a potential mechanism of GABAergic signaling disorder.

MEG3 activates necroptosis in human neuron xenografts modeling Alzheimer's disease

Neuronal cell loss is a defining feature of Alzheimer's disease (AD), but the underlying mechanisms remain unclear. We xenografted human or mouse neurons into the brain of a mouse model of AD. Only human neurons displayed tangles, Gallyas silver staining, granulovacuolar neurodegeneration (GVD), phosphorylated tau blood biomarkers, and considerable neuronal cell loss. The long noncoding RNA MEG3 was strongly up-regulated in human neurons. This neuron-specific long noncoding RNA is also up-regulated in AD patients. MEG3 expression alone was sufficient to induce necroptosis in human neurons in vitro. Down-regulation of MEG3 and inhibition of necroptosis using pharmacological or genetic manipulation of receptor-interacting protein kinase 1 (RIPK1), RIPK3, or mixed lineage kinase domain-like protein (MLKL) rescued neuronal cell loss in xenografted human neurons. This model suggests potential therapeutic approaches for AD and reveals a human-specific vulnerability to AD.

Pitfalls of predicting age-related traits by polygenic risk scores

Polygenic risk scores (PRS) are a method increasingly used to capture the combined effect of genome-wide significant variants and those which individually do not show genome-wide significant association but are likely to contribute to the risk of developing diseases. However, their practical use incurs complications and inconsistencies that so far limit their clinical applicability. The aims of the present review are to discuss the PRS for age-related diseases and to highlight pitfalls and limitations of PRS prediction accuracy due to ageing and mortality effects. We argue that the PRS is widely used but the individual's PRS values differ substantially depending on the number of genetic variants included, the discovery GWAS and the method employed to generate them. Moreover, for neurodegenerative disorders, although an individual's genetics do not change with age, the actual score depends on the age of the sample used in the discovery GWAS and is likely to reflect the individual's disease risk at this particular age. Improvement of PRS prediction accuracy for neurodegenerative disorders will come from two sides, both the precision of clinical diagnoses, and a careful attention to the age distribution in the underlying samples and validation of the prediction in longitudinal studies.

Education counteracts the genetic risk of Alzheimer's disease without an interaction effect

Background

Alzheimer's disease (AD) is a major cause of disability and mortality in older adults. This study aimed to investigate the association of AD with education and genetic factors.

Methods

We conducted a prospective cohort study using data from the UK Biobank. Genetic risk was assessed using a polygenic risk score for AD. The educational level was categorized as either low, intermediate, or high. AD was defined using the International Classification of Diseases and Related Health Problems, 10th revision. Logistic regression models were used to investigate the independent and combined effects of genetic factors and educational levels on the risk of AD.

Results

We included 318,535 participants in this study (age: 56.53 ± 8.09 years; male: 44.81%). Compared with a low genetic risk, a high genetic risk was associated with a significantly greater risk of AD (OR = 7.09, 95% CI: 6.09-8.26). A high educational level was associated with a 30% lower risk of AD compared with a low educational level (OR = 0.70, 95% CI: 0.60-0.81). Combining genetic risk and education categories, individuals with a low genetic risk and high educational level had a more than 90% (OR = 0.09, 95% CI: 0.05-0.16) lower risk of AD compared to those with a high genetic risk and low educational level. There was no significant interaction between genetic risk and educational level regarding AD risk (p for interaction = 0.359).

Conclusion

Education counteracts the genetic risk of AD, without an interaction effect. Increasing education to reduce the incidence of AD is of same importance across individuals with different genetic risk.

Unraveling patient heterogeneity in complex diseases through individualized co-expression networks: a perspective

This perspective highlights the potential of individualized networks as a novel strategy for studying complex diseases through patient stratification, enabling advancements in precision medicine. We emphasize the impact of interpatient heterogeneity resulting from genetic and environmental factors and discuss how individualized networks improve our ability to develop treatments and enhance diagnostics. Integrating system biology, combining multimodal information such as genomic and clinical data has reached a tipping point, allowing the inference of biological networks at a single-individual resolution. This approach generates a specific biological network per sample, representing the individual from which the sample originated. The availability of individualized networks enables applications in personalized medicine, such as identifying malfunctions and selecting tailored treatments. In essence, reliable, individualized networks can expedite research progress in understanding drug response variability by modeling heterogeneity among individuals and enabling the personalized selection of pharmacological targets for treatment. Therefore, developing diverse and cost-effective approaches for generating these networks is crucial for widespread application in clinical services.

Associations of air pollution with all-cause dementia, Alzheimer's disease, and vascular dementia: a prospective cohort study based on 437,932 participants from the UK biobank

Objective

To prospectively assess whether air pollution, including PM2.5, PM10, and NOx, is associated with the risk of all-cause dementia, Alzheimer's disease (AD), and vascular dementia, and to investigate the potential relationship between air pollution and genetic susceptibility in the development of AD.

Methods and results

Our study included 437,932 participants from the UK Biobank with a median follow-up period of over 10 years. Using a Cox proportional hazards model, we found that participants exposed to PM2.5 levels of ≥10 μg/m3 had a higher risk of developing all-cause dementia (HR = 1.1; 95% CI: 1.05-1.28; p < 0.05) compared to the group exposed to PM2.5 levels of <10 μg/m3. However, there was no significant association between PM10 levels of ≥15 μg/m3 and the risk of all-cause dementia, AD, or vascular dementia when compared to the group exposed to PM10 levels of <15 μg/m3. On the other hand, participants exposed to NOx levels of ≥50 μg/m3 had a significantly higher risk of all-cause dementia (HR = 1.14; 95% CI: 1.02-1.26; p < 0.05) and AD (HR = 1.26; 95% CI: 1.08-1.48; p < 0.05) compared to the group exposed to NOx levels of <50 μg/m3. Furthermore, we examined the combined effect of air pollution (PM2.5, PM10, and NOx) and Alzheimer's disease genetic risk score (AD-GRS) on the development of AD using a Cox proportional hazards model. Among participants with a high AD-GRS, those exposed to NOx levels of ≥50 μg/m3 had a significantly higher risk of AD compared to those in the group exposed to NOx levels of <50 μg/m3 (HR = 1.36; 95% CI: 1.03-1.18; p < 0.05). Regardless of air pollutant levels (PM2.5, PM10, or NOx), participants with a high AD-GRS had a significantly increased risk of developing AD. Similar results were obtained when assessing multiple variables using inverse probability of treatment weighting (IPTW).

Conclusion

Our findings indicate that individuals living in areas with PM2.5 levels of ≥10 μg/m3 or NOx levels of ≥50 μg/m3 are at a higher risk of developing all-cause dementia. Moreover, individuals with a high AD-GRS demonstrated an increased risk of developing AD, particularly in the presence of NOx ≥ 50 μg/m3.

Microenvironment Restruction of Emerging 2D Materials and their Roles in Therapeutic and Diagnostic Nano-Bio-Platforms

Engineering advanced therapeutic and diagnostic nano-bio-platforms (NBPFs) have emerged as rapidly-developed pathways against a wide range of challenges in antitumor, antipathogen, tissue regeneration, bioimaging, and biosensing applications. Emerged 2D materials have attracted extensive scientific interest as fundamental building blocks or nanostructures among material scientists, chemists, biologists, and doctors due to their advantageous physicochemical and biological properties. This timely review provides a comprehensive summary of creating advanced NBPFs via emerging 2D materials (2D-NBPFs) with unique insights into the corresponding molecularly restructured microenvironments and biofunctionalities. First, it is focused on an up-to-date overview of the synthetic strategies for designing 2D-NBPFs with a cross-comparison of their advantages and disadvantages. After that, the recent key achievements are summarized in tuning the biofunctionalities of 2D-NBPFs via molecularly programmed microenvironments, including physiological stability, biocompatibility, bio-adhesiveness, specific binding to pathogens, broad-spectrum pathogen inhibitors, stimuli-responsive systems, and enzyme-mimetics. Moreover, the representative therapeutic and diagnostic applications of 2D-NBPFs are also discussed with detailed disclosure of their critical design principles and parameters. Finally, current challenges and future research directions are also discussed. Overall, this review will provide cutting-edge and multidisciplinary guidance for accelerating future developments and therapeutic/diagnostic applications of 2D-NBPFs.

microRNA-132 regulates gene expression programs involved in microglial homeostasis

microRNA-132 (miR-132), a known neuronal regulator, is one of the most robustly downregulated microRNAs (miRNAs) in the brain of Alzheimer's disease (AD) patients. Increasing miR-132 in AD mouse brain ameliorates amyloid and Tau pathologies, and also restores adult hippocampal neurogenesis and memory deficits. However, the functional pleiotropy of miRNAs requires in-depth analysis of the effects of miR-132 supplementation before it can be moved forward for AD therapy. We employ here miR-132 loss- and gain-of-function approaches using single-cell transcriptomics, proteomics, and in silico AGO-CLIP datasets to identify molecular pathways targeted by miR-132 in mouse hippocampus. We find that miR-132 modulation significantly affects the transition of microglia from a disease-associated to a homeostatic cell state. We confirm the regulatory role of miR-132 in shifting microglial cell states using human microglial cultures derived from induced pluripotent stem cells.

Neurodegeneration cell per cell

The clinical definition of neurodegenerative diseases is based on symptoms that reflect terminal damage of specific brain regions. This is misleading as it tells little about the initial disease processes. Circuitry failures that underlie the clinical symptomatology are themselves preceded by clinically mostly silent, slowly progressing multicellular processes that trigger or are triggered by the accumulation of abnormally folded proteins such as Aβ, Tau, TDP-43, and α-synuclein, among others. Methodological advances in single-cell omics, combined with complex genetics and novel ways to model complex cellular interactions using induced pluripotent stem (iPS) cells, make it possible to analyze the early cellular phase of neurodegenerative disorders. This will revolutionize the way we study those diseases and will translate into novel diagnostics and cell-specific therapeutic targets, stopping these disorders in their early track before they cause difficult-to-reverse damage to the brain.

TOMM40 Genetic Variants Cause Neuroinflammation in Alzheimer's Disease

Translocase of outer mitochondrial membrane 40 (TOMM40) is located in the outer membrane of mitochondria. TOMM40 is essential for protein import into mitochondria. TOMM40 genetic variants are believed to increase the risk of Alzheimer's disease (AD) in different populations. In this study, three exonic variants (rs772262361, rs157581, and rs11556505) and three intronic variants (rs157582, rs184017, and rs2075650) of the TOMM40 gene were identified from Taiwanese AD patients using next-generation sequencing. Associations between the three TOMM40 exonic variants and AD susceptibility were further evaluated in another AD cohort. Our results showed that rs157581 (c.339T > C, p.Phe113Leu, F113L) and rs11556505 (c.393C > T, p.Phe131Leu, F131L) were associated with an increased risk of AD. We further utilized cell models to examine the role of TOMM40 variation in mitochondrial dysfunction that causes microglial activation and neuroinflammation. When expressed in BV2 microglial cells, the AD-associated mutant (F113L) or (F131L) TOMM40 induced mitochondrial dysfunction and oxidative stress-induced activation of microglia and NLRP3 inflammasome. Pro-inflammatory TNF-α, IL-1β, and IL-6 released by mutant (F113L) or (F131L) TOMM40-activated BV2 microglial cells caused cell death of hippocampal neurons. Taiwanese AD patients carrying TOMM40 missense (F113L) or (F131L) variants displayed an increased plasma level of inflammatory cytokines IL-6, IL-18, IL-33, and COX-2. Our results provide evidence that TOMM40 exonic variants, including rs157581 (F113L) and rs11556505 (F131L), increase the AD risk of the Taiwanese population. Further studies suggest that AD-associated mutant (F113L) or (F131L) TOMM40 cause the neurotoxicity of hippocampal neurons by inducing the activation of microglia and NLRP3 inflammasome and the release of pro-inflammatory cytokines.

Rate of tau propagation is a heritable disease trait in genetically diverse mouse strains

The speed and scope of cognitive deterioration in Alzheimer's disease is highly associated with the advancement of tau neurofibrillary lesions across brain networks. We tested whether the rate of tau propagation is a heritable disease trait in a large, well-characterized cohort of genetically divergent mouse strains. Using an AAV-based model system, P301L-mutant human tau (hTau) was introduced into the entorhinal cortex of mice derived from 18 distinct lines. The extent of tau propagation was measured by distinguishing hTau-producing cells from neurons that were recipients of tau transfer. Heritability calculation revealed that 43% of the variability in tau spread was due to genetic variants segregating across background strains. Strain differences in glial markers were also observed, but did not correlate with tau propagation. Identifying unique genetic variants that influence the progression of pathological tau may uncover novel molecular targets to prevent or slow the pace of tau spread and cognitive decline.

The role of structural variations in Alzheimer's disease and other neurodegenerative diseases

Dozens of single nucleotide polymorphisms (SNPs) related to Alzheimer's disease (AD) have been discovered by large scale genome-wide association studies (GWASs). However, only a small portion of the genetic component of AD can be explained by SNPs observed from GWAS. Structural variation (SV) can be a major contributor to the missing heritability of AD; while SV in AD remains largely unexplored as the accurate detection of SVs from the widely used array-based and short-read technology are still far from perfect. Here, we briefly summarized the strengths and weaknesses of available SV detection methods. We reviewed the current landscape of SV analysis in AD and SVs that have been found associated with AD. Particularly, the importance of currently less explored SVs, including insertions, inversions, short tandem repeats, and transposable elements in neurodegenerative diseases were highlighted.

Overlapping brain correlates of superior cognition among children at genetic risk for Alzheimer's disease and/or major depressive disorder

Early life adversity (ELA) tends to accelerate neurobiological ageing, which, in turn, is thought to heighten vulnerability to both major depressive disorder (MDD) and Alzheimer's disease (AD). The two conditions are putatively related, with MDD representing either a risk factor or early symptom of AD. Given the substantial environmental susceptibility of both disorders, timely identification of their neurocognitive markers could facilitate interventions to prevent clinical onset. To this end, we analysed multimodal data from the Adolescent Brain and Cognitive Development study (ages 9-10 years). To disentangle genetic from correlated genetic-environmental influences, while also probing gene-adversity interactions, we compared adoptees, a group generally exposed to substantial ELA, with children raised by their biological families via genetic risk scores (GRS) from genome-wide association studies. AD and MDD GRSs predicted overlapping and widespread neurodevelopmental alterations associated with superior fluid cognition. Specifically, among adoptees only, greater AD GRS were related to accelerated structural maturation (i.e., cortical thinning) and higher MDD GRS were linked to delayed functional neurodevelopment, as reflected in compensatory brain activation on an inhibitory control task. Our study identifies compensatory mechanisms linked to MDD risk and highlights the potential cognitive benefits of accelerated maturation linked to AD vulnerability in late childhood.

Microglia PTK2B/Pyk2 in the Pathogenesis of Alzheimer's Disease

Alzheimer's disease (AD) is a highly hereditary disease with complex genetic susceptibility factors. Extensive genome-wide association studies have established a distinct susceptibility link between the protein tyrosine kinase 2β (PTK2B) gene and late-onset Alzheimer's disease (LOAD), but the specific pathogenic mechanisms remain incompletely understood. PTK2B is known to be expressed in neurons, and recent research has revealed its more important significance in microglia. Elucidating the role of PTK2B high expression in microglia in AD's progression is crucial for uncovering novel pathogenic mechanisms of the disease. Our review of existing studies suggests a close relationship between PTK2B/proline-rich tyrosine kinase 2 (Pyk2) and tau pathology, and this process might be β-amyloid (Aβ) dependence. Pyk2 is hypothesized as a pivotal target linking Aβ and tau pathologies. Concurrently, Aβ-activated Pyk2 participates in the regulation of microglial activation and its proinflammatory functions. Consequently, it is reasonable to presume that Pyk2 in microglia contributes to amyloid-induced tau pathology in AD via a neuroinflammatory pathway. Furthermore, many things remain unclear, such as identifying the specific pathways that lead to the release of downstream inflammatory factors due to Pyk2 phosphorylation and whether all types of inflammatory factors can activate neuronal kinase pathways. Additionally, further in vivo experiments are essential to validate this hypothesized pathway. Considering PTK2B/Pyk2's potential role in AD pathogenesis, targeting this pathway may offer innovative and promising therapeutic approaches for AD.

Novel Genetic Variants in TP37, PIK3R1, CALM1, and PLCG2 of the Neurotrophin Signaling Pathway Are Associated with the Progression from Mild Cognitive Impairment to Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is a common neurodegenerative disease and mild cognitive impairment (MCI) is considered as the prodromal stage of AD. Previous studies showed that changes in the neurotrophin signaling pathway could lead to cognitive decline in AD. However, the association of single nucleotide polymorphisms (SNPs) in genes that are involved in this pathway with AD progression from MCI remains unclear.

OBJECTIVE

We investigated the associations between SNPs involved in the neurotrophin signaling pathway with AD progression.

METHODS

We performed single-locus analysis to identify neurotrophin-signaling-related SNPs associated with the AD progression using 767 patients from the Alzheimer's Disease Neuroimaging Initiative study and 1,373 patients from the National Alzheimer's Coordinating Center study. We constructed polygenic risk scores (PRSs) using the identified independent non-APOE SNPs and evaluated its prediction performance on AD progression.

RESULTS

We identified 25 SNPs significantly associated with AD progression with Bayesian false-discovery probability ≤0.8. Based on the linkage disequilibrium clumping and expression quantitative trait loci analysis, we found 6 potentially functional SNPs that were associated with AD progression independently. The PRS analysis quantified the combined effects of these SNPs on longitudinal cognitive assessments and biomarkers from cerebrospinal fluid and neuroimaging. The addition of PRSs to the prediction model for 3-year progression to AD from MCI significantly increased the predictive accuracy.

CONCLUSION

Genetic variants in the specific genes of the neurotrophin signaling pathway are predictors of AD progression. eQTL analysis supports that these SNPs regulate expression of key genes involved in the neurotrophin signaling pathway.

GhostKnockoff inference empowers identification of putative causal variants in genome-wide association studies

Recent advances in genome sequencing and imputation technologies provide an exciting opportunity to comprehensively study the contribution of genetic variants to complex phenotypes. However, our ability to translate genetic discoveries into mechanistic insights remains limited at this point. In this paper, we propose an efficient knockoff-based method, GhostKnockoff, for genome-wide association studies (GWAS) that leads to improved power and ability to prioritize putative causal variants relative to conventional GWAS approaches. The method requires only Z-scores from conventional GWAS and hence can be easily applied to enhance existing and future studies. The method can also be applied to meta-analysis of multiple GWAS allowing for arbitrary sample overlap. We demonstrate its performance using empirical simulations and two applications: (1) a meta-analysis for Alzheimer's disease comprising nine overlapping large-scale GWAS, whole-exome and whole-genome sequencing studies and (2) analysis of 1403 binary phenotypes from the UK Biobank data in 408,961 samples of European ancestry. Our results demonstrate that GhostKnockoff can identify putatively functional variants with weaker statistical effects that are missed by conventional association tests.

Deep neural networks with controlled variable selection for the identification of putative causal genetic variants

Deep neural networks (DNNs) have been successfully utilized in many scientific problems for their high prediction accuracy, but their application to genetic studies remains challenging due to their poor interpretability. Here we consider the problem of scalable, robust variable selection in DNNs for the identification of putative causal genetic variants in genome sequencing studies. We identified a pronounced randomness in feature selection in DNNs due to its stochastic nature, which may hinder interpretability and give rise to misleading results. We propose an interpretable neural network model, stabilized using ensembling, with controlled variable selection for genetic studies. The merit of the proposed method includes: flexible modelling of the nonlinear effect of genetic variants to improve statistical power; multiple knockoffs in the input layer to rigorously control the false discovery rate; hierarchical layers to substantially reduce the number of weight parameters and activations, and improve computational efficiency; and stabilized feature selection to reduce the randomness in identified signals. We evaluate the proposed method in extensive simulation studies and apply it to the analysis of Alzheimer's disease genetics. We show that the proposed method, when compared with conventional linear and nonlinear methods, can lead to substantially more discoveries.

A Fast and Robust Strategy to Remove Variant-Level Artifacts in Alzheimer Disease Sequencing Project Data

Background and Objectives

Exome sequencing (ES) and genome sequencing (GS) are expected to be critical to further elucidate the missing genetic heritability of Alzheimer disease (AD) risk by identifying rare coding and/or noncoding variants that contribute to AD pathogenesis. In the United States, the Alzheimer Disease Sequencing Project (ADSP) has taken a leading role in sequencing AD-related samples at scale, with the resultant data being made publicly available to researchers to generate new insights into the genetic etiology of AD. To achieve sufficient power, the ADSP has adapted a study design where subsets of larger AD cohorts are collected and sequenced across multiple centers, using a variety of sequencing platforms. This approach may lead to variable variant quality across sequencing centers and/or platforms. In this study, we sought to implement and evaluate filters that can be applied fast to robustly remove variant-level artifacts in the ADSP data.

Methods

We implemented a robust quality control procedure to handle ADSP data. We evaluated this procedure while performing exome-wide and genome-wide association analyses on AD risk using the latest ADSP whole ES (WES) and whole GS (WGS) data releases (NG00067.v5).

Results

We observed that many variants displayed large variation in allele frequencies across sequencing centers/platforms and contributed to spurious association signals with AD risk. We also observed that sequencing platform/center adjustment in association models could not fully account for these spurious signals. To address this issue, we designed and implemented variant filters that could capture and remove these center-specific/platform-specific artifactual variants.

Discussion

We derived a fast and robust approach to filter variants that represent sequencing center-related or platform-related artifacts underlying spurious associations with AD risk in ADSP WES and WGS data. This approach will be important to support future robust genetic association studies on ADSP data, as well as other studies with similar designs.

Direct Oral Anticoagulants (DOACs) for Therapeutic Targeting of Thrombin, a Key Mediator of Cerebrovascular and Neuronal Dysfunction in Alzheimer's Disease

Although preclinical research and observer studies on patients with atrial fibrillation concluded that direct oral anticoagulants (DOACs) can protect against dementia like Alzheimer's disease (AD), clinical investigation towards therapeutical approval is still pending. DOACs target pathological thrombin, which is, like toxic tau and amyloid-ß proteins (Aß), an early hallmark of AD. Especially in hippocampal and neocortical areas, the release of parenchymal Aß into the blood induces thrombin and proinflammatory bradykinin synthesis by activating factor XII of the contact system. Thrombin promotes platelet aggregation and catalyzes conversion of fibrinogen to fibrin, leading to degradation-resistant, Aß-containing fibrin clots. Together with oligomeric Aß, these clots trigger vessel constriction and cerebral amyloid angiopathy (CAA) with vessel occlusion and hemorrhages, leading to vascular and blood-brain barrier (BBB) dysfunction. As consequences, brain blood flow, perfusion, and supply with oxygen (hypoxia) and nutrients decrease. In parenchymal tissue, hypoxia stimulates Aß synthesis, leading to Aß accumulation, which is further enhanced by BBB-impaired perivascular Aß clearance. Aß trigger neuronal damage and promote tau pathologies. BBB dysfunction enables thrombin and fibrin(ogen) to migrate into parenchymal tissue and to activate glial cells. Inflammation and continued Aß production are the results. Synapses and neurons die, and cognitive abilities are lost. DOACs block thrombin by inhibiting its activity (dabigatran) or production (FXa-inhibitors, e.g., apixaban, rivaroxaban). Therefore, DOAC use could preserve vascular integrity and brain perfusion and, thereby, could counteract vascular-driven neuronal and cognitive decline in AD. A conception for clinical investigation is presented, focused on DOAC treatment of patients with diagnosed AD in early-stage and low risk of major bleeding.

Gold Nanostrip Array-Mediated Wireless Electrical Stimulation for Accelerating Functional Neuronal Differentiation

Neural stem cell (NSC)-based therapy holds great promise for the treatment of neurodegenerative diseases. Presently, however, it is hindered by poor functional neuronal differentiation. Electrical stimulation is considered one of the most effective ways to promote neuronal differentiation of NSCs. In addition to surgically implanted electrodes, traditional electrical stimulation includes wires connected to the external power supply, and an additional surgery is required to remove the electrodes or wires following stimulation, which may cause secondary injuries and infections. Herein, a novel method is reported for generation of wireless electrical signals on an Au nanostrip array by leveraging the effect of electromagnetic induction under a rotating magnetic field. The intensity of the generated electrical signals depends on the rotation speed and magnetic field strength. The Au nanostrip array-mediated electric stimulation promotes NSC differentiation into mature neurons within 5 days, at the mRNA, protein, and function levels. The rate of differentiation is faster by at least 5 days than that in cells without treatment. The Au nanostrip array-based wireless device also accelerates neuronal differentiation of NSCs in vivo. The novel method to accelerate the neuronal differentiation of NSCs has the advantages of wireless, timely, localized and precise controllability, and noninvasive power supplementation.

A Prospective Viewpoint on Neurological Diseases and Their Biomarkers

Neurodegenerative diseases (NDDs) are disorders that affect both the central and peripheral nervous systems. To name a few causes, NDDs can be caused by ischemia, oxidative and endoplasmic reticulum (ER) cell stress, inflammation, abnormal protein deposition in neural tissue, autoimmune-mediated neuron loss, and viral or prion infections. These conditions include Alzheimer's disease (AD), Lewy body dementia (LBD), and Parkinson's disease (PD). The formation of β-sheet-rich aggregates of intra- or extracellular proteins in the CNS hallmarks all neurodegenerative proteinopathies. In systemic lupus erythematosus (SLE), numerous organs, including the central nervous system (CNS), are affected. However, the inflammatory process is linked to several neurodegenerative pathways that are linked to depression because of NDDs. Pro-inflammatory signals activated by aging may increase vulnerability to neuropsychiatric disorders. Viruses may increase macrophages and CCR5+ T cells within the CNS during dementia formation and progression. Unlike medical symptoms, which are just signs of a patient's health as expressed and perceived, biomarkers are reproducible and quantitative. Therefore, this current review will highlight and summarize the neurological disorders and their biomarkers.

Geranylgeranylacetone Ameliorates Beta-Amyloid Toxicity and Extends Lifespan via the Heat Shock Response in Caenorhabditis elegans

Activation of a cytoprotective cellular pathway known as the heat shock response (HSR) is a promising strategy for the treatment of Alzheimer’s disease and other neurodegenerative diseases. Geranylgeranylacetone (GGA) is a commonly used anti-ulcer drug in Japan that has been shown to activate the HSR. Here, we establish C. elegans as a model system to investigate the effects of GGA. First, we show that GGA-mediated activation of the HSR is conserved in worms. Then, we show that GGA can ameliorate beta-amyloid toxicity in both muscle and neuronal worm Alzheimer’s disease models. Finally, we find that exposure to GGA is sufficient to extend the lifespan of wild-type worms. Significantly, the beneficial effects of GGA on both beta-amyloid toxicity and lifespan are dependent on HSR activation. Taken together, this research supports further development of GGA as a therapeutic for Alzheimer’s disease, provides evidence that HSR activation is a relevant therapeutic mechanism, and indicates that the beneficial effects of GGA are not limited to disease.

Solving neurodegeneration: common mechanisms and strategies for new treatments

Across neurodegenerative diseases, common mechanisms may reveal novel therapeutic targets based on neuronal protection, repair, or regeneration, independent of etiology or site of disease pathology. To address these mechanisms and discuss emerging treatments, in April, 2021, Glaucoma Research Foundation, BrightFocus Foundation, and the Melza M. and Frank Theodore Barr Foundation collaborated to bring together key opinion leaders and experts in the field of neurodegenerative disease for a virtual meeting titled "Solving Neurodegeneration". This "think-tank" style meeting focused on uncovering common mechanistic roots of neurodegenerative disease and promising targets for new treatments, catalyzed by the goal of finding new treatments for glaucoma, the world's leading cause of irreversible blindness and the common interest of the three hosting foundations. Glaucoma, which causes vision loss through degeneration of the optic nerve, likely shares early cellular and molecular events with other neurodegenerative diseases of the central nervous system. Here we discuss major areas of mechanistic overlap between neurodegenerative diseases of the central nervous system: neuroinflammation, bioenergetics and metabolism, genetic contributions, and neurovascular interactions. We summarize important discussion points with emphasis on the research areas that are most innovative and promising in the treatment of neurodegeneration yet require further development. The research that is highlighted provides unique opportunities for collaboration that will lead to efforts in preventing neurodegeneration and ultimately vision loss.

Periodontal microorganisms and Alzheimer disease - A causative relationship?

In the initiation or exacerbation of Alzheimer disease, the dissemination of oral microorganisms into the brain tissue or the low‐level systemic inflammation have been speculated to play a role. However, the impact of oral microorganisms, such as Porphyromonas gingivalis, on the pathogenesis of Alzheimer disease and the potential causative relationship is still unclear. The present review has critically reviewed the literature by examining the following aspects: (a) the oral microbiome and the immune response in the elderly population, (b) human studies on the association between periodontal and gut microorganisms and Alzheimer disease, (c) animal and in vitro studies on microorganisms and Alzheimer disease, and (d) preventive and therapeutic approaches. Factors contributing to microbial dysbiosis seem to be aging, local inflammation, systemic diseases, wearing of dentures, living in nursing homes and no access to adequate oral hygiene measures. Porphyromonas gingivalis was detectable in post‐mortem brain samples. Microbiome analyses of saliva samples or oral biofilms showed a decreased microbial diversity and a different composition in Alzheimer disease compared to cognitively healthy subjects. Many in‐vitro and animal studies underline the potential of P gingivalis to induce Alzheimer disease‐related alterations. In animal models, recurring applications of P gingivalis or its components increased pro‐inflammatory mediators and β‐amyloid in the brain and deteriorated the animals' cognitive performance. Since periodontitis is the result of a disturbed microbial homoeostasis, an effect of periodontal therapy on the oral microbiome and host response related to cognitive parameters may be suggested and should be elucidated in further clinical trials.

Promoter Hypomethylation of TGFBR3 as a Risk Factor of Alzheimer’s Disease: An Integrated Epigenomic-Transcriptomic Analysis

Alzheimer’s disease (AD) is characterized by the abnormal deposition of amyloid-β (Aβ) plaques and tau tangles in the brain and accompanied with cognitive impairment. However, the fundamental cause of this disease remains elusive. To elucidate the molecular processes related to AD, we carried out an integrated analysis utilizing gene expression microarrays (GSE36980 and GSE5281) and DNA methylation microarray (GSE66351) in temporal cortex of AD patients from the Gene Expression Omnibus (GEO) database. We totally discovered 409 aberrantly methylated and differentially expressed genes. These dysregulated genes were significantly enriched in biological processes including cell part morphogenesis, chemical synaptic transmission and regulation of Aβ formation. Through convergent functional genomic (CFG) analysis, expression cross-validation and clinicopathological correlation analysis, higher TGFBR3 level was observed in AD and positively correlated with Aβ accumulation. Meanwhile, the promoter methylation level of TGFBR3 was reduced in AD and negatively associated with Aβ level and advanced Braak stage. Mechanically, TGFBR3 might promote Aβ production by enhancing β- and γ-secretase activities. Further investigation revealed that TGFBR3 may exert its functions via Synaptic vesicle cycle, Calcium signaling pathway and MAPK signal pathway by regulating hub genes GNB1, GNG3, CDC5L, DYNC1H1 and FBXW7. Overall, our findings highlighted TGFBR3 as an AD risk gene and might be used as a diagnostic biomarker and therapeutic target for AD treatment.

Impairment of the autophagy-lysosomal pathway in Alzheimer's diseases: Pathogenic mechanisms and therapeutic potential

Alzheimer's disease (AD), the most common neurodegenerative disorder, is characterized by memory loss and cognitive dysfunction. The accumulation of misfolded protein aggregates including amyloid beta (Aβ) peptides and microtubule associated protein tau (MAPT/tau) in neuronal cells are hallmarks of AD. So far, the exact underlying mechanisms for the aetiologies of AD have not been fully understood and the effective treatment for AD is limited. Autophagy is an evolutionarily conserved cellular catabolic process by which damaged cellular organelles and protein aggregates are degraded via lysosomes. Recently, there is accumulating evidence linking the impairment of the autophagy–lysosomal pathway with AD pathogenesis. Interestingly, the enhancement of autophagy to remove protein aggregates has been proposed as a promising therapeutic strategy for AD. Here, we first summarize the recent genetic, pathological and experimental studies regarding the impairment of the autophagy–lysosomal pathway in AD. We then describe the interplay between the autophagy–lysosomal pathway and two pathological proteins, Aβ and MAPT/tau, in AD. Finally, we discuss potential therapeutic strategies and small molecules that target the autophagy–lysosomal pathway for AD treatment both in animal models and in clinical trials. Overall, this article highlights the pivotal functions of the autophagy–lysosomal pathway in AD pathogenesis and potential druggable targets in the autophagy–lysosomal pathway for AD treatment.

Identification of Genetic Networks Reveals Complex Associations and Risk Trajectory Linking Mild Cognitive Impairment to Alzheimer’s Disease

Amnestic mild cognitive impairment (aMCI) and sporadic Alzheimer’s disease (AD) are multifactorial conditions resulting from a complex crosstalk among multiple molecular and biological processes. The present study investigates the association of variants localized in genes and miRNAs with aMCI and AD, which may represent susceptibility, prognostic biomarkers or multi-target treatment options for such conditions. We included 371 patients (217 aMCI and 154 AD) and 503 healthy controls, which were genotyped for a panel of 120 single nucleotide polymorphisms (SNPs) and, subsequently, analyzed by statistical, bioinformatics and machine-learning approaches. As a result, 21 SNPs were associated with aMCI and 13 SNPs with sporadic AD. Interestingly, a set of variants shared between aMCI and AD displayed slightly higher Odd Ratios in AD with respect to aMCI, highlighting a specific risk trajectory linking aMCI to AD. Some of the associated genes and miRNAs were shown to interact within the signaling pathways of APP (Amyloid Precursor Protein), ACE2 (Angiotensin Converting Enzyme 2), miR-155 and PPARG (Peroxisome Proliferator Activated Receptor Gamma), which are known to contribute to neuroinflammation and neurodegeneration. Overall, results of this study increase insights concerning the genetic factors contributing to the neuroinflammatory and neurodegenerative mechanisms underlying aMCI and sporadic AD. They have to be exploited to develop personalized approaches based on the individual genetic make-up and multi-target treatments.

A novel DPP-4 inhibitor Gramcyclin A attenuates cognitive deficits in APP/PS1/tau triple transgenic mice via enhancing brain GLP-1-dependent glucose uptake

Enhancing glucagon-like peptide 1 (GLP-1) signaling with a dipeptidyl peptidase IV (DPP-4) inhibitor might exert protective effects on Alzheimer's disease (AD). We found that intragastric administration of Gramcyclin A (10, 20 and 40 mg/kg), a novel DPP-4 inhibitor, for 3 months significantly reversed cognitive decline in APP/PS1/tau triple transgenic mice in a dose-dependent manner. Gramcyclin A treatment markedly reduced Aβ plaques as well as the insoluble and soluble forms of Aβ40 and Aβ42 in the hippocampus of APP/PS1/tau mice. Treatment with Gramcyclin A remarkedly decreased the level of microglia and suppressed neuroinflammation in the hippocampus of APP/PS1/tau mice. Moreover, Gramcyclin A treatment could increase brain glucose uptake in APP/PS1/tau mice, as detected by 18-fluoro-2-deoxyglucose (¹⁸ F-FDG) micro-positron emission tomography (micro-PET) imaging. Furthermore, Gramcyclin A significantly increased expression of glucagon-like peptide-1 (GLP-1), GLP-1R, proliferator-activated receptor gamma coactivator (PGC)-1α and glucose transporter 4 (GLUT4), and inhibited insulin receptor (IRS)-1 phosphorylation and tau hyperphosphorylation in the hippocampus of APP/PS1/tau mice. Collectively, Gramcyclin A conferred protective effects against AD via enhancing brain GLP-1-dependent glucose uptake. The DPP-4 inhibitor Gramcyclin A might be a potential therapeutic drug for AD.

MDGA1 negatively regulates amyloid precursor protein-mediated synapse inhibition in the hippocampus

Balanced synaptic inhibition, controlled by multiple synaptic adhesion proteins, is critical for proper brain function. MDGA1 (meprin, A-5 protein, and receptor protein-tyrosine phosphatase mu [MAM] domain-containing glycosylphosphatidylinositol anchor protein 1) suppresses synaptic inhibition in mammalian neurons, yet the molecular mechanisms underlying MDGA1-mediated negative regulation of GABAergic synapses remain unresolved. Here, we show that the MDGA1 MAM domain directly interacts with the extension domain of amyloid precursor protein (APP). Strikingly, MDGA1-mediated synaptic disinhibition requires the MDGA1 MAM domain and is prominent at distal dendrites of hippocampal CA1 pyramidal neurons. Down-regulation of APP in presynaptic GABAergic interneurons specifically suppressed GABAergic, but not glutamatergic, synaptic transmission strength and inputs onto both the somatic and dendritic compartments of hippocampal CA1 pyramidal neurons. Moreover, APP deletion manifested differential effects in somatostatin- and parvalbumin-positive interneurons in the hippocampal CA1, resulting in distinct alterations in inhibitory synapse numbers, transmission, and excitability. The infusion of MDGA1 MAM protein mimicked postsynaptic MDGA1 gain-of-function phenotypes that involve the presence of presynaptic APP. The overexpression of MDGA1 wild type or MAM, but not MAM-deleted MDGA1, in the hippocampal CA1 impaired novel object-recognition memory in mice. Thus, our results establish unique roles of APP-MDGA1 complexes in hippocampal neural circuits, providing unprecedented insight into trans-synaptic mechanisms underlying differential tuning of neuronal compartment-specific synaptic inhibition.

Integrative genomic analysis of PPP3R1 in Alzheimer's disease: a potential biomarker for predictive, preventive, and personalized medical approach

Alzheimer's disease (AD) is associated with abnormal calcium signaling, a pathway regulated by the calcium-dependent protein phosphatase. This study aimed to investigate the molecular function of protein phosphatase 3 regulatory subunit B (PPP3R1) underlying AD, which may provide novel insights for the predictive diagnostics, targeted prevention, and personalization of medical services in AD by targeting PPP3R1. A total of 1860 differentially expressed genes (DEGs) from 13,049 background genes were overlapped in AD/control and PPP3R1-low/high cohorts. Based on these DEGs, six co-expression modules were constructed by weight gene correlation network analysis (WGCNA). The turquoise module had the strongest correlation with AD and low PPP3R1, in which DEGs participated in axon guidance, glutamatergic synapse, long-term potentiation (LTP), mitogen-activated protein kinase (MAPK), Ras, and hypoxia-inducible factor 1 (HIF-1) signaling pathways. Furthermore, the cross-talking pathways of PPP3R1, such as axon guidance, glutamatergic synapse, LTP, and MAPK signaling pathways, were identified in the global regulatory network. The area under the curve (AUC) analysis showed that low PPP3R1 could accurately predict the onset of AD. Therefore, our findings highlight the involvement of PPP3R1 in the pathogenesis of AD via axon guidance, glutamatergic synapse, LTP, and MAPK signaling pathways, and identify downregulation of PPP3R1 as a potential biomarker for AD treatment in the context of 3P medicine-predictive diagnostics, targeted prevention, and personalization of medical services.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-021-00261-2.

lncRNA MIR600HG Knockdown Alleviates Cognitive Impairment in Alzheimer's Disease Through NEDD4L Mediated PINK1 Degradation

BACKGROUND

Growing evidence has demonstrated that long non-coding RNAs (lncRNAs) play a critical role in Alzheimer's disease (AD), which is characterized by sustained mitochondrial dysfunction, inevitable memory loss, and cognitive decline. However, the potential function of lncRNAs MIR600 Host Gene (MIR600HG) in AD remains unanswered.

OBJECTIVE

Our study aimed to investigate the role of MIR600HG and its related molecular mechanism in AD.

METHODS

The expression of MIR600HG was examined by qRT-PCR. The MIR600HG interacting proteins were identified by RNA pull-down assay and mass spectrometry and verified by RNA immunoprecipitation. Immunofluorescence staining was applied to examine the colocalization of PINK1 and NEDD4L. The PINK1 level and the activation of autophagy were detected by immunoblotting. Morris water maze test was performed to evaluate cognitive decline in AD mice model.

RESULTS

MIR600HG expression was elevated during aging in two different types of AD transgenic mouse models. Next, we found that increased MIR600HG directly interact with NEDD4L, which promoted PINK1 ubiquitination and degradation, and as well as autophagy activation. Additionally, MIR600HG promoted Aβ production and suppressed Cytochrome C Oxidase activity. Administration of AAV-shMIR600HG restored the Cytochrome C Oxidase activity and inhibited Aβ production. Furthermore, PINK1 overexpression or MIR600HG knockdown significantly ameliorated the cognitive impairment in APP/PS1 mice. PINK1 depletion recovered the spatial memory defect in the AAV-shMIR600HG injected APP/PS1 mice.

CONCLUSION

MIR600HG was increased in AD and promoted AD pathogenesis. Targeting MIR600HG significantly improved cognitive function in AD mice, which could pave the way for exciting new avenues in AD therapeutic strategy research.